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PARIKALPANAKIIT Journal of Management

June - 2018, Volume-14(I)

Parikalpana: KIIT Journal of ManagementJune-2018 Volume-14(I)

CONTENTS

l Editorial- Growth, Development and Equity: India’s tryst 1-10with Economic ReformsS. N. Mishra

l Path analytic study on relationship between shopping 11-39orientation, store attributes and patronage behaviourof retail shoppers in selected cities of Gujurat stateParimal H. Vyas & Parag Shukla

l Feasibility of costing model variants: An investigation 40-53of small scale industrySwati Gupta & Rajesh Tripathi

l Nudge applications in consumer socialization of Children 54-68Vivek Mishra & Biswajit Das

l Factors determining buyer behaviour in shopping goods 69-79with reference to branded productsMamatanjali Parida

l Role of information- Source and applications’ disconfirmation 80-90sensitivity in job application decisionsUrvashi Thakur

l Cashless financial transaction behaviour of urban 91-104middle class in BhubaneswarSriya Mahapatra

l Motivational factors and it’s impact on students’ 105-119performance in higher education: A ReviewD. Nisrutha

l Analysis of Interaction between global crude oil price, 120-133exchange rate, inflation and stock market in India:Vevtor auto regression approachShekhar Mishra & Sathya Swaroop Debasish

l Impact of macroeconomic factors on Indian stock market 134-145Keshav Garg & Rosy Kalra

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l Macro Economic factors and share price behaviour: 146-160A study on selected industries in IndiaPramath Nath Acharya & Rudra Prasanna Mahapatra

l Influence of Capital structure on financial performance 161-171Chandrika Prasad Das & Rabindra Kumar Swain

Case Study

l Swachha Bharat Gramin: A budget analysis of India’s 172-186sanitation program. examining odisha stateMadhumita Ray

GROWTH, DEVELOPMENT AND EQUITY:INDIA’S TRYST WITH ECONOMIC REFORMS

S. N. MishraDean, School of Management,

Kalinga Institute of Industrial Technology, Deemed to be University, [email protected] & [email protected]

DOI: 10.23862/kiit-parikalpana/2018/v14/i1/173258

ABSTRACTIndia took a definitive step towards market reforms in 1991 by dismantling theLicense-Permit Quota (LPQ) Raj. This brought in significant spurt in GrossDomestic Product (GDP) growth rates, exports, Foreign Exchange (FE) reservesand reduced percentage people Below Poverty Line (BPL) considerably. However,the human development story, in terms of Infant Mortality Rate (IMR), MaternalMortality Rate (MMR), malnutrition of children, mean year of schooling havebeen quite dismal. The picture on containing income inequality is also quitedisappointing in the urban segment as it shows an upward trajectory. The papermakes a strong case for opting for balanced growth where right priority isaccorded to merit goods like quality primary education and health as publicremit. A balanced growth strategy between economic infrastructure and socialoverheads would be the right cocktail for India’s policy makers. Therecommendations include introducing General Anti-Avoidance Rule (GAAR) atthe earliest to pre-empt illegal parking of funds in tax havens, privatisation ofPublic Sector Banks (PSB) to promote better financial intermediation. It alsosupports strongly the case for introducing a Universal Basic Income (UBI) scheme,in lieu of plethora of subsidies to guarantee a minimum standard of living forevery Indian citizen. It draws comparison with China, whose growth anddevelopment story have walked hand, in hand after liberalization in the 1980s.

INTRODUCTION

Our Constitution makers tried to strike afine balance between individual liberty withSocio, Economic and Political Justice forall its citizens, 67 years back. Article 325provides universal adult franchise; therebyensuring political justice to all its citizens.Social justice has, however, eluded Indiaas it is inextricably linked with a moribund

the caste system, where your socialposition is determined by accident of birth.It is only through economic justice thatthere can be vertical mobility in the socialladder. Prof. M.N. Srinivas in his seminalconcept “Sanskritization” brought out howimprovement in economic status can be apotent factor in facilitating social vertical

Special Editorial

Parikalpana - KIIT Journal of Management2

mobility in India. However, the real gamechanger for social justice can be throughpromotion of economic justice throughstate intervention. Accordingly theDirective Principle of State Policy whilereiterating the commitment of socioeconomic justice provides for provisionslike early childhood care, raising level ofnutrition, promoting economic interests ofSC/ST, maternity relief, special provisionsfor women etc. The Right to Education(2009) has been the most talismanicmoment to promote economic justice, asaccess to education could be the “swiftestelevator to modern Indian power”. Article38(2) specifically calls upon the state tominimize acute inequality of income. In thisbackdrop we examine the variousideological alternatives that the fledglingdemocracy after independence had, topromote economic justice, the path theychose. It takes a panoramic view of theimpact of major economic reforms whichwere introduced in 1990 and in particular,disconnect between India’s journeythrough the trajectory growth & humandevelopment and our abject failure to bringdown inequality. It also comparesexperience of China, which adapted theeconomic liberalisation path, a decadeearlier than India’s, with India in variousgrowth and development parameters.

India after Independence

After independence India had the choiceof adopting the British model of capitalismcanvassed by Adam Smith, communism

as practiced in Russia through stateplanning or the liberal ideas of Keyneswhich promoted a welfare state. It wasAdam Smith who said that “Private pursuitof self interest would lead, as if by aninvisible hand, to the well being of all”. ForSmith the critical impetus for wealthcreation would be free market and divisionof labour. For Karl Mark the primordialconcern was equity, as exploitation oflabour was the rampant in post industrialrevolution western society. A socialist statewould be a catalyst for bringing downincome inequality and “Das Kapital”documented the innards of exploitation,prognosticating how “capitalism containsthe seeds of its own destruction”. In sharpcontrast John Maynard Keynes, writing inthe backdrop of the great depression ofthe 1930’s, was a strong votary for thestate to generate employment throughmassive public investment. The New DealPolicy of Franklin D. Rooseveltencapsulated these ideas.

Pandit Jawaharlal Nehru had a distinctpredilection for the Soviet economicmodel of state planning and heavy industrywas considered as the temples of modernIndia. Prof. P.C. Mahalanobis providedthe architecture for industrialisation throughmassive public sector intervention andforeign borrowing. Sadly the public sectorundertaking, nationalisation of banks andcoal mines that followed, ensured that Indiathe “animal spirits” of the private sectorwas hardly roused. And India remained

3Growth, Development and Equity: India’s tryst with economic reforms

struck at what is popularly called the“Hindu rate of growth” of 3.5%. 1990became a watershed moment, when acombination of high inflation, low foreignexchange reserves, and unacceptably highlevel of fiscal deficit forced India to seekthe help of International Monetary Fundwhich imposed conditionalities such asdevaluation the rupee by 22%, reducingimport tariff from 130% to 30%, containingsubsidy. In his famous budget speech Dr.Manmohan Singh in 1991 quoted VictorHugo “No one can stop an idea whosetime has come”, to underlining thateconomic liberalisation in India was not amatter of choice but a preferred path forIndia’s future economic journey. Twentyseven years thereafter it’s time to takestock of the multi-dimension impact ofthese market reforms on growth,development and inequality in India.

First Generation Reforms (1991-2000)

The baby steps at reforms aimed atpromoting industrial activities, boostingexports and encouraging foreign directinvestment into our country. De-licensingof industry and abolition of Monopolies& Restrictive Trade Practices (MRTP)limit were the main stimulants for the privatesector industries. In case of public sector,disinvestment became the big ticket reform,where the Public Sector Undertakings(PSUs) were becoming a drag on theeconomy. On the external sector,significant custom duty reduction, and

having a managed float system became ourpredominant policy mosaic. ForeignExchange Regulation Act (FERA) wasreplaced with Foreign ExchangeManagement Act (FEMA), with foreigncurrency limit violation being subject tofines rather than being criminally culpable.The foreign Direct Investment (FDI) normswere significantly liberalised to encouragetechnology transfer and long term foreigncollaboration with OEMs.

Second Generation Reforms (2001-2014)

The earlier reforms where steps to alignIndia with the conditionalities ofInternational Monetary Fund (IMF). Thenext generation reforms were aimed attaking advantage of globalisation whichwas sweeping across the developingcountries and had been one of the majorreasons for the growth of emerging marketeconomies of East Asia tigers. Thereforms during this period were essentiallyto dismantle the administered pricemechanism for scarce commodities likecement, sugar, fertilizer, drugs andpetroleum. The public sector undertakingwere categorised as Maharatnas andMiniratnas to facilitate international tie-ups,joint ventures and green field investment.On the legal side the reforms in theCompany Act 1956 was essentially tobring in Corporate Social Responsibilityto the centre stage. The InformationTechnology Act 2000 was another


significant addition to ensure that the digitalinterface conforms to the agreed protocolsand deviances suitably penalised. Post USeconomic financial crisis a committeechaired by Justice Srikrishna gave farreaching recommendations for bringing upan independent public debt managementauthority in lieu of Reserve Bank of India(RBI), merging Securities & ExchangeBoard of India (SEBI) with FMC, andprovide the consumers with greaterprotection for the financial products.

One of its significant recommendations wasto supplant repo rate determination by theRBI Governor with a broad basedmonetary policy committee which has sincebeen put in place. While public debtmanagement continues to be done by RBI,the Financial Sector Legislative ReformsCommission (FSLRC) is a welcomeinitiative to sensitize policy makers with thecross currents of fiscal instability.

Reforms Post 2014

The most significant reform post 2014 hasbeen to replace a Centralised PlanningCommission devolving nearly 30% ofgovernment expenditure to both centrallysponsored and state sponsored schemesby a mechanism called Niti Aayog. This isa bottom top development approach andlooks at planning from the grass-rootvillage level which can be aggregatedprogressively at higher level. It’s anadvisory body instead of allocating plan

fund and will provide directional andstrategic inputs to the centre and the states.The other significant reform has been theGoods and Services Tax which is a majorindirect tax return to promote the conceptof One India, One Market. This shouldeventually do away with the price distortionthan exists between different states formany commodities; and thereby boost oureconomic activity and GDP by 1 – 1.5%.

Overall Impact of Reforms

As would be seen from the figure below,the growth rate has increased from a verylow 1% (1990) to about 7% now, and theshare of service sector has significantlyincreased and that of agricultural sectorslumping. The reforms have also reducedthe percent below poverty line significantly;and we have a comfortable FE reservesto take care of 7 months’ importrequirements as against 7 days in 1990.

India’s Growth Story

India’s growth story during the last 56years, decade wise, clearly show how theHindu rate of growth, has been supplantedby 7 – 7.5% growth. Savings aspercentage to GDP has doubled andexport has nearly increased by five times.The change in thrust from “importsubstitution” to export promotion, enablingtrade policy, creation of Special EconomicZones (SEZs) has contributed mostsignificantly to our export growth.

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Table 1: GDP, Saving and Export: TrendsYear GDP Growth Savings % Export as % GDP

1960-80 3.5 17 4.6

1980-90 5.6 19.4 6.1

1990-2001 6.0 24 13

2001-2010 7.8 33 20

2010-2015 7 31 25

Source: Economic Survey 2016-2017

India’s Development Story

The real lament is the trend progress inmean years of schooling, high infant and

maternal mortality rates and very high totalfertility for women (2.4); as against globalaverage of (1.5) for developed countries.

Table 2: Trends of Development in India

Sl. No. Parameter 1988-89 2014-15

1. Literacy Rate 51 67

2. Life Expectancy 51 66

3. Mean Years of Schooling 3.5 4.4

4. IMR (1000) 53 44

5. MMR (1 lakh) 260 200

6. Total Fertility Rate 2.5 2.4

Source: Economic Survey 2016-2017

India & China: A Comparison

In this backdrop, it will be of interest tocompare the growth and developmentstory of India. More so since China theychose the liberalisation both in 1980 andIndia in 1990.

It’s quite clear that China’s robust growth

is due to significantly high growth rate inagricultural sector and its boomingmanufacturing hubs. They have performedsignificantly better in every developmentparameter, be it schooling, childmalnutrition, infant and maternal mortalitycompared to India.

Growth, Development and Equity: India’s tryst with economic reforms


Table 3: Comparative Growth & Development Trends: India & China

Sl. No. Parameter China India

1. Real GDP in 1950 in $ 448 619

2. GNI at PPP in 2015 $ 12547 5497

3. Agricultural Growth 6.7 2.5

4. Manufacturing: Share in GDP 30 16

5. HDI 0.727 0.608

6. Mean Years of Schooling 7.5 5.4

7. IMR (1000) 12.7 52.7

8. Child Malnutrition 9.4 47.9

9. MMR (1 lakh) 32 190

10. % Below Poverty Line ($1.25 per day) 6.3 23.6

Source: An Uncertain Glory: India & its Contradictions: Jean Dreze & Amartya Sen

Income Inequality

Sadly reducing income inequality has notbeen a strong agenda in most of thedeveloped countries irrespective of their

ideology as the following graph wouldshow. Interestingly China has higher ginicoefficient than India.

Figure 1: Gini Coefficient of Select Countries

Source: Human Development Report 2015

Trend of Inequality after Liberalization in India

The following table shows trend of income inequality in rural and urban sector in India,post economic liberalisation.

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Table 4: Trends of Income Inequality in Rural & Urban Sector

Year Rural Urban Total

1993-94 25.8 31.9 30.1

2004-05 28.1 36.4 34.6

2009-10 28.8 38.4 36.2

Source: National Sample Survey Office Ministry of Statistics & Programme Office

What is more worrying is the rising trendof inequality, particularly in the urbansegment of India. The rural sector has beenstagnant; and therefore does not exhibitsuch a trend. Increasing urbanisation andopportunity in the service sector hascontributed to the spurt in incomeinequality in the urban areas in India.

Millennium Development Goals

189 nations made a pledge in 2000 to freepeople from extreme poverty and multipledeprivations. This pledge is encapsulatedin eight MDG goals to be achieved by2015.

Table 5: Millennium Development Goals

Goals India’s Achievement

Goal 1: Eradicate Extreme Hunger and Poverty 23.6% (BPL)

Goal 2: Achieve Universal Primary Education Achieved

Goal 3: Promote Gender Equality and Empower Women Achieved

Goal 4: Reduce Child Mortality by 2/3rd 1/3rd

Goal 5: Improve Maternal Health by 3/4th 1/3rd

Source: UN Millennium Project Goals & Human Development Report 2015

It would seen from the above that whileRight to Education and Sarva ShikshaAbhiyan (SSA) as a flagship programmehas ensured universal access to education,

cutting across gender, our progress interms of child mortality and improvementof maternal health is far short of MDGtargets. Prof. Jean Dreze has brought out



how poor allocation of Rs.2700 crore in2017-18 budget for maternity benefit isfar short of the promise to give Rs.6000/-to every pregnant women in the informalsector.

The Rural Distress

Close to 60% live in India’s villages andmore than 50% depend on agriculture fortheir livelihood. The percentagecontribution of agriculture to GDP hasdeclined from 45% (1947) to 16% now;clearly reflecting disguised employment,low productivity and farmer distress. Thefollowing table will highlight the concerns.Reforms Awaited

The major reforms awaited are in financialintermediation like banking, where thePSBs are saddled with 9% of gross non-performing assets (NPA). There is a strongcase for privatising the nationalised banks,as it would ensure whittling down of prioritysector lending and make banking moreprofitable and resilient. General Anti-Avoidance Rule (GARR) is long awaited,as this could cut down on malpractices like“round tripping” and parking of illegalmoney in tax havens. A Direct Tax Code,keeping the IT Act 1961 would makeIndia’s direct tax provisions in sync withbest global practices.But the real paradigm shift could be if wecan bring in Universal of Basic IncomeScheme to usher a just society, whereevery individual is guaranteed a minimumincome. This idea has been mooted in ourrecent Economic Survey, which has

assessed that the cost of UBI would be alittle over 1% of all existing subsidies whichis around 5% of the GDP. This will cutdown all leakages and pre-empt nontargeted beneficiaries. It will ensure thatevery Indian has the right to live withdignity, which is part of “Right to Life” asper the UN Human Rights Declaration inwhich India is a signatory.For manufacturing to really kick-start, thelabour laws would need to be streamlinedto provide flexibility in production whileprotecting interests of the labourers. Whilethe Rajasthan government has taken apioneering step in this regard, the otherstates are yet to replicate such bestpractices. The National ManufacturingZone (NMZ) vision by the KrishnamurthyCommittee needs to see the light of theday. To succeed India needs to have betterCentre-State synergy beyond the rhetoricof cooperative federalism.

The Road Ahead

The foregoing clearly reveal disconnectbetween India’s growth record and humandevelopment initiatives, post economicliberalisation. India has not achieved thetwo crucial targets of reducing childmortality by 2/3rd and maternal health by3/4th, as mandated by the millenniumdevelopment goals (2000-2015). Childmalnutrition continues to remind anunacceptably high level of 48%. India’sreal challenge would be how to achievebalanced growth of different sectors,particularly a balance between economicinfrastructure and social overheads. Quality

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primary education and reasonable healthcare at affordable cost, as merit goods,must be the predominant remit of the state.The present tendency to abdicate thisresponsibility to the private sector withtheir oppressive commercial orientation,runs contrary to the concept of welfarestate. Universal Basic Income, as aconcept, must receive serious publicattention and debate, as it would guarantee312 million, who live below poverty line,a chance to live a life of dignity which isguaranteed as a fundamental right. AsJeffrey Sachs rightly observes “Ourgreatest illusion is that a healthy society canbe built on mindless pursuit of wealth”.Growth and development can go hand inhand, as China has shown, post theirliberalisation in the 1980s.

REFERENCES

Dreze, J. (2017). Giving short shrift tochildren’s right: In the last three years,important entitlements for childrenhave been undermined by the centre.The Hindu: retrieved from http://www.thehindu.com/todays-paper/tp-opinion/giving-short-shrift-to-childrens-rights/article17692034.ece. 28.03.2017

Dreze, J., & Sen, A. (2013). Anuncertain glory: India and itscontradictions. New Delhi: PenguinBooks India Pvt. Ltd.

Economic Survey, 2016-2017,Government of India. Retrieved from http://indiabudget.nic.in/survey.asp

Government of India, Ministry of Finance.http://www.finmin.nic.in/

India Union Budget 2017-18. http://indiabudget.gov.in/

Jaffrelot, C. (2006). India since 1950:Society, politics, economy and culture.New Delhi: Cambridge University PressIndia Pvt. Ltd.

Keynes, J.M. (2008). General Theory ofEmployment, Interest and Money.Atlantic

Malhotra, R. (2014). India public policyreport 2014: Tackling poverty, hungerand malnutrition. India: OxfordUniversity Press

Misra, S.N. & Ghadai, S.K. (2015).Merit Goods, Education Public Policy–India At Cross Roads. Journal ofEducation and Practice. Vol.6, No.12,PP140-147

Rajan, R.G. (2010). Fault lines: Howhidden fractures still threaten the worldeconomy. India: HarperCollins Publisher

Rajan, R.G., & Zingales, L. (2014).Saving capitalism from the capitalists.UP: Collins Business.

Smith, A. (1937). The wealth of nations.New York: The Modern Library,

Socio Economic & Caste Census (SECC)Report, 2011. Retrieved from http://rural.nic.in/sites/downloads/general/SECC_15JAN.pdf

Srinivas, M.N. (2000). Village, Caste,Gender and Method: Essays in Indian



Social Anthropology. New Delhi: OUPIndia; New edition

Srinivasan, T.N. (2011). Growth,Sustainability and India’s EconomicReforms. New Delhi: Oxford UniversityPress.

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Stiglitz, J. (2002). Globalization and itsdiscontents. New Delhi: Penguin BooksIndia Pvt. Ltd.

Virmani, A. (2009). The Sudoku of India’sgrowth. New Delhi: Business StandardBooks

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PATH ANALYTIC STUDY ON RELATIONSHIP BETWEENSHOPPING ORIENTATION, STORE ATTRIBUTES ANDPATRONAGE BEHAVIOUR OF RETAIL SHOPPERS IN

SELECTED CITIES OF GUJARAT STATE

Parimal H. VyasVice Chancellor, The Maharaja Sayajirao University of Vadodara and

Professor of Management Studies, Faculty of Management Studies andProfessor of Commerce And Business Management, Faculty of Commerce,

The Maharaja Sayajirao University of Vadodara, Vadodara [email protected]

Parag ShuklaAssistant Professor of Commerce & Business Management, Faculty of Commerce

The Maharaja Sayajirao University of Vadodara, [email protected]

B-9 Shantiniketan Society, White Church Road, Fatehgunj- 390002, Vadodara, Gujarat


ABSTRACTThis paper aims to examine influences of shopping orientation and store attributeson store patronage behaviour of selected shoppers who were conveniently drawnfrom amongst selected shopping malls of the selected cities of the Gujarat State,India.

This empirical descriptive research study is based on responses of 1500 Shopperswho were conveniently drawn to collect primary data with the help of structuredquestionnaire aimed at identification and evaluation of crucial dimensions relatingto shoppers’ patronage behaviour. An attempt is made to develop a Path AnalysisModel to study and showcase the linkages between shopping orientation, storeattributes and store patronage behaviour of selected shoppers who wereconveniently drawn from amongst selected shopping malls of the selected cities ofthe Gujarat State, India.

This research study in light of its findings suggests that the retailers need toeffectively offer and maintain the store attributes to drive store traffic and enhancepatronage intention.

Key words: Retailing, Shopping Orientation, Store Attributes, Patronage Behaviour,Customer Satisfaction

Parikalpana - KIIT Journal of Management, Vol.14(I), 2018


PROLOGUE:

The growth of organized retail industry inIndia is likely to entail large number of newjobs; income generation resultant intoimproved standard of living. The growingmiddle class is an important factorcontributing to the growth of retail in India.According to estimate, 91 Millionhouseholds will become part of ‘MiddleClass’ by the year 2030, the 570 Millionpeople are expected to live in cities, nearlytwice the current population of the UnitedStates. India’s consumption level is set toreach figure of US$ 1.5 Trillion from thecurrent level of US$ 750 Billion by the year2020 (Deloitte Indian Retail MarketReport, 2013, Lynch, 2005). India has theyoungest population profile in the wholeworld and this global Indian households isexpected to reach level of 9.5 Million withtheir spending power of 14.1 Trillionrupees by the year 2025 (Farrell andBeinhocker, 2007). There exists arelationship between shoppers’ beliefsabout the physical attractiveness of a storeand a patronage intention which suggeststhat the store attributes play a significantrole in influencing the shoppers’ choice ofa store and patronage behaviour (ibid).”

The chief objective of this research studyis to identify the linkages between shoppingorientations and store attributes and itsinfluences on Patronage Behaviour ofSelected Shoppers with the help of pathanalytical model in the selected cities ofthe State of Gujarat.

About Retail Sector in India:

The Indian retail market was estimated atUS$ 470 Billion in the year 2011 whichaccounted for approximately 35 per centof Gross Domestic Production (GDP), andis expected to reach US$ 675 Billion bythe year 2016 at the rate of CompoundedAnnual Growth Rate [CAGR] of 7.5 percent. (Technopak Retail Research Report-2011). The overall retail market of Indiais estimated to reach figure of Rs. 47Trillion (US$ 792.84 Billion) by the year2017 showing a strong potential for foreignretailers planning to enter India. In termsof the product category, 60 percent of theretail market of India is dominated by Food& Grocery whereas the figures for theApparel segment is 8 percent followed byMobile & Telecom Retail operating undernew modern formats. These are namely,Departmental Stores; Hypermarkets;Supermarkets, and Specialty Storesacross a range of categories fuelled by theliberalization of Foreign Direct Investment[FDI] Policy which is expected to propelforay of global retailers resultant intofurther fuelling of the growth of organizedretail in India (Ernst & Young RetailAssociation of India Report, March2014).”

REVIEW OF LITERATURE:

An attempt has been made to outline inbrief key aspects of earlier research studiesconcerning store attributes in retailing,shopping orientations & store patronagebehaviour of retail shoppers given asfollows.

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Store Attributes in Retailing:

Herpen and Pieters (2000) had identifiedthat the attribute-approach capturescustomers’ perception of assortmentvariety better than the product-basedapproach. Popkowski et al. (2001) hadconcluded the importance of various storeattributes varies by store format andcustomer base. Store attributes refers tothe underlying components of a store imagedimensions viz., merchandise; physicalfacilities; services; atmospherics etc.(Assael, 1992; Wong and Yu, 2003).Erdem et al. (1999) had examined thelinkages between consumer values and theimportance of some salient store attributesviewed as important by the retail shoppersand concluded that branding is an importantmarketing tool in retailing.”

Rajagopal and Srivastava (2008) havesupported the view that customers’ choiceof shopping malls over traditional marketstores is influenced by various factors viz.,ambience; assortment; sales promotionschemes and in-store servicesrespectively.”

Store Patronage Behaviour:

According to Engel, Blackwell andMiniard (1995), environmental dimensionsviz., air quality; lighting; layout; carpeting;and aisle width and placement are physicalstore attributes that are used to projectstore image and influence store choicerespectively. According to Bitner (1992),the physical environment creates an imageand influences individual behaviour of retail

shopper in retail stores. The patronagebehaviour encompasses the decisionprocess related to where customers shop;how they shop, and what they purchaserespectively. (Moschis, 1992; Stafford &Stafford, 1986). The driving force behindshopping decision process is patronagemotives which are the reasons why retailshoppers shop and make shopping fromcertain retail stores (Michman, 1991).Paulins and Geistfeld (2003) as well asShim and Kotsiopulos (1992) hadsupported the relationship between storeimage attributes and patronage behaviourof retail shoppers.

The behaviour of shoppers differsaccording to the place where they areshopping from and also their involvementlevel too differs with the act of shopping(Berman and Evans, 2005). There is agrowing need to evaluate the true driversof shopping behaviour in the Indian retailingcontext (Sinha and Banerjee, 2004).”

Shopping Orientation:

Darden and Dorsch had stated thatorientations are based on past shoppingexperiences and the personal value system.To illustrate, with respect to values,orientations may reflect consumers’appreciation for environmentally friendlytextiles and apparel products. Additionally,shopper orientations may be used torepresent consumers’ personal, economic,recreational and social motivations forshopping (Darden and Dorsch, 1990).These orientations vary from consumer to

Path analytic study on relationship between shopping orientation....


consumer (Luomala 2003) and theyrepresent rather “enduring characteristicsof individuals” (Westbrook and Black1985). Other studies had emphasized theindividual character of central perceptiondimensions, whose importance weightingsmay be different for different consumersdue to their shopping orientations(Birtwistle et al. 1999; Doyle and Fenwick(1974-75). Jarratt (1996) had attemptedto cluster or classify shoppers. Suchshopper taxonomies are often based onshopping orientations (Jarratt, 1996). Hehad identified “have to” shoppers,“moderate” shoppers, “experiential”shoppers, “product-focused” shoppers,“service” shoppers, and “practical”shoppers based on the importance theshoppers put on certain store features(Jarratt, 1996). A similar study wasconducted by Brown and Reid (1955)using in-depth interviews of womenshoppers had found that shoppers couldbe classified as dependent, compulsive,and individualistic (Brown and Reid,1955).”

Concepts, constructs:

The researchers have defined the basicterms used in this research paper asfollows.

Patronage Behaviour:

Patronage behaviour is defined as howindividuals choose an outlet for shopping,store choice and patronage patterns arebased on consumer’s perceptions, images,

and attitudes formed from experiences,information, and need. (Haynes, Pipkin,Black, and Cloud, 1994).”

Store Attributes:

“Store attributes refers to specific attributesgrouped under each specific store imagedimensions viz., atmosphere; convenience;facilities; institutional; merchandisepromotion; sales personnel, and servicerespectively (Janse van Noordwyk,2002).”

Shopping Orientation:

Shopping orientation is defined as ashopper’s style that places particularemphasis on a shopping-specific lifestyleencompassing shopping activities, interestsand opinions, and reflecting a view ofshopping as a complex social, recreationaland economic phenomenon (Visser andPreez, 2001).”

RESEARCH PROBLEM:

The researchers sought to study andexamine the relationship betweenshopping orientations and store attributesand its influences on Patronage Behaviourof Selected Shoppers with the help of pathanalytic model in the selected cities of theState of Gujarat viz., Vadodara,Ahmedabad, Surat and Rajkotrespectively.”

RESEARCH METHODOLGY:

An empirical research study based ondescriptive research design was

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conducted to study influences of shoppingorientation and selected store attributes onstore patronage behaviour of selectedshoppers that were from amongst differentshopping malls located in the selected citiesof the State of Gujarat. The primary datawere collected using structuredquestionnaire from 1500 shoppers whowere conveniently drawn using non-probability sampling design from differentretail stores located from the selected citiesof the Gujarat State viz; 280 shoppers fromVadodara, 475 from Ahmedabad, 400from , and 250 shoppers were drawn fromthe Rajkot City respectively. The reliabilitytest was administered and data analysis hadbeen carried out. The researchers havealso applied Confirmatory Factor Analysis[CFA] and the Path Analysis Model wasdeveloped to study the linkages betweenshopping orientations, store attributes andthe patronage behaviour of selected retailshoppers. The study offers useful findingsand implications which shall be useful informulating customized retail marketingstrategies by retailers.”

OBJECTIVE

The key objective of this research studywas to identify the linkages betweenshopping orientations and store attributesand its influences on Patronage Behaviourof Selected Shoppers with the help of pathanalytic model in the selected cities of theState of Gujarat.”

RELIABILITY

The result of reliability test showed theCronbach’s Alpha value ranging from

0.700 to 0.870 which showed the internalreliability of the scale, and reflected thedegree of cohesiveness amongst theselected items (Naresh K. Malhotra, 2007and Jum C. Nunnally, 1981).DATA ANALYSIS ANDINTERPRETATION:Demographic Profile of SelectedShoppers’:The data analysis of age groups ofshoppers revealed that in age group of 16to 40 years the 53 percent shoppers werefrom Baroda, 43 percent from Surat, 36percent from Rajkot and 80 percent fromAhmedabad city. Similarly, in the age groupof 41 to 59 years 36 percent were fromBaroda City, 42 percent were from SuratCity, 48 percent were from Rajkot and 2percent were from Ahmedabad City.Further, male shoppers were found around70 percent whereas nearly 30 percent ofthem were females. Overall, 33 percentshoppers were found as unmarried andremaining 67 percent were married. So faras Educational Qualifications is concerned43 per cent in Baroda and AhmedabadCities, 38 percent in case of Surat and 30percent in Rajkot Cities were found havingPost-Graduation as their EducationalQualifications respectively. Considering theannual family income in various cities, itwas found that 32 percent of shoppers’ inBaroda City were having annual familyincome of less than Rs 4 lakhs, followedby almost similar trend that is 36 percentin Surat City followed by 47 percent inRajkot City, and 19 percent inAhmedabad City respectively.””



Table 01: Summary of Indicators (Experience) andReliability Alpha Score for Measuring Store Attributes

Sr. No

Name of the Grouping Variable

Constructs Vadodara City

Surat City

Rajkot City

Ahmeda-bad City

Total Sample Size (1500)

Number of Shoppers’ (280) (280) (275) (475)

Number of Items (65)

CRONBACH'S ALPHA SCORE Overall Reliability

01 Accessibility of the Retail Store 05 0.663 0.787 0.818 0.649 0.737

02 Range of the Products 04 0.773 0.861 0.890 0.686 0.794

Sr. No

Name of the Grouping Variable

Construct Vadodara City

Surat City

Rajkot City

Ahmedabad City

Sample Size(1500)

Number of Shoppers’ (280) (280) (275) (475)

Items (65) CRONBACH'S ALPHA SCORE Overall Reliability

03 Sales Promotion Schemes offered in the Retail Store

05 0.679 0.697 0.736 0.601 0.692

04 Behaviour of Staff of the Retail Store 09 0.773 0.825 0.854 0.737 0.796

05 Store Layout/Ambience of the Retail Store

12 0.712 0.714 0.754 0.639 0.700

06 Physical Facilities in the Retail Store 17 0.795 0.894 0.922 0.727 0.870

07 Atmosphere in the Retail Store 08 0.717 0.792 0.814 0.636 0.742

08 Institutional Factors 05 0.713 0.744 0.762 0.632 0.715

The Selected Retail Shoppers’ OverallSatisfaction/Dissatisfaction from StoreAttributes.

Table 02 represent the perceivedimportance of the Store Attributes and theRetail stores’ ability in meeting theseexpectations of the shoppers’. It clearlyindicates that the ratio of the Attribute of‘Institutional Factors’ of the retail store is

0.98 was found as the highest. It meansthat the Institutional factors such asclientele, overall impression, storereputation, store association was found ashaving high perceived importance to theretail shoppers’ in the retail store, and theretailers were able to successfully meetthese expectations of the shoppers’ whichis reflected in terms of the shoppers’ overallsatisfaction with these factors.

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The other important store attribute is‘Accessibility’ was found as having theratio 0.94 followed by ‘Store Layout/

Table 02: Table showing the Ratio of perceived importance and overallsatisfaction with the selected criteria of store attributes

Sr. No.

Selected Store Attributes Mean Score

Selected Store Attributes Mean Score

Ratio

01 Perceived Importance of Accessibility of the Retail Store

3.57 Overall Satisfaction with Accessibility of the Retail Store

3.34 0.94

02 Perceived Importance of Range of the Products in the Retail Store

3.81 Overall Satisfaction with Range of the Products in the Retail Store

3.44 0.90

03 Perceived Importance of Sales Promotion Schemes offered in the Retail Store

3.93 Overall Satisfaction with Sales Promotion Schemes offered in the Retail Store

3.30 0.84

04 Perceived Importance of Behaviour of Staff of the Retail Store

3.70 Overall Satisfaction with Behaviour of Staff of the Retail Store

3.19 0.86

05 Perceived Importance of Store Layout/Ambience of the Retail Store

3.66 Overall Satisfaction with Store Layout/Ambience of the Retail Store

3.34 0.91

06 Perceived Importance of Physical Facilities in the Retail Store

3.70 Overall Satisfaction with Physical Facilities in the Retail Store

3.23 0.87

07 Perceived Importance of Atmosphere in the Retail Store

3.84 Overall Satisfaction with Atmosphere in the Retail Store

3.26 0.85

08 Perceived Importance of Institutional Factors

3.52 Overall Satisfaction with Institutional Factors

3.44 0.98


Ambience’ having the ratio of 0.91 and‘Range of the Products in the Retail Store’which had the ratio of 0.90 respectively.

PROPOSED STRUCTURALMODEL OF THE RESEARCHSTUDY:

In order to evaluate how well a proposedconceptual model consists of observedindicators and the hypothesized constructsexplains or fits the data the StructuralEquation Model is designed and has beenshown as given below as per the FigureNumber: 01.

In order to achieve the objectives of thestudy, an attempt was made to carry outcomprehensive review of the existing

relevant literature was undertaken, andsubsequently, a Theoretical StructuralModel was developed as shown in theFigure Number 01 that incorporatesconcepts from the subject domain ofconsumer behaviour in retail stores. Theretail shopper is presumed to be influencedby the store attributes that are used by theretailers to influence retail shoppers’behaviour while shopping. The researchershave considered to include 08 selectedvariables of the store attributes viz.,accessibility, sales promotional schemes,ambience of the retail store, store


Figure No 01: Proposed Structural Model of Shopping Orientations andStore Attributes on Patronage Behaviour and Overall Satisfaction

of the Retail Shopper

atmosphere, institutional factors of the retailstore, the sales staff behaviour, the rangeof products in the store, and the physicalinfrastructure facilities of the storerespectively. The shopping orientations ofthe retail shoppers that can be describedas his or her own pre-dispositions towardsthe act of shopping. The retail shoppers’tend to have their individualistic style andpreferences for shopping while visiting theretail store. Some retail shoppers’ tend tohave an economic orientation where theytry to maximize on the economic value ofshopping whereas others might seekrecreation while they visit the retail store.

There are some retail shoppers’ who wanta personalised shopping experience by theretailers. This will influence their intentionsto visit a particular retail store which in turnleads to store loyalty and repurchaseintention of the retail shoppers.

The retail shopper will spread a positiveword of mouth as he or she is satisfiedfrom the retail store derived from his orher overall satisfaction from the retail store.

This research study has attempted todevelop and empirically test a theoreticalmodel describes a logical flow among theconstructs by indicating the directions ofthe causes and effects of the interplay of

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the factors relating to the shoppingorientations and store attributes onpatronage behaviour and overallsatisfaction of the retail shopper.””

Each arrow at the end of a line depicts aprogressive linkage between constructs ofthe research study. The direction of thearrows in the model specifies therelationship as well as the linkages betweenthe constructs which is empirically testedas per the degree of the relationshipbetween the constructs in this study.”

Another two important constructs that is‘I would continue to shop from the sameretail store’ and ‘I shall recommend thestore to others’ has been regarded as themediating endogenous construct that alsoplays the role of dependent variable inthese relationships. This construct alsoincludes and intervenes between the twoexogenous constructs that is storeattributes and shopping orientations thatare considered to explain the intention ofthe retail shopper to continue to shop morefrom the retail store and recommendationof the same retail store to other retailshoppers and the overall satisfaction of theretail shoppers. The arrows lead from theexogenous constructs to the mediatingconstruct, which is thought to be partially

explained by the preceding (Exogenous)constructs.”

KMO MEASURE OF SAMPLINGADEQUACY:

The result of KMO measure of samplingadequacy was closer to 0.60 whichindicated that the present data weresuitable for application of the factoranalysis. Similarly, Bartlett’s Test ofSpehericity (0.00) was found as significant(p<.05) reflective of the fact that sufficientcorrelation exists between the criteria forapplication of the factor analysis.”

SUMMARY OF CONFIRMATORYFACTOR ANALYSIS [CFA]:

The researchers have attempted toempirically test by applying theConfirmatory Factor Analysis amongst onthe selected dimensions of shoppingorientations that is ‘Way of Shopping’,‘Planning for shopping’, and ‘Experienceof shopping’ respectively. The FigureNumber: 02 to 08 depicts theHypothesized Measurement Models forconfirmatory factor as well as revisedmodel fit. Further, the Table Number: 03to 05 offers information on the storeattributes taken into consideration for theConfirmatory Factor Analysis in thisresearch study.



Figure: 02: Hypothesized Measurement Model for Confirmatory FactorAnalysis of Way of Shopping

Table 3: Detailed List of Items for Shopping Orientation Attributes of Way of Shopping

Sr. No. Item Code List of the Items 01 1 WAY I like to go for shopping to pass leisure time 02 2 WAY I go for shopping to reduce my stress 03 3 WAY I feel tired after shopping 04 4 WAY The sales people add enjoyment to my shopping 05 5 WAY I do not like to spend too much time for shopping 06 6 WAY Shopping is full of joy and fun for me 07 7 WAY I dislike presence of crowd while shopping 08 8 WAY Shopping provides me social experiences 09 9 WAY I like to go for shopping alone 10 10 WAY I like to buy from a particular retail store only

In the above measurement model forconfirmatory factor analysis ofshopping orientation in which theselected fourteen statements were aboutway of shopping of the shoppers’ in the

retail store were adapted. A five-pointLikert scale was used as the responseformat with assigned values rangingfrom 1 = Strongly Disagree to 5 =Strongly Agree.

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Figure 03: Revised Model Fit for Confirmatory Factor Analysis of ShoppingOrientation of Way of Shopping

The Confirmatory Factor Analysis on themeasurement model was conducted andthe less influencing variables wereeliminated from the model. The revisedmodel fit was developed as given in theFigure Number: 03 that has identified thekey influencing variables i.e. five variablesfor way of shopping viz; ‘I like to go for

shopping to pass leisure time (1 WAY)’,‘I go for shopping to reduce my stress (2WAY)’, ‘The sales people add enjoymentto my shopping (4 WAY)’, ‘Shopping isfull of joy and fun for me (6 WAY)’, and‘Shopping provides me social experiences(8 WAY)’ respectively.

Figure: 04: Hypothesized Measurement Model for Confirmatory FactorAnalysis of Planning for Shopping



Table: 04: Detailed List of Items for Shopping Orientation Attributes ofPlanning for Shopping

Sr. No. Item Code List of the Items 01 1PLAN I prefer to check price tag before buying a particular product 02 2 PLAN I prefer to touch and inspect the products before buying 03 3 PLAN I seek help from sales staff while buying a product 04 4 PLAN I like to buy from new retail stores 05 5 PLAN I like to compare different products before buying a product 06 6 PLAN I like to spend less time while shopping 07 7 PLAN I prepare a shopping list before actual shopping 08 8 PLAN I often end up shopping more products than I actually need 09 9 PLAN The retail stores offers me better services 10 10 PLAN I make unplanned visits to retail stores

In the above measurement model (FigureNumber: 04) for confirmatory factoranalysis of shopping orientation in whichthe selected ten statements were about‘Planning for Shopping by the shoppers’

in the retail store were adapted. A five-point Likert scale was used as theresponse format with assigned valuesranging from 1 = Strongly Disagree to 5 =Strongly Agree.

Figure 05: Revised Model Fit for Confirmatory Factor Analysis of ShoppingOrientation of Planning for Shopping

The Confirmatory Factor Analysis onthe measurement model was conductedand the less influencing variables wereeliminated from the model. The revisedmodel fit was developed as given in theFigure Number: 05 that has identifiedthe key influencing variables that is

three variables for planning forshopping viz; ‘I seek help from salesstaff while buying a product (3 PLAN’,‘I like to spend less time whileshopping (6 PLAN)’, and ‘I prepare ashopping list before actual shopping (7PLAN)’ respectively.”

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Figure: 06: Hypothesized Measurement Model for Confirmatory FactorAnalysis of Shopping Orientation of Sharing Experiences

Table: 05: Detailed List of the Items for the Shopping Orientation ofExperience of Shopping

Sr. No.

Item Code

List of the Items

01 1EXP I discuss with family members about products to be purchased by me 02 2 EXP I discuss with others about products in the retail stores 03 3 EXP I share bad shopping experiences with others 04 4 EXP I share information about various sales promotion schemes with others

In the above measurement model (FigureNumber 06) for Confirmatory FactorAnalysis of shopping orientation in whichthe selected four statements were about‘Experience of Retail shoppers in the

retail store’ were adapted. A five-pointLikert scale was used as the responseformat with assigned values ranging from1 = Strongly Disagree to 5 = StronglyAgree.

Figure: 07: Revised Model Fit for Confirmatory Factor Analysis of ShoppingOrientation of Sharing Experiences of Shopping

Confirmatory Factor Analysis on themeasurement model was conducted andthe less influencing variables wereeliminated from the model. The revisedmodel fit was developed as given in theFigure Number: 07 that has identified thekey influencing variables i.e. three variables

for shopping experience of shoppers’ viz;‘I discuss with others about products inthe retail stores (2 EXP)’, ‘I share badshopping experiences with others (3EXP)’, and ‘I share information aboutvarious sales promotion schemes withothers (4 EXP)’ respectively.



SUMMARY OF CONFIRMATORYFACTOR ANALYSIS [CFA] OFSTORE ATTRIBUTES USINGANALYSIS OF MOMENTSSTRUCTURE [AMOS]:The researchers have attempted toempirically test the Confirmatory FactorAnalysis amongst selected 08 storeattributes constructs i.e. accessibility, salespromotion schemes, store ambience, storeatmosphere, physical facilities in the store,

institutional factors, range of products andbehaviour of the sales staff in the retailstore respectively.The Figure Number 07 to 14 depicts theHypothesized Measurement Models forConfirmatory Factor as well as revisedmodel fit. Further, the Table Number: 06to 09 offers details about the storeattributes taken into consideration for theConfirmatory Factor Analysis of thisresearch study.

Figure: 08: Hypothesized Measurement Model for Confirmatory FactorAnalysis of Accessibility, Sales Promotion Schemes and Store Ambience

Table 06: Detailed List of the Items for the Store Attributes of Accessibility,Sales Promotion Schemes and Store Ambience

Sr. No. Item Code List of The Items For The Store Attributes 01 ACC 1 I like a retail store for shopping which is located near to my residence 02 ACC 2 I like a retail store for shopping which is located near to my office 03 ACC 3 It is convenient for me to go for shopping at any time in the store 04 ACC 4 I get required information about the retail store 05 ACC 5 The opening hours of the retail store are convenient to me 06 PROMO 1 The products offered with lower prices makes me feel less burden of

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06 PROMO 1 The products offered with lower prices makes me feel less burden of making the payment

07 PROMO 2 The retail store gives me discount schemes 08 PROMO 3 The colour(s) and symbols used in promotions (e.g. advertisements)

are attractive 09 PROMO 4 I like to buy products offered to me by retail store on promotional,

discounted schemes 10 PROMO 5 I like to buy products at special events (e.g. Wednesday bazaar at big

bazaar ) 11 AMB 1 I feel at ease while shopping at the retail store 12 AMB 2 The infrastructure of the retail store is properly maintained 13 AMB 3 The retail store has an attractive look 14 AMB 4 The retail store has an attractive interior 15 AMB 5 The placement of aisles in the retail store is appropriate which makes

easy for me to get what I want 16 AMB 6 There is plenty of room to walk around in the retail store 17 AMB 7 The sufficient information on signboards is displayed in the retail

store 18 AMB 8 The décor of the retail store is attractive 19 AMB 9 I like clearly visible store advertisements in the retail store 20 AMB 10 Striking window displays of products increases my desire to buy in

that retail store 21 AMB 11 The entry to the retail store is comfortable 22 AMB 12 The retail store has enough checkout points

In the above measurement model (Figure08) for Confirmatory Factor Analysis ofaccessibility, sales promotion schemes andstore ambience in which the selected 05statements were about ‘accessibility of theretail store’, five statements related to the‘sales promotion schemes in the retailstore’, and the 12 statements related tothe ‘ambience of the retail store’ wereadapted. The statements and hypothesizedmeasurement model contains the selectedstore attributes of viz., accessibility, salespromotion schemes and store ambienceare shown in Figure number one. A five-point Likert scale was used as theresponse format with assigned values

ranging from 1 = strongly disagree to 5 =strongly agree. The model shows thepositive correlation between accessibility,sales promotion schemes and storeambience.The Confirmatory Factor Analysis on themeasurement model (Figure 09) wasconducted and the less influencingvariables were eliminated from the model.The revised model fit was developed asgiven in the Figure 08 had identified thekey influencing variables that is 03 variablesfor accessibility viz; ‘I like a retail storefor shopping which is located near to myresidence (ACC 1)’, ‘I like a retail store



for shopping which is located near to myoffice (ACC 2)’, and; It is convenient for

me to go for shopping at any time in theretail store (ACC 3)’ respectively.”

Figure 09: Revised Model Fit for Confirmatory Factor Analysis ofAccessibility, Sales Promotion Schemes and Store Ambience

“In case of the store attribute of salespromotion schemes in the retail store the03 key influencing variables viz; ‘Thecolour(s) and symbols used in promotionsare attractive (PROMO 3)’, ‘I like to buyproducts offered to me by retail store onpromotional discounted schemes(PROMO 4)’, and ‘I like to buy productsat special events (PROMO 5)’ wereidentified respectively.”

“In case of the store attribute of ambiencein the retail store the 04 key influencingvariables viz; ‘The retail store has anattractive interior (AMB 4)’, ‘Theplacement of aisles in the retail store isappropriate which makes easy for me toget what I want (AMB 5)’, ‘There is plentyof room to walk around in the retail store(AMB 6)’, and ‘The sufficient informationon signboards is displayed in the retail store(AMB 7)’ were identified respectively.”

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Table 07: Detailed List of Items for Store Attribute of Physical Facilities inRetail Store

Sr. No. Item Code List of The Items For The Store Attributes 01 FAC 1 A trolley and/or shopping basket for carrying products is

available in the retail store 02 FAC 2 The retail store exchanges products returned by me 03 FAC 3 The retail store refunds price of products once sold 04 FAC 4 The retail store accepts a credit card 05 FAC 5 The retail store accepts a debit card 06 FAC 6 The retail store provides membership cards 07 FAC 7 The retail store provides discount on membership cards 08 FAC 8 The retail store provides after sales services 09 FAC 9 The retail store has an escalator facilities 10 FAC 10 The retail store has an elevator facilities 11 FAC 11 The retail store has clean washroom/toilets 12 FAC 12 The retail store has a resting area 13 FAC 13 The retail store has a provision for physically challenged

people 14 FAC 14 The retail store has spacious fitting and dressing rooms 15 FAC 15 The retail store has adequate security arrangements for the

safety of vehicles in the parking area 16 FAC 16 The availability of parking area in retail store is sufficient 17 FAC 17 There are restaurants and other shops in the vicinity of the retail

store

In the above measurement model shown(Figure 10) for confirmatory factoranalysis of physical facilities in the retailstore in which the 17 statements relatedto the physical facilities of the retail storewere adapted. The statements andhypothesized measurement model

contains the selected store attributes ofphysical facilities in the retail store andthe same were measured on a five-pointLikert scale as the response format withassigned values ranging from 1 =Strongly Disagree to 5 = StronglyAgree.

Figure 11: Revised Model Fit for Confirmatory Factor Analysis of PhysicalFacilities in the Retail Store



The Confirmatory Factor Analysis on themeasurement model was conducted andthe less influencing variables wereeliminated from the model. The revisedmodel fit was developed as given (FigureNumber:11) that has identified the keyinfluencing variables of physical facilitiesin the retail store viz; ‘The retail store

accepts a credit card (FAC 4)’, ‘Theretail store accepts a debit card (FAC 5)’,‘The retail store provides membershipcards (FAC 6)’, ‘The retail store providesdiscount on membership cards (FAC 7)’,‘The retail store has an elevator facilities(FAC 10)’, and ‘The retail store has cleanwashroom/toilets (FAC 11) respectively.

Figure 12: Hypothesized Measurement Model for Confirmatory FactorAnalysis of Institutional Factors and Behaviour of the Sales Staff

Table 08: Table Showing Detailed List of the Items for the Store Attributesof Institutional Factors and Sales Staff in the Retail Store

Sr. No. Item Code List of The Items For The Store Attributes 01 INST 1 I receive birthday wishes on mobile from the retail store 02 INST 2 I receive birthday wishes on email from the retail store 03 INST 3 I receive anniversary wishes on mobile from the retail store 04 INST 4 I receive anniversary wishes on email from the retail store 05 INST 5 The retail stores are crowded 06 STAFF 1 The sales staff of the retail store has required information of the

products 07 STAFF 2 The sales staff of the retail store has required information of the

availability of the products 08 STAFF 3 The sales staff of the retail store has the required information of

the price of the products 09 STAFF 4 The sales staff of the retail store has the required information of

the display of the products 10 STAFF 5 The sales staff of the retail store responds to my queries 11 STAFF 6 The sales staff of the retail store responds to my problems 12 STAFF 7 The sales staff of retail store are friendly with me 13 STAFF 8 The sales staff of retail store are polite and courteous 14 STAFF 9 The sales staff of retail store are well trained

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In the above measurement model shown(Figure : 12) for Confirmatory FactorAnalysis of institutional factors andbehaviour of the sales staff in the retailstore in which the 05 statements relatedto the Institutional factors and 09statements related to the Behaviour of thesales staff in the retail store wereconsidered. The statements andhypothesized measurement model contains

the selected store attributes of Institutionalfactors of the retail store and the behaviourof the sales staff in the retail store and thesame were measured on a five-point Likertscale as the response format with assignedvalues ranging from 1 = Strongly Disagreeto 5 = Strongly Agree. The model assumesthe positive correlation betweeninstitutional factors and the behaviour ofthe sales staff in the retail store.

Figure 13: Revised Model Fit for Confirmatory Factor Analysis ofInstitutional Factors and Behaviour of the Sales Staff

The Confirmatory Factor Analysis on themeasurement model was conducted andthe less influencing variables wereeliminated from the model.

The revised model fit was developed asgiven in the Figure : 13 that has identifiedonly the key influencing variables i.e. fourvariables for Institutional Factors viz; ‘Ireceive birthday wishes on mobile from theretail store (INST 1)’, I receive birthdaywishes on email from the retail store (INST2)’, ‘I receive anniversary wishes onmobile from the retail store (INST 3)’, and‘The retail store keeps me updated by

sending regular information about variousoffers and schemes (INST 4)respectively.”

In case of the store attribute of sales staffbehaviour in the retail store the 04 keyinfluencing variables that were identifiedwere viz., ‘The sales staff of the retailstore responds to my queries (STAFF5)’, ‘The sales staff of the retail storeresponds to my problems (STAFF 6)’,‘The sales staff of retail store are friendlywith me (STAFF 7)’, ‘The sales staff ofretail store are polite and courteous(STAFF 8) respectively.



Figure 14: Hypothesized Measurement Model for Confirmatory FactorAnalysis of Range of Products and Store Atmosphere in the Retail Store

Table 09 : Detailed List of Items for Store Attributes of Range of Productsand Store Atmosphere

Sr. No. Item Code Detailed Name of The Items For The Store Attributes of Range of Products and Store Atmosphere

01 RANGE 1 The retail store provides me a wide variety of products 02 RANGE 2 The retail store provides me a variety in different

categories of products 03 RANGE 3 The products are available in different sizes in the retail

store 04 RANGE 4 I get products of good quality in the retail store 05 ATM 1 There are sufficient lights in the retail store 06 ATM 2 The retail store has sufficient air conditioning 07 ATM 3 The house keeping of retail store is good 08 ATM 4 I feel pleased and comfortable due to the presence of the

other shoppers in the retail store 09 ATM 5 I feel safe due to the presence of other shoppers in the

retail store 10 ATM 6 I feel comfortable because of light music being played in

the retail store 11 ATM 7 The environment of the retail store motivates me for

shopping 12 ATM 8 I get pleasant smells inside the retail store

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In the above measurement model shown(Figure : 14) for Confirmatory FactorAnalysis of range of products in the retailstore and the retail store atmosphere inwhich the 04 statements related to therange of products, and 08 statementsrelated to the retail store atmosphere wereconsidered. The statements andhypothesized measurement model containsthe selected store attributes of range of

products of the retail store and the retailstore atmosphere and the same weremeasured on a five-point Likert scale asthe response format with assigned valuesranging from 1= Strongly Disagree to 5 =Strongly Agree.This model assumes the positivecorrelation between range of products inthe retail store and the retail storeatmosphere.

Figure 15: Revised Model Fit for Confirmatory Factor Analysis of Range ofProducts and Store Atmosphere in the Retail Store

Confirmatory Factor Analysis on themeasurement model was conducted andthe less influencing variables wereeliminated from the model. The revisedmodel fit was developed as given in theFigure Number: 15 that has identifiedonly the key influencing variables that is04 variables for range of products viz;‘the retail store provides me a widevariety of products (RANGE 1), ‘Theretail store provides me a variety indifferent categories of products (RANGE2)’, ‘The products are available indifferent sizes in the retail store (RANGE

3)’, and ‘I get products of good qualityin the retail store (RANGE 4).”

In case of the store attribute of StoreAtmosphere in the retail store only thethree key influencing variables that wereidentified were viz.,’I feel pleased andcomfortable due to the presence of theother shoppers in the retail store (ATM4), I feel safe due to the presence of othershoppers in the retail store (ATM 5) and Ifeel comfortable because of light musicbeing played in the retail store (ATM 6)respectively.



STRUCTURAL EQUATION MODELING [SEM] USING PATH ANALYSISCONSIDERING SHOPPING ORIENTATIONS AND STORE ATRRIBUTES:

Figure 16: Structural Equation Modelling [SEM] Using Path Analysis ShowingRelationship between Shopping Orientations and Store Attributes with Overall

Satisfaction through Mediating Variable

The above given Figure Number 16 depictrelationship between shopping orientationsand store attributes with overall satisfactionthrough mediating variables viz., ‘I wouldcontinue to shop more”, and “’I shallrecommendation to others’. In the abovemode the relationships between theconstructs were examined based on chi-square associated with path coefficientsbetween the constructs. The Chi-squarevalue (2188.207) was on higher side thana certain critical value i.e. p < .05 whichindicated that there exists a significantrelationship between constructs.”

The major determinants of shoppingorientations included all the 03 variablesdepicted in the model that is ‘The style orway of shopping’, ‘His planned effort forshopping’, and ‘His actual experiencefrom shopping’ respectively. The major

determinants of store attributes includedthe 05 variables that is ‘PromotionalSchemes’, ‘Range of Products’,‘Atmosphere of the Store’, ‘Accessibilityof the Retail Store’, ‘Sales Staff of theRetail Store’, and Store Atmosphere ofthe Retail Store out of 08 depicted in themodel that is ‘Accessibility, ‘PromotionalSchemes’, ‘Ambience of the Store’,‘Range of Products’, ‘Facilities in theStore’, Staff Behaviour in the Retail Store,Atmosphere of the Store, and ‘TheInstitutional factors of the Retail Store. Theshopping orientation of shoppers’ thatreflected shoppers’ way of shopping andthe store attributes used by the retailers inorder to attract shoppers’ are the majordeterminants of the shoppers’ overallsatisfaction through the mediating effects of“I would continue to shop more” and“Recommendation to others” respectively.”

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The result of SEM Analysis indicated thatthe path from the construct of shoppingorientations as well as the construct ofstore attributes was significant andpositively related with overall satisfactionof shoppers through mediating variables.Thus, it can be inferred that shoppingorientations and store attributes both playa vital role in determining the shoppers’own decision to shop and hisrecommendation to others to shop fromthe same retail store that is the positive

word of mouth spread to others. Theinfluence of the selected retail storeattributes used by the retailers also playsan important role while shoppers are insidethe retail store for actual shopping. Theretailers must focus on understanding theshopping orientations of the shoppers’ soas to effectively create an atmosphere andalign the store attributes that matches withthe shoppers’ own style and predispositionof shopping.

Table 10: Fit Indices of Measurement Model[Model as Given in Figure: 16]

The below given table provides the model fit Indices for the Structural Equation Model[SEM] Using Path Analysis Showing Relationship between Shopping Orientations andStore Attributes with Overall Satisfaction through Mediating Variable.

Name of the Index Model fit Indices CMIN (Chi-square or Minimum Discrepancy Chi-square) 27.01 GFI (Goodness of Fit Index ) 0.829 NFI (Normed-Fit Index) 0.648 RFI (Relative Fit Index) 0.604 CFI (Comparative Fit Index ) 0.656 AGFI (Adjusted Goodness of Fit Index) 0.779 RMR (Root Mean Square Residual) 1.049 RMSEA (Root Mean Square Error of Approximation ) 0.132

MANAGERIAL IMPLICATIONSOF THE RESEARCH STUDY:The researchers have attempted to provideimplications based on the selected criteriaof shopping orientations that is ‘The wayof shopping’, ‘The planned activities thatshoppers’ undertake before their shoppingjourney’, and ‘Their experiences ofshopping which plays an important role in

shaping the overall predispositions of theshoppers’ respectively.

The shoppers’ do shopping with these pre-defined philosophies that they have beforethey undertake the task of shopping. Forsome shoppers, the act of shopping ismerely a pass time activity in their leisuretime, some feel that shopping is fun andenjoyment, and they tend to seek



recreation, and fun while they are in theretail store. It is also evident that someshoppers are meticulous and they doprepare a shopping list, discuss with familymembers and others and also pay attentionto all the sales promotional schemes of theretailers.”

The results of the research study pertainingto the store attribute of accessibility hadrevealed that shoppers feel comfortable,and find the store easily accessibleconsidering is location that is nearbyresidence or office or acquiring theinformation about the retail stores openinghours.”

The data analysis considering the differentgroups of different shoppers from differentcities had revealed that their criterion fordetermining accessibility as a store attributeis different for each group of shopper aswell as the preference of kind ofinformation need and convenient openinghours of the retail store.”

The retailers must ensure specific area wisesegmentation strategies to attract and lureshoppers by communicating them aboutthe accessibility in terms of nearness, hoursof operation of store. The retailers needto focus on identifying the accessibilityfactor of their retail store in city by knowingthe store traffic in the different locationsso as to track the movement in the areawhere people can move comfortably andeasily. The retailers should ensure that theyopen more branches in the most convenientlocation considering the different areas ofthe given city.”

The retailers should also make sure thattheir retail stores are situated in the areaswhere the road connectivity, transportationfacilities and other infrastructural facilitiesare available so as to facilitate more numberof shoppers to visit the retail store. It canbe inferred from the data analysis that thepromotional schemes play a major role instimulating the shoppers’ to buy more. Thesales promotion schemes viz., bundlingoffers, charging less price, offeringdiscount schemes, special discount periodduring festive season and specialpromotion schemes can influence theshoppers’ buying motives. The variety ofsales promotion schemes will not onlyincrease the sales volume of the retail storebut also create a Unique SellingProposition in a competitive organizedretail market.”

The special discount events like the“Wednesday bazaar at Big Bazaar” and“Sabse Sasta Din” will make shoppers’visit regularly with an anticipation ofdiscount on even regular days.”

The sales promotion schemes will lead toimpulse buying and the retail shoppers’ willend up buying more products which in turnhelps to increase the sales volume and alsostock clearance of old as well as non-moving, out of fashion trends productswhich facilitates working capitalmanagement by converting stocks intosales proceeds. The retailers mustemphasis on proper display of merchandiseand Mannequins by proper windowdressing for promotion of the particular

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product. The aim of the retailer should beto create differentiation to grab maximumeye-balls and in-store promotional signage,and floor merchandising in a creativemanner may lead higher level of impact onconsumers’ impulse buying behaviour. Thefindings of this research study providedsufficient evidence that retailers caneffectively utilize promotional campaignsto increase desirability of products, andto help customers become aware of theproducts as well as to create favourableattitudes.”

It can be analysed from the data that theshopping facilities in the retail store viz.,availability of adequate number of trolleysfor shopping, refund and exchange offers,accepting all Debit cards and credit cards,discount schemes on membership orprivilege cards, after sales services,escalator and elevator facilities, cleanwashrooms, provision of resting area forthe differently able people, spaciousdressing rooms, adequate parking spaceand security arrangements and availabilityof restaurants and other shops in thevicinity of the retail store can serve as majorfactor in making a selection of the retailstore by the shoppers. The retail store musthave a proper policy for refund andreplacement of various goods purchasedby the retail shopper so as to facilitate theshopper while making the purchasetransaction. The retail store should acceptall types of credit cards and debit cards togive the shopper the ease and convenienceof transactions while shopping. The retail

stores need to give flexible payment termsthereby creating a unique image.The data analysis indicated that theinstitutional factors have a focal area ofCustomer Relationship Management[CRM] in a competitive market. The retailstore can occupy a distinct image in theminds of the retail shoppers’ by keeping aclose connect with the shoppers’ bysending birthday wishes through SMS, e-mail etc. The retailers can create top ofthe mind awareness which results intopossibilities of getting more business as theretail shopper is always well informedregarding all activities of the retail store.The retail store can position their storesas popular destinations for shopping alongwith fun and recreation. This will generatecuriosity amongst infrequent visitors to visitand shop in the retail outlet. This willincrease the footfalls in the retail store bydrawing more people to visit the retailstore. The sales personnel should betrained in terms of understanding theshoppers’ information need as well aswilling to share the information to theshoppers’. The sales staff should have theup to date information regarding theproducts availability, the product display,product location, product assortments andwhen the product is expected to arrive incase of stock out situation of the particularproducts. The sales staff should approachthe shoppers’ in the convincing yet friendlymanner so as aid the shopper in hisshopping journey.”The retailers should focus on propertraining and induction of the sales staff so



that they will deliver the best possibleservices to the shoppers ‘as well as buildlong term customer relations which willhelpful in creating loyalty intentionstowards the store amongst the shoppers’.The availability of customised productssuiting the individual requirements of theshoppers’ will create repurchase intentionsamongst shoppers for the store. Theavailability of different assortments in termsof size of the products will enable theshoppers’ to buy the enough quantityaccording to their family consumptionpatterns.”

The retailers by providing wide range ofproducts will not only help the shoppers’to chooses from the wide variety ofalternatives but also to remain competitivein the organised retail market andpositioning themselves differently byattracting large number of shoppers’. Theoverall environment of the outlet will createa feeling of pleasure of shopping in a givencontext which leads to satisfaction fromthe retail store and memorable shoppingexperiences. The appropriate illuminationwill enable the shoppers to identify, verifyand choose various products in differentlocations in the shopping space along withthe illumination the housekeeping andcleanliness of the store will help theshoppers’ to stay long and take their owntime to choose and purchase the products.The positivity in the retail store atmospherewill play a crucial role as it uplifts the spiritof the shoppers’ to shop from the retailstore. The background music in the retailstore helps to the shoppers’ to reduce the

boredom and at the same time making theshopping task interesting. The soft musicthat is played in the store will helpshoppers’ to feel active and upbeat so thatthey can carry out the task of shoppingwith zeal and enthusiasm.”

CONCLUSION:The contribution of retail sector can beseen to a great extent in the emergence ofshopping culture of Gujarat. Retailing inIndia is receiving global appreciation andattention and this emerging market iswitnessing a significant change in its growthand investment pattern. Urban Gujaratishoppers prefer retail stores that give themvalue for money and “self service” optionsin the retail store. This beckons the era of“Serviced Retailing,” where the shopperapproaches the retailer and asks forspecific items, which the retailer fetchesfrom behind the counter. In order to deviseappropriate plans and strategies and takeadvantage of these opportunities of growthto its fullest extent the retailers need to givethe best shopping experience in such kindof malls and organized stores. It isimperative to understand the consumerbehaviour in different formats of organizedretailing will help the different stakeholdersof this industry. Factually thousands offirms are spending millions of rupees tosway consumers in every market placethrough the medium of advertisements,packaging, product features, sales pitchesand store environment. But it is evident thatevery strategy formulated for attractingcustomers may have different implications.Hence this research has made it possible

37

to understand the consumer behaviour interms of shopping orientations at greaterdepth specifically with reference to theselected retail stores in the state ofGujarat.”

In terms of store attributes the shoppersin the selected cities of Vadodara, Surat,Ahmedabad and Rajkot gave moreimportance to the promotional schemes,ambience of the store, range of products,atmosphere of the store and the overallimage of the retail store. These attributesof the retail store should be given dueconsideration by the retailers in the Stateof Gujarat by seamless integration of all ofthem in order to portray a unique image ofthe store.

In this research study, we have found thatthe orientation of the shoppers in the Stateof Gujarat is based largely onentertainment value derived out ofshopping. The data analyses haveindicated that the retail shoppers soughtemotional value more than the functionalvalue of shopping. Although, there is abelief that shopping being considered atask and should be finished as soon aspossible, this orientation is overshadowedby the entertainment value derived by theretail shoppers. The tendency of the retailshoppers to talk about their shoppingexperience has implications for building thereputation of the store. It is imperative thatevery retail shopper visiting a store needsto be handled carefully because whetherthe shoppers buy or not, they woulddiscuss about their visit with others,

showed an inclination to patronize stores,and attached importance to referrals. Apositive opinion would surely help buildstore traffic as well as loyalty to the store.The retail shoppers in the State of Gujarathave a very limited choice of retail formats,an important variable in shapingorientation.”

Due to the lack of a varied experience,the retail shoppers do not seem to expectdistinctive characteristics from differentstores which usually shoppers indeveloped western countries usuallyexpect. From the research study it wasalso clearly identified that the retail storeswere chosen based on the products thatthey handle and hence the productsbecame the primary consideration andsubdued the importance of other storevariables. Retailers in the State of Gujaratneed to take up the task of demonstratingthe value added by a store. The format ofthe store could be the prime driver.

REFERENCES:Assael, H. (1992). Consumer Behaviourand Marketing Action (4th Ed.). Boston,MA: PWS-Kent Publishing Company.Berman, B., and Evans, J.R. (2005).Retail Management-A Strategic Approach(8th Ed.). Pearson Education, Singapore,New Delhi.Birtwistle, Grete, Ian Clarke, and PaulFreathy (1999). Store image in the UKfashion sector: consumer versus retailerperceptions. The International Review ofRetail, Distribution and ConsumerResearch, 9 (1), 1-16.



Bitner, M.J. (1992). Servicescape: theimpact of the physical environmentsurrounds customers and employees.Journal of Marketing, 56, 69- 82.Bittner, Mary Jo, (1982). Services capesin Retail: the impact of physicalsurroundings on customers andemployees. Journal of Marketing, 58(April), 57–71.Brown, S and Reid, R (1955).Psychological Aspects of Shopping: ASupplement to the New Consumer.Chicago Tribune, Chicago TribuneResearch Divisions.Darden, W. R., & Dorsch, M. J. (1990).An action strategy approach to examiningshopping behaviour. Journal of BusinessResearch, 21, 289–308.Deloitte Indian Retail Report (2013).Indian Retail Market Opening MoreDoors.Doyle, Peter and Ian Fenwick (1974/75).How store image affects shopping habitsin grocery chains. Journal of Retailing, 50(4), 39-52.Engel, J.F., Blackwell, R.D., Miniard, P.W.(1995). Consumer Behaviour. TheDryden Press, Fort Worth.Erdem, O., Oumlil, A.B. & Tuncalp, S.(1999). Consumer values and theimportance of store attributes. InternationalJournal of Retailing and DistributionManagement, 27 (4), 137-144.Ernst & Young-Retail Association of IndiaReport, (March 2014). PP. 20-25.Farrell and Beinhocker (2010). Next bigspenders: India middle class. Retrieved

from http://www.mckinsey.com/insights/m g i / i n _ t h e _ n e w s /next_big_spenders_indian_middle_class.Haynes, J. L., Pipkin, A. L., Black, W.C., & Cloud, R. M. (1994). Applicationof a choice sets model to assess patronagedecision styles of high involvementconsumers. Clothing and Textiles ResearchJournal, 12(3), 22-31.Herpen, E.V., and Pieters, R. (2000).Assortment Variety: Attribute-VersusProduct Based. Retrieved from SSRN:http://ssrn.com/abstract=246956.Janse van Noordwyk, H.S. (2002).Perceived importance of retail store imageattributes to the female large-size apparelconsumer in a multicultural society.Unpublished master’s thesis, StellenboschUniversity, Stellenbosch, PP. 25-31.Jarratt, D. (1996). Shopper taxonomy forretail strategy development. TheInternational Review of Retail, Distributionand Consumer Research 6 (2), 196–215.Jum C. Nunnally (1981). PsychometricTheory. Tata McGraw-Hill Publishing Ltd.New Delhi.Luomala Harri T, Paasovaara Rami.Lehtola Katariina. Exploring consumers2health meaning categories: Towards ahealth consumption meaning model.Journal of Consumer Behaviour, 5(3),269–79.Lynch (2005). The Global Indian Shopper.Journal of Retailing, May/June, 15-23.

Michman (1991). The influence of mallenvironment on female fashion shopper’s

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value and behaviour. Journal of FashionMarketing and Management, 12 (4), 446–456.

Moschis, G P (1992). ShoppingOrientations and Consumer Uses ofInformation. Journal of Retailing, Vol. 52(2), 61-70 & 93.

Naresh K. Malhotra (2007). MarketingResearch: An Applied Orientation. NewJersey: Pearson Education, Inc.

Paulins, V.A. & Geistfeld, L.V. (2003). Theeffect of consumer perceptions of storeattributes on apparel store preference.Journal of Fashion Marketing andManagement, 7 (4), 371-385.

Popkowski Leszczyc, Peter T. L., &Timmermans, Harry J. P. (2001).Experimental choice analysis of shoppingstrategies. Journal of Retailing, 77(4),493–509.

Rajagopal, Srivastava (2008). LeisureShopping Behaviour and RecreationalRetailing: A Symbiotic Analysis ofMarketplace Strategy and ConsumerResponse. Journal of Hospitality &Leisure Marketing, 15(2), 5-31.

Retail Report on the Emerging Trends inIndian Retail and Consumer (2011).Technopak, PP. 25.Shim, S. & Kotsiopulos, A. (1993). Atypology of apparel shopping orientationsegments among female consumers.Clothing and Textiles Research Journal, 12(1), 73-85.Sinha, P K; Banerjee, A and Uniyal, D P(2004). Deciding Where to Buy: ChoiceBehaviour of Indian Shoppers. Vikalpa,27 (2) 13-28.Visser, Preez, E.M. & Joung, H-M Miller,N.J., Van Aardt, A.M., (2000). US andSouth African College Age Consumers’Preference for Apparel Store Image.Unpublished manuscript. Department ofTextiles, Clothing and Design, Universityof Nebraska, Nebraska, PP. 65-70.Westbrook, R.A., Black, W.C. (1985).A motivation-based shopper typology.Journal of Retailing, 61 (1), 78–103.Wong, G. K. M. and Yu, L. (2003).Consumers’ perception of store image ofjoint venture shopping centres: First-tierversus second-tier cities in China. Journalof Retailing and Consumer Services, 10,61 – 70.

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FEASIBILITY OF COSTING MODEL VARIANTS: ANINVESTIGATION OF SMALL SCALE INDUSTRY

Swati GuptaFaculty, Deptt. of Accounts &Finance, SOB, UPES,

Dehradun, [email protected]

Rajesh TripathiAsst. Professor (SS), Dept of

Strategic Management, SOB, UPES, Dehradun, [email protected]


ABSTRACTActivity-based costing as a technique has proved an innovative practice in thearea of management accounting. ABC has facilitated companies to classify thetrue costs of not only product and services but also processes. This empoweredmanagement to make sound decisions related to profitability and the effectivenessof their production process. Many scholars have proved the advantage of activity-based costing over traditional costing system; this paper explores the benefits ofABC to the Small & Medium Enterprises (SMEs) population. Also, the challengesfaced by SMEs. The paper demonstrates the framework for ABC implementationwith the support of real-time case of an Indian SME.Key word: Costing model, SSI, Strategy

INTRODUCTION

The development that was orchestratedwith technological advancement, witnessedexperimentation and innovation galore inthe mid-1980s which further lead to thedevelopment of innovative practices in themanagement world. These practicesembrace innovative costing techniquesinitiated through Activity Based Costing.Literary evidences related with innovationin accounting practices, highlights,technological advancement inmanufacturing practices have been aroundthose primary persuasive elementsanswerable for criticizing the performanceof traditional management accounting

techniques (Askaramy & Smith 2004,2003; Benet et al 1994,Bork & Morgan1993, Chenhall 2003, Gosselin 1997,Hartnett & Lowry 1994, Lefebrre &Lefebvre 1993, Spicer 1992).Amid most recent two decades, traditionalcost and management accountingtechniques have been under academicradar for its alleged inability to give itemizedand convenient data and to content theusers of such data (Askaramy 2005 &2003, Baines & Langfield Smith 2003).This paper demonstrates the benefitsbestowed to an Indian SME and its impacton the profitability of the company.


41

LITERATURE REVIEW

Harvard Business Review and numerousdifferent literature and journals havepublished about ABC, execution of ABCand its effect on manufacturing process visa vis organization performance. literaturedating around the 1980s, impulses ABCas a device for exactness of product costutilizing cost pools and cost drivers. Thishelped management to recognizegainfulness of products. They watched themany-sided quality off executing the ABCframework. Mid 1990s forms exhibit basicviewpoint of ABC, where on one hand;practitioners saw with the execution ofABC management could oversee cost andexercises prompting the development ofActivity-Based Management. Then again,commentators were contending theirregularity of ABC with the standards ofnonstop change, add up to qualitymanagement, the absence of customercenter, conflicting with the theory ofconstraints. In the nutshell, ABC wasconfronting the moving impacts.

In justification of the proclamations madeagainst ABC, Kaplan averred that ABC

framework gave profitable monetary datain regards to process change andconsumer loyalty. It was too soon to assessthe execution. Or maybe ABC frameworkproduces data to be incorporated withother data, for example, customerprofitability, process quality, and revenueand process duration.

Notwithstanding the basic editorial, lowattention, and disappointment in ABCframework usage, ABC proceeded on itsexpectation to absorb information. Withits persistent advancement, ABCmaterialness expanded to zones outsidethe extent of cost accounting. Academiciansand practitioners were applying ABCframework in the regions of marketing,logistics, and supply chain. It likewisebegan to apply in spaces like banking,healthcare, energy and differententerprises. ABC points of interest promptthe rise of ABM yet, in addition, ledscholastics and managers to look at howABC could communicate with othermanagement advancements and changeinitiatives, for example, TQM, EVA orTOC.

Industry Title Authors Years

Manufacturing A generalised cost-estimation model for job shop Aderoba, A. 1997

Logistics Application of activity-based costing to a land transportation company: a case study

Baykasoǧ Lu, A.; Kaplanoǧ lu, V.

2008

Postal service Applying activity-based costing model on cost accounting of provider of universal postal services in developing countries

Blagojević , M.; Marković , D.; Kujačić , M.; Dobrodolac, M.

2010

Healthcare Improving hospital cost accounting with activity-based costing

Chan, Y. C. 1993

Police Costing police services: the politicization of accounting

Collier, P. M. 2006

Feasibility of costing model variants: An investigation of small scale industry


Hotel Customer profitability analysis with time-driven activity-based costing: a case study in a hotel

Dalci, I.; Tanis, V.; Kosan, L.

2010

Health care Health-care financial management in a changing environment

Devine, K.; O'clock, P.; Lyons, D.

2000

Health care: Physician

Development of an activity-based costing model to evaluate physician office practice profitability

Dugel, P. U.; Tong, K. B. 2011

Health care: Intensive care

A new method of accurately identifying costs of individual patients in intensive care: the initial results

Edbrooke, D. L. Stevens, V. G.; Hibbert, C. L.;

1997

Library Activity-based costing in user services of an academic library

Ellis-Newman, J. 2003

Library The cost of library services: Activity-based costing in an Australian academic library

Ellis-Newman, J.; Robinson, P.

1998

Healthcare: Mammography

Providing professional mammography services: financial analysis

Enzmann, D. R.; Anglada, P. M.; Haviley, C.; Venta, L. A.

2001

Health care Building an activity-based costing hospital model using quality function deployment and benchmarking

González, M. E.; Quesada, G.; Mack, R.; Urritia, I.

2005

Service Management accounting systems in Finnish service firms

Hussain, M. M.; Gunasekaran, A.; Laitinen, E. K.

1998

Financial institution

The application of activity-based costing in the United Kingdom's largest financial institutions

Innes, J.; Mitchell, F. 1997

Library Time-driven activity-based costing for inter-library services: a case study in a university

Pernot, E.; Roodhooft, F.; Van den Abbeele, A.

2007

Health care Activity-based costs of blood transfusions in surgical patients at four hospitals

Shander, A.; Hofmann, A.; Ozawa, S.; Theusinger, O. M.; Gombotz, H; Spahn, D R

2010

Health care Costs and effects in lumbar spinal fusion: a follow-up study in 136 consecutive patients with chronic low back pain

Soegaard, R.; Christensen, F. B.; Christiansen, T.; Bünger, C.

2007

Logistic Logistic costs case study: an ABC approach Themido, I.; Arantes, A.; Fernandes C;. Guedes A P.

2000

Tourism Activity-based management and traditional costing in tourist enterprises (a hotel implementation model)

Vazakidis, A.; Karagiannis, I.

2011

Health care Application of activity-based costing (ABC) for a Peruvian NGO healthcare provider

Waters, H.; Abdallah, H.; Santillán, D.

2001

Education Adoption of Activity-based costing: A survey of the education sector of Greece

John Sorros; Alkiviadis Karagiorgos; Nikos Mpelesis

2017

Source: Stefano and Filho (2013)

43

BENEFITS Accurate cost information for product costing

Qian & Bin-Arich Charles & Hansa Ozbayrak et al Tayles &Drury Clarke et al Hussain et al Kingsman & De Souza Pirttila & Sandstrom Friedman & Lynne

2008 2008 2004 2001 1999 1998 1997 1996 1995; 1999

Improve performance measurement system

Gunasekaran & Sarhadi Kim et al

1998 1997

Facilitating optimal joint product mix decisions

Tsai et al Kee

2008 2008

Improved cost control Clarke et al Hussain et al Friedman & Lynne

1999 1998 1995; 1999

Cost reduction Bescos et al Andrade et al Gunasekaran & Sarhadi Hussain et al Innes & Mitchell

2001 1999 1998 1998 1995

Accurate allocation of indirect costs Hussain et al 1998 Improved insight into cost causation Clarke et al

Hussain et al Friedman & Lynne

1999 1998 1995; 1999

Identification of activity costs Hussain et al 1998 Improvement of operational efficiency

Kee Tayles & Drury

2008 2001

Improve customer profitability analysis

Bescos et al Tayles & Drury Clarke et al Innes & Mitchell

2001 2001 1999 1995

Accurate cost information for pricing

Kee Bescos et al Tayles & Drury Kocakulah et al Clarke et al Innes & Mitchell

2008 2001 2001 2000 1999 1995

Prepare relevant budgets Bescos et al Tayles & Drury Innes & Mitchell

2001 2001 1995

Modernize cost accounting system Satoghi et al 2006


Parikalpana - KIIT Journal of Management44Innes & Mitchell 1995

Modernize cost accounting system for better depicts costs or to improve their business processes

Satoghi et al Tatsiopoulos & Panayiotou Hussain et al Malmi Spedding & Sun Salafatinos

2006 2000 1998 1999 1999 1996

Supply chain tactical production planning

Comelli et al Whicker et al

2008 2006

Supporting decision making Thyssen et al Seneschal & Tahon

2006 1998

Designing & development of activities

Ben-Arieh & Qiar Tornberg et al Gunasekaran & Sarhadi

2003 2002 1998

Source: Authors’ compilationDIFFICULTIES Reservations from employees or managers regarding the usefulness of the new system

Tayles & Drury Clarke et al Gunasekaran et al Hussain et al Innes & Mitchell

2001 1999 1999 1998 1995

Difficulties in identifying & selecting activities or cost drivers

Clarke et al Hussain et al

1999 1998

Problems in accumulating cost data for new system or lack of resources

Tayles &Drury Clarke et al Hussain et al

2001 1999 1998

Time-consuming Gunasekaran et al 1999 Excessive cost budget Tayles &Drury

Hussain et al 2001 1998

Inadequate computer software Clarke et al 1999

REJECTION Satisfaction with the existing costing system

Bescos et al Innes et al Innes & Mitchell

2001 2000 1995

Implementation associate high cost

Bescos et al 2001

Lack of assessment time Innes & Mitchell 1995 Perceive inadequate accurate cost information

Bescos et al 2001

Lack of management support Innes et al Innes & Mitchell Friedman & Lynne

2000 1995 1995; 1999

Source: Authors’ compilation

Source: Authors’ compilation

45

SMEs which aspires to be a businessvisionary and ready for imaginative flight,accept fortitudes of these factors andfurther more have a penchant as the mainadopters the of new systems in the market.Likewise Shieldsa and Young (1994)contended that firms-which are small-sizedin operations- progressively achieveaggressive edge through creative action byadopting an innovation.

In an exhaustive survey of 60 large andmedium-sized manufacturing companies inIndia, Joshi (2001) thesis that adoptionrate of 20% for ABC, 13% for ABM and7% for activity-based budgeting.Adoption of these contemporarymanagement accounting techniques hasbeen highly contributed by factors like themagnitude of total assets. Owing to higherperceived benefits, practitioners put muchweight on the traditional managementaccounting techniques againstcontemporary techniques.

Through a case study of two branches ofa large Indian private sector bank,Narasimhan & Thampy (2002)promulgated ABC system for establishingservice cost for customers withmultifaceted operations. Scholars haveprofusely talked about the utility of ABCinformation in business process outsourcingand identification of value added and non-value added activities and benchmarkingbranch network restructuring. Ahmad etal (2017) investigated the implementationof ABC in SMEs in Malaysia with aresponse rate of 108, 17% of respondentshave adopted ABC. The indicators like

the degree of intricacies in a manufacturingenvironment and top managementunflinching support stand as testimony tosuccessful implementation. Reasons forrejection include lack of resources,expertise and cost factor.

Bromwich and Bhimani (1989) concurredthat the product cost distortions could beeasily rectified though ABC while. Hubbell(1996) laid stress on forging ABCmanagement systems vis a vis shareholdervalue such as EVA. Advocating acomprehensive relation between ABCimplementation and shareholder value,Kennedy & Affleck Graves (2001)strongly voted for ABC analysis.

Dini and Guerginal (1994) havedistinguished some imperative elementsimpacting the success of small andmedium-sized firm’s (SME’s) system. Theessential achievement factors for the usageof activity-based costing (ABC) in SMEsare deciphered with mettle in makingquality products and services and effectivevigil on the capital intensity and debt levels.Another vital potential lies in owning andtranslating the capacity to actualize asuccessful approach. Accordingly, anyauthoritative process that decreases thecash surges for an SME undertaking isprone to have a positive effect as far as alessening of obligation, and the significantinvestment funds transformed into benefits.Besides, the viable control of income maydecrease long-term capital prerequisitesand lighten the normal SMEs issue ofunder-capitalization.



As identified by Gunasekaran et al (1999),following criteria to justify the application

of ABC in SMEs undertaking as per theircharacteristics:

Source: Gunasekaran et al (1999)

The present period of worldwidecompetition is driving all SMEs towards areestablished sense of duty regardingmagnificence in manufacturing. Theconventional costing frameworks do notgive sufficient non-financial data aboutSMEs. The customary cost frameworksgive little data about what makes adifference to the customers (which is theprimary prerequisite of any world-classorganization). Factors, for example, qualityand administration are out of their domain.They report just financial related data.Non-financial related data, for example,defect rates and throughput rates in everymovement are past the extent of theconventional costing framework. As oflate, SMEs have decreased their relianceon customary costing frameworks bycreating ABC frameworks. At first,

managers observed the ABC approach asa more exact method for computingproduct costs. In any case, ABC hasdeveloped as a hugely helpful manual formanagerial actions that can make aninterpretation of higher benefits (Cooperand Kaplan, 1991). Understanding thesignificance of ABC in SMEs to remainaggressive, an endeavour has been madein this paper to build up a structure for theusage of ABC in SMEs which isdemonstrated with the help of a real-timecase in the following section.

CASE STUDY

The researcher was approached by anIndian SME located in the outskirts ofDelhi. The firm was engaged in theproduction of lenses for the taillights ofautomobiles. They got a contract of

47

manufacturing lenses, L1 and L2, from anautomobile company. The productionprocess of L1 was more complex ascompared to L2 because of its specialfeatures including multicolour moulding.The firm was running at capacity and hadgood competition for L1 lenses. With thecompetition faced by the firm, thecustomer informs them competitive priceby another competitor for L1 lenses at Rs450 as compared to their price of Rs 650.Such competition was not faced by L2lenses which were priced at Rs 1200each.

For such competition, the management hadtwo options in front of them, first, to forgo

the order of L1 lenses to their competitor.Thus, not supplying L1 lenses to thecustomer. Second, reduce the price oflenses by either lowering the margin or byreducing cost. To study such situation, theresearcher tried to understand their costingsystem particularly manufacturingoverhead. They found the company usedto allocate indirect costs using a singleindirect cost rate based on labour hours,38,550 hours. The company managersbudgeted 30,000 hours to manufacture60,000 L1 lenses and 8,550 hours for15,000 L2 lenses. Thus, bringing the costof L1 at Rs 594.16 and L2 at Rs 960; thismade the firm to earn a profit margin of8.6% for L1 and 20% for L2.

It made management to take a tough callon L1 lenses as their design team hasalready evaluated and analyzed L1operations comparing to their competitor,is a competitive product in the market.

The researcher observed, after reviewingfirm’s costing system, the complexity offirm’s costing environment in term of

allocation of overhead towards both theproduct, L1, and L2. They identifiedmiscasting of product costs asmanagement was confident about thedirect material and labour as it was easilytraceable but were concerned about theaccuracy of the system to measureoverhead used by each product. To resolve



the challenge faced by the firm, researcherintroduced an Activity-based system tothe management and convinced them toimplement ABC system for costallocation.

The researcher along with the managementmade a team for identifying the activitiesto break down its current single indirectpool to improved pools of cost related tovarious activities.

Indirect cost pool

Design products and processes

4,000,000 100 parts square feet

Setting up machine 3,500,000 2,000 set up hours Operate machine 6,580,000 12,750 machine hours Administration of processes 800,000 39,550 admin hours Batches of finished lenses for shipment

3,500,000 200 shipments

Distribution 2,500,000 67,500 cubic feet delivered

Direct cost pool Clean and maintenance of machines

3,920,000

It was observed that maintenanceactivity was easily traceable to aparticular product, thus, considered asdirect cost pool and included in thedirect cost. This made the direct cost

as Rs 29,170,000. After computing rateper unit of each cost allocation base,total indirect cost based on activitiesdefined was calculated for eachproduct.

Single Cost Pool system

Activity Cost Pool system (ABC)

Difference

Direct cost items Direct Material + Direct labor

Direct Material + Direct labor + Maintenance

Direct cost 25,250,000 29,170,000 3,920,000 Indirect cost items Single indirect

cost pool Design + Setting up + Operation + Administration + Shipment + Distribution

Indirect cost pool 24,800,000 20,880,000 (3,920,000) Total cost: L1 35,649,611 24,465,920 L2 14,400,386 25,584,080 Cost per unit L1 594.16 407.76 (186.4) L2 960 1705.6 745.6

49

With the help of ABC system, managementwas able to trace more cost as a directcost, created uniform cost pools relatedto different activities and for each costpool, ABC system identified appropriatecost allocation base that has a cause-effectrelationship with costs in the cost pool.Uniformity in cost pool and allocation base,linked to the cost hierarchy, gavemanagement a confidence in the costnumbers for the products and identified L1was overcost by Rs 186.40. Thus,management can match its competitor’sprice and make a profit by considering theorder below competitor’s price.

Also, management was able to identifyhow and where to reduce costs. The targetof cost reduction was foreseen as per thecost per unit of the cost allocation base indistribution activity by decreasingdistribution cost per cubic foot of productdelivered from Rs 60 to Rs 58 by reducingthe rental costs. The motive was to reducethe cost by improving the process withoutcomprising customer service. Thus,management attempted to take out onlythose costs that are non-value added. Itwas also observed when single cost poolallocation based on direct labour hours wasused, gave a wrong signal that the firm waschoosing those designs that most reducedirect labour hours, in fact, there was aweak cause-effect relationship betweendirect labour hours and indirect costs. Theyalso used the system in their budgetingprocess to compare their actuals with abudgeted number for adjusting under-allocated or overallocated indirect costsfor each activity.

CHALLENGES

While implementing the ABC system,researcher faced few challenges includingimplementation of ABC which brings asignificant change in the system. It requiresmanagement to decide on activities and itslevel copiously. It is not only the supportof top management to implement thesystem but also managers’ cooperation isrequired as they have the knowledge aboutactivities and cost drivers. It was essentialto bring them into the system for theirexpertise, proper credibility, coordinationand the required leadership.

CONCLUSION

The case findings suggest that single costpool system is unable to mirror theactivities and assets expired at some stagein the production process with the intentionto distort cost numbers. The ABC systemgives correct cost data with a couple ofactivity cost drivers and casualrelationships among resource consumptionand costs all through manufacturing. Thecost records are the crucial references thathelp SME firms set approach to priceproperly. The studies framework,implementation procedure of ABC systemand research findings of this paper canprovide beneficial reference andcontribution to the SME firms which aregoing through the competitive globalenvironment.

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NUDGE APPLICATIONS IN CONSUMERSOCIALIZATION OF CHILDREN

Vivek MishraAssistant Professor (Marketing), CV Raman Group of Institutions, Bhubaneswar, India,

[email protected]

Biswajit DasProfessor (Marketing), KIIT School of Management, Bhubaneswar, Odisha, India,

[email protected]


ABSTRACTA child’s thought process is sculptured by the factors that are found typically inthe environment; where he/she grows up. Hence the efforts of marketers aredirectionally focused on creating an environment in order to facilitate the consumersocialization of children. Recently nudge strategies have also attracted theattention of researchers and policymakers because of their potential in influencingthe behavior of individuals. By adopting and utilizing review of existing literature,this perusal attempts to analyze the socialization process through facets ofbehavioral economics, to “nudge” children towards a consumer-specific behavior.The study also intends to facilitate marketers in framing the right strategy, whiledeciding on the content of their promotions. It facilitates advertisers to have abetter understanding of a child’s cognitive abilities, the perception ofadvertisements and their progression as consumers.

Keywords: Nudge, Perception, Consumer Socialization, Advertising, Cognition, Attitude

INTRODUCTION

Child customers are heavily influenced bythe various commercial messages that lureand excite through the various mediapromotions. Evidently, children are a vitaltarget segment for advertisers around theworld. They are thought to be capable ofinfluencing their parent’s purchasedecisions. Hence promoting to them isviewed as an exceptionally effectiveapproach in order to create a pool ofprospective customers. In order to make

an alluring picture in the brains of thechildren, advertisers wish to secure alifetime shopping experience in their mindsand heart. They are being focused on childconsumers with enormous proportions anddoses. There are numerous ways thatorganizations promote to children andcontextually television has turned out to bea vital impact in the child’s life.

Research based on advertisements havereliably attempted to distinguish and delivervital issues relating to kids’ demeanors


55Nudge applications in consumer socialization of children

towards television commercials. It iscrucial for marketers to recognize whetherchildren understand the intent ofadvertising. For marketers, the major areaof concern is whether children are able todifferentiate between advertisements andprograms while watching television. Threecategories of specific impact of televisioncommercials have been identified byRossiter (1979), namely: cognitiveeffects, concentrating on child’s potentialto comprehend promotions, attitudinaleffects, focusing on children’s feelingstowards television advertising andbehavioral effects, uniting on the level towhich kids are induced to want andrequest the brands being promoted.

Interest in the area of consumersocialization of children is growing rapidlyamong public policy makers, marketers,consumer educators, and researchers.According to Schiffman and Kanuk(2007), consumer socialization can bedefined as “the process by which childrenacquire the skills, knowledge, attitudes,and experiences necessary to function asconsumers”. The socialization processrevolves around, the socialization agent andthe type of learning actually operating. Anumber of studies have concentrated onhow youngsters form skills related toconsumption. Researchers have alsoadditionally revealed that children primarilyrespond to advertisements emphatically.For their choice of products, they try toutilize the celebrity/ representative in theendorsement, who appears to satisfy aparental part.

The concept of nudging was firstintroduced by American authors RichardH. Thaler and Cass R. Sunstein (2008) intheir book “Nudge: improving decisionsabout health, richness, and happiness”. Ina general sense, nudging refers to adifferent aspect of choosing thearchitecture which alters the behavior ofindividuals in a prognostic manner, withoutexcluding other options (Thaler, Sunstein,2008). The nudge theory aims atimproving, changing and administrating theprocess of heuristic influences on thehuman behavior, which is targeted atchanging people. These days, expandingconsideration is being paid to nudging asa sort of mediation to make little,recognizable or unnoticeable changes in theenvironment to make the alternatives moreideal. As indicated by Thaler and Sunstein“it is conceivable to nudge people into aspecific behaviour by utilization of theheuristics, emotions, habits and biases wehave”. Nudging intercessions intend toencourage buyer’s choice by altering theenvironment in which such choices aremade. In that capacity, nudging alludes to“any aspect of the choice architecture thatadjusts individuals’ conduct in a predictableway without forbidding any options orsignificantly changing their economicincentives” (Marteau, Ogilvie, Roland,Suhrcke, & Kelly, 2011).

Theoretical BackgroundAccording to John (1999), there are threestages of consumer socialization inchildren, classified by their ages. First isthe perceptual stage which is related to


three to seven years of age, wherein kidscan differentiate advertisements from aprogram based on perceptual features,holding positive attitudes towardscommercials and believe that they aretruthful, funny and interesting. The secondstage, known as the analytical stage,related to seven to eleven years of age,kids can differentiate commercials fromprogrammes through a persuasive intent,

holding negative attitudes and understandthat advertisements may contain bias anddeception. In the last stage, the reflectivestage, including kid’s between eleven tosixteen years of age, kids understand thepersuasive intent, tactics, and appealsinvolved in the advertisement. Anillustration of the same has been given inthe below figure (Figure 1).

Perceptual Stage: This stage (ages 3–7)is described by a general introductiontowards the prompt and readily noticeableperceptual components of the market-place. The consumer knowledge ofchildren is portrayed by perceptualelements and refinements, regularlycentered on a single element or feature,and meant by real subtle elements fromtheir own perceptions.

Figure 1 – Stages of Consumer Socialization. Source: John (1999)

Analytical Stage: Huge changes happen,both socially and psychologically, aschildren progress into this stage (ages 7–11). This phase includes the most essentialadvancements as far as consumerinformation and aptitudes are concerned.Cognition takes place at a more dynamiclevel, creating a ground for learningorganizations that incorporate statisticsregarding unique ideas, e.g. advertiser’s

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create an environment where children learnto behave as consumers (John, 1999).According to Moschis and Churchill(1978) taking a closer look at the relativeinfluence of these agents of socializationwill enable policymakers to evaluatecommercial stimuli. Although there hasbeen extensive research on the agents ofconsumer socialization and their relativeimpact, no previous studies haveattempted to apply nudge principles to theprocess of socialization. This conceptualarticle aims at addressing that gap bybuilding a hybrid frameworkencompassing both traditional and nudgestools for the socialization to occur. Thispaper argues that the two agents ofsocialization namely television and siblingsactually aim at shaping the consumer skillsof a child through nudging.

Review of Literature

Children as Potential Consumers

The study by McNeal (1998) featured thatchildren comprise three distinctiveconsumer markets: “primary, influence andfuture”. Significance of children as anessential target market for items like toys,snacks, garments and so forth, has for quitesome time been recognized and tended toby advertisers. Anyway the power andsize of this market has now gone upsignificantly. According to Gram (2007),advertisers of adult product-classes arelikewise escalating endeavors to charmchildren for their part as key influencersand future shoppers. The explorations byHoward and Madrigal (1990) & Gram and

thought processes and also the thought ofpossibilities.

Reflective Stage: This phase (age 11–16yrs.) is portrayed by further improvementin various proportions of reasoning andsocietal advancement. Gaining insights intothe ideas related the marketplace likebranding and pricing turns out to be muchmore mind-boggling as kids cultivateabilities related to the processing ofinformation and socialization.

Objectives of the study

1. To examine and compare the influenceof television commercials and siblingson the child’s product-specificconsumption preferences

2. To correlate the nudge principles ofpriming and framing with the consumersocialization process

3. To help marketers modify theirstrategies in order to create maximumimpact in the children’s consumptionpatterns through an understanding oftheir cognitive abilities.

Research Gap

Over the last few years, research in thearea of behavioral economics and nudginghas attempted to provide insights into howpeople actually make decisions based ontheir judgment of the stimulus they areexposed to. From the consumersocialization perspective, children oftenacquire social skills by modeling parents,peers, siblings and mass media (Bandura,2002). These agents of socialization also

Nudge applications in consumer socialization of children


Therkelsen (2003) reveal that childrenhave a strong impact in family decisionmaking and they may initiate the buy,gather data about available alternatives,propose retail outlets, and have a say inthe final product choice. Bridges andBriesch (2006), suggest that while devisingmarketing strategies focusing on children,it is critical to consider whether the productcategory is one in which children may haveimpact. As per Beatty and Talpade(1994), the extent and nature of children’simpact is dependent on, who uses theproduct and the apparent significance ofthe product to the user.

Consumer SocializationIn the words of Ward & Wackman(1972), consumer socialization can bedefined as “the process by which youngpeople acquire skills, knowledge andattitudes relevant to their functioning in themarket place”. The most commonsocialization agents for children are family,siblings, television, in which parental styleand media communication patterns arepivotal in children’s purchase behavior.According to McNeal and Yeh (2003), theconsumer socialization process of childrenbegins when they start accompanying theirparents to various stores for purchases.Children initially make purchase requestsfor the products they prefer, but as theygrow they start visiting the stores and makepurchases of their choice. A number ofstudies have been carried out in order tounderstand how children developconsumption habits and act as consumers.According to John (1999), children

develop their consumer behavior norms byobserving their parents and siblings, whooften act as role models and potentialsources for consumption related cues. Astudy by Rummel et al. (2000), shows thatchildren react positively to commercialsinvolving a spokesperson, who fulfills therole of a parent.

Agents of Consumer socializationIn his study John (1999), combined thefindings from Piaget’s (1970) theory ofintellectual development and Selman’s(1980) theory of social development andproposed a consumer socialization modelwhere children transform into consumersby passing through a series ofdevelopmental processes. In their researchWard et al. (1977) have put the learningtheory into practice, in order to elaborateon the concept of consumer socializationand assumed that: understanding ofproduct-related information is a primaryelement of children’s learning of themarketplace. According to McLeod andO’Keefe (1972), agents of socializationare those persuasive sources that expressnorms, attitudes, motivations, and behaviorto the learner. Further research conductedby Ward (1974), has provided withsubstantial evidence to prove that brands,products, packaging, parents, peers, massmedia, and retail outlets are considered tobe sources of information and have beenidentified as agents of socialization. Thesources of influence upon the socializationof children are personal and situationalfactors, namely: attitude towards theproduct, brand and store experiences,

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advice in the marketplace and the buyingculture adopted from parents, peers andmass-media (Mascarenhas and Higby,1993).

Television as an Agent of Socialization

In the words of Moschis (1987), ascompared with other agents, mass mediahas received the most attention, as an agentof consumer socialization. Specifically,television among all forms of media playsthe role of a pervasive agent of socializationfor children. According to O’Guinn andShrum (1997), the two primary dimensionsof media, namely – advertising and content,are the key influencers and have maximumimpact on children. A study by Moschisand Churchill (1978), reveals that in thecontext of consumer socialization, higherexposure and interaction with mass medialeads to increased learning of consumerbehavior among children. The researchconducted by McNeal and Ji (1999),revealed that on an average, children areexposed to around four hours of televisionevery day, which is considered to be a vitalsource of information for learning aboutnew products.

Distinguishing Advertisements fromTelevision ProgramsChildren’s ability to distinguish a televisionprogram from a commercial is an area thathas been subject to a lot of disagreement.In the study of children aged between twoto seven years by Rubin (1974) and aperusal of children less than five years ofage by Kunkel and Robert’s (1991), it wasevident that children were incapable of

distinguishing between televisionadvertisements and programmes. On theother hand, a study of children under fiveyears of age by Gaines and Esserman(1981), followed by Petros and Petrella(1982), advocated that children are verymuch capable of distinguishing betweenboth. These contradicting views can besubstantiated by taking into account therelevant age-group under scrutiny and themethod of research adopted, namely;verbal, non-verbal or observational. Intheir respective studies, Preston (2000),Young (1990) and Dorr (1986) argue thatfive years is the defining moment whenchildren cultivate the ability for theadvertisement/programme differentiationbu the help of cues. As examined byGoldberg (1990), in a study of four andfive-year-olds, it was evident that childrenwere able to point out how anadvertisement is different from aprogramme but could not explain why theywere different.

Childs Understanding of AdvertisingIntentAccording to Martin (1997), advertisingintent can be defined with regard to thechild’s comprehension of an advertisementand additionally their understanding of theadvertiser’s primary motive behind thesame. In this regard, children’sunderstanding of the advertising intent isconsidered to be either assistive/informative or persuasive/selling. In thewords of Preston (2000), deliveringproduct related information to the intendedtarget audience is facilitated by the



informative role, whereas the persuasiverole denotes the motive of anadvertisement aiming at the developmentof a purchase intention. Blosser andRoberts (1985) are of the view that,advertising intent in a broader scopeincludes – information, teaching,entertainment, selling, and persuasion.Further study by Lawlor and Prothero(2000), suggests that the schema of theadvertiser can be represented by twoprimary intentions, namely; persuasive andinformational.

Effects of Advertising on Children

As the essential goal of promoting is toimpact the consumer perceptions about abrand (Romaniuk and Nicholls, 2006)which are ultimately related to the finalpurchase (Nedungadi 1990; Keller, 2003;Tipps, Berger, and Weinberg 2006), it isnormal that many studies in advertisinghave attempted to think of more effectiveapproaches to persuade buyers(Romaniuk and Nicholls, 2006). As of late,discourses of advertising impacts from thepoint of view of purchasers have gottenmore consideration (Gould and Gupta,2006). Research concentrating on theconceivable negative effect of advertisingon particular groups of consumers, forexample, children, has expanded(Livingstone and Helsper, 2006). Notquite the same as the discourses abouthow advertising can persuade targetgroups all the more proficiently, the realreasons for the examinations managingconceivable negative impacts of advertising

talk about stricter directions on the contentof commercials (Henderson et. al., 2004).

Siblings as Agents of Socialization

Siblings are considered to have a profoundimpact on the emotional, cognitive andsocial development of children (Dunn,2002; Karos et al., 2007; Pike et al.,2005), and for some people, the siblingrelationship is their most perseveringassociation. Relationship among siblings isa crucial aspect of children’s socialuniverses and is implanted in a progressionof pro-social and negative interactions(Karos et al., 2007), with it portrayed asa fluctuating relationship (Edwards et al.,2005; Punch, 2008) that regularly includesboth co-operation and strife (Punch,2008). In accordance with fundamentalways to deal with family life, the nature ofparent-child relationship can also affectsibling relations (Minuchin, 1988; Pike etal., 2005), with parental differentialtreatment (PDT) of kids offering to ascendto sibling contention (Suitor et al., 2008;Tucker et al., 2005).

Nudging and its effectiveness

The effectiveness of nudging in altering thebehavior and value structure of individualsis considered to be of high practicalsignificance. The critics of nudging seekan explanation to whether designing choicearchitecture facilitates sustainable changesin the behavior of individuals (Goodwin,2012). They claim that considerablebehavioral effect prompting long-termsustainable practices requires consumer’sacknowledgment of the criticalness to

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change ways of life and consequentbehavioral modifications. Additionally, intheir effort to increase revenues, marketerscan neutralize uninformed behavior whichas a resultant of nudges. Therefore, thesecontradicting forces could prompt aframework in which huge investments inthe form of public finance can be utilizedto nudge behaviors. These nudges canbenefit the individuals and the society atlarge, simultaneously being counteractedby marketing strategies (Wilkinson, 2013).

Nudging as a behavioral mediationNudging is derived from conceptsdeveloped in the field of behavioraleconomics, which is the science ofbehavior choice or “choice architecture”(Desai 2011; Hargreaves Heap 2013).Nudges have been also widely applied inconsumer and competition policies,especially when it comes to providingdefault options in situations with complexinformation or simplifying complexinformation for users. In the words ofThaler and Sunstein (2008), there existsan automatic mental system, which theyrefer to as “mindless choosing”. The nudgetactics are aimed at influencing this aspectof “mindless choosing”. They are of theview that consumers know about thedecisions they make and the results in spiteof the fact that the choices may not be totheir best advantage. Nudging can beviewed as the ‘libertarian paternalism’,development, where “libertarian” alludesto an opportunity of a decision. Whereas,“paternalism”, suggests a methodologywhere it is authentic to impact the settings

to build one specific decision (Bonell,McKee, Fletcher, Wilkinson, and Haines,2011; Thaler and Sunstein, 2008).

Nudging and Consumer decisionmaking

The varied choices made by consumersmake are grounded on direct gratificationand receiving an immediate favorableoutcome which is widely preferred (Ainslie,2001). Individuals tend to favor delightsof a shorter duration and get over the long-term impact of a buying decision. Incontrast, they will agree to take a phaseof non-pleasantness if the culmination isworthy (Kahneman, 2012). Individualpractices are primarily decisions that aretaken in a subconscious way and theyrepresent non-reflective repetitive behavior(Verplanken & Wood, 2006). In the wordsof Wood & Neal, (2007) people acquirehabits by those series of actions which havebeen repeated earlier through gratifyingoutcomes and the environment acts as atrigger to produce that behavior. Accordingto (Aarts & Dijksterhuis, (2000), as afunctional tool habits are aimed atobtaining specific goals and they tend tostrengthen over time through repetitivebehavior.

Developing Conceptual Frameworksutilizing Framing and PrimingFraming and Consumer SocializationNudging expands on the knowledge thatavailability of information to individualmatters but also the way it is presented isequally crucial. Simplifying information anda proper understanding of its context of



the presentation, often leads a change inan individual’s choice of products.According to John et al (2013), nudgingis all about providing information andmeaningful gestures in order to enableindividuals to make positive choices forthemselves. The framing of an issue is alsoadditionally imperative, it can be explainedas the phrasing of information in a mannerthat essentially facilitates and initiatescertain values and attitudes of people.Framing basically includes choice andprominence. It involves choosing someaspects of a perceived reality and makingthem more noteworthy in the context ofcommunication. As explored by Entman(1993), framing facilitates the promotionand definition of specific issues, causalunderstanding, moral assessment and

treatment suggestions for the object beingportrayed. A conceptual frameworkportraying the concept of framing is givenas below (Figure 2).

As depicted in the above model (Figure2) primarily comprises of four sections,namely- antecedents, framing, mentaloutcomes and behavioural outcomes.Section one of the model represents thoseelements that pre-exist the framing process.The second part of the framework includesthe typical roles played by siblings in thepassing on and framing the information fortheir younger brother/sister. They play therole of simplifying the information throughregular interactions, further facilitated bysharing of products. The penultimatesegment portrays the child’s understanding

Figure 2: A Conceptual Model of Sibling Relationship, Framing andConsumer Socialization of Children.

Source: Adapted from Daniel B. Wackman & Scott Ward (1976) and Danny N. Bellenger &George P. Moschis (1982).

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of the information thereby leading tolearning. The child pays attention to theinformation received based on his/her levelof cognitive development. Then thesequence of the structuring of informationdirectionally leads to brand perception.The final phase of the figure denotes thebehavioural outcomes of framing in theform of purchase requests by the child.

Consumer Socialization throughPriming

Having already discussed on the children’sattention and thought to the behavior oftheir siblings, this framework focuses onthe power of priming. Research in socialsciences has uncovered that individualscan be primed into specific behavior byoffering straightforward and evidently

irrelevant cues (Thaler and Sunstein,2008). William J. Cusick (2009), in hisbook, elaborates on the concept ofpriming. According to him, primingdescribes a phenomenon wherein a personis subconsciously reacting to a stimulus thatis inherently positive/negative. Priming heremight be seen as an idea that portrays howexternal forces influence our emotions,decision and action in a random manner.In the words of David Halpern (2015),priming sometimes is with the intent, suchas through the thousands ofadvertisements we are exposed to.

A conceptual model on priming is depictedbelow (Figure 3). The frameworkillustrates the four core phases of stimuli,priming, processing of information and the


Figure 3: Television Commercials, Priming, and Consumer Socialization.

Source: Adapted from Scott Ward, Donna M. Klees and Thomas S. Robertson (1987).


outcomes. It is an elaboration of the S-O-R (Stimuli Organism Response) model ofconsumer behavior. The initial phase of themodel represents the various aspects ofthe stimuli (television advertisements),which include elements like advertisingcontent, the intent of the advertiser, theappeal created through advertisementsand the degree of the child’s exposure tothe medium, often regulated by the parents.A crucial element of this phase being, theability of the child to differentiate betweentelevision programs and adverts.

The second section of the model highlightsthe priming concept, which includes thefollowing celebrity endorser/commercialcontent elements: Direct/Indirectinstructions – where the child viewer istold what to do and what not to. TheModeling element approaches the childviewer by depicting good things happeningto children because of something they do.Overvoice, a cultural way of addingauthority to the commercial message,normally by using a male voice, ultimatelyappealing to the anxieties of the child. Thelast two sections of the model include theInformation Processing phase and theOutcomes of the same.

Limitations and Scope for FutureResearch

This conceptual article is not devoid oflimitations. The perusal and the conceptualmodels have been developed using reviewof existing literature only, research in futurecan aim at validating the same throughempirical evidence. This study has taken

into consideration only two agents ofsocialization, namely – television andsiblings. Future explorations can make anexhaustive comparison of all the otherforms of socialization agents in children.The concept of nudging incorporates manyother strategies, this paper has utilized onlytwo of them i.e. priming and framing. Theother nudges can also be delved into inthe future.

Implications

This study raises interesting implications asto how companies would want to designthe child consumers experience in orderto encourage purchase. If companiescould really understand the impact ofpriming and framing on their childcustomers, it would encourageintrospection regarding their overallcustomer experience. This paper focuseson the lessons that can be drawn frombehavioral economics and the nudgeapproach in overcoming global marketingchallenges which shall help global practicesin marketing.

Conclusion and Discussions

This study was designed to have a deeperunderstanding of the role of televisionadvertisements and the siblings’psychology, leading to the shaping ofchildren psyche as consumers. Designinga schematic plan to nudge the childcustomer and effectively impacting theirconsumption preferences requires athorough understanding of their cognitiveabilities. The conceptual modelsdeveloped in the study shall facilitate a

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better understanding of nudging andapplication of the same in the field of globalmarketing practices. The effect of parentaldifferential treatment, coupled with thenature of sibling realtionships, can act aspotential cues for marketers in creatingbetter nudges in the form of their marketingcommunications.

The conceptual foundations developed inthis paper can be of specific significancein the context of current scholarly debateson the relevance of nudging. Apart fromthat, this study revealed a lackingacquaintance with the idea of nudging andperhaps inadequate significant impressionsof these strategies on child consumers.Considering the possible theoreticalimplications and relevance of this article inimbibing nudge aspects in the area ofconsumer behavior, it should not beconsidered as a ground for deciding foror against the implementation of nudges.Rather, this paper argues that the cognitiveand behavioral aspects of the child shouldbe considered as a basis for strategy designand implementation. At the same time, theethical need of involving consumers intothe judging of nudge elements requiresenhanced information levels and consumerinvolvement. For the meantime, no directrationalization can be identified to rejectnudging, yet this conclusion cannot bedrawn across all purviews of behavior.

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FACTORS DETERMINING BUYER BEHAVIOUR IN SHOPPINGGOODS WITH REFERENCE TO BRANDED PRODUCTS

Mamatanjali ParidaLecturer, Disha College of Management and Technology, Berhampur, Odisha

[email protected]


ABSTRCTThe consumers market now, turning into more complex and competitive in postLPG era. As customer is the focal point for any marketer, studying their behaviourbecoming vital. Now-a-days consumers are very much conscious about their choicesand preferences and attracted towards those products which can give themmaximum value with social recognition So, it is obvious that the consumerspurchasing decision will be influenced by a lot of factors like buyers personalfactors, cultural factors, psychological differences, product related factors etc.Today consumers have handful of alternatives to chose among. So it is becomingdifficult for marketers to understand consumers’ black box and formulate strategyaccording to that. This study focuses on investigating the awareness of consumerson various brands and to examine their behaviour in market. This is an empiricalstudy aim to analyse the consumer behaviour in the state capital of Odisha. Primarydata collected from 100 samples through a structured questionnaire. Hypothesesare formulated and tested applying various statistical tests. The result derived bytesting of hypothesis is very useful which says that the buyers are basically affectedby their demographic characteristics like age, gender, family structure, income,occupation and other brand related benefits.Key Words: competitive, black box, strategy, choices and preferences

INTRODUCTION

Indian market today categorized as everincreasing market for consumption ofgoods and services as essential which areconsidered as luxury until yesterday. Thedemand is growing at high pace for everykind of product, whether it is FMCG orfashionable. It is not only people who arechanging but all factors related todemographics and psychographicscontributing a lot towards consumptiontrend. Today, we can find co-existence ofat least three generations in a single family

and shifts in lifestyle. For understandingconsumer behaviour, mind of all consumersto be studied differently on the basis theirage group, income group etc. for example:a marketer should not treat two individualsin same way where one belongs to postindependence era and another born afterliberalization. The marketer needs to doone thing i.e. he has to diagnose theconsumers mind to study how and whyconsumers having all experience with theproductsandservices. He needs to study



it from every aspect. Studying only fewaspects may not be helpful for building acomplete strategy.

The buyer is remained as an enigmaalthough marketers focusing onunderstanding buyer behaviour. Themarketers provide stimuli but he is notcertain about the buyer’s response. Thisis why the buyer’s mind is termed as a blackbox. Consumers decision influenced byhundred of reasons and today, consumersare mostly influenced by technologicaladvancements, media i.e. news media aswell as social media and consumer choicesalso affected by acute competition amongvarious products and services. So, in thiscompetitive & complex market situation,it is very difficult and sometimes impossibleto predict their behavior.

It is even more difficult to understand buyerbehaviour towards branded products inconsumer durable segment as there are ahandful of national and multinational brandsare available. Most of the urban customersare aware about brands where ruralmarket is in emerging trend. Today,Information technology helping consumersextensively in comparing Prices of brandsand their features. In India consumers aregreatly influenced by the suggestions andreviews of their near and dear ones fortaking purchasing decision.. So, it isimportant to examine consumersperception towards a particular brand orproduct. Moreover, the choice anddecision of consumers about a specificbrand over the time is determined on thebasis of the benefits sought i.e. quality,

guarantee and price especially frombranded products. And it becomes theimportant factor when it comes to thedurable and shopping goods.

Literature Review

A number of research studies on this areahas been reviewed which have been carriedout for examining various factors andstimuli affecting the consumers. Some ofthe important research studies arepresented here.

Miss Rupali Khanna (2015) has made astudy entitled “Customer Perceptiontowards Brands: A study on Patanjali”. Thestudy was conducted with objectives tostudy the perception of customers aboutthe brand ‘Patanjali’, to find out theperceived benefit in the minds of customersat the time of buying the particular brandand to analyse the satisfaction level ofcustomers and past purchasing experience.The study conducted by examining 100samples in the area of Punjab throughquestionnaire method. The study revealedthat out of total sample 2/3rd are in betweenthe age group of 20-40 and female usersare more interested to buy ‘Patanjali’products than male users. There are variousfactors like Income, Price, advertisementetc. are affecting the brand choice. Incomehas a negative but insignificant effect onthe purchase decision where as it ispositively correlated with the quality.Quality of the product trusted not byadvertising but after using only.

Syed Tabrez Hassan, Bilal H Hurrah andAmit Lanja (2014) were made a study

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entitled “A Study of Customer Perceptionof Youth towards Branded FashionApparels in Jalandhar City”. The mainobjective was to study the youth ofJalandhar city and find out their brandpreferences for apparels. Another aim wasidentifying the factors determining thebuying behaviour of that particular group.A sample of 200 respondents was selectedby random sampling technique. The surveyreveals that most of the people choose towear branded apparels just for maintainingstatus and they mainly influenced by trendof fashion, price offers, suggestions offriends and family. For this gropu ofcustomers price is not a big deal as theyare determined to wear branded clothesand believe costly products means brandsproviding high quality products. But, in thiscase people change their brandpreferences time to time and not loyal to aparticular brand.

Manish Kumar Rai & Dr.R.Gopal studied‘The Consumer buying behavior onbranded ethnic apparel’ by collecting datafrom 100 respondents from Navi Mumbai.The main objectives of the study were toidentify the target consumers having highvalue towards ethnic wear and analyse towhat extent they are affected by theirdemographic characteristics and economiccondition. They found that the buyingbehavior of consumers has no associationwith gender, income level and region towhich they belong. But the occupation andage affect the buying of ethnic apparel.According to the findings of the study theperception and preference of customers

for ethnic apparel do not vary on the basisof income level but on the basis ofoccupation. Professionals and job holdersliking it more while students are lessinterested.

Research Objectives

The study has been conducted to identifythe customers awareness, preferences andattitudes towards buying of shoppinggoods in the capital city of Odisha. Themain objectives are:

· To examine consumer awareness aboutvarious brands in shopping goods

· To identify various factors influencingbuyer behaviour

· To study the buyer behaviour on thebasis of their demographic differences

Research MethodologyData have been collected both fromprimary and secondary sources. Aresearch survey was conducted for primarydata in the capital city Bhubaneswar,Odisha. The survey based on primary datawhich was obtained through a structuredquestionnaire. The questionnaire wasadministered to the consumers purchasingshopping goods of various brands to thesampling unit classified on the basis of age,gender, income, occupation, educationalqualification and monthly income. Stratifiedsimple random sampling techniques areused in the study comprising 100 samples.Various statistical tools and t test analysisare used to study the significance ofdemographic factors of age, income,occupation and status towards the

Factors determiniing buyer behavious in shopping goods with reference...


perception of respondent on shoppinggoods.

Hypothesis

For studying buyer behaviour somehypotheses are formulated and tested.Those hypotheses are as below:

H0: There is no difference between thegender of the respondents and repurchaseof the brand which the respondents areusing

H0 – There is no significant differencebetween the family structure andrepurchase of the brand which therespondents are using.

H0: There is no significant differencebetween male and female to prefer buyingof branded goods in terms of guaranteedafter sales services

H0: There is no significant differencebetween Nuclear and Joint family in buyingthe branded goods in terms of guaranteedafter sales services

Concept of Buyer Behaviour

The field of consumer behavior is definitelynot a narrow concept. It covers a lot ofground to be studied. Consumer behavioris the process and activities people engagein at the time of searching, selecting,purchasing and using for the fulfillment oftheir wants and desires. Buyer behavior isdefined as “all psychological, social andphysical behavior of potential customersas they become aware of, evaluate,purchase, consume and tell others aboutproducts and services. According to

marketing theories a customer goesthrough various stages or has a life cyclefor a particular product or firm.• First stage is that time period when the

buyer has not yet bought a firmsproduct brand. At this stage customerseek awareness and marketer try toinduce purchase. These customers arecalled prospects means potentialcustomer in target market.

• Once the customer decides topurchase, he enters into second stageand try out the product. After using forthe first time, buyer evaluates the firm,product and whole total experience hegot. Here marketer needs to promoteto retain the customer not affecting thebrand image.

• Some customers who are satisfiedenter into third stage and make a repeatpurchase. But they cannot be called asloyal customers because they may shiftbrand by getting superior service fromcompetitor firms.

• Those customers do not shift to otherbrands become core customers andthey are very precious to the firms.Generally there are about 2-3% ofthese type customers exist in mostcompanies.

• There are some customers who haverejected the firm’s offerings calleddefectors. The cause of such defectionis to be analysed and corrective stepsshould be taken.

Determinants of Buyer BehaviourPeople choose a product to buy after goingthrough a process of identifying needs and

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preferences, selecting out of variousalternatives and analyzing the utility incomparison to price. Customers can bevarious types who purchase different typesof goods for them like: Shopping goods,consumable goods, specialty goods orindustrial goods. A person’s buyingdecision related to what should he buy,how should he buy, when and from whereshould he buy etc. backed by many factorslike his perception, self concept, his socialand cultural environment, peer groups, hisage and personality, his family and manyother. Further the selection and purchaseof any branded product by a customerprobably influenced by several factorsincluding his perception towards thatparticular brand, all total information andexperience he has with the brand and hisattitude which determines the repeat buyingbehaviour. Some of the factors arediscussed below:

Cultural background of a person can betreated as the basic factor whichdetermines a buyer’s wants andpreferences. Generally different set ofvalues of different cultures, their traditions,beliefs influence the customers’preferences and behaviours. Some of thebehaviours have been learned byindividuals throughout the life. FurtherPeople belong to different culture, sub-culture and social class have differentcharacteristics which lead to distinctproduct and brand preferences. Cultureinfluences communication and language,dress and appearance, food and eatinghabits, work habits and practices ofcustomers.

In addition to cultural factors, aconsumer’s society has the broadestinfluence on consumer’s choice. Thosesocietal factors constitute all the peoplearound him who are called as referencegroups include his family, friends, relatives,neighbors, colleagues and his class in thesociety. These people have a direct as wellas indirect effect on consumers thinkingand decision and ultimately affect thebuying behaviour. This factor can havemore influence because of regularinteraction and meeting.The buyer’s decision is also determinedby his personal characteristics. Theseinclude the particular buyer’s age, gender,stage in the life cycle i.e. childhood, youthstage and old age, his occupation, financialbackground, lifestyle. In this point of view,we have child market, youth market, adultmarket etc. In spite of these factorsphysiological differences between men andwomen create different demand of healthand beauty products and their needsbacked by their distinct roles played bythem. Instead of gender differences, agehas the great influence of purchasedecision. People choose clothes, furnitureand recreation etc. according to theirstages in the life cycle. Moreover, thepersonality difference affects the buyingdecision between persons.There are four major psychological factorsthat affect the purchasing behaviour ofconsumers i.e. motivation, perception,attitudes and beliefs. First thing is the levelof motivation. Generally different needs ofdifferent consumers and the nature of



requirement motivated towards shoppinga selected product with specific features.However there are some perceptualprocesses. Moreover the marketers canalso change the beliefs and attitudes ofcustomers with special campaigns.Buyer not only behaves differentlyaccording to product differences anddeterminants but sometimes the situationdiffers. In the absence of some factors,differentiation in two buying situationoccurs. Those are: (a) awareness aboutcompeting brands in a product group (b)customer has a decision criteria (c)customer is able to evaluate and decideon his choice.Analysis and InterpretationIn this study, an attempt has been made tostudy the consumer characteristics such as

demographics and behavioural variablesin the purchase of shopping goods by usingthe data collected from the respondentsthrough administrating the questionnaire.The demographical characteristics of thesample respondents and behaviouralvariables in the purchase of shoppinggoods have been analysed by usingpopular statistical tools and statistical testslike Chi square Test and t test for testingof the hypothesis.

Analysis of Profile of the respondents:The profile of the respondents includes allthe demographic details like gender, age,income, occupation, family structure etc.In this study Respondentsare studied onthe basis of gender, income and familystructure.

Frequency and percentage of respondents w.r.t gender

TABLE-1

Frequency Percent Valid Percent Cumulative Percent

Valid Male 67 67.0 67.0 67.0 Female 33 33.0 33.0 100.0 Total 100 100.0 100.0

Source: self compiledOut of 100 respondents 67 % of male respondents, 33% of female respondents haveparticipated in this study.

Frequency and percentage of respondents w.r.t family structureTABLE – 2

Frequency Percent Valid Percent Cumulative Percent

Valid Nuclear 66 66.0 66.0 66.0 Joint 34 34.0 34.0 100.0 Total 100 100.0 100.0

Source: self compiled

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The above table show the Type of Familydistribution. It shows that 66% of

respondents were Nuclear whereas 34%of respondents were from Joint family.

Frequency and percentage of respondents w.r.t Income

TABLE- 3 Frequency Percent Valid Percent Cumulative Percent Valid Up to 10000 14 14.0 14.0 14.0

10000 to 50000 59 59.0 59.0 73.0 50000 to 75000 15 15.0 15.0 88.0 75000 to 100000 6 6.0 6.0 94.0 above 100000 6 6.0 6.0 100.0 Total 100 100.0 100.0

Source: selfcompiled

Fig 2 Graphical Presentation of respondents w.r.t Income

The table no.3 shows the income distributionsof respondents, 14% respondents were Rs.Upto-10,000, 59% respondents wereRs.10,000-50,000 and 15% respondents

were Rs. 50,000-75,000 income group.The maximum participated in the researchstudy from the income group were betweenRs. 10,000 to 50,000.


Frequency and percentage of respondents Aware about various brands

TABLE – 4 Frequency Percent Valid Percent Cumulative Percent Valid Yes 93 93.0 93.0 93.0

No 7 7.0 7.0 100.0 Total 100 100.0 100.0

Source: self compiled


The table 4 shows the distribution of therespondents about their awareness on thedifferent brands of shopping goods. Itshows that 93% of respondents wereknown about the different brands availablein the market whereas only 7% ofrespondents were unknown about it.

Purchase behaviour of therespondents: This analysis depicts thebuyer behaviour at the market place i.e theirfrequency of shopping, their choice ofbrands, the benefits they aspire from anybrand and the how is the behaviour differsgender to gender, one income group toanother and one family structure to another.

TABLE – 5

Frequency Percent Valid Percent

Cumulative Percent

Valid Once 10 10.0 10.0 10.0 Twice 13 13.0 13.0 23.0 three times 9 9.0 9.0 32.0 four times 10 10.0 10.0 42.0 more than four times 58 58.0 58.0 100.0 Total 100 100.0 100.0

Frequency of Shopping made by respondents

The table no 5 presents the frequency ofshopping. It is revealed that maximumparticipated in the research study had

visited more than four times for shoppingwhich is around 68 percent of the totalrespondents of the study.

Factors given emphasis for the purchase of a shopping product

TABLE – 6 Price as

factor Quality as factor

Fashion as factor

Influence of family

Advertisement

Technology as factor

Promotion schemes

Yes 57 75 18 12 35 16 09 No 43 25 82 88 65 84 91

The above table presents the distributionof various factors that was given emphasisat the time of purchasing shopping goods.The respondents were given emphasis to

price and quality and were not givenemphasis to technology, influence of family,advertisement, sales promotion schemesand fashion.

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H0: There is no difference between thegender of the respondents and repurchase

of the brand which the respondents areusing-

TABLE - 7: STATISTICAL COMPARISON between Male and Female on repurchase of the brand which the respondents are using

GENDER N Mean Std. Deviation T Df Sig.

(2-tailed) Male 66 1.3939 .49237 -6.946 99 .000

Female 34 1.2059 .41043 Source: Self Compiled

According to the table, which indicates thatMean & S.D of Male Vs Female onrepurchase of the brand which therespondents are using i.e. Male group are1.39±0.49, Female group are 1.20±0.41.As per the table the p value is less thansignificant level at .05. Hence nullhypothesis is rejected. It means alternative

hypothesis is accepted. There is somedifference between male and female onrepurchasing the brands they are using.

H0 – There is no significant differencebetween the family structure andrepurchase of the brand which therespondents are using.

TABLE NO – 8: STATISTICAL COMPARISON between Nuclear and Joint family on repurchase of the brand which the respondents are using

Type of family

N

Mean

Std. Deviation T Df Sig. (2-tailed)

Nuclear 66 1.3333 .47502 -6.865 99 .000 Joint 34 1.3824 .49327

Source: Self CompiledAccording to table No.8 , which indicatesthat Mean & S.D of Nuclear Vs Jointfamily on repurchase of the brand whichthe respondents are using i.e. Nucleargroup are 1.33±0.47, Joint group are1.38±0.49. As per the table the p valuewas statistically significant at .05 level ofconfidence. Hence null hypothesis is

rejected. It reveals that alternativehypothesis is accepted. There are somedifference exist between nuclear and jointfamily for the repurchase decision.H0: There is no significant differencebetween male and female to prefer buyingof branded goods in terms of guaranteedafter sales services

TABLE –9 STATISTICAL COMPARISON between Male and Female on buying branded goods in terms of guaranteed after sales services

GENDER N Mean Std. Deviation t-test value Male 67 3.3284 1.15978 638 Female 33 3.4848 1.14895



According to table No.9 which indicatesthat Mean & S.D of Male vs Female onthe brand that is preferred to buy in termsof guaranteed after sales services i.e. Malegroup are 3.32±1.15, Female group are3.48±1.15. As per the table the t-test werestatistically insignificant as the obtainedvalue (1.03) is less than the tabulated

value (1.97) required for t-test to besignificant at .05 level of confidence. Hencenull hypothesis is accepted.

H0: There is no significant differencebetween Nuclear and Joint family in buyingthe branded goods in terms of guaranteedafter sales services

TABLE – 10 STATISTICAL COMPARISON between Nuclear and Joint family on buying in terms of guaranteed after sales services

Type of family N Mean Std. Deviation T-test value Nuclear 35 3.5714 1.14496 1.22 Joint 65 3.2769 1.15255

Source: Self Compiled

According to the above table, whichindicates that Mean & S.D of Nuclear VsJoint family on the brand that is preferredto buy in terms of guaranteed after salesservices i.e. nuclear group are 3.57±1.14,Joint group are 3.27±1.15. As per thetable the t-test were statistically insignificantas the obtained value (1.22) is less thanthe tabulated value (1.97) required for t-test to be significant at .05 level ofconfidence. Hence null hypothesis isaccepted.

Findings and Conclusion

The present study is an empirical study onconsumer buying behaviour regardingshopping goods. The customers’ decisionis influenced by personal factors as wellas environmental factors. In this study thebehaviour of consumers is analysedaccording to their demographiccharacteristics. The hypothesis are testedand the result can be concluded that

decision towards repeat purchasing of abrand differs among male and femalewhereas there is no difference in perceptionexist towards guaranteed after salesservices. The behaviour of buyers on thebasis of family structure also been studiedand the result showing that there is somedifference exist among nuclear and jointfamily in repurchasing a product. The nullhypothesis formed for studying theperception on after sales services holdstrue and there is no difference betweennuclear and joint family in taking decisionconsidering the after sales servicesprovided by various brands. The brandingis not the only influencer on the buyingdecision of the customers. There are manyother determinants of buyer behaviour.Buyer selects a product through a process.He searches for various alternativeproducts which can fulfill his need, and thenhe compares them and chooses the bestproduct for him. Therefore, proper

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formulation of marketing strategy requiresan overall study and understanding ofpsychological factors that influencesbehavioral pattern of consumers. Thus, themarketer who understands consumersmind and make strategy for fulfilling theirneed will definitely have advantage overother competitors.

ReferencesBhuvan Lamba, Influence of brands onconsumer’s buying behaviour, NationalMonthly Refered Journal of Research inCommerce & Management, VolumeNo.2,Issue No.11, ISSN/2277-1166David L. Loudon, Albert J. Della Bitta,Consumer Behaviour- Concepts &Application, Tata MC Graw HillPublishing company Ltd.Dr. Manish Kumar Srivastava & Dr. A.K. Tiwari(2014), A Study Of ConsumerBehaviour With Reference To BrandLay’s, Pacific Business ReviewInternational, volume6,ISSUE 11Dr. Seema Laddha(2015), RuralConsumer Buying Behaviour And BrandAwareness of Durable Products, NBR E-JOURNAL, Volume1, Issue 1, ISSN/2455-0264.Khor Eng Tatt(2010), Factors InfluencingConsumer Buying Behaviour of LuxuryBranded Goods, University Sains MalayasiaM. Vijaya Bhaskar & N. Sundaram(2014), Indian Consumer PurchasingBehaviour Towards Branded ProcessedFood, Asian Social Science, Vol.10,No.11, ISSN 1911-2017, E-ISSN 1911-2025

Manish Ku. Rai, Dr. R. Gopal, Study ofConsumer Buying Behaviour on Brandedethnic Apparel, IOSR Journal of BusinessM a n a g e m e n t ( I O S R - J B M ) , e -ISSN:2278-487X,P-ISSN:2319-7668.Pathak S.V. and Aditya P. Tripathi (2009),Consumer Shopping Behaviour AmongModern Retail Formats: A Study Of Delhi& NCR, Indian Journal OfMarketing,39(2), pp.312Philip Kotler, Marketing Management,Himalaya Publishing House, 13th EditionPinki Rani(2014), Factors InfluencingConsumer Behaviour,Int.J.Curr.Res.Aca.Rev.2014;2(9):52-61Reetika Gupta, Dr. V. K. Jain(2014), AStudy Of Consumer Behaviour TowardsBranded Food Products In Urban AndRural Areas In India, InternationalJournal Of Management And BusinessStudies, vol-4, Issue-2, e-ISSN:2230-9519, p-ISSN:2231-2463Ritu Narang(2006), A Study On BrandedMen Wear, Indian Journal OfMarketing, 36(11)pp.39Syed Ahamed. S & Dr. A. Ravi(2016), AStudy On Consumer Behaviour TowardsBranded Garments Among MaleShoppers, International Journal OfBusiness And Management Invention,e-ISSN:2319-8028, p-ISSN:2319-801X,Volume 5, Issue 5• ht tp: / /www.ibef.org/ industry/

indianconsumermarket aspx 1• www.moneycontrol.com• www.marketing91.com• www.study.com

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INTRODUCTION

Among the many objectives of anorganisation, recruiting and selecting theright people to join and contribute towardsachieving success in the ever competitivemarket, is one of the most important ones.Organisations create awareness aboutvacancies for the job seekers through

ROLE OF INFORMATION- SOURCE AND APPLICANTS’DISCONFIRMATION SENSITIVITY IN JOB

APPLICATION DECISIONS

Urvashi ThakurXLRI Campus, Jamshedpur [PhD Scholar, KSoM, KIIT]

[email protected]


ABSTRACTEvery recruitment exercise, designed to get the right people, involves assimilationsof factors that could positively influence and/or convert a job seeker’sorganisational attraction to a decision to apply. These factors could be varied innature from being internal and/or external. This article takes a discursive route tostate the importance of studying the role of disconfirmation sensitivity andinformation quality; factors, vital to the process of recruitment with tremendousimpact on the perception of job expectations and intention to apply. Moderationto application decisions in the preliminary stages of recruitment are critical tothe success of any recruitment exercise. Fast paced changes in the businessprocesses, virtual job arrangements and changing nature of sources of recruitmentalong with dynamic employment objectives of job seekers render the subject ofinformation quality and disconfirmation sensitivity worthy of discussion.

This article adopts a discursive analysis to present the latent importance ofinformation quality and disconfirmation sensitivity in a recruitment process andintention to apply. High-quality information programmes contribute toemployability and right career choices for a job seeker in the digital age. Therelationship between job application decision, information quality anddisconfirmation is one which holds a cohesive structural utility and is based onthe functionality of the emerging demands and dynamics of the job market.

Keywords: Information quality, job expectations, dis confirmation sensitivity, HR

various sources of recruitment, which arelarger devices to help the organisations tapthe employment market in constituting anapplicant pool. A job seeker decides tobe a part of the applicant pool, only afterhe or she receives favourable andconvincing information about the job

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Alderfer & McCord, 1970; Cohen &Bunker, 1975; Schmitt & Coyle, 1976;Simas & McCarrey, 1979).The secondevaluated the effectiveness of differentrecruiting methods and strategies (Decker& Cornelius, 1979; Rynes & Miller, 1983;Sands, 1973).The third explored realisticjob previews (RJPs) and applicant-focused perceptions (Reilly, Tenopyr, &Sperling, 1979; Rynes & Lawler, 1983;Wanous, 1973). Recruitment research inthe 1980s largely continued the researchof the 1970s: recruitment interviews(Borman, Eaton, Bryan, & Rosse, 1983;Rynes & Miller, 1983); sourcing strategies(Swaroff, Barclay, & Bass, 1985); andRJPs (Premack & Wanous, 1985).Job markets and its stakeholders-organisations, job seekers and educationalinstitutions as well as mediatory bodies(staffing and recruiting agencies, jobboards) are constantly affected by themacro and micro-level technicaltransformations, economic developmentsand the societal changes such asdemographic shifts, migration, job valuesand expectations. These changes alongwith the over-arching dominance ofInternet and globalisations to match geopolitical factors affect organisations andtheir processes and objectives.Recruitment managers perform undermuch uncertain conditions than everbefore. Organisations and economies haveno more singular dimensions of operationof earning profit and so do employees andjob seekers. The present generation has alarger concept of employment, which has

attributes, work culture and workenvironment and creates a self-assuringpreliminary recruitment image. Sources notonly bear the responsibility of attracting asmany applicants as possible (Rynes &Cable 2003) but also facilitate the selectionprocess, by way of sustaining a jobseeker’s interest in the job vacancy. Todo so and achieve an organisation’srecruitment objective, the source’sinformation needs to be as realistic aspossible in nature, Breaugh (1983).Realistic information is supposed to createa close to -reality, job image for the jobseeker. Realistic information has been aprimal line of thought for establishingrelationship between recruitment andemployee turnover. It has been argued thatorganisations in order to improve the short-term recruitment outcome(high responserate to advertisements)convey informationto glamourize job image, jeopardizing thelong-term commitment of employees(caseof unmet expectations) and therefore theneed arises to understand how informationaffects a job applicant in the most initialphase of recruitment.

Recruitment research of the past states thatrealistic image has been one of theconsistent features over the past fifty years.As per Ployhart, Tippins and Schimtt,(2017) there have been three main areasof focus in recruitment research. The firstconcentrated on the recruitment interview(i.e., interviews designed primarily toattract applicants to a firm) and the factorsthat influenced either applicant orinterviewer responses to the interview (e.g.,

Role of information- Source and applicants’ disconfirmation sensitivity in job...


more to do with employability in the long-term. This brings the focus on theimportance of factors that affect jobapplication intentions of job seekers.

Literature Review:

Sources, which are the primary carriersof job information and their effect onapplicants carry high valence for achievingrecruitment objectives for organisations.Recruitment managers choose sources forbroadcasting a vacancy considering theoutcome of utilising a particular source.Factors for a choice of source could betime, audience, cost, level of filter andsorting; they could help a manager decidethe utility of a source for a vacancy(Chapter 4, Employee RecruitmentHandbook 2001). Each source differsfrom others in terms of its access tosuitable candidates and ability for anapplicant pool creation for theorganisation. Rynes (1991) put forth ahypothesis of individual difference statingthat sources reach different segments ofpopulation and therefore shall impact therecruitment outcome differently. Anotherhypothesis proposed by Taylor andSchmidt (1983) stated that sourcespresented information differently to targetpopulation and thus asymmetricinformation creates irregular recruitmentimage and unrealistic job expectations forthe job seeker. Ryan, Kriska and Horvath(2005)stated that organisation increase theflow of information towards those sources,which yield better response whereas for along-term benefit, sources should provide

applicants with better understanding of thejob and organisation. Standardised high-quality information by way of quantity,presentation and informativeness couldchange the perception of a job for a jobseeker. Perception of information from asource is subject to moderation by traitsof individuals receiving it and thedimensions of the source as well as theinformation itself leading to asymmetry.

Information Quality

Information here is considered in generalmanagement sense and unless specifiedshould not be restricted to system designonly. Any process of knowledge creationand transfer should carry a high degree ofinformation quality. Knowledge creation,management and transfer in highinformation quality environment help inright decision-making by an individual andan organisation, Eppler (2006). Meaningof information quality lies in howinformation is presented, perceived andused. Dimensions of information areimportant but a user’s perception of thesedimensions matter foremost, (Miller&Holmes 1996). Some of these dimensionsare accuracy, timeliness or currency,format, validity, security and so on. Studiesso far in the area of recruitment have notmentioned the dimensions of informationas such but they have concentrated on thenature of information specificity, (Barber& Roehling1993; Collins & Stevens,2002). The amount of informationavailable to applicants from differentsources in terms of high and low

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information (Gatewood, Gowan &Lautanschlager, 1993), sourceinformativeness and familiarity of thesource, (Ryan, Kriska & Howarth, 2005).Information credibility, Walker et al (2009)and information credibility and mediarichness, (Cable & Yu 2006).

In effect all these works have corroboratedthat information in varying sense mattersto recruitment. Recruitment as a processshould not be too predictable so that itcontinues to respect the differencebetween individuals’ reaction to thechanging nature of jobs, economy,education and level of critical thinking,availability of resource and its effectiveutilisation. These variables interact with theinformation that a job seeker seeks orreceives through information projectionmechanisms of recruitment sources usedby organisations.This article focuses on the way informationis presented, which leads to asymmetry inperceiving expectations. Multitudinalfactors causing perceptual disturbanceneed to be sorted so as to appropriaterequired action.

Information quality also deserves to be asubject of observation and study owing tothe fact that the present economy, whichis moving towards digitalization relies oncomplex extraction and utilisation ofinformation for an organisation. Today’sorganisations hold information as keyresource in the environment and virtuallyengaged individual teams contributetowards a common goal of a particular

assignment or product or service. Olderfull- time jobs have now given way toshort-term, result oriented contracts andenvironmental set ups, which may not evenhave a physical presence. The changingnature of job has also bought aboutchanges in the sources of recruitment aswell. Newspapers and regionalemployment weeklys gave way to privatejob agencies. These were overshadowedby online job boards Naukri, Monster andthe likes. By the 90s most of theorganisations had their own website, whichhandled recruitment queries as well. In themiddle of 2000 some of the organisationshandled all recruitment- related activitiesthrough their official website only.On the other hand technical and businessschools have their own placement cells,which caters exclusively to the nature ofthe courses taught and skills developmentof the students. The past two decadeshave been of the indispensable Internet.Organisations, market and individualshelplessly depend upon it for varied kindof decision making. It is also the backboneof all the recruitment activities and a singleplatform for all the sources of recruitmentto conduct their businesses. What coulddifferentiate these players in terms ofeffectively enabling the organisations tocomplete their recruitment activities is theinformation they carry for the job seeker,so as to discern their position in the market.

The question is how do organisationscreate recruitment processes and map itto gain access to desired skills andindividuals Breaugh stated in (1983) in a



highly complex environment. Recruitmentprocesses essentially need recruitmentobjectives to guide usage of sources ofrecruitment. It may also be affected by thetype of source available, the educationlevel of the job seeker and the culture ofhis community and country. Greater usageof different sources of recruitment shalllead to larger set of information availablebut the culture of the community or countrymay offset the usage of a particular source,(Linnehan & Blau 2003).It is accepted thatquality of information has major effects onthe decision taken there upon (O’Reilly1982).There are many studies on theimportance of information quality for theinformation systems management and thedirect access of information by varioususers increases the importance of qualityof information (Lee et all, 2002) and toareas it serves.Recruitment is one such area whereapplicants’ access information about job& organisation freely from various sourcesand since information variable can beinferred to impact their applicationdecisions. It is all the more relevant todaywith multitude of information sourcesemerging from the Internet services(company website, online job boards,social platforms such as Facebook andLinkedIn etc.) and the quality of theinformation available or accessible couldbe the source differentiator. Since it is notpossible to consider all aspects ofinformation quality, here a few of themhave been discussed in a seemingproximity to recruitment and applicant

relationship - completeness, accuracy,format and currency. Completeness refersto the information being complete in termsof the need of the information seeker, herethe applicant. Accuracy refers to thecorrectness of the information provided bythe source about the job attribute,organisation, work environment and theprocess itself. Format is the way ofinformation presentation across the mediaso as to convey a standard and setinformation without diluting the uniquenessof each source. Currency is the value ofinformation in terms of whether it is currentand valid (Sethia, and Venkatesh&Joglekar 2013; Wixom and Todd 2005).There are studies, which show informationquality being used by organisations toimprove their customer response system,digital media and to gain better access tocustomer choice issues and understandingits customer better. (Sethia, Venkatesh &Joglekar 2013, Lee, Strong, Kahn &Wang 2001). Use of information qualitycan lend much to recruitment process. Iforganisations & their sources exercise highinformation quality, it is expected to leadto individuals having reliable information,which shall in turn increase their trust onthe organisation and create an attractionor fuel a latent one for the organisation.Information plays a crucial role in terms ofthe effect it has on the mind of theapplicant, which is supposed to be allaccepting, (YPC, Popovich & Wanous1982). Source may be differentiated bythe applicants based on source informationquality rendering them asymmetric and

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relatively more or less persuasive thanothers and creating diverse value in termsof expectations and perceptions of the joband organisation. Information quality isexpected to work upon the expectationof the applicant and his/ her behaviouraltrait as well.

Proposition 1: Information quality of asource of recruitment helps create jobexpectations.

Proposition 2: Sources with highinformation quality help create realistic jobexpectations.

Proposition 3: Sources with lowinformation quality create unrealistic jobexpectations.

Disconfirmation sensitivity:

An applicant is no less a consumer, whoseeks information from varied sources togain knowledge about the job andorganisation in which he/she plans to investa certain part of his life and career (YPC,Wanous, Popovich 1982). If informationquality is an attribute of the source and isan external factor moderating the intentionto apply of a jobseeker, disconfirmationsensitivity is an internal factor, which caninteract with the information impacting thejob expectations in the job applicationdecision process.

Like marketing, recruitment is also aninformation driven process. If marketingis about attracting consumers towards aproduct, through a recruitment drive a firmcompetes to attract a typically skilled setof individuals to a job vacancy, (Cable &

Turban, 2001). Bringing together themarketing and recruitment literature couldenable individuals and organisations toexplore the possibilities of discoveringfactors active in marketing drives andwhich have not been explored inrecruitment context so far. There arethough few studies, which have broughtto light the similarities of informational valuein marketing as well as recruitment,(Collins& Bell 2010; Collins 2007; Kanar,Collins &Steven 2003). Besidesinformational value, based on individual’sdifference and attitudinal factor isdisconfirmation sensitivity, a conceptfrequently used in customer satisfactionstudy; in fact it is similar to expectationlowering process(ELP), which has beenused to explain how ELP facilitates anapplicant in effective post hiremanagement of expectations (Buckley etal.1998). Application of disconfirmationsensitivity concept to job applicationintentions may unfold a new perspectivefor the process of recruitment and effectiveutilisation of sources since it evaluates theeffectiveness of the source informationquality at a pre hire stage. Attraction, byway of realistic expectations is created andstrengthened by the information, which iscomplete, accurate, has the right formatacross different platforms and hascurrency. Realistic expectation is assumedto act as a stimulus, which may result inthe intention to apply (Fishben & Ajzen,1972) and therefore the need to explore.This study opines that disconfirmationsensitivity of an individual job seeker could



be a moderator between quality ofinformation and a job seeker’sexpectations from a job. This moderationof expectation affects his intentions toapply for a job.Dis confirmation sensitivity is a concept ofhow much an individual confirms to theavailable information/product/concept oridea. It is a widely studied subject inmarketing specially customer satisfaction.Oliver (1977) stated that individuals eitherconfirm or dis confirm expectations. It hasfound its way from psychology andmarketing to consumer research andinformation technology and it should makesense to include it in studies of acquisition,management and development of humanresources for organisations.

Its interaction with individual’s expectationis of our interest since disconfirmation-sensitive individuals are said to moderatetheir expectations in order to increase theirlong term satisfaction based on of theinformation available to them (Kopalle &Lehmann 2001). There is an overallimplication here for the sourceeffectiveness their importance furthered bythe opinion that recruitment is a practicethat alters the characteristics of theapplicant to whom the selectionprocedures are ultimately applied(Bourdreau & Rynes 1995). Of particularimportance to this study of recruitmentprocess is effectiveness assessment of thesources in terms of their effect onapplicant’s expectation and the effect ofindividual’s disconfirmation sensitivity onhis intention in consideration of his need

for employment. An individual with highdisconfirmation sensitivity may reduce hisjob expectation in order to derive moresatisfaction and take decisions relatively.

This line of thought should helporganisations and other job marketstakeholders to understand how theexpectations of applicant may get alteredby quality of information accessible to him/her and individual’s behavioural andattitudinally guided response. The idea isto bring forth the importance of realisticand quality information from sources ofrecruitment in the process of recruitmentand behavioural traits that may moderatethe ultimate actions of the applicant. Underhigh disconfirmation sensitivity anindividual lowers his expectation from theinformation available and hence if theexperience or outcome is more thanexpected it results in higher satisfaction andvice versa (Kopalle & Lehermann 2001).Studies by (Wanous & Premack 1985),Breaugh (1983) stressed on howinformation from different sources, whichare more realistic and acceptable by theapplicants lead to greater degree ofsatisfaction and corroborate the metexpectation theory. The organisations usevarious media to create an attractive imageand pursue the members of the applicantpool and on the other hand the applicantscurate information from sources either tosupport the initial job and organisationimage or acquire new knowledge. In bothcases the objective is to maximiseknowledge and benefit from the availableinformation (Popovich & Wanous, 1982).

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It can thus be assumed thatdisconfirmation sensitivity of applicantsshall moderate their job expectationsbased on of information quality availableto him or her. A high disconfirmationsensitive applicant is expected to lowerexpectations on the basis of sourceinformation quality, but if the sourceinformation quality is high, (availableinformation in terms of frequency, accuracyand currency of information) theexpectations are realistic and the intentionto apply will improve. In case of individualswith lower disconfirmation sensitivity it isassumed that the expectation shall not getaltered as the information quality shall beaccepted as it is though in case the sourceinformation quality is low as well, theexpectation may dip but shall not take anegative value in turn the expectation holdson. Applicants with low disconfirmationsensitivity will minimally lower theirexpectation with little or no effect on theintention to application. Their jobexpectation is expected to increase withhigh information quality. The informationquality, when high would tend to renderthe information realistic and henceincreasing the related job expectation forthe applicant.

One of the most studied areas ofrecruitment has been of realisticexpectations and relating informationquality to realistic expectation should leadto a better understanding of the roleinformation plays in effectiveness of asource of recruitment and shall enableorganisations to analyse their strategies

regarding usage of sources so as toleverage them best.

Proposition 4: Disconfirmation sensitivityof a job seeker will moderate relationshipbetween information quality andexpectations.

Proposition 5: High job expectations willencourage the intention to apply for a jobvacancy.

Discussion:

Initial phase of recruitment, Breaugh et al(2003) refers to as the most critical phasebecause if the organisations fail to makethe first contact and persuade the jobseeker to be a part of the applicant poolthen the organisations have lost the jobseeker. It is a lost opportunity. If such isthe role of recruitment then it is imperativeto look at the existing factors affectingrecruitment and the ones that could andhave not been discussed so far. This articletakes a step in that direction by choosingto encourage an observation ofinformation quality of a source anddisconfirmation sensitivity as factors thatcould have a moderating effect on a jobseeker’s intention to apply for a job basedon information available to him or her.Implications of such observations may notmake drastic change in recruitmentapproaches but it would carry substantiallearning and knowledge creation forrecruiting managers and scholars alike.

Conclusion: This study intends to add tothe existing literature on recruitment



sources. It carries value for theorganisations in selective utilisation ofrecruitment sources for achievingrecruitment targets and the importance ofinformation and its dimensions. Intechnology-driven economies theenvironment of business processes arecontingent to even the smallest of change.Certain processes, which could be highlydependent on the environment areindividual behavioral responses.Recruitment is one such process, being themost critical in organisation’s success andcompetitive advantage, it needs continuedintrospection to so as to be mostresponsive to change. In light of theseaspects and conclusions of the pasthundred years of study on recruitment,sources of recruitment are epicenters,which can lead to discussions on newerways of looking at recruitment processesmethods, objectives and the means toachieve them.

Reference

Ann Marie Ryan, S. David Kriska &Michael Howarth. 2005. The role ofsource Informativeness and organisationalperceptions in decisions to apply.International Journal of Selection andAssessment.

Breaugh, J. A. 1983, Realistic jobpreview: A critical appraisal and futuredirection. Academy of ManagementReview, 8: 612-619 Breaugh, J. A.,Greising, L. A., Taggart, J. W., & Chen,H. (2003). The Relationship of Recruiting

Sources and Pre Hire Outcomes:Examination of Yield Ratios and ApplicantQuality. Journal of Applied SocialPsychology, 33(11), 2267-2287.

Chapter 4: Recruitment Sources andTechniques. (2001). EmployeeRecruitment & Retention Handbook (pp.93-123). American ManagementAssociation International.

Cable & Turban. 2001. Establishing thedimensions, sources and value of jobseekers’ employer knowledge duringrecruitment. Research in personnel andhuman resources management, 20:115-163

Cable & Yu. .2006. Managing jobseekers’ organizational image beliefs: Therole of media richness and mediacredibility. Journal of Applied Psychology,91: 828–840.

Charles A.O’Reilly III. 1982. Variationsin decision makers’ Use of informationsource: Impact of quality and accessibilityof information: Academy of Management,25:756-771.

Eppler. M.J Managing InformationQuality, Increasing the value of informationin knowledge intensive products andprocesses, Springer, Heidelberg Germany2006. Collins, C. J., & Stevens, C. K.(2002). The relationship between earlyrecruitment-related activities and theapplication decisions of new labor-marketentrants: a brand equity approach torecruitment. Journal of applied psychology,87(6), 1121.

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Collins, C. J. (2007). The interactiveeffects of recruitment practices andproduct awareness on job seekers’employer knowledge and applicationbehaviors. Journal of applied psychology,92(1), 180.

Fishbein, M., & Ajzen, I. (1972).Attitudes and opinions. Annual review ofpsychology, 23(1), 487-544.

Gatewood, R. D., Gowan, M. A., &Lautenschlager, G. J. (1993). Corporateimage, recruitment image and initial jobchoice decisions. Academy ofManagement journal, 36(2), 414-427.

Holmes Miller (2007)The MultipleDimensions Of Information Quality,Information Systems Management, 13:2,79-82

Kanar, Collins & Bell. 2010. AComparison Effect of Positive andNegative Information on JobseekersOrganisational Attraction & Attributerecall, Human Performance 193-212

Kopalle, Lehmann, Farley. 2010. Journalof Consumer Research, 38

Kopalle, Lehmann. 2001. StrategicManagement of Expectations: Role ofDisconfirmation Sensitivity AndPerfectionism, Journal of MarketingResearch: 386-394.

Lee, Y. W., Strong, D. M., Kahn, B. K.,& Wang, R. Y. (2001). Aimq: Amethodology for information qualityassessment. Forthcoming in Information &Management.

Lee, Y. W., Strong, D. M., Kahn, B. K.,& Wang, R. Y. (2002). AIMQ: amethodology for information qualityassessment. Information & management,40(2), 133-146.Ployhart, R. E., Schmitt, N., & Tippins,N. T. (2017). Solving the SupremeProblem: 100 years of selection andrecruitment at the Journal of AppliedPsychology. Journal of AppliedPsychology,10.Paula Popovich and John P. Wanous, TheRealistic Job Preview as a PersuasiveCommunication. Academy ofManagement Review 1982 7:4, 570-578Premack, S. L., & Wanous, J. P. (1985). Ameta-analysis of realistic job previewexperiments. Journal of Applied Psychology,70(4), 706-719.2(3), 291-304.Rynes, S L & Boudreau, JW 1986,College recruiting in large organizations:Practice, evaluation, and researchimplications. Personnel Psychology, 39:729-757Steven L Neuberg, T. Nicole Judice, LynnM. Virdin, and Mary A.Carrillo.1993.Perceiver Self Presentational Goals asModerators of Expectancy Influences:Ingratiation and the Disconfirmation ofNegative Expectancies, Journal ofPersonality and Social Psychology:409420. Setia, P., Venkatesh, V., &Joglekar, S. (2013). Leveraging digitaltechnologies: How information qualityleads to localized capabilities and customerservice performance. Mis Quarterly,37(2).



Taylor, M S. and D W. Schmidt. 1983. Aprocess - oriented investigation ofrecruitment source effectiveness, 36: 343-354.

Walker, H. J, H. S. Feild, et al. 2009.So what do you think of theOrganisation? Contextual priming,displaying employee testimonials onrecruitment web sites: Effects of

communication media, employee race,and job seeker race on organizationalattraction and information credibility.Organisational, Human Decisionprocesses, 94: 1354-1364.

Wixom, B. H., & Todd, P. A. (2005). Atheoretical integration of user satisfactionand technology acceptance. Informationsystems research, 16(1), 85-102.

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CASHLESS FINANCIAL TRANSACTION BEHAVIOUR OFURBAN MIDDLE CLASS IN BHUBANESWAR

Sriya MahapatraResearch Scholar, Department of Business Administration,

Utkal University, [email protected]


ABSTRACTIndia is passing through a window of demographic transition, not only is itconverting to a cashless economy but it is also witnessing a drastic makeover inthe paradigm of banking sector. With a purpose to transform India into a digitallyempowered society and knowledge economy, the “The Digital India Programme”was launched by Government of India, “Faceless, paperless, cashless” is one ofthe professed role of digital India. Digitalisation without financial inclusion wasincomplete hence RBI, in August, 2015, issued banking licences to, 11 paymentbanks, 2 universal banks and 10 small finance banks. First time in the history ofIndian economy, such differentiated banks were introduced. Despite such giganticmoves, the larger question here is how cashless are we? Therefore the main objectiveof the study is to determine how mobile payments options are associated withdemographic factors thereby providing us with the sections of our society thathave adopted cashless payments or have failed to do so.

Keywords: Mobile banking, mobile wallets, UPI, financial transaction behaviour

INTRODUCTIONIn April, 2018, reports of currencyshortages emerged from several parts ofthe country. This is not the first time thatthe country faced such a situation. Similarbut more grave situation took place in theyear 2016 when Prime Minister NarendraModi announced that Rs 500 and Rs 1000notes were not legal tender anymore andneeded to be exchanged for new currency,thus withdrawing 86% of the cash in theIndian economy. A much worse cashcrunch that followed had a significantadverse impact on the informal sector in

particular, which predominantly uses cashfor transactions and depends largely oninformal cash credit.The consequences can be far reaching fora country like India, as it uses cashextensively for almost all transactions. Oneway to look at it is by comparing cash incirculation to gross domestic product ofthe nation. It is one of the highest in theworld at 12.42% in 2014, compared to4% in Brazil or 9.47% in China. Electronictransactions account to less than 5% of alltransaction. The number of currency notes



in circulation is also far greater than inother larger economies of the world. In2012-13, currency notes in circulation inIndia were 76.47 billion while it was 34.5billion in the US. Studies suggest that evenin places like restaurants, hotels, malls andspas, frequented by people who are likelyto own and use credit/debit cards, use cashpredominantly. So, it is quite evident thatcash will rule in other markets as well.

India is passing through a window ofdemographic transition, not only is itconverting to a cashless economy but it isalso witnessing a drastic makeover in theparadigm of banking sector.Demonetisation in 2016 was the landmarkto introduce the cash habituated Indiansto cashless transactions. But what is “cashless economy”? An economy in which allthe transactions are done using cards ordigital means is known as a cashlesseconomy. The various modes of digitalpayments are banking cards, UPI, USSD,AEPS, mobile wallets, internet banking,AadharPay etcDespite all these gigantic and bold moves,there is a question largely looming over theeconomy. Has there actually been achange in the financial transaction modeamongst the common people? In 2017,transactions through digital means rose13.5% to Rs.124.69 trillion in Septemberfrom Rs109.82 trillion in August, accordingto provisional data released on 4th ofOctober by the Reserve Bank of India(RBI). As per NPCI data, UPI and BHIM(also using UPI) has recorded astupendous growth of 56 times(value wise)

from October 2016 to may 2017. But RBIhas also stated that UPI has replaced only1% of cash transaction. Till May 2017,14.54 million downloads of BHIM app hasbeen recording; it is being used by only0.88% of those people who havedownloaded it. USSD is even negligible.Cash dominate all transaction and itsimportance has hardly made a shift.

The attempt to convert India to a cashlesseconomy should ideally commence withdigitalisation of urban India as 70% ofIndia’s GDP comes from urban areas. Itwill expedite the process and will help thegovernment achieve its goal briskly. Theprocess of migration will be comparativelyeasier as it comprises of mostly educatedmass and benefit could be multifold.Hence, the study on payment behaviourof urban middle class in India is crucial asthey constitute the major digitalisedpopulation through mobile phones and canbring about the ambitious makeover of theeconomy from cash to cashless throughdigitalisation.

LITERATURE REVIEW

Research has proved that majority of theIndian population that is without a bankaccount, use cash for almost alltransactions while the high incomepopulation use non cash medium to payfor high value transactions (Balaji K,2017).“Cross Country Monetary Aggregate” isa useful tool for assessment to comparecash intensity. It is calculated by derivingthe ratio of money held in bills and coinsto the amount held in demand deposit/

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saving account(Korenke et al., 2013).

The understanding of ICT( Informationand Communication Technologies) amongusers and the fright of security breach areidentified as the major concern amongstindividuals, experts and organisations(Khairun & Yasmin, 2010). The adoptionof electronic payment system is much lessin government and public sectorestablishments (Hussein, Mohamed,Ahlan, & Mahmud 2010). Cashlesseconomy is the one where the amount ofcash transactions is kept at a bare minimumand not where there is absolutely no cashtransaction. It is defined as “one in whichthere are assumed to be no transactionfrictions that can be reduced through theuse of money balances, and thataccordingly provide a reason for holdingsuch balances even when they earn rateof return” (Woodford, 2003).

The advantages of cashless transactionsare many. Firstly, it reduces the fear of theftand botheration of carrying cash. It canbe easily reloaded with plastic money andinternet banking and at the same time helpsin keeping a record of the transactions.Secondly, it reduces the printing cost forthe government treasury, reducescounterfeit currency and black/unaccounted money and in long run,minimises corruption. It also brings downconsiderably the cost of maintenance ofATM and cash handling for a bank. Thereis virtually no waiting time for receivingmoney in case of instant money transferthrough cashless means (Rajadhyaksha &

Jaiswal, 2017).

The definition of “Financial Inclusion” givenin the report of the Committee on financialinclusion in India is “the process of ensuringaccess to financial services and timely andadequate credit where needed byvulnerable groups such as weaker sectionsand low income groups at an affordablecost” (Rangarajan, 2008). Studies suggestthat the GDP of a nation is positivelyimpacted by the proxies of financialinclusion such as number od bankbranches and credit deposit ratio of banks.But ATM growth rate as an indicator hasno statistical significant impact on GDP.Therefore the association of progress anddevelopment of an economy and the GDPof a nation is strong (Iqbal & Sami, 2017).

Review of papers on mobile bankingworldwide

Branchless Banking Model in Africa hasbeen studied by dividing into threecategories -, Bank-Led, Nonbank-Ledand Bank Focused (Andrew, 2009).Various independent variable such asattitude to technology, access to bank,organisation type and profile, businesssector, profile of user, positively impactsthe dependant variable which is the successof small scale business using mobiletransactions(Andrew, 2009).

The principal reasons for Kenya’s successin muster the power of mobile banking topropel its quantum leap over high hurdlesto financial inclusion that can be explainedfrom the demand and supply point of view.

Cashless financial transaction behavious of urban middle class in Bhubaneswar


Demand side includes demand amonglow-income households for a moreaccessible and affordable delivery channelfor financial services, political andeconomic stability for an extended periodof time and sufficient population densityto exploit economies of scale. Supply sideincluded market dominance of onetelecommunications company –Safaricom’s market, provision of a safe,reliable, accessible, convenient, andaffordable product and extremelycompetitively priced (Kaffenberger et al.,2015).

Market Penetration and Business Edge ofmobile banking companies.

Traditional banks may be hesitant to openbranches in every village due to itsuneconomic returns, but simple mobilephone coverage is all that is required now.India also serves as a big remittancemarket and with money transfers possiblethrough mobile phones, workers andmigrant labours could simply shift to mobilepayments and send their money home.They can avail Government benefits,insurance, loans and interest on savingsthrough mobile banking. PMJDY andIPPB can be accessible from any sectionof the society in remotest corner of thecountry {Srinivas2017}.

As only 5% of rural India has bankbranches, mobile banking can plan theirexpansion in villages which should involvegreater digitalisation and lower costs. Ifassociated with govt social welfareschemes, more growth can be achieved.

Also if easiness, quickness, transparencyand security could be ensured, it can easilycompete with traditional banks. Simplicityof digital product, support for help andinformation will boost penetration andprofit margins(Garg, Professor, & Kapoor,2015). Challenges that these new agetechnology might ecounter include,awareness, competent staff, security andoperational profit(Garg et al., 2015).Customers are looking for innovation andservice because of which private banksflourished. Soon the shift from privatebanks to payment banks will be seen(Shivnani, 2017)

Amongst the newly setup payment banks,IPPB (India Post Payment Bank) is likelyto achieve higher penetration due to itswide and deep network and diverseservices (Srinivas, 2017).

Analysis of usage of Paytm in pre and postdemonetisation era, purpose of usage,demographic distribution, comparativeanalysis to existing players reveals a sharpacceleration in the past 5 years (Dixit,Prakash, & Tiwari, 2017). Given belowis a distribution of percentage of e-walletuser with respect to companies.

Research suggests ways by which mobilebanking can be brought into the currentbanking ecosystem. Better technologycoupled with security and awareness canboost mobile banking. Cashbacks, discounts,royalty points and bonuses can act as incentiveto user to motivate them towards cashlesstransactions (Dixit et al., 2017).

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RESEARCH METHODOLOGY

Objective of The Study

The objective was to study the associationof cashless financial transaction behaviourby gender, age and employment status.Based on the objectives, the followinghypothesis was formulated.

H0 : There is no difference in the cashlessfinancial transaction behaviour betweendifferent gender, age group andemployment status.

H1 : There is a difference in the cashlessfinancial transaction between behaviourdifferent gender, age group andemployment status.

Scope of Study

The study primarily aimed at understandingthe present payment behaviour of urbanmiddle class of Bhubaneswar. It aims tounderstand preference of mode of cashlesspayment i.e. debit/credit cards (byproviding CVV followed by Password orOTP), online wallets (Paytm, Ola money,Mobikwik, Freecharge, Buddy), bankapps, net banking(financial institution’swebsite) and UPI(Unified PaymentInterface) with respect to gender, age andemployment status. Bhubaneswar has beenselected because of convenience and alsoavailability of the target group, i.e. middleclass population.

Research design

The path of investigation has been designedkeeping the objectives in mind and toderive at answers that can appropriately

address the research questions. Theapproach is descriptive hence a crosssectional study is undertaken to meet thepurpose of the research. The study amongthe urban middle class population inBhubaneswar based upon themethodology that is most suitable forempirical analysis, has been undertaken.

Sampling procedure and design

The scope of the study has restricted thesample to Bhubaneswar only to fulfil theobjective of the study. The samplingmethod followed has been designed toinclude urban middle class from all gender,age groups and employment status. Hencestratified convenience sampling methodhas been followed. The questionnaire wasadministered to 100 people of both genderin equal proportion i.e. 50male and 50female. Respondants belong to differentage groups and to different occupations(Govt employee 15%, Private companyemployee 19%, Business and Selfemployed 17%, Student 17%, Homemaker 16% and Retired/Unemployed16%) have been equallybalanced for a fair analysis. All theresponses were found fit to be used foranalysis.Figure 1: Gender distribution in sample



Figure 2: Employment Distribution in Sample

Data Collection, analysis and interpretationData was collected from respondents inGoogle forms and hard copy. The datacollected through hard copy was enteredin Google form so that all the responsescan be tabulated easily in excel sheet. Thedata analysis has been conducted withdescriptive statistics and techniques likeChi Square which has been used to findout if there is a significant relationshipbetween variables among the urbanmiddleclass and their financial behaviourin terms of payment modes for multiplepurposes. The registered software of‘SPSS-19’ statistical software has beenapplied for analysis of the data andinterpretation done based on the outputof the software.Limitations :The study had been carried out with alimited sample size, a larger sample size

can give a different result, which may bemore useful. The study also has limited toone tier II city only. An inclusion of middleclass population from different tiers ofcities and towns across the state or nationcan give more comprehensive and betteranalysis. It would help to understand thefinancial transaction behaviour overdifferent region, economic status andculture.DATA ANALYSISData collected on a sample of 100 urbanmiddle class populations was analysedusing statistical tools and techniques asexplained in the methodology and analysedalong with the interpretation and arepresented according to the objective of thestudy.Profile of the samplei. Age DistributionThe mean age of the sample was 40.56 ±15.60 years. The median year was 37.5with inter-quartile range 29 - 45 years. Thatmeans a quarter of our sample have ageless than 29 years and a half of the sampleare below the age 37.5 years. And anotherquarter of the sample subjects are above45 years age. The sample has equalproportion of male and female.

Age group Male Female Total No. % No. % No. %

18-29 15 30 13 26 28 28 30-39 12 24 20 40 32 32 40-50 14 28 7 14 21 21 >50 9 18 10 20 19 19 Total 50 100 50 100 100 100 Mean ± SD 41.06 ± 16.18 40.06 ± 15.15 40.56 ± 15.60 Q1 27.75 29 29 Q2 38 37 37.5 Q3 47.25 45 45

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Figure 3: Mean Age of Sample Subjects

i. Employment Status

Table 2 and Figure 4, furnished theemployment status of the sample subjects.The major chunk of the sample subjectswas employed or self employed which wasa little higher than 50%. Homemaker,students and retired/unemployed

constituted the remaining half of the sampleapproximately in equal proportions.Employed and self employed were 68%among males while the correspondingproportion amongst females were 34%.The males have higher association withemployment than females (P=0.000)

Table 2: Employment Status of Sample Subjects by gender

Employment status Male Female Total p No. % No. % No. % Homemaker 0 0 16 32 16 16

=22.446 p=0.000

Student 7 14 10 20 17 17 Retired/unemployed 9 18 7 14 16 16 Employed/Self employed 34 68 17 34 51 51

Total 50 100 50 100 100 100

Figure 4: Employment Status of Study Subjects by Gender



Mode of Cashless Financial Transaction By Gender, Employment Status And Age

Table 3: Preference of mode of cashless financial transaction by gender

Financial transaction of Mobile Male Female Total χ2, p No. % No. % No. %

Debit/credit card by entering CVV/ OTP/PASSWORD Moderately preferred 18 41.9 11 32.4 29 37.7

χ2=0.994 p=0.803

Least preferred 4 9.3 3 8.8 7 9.1 Most preferred 18 41.9 18 52.9 36 46.8 Never 3 7 2 5.9 5 6.5 Total 43 100 34 100 77 100 Wallets like Paytm, Ola money, Mobikwik, Freecharge, Buddy Moderately preferred 18 47.4 12 35.3 30 41.7

χ2=1.107 p=0.775

Least preferred 5 13.2 5 14.7 10 13.9 Most preferred 8 21.1 9 26.5 17 23.6 Never 7 18.4 8 23.5 15 20.8 Total 38 100 34 100 72 100 Bank apps Moderately preferred 16 44.4 10 33.3 26 39.4

χ2=4.744 p=0.192

Least preferred 4 11.1 9 30 13 19.7 Most preferred 3 8.3 4 13.3 7 10.6 Never 13 36.1 7 23.3 20 30.3 Total 36 100 30 100 66 100 Net banking Moderately preferred 16 42.1 11 36.7 27 39.7

χ2=2.086 p=0.555

Least preferred 5 13.2 6 20 11 16.2 Most preferred 9 23.7 4 13.3 13 19.1 Never 8 21.1 9 30 17 25 Total 38 100 30 100 68 100 UPI (Unified Payment Interface) through Tez, BHIM, PhonePe Moderately preferred 5 13.9 4 12.9 9 13.4

χ2=0.742 p=0.863

Least preferred 7 19.4 5 16.1 12 17.9 Most preferred 4 11.1 2 6.5 6 9 Never 20 55.6 20 64.5 40 59.7 Total 36 100 31 100 67 100

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Figure 5 : Graphical representation - Preference of mode of cashless financialtransaction by gender

Table 3, Figure 5 illustrates thepreference of cashless payment technologyby different gender. Usage of Debit/creditcards (by providing CVV followed byPassword or OTP) was preferred‘moderately’ and ‘mostly’ together by83.8% of males and 85.3% of females.There was no significant difference in theirpreference (p=0.803). Usage of onlinewallets (Paytm, Ola money, Mobikwik,Freecharge, Buddy) displayed similarassociation with both gender (p=0.775).While it was moderately preferred by47.4% males, 35.3% females also did so.It was least preferred by 13.2% and

14.7% males and females respectively.Bank apps as a mobile banking tool wasalso not particularly associated with gender(p=0.192). It was most preferred by 8.3%males and 13.3% females and moderatelypreferred by 44.4% and 33.35 of malesand females respectively. Net banking(financial institution’s website) and UPI(BHIM, Tez, PhonePe etc) displayed nosignificant difference in preference. Netbanking was moderately preferred by42.1% males and 36.7% females(p=0.555) and UPI was never used by55.6% males and 64.5% females(p=0.863).



Table 4: Preference of mode of cashless financial transaction by age groupFinancial transaction of Mobile

18-29 30-39 40-50 >50 Total χ2, p No. % No. % No. % No. % No. %

Debit/credit card by entering CVV/ OTP/PASSWORD Moderately preferred 13 48.1 8 26.7 8 47.1 0 0 29 37.7

χ2=11.993 p=0.214

Least preferred 3 11.1 4 13.3 0 0 0 0 7 9.1 Most preferred 9 33.3 16 53.3 9 52.9 2 66.7 36 46.8 Never 2 7.4 2 6.7 0 0 1 33.3 5 6.5 Total 27 100 30 100 17 100 3 100 77 100 Wallets like Paytm, Ola money, Mobikwik, Freecharge, Buddy Moderately preferred 13 50 11 37.9 5 35.7 1 33.3 30 41.7

χ2=18.159 p=0.033

Least preferred 3 11.5 5 17.2 2 14.3 0 0 10 13.9 Most preferred 10 38.5 6 20.7 1 7.1 0 0 17 23.6 Never 0 0 7 24.1 6 42.9 2 66.7 15 20.8 Total 26 100 29 100 14 100 3 100 72 100 Bank apps Moderately preferred 7 30.4 13 48.1 6 46.2 0 0 26 39.4

χ2=10.2 p=0.335

Least preferred 7 30.4 3 11.1 3 23.1 0 0 13 19.7 Most preferred 2 8.7 4 14.8 0 0 1 33.3 7 10.6 Never 7 30.4 7 25.9 4 30.8 2 66.7 20 30.3 Total 23 100 27 100 13 100 3 100 66 100 Net banking Moderately preferred 10 43.5 12 42.9 5 35.7 0 0 27 39.7

χ2=5.411 p=0.797

Least preferred 5 21.7 3 10.7 2 14.3 1 33.3 11 16.2 Most preferred 2 8.7 7 25 3 21.4 1 33.3 13 19.1 Never 6 26.1 6 21.4 4 28.6 1 33.3 17 25 Total 23 100 28 100 14 100 3 100 68 100 UPI (Unified Payment Interface) through Tez, BHIM, PhonePe Moderately preferred 3 12 4 15.4 2 15.4 0 0 9 13.4

χ2=14.884 p=0.094

Least preferred 5 20 6 23.1 1 7.7 0 0 12 17.9 Most preferred 6 24 0 0 0 0 0 0 6 9 Never 11 44 16 61.5 10 76.9 3 100 40 59.7 Total 25 100 26 100 13 100 3 100 67 100

Figure 6 : Graphical representation - Preference of wallets as a cashless modeof financial transaction by age group

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Table 4 depicts preference of cashlesstransaction modes by different age groups.Debit/credit cards (by providing CVVfollowed by Password or OTP) is the mostpreferred mode by all age groups and nosignificant difference exists (p=0.214).66.7% in the age group of >50 years,52.9% in the age group of 40-50 yearsand 53.3% in the age group of 30-39 yearsstated it as their most preferred mode ofcashless payment technology. Wallets

((Paytm, Ola money, Mobikwik,Freecharge, Buddy) were associated withyounger age group (p=0.033). 88.5% of18-29 years age group preferred it as‘most’ and ‘moderate’. >50 years old didnot prefer wallets as 66.7% have statedof never preferring it (refer to Figure 6).Bank apps as a mobile paymenttechnology do not show any associationto age group in particular. It wasmoderately preferred by 30.4%, 48.1%,

Table 5 : Preference of mode cashless financial transaction by employment status

Financial transaction of Mobile

Homemaker Student Retired/ unemployed

Employee/ Self employee

Total χ2, p

No. % No. % No. % No. % No. % Debit/credit card by entering CVV/ OTP/PASSWORD Moderately preferred 2 28.6 7 43.8 2 50 18 36 29 37.7

χ2=5.975 p=0.742

Least preferred 0 0 1 6.2 0 0 6 12 7 9.1 Most preferred 4 57.1 7 43.8 1 25 24 48 36 46.8 Never 1 14.3 1 6.2 1 25 2 4 5 6.5 Total 7 100 16 100 4 100 50 100 77 100 Wallets like Paytm, Ola money, Mobikwik, Freecharge, Buddy Moderately preferred 0 0 6 35.3 1 25 23 51.1 30 41.7

χ2=26.24 p=0.002

Least preferred 2 33.3 2 11.8 0 0 6 13.3 10 13.9 Most preferred 0 0 9 52.9 1 25 7 15.6 17 23.6 Never 4 66.7 0 0 2 50 9 20 15 20.8 Total 6 100 17 100 4 100 45 100 72 100 Bank apps Moderately preferred 1 16.7 5 38.5 0 0 20 46.5 26 39.4

χ2=10.086 p=0.344

Least preferred 2 33.3 3 23.1 0 0 8 18.6 13 19.7 Most preferred 0 0 2 15.4 1 25 4 9.3 7 10.6 Never 3 50 3 23.1 3 75 11 25.6 20 30.3 Total 6 100 13 100 4 100 43 100 66 100 Net banking Moderately preferred 1 16.7 8 57.1 0 0 18 40.9 27 39.7

χ2=12.827 p=0.171

Least preferred 1 16.7 2 14.3 1 25 7 15.9 11 16.2 Most preferred 0 0 1 7.1 1 25 11 25 13 19.1 Never 4 66.7 3 21.4 2 50 8 18.2 17 25 Total 6 100 14 100 4 100 44 100 68 100 UPI (Unified Payment Interface) through Tez, BHIM, PhonePe Moderately preferred 1 16.7 2 13.3 0 0 6 14.3 9 13.4

χ2=7.246 p=0.612

Least preferred 1 16.7 4 26.7 0 0 7 16.7 12 17.9 Most preferred 0 0 3 20 0 0 3 7.1 6 9 Never 4 66.7 6 40 4 100 26 61.9 40 59.7 Total 6 100 15 100 4 100 42 100 67 100



46.2% amongst 18-29, 30-39 and 40-49age groups respectively(p=0.335). Netbanking (financial institution’s website) alsodid not display association with age(p=0.797). UPI (BHIM, Tez, PhonePeetc) was never preferred by 44% in 18-29 years age group, 61.5% in 30-39 years

age group, 76.9% in 40-49 years agegroup and 100% in >50 years age group.Therefore there is no significant differencein the preference of UPI as a mobilepayment technology with respect to agegroup (p=0.094).

Figure 7: Preference of mode of cashless financial transaction by employment status

Table 5, Figure 7 depicts thepreference of mode of cashless financialtransactions on the basis of employmentstatus. Debit/credit card is mostpreferred by 57.1% of homemakers,43.8% students, 25% of retired/unemployed and 48% of employed.There is no significant difference inpreference of debit/credit card byemployment status (p=0.742). Wallets(Paytm, Ola money, Mobikwik,Freecharge, Buddy) are associated withstudents as 52.9% preferred it the most.

On the other hand, 66.7% homemakersand 50% of retired/unemployed neverpreferred it (p=0.002). Banks appsshowed no particular association toemployment status as it was mostpreferred by 15.4% of students, 25% ofretired/unemployed and 9.3% employedpopulation. Net banking (financialinstitution’s website) with p value of 0.171and UPI with p-value of 0.612, did notdisplay any significant difference inpreference amongst population ofdifferent employment status.

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CONCLUSIONThe purpose of the study was to identifythe association of modes of cashlessfinancial transactions with demographicfactors of age, gender and employmentstatus. Based on the findings, followingconclusions are drawn.

1. It was observed that there was nosignificant difference in preference ofcashless modes of financialtransactions based on gender. UPI wasleast popular and debit/ credit card (byproviding CVV followed by Passwordor OTP) was most preferred by bothgenders.

2. Debit card was most popular amongstall age groups and net banking, bankapps and UPI showed no significantdifference in preference. Younger agegroup i.e. 18-29 years old and 30-39years old, were more associated withwallets than the older age group.Hence, can be concluded that there isa difference in preference of mobiletechnology for financial transaction onthe basis of age group.

3. Employment status also displayedvaried association. Students associatedwith use of wallets but the rest werenot. UPI was universally never popularwith people of different employmentstatus. Therefore, it can be deductedthat there exists a difference inpreference of mobile technology forfinancial transaction based onemployment status.

REFERENCEShivnani, T. (2017). Customer Opiniontowards Airtel Payment Banks in India/ :An Analytical Study, (August), 1–12.Road, L., Delhi, N., & Road, L. (2015).Payment Banks in India –Demystified, 2,1–4.Damle, madhavi, Thenuan, P., & Raval, J.(2016). Genesis of Payment Banks: It’sStimulus on the financial inclusion in India.International Journal of Scientific &Engineering Research, 7(3), 783–391.Kaffenberger, M., Butt, S., The, B.,Dilemma, M. S., Yal, I. T. E., Oji, C. K.,… Sweatt, E. L. (2015). RegulatoryImpact on Mobile Money and FinancialInclusion in African Countries - Kenya ,Nigeria , Tanzania and Uganda RegulatoryImpact on Mobile Money and FinancialInclusion in African Countries. CGAPFocus Note, 62(January 2012), 1–16.Iqbal, B. A., & Sami, S. (2017). Role ofbanks in financial inclusion in India.Contaduría Y Administración, 62(2),644–656. https://doi.org/10.1016/j.cya.2017.01.007Andrew, W. (2009). MOBILEBANKING IN DEVELOPINGCOUNTRIES . ( A CASE STUDY ONKENYA). Degree Programme ofInformation Technology, 45.Abid, S. (2016). Payment Banks/ : ARevolutionary Step in Indian BankingSystem, 7(6), 81–83. https://doi.org/10.9790/5933-0706018183Garg, S. G., Professor, A., & Kapoor, N.(2015). Changing Landscape of Banking



System in India: Payment BanksOpportunities or Challenges. ELK AsiaPacific Journals – Special Issue ISBN,978–93.Khairun, N.K. and M. H. Yasmin, (2010)¯E-commerce Adoption in Malaysia:Trends, Issues and Opportunities ,Strategic Review, (pp 89-134), Malaysia:PHussein R., N. Mohamed, A., Ahlan andM. Mahmud (2010) ¯ E-GovernmentApplication: an Integrated Model on G2CAdoption of Online Tax . TransformingGovernment: People, ProcesStudies, M., & Fellow, V. (2017).CASHLESS RURAL ECONOMY – ADREAM OR REALI Cs, R. (2017).Digital payments system and rural India/ :A review of transaction to cashlesseconomy, 3(5), 169–173.Rajadhyaksha, M., & Jaiswal, S. (2017).Black Swan Effect of Demonetisation onDigital Mode of Payment in India, 2(4),19–24.Delhi, N. (2010). Financial Inclusion and,628(May), 613–628. https://doi.org/10.1002/jid

Diniz, E. H., Porto de Albuquerque, J., &Cernev, A. K. (2011). Mobile Money andPayment: A Literature Review Based onAcademic and Practitioner - OrientedPublications (2001 - 2011). SSRNElectronic Journal. https://doi.org/10.2139/ssrn.2924669 Sheetal Thomas 1 & G. Krishnamurthi 2,15(2), 7269–7281. Info, A. (2017). aStudy on Demonetization and Its Impacton Cashless Transactions, 4, 58–64.ndPolicy, Vol. 5 (3), pp. 225-248.Woodford, 2003, ¯Interest and Price:Foundation of a Theory of MonetaryPolicy , Princeton University Press.Kumari, N., & Khanna, J. (2017).Cashless Payment: A Behaviourial ChangeTo Economic Growth. InternationalJournal of Scientific Research andEducation, 5(7), 6701–6710Sultana, M., & Kumar, K. (2015). A studyon customer payment behaviour inorganised retail outlets at CoimbatoreKorenke, R., Joseph, N., Benjamin, D.,Joseph, N., Korenke, R., & Mazzotta, B.D. (2013). Cash Outlook/ : India,(September), 31.District. Journal ofManagement Science, 5(2), 1–16

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105

MOTIVATIONAL FACTORS AND IT’S IMPACT ONSTUDENTS’ PERFORMANCE IN HIGHER

EDUCATION: A REVIEW

D. NisruthaResearch Scholar, KSOM, KIIT University, Bhubaneswar, Odisha

[email protected]


ABSTRACTThe purpose of the paper is to study different motivational factorsinfluencing students in their higher education. In this paper, the authortried to study the influence of motivation on a student in differentperspectives like how the motivation of student is connected withtheir age, teacher’s instruction style, teachers motivation. The Authoralso tried to examine the different motivation theories which are usedin assessing student motivation by various authors. From the findingsof different papers, it is evident that based on the discipline which heis studying the motivational approach need to be different. The AMS(Academic Motivation Scale) instrument to measure different subtheories of self-determination theory were also studied. The findingsfrom this review paper will help teachers and students to know aboutdifferent motivational factors involved in higher education whichfurther helps them to understand each other in a continuous and betterlearning process.Keywords: Motivation, Higher Education, Teacher’s Instruction style, AMS.

INTRODUCTION

The stimuli are needed for a human beingin any sector to work by using his at mostcapabilities. Motivation is defined as theenergy or catalyst that triggers a person tomake choices, pursue certain purposes,and to focus in a particular direction

(Brophy,1983; Obade,2013). Motivationdirects individual to attain one’s goal.Motivational theories help us tounderstand what makes an individual giveshis best. Akitson postulated that motivationexplains three critical issues related to



human behavior. First motivation helpsindividual to select the best option amongpossible alternatives. Second motivationhelps individual to pay a proper attentionto a task in a given situation. ThirdMotivation determines the persistence oftask. The purpose of this paper is to findout different factors of motivation whichare influencing students in their highereducation. In common there are two kindsof motivation one is intrinsic motivation andanother is extrinsic motivation. Intrinsicallymotivated people don’t expect anyexternal stimuli as their self-goal is amotivating factor for them, whereasextrinsically motivated people needexternal stimuli and that external stimuli isdifferent for different people based on thesituation and their personal characteristics.

Motivation in education

Motivation helps a person to do the taskwith commitment. Motivating studentsboth in an extrinsic and intrinsic way isimportant to raise their perceptionstowards learning (Dahl & Smimou 2011).Extrinsic Motivation works as externalstimuli to a student which helps him Howto motivate student for learning is alwaysa researchable topic in education and alsoin psychology (Dahl & Smimou 2011).Richardson, Abraham, and Bond (2012)conducted a meta-analysis in which theyreviewed more than ten years of researchon the antecedents of university studentsgrades and percentages. Their findingsdemonstrated that motivational factorswere some of the most substantive

correlates of students performance(Obade, 2013). From their findings, it isevident that students performance isdirectly affected by the way in which theyare motivated.

A Relation between student motivation andtheir age

Leper, Corpus, and Iyengar (2005) haveshown that intrinsic motivation diminishesas children progress through school (Hegarty,2010). Barron and Harackiewcz(2001) found that undergraduate studentswith high-performance goals, which areextrinsic in motivation, can also achievehigh outcomes( Hegarty,2010). It supportsthe view that the lack of intrinsic motivationis not related to poor performance(Hegarty,2010). Gottfried (1985,1990)and Harter (1981) also noted the highlevels of intrinsic motivation in youngchildren and documented how thismotivation decreases with age. Harter’s1981 study has become the cornerstoneof validation of the decline in intrinsicmotivation with age. Pintrich (2000) affirmsthat mastery goals diminish with agewhereas performance goals, whichbecome the yardstick of measurement ineducational systems, increase with age.Stewart (2005), through a study ofundergraduate students, asserted thatmotivation changes as an individual movethrough a program and that motivationitself is different across various majors.Hegarty used Preliminary descriptiveanalysis to present an overall indication ofmotivation types and levels in graduate

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students. Chi-square analysis was alsoused to investigate whether scale items areindependent or homogenous (i.e does anabsence of intrinsic motivation indicate thepresence of extrinsic motivation oramotivation?)Teachers instructional style to meetstudent’s needsSDT researchers arrogated that threetypes of instructional styles should beadopted in classrooms. First, autonomysupport is necessary to satisfy the needfor autonomy, the opposite meaning of acontrolling style. This style aims to promotestudents inner motivational resources, suchas their interests and values, by usingpractices such as allowing choice,spending the time to communicate withstudents, offering encouragements, andproviding rationales (Reeve, 2002; Reeve& Jang, 2006). Second, the structuremeets students need for competence, thisstyle involves three representativebehaviors: presenting clear expectationsand directions to students, providingguidance when students need help, andoffering informative feedback (Jang,Reeve, & Deci, 2010; Reeve, 2006). Last,involvement is important to satisfy the needfor relatedness. Involvement is concernedwith social and interpersonal relationshipswith others such as between students andteachers. This style entails the expressionof affection and cares to students, andteachers dedication to time and interestsof their students (Skinner &Belmont,1993). Structure meets studentsneed for competence. It refers to the

amount of time and quality of informationthat students receive in order to achievethe expected outcomes (Jang etal.,2010;Reeve,2006).

Relation between teachers’ motivationand student motivation

When teachers are intrinsically motivatedfor teaching, students also report highintrinsic motivation for learning (Lam et al.,2009). Furthermore, students who aretaught by not only intrinsically motivatedteachers, but also intrinsically motivatedpeers who play a role as teachers are likelyto have greater interests and engagedbehaviors in the given tasks ( Radel,Sarrazin, Legrain, & Wild, 2010). Themotivation of the person teaching positivelyaffects the motivation of learners; namely,“social contagion of motivation” exists(Radel et al., 2010, p.578). Even thoughthe majority of studies show that therelations between teachers and studentsmotivation are positive, this conclusion isnot unequivocal.

Understanding Motivation factors inhigher education

For higher education organizations, theycan use analysis of student survival ratesto better understand which factorscontribute to surviving until graduation. Theschool can better investigate therelationship with high school GPAs, SATscores, majors, socio-economicbackgrounds, lower division grades andso forth to understand which factors helpto promote student success. Lainson in histhesis examined whether any changes

Motivational factors and it’s impact on students’ performance ....


occur based on students progress towardstheir graduation. He used a frameworkbased upon “ Herzberg’s two-factortheory (1959)”,and an “expanded model”developed by DeShields, Kara, andKaynak (2005), Lainson conducted asurvey where he collected 535 studentsdata from 3 different universities out ofwhich 1 is public state university insouthern California and other two areprivate liberal art universities. Lainsontested” maintenance and motivationfactors against dependent variablesand assessed segmentation by classstanding ”. Results of Lainson findingssupport that students dissatisfaction raisesas he is coming closer to graduation andhis motivation levels are declining year byyear. “A key exception is that a student’smotivation to finish a degree was notdiminished, regardless of dissatisfactionor lack of motivation in other areas “.Lainson mentioned that they are “ threekey areas of dissatisfaction emerged: “ 1.expectations, 2. learning practical skillsand 3.value”. Dissatisfied students aremore likely to drop out from education orthey may transfer to another college.Lainson’s Objective is to evaluate factorsthat contribute to satisfaction and retentionby building upon student satisfaction andretention model (SSRM) developed byKeveaney and Young (1997).Building onboth Keaveney and Young’s SSRM model(1997) and Deshields et al.study (2005),this study introduces a new StudentMaintenance and Motivation Model forSatisfaction (SMMMS).This model

includes the original extrinsic factors inSSRM and adds several additional intrinsicfactors to align more closely to themethodology of Herzberg’s two-factortheory. This model was then applied to astudy of college students, lookingspecifically at levels of satisfaction acrossacademic years. Evidence of student’sacademic year standing affectingsatisfaction begins with the first year of theircollege life. “ The CooperativeInstitutional Research Program, run bythe Higher Education Research Instituteat the University of California at LosAngeles, annually surveys more than400,000 incoming freshmen “. Surveydata showed that student satisfaction isinfluenced by students prediction ofsatisfaction. Most influential is studentspost- enrollment. The survey found thatthe most powerful predictor of satisfactionwas a “sense of belonging”. “Studentswho felt connected to campus life weremore likely to be satisfied with theirchoice of college” (Lainson,2014). Inaddition, Interaction of faculty memberswith students has improved students levelof satisfaction and also sense ofbelongingness. Surveys also showed that“ students who indicated making moneywas a critical reason to attend collegewere shown to be slightly less likely toreport satisfaction than studentsindicating other reasons, such asgaining an appreciation for ideas “(Hoover 2010;Lainson 2014). Lainsonstudy explored the correlation betweenmaintenance and motivation factors,

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students class standing and retention. Thestudy used a correlational approach toexamine quantitative data collected bysurveying 535 undergraduate students ofthree southern California schools. Thisstudy analyzed data using conveniencesampling on student perceptions ofmaintenance and motivation factors. Thelresearch question of the study is as follows:“ What is the relationship betweenstudents class standing and their levelof satisfaction and motivation? “. Theresearcher focused on a hypothesis thatestablishes the link between class standingand motivation and hygiene factors. Astudent is more likely to persist if he orshe is close to graduating. From theinterpretations of the study it was clear thatSeniors were less motivated to study hard,achieve good academic grades, to obtainknowledge from attending classes, andto develop social relationships with otherstudents. Seniors were also more likely tobe frustrated by university policies andprocedures. Herzberg never measuredhow likely a person was to feel motivatedto work under the condition of “workingto survive, “regardless of the employer; heonly examined if and how motivationoccurred within the context of theemployer. Providing a treat or, as Herzbergsays, “kicking the dog” is simplyincentivizing the recipient to move, not tobe motivated (Herzberg,1987). Thisreality is why pay/compensation hasremained a maintenance factor and not amotivator, even though this point remainscontentious for many critics of Herzberg.

Increase in dissatisfaction of seniorstudents will decrease their motivationwhich affects their academic achievementsand performance in placement drives,which enforces them to slowly disconnectthem from college related activities and infuture also this gap will remain and theywill not attend for alumni meets. Dissatisfiedseniors may not only feel trapped, but mayalso “ become punitive-not throughleaving, but in attitude and actionsrelated to alumni issues, futurerecommendations and negativelyperceived brand awareness “. In essencethese students are crying “ Help! I’m asenior. Get me out of here,” with anincreased singular motivation to finish evenas they are disconnecting motivationallyfrom the university family with potentiallynegative, long-term consequences.

Assessing Student Motivation usingExpectancy Value theory

Expectancy value theory was used as anassessment tool for knowing studentssentiment towards sustainable engineering.Assessing students’ motivation to engagein sustainable engineering was the firsteffort to measure engineering students’attitudes toward SE using the three sub-scales of expectancy value theory andassessing correlations in these attributeswith students’ participation in variouslearning experiences to measureengineering students’ attitudes toward SEusing the three sub-scales of expectancyvalue theory and assessing correlations inthese attributes with students’ participation



in various learning experiences.(McCormick et al 2013).Many researchershave addressed the point of qualityteaching in higher education. In marketingquality of product is always measured withthe help of customer satisfaction, in thesame way management of educationalinstitutions should treat their students ascustomers as they are the main stakeholders Bensimon (1995). Ames andArcher (1988) found that classroomclimate will have an impact on motivationalvariables and if students are connected withclassroom climate they will show longterm involvement in learning. Autonomousmotivation of the students have an impacton producing desirable outcomes.Fordham findings support that a positiverelation exists between student’s intrinsicmotivation and their knowledge ofcurriculum (Dahl & Smimou,2011).Pintrich (2003) underlined the importanceof scientific oriented research on studentmotivation. Pintrich in his researchattempted to find out about expectationsof students from the classroom, i.e what isthe main aspect which motivates studentto come to classroom, are they aware oftheir own motivational factor ? he alsostudied the how motivation leads tocognition (Dahl & Smimou,2011). Leperand Corpus (2005) studied the associationbetween age of a student and theirmotivational orientations with the help oftheir academic outcomes. Leper andCorpus also supports that decline inintrinsic motivation as one becomes olderin age and extrinsic motivation increases

as one becomes older there by heconcluded that “intrinsic motivation hasa positive correlation with theacademic outcome” (Dahl &Smimou,2011). Darren and Kamalspecifically worked on student’sperception on teaching quality and hestresses on the point that student willpercept positively on teaching quality ofhis instructors only when they have positiveopinion on educational institution.Student’s outcome depends on the qualityof education provided by the institution andthe most important factor is their motivationitself (Dahl & Smimou, 2011). Bean andMetzner (1985) mentioned that studentsachieving high grades may drop out fromcollege if they have passed through lowlevels of utility, satisfaction and high levelsof stress.

Student Motivation in EngineeringCoursesAttrition of students is one of the raisingproblem in educational institutions duringthe first two years. Attrition of students inundergraduate level is high when they arein first two years ( Suresh,2006;Vogt,2008; Mamaril & Usher,2013).Classroom Strength in service courses arelarge generally more compared to othercourses. Students in these classes havepointed out that likened with other classeshave course load to a greater extent andthey do not have fundamental interactionwith educators (Suresh,2006; Mamaril &Usher,2013). Research on Studentmotivation in engineering courses helpsinstructors to better understand the

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relationship between student academicoutcomes and their aim to persist inengineering (Mamaril & Usher,2013).Mamaril and Usher have found therelationship between constructs ofmotivation like self efficacy, task value,achievement goals to achievement andpersistence using measures providing clearactivities and tasks in engineering. Mamarilexamined students engineering self efficacy,he proposed that “student’s continuedmatriculation in engineering programsmay be due (in part) to their self-efficacy- the belief they hold about theircapabilities”. “social cognitive theory isbased on the view that personal factors,behavioral factors, and environmental

factors are interconnected and affectone another”(Bandura,1997). Bandura’sresearch showed that the individuals beliefon their own capabilities to achieve desiredoutcomes acts as a primary motivator invarious situations of once life. “Self-efficacy helps determine the amount ofeffort people exert in an activity, andtheir persistence and resilience in theface of adversity” (Pajares,1996).Students who have interest in engineeringand who have believe on their owncapabilities are motivated to complete thetask with more efficiency(Bandura,1997).Table 1 shows theexamples of items used by Mamaril andUsher in their survey.

Mamaril and Usher examined theassociation between self-efficacy andacademic achievement using student’sacademic achievements obtained in servicecourses. Academic persistence andprofessional persistence were measured.Research findings support that self-efficacyand academic achievement are positivelyrelated. Mamaril used Independent-samples t tests to test the significancebetween gender and self-efficacy, hisfindings support that gender differences andengineering skills self-efficacy aresignificant. Men scored much higher in

Table 1 SELF-EFFICACY SCALE AND EXAMPLES (Mamaril & Usher,2013)

Scale Example General engineering self-efficacy I can complete my course work if I

do not quit (Mamaril & Usher,2013) Engineering skills self-efficacy I can invent new designs

engineering self-efficacy and MSE self-efficacy engineering compared to women.So, self-efficacy in engineering is differentfor men and women (Vogt, Hocevar,Hagedorn,2007; Jones, Paretti, Hein,Knott,2010;Mamaril 2013 ).Researchfindings proved that “women seem toreport a lack of self-efficacy related tospecific areas of skill, knowledge, orability” (Baker, Krause, Yaser, Roberts,Kurpius, 2007; Mamaril 2013). Mamaril’sand Usher’s findings support that whohave better engineering self-efficacy haveperformed better in their academics .



needs. Perhaps the most distinctive featureof non-traditional students is that theysimultaneously combine their collegeeducation with other significant role, suchas caring for dependents and full timeemployment (Deutsch &Schmertz,2011;Obade, 2013).In fact,non-traditional students, when comparedto traditional students, are twice as likelyto leave college without earning a degree(NCES,2002; NCES,2011; Radford,Berkner,Weeless, & Sepherd,2010;Obade,2013). Within a five year period,among the non-traditional students whohad enrolled to obtain a bachelor’s degree(rather than certificates), only 31 % hadearned one after five years, compared with54% of traditional students(NCES,2002).Obade mentioned that it is essential thathigher education stake holders shouldpromote the factors which are essential forstudents success in college. Studentmotivation has gained prominence as aviable explanation for student collegesuccess (Robbins et al.,2004),yet studiesof non-traditional students motivation arelimited(Obade,2013). Obade examinedthe role of achievement motivation inpredicting non-traditional student successusing the “expectancy -value theory ofachievement motivation” (Eccles et al.,1983) and achievement goals theory(Dweck, 1986; Maehr, 1989; Nicholls,1984). Better understanding of theachievement motivation factors of non-traditional students will enable colleges torespond to the needs of these studentsmore appropriately and help them

Non-Traditional College StudentMotivation and Success

Tales of unaccomplished dreams in theform of unfinished college degrees abound.These stories are rampant amongnontraditional students who typicallyexperience higher attrition rates fromcollege when compared to their traditionalcounterparts (National Center forEducation Statistics, NCES, 2002;Obade,2013). Horn defined Non-traditional students as “undergraduateswho have at least one or more of thefollowing characteristics: delayedcollege enrollment after graduatinghigh school, working full time whileenrolled, financially independent,attend college part-time, havedependents, obtained a generaleducation development certificate(GED) rather than a standard highschool diploma, or single parenthood”(Obade, 2013). University students whoare older than 24 years and who ispursuing his graduation and whose maritalstatus is married are also called as non-traditional students (Kasworm & Pike,1994; Obade,2013), hence they are oftenalso called adult learners (Merriam,Caffarella, & Baumgartner, 2007; Obade,2013). Non-traditional students aredistinct from traditional students has theymight have negative pressures of life(Levin,2007;Obade,2013).These studentsare entering post secondary institutionswith a heavier role burden based on their‘adult’ life experiences than traditionalstudents and thus have different sets of

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succeed. Bean and Metzner argued that“although environmental variables(e.g., hours of employment, familyresponsibilities) and academic variables(e.g., GPA) are both important,environmental factors supersedeacademic outcomes when it comes toinfluencing non-traditional studentsintent to leave or stay in college”. Obadeconsidered three motivational factorsnamely balance self-efficacy, subjectivetask value, and achievement goals areincluded as mediators between non-traditional student status and collegesuccess outcomes.

Academic Motivation Scale toMeasure Self-determination

Academic Motivation Scale (AMS) is aninstrument used to measure self -determination. Self-determination theorydescribes three levels of academicmotivation- that are intrinsic motivation,extrinsic motivation and amotivation.AMS instrument has been used reliably tostudy and measure motivation levels instudents at different levels.” Self-determination theory identifies twocauses of desire to study; the need forrecognition, praise and/or money(extrinsic motivation) and the need tofulfil and interest (intrinsic motivation)“ (Deci et.al,1991).Students who areintrinsically motivated show greater interesttowards learning and it is known as deeplearning style. Students who areextrinsically motivated does not showmuch interest towards learning compared

to intrinsically motivated students as thesestudents are referred as ‘surfacelearners’. Rowe (2001) found that firstyear engineering students are extrinsicallymotivated to do engineering and theiracademic success is through surfacelearning style. The students who areintrinsically motivated are independent andthey follow the approach of self-developmental learning. CourseCurriculums of the universities should bein such a way that courses must bedesigned which promotes interest towardslearning. Savage and Birch have recordeda quantifier of student motivation beforeentering the department by designing aquestionnaire and conducted a pilot study,researcher also used informalconversations, and after collecting the dataassessment was done based on the studentresponses. Students who state theirresponses in generic terms are awarded‘1’, Examples of recorded statements are“I have been interested in electronicssince an early age” , “I would liketo study electronics because I feel it isa fast moving industry”. A student’sstatement would be awarded a ratingof “2” ,if students have quoted anexample in their responses it will give anappropriate idea about student’sknowledge. The statements for which itcan be awarded as “2” are “I havebeen learning C and C++” & “I havebuilt some digital electronic projects”.Responses can be awarded as 3 if interestis provided with an evidence whichsupports their response.



The rating was done based on theirresponses it is decided based on whichstatement got highest rating ,15 statementswere assessed twice, there is time gap ofmore than 6 months for the first assessmentand second assessment. The similar kindof assessment was done for the secondtime, during the second assessment alsostudents rated the personal statementsexactly the same. From findings it wasevident that students understood the valueof own learning and still they expectsomeone to guide them in a properdirection so that they can achieve thedesired results. Savage and Birch foundthat students are not confident in classroom discussions, Seven questions fromthe questionnaire found responses arevaried with the student’s year of study thatis student from first year respondeddifferently and student from 2nd yearresponded differently. Informalconversations with first year studentsrevealed that if students have option tochoose their electives for course work theywould achieve better results, this enhancestheir motivation. From the data collectedit was evident that “ no significantdifferences in motivation levels betweenthe different years of study”.Savage andBirch found that motivation and studentperformance are not correlated. Interestingfindings are though students are intrinsicallymotivated before joining the institution, asinstitution has not given opportunity forchoosing their subjects based on theirinterest it ruined their interest of deeplearning style which negatively affected

their performance. “ However, thepreUniversity motivation rating wasuncorrelated with the response to theextrinsic motivation questions (Pearsoncorrelation coefficient of 0.072) andwas only correlated with the responseto the intrinsic motivation questions witha coefficient of 0.13. This gives indicatesthat the personal statement may not bea very accurate instrument in assessingstudents for admission to the department.“ ( Savage & Birch, 2008 ).Personalstatements may not help to infer student’smotivation. Riderer (2015) thesis workexamined the relationship between the“levels of motivation as measured on acontinuum of self-determination ofscience, technology, engineering andmathematics students at sub-urban,single campus community in los-angels”. The study inquired therelationship between student’s motivationlevel , gender, ethnicity. Data was collectedusing a AMS-C questionnaire, The datawas analyzed using statistical methods:multiple linear regression, pearson-correlation, independent sample t-test andMANOVA. It is evident from the analysisthat “gender and ethnicity are predictorsfor several of the self-determinationmotivation continuum’s levels but noneof the motivation levels are predictorsof the overall academic success ofcommunity college STEM students”(Riderer, 2015). Motivation levels ofstudents and their academic grades are notsignificant .” Significant differencesbetween motivational levels across

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genders and ethnicities werediscovered” (Riderer, 2015). Femalestudents scored high in both extrinsicmotivation and intrinsic motivationcompared to males. Teachers instructionalpractices such as facilitating students andcounselling them have positive effect ontheir motivation and outcomes. There is asignificant relation between teachersmotivation and students motivation.Considering the significant relationsbetween teachers and students motivation,researchers have proposed that teachersinstructional styles may play a role asmediators between teachers and studentsmotivation. The premise of SDT (Selfdetermination theory) is that people areactive organisms who develop theirbehaviors and goals, which mean thatpeople are intrinsically motivated to doactions( Ahn). Within SDT, there are fivesub-theories: “ Cognitive Evaluationtheory (CET), Organismic IntegrationTheory (OIT),Causality OrientationTheory (COT), Basic psychologicalneed theory (BPNT), and Goal Contentstheory (GCT)” (Deci & Ryan,1985; Deci& Ryan ,2000). BPNT “addresses theconcept of human beings needs (i.e.,autonomy , competence andrelatedness) at the psychological leveland how those needs relate to intrinsicmotivation and psychological well-being”. Cognitive EvaluationTheory(CET) addresses intrinsicmotivation. “ Intrinsic motivation refersto engaging in an activity for its ownsake “. People who have intrinsic

motivation are doing an activity to attaininnate satisfaction from the activity per se(Ryan & Deci, 2000 a). OrganismicIntegration Theory (OIT) is focused onextrinsic motivation, “ which is the pursuitof an activity to obtain outcomesoutside of the activity”. For instance, Theprinciple of OIT is that not all behaviorsare intrinsically motivated, but rather somebehaviors are motivated by interacting withenvironmental and contextual factors. SDTresearchers divide extrinsic motivation intofour types ,spread along a continuum frommost to least externally controlled; theseare “external regulation, introjectedregulation ,identified regulation , andintegrated regulation”. Furthermore,some studies grouped external andintrojected regulations together, labellingit as non-autonomous ( or controlled )extrinsic motivation; the first level isexternal regulation, where behavior isguided by external control. At this level,the reason why people behave is to obtainrewards or avoid punishment. Suchregulations occurs in the most controllingcontext and people’s interests are notregarded. The second level, introjectedregulation ,is still controlling but less thanexternal regulation. People engage inactivities because they either want to avoidthe feeling of guilt or attain the feeling ofapproval. Because feeling guilt or approvalis derived from the feeling of pressure, thisintrojected regulation is barelyautonomous( Ryan & Deci,2000 a).Identified regulation is less controlling andmore autonomous than the previous level.



According to this regulation, peopleperform acts when they think they arevaluable or important to achieve their goals(Ryan & Deci,2000a).Thus, identifiedregulation is somewhat close to intrinsicmotivation, even though the personalimportance is not from intrinsic value butfrom utility value (Eccles,2005). The lastlevel of extrinsic motivation is integratedregulation, which is the most autonomousand the least controlling form. At this level,people engage in activities because theactivities have been incorporated into theirsense of self. Integrated regulation is verysimilar to intrinsic motivation because thecause of behaviors is from an individual’sinternal need. self-determination theoryhas defined five detailed types ofmotivation intrinsic, integrated, identified,introjected, and external motivation, these5 are clubbed into two major categoriesof motivation named as autonomous andcontrolled motivation (e.g., Ryan &D e c i , 2 0 0 0 a ; Va l l e r a n d , 1 9 9 7 ) .Autonomous motivation is a sum of intrinsicmotivation, integrated motivation andidentified regulation. Controlled motivationconsists of introjected and externalregulation. BPNT elaborates that ifteachers satisfy students basicpsychological needs, students areintrinsically motivated for learning (Deci &Ryan,2000; Ryan , 1995).

Research Gap

1. Studies have largely focused on intrinsicmotivation, but not on extrinsicmotivation.

2. Study mentioned that dissatisfactionoccurs to a student and his motivationlevels decrease as he or she is close tograduation but why these changesoccur are not identified properly.

3. No single set of factors can fullyaccount for why some students fail incollege and why others succeed.

4. There is a limited research on studentmotivation.

The Implication from Review of Literature

1. Universities are focusing on recruitingand marketing efforts, Universities mustimplement strategies to preventdissatisfaction and to improvemotivation.

2. Increase in dissatisfaction of seniorstudents affects their relationships withalumni and participate in future events.

3. Colleges and Universities may need toreconsider how they monitor, measure,and manage student/ customerrelationships.

Conclusion and SuggestionAs the paper is a review paper theresearch data which supports the findingsare missing. The author tries to examinethe findings practically in future research.The Literature on the extrinsic motivationof students is very limited. Researchers canfocus on this area which is challenging andwhich brings productivity to universities.The research on Students should be aninteresting area for young researchers inindia but unfortunately, the papers which

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brings support to students in the Indiancontext are missing.

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on students reactions to a managementclass”,Academy of Management Learning& Education, Vol.3 No. 1,pp.64-85.D. Baker, S. Krause, S. Yasar, C. Roberts,and S. Robinson-Kurpius, “An interventionto address gender issues in a course ondesign, engineering, and technology forscience educators,” J. Eng. Educ., vol. 96,pp. 213-226, 2007.Dahl, D.W.,& Smimou , K.,(2011) “Doesmotivation matter?: On the relationshipbetween perceived quality of teaching andstudents’ motivational orientations”,Managerial Finance, Vol. 37 Issue:7,pp.582-609,https://doi.org/10.1108/03074351111140243 Permanent link tothis document: https://doi.org/10.1108/03074351111140243 Downloaded on:29 October 2017, At: 23:17 (PT).Deci, E. L., & Ryan, R. M. (2000). The‘what’ and ‘why’ of goal pursuits: Humanneedsand the self-determination of behavior.Psychological Inquiry, 11, 227-268.Deci, E.L., Ryan , R.M., Gagne, M.,,Leone, D.R., Usunov, J. and Kornazheva,B.P.(2001),”Need satisfaction, motivation,and well-being in the work organizationof a former Eastern bloc country”,Personality and Social Psychology Bulletin,Vol.27,pp.930-42.F. Pajares, “Self-efficacy beliefs inacademic settings,” Rev. Educ. Res., vol.64, pp. 543-578, 1996.

Fordham(1980) referred to the dimensionsof learning environment as facilitation ofintrinsic motivation.



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Horn, L. J. (1996). Nontraditionalundergraduates: trends in enrollment from1986 to 1992 and persistence andattainment among 1989–90 beginningpostsecondary students (NCES 97–578).U.S. Department of Education, NationalCenter for Education Statistics.Washington, DC: U.S. GovernmentPrinting Office.

Hoover, E. (2010). The science of studentsatisfaction. The Chronicle of HigherEducation.

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Mamaril,A.N, & User,L.E.,(2013).” AnExamination of Students Motivation inEngineering Service Courses”.2013 IEEEFrontiers in Educational Conference.

O. Eris, D. Chachra, H. L. Chen, S.Sheppard, L. Ludlow, C. Rosca, et al.,“Outcomes of a longitudinal administrationof the persistence in engineering survey,”J. Eng. Educ., vol. 99, pp. 371-395,2010.

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R. Suresh, “The relationship betweenbarrier courses and persistence inengineering,” J. Coll. Student Retention,vol. 8, pp. 215-239. 2006-2007.Reeve,J., Deci,E.L., & Ryan, R.M.(2004), “Self-determination theory: adialectical framework for understandingsocio-cultural influences on studentmotivation”,in Van Etten, S. &Pressley,M.(Eds),Big Theories Revisited,

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ANALYSIS OF INTERACTION BETWEEN GLOBALCRUDE OIL PRICE, EXCHANGE RATE, INFLATION

AND STOCK MARKET IN INDIA: VECTOR AUTOREGRESSION APPROACH

Shekhar Mishra,Assistant Professor, Department of Business Management,

C.V. Raman College of Engineering, Bhubaneswar, PIN: 752054,[email protected], [email protected]

Sathya Swaroop Debasish,Associate Professor, Department of Business Administration, Utkal University,

Bhubaneswar,751004, [email protected]


ABSTRACTThe present paper analyses the association between global crude oil price,exchange rate, inflation and stock market in Indian economic scenario. The paperemploys Vector Auto Regression Model on monthly data from April 2001 to March2017. The monthly data has been sourced from official website of Energy InformationAgency (EIA), Reserve Bank of India (RBI) and Bombay Stock Exchange (BSE).The analysis reveals the variables being integrated of Order I (1) and negates thepossible existence of long run relationship among them. The analysis shows thenegative relationship between stock index and inflation and positive associationwith exchange rate and WTI crude oil price. The paper also indicates the indicatesthe WTI crude oil price increase cause increase in inflation and exchange ratedepreciation. Although the increase in WTI crude oil price has a favourable impacton BSE Index, the paper necessitates the need of decrease in reliance upon crudeoil price so as to curb the increase in inflation and exchange rate depreciation.The policymakers need to devise policies to keep control on the increase ininflation and conserve the foreign exchange.

Keywords: WTI, Inflation, Exchange Rate, Vector Auto Regression Model.

INTRODUCTIONOil has always been termed as one of thekey essential commodities in the globaleconomy. Crude oil has always beenconsidered to play a crucial role ineconomic activities at a global level as a

whole. The oil price fluctuations have acapability of bringing in a paradigm shift inpolicies at macroeconomic level anddecisions at microeconomic level of anynation as a whole.

Parikalpana - KIIT Journal of ManagementParikalpana - KIIT Journal of Management, Vol.14(I), 2018

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Owing to key role of oil price fluctuationsin any economy, many researchers haveexamined the interaction between globalcrude oil price and differentmacroeconomic variables like GDP,Foreign Exchange Reserve, Stock MarketFluctuation, Ratio of Export to Import toname a few. However, the outcome ofstudies has varied according to variationsin the assumptions, research methods,variables, frequency of data etc. adoptedby different researchers.

The present paper endeavours to analysethe relationship between global crude oilprice, inflation, exchange rate and stockreturns in India., one of the major oilimporting country not only in Asia, but inthe world. The paper employs Vector AutoRegression Approach to investigate therelationship between the given variables.The variables’ stationarity is tested byemploying, Augmented Dickey Fuller Testand Phillips-Perron Test. AkaikeInformation Criterion is taken as theparameter to estimate the appropriate lagorder for the Vector Auto RegressionApproach. The present paper intends tocontribute to existing literature by analysingthe relationship between the given variablesin India, for which there is a dearth ofstudies.

Literature ReviewA number of researchers have endeavoredto examine the influence of global crudeoil price shocks on macroeconomicvariables of not only developed or oilexporting countries, but also in emerging

and major oil importing nations too. Arinze(2011) when applied simple regressionanalysis on the variables, observed positiverelationship between global crude oil priceand inflation represented by ConsumerPrice Index. Le Blanc and Chin (2004)while estimating the influence of oil pricefluctuations on inflation in U.S., Japan andselect European countries by employingAugmented Phillips Curve ParameterEstimates found minimal effect of oil pricefluctuations on inflation in economies understudy. While comparing the same, theauthors observed oil price having largeimpact on inflation in European countriesunder study as compared to that of UnitedStates. Roger (2005) highlighted the shortrun significance of oil price in Europeancountries by analysing the short run trade-off between GDP and inflation in thecountries under study. In small openeconomies like Ireland, Bermingham(2008) also observed the significant impactof oil price on inflation. For Euro area,Jacquinot et.al. (2009) also recognised oilprice change as one of the major factor inestimating short run inflation. SimilarlyCastillo et.al. also found increase in oilprice leavel causing higher level inflation.

Cologni and Monera (2008) in most ofthe G-7 countries observed significantimpact of oil price on inflation and outputgrowth. The authors observed increase inoil price causing increase in inflation anddecrease in output growth. In Russia, whileexamining the influence of oil price andmonetary shocks on the nation’s economy,Ito (2008), found 1% increase in oil price

Analysis of interaction between global crude oil price, exchange rate...


causing 0.25% increase in real GDP and0.36% increase in inflation. In Taiwan,while applying ARDL Model withAugmented Phillips Curve on the data fromJanuary, 1982 to December, 2010, Chouand Tseng (2011) observed oil price havingsignificant impact on inflation in long term.However in short term, the effect wasinsignificant. By using simple regression,Ali and Ramzan (2012), examined theeffects of oil price on food sector prices inPakistan. In their study, the authorsobserved, positive relationship betweencrude oil price and inflation in food prices.In Nigeria, When Phillip and Akintoye(2006) applied Vector Auto RegressionModel on the data from year 1970 to2003, did not observe any noteworthyinfluence of oil prices on output andinflation. However the authors observedsignificant influence of oil price shocks onexchange rate.

In Vietnam prior to year 1999, Nguyenand Seiichi (2007) observed bidirectionalcausality between real effective exchangerate and inflation level. The authors alsoobserved existence of similar strongrelationship between the given variables inother ASEAN nations like Malaysia,Singapore, Thailand and China. Arie et.al. (2010) also observed bidirectionalcausality between inflation and nominalexchange rate.

While analysing the relationship betweenoil price and industrial production, Cunadoand Prez De Garcia (2003) observed indexof industrial production having significant

influence on oil price change. The influenceof Industrial production on oil pricevolatility was also proved in the works ofSerlettis and Shahmoradi (2005) andEwing and Thompson (2007).

While analysing the influence of oil priceshocks on international stock markets,Jones and Kaul (1996) postulated that inost war period, the reaction of US andCanadian stock prices to oil price shockscan be entirely accounted for by the impactof oil price shocks on real cash flowsalone. By employing Vector AutoRegression Model to examine to examinethe influence of oil price volatility on realstock returns, Perry Sadorsky (1999)significant influence of oil price on stockreturns. When Cong et.al. (2008)employed Multivariate Vector AutoRegression to analyse the relationshipsbetween oil price shocks and China Stockmarkets, the author did not find significantimpact of the independent variables on thereal stock returns of most of the stockindices except manufacturing index andsome oil companies. Similarly Driespronget.al (2008) also observed rising oil pricescausing significant lowering of future stockreturns of developed economies.

Abedeyi et.al. (2012) while estimating theimpact of oil price shocks and exchangerates on real stock returns in Nigeriaobserved negative effects of oil priceshocks on the stock returns. While applyingGranger Causality test, the authorsobserved unidirectional causality runningfrom oil price shocks to stock returns and

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from stock returns to oil price shocks.Korhonen et.al. (2009) postulated that inin oil dependent OPEC Countries higheroil price lead to appreciation of realexchange rate with elasticity of the samewith respect to oil price typically rangingbetween 0.4 and 0.5. Similarly in TurkeyOrtuk et.al. (2008) found international oilprice Granger causing the USD/YTLexchange rate.

The present paper intends to extend theexisting literature by analysing thecombined interaction between global crudeoil price, exchange rate, inflation and stockmarket behaviour in Indian economicscenario.Research Methodology: Data:

To analyse the dynamics of relationshipbetween the given variables, the monthlydata for the period April 2001 to March2017, for BSE Stock Index, ConsumerPrice Index (CPI) as proxy variable forInflation in India, Exchange Rate andGlobal Crude Oil Price is collected. Thedata for Global Crude Oil Pricerepresented by WTI Crude is obtainedfrom official website of Energy InformationAgency. The historical data for BSE StockIndex is obtained from official website ofBombay Stock Exchange. The data forConsumer Price Index and Exchange rateis obtained from official website of ReserveBank of India.Unit Root Test:To ascertain data stationarity AugmentedDickey Fuller Test and Phillips Peron Test

are employed. Before proceeding toanalysis of data Unit Root Test isimperative so as to avoid the problem ofspurious regression. The process followedfor testing the unit root in a given samplecan be explained as follows.

The Augmented Dickey Fuller Test themodified version of Dickey Fuller Testcomprises of 3 models which can beemployed for obtaining required statistics

Equation 1

Equation 2

Equation 3

denotes the variables to be tested for

stationarity and , t isthe time trend.

The ADF test adds the lagged terms ofdependent variable in the regressionequation to take care of deterministic partof higher order correlation.

Phillips Perron (P-P) Test is a non-parametric approach which controls theserial correlation while testing the UnitRoot. The method estimates the non-augmented Dickey Fuller Test Equation asfollows:

Equation 4Where is optional exogeneousregressor which may consists of constantor a constant and trend.



The Phillips Perron (P-P) Test controls theserial correlation and heteroskedasticity inerror terms of regression by modifying thet-statistics of coefficients.

Johanssen Cointegration Test:

The precondition for application of VectorAuto Regression Model is absence ofcointegration or long run relationshipbetween the given variables. There shouldnot be any cointegration among thestationary variables of order I (1). The twonon-stationary series are said to be co-integrated if there exists a stationarity inlinear combination between them or thereexists a long run equilibrium relationshipbetween the given variables. TheJohanssen’s Co Integration approachdeveloped by Johanssen and Juesilius(1990) is employed to calculate the co-integrating regressions and ascertain thelong run equilibrium relationship betweenthe given variables.

The Johanssen Cointegration frameworkemploys the maximum likelihoodprocedure to ascertain the presence of co-integrating vectors in non-stationary timeseries as Vector Auto Regression (VAR)

(Equation 5)

is a vector of non - stationary (log level)variables and C is termed as constant term.The information on the coefficient matrixbetween the levels of is decomposed as

= , where the relevant elements, the

matrix are termed to be adjustmentcoefficients and matrix consists of cointegrating vectors.

The Johanssen’s Co integration approachemploys two test statistics i.e. TraceStatistics () and maximum Eigen valuestatistic () to determine the number of cointegrating vectors (Brooks, 2008). Thetest statistics i.e. and can be expressedas follows.

= +1

(Equation 6)

and (Equation 7)

Where r is expressed as number of cointegrating vectors under null hypothesis andis the estimated value for the ordered Eigenvalue from the matrix. The different cointegrating vectors termed as Eigen Vectorswill be associated with Eigen Value.

The test statistics are then compared withtheir respective critical values givenJohanssen and Juleius (1990). If the teststatistics are greater than their respectivecritical values, then reject the nullhypothesis that there are r co integratingvectors in favour of alternative that thereare r+1 (for and more than r (for

3.3 Vector Auto Regression Model:

The Vector Auto Regression Models wereintroduced and popularised by Shims inthe year 1980. These models are thesystem of regression models and aretermed to be intermediate betweenunivariate time series models andsimultaneous equation models. The term

( , + 1) = − ln( 1 − +1)

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autoregressive in the VAR Models isattributed to the presence of lagged valuesof the dependent variable and the termvector is due to the vector of two or morevariables.

The VAR models depicting the relationshipbetween the given variables under studymay be specified as follows:

Where: lnBSE = natural logarithm of BSEstock indexlnCPI = natural logarithm of ConsumerPrice index proxy variable for inflation.lnExR = natural logarithm of ExchangeRate Variable.lnwti= natural logarithm of WTI, proxyvariable for crude oil price.T = Current Timeα , β , γ and δ are the parameters ofexplanatory variables.Empirical Findings:Unit Root Tests: As observed from Table1, presenting the results of Augmented

0 1 − =1 2 −

=1 3 − =1 4 −

=1 0 1 −

=1 2 − =1 3 −

=1 4 − =1

0 1 − =1 2 −

=1 3 − =1 4 −

=1 0 1 −

=1 2 − =1 3 −

=1 4 − =1

Dickey Fuller (ADF) Test statistics andPhillips Perron (P-P) Test statistics,conducted for the presence of Unit Root,the variables under study are integrated ofOrder (1) and show stationarity at firstorder difference of the variable.However, Inflation represented byConsumer Price Index did not showstationarity at first order differenceaccording to Augmented Dickey FullerTest, but satisfied the stationarity conditionaccording to Phillips Perron Test.

(Equation 8)

(Equation 9)

(Equation 10)

(Equation 11)

Variables

Level I(0) First Order Difference I(1) ADF Statistic PP Statistic ADF Statistic PP Statistic

BSE Index (LBSE) -1.62 -1.92 -12.50 -12.57 Exchange Rate (LExC) -1.75 -1.81 -12.54 -12.51 Inflation (LInf) -1.85 -1.72 -1.03 -10.37 Crude Oil (LWTI) -2.11 -1.99 -9.82 -9.70

Table 1: Unit Root Test Statistics of the Variables



To ascertain the presence of any long run relationship among the given variables,Johanssen Cointegration test is conducted. The results of the test are presented inTable2 and Table 3.

Hypothesized No of CE(S) Eigenvalue

Trace Statistic

0.05 Critical Value Prob.**

None 0.079495 33.7054 47.85613 0.518 At most 1 0.060901 18.21563 29.79707 0.5502 At most 2 0.032733 6.465511 15.49471 0.6405 At most 3 0.001294 0.242066 3.841466 0.6227

Table 2: Trace Test for Johanssen Cointegration TestHypothesized No. of CE(s) Eigenvalue

Max -Eigen Statistic

0.05 Critical Value Prob.**

None 0.079495 15.48977 27.58434 0.7086 At most 1 0.060901 11.75012 21.13162 0.5725 At most 2 0.032733 6.223446 14.2646 0.5847 At most 3 0.001294 0.242066 3.841466 0.6227 Table 3: Maximum Eigen Value Statistics for Johanssen Cointegration Test

The results presented in Table 2 and Table3 confirms the absence of anycointegration or long run relationshipamong the given variables under study. Theoutcome of the cointegration test paves forapplying Vector Auto Regression Modelto analyse the relationship between crudeoil price, inflation, exchange rate and stockreturns in India.

VAR Lag Order Selection CriteriaBefore application of Vector AutoRegression Model, appropriate lag lengthis required to be estimated. The lag lengthis estimate by applying lag order selectioncriteria like Akaike Information Criterion(AIC), Schwarz Information Criterion(SIC) etc. The lag order selection criteriaare presented in Table 4.

Lag LogL LR FPE AIC SIC HQ 0 1522.678 NA 7.28E-13 -16.59758 -16.52742* -16.56914 1 1558.689 70.05286 5.85e-13* -16.81627* -16.46551 -16.67409* 2 1565.857 13.63081 6.44E-13 -16.71974 -16.08837 -16.46382 3 1577.821 22.22806 6.74E-13 -16.67563 -15.76365 -16.30596 4 1589.498 21.18478 7.07E-13 -16.62839 -15.43579 -16.14497 5 1603.22 24.2946 7.26E-13 -16.60349 -15.13029 -16.00633 6 1616.933 23.68044 7.47E-13 -16.57851 -14.82469 -15.8676 7 1633.91 28.57358* 7.42E-13 -16.58919 -14.55476 -15.76453 8 1644.839 17.91496 7.88E-13 -16.53375 -14.21872 -15.59536

Table 4: VAR Lag Order Selection Criteria

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According to Akaike InformationCriterion, Schwarz Information Criterionand Future Prediction Error, theappropriate lag length comes out to be 1.The appropriate lag length is estimatedfrom minimum values of employedinformation criterion and the same is to beused in the model estimation.

Estimation from Vector AutoRegression ModelAfter obtaining the appropriate lag lengthfrom lag order selection criteria, The VARmodel is estimated from the monthly of thevariables from the period, April, 2001 toMarch 2017. The results of the VARmodel estimation are presented in Table 5

LBSE LINFINDIA LEXCINDIA LWTI LBSE(-1) 0.995509 -0.001106 -0.016002 0.037227 -0.02394 -0.00266 -0.00789 -0.03114 [ 41.5810] [-0.41565] [-2.02939] [ 1.19534] LINFINDIA(-1) -0.028233 1.000601 0.059251 0.053787 -0.07567 -0.00841 -0.02492 -0.09843 [-0.37312] [ 118.977] [ 2.37758] [ 0.54647] LEXCINDIA(-1) 0.067841 -0.003397 0.926143 -0.260026 -0.10272 -0.01142 -0.03383 -0.13362 [ 0.66046] [-0.29753] [ 27.3757] [-1.94605] LWTI(-1) 0.002908 0.00484 0.002892 0.915248 -0.01948 -0.00216 -0.00641 -0.02534 [ 0.14930] [ 2.23574] [ 0.45077] [ 36.1254] C -0.096696 0.006717 0.162067 0.773549 -0.26995 -0.03 -0.08891 -0.35116 [-0.35819] [ 0.22387] [ 1.82279] [ 2.20282] R-squared 0.991408 0.99955 0.980243 0.966446 Adj. R-squared 0.991223 0.99954 0.979818 0.965724 Sum sq. resids 0.833313 0.010295 0.090395 1.410083 S.E. equation 0.066934 0.00744 0.022045 0.087069 F-statistic 5365.444 103279.8 2307.049 1339.31 Log likelihood 247.9889 667.5954 460.1157 197.7564 Akaike AIC -2.544386 -6.938171 -4.765609 -2.018392 Schwarz SC -2.459248 -6.853033 -4.680471 -1.933254 Mean dependent 9.403295 4.515188 3.915369 4.074259 S.D. dependent 0.714459 0.346983 0.155178 0.470296 Determinant resid covariance (dof adj.) 6.02E-13 Determinant resid covariance 5.42E-13 Log likelihood 1613.226 Akaike information criterion -16.683 Schwarz criterion -16.34244

From the estimated results presented inTable 5, R2 of 0.9914 indicates 99% ofvariation in BSE Index is explained byexplanatory variables. The adjusted R2 of

0.9912 i.e. 99% indicates the robustnessof explanatory variables in explaining thevariation in BSE Index. Similarly, R2 forExchange Rate, Inflation and Crude Oil



Price of 0.9995, 0.98025 and 0.9664respectively explains 99%, 98%, and 96%variations in the dependent variables byexplanatory variables. The adjusted R2 of99%, 97% and 96% shows the robustnessof explanatory variables in explaining thevariations in inflation, exchange rate andcrude oil price respectively. To interpretthe individual parameters of the variables,

Block F Test is employed to analyse thecollective influence of the explanatoryvariables.Block F- TestThe estimation from Block F Test ispresented in Table 6. The Lag exclusiontest points towards the parameters of alllag 1 variables being significant as well asjointly significant.

Chi-squared test statistics for lag exclusion: Numbers in [ ] are p-values

Lag 1

LBSE LINFINDIA LEXCINDIA LWTI Joint 21461.78 413119.4 9228.197 5357.241 458878.1

[ 0.000000] [ 0.000000] [ 0.000000] [ 0.000000] [ 0.000000] df 4 4 4 4 16

Table 6: VAR Lag Exclusion Wald Test

Granger Causality TestThe estimated results from the GrangerCausality Analysis is presented in Table 7.From the estimated results it can beobserved that there exists a unidirectional

causality running from Grobal crude oil priceto inflation, Stock index and inflation toexchange rate and from exchange rate toglobal crude oil price. Apart from there isabsence of causality among the rest variables.

Dependent variable: LBSE Excluded Chi-sq df Prob.

LINFINDIA 0.139222 1 0.7091 LEXCINDIA 0.436213 1 0.509

LWTI 0.022289 1 0.8813 All 0.954327 3 0.8123

Dependent variable: LINFINDIA Excluded Chi-sq df Prob.

LBSE 0.172767 1 0.6777 LEXCINDIA 0.088525 1 0.7661

LWTI 4.998538 1 0.0254 All 13.694 3 0.0034

Table 7: Granger Causality Test of the Variables.

129All 13.694 3 0.0034

Dependent variable: LEXCINDIA Excluded Chi-sq df Prob.

LBSE 4.118432 1 0.0424 LINFINDIA 5.652864 1 0.0174

LWTI 0.203195 1 0.6522 All 10.22864 3 0.0167

Dependent variable: LWTI Excluded Chi-sq df Prob.

LBSE 1.428849 1 0.232 LINFINDIA 0.298628 1 0.5847 LEXCINDIA 3.787104 1 0.0516

All 11.53597 3 0.0092

Impulse Response Function (IRF)The Impulse Response Function for givenVector Auto Regression Model for thevariables is presented in Figure 1. FromImpulse Response Graph it can beobserved that Stock Index to global crudeoil price and exchange rate has remained

positive but for inflation the response hasremained negative. The response ofexchange rate has remained positive toimpulse from inflation and global crude oilprice but negative to Stock index. TheInflationary index initially remainednegative and then become positive to

Figure 1: Impulse Response Graph for Vector Auto Regression Model



impulse from stock index and for exchangerate the response of inflation is initiallypositive and then becomes negative. Theresponse of inflation to WTI crude oil pricehas remained positive all throughout. Theresponse of WTI Crude Oil Price

remained positive to impulse from inflationand Stock index but became negative toimpulse from exchange rate. From theimpulse response graph it can be observedthat the impulse responses have rarelyreturned to equilibrium path.

Variance Decomposition of LBSE: Period S.E. LBSE LINFINDIA LEXCINDIA LWTI 1 0.066934 100 0 0 0 2 0.093908 99.98252 6.49E-05 0.016717 0.000694 3 0.114111 99.94491 0.000176 0.052687 0.002224 4 0.130742 99.89029 0.000298 0.10491 0.004502 5 0.14505 99.82142 0.000408 0.170721 0.007453 6 0.157683 99.74074 0.000491 0.247758 0.01101 7 0.169028 99.65041 0.00054 0.333935 0.015117 8 0.179341 99.55231 0.000555 0.427413 0.019723 9 0.188799 99.4481 0.000541 0.526574 0.024785 10 0.197535 99.33923 0.000508 0.630001 0.030264 Variance Decomposition of LINFINDIA: Period S.E. LBSE LINFINDIA LEXCINDIA LWTI 1 0.00744 0.062354 99.93765 0 0 2 0.010551 0.051383 99.78534 0.010896 0.152383 3 0.012968 0.039073 99.45054 0.040325 0.47006 4 0.015037 0.029132 98.96345 0.091895 0.915527 5 0.01689 0.025711 98.34939 0.168181 1.456722 6 0.018594 0.033151 97.6295 0.270732 2.06662 7 0.020191 0.055796 96.82134 0.400137 2.722728 8 0.021704 0.097844 95.9395 0.556126 3.406532 9 0.023153 0.163232 94.9961 0.737699 4.102966 10 0.024548 0.255559 94.00128 0.943252 4.799911 Variance Decomposition of LEXCINDIA: Period S.E. LBSE LINFINDIA LEXCINDIA LWTI 1 0.022045 30.3372 0.592517 69.07029 0 2 0.030465 32.15236 0.754872 67.08625 0.006524 3 0.036488 33.94182 0.938337 65.09845 0.021392 4 0.041234 35.69575 1.141906 63.1181 0.044241 5 0.045151 37.405 1.364428 61.1559 0.074667 6 0.048477 39.06126 1.604627 59.22188 0.112234 7 0.051356 40.65713 1.861125 57.32527 0.156479 8 0.053886 42.18617 2.132474 55.47444 0.206918 9 0.056133 43.64294 2.417174 53.67683 0.263055 10 0.05815 45.02301 2.713704 51.93891 0.324386

Table 8: Variance Decomposition of the Variables

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Variance Decomposition of LWTI: Period S.E. LBSE LINFINDIA LEXCINDIA LWTI 1 0.087069 2.607307 0.574477 1.291969 95.52625 2 0.119235 3.799415 0.559453 2.032729 93.6084 3 0.141852 5.217531 0.538109 2.875152 91.36921 4 0.159571 6.837907 0.511845 3.775046 88.8752 5 0.174264 8.632657 0.482169 4.692678 86.1925 6 0.186914 10.57167 0.450597 5.594171 83.38357 7 0.198104 12.6243 0.418576 6.452206 80.50492 8 0.208208 14.76077 0.387421 7.246105 77.60571 9 0.217477 16.95318 0.358274 7.961452 74.7271 10 0.226084 19.17618 0.332088 8.589416 71.90232 Cholesky Ordering: LBSE LINFINDIA LEXCINDIA LWTI

Stability of the Vector Auto RegressionModelFrom the Auto Regressive Inverse Rootsof the Vector Auto Regression Model, itcan be observed that the polynomial rootsare within the unit circle indicating thestability of the model.Table 9: Auto Regressive Inverse Rootsof VAR Model.

Root Modulus 0.997063 0.997063

0.962937 - 0.018370i 0.963113 0.962937 + 0.018370i 0.963113

0.914563 0.914563 No root lies outside the unit circle. VAR satisfies the stability condition.

Figure 2: Graph of AR Inverse Root.

Conclusion

The present paper employed Vector AutoRegression Model to analyse and estimatethe association between global crude oilprice, exchange rate, inflation and stockindex in Indian economic scenario. Fromthe paper it can be well observed that thereis a negative association between stockindex and inflation which may be attributedto decrease in consumer purchasing powerdue to increase in inflation and in turn hasa negative impact on the stock index.There exists a positive relationshipbetween BSE Index and Exchange Rateand WTI Crude Oil Price. There exists anegative association between inflation andBSE Index and exchange rate. Theincrease in WTI crude oil price raises thecost of production for an oil importingcountry and thus causes increase ininflation and the same is well evident incase of data pertaining to India presentedhere. Similarly depreciation in exchangerate also causes increase in inflation. Theincrease in WTI crude oil price also causesdepreciation in exchange rate value which



may be attributed to increase in demandof U.S. Dollar in which majority of tradeis done.ReferencesAdebiyi, M. A., Adenuga, A. O., Abeng,M. O. and Omanukwue, P. N. (2012).“Oil Price Shocks, Exchange Rate andStock Market Behavior: EmpiricalEvidence from Nigeria.”InternationalJournal of Economics and Statistics, Vol.22 (13), pp. 1-36.Ali, S. A., Ramzam, M., Razi, M., &Bhatti, A. G. (2012). “The Impact of OilPrices on Food Inflation in Pakistan.”,Interdisciplinary Journal of ContemporaryResearch in Business, 3(11).Bermingham, C., (2008), “Quantifying theimpact of oil prices on Inflation.”, Centralbank and financial services authority ofIreland research technical paper.Castillo, P., Montoro, C. & Tuesta, V.,(2010), “Inflation, oil price volatility andmonetary policy.”, [Online] Available at: http://core.kmi.open.ac.uk/download/pdf/6616677.pdf [Accessed 20 January 2017].Cong, R.G., Y.M., Wei, J.L., Jiao, andY.Fan, (2008). “Relationships between OilPrice Shocks and Stock Market: AnEmpirical Analysis from China.”, EnergyPolicy, Vol-36 (9).Chou, K. W. & Tseng, Y. H. (2011). “Oilprice pass-through into CPI inflation inAsian emerging countries: the discussionof dramatic oil price shocks and high oilprice periods.”, Journal of Economics,Finance and Management Sciences, Vol.2(1), pp- 1-13.

Cologni, A., & Manera, M. (2005), “OilPrices, Inflation and Interest Rates in aStructural Cointegrated VAR Model forthe G-7 Countries.”, Working Paper.Cunado J. and Perez de Garcia F., (2003).“Do oil shocks matter? Evidence fromsome European countries.”, EnergyEconomics, Vol. 25 pp-137-154.Driespronga, G., B. Jacobsenb, and B.Maat (2003), “Striking Oil: AnotherPuzzle?”, Journal of Financial Economics,Vol 89(2), pp-307-327.Ewing, B. & Thompson, M., (2007), “Dynamic cyclical co-movements of oilprices with industrial production, consumerprices, unemployment, and stock prices.”,Energy Policy, Vol. 35, pp- 5535–5540.Ito, K. (2008)., “Oil Price and the RussianEconomy: A VEC Model Approach.”,International Research Journal of Financeand Economics, Vol. 17, pp- 68-74.Jacquinotl, P., Kuismanen, M. & Mestre,R., (2009), “An assessment of theinflationary impact of oil shocks in the Euroarea.”, The Energy Journal, Vol. 30(1),pp- 49-84.Jones, C.M., and Kaul, G., (1996), “Oiland the Stock Markets”, The Journal ofFinance, Vol. 11(2).Korhonen. I., and T. Juurikkala (2009).,“Equilibrium Exchange Rates in OilExporting Countries”., Journal ofEconomics and Finance, Vol 33(1).LeBlanc, M., & Chin, M. D. (2004)., “DoHigh Oil Prices Presage Inflation? TheEvidence from G-5 Countries.” EconomicResearch Service.

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Nguyen, T. and F. Seiichi, (2007).,“Impact of the real exchange rate on outputand inflation in Vietnam. A VARapproach”, Discussion Paper No.0625.Ozturk I., M., Feridun and H. Kalyoncu(2008), “Do Oil Price affects the USD/YTL Exchange Rate: Evidence fromTurkey”, Prevredna Kretanja IEconomska Politika 115.Philip OA, Akintoye AV (2006). “Oil PriceShock and Macroeconomic Activities inNigeria.”, International Journal of FinancialEconomics., Vol. 3, pp-28-34.

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IMPACT OF MACROECONOMIC FACTORS ONINDIAN STOCK MARKET

Keshav GargAmity Business School, Amity University, Noida, [email protected]

Rosy KalraAssociate Professor, Amity Business School, Amity University, Noida

[email protected]


ABSTRACTThis study is on Impact of Macroeconomic factors on Indian stock market. The aimof the study is to analyze the relationship between selected macroeconomic factorsand Indian stock market price. This study may also facilitate to the investors inbuying and selling decisions of securities as in the study the effect of the selectedmacroeconomic variables on the stock market price returns is been analysed. Thisstudy may also be make investors capable to take better decision by viewing therelationship between the dependent (Sensex) and independent variables(Macroeconomic factors).The methodology is used for the study is descriptive and Pearson correlation isused to find the relationship between the dependent and independent variables.Data over the period of 1991 to 2017 is used for the study.The result shows that there is a positive relationship between the sensex andmacroeconomic factors except avg. inflation and unemployment rate as they shownegative relationship.Key words : Stock market, Economic factors, SEBI

INTRODUCTION

The Indian stock market had seen variousup-down since 1991, after the governmentimplemented the Liberalization,Privatization and Globalization Model inIndia. This model has connected everycountry with other countries and as a resulta single market is created. And thus fromthe economic point of view the importanceof stock market is growing as it helps inmovement of capital in rising and

developed nations, prompting thedevelopment of industry and business ofthe country. There is a significant role ofIndian capital market in the Indianeconomy growth. A small movement in thestock market affects the performance ofeconomy. Investors regardless of whetherIndians or outsiders can contribute or takethe assets (funds) for capital appreciationin the capital market. An investor considers


135

various factors before and at the time ofinvesting his funds into the stock market.These various factors may include pastperformance of a company, return onindex or by company, return on assets orequity, free cash flow, internalmanagement, various macroeconomicfactors like GDP, inflation, interest rate,unemployment rate etc.

It is believed that return on stock marketis changed as change or fluctuations in themacroeconomic factors. Somemacroeconomic factors are significantlyaffecting the return on stock whereas somehave mild affect. The market can beclassified into two i.e. Primary market andsecondary market. Primary and secondarymarket both are inter-related to each otheras primary market creates secondarymarket. In the primary market variouscompanies as well as government sell thesecurities first time in the market and whenthese securities further sold in the marketthat market called as secondary market.

The SENSEX, propelled in 1986 iscomprised of 30 of the most effectivelyexchanged stocks in the market. Truth betold, they represent a large portion of theBSE’s market capitalisation. They speakto 13 areas of the economy and arepioneers in their individual enterprises. TheSENSEX is one of the benchmark in India.The SENSEX is considered an essentialindicator of the Indian securities exchangebecause the BSE is the main exchange ofthe Indian resold market. It is the most asoften as possible utilized indicator while

giving an account of the condition of themarket.

The major role of an index is to catch thechange in the price. Along these lines, astock index will mirror the change in theprice of stock, whereas index of bondcatches the way in which bond costs goup or down. In the event that the SENSEXrises, it shows the market is doingadmirably. Since stocks should reflect whatorganizations hope to earn later on, a risingindex demonstrates that investor expectbetter profit from organizations.Furthermore, it is additionally a measureof the condition of the Indian economy.

Trends in Indian Stock Market

The stock market of India has an importantposition in Asia as well as in the world.Across the world the Bombay StockExchange (Sensex) is one of the earliestexchanges whereas if we look at NationalStock Exchange is considered to be bestin terms of advancement & sophisticationof technology. After the globalization Indianstock market pace increased too fast andas a result it becomes a centre of attractionfor investors over the world. The entire ofnineties were utilized to investigation andadjust a productive and successfulframework, and from the time ofglobalization, the stock market began towork proficiently and demonstrated itsnew statures, at various periods of itsadvancement. Indian stock market hasseen various ups and downs there weretimes when the Indian stock marketaccomplishes new statures, breaking its

Impact of macroeconomic factors on Indian stock market


past records and there is time likewisewhen stock market dives up to itsoutrageous. As stock market index is anessential piece of the economy, these upsand downs cannot be ignored as aneconomy is affected by the several policiesand other unavoidable situations createdin an economy.

Macroeconomic Factors

Ø Inflation is an ascent in costs or priceof a few things over a period of time.It is estimated through differentindices and each gives particular dataabout the costs of things that it shows.The index could be the ConsumerPrice Index (CPI) or WholesalePrice Index (WPI) for indicatedclasses of individuals like farminglaborers or urban non-manualworkers. Every one of the index ismade in a particular way with aspecific year as the base year and theyconsider the value change over a year.

Ø The Unemployment rate is describedas the level of unemployed workersin the aggregate work force. Workersare viewed as jobless in the event thatthey as of now don’t work, in spiteof the way that they are capable andwilling to do as such. The aggregatework force comprises of allemployed and jobless individualsinside an economy.

Ø An exchange rate is the cost of acountry’s cash as far as money. In thisway, a exchange rate has twosegments, the country’s own money

and foreign currency, and can be citedeither straightforwardly or in aroundabout way. In an immediatecitation, the cost of a unit of remotecash is communicated as far as thecountry’s own money. In aroundabout citation, the cost of a unitof country’s own is communicatedregarding the foreign currency. Thewhole procedure of sending out andbringing in procedure of any nation isentirely subject to the exchange rateof money value of the country.

Ø Gold is a substitute speculation roadfor Indian financial specialists. Thesignificance of gold has beenexpanded in the present worldbecause of the monetary emergencyin the present financial world. Thefinancial specialists are puttingresources into the Gold. Gold is dealtwith as an elective speculation road.It is frequently expressed that gold isthe best protecting acquiring powerover the long haul.

Ø Foreign Exchange Reserve or ForexReserves is the reserves ofdifferent currencies like JapaneseYen, United States Dollar, pound,Euro etc., control and kept bythe financial organization i.e ReserveBank of India and numerousalternative financial authorities asaffirmed by the govt... The reasonbehind to keep up this sort ofreserves is to manage any unexpectedfinancial stuns and crises.

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Ø Gross Domestic Product (GDP) isthat the quantitative live of theoverall financial movementin an economy. In significantly moreparticular terms, GDP speaks to themoney related estimation of theconsiderable number of products andservices created or produced in aneconomy inside a timeframe andinside a country’s land limit. Grossdomestic product is measures thathelp in estimating the execution of aneconomy.

Securities and Exchange Board ofIndia

On 12 April, 1988 a board was set up bythe Govt. of India named as “Securitiesand Exchange Board of India” (SEBI), asa between time administrative body toprogress, arrange and sound advancementof securities and for saving and protectingthe interest of investors and shareholders.Before getting a statutory status throughan announcement as on January 30, 1992the Securities and Exchange Board of Indiawas to work inside the general definitivecontrol of the Ministry of Finance,Government of India.

The declaration was later changed by alaw of Parliament known as the Securitiesand Exchange Board of India Act, 1992.Objectives were in concurrence with theformation of SEBI, which were for theimprovement of capital market. The capitalmarket had seen an immense advancementin the midst of 1980’s was depictedparticularly by the growing help of general

society. This regularly assists the investorsin the market and market itself.Capitalisation incited different types of actsof neglect concerning associations, expertsin the market, shareholders or investors,and others related with the securitiesdisplaying. The powerful instances of theseacts of neglect in corporate segment bythe self – styled exchange lenders, casualprivate game plans, device of expensesand casual premium on new issues andnon-adherence of game plans of theCompanies Act and encroachment of rulesand controls of stock exchanges andposting essentials delay in movement withthe offers et cetera. These demonstrationsof disregard and out of the line exchanginghones have divided theorist sureness andcopied money related pro grievances.Role of SEBIThe fundamental reason behind Securitiesand Exchange Board of India was createdis to provide a platform to support betterexchange of securities through thesecurities markets. It similarly means toreinforce competition and bolsterheadway. This state joins the rules andcontrols associations, theirinterrelationships, establishments,practices, instruments and approachframework. This state goes for tending tothe fundamental necessity of the three socialevents which essentially constitutes themarket, viz., the patrons of securities(Companies), the monetary pros and themarket middle people.ü To the investors, it provides to give a

business focus in which they can



irrefutably suspect bringingresponsibility & accountability whichthey require in an effective andefficient and very simple reasonableway.

ü To the various investors it certainlyneeds to give confirmations for theirrights and premiums throughadequate, correct and genuineinformation and revelation ofinformation on a reliable introduce.

ü To the mediators, it should offer acentred, professionalized anddeveloping business division withattractive and beneficial nuts and boltsso they can render better help for theexaminers and budgetary patrons.

Literature Review

R. Mookerjee and Q. Yu (1997) used themonthly data of four macroeconomicfactors such as Broad money supply,foreign reserve, narrow money supply andexchange rate over the period of Oct 1984to Apr 1993 to analyse the relationshipbetween macroeconomic factors andSingapore stock returns. Their studyshowed that foreign reserve, broad andnarrow money supply had a long runassociation with stock market returnsthough exchange rate didn’t show l;ongterm relationship.

Sangeeta Chakravarty (2005) conducteda study that aim to know the nexusbetween macroeconomic factors andIndian stock market prices over the periodof 1991-2005. The secondary monthlydata was used for the study. She revealed

positive impact of inflation, money supplyand index of industrial production on Indianstock return by using Granger Causality.Whereas it was found that there was norelationship of exchange rate, gold priceswith the Indian stock market.

K. Pal and R. Mittal (2011) have takenquarterly data over the period of Jan 1995to Dec 2008 to conduct a study onrelationship between Indian stock marketand macroeconomic factors with theJohansen’s co-integration framework.Their study showed that there was a long-run relationship exists between themacroeconomic factors and Indian stockmarket. The outcomes likewisedemonstrated that exchange and inflationrate significantly affect BSE Sensex yetgross domestic saving and interest ratewere not significant.

A. Pethe and A. Karnik (2000) have takenmonthly data over the period of Apr 1992to Dec 1997 to conduct a study onrelationship between Indian stock marketand macroeconomic factors using errorcorrection model and co-integration. Theirstudy showed that the condition ofeconomy and the stock market pricesdon’t show a long run relationship.

Menike (2006) analysed a study on howmacroeconomic factors affect stock pricesin developing Sri Lankan Stock Market.Secondary data was used from 1991 to2002. Multivariate regression was used bythem on all factors for each stock. Thestudy too discovers that there is arelationship between stock market in the

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Colombo Stock Exchange andmacroeconomic factors. It is also revealedthat there is negative relationship betweenmacroeconomic factors like Inflation rate,exchange rate and stock market inColombo Stock Exchange.

Zhao (1999) conducted a study that aimto know the connection between Chinesefinancial market that consists of factors likeindex of industrial production and inflation.The secondary data was used for the studyover the period of 1993 to 1998. Theoutcomes show that both expected growthin the industrial production and inflationhave negative associations with the stockmarket prices.

Wong et al. (2005) analyzed a study toknow whether macroeconomic factorsaffect the stock prices of Singapore andUnited States. They analyze the long runequilibrium relationships between themacroeconomics factors and the twocountries. The secondary data was usedover the period of Jan 1982 to Dec 2002.They found through a co-integration testthat United States Stock’s prices don’tshow relationship with the money supplyand interest rate whereas there is a longrun equilibrium relationship with theSingapore stock’s prices of those factors.

Pimenta Junior and Hironobu Higuchi(2008) have taken monthly data over theperiod of 1994 to 2005 to conduct a studyon the relationship between Ibovespa andmacroeconomic factors such as inflationrate, interest rate and exchange rate usingGranger causality test, Impulse and

Response functions analysis, unit root test,and variance decomposition analysis. Thestudy found that the Exchange rate wasvariable with a more advanced amount ofcausality in the Ibovespa, in any case, thisoutcome is factually satisfactory andimpressive; along these lines, none of thefactors chose introduced causalityconnection to the index.

Maku and Atanda (2009) conducted astudy that aim to analyzed the short-runand long-run impact of macroeconomic onNigerian capital market. Secondary datawas used from 1984 to 2007. Themacroeconomic factors (dependentvariable) used for the study were realoutput, exchange rate, inflation rate andmoney supply. The outcomes of the study,acquired utilizing Error Correction Modeland ADF, revealed that the share index ismore receptive to chose factors and alongthese lines have noteworthy effect on shareindex.Sezgin Acikalin, Rafet Aktas, and SeyfettinUnal (2008) have been taken quarterlydata over the period of 1991 to 2006 toanalyse the relationship between themacroeconomic factors and the stockmarket of Turkey named as Istanbul StockExchange. To find the relationship theyused the secondary data. They selectedfour macroeconomic factors i.e. foreignexchange rate, production level, currentaccount deficit, and interest rate of Turkey.They used the vector error correlationmodel and cointegration test and foundedthe long run stable relationship. With thehelp of casualty test, they found



unidirectional relationship between Turkeystock market and macroeconomicvariables and change in the current accountdeficit, production level, and foreignexchange rate also affect the Istanbul StockExchange.

Joseph Tagne Talla (2013) had takenmonthly data over the period of 1993 to2012 to analyse the impact ofmacroeconomic factors on the stockmarket returns, a case of StockholmStock Exchange. For the study secondarydata was used of four macroeconomicvariables i.e. exchange rate, consumerprice index, money supply, and interestrate. Multivariate Regression Model, unitroot test and Granger causality test wereused to find the relationship. The resultsshow that both currency depreciation andinflation have significant negative impact onstock market returns. Whereas interestrate do not have any significant relationshipbut it affect the stock market returnsnegatively. Money supply has positiverelationship with the stock market returnsthough not significant. No unidirectional,using Granger Causality, is found betweenthe selected macroeconomic variables andthe stock market returns.

Ngoc (2009) has taken monthly data overthe period of 2001 to 2008 to analyze therelationship between Vietnamese stockprices and macroeconomic factor i.e.interest rate. In the study he additionallydemonstrates the nexus betweenVietnamese stock prices and USmacroeconomic factors. Statistically, hediscovered imperative associations

between the money markets, domesticproduction sector and Vietnamese stockprices and Vietnamese stock price is alsosignificantly affected by the USmacroeconomic.

Mgammal (2012) conducted a study thataim to analyze the effect of variousmacroeconomic variables like inflation rate,exchange rate, and interest rate on thestock price of two gulf countries i.e.Kingdom of Saudi Arabia and United ArabEmirates. The secondary data was usedfor the study over the period of Jan 2008to Dec 2009. The study revealed that inthe short run the stock prices index 0ofthe Kingdom of Saudi Arabia is negativelyinfluenced by the exchange rate whereasUnited Arab Emirates is positively affectedby the exchange rate. The outcomes ofstudy in long run showed that stock pricesindex of United Arab Emirates is negativelyaffected by the exchange rate.

Research Methodology

Objective

To measure the relationship between thestock market and selectedmacroeconomic variables.

Variables Selectedü Dependent Variable

Ø Sensex

ü Independent Variables

Ø Unemployment Rate

Ø Exchange Rate

Ø Average Inflation Rate

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Ø Gold Prices

Ø Foreign Exchange Rate

Ø Gross Domestic Product (GDP)

Limitations of the StudyThis study is conducted on the Stockmarket indicator’s sensex using themacroeconomic factors. This study coversonly six macroeconomic factors tomeasure the relationship. The study isprepared within a limited time.

Sources of Data

Secondary data is used to analyzed therelation between the sensex and selected

macroeconomic factors over the period ofJan 1991 to Dec 2017. Data was collectedfrom Reserve Bank of India, World Bank,Bombay Stock Exchange.

Data Analysis

A stock market is affected by severalfactors so it is necessary to analyze thosefactors. In this study it is tried to do analyzehow the different macroeconomic factorsaffect stock market indicator ‘Sensex’ andhow it impact the investors’ decision andtheir investment. To analyse therelationship Sensex as a dependentvariables and all macroeconomic factorsas a independent variables are selected.

A. Sensex and GDPCorrelations

Sensex GDP_Rate Sensex Pearson Correlation 1 .408*

Sig. (2-tailed) .035 N 27 27

GDP_Rate Pearson Correlation .408* 1 Sig. (2-tailed) .035 N 27 27

*. Correlation is significant at the 0.05 level (2-tailed).

The above table shows the relationshipbetween the Sensex and GDP. It isfounded that there is a positiverelationship between the sensex and GDP

rate, means increase in the GDP rate willalso lead to increase in the sensex or thestock market. The relationship betweenboth is 0.408.

B. Sensex and Average InflationCorrelations

Sensex Avg_Inflation Sensex Pearson Correlation 1 -.169

Sig. (2-tailed) .399 N 27 27

Avg_Inflation Pearson Correlation -.169 1 Sig. (2-tailed) .399 N 27 27



The above table shows the relationshipbetween the Sensex and Average Inflation.The result shows that there is negativerelationship between the avg. inflation and

sensex, means increase in the inflation rateleads to the decrease in the stock marketindicator. The relationship between bothis -0.169.

C. Sensex and Unemployment

Correlations

Sensex UnEmp_Rate_No

Sensex Pearson Correlation 1 -.734** Sig. (2-tailed) .000 N 27 27

UnEmp_Rate_No Pearson Correlation -.734** 1 Sig. (2-tailed) .000 N 27 27

**. Correlation is significant at the 0.01 level (2-tailed).

The above table represents therelationship between the Sensex andUnemployment rate. The resultindicates that there is a negativerelationship between the unemployment

rate and the sensex as the correlationbetween factors is -0.734. It means thatincrease in the unemployment rate leadsto the decrease in the stock marketindicator i.e sensex.

D. Sensex and Exchange Rate

Correlations

Sensex Exchange_Rate_US_IND

Sensex Pearson Correlation 1 .794** Sig. (2-tailed) .000 N 27 26

Exchange_Rate_US_IND Pearson Correlation .794** 1 Sig. (2-tailed) .000 N 26 26


The above table represents the relationshipbetween the Sensex and exchange rate. Itis founded that there is positive relationshipbetween the exchange rate and sensex as

the correlation between factors is 0.794.It shows that the change in the exchangerate will result in change in the stock marketprice.

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C. Sensex and Foreign Reserve

Correlations

Sensex Forex_Reserve_in_Billion

Sensex Pearson Correlation 1 .959** Sig. (2-tailed) .000 N 27 27

Forex_Reserve_in_Billion Pearson Correlation .959** 1 Sig. (2-tailed) .000 N 27 27


The above table represents the relationshipbetween the Sensex and Foreign Reserve.The result indicates that there is a positiverelationship between the foreign reserve

and sensex. It can be said that increase inthe foreign reserve will lead to increase inthe sensex or stock market prices. Therelationship between both is 0.959.

C. Sensex and Gold Prices

Correlations Sensex gold_prices Sensex Pearson Correlation 1 .918**

Sig. (2-tailed) .000 N 27 27

gold_prices Pearson Correlation .918** 1 Sig. (2-tailed) .000 N 27 27


The above table represents the relationshipbetween the Sensex and gold prices. It isfounded that there is positive relationshipbetween the gold prices and sensex as thecorrelation between factors is 0.918. Itcan be interpreted that change in the goldprices lead to change in the stock marketprices, means increase in the prices of goldleads to increase in the stock market pricesand vice-versa.

Findings

Ø The correlation between Sensex andGDP is positive that means GDPaffects the movement in the sensex.Increase in GDP certainly leads toincrease in the sensex and vice versa.

Ø The relationship between thedependent variable i.e sensex andindependent variable i.e averageinflation is negative. That shows



negative movement in both variables.If there is an increase in independentvariable, dependent variable behavesreversely.

Ø The correlation between Sensex andUnemployment rate is found to benegative as the correlation is -0.734.It means that increase in theunemployment rate leads to thedecrease in the stock market pricesor in sensex.

Ø The relationship between exchangerate and sensex is found to be positiveas the correlation between factors is0.794. Increase in the exchange ratemay be result in the increase in thesensex as the relationship is positivebetween variables.

Ø The correlation coefficient is 0.959that shows a positive relationshipbetween the two variables i.e. sensexand foreign reserve. Increase in theforeign reserve will lead to increasein the sensex or stock market prices.

Ø The relationship between Sensex andgold prices is positive as thecorrelation coefficient is 0.918. So,with the increase in the gold prices,the stock market prices will alsoincrease or there is up movement onthe sensex.

Conclusion

To support the macroeconomic variablesthe govt. and the policy makers need tomake strategies and policies thatcomplement with macroeconomicframework and further support the Indian

stock market. In the report I study howmacroeconomic factors affect the Indianstock market using the six factors i.e.unemployment rate, average inflation rate,gold prices, gross domestic product,exchange rate, and forex reserve.

It can be concluded all the macroeconomicfactors has been taken for the study havethe relationship with the Indian stockmarket and all the factors whether inpositive and negative way affect themovement in the stock market prices. BothUnemployment rate and average inflationhave inverse relationship with the sensexwhereas all other factors show positiverelationship.

In the report it has also been founded theglobal recession in the early 2000s and inthe 2008 hit the Indian stock market, thisis due to the macroeconomic variables asvariables like gross domestic product felldown drastically and other variables arealso get affected.

Further to have better returns on the stockmarket and to retain the Indian investorsand foreign investors, government andother policy makers are needed to makepolicies in complement to themacroeconomic variables.

REFERENCES

Higuchi, R. H.; Pimenta Junior, T.relationship between Ibovespa andmacroeconomic factors. RevistaEletrônica de Administração, v.14, n. 2.Joseph Tagne Talla (2013), Impact ofMacroeconomic Variables on the Stock

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Market Prices of the Stockholm StockExchange (OMXS30), JonkopingInternational Business School.Maku, O.E. and Atanda, A.A. (2009),“Does macroeconomic variables exertshock on the Nigerian Stock Exchange”,Munich Personal RePEc Archive, PaperNo. 17917.Menike. (2006). The Effect ofMacroeconomic Variables on Stock Pricesin Emerging Sri Lankan Stock Market.Sabaragamuwa University Journal, 2, 50-67.Mgammal, M. H. (2012). The Effect ofInflation, Interest Rates and ExchangeRates on Stock Prices Comparative StudyAmong Two Gulf Countries. InternationalJournal of Finance and Accounting, 1(6),179 to 189.Mookerjee, R. and Yu, Q. (1997).Macroeconomic Variables and StockPrices in small Open Economy: The caseof Singapore, Pacific-Basin FinanceJournal, 5: 377-788.Ngoc, K. H. (2009). The impact ofmacroeconomic indicators on Vietnamesestock prices. The Journal of Risk Finance,10, 321-332.

Pal, K. and Mittal, R. (2011). Impact ofMacroeconomic Indicators on IndianCapital Markets, Journal of Risk Finance,12 (2): 84-97.Pethe, A. and Karnik, A. (2000). DoIndian Stock Market Maters? StockMarket Indices and MacroeconomicVariables, Economic and Political Weekly,35 (5): 349-356.Sangeeta Chakravarty, “Stock Market andMacro Economic Behavior in India”Institute of Economic Growth, UniversityEnclave, Delhi, 2005.Sezgin Acikalin, Rafet Aktas, and SeyfettinUnal (2008), “Relationships BetweenStock Markets and MacroeconomicVariables: an Empirical Analysis of theIstanbul Stock Exchange”, Investmentmanagement and Financial Innovations,5(1).Wong, W., Khan, H., and Du, J. (2005).“Money, Interest Rate, and Stock Prices:New Evidence from Singapore and theUnited States”. U21 Global WorkingPaper No. 007/2005.Zhao, X. Q. (1999). Stock prices, Inflationand Output: Evidence from China. AppliedEconomic Letters, 6 (8), 509–511.

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MACRO ECONOMIC FACTORS AND SHARE PRICE BEHAVIOUR:A STUDY ON SELECTED INDUSTRIES IN INDIA

Pramath Nath AcharyaNIST, Brahmapur, Odisha, [email protected]

Rudra Prasanna MahapatraProfessor, PG Dept. of Commerce, Berhampur University


ABSTRACTShare Market Investment has become popular in recent days due to its higherreturn comparing with other traditional form of investment. However, it is a factthat the market does not pay guaranteed return like in the traditional form ofinvestment. The ups and downs in the return are the phenomena of a share marketinvestment. The fluctuations in the share market are influenced by several set offactors relating to company, industry as well as economy. Hence, the investorsshould take the note of these factors while investing. The present study is anattempt to find out the relation as well as the effect of macroeconomic factors onthe share price of selected industries. The result of the study disclosed that themacroeconomic variables are having significant influence on the share price.Key Words: Share Price, Macroeconomic factors, Regression analysis

INTRODUCTION

Share market investment has become aninteresting option for the investors sinceits inception in India, particularly after theeconomic liberalisation. This is one of themajor avenues of investment that yieldsconsiderable returns to investors. Makingprofit in the market is a top as well as atuff game. An investor with an objectiveof maximising return and minimising riskwants to know when he should invest orwhen he should divest. To be successfulin this game requires the knowledge ofthe forces that cause ups and downs inthe share prices. The available literaturesuggests that, there are mainly two sets offactors responsible for change in share

price. They are micro and macro levelfactors. The micro factors refer to firmspecific factors such as ; dividend, profit,leverage, size of the firm etc. and macrofactors refers to the macro economicvariables such as; GDP, IIP, Money supplyetc. The study on both the categories offactors is important to predict the pricechange. Due consideration of such factorsby investors is also felt while investing theirfunds, since this would aid them in makingwise investment decision. As on march,2014, equity investment by Indianhouseholds is about 7.8% of the totalfinancial savings. The equity culture hasspread in our nation, what was the earlier


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concern of rich and privileged class is nowbecoming a matter of interest for millionsof middle and low income groups. A well-developed equity market helps in theprogress of economy and it providesinvestors with a range of assets withvarying degree of risk, return and liquidityapart from enhancing savings and capitalcreation. In the view of economicdevelopment, it has become imperative tostudy the relation of stock price movementand the numerous macroeconomicindicators. The macroeconomic eventsinfluence investors’ psychology and itaffects their buying and selling decisions.Hence, in this context, current research isan attempt to examine the influencingpower of macroeconomic factors on shareprice.

REVIEW OF LITERATURES

In the last few decades, numerous studieshave been carried out to examine thedynamic relationship between stockmarket behaviour especially relating toshare price and economic activities. Fama(1981) laid foundation stone in this regardto understand the relation ofmacroeconomic indicators and stockprices. He found a significant relationshipbetween them. Following his study, anumber of empirical studies explored thistopic. Industrial production was found tobe a significant factor for Italy andNetherlands. However, in case of UK,Switzerland and Belgium, the importanceof macroeconomic factors did not improvetheir ability to forecast.

Sen (1996) examined the share pricemovement in India during 1985–1994 toascertain the role of foreign capital vis - a- vis internal economic factors such as GDPgrowth, change in interest rate andexchange rate movements in determinationof stock prices. By employing regressionmodel, the result of the study disclosed thatboth industrial production and foreignexchange reserve are key determinants ofstock market performance in India.Further, the study revealed that stockprices received significant support fromforeign capital flows.

Ibrahim (1999) investigates the dynamicinteractions between sevenmacroeconomic variables and the stockprices for an emerging market, Malaysia,using co-integration and Granger causalitytests. The results strongly suggestinformational inefficiency in the Malaysianmarket. The bi-variate analysis suggestsabout the co-integration between the stockprices and three macroeconomic variables– consumer prices, credit aggregates andofficial reserves.

Günsel and Çukur (2007) carried out astudy to know the effect of macro-economic factors on the London stockreturn. It considers seven macro-economic factors such as 1. the termstructure of the Interest rate 2. Inflation 3.risk premium 4. Sectoral IndustrialProduction 5. Exchange rate 6. Moneysupply and 7. Sectoral dividend yield. TheRegression results of the study show thatthere are big differences among industryportfolios against macroeconomic

Macro economic factors and share price behaviour: A study on selected...


variables. Test results indicated thatdividend yield is significant and negativeat 1% significance level for all the industriesnamely 1. Food beverage & tobacco 2.Constructions 3. Building materials &Merchants 4. Electronics and electricalequipment 5. Engineering 6. Householdgoods & Textiles 7. Paper, Packaging &Printing 8. Chemicals 9. Diversified and10. Oil exploration & production. Currentunexpected inflation does not have anyeffect on the industry returns except Food,Beverage and Tobacco at 10% accordingto the test results. Risk premium has apositive effect on the return of Constructionand Engineering. Effective exchange rateis an important factor to determine theinternational competitiveness. Our resultsimply that two sectors, Building Materials& Merchants and Engineering sufferbecause of the effective exchange ratemovements. Current money supply has apositive effect on the return of BuildingMaterials & Merchants, Food, Beverageand Tobacco, and a negative effect on thereturn of Household Goods and Textiles.One month lagged term structure of interestrate has positive effect on the returns offour industries, Construction, Food,Beverage & Tobacco, Oil Exploration &Production and Electronic & ElectricalEquipment. Unexpected Sectoralproduction figures seem to have negativerelation with Food, Beverage and Tobaccoindustry at 5% significance level.

Gay (2008) has tried to identify byinvestigating the time series relationshipbetween stock market index and

macroeconomic variables like exchangerates and oil prices of BRIC countries. Heused the Box Jenkins ARIMA model andstudied for 1999-2000. The study resultdisclosed that there was no significantrelationship between respective exchangerate and oil rate on the stock marketindices of BRIC countries.

Somoye, Akintoye and Oseni (2009)carried out a research study on thedeterminants of equity prices in Nigeriancapital Market. Considering a sample sizeof 130 companies, the study disclosedthat all the variables have positivecorrelation to stock price with theexception of lending interest rate andinflation rate.

The study of Hussainey and Ngoc (2009)is based on two important aspects of shareprice behaviour in the context ofVietnamese stock market where the studydisclosed the positive relation of domesticindustrial production and US industrialproduction on the Vietnamese stock price.

Rahman, Sidek and Tafri (2009) in theirstudy they tried to explore the interactionsbetween selected macroeconomicvariables such as money supply, exchangerate, reserves and industrial productionindex and stock prices in Malaysia. Thestudy reveals the linkage of all the variableswith stock prices.

Büyüsalvarci (2010) tries to study theimpact of macroeconomic variables in ISE-100 index of Turkish Stock Market byusing multiple regression model to themonthly data from 2003 to March 2010.

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The result of the study indicates that interestrate, industrial production index, oil price,foreign exchange rate have negative effecton ISE-100 index return, while moneysupply positively influence ISE-100 Indexreturn. However, inflation rate and goldprice do not appear to have any significanteffect in ISE-100 index return.

The study of Singh, Mehta and Varsha(2011) on Taiwan stock market revealedthe effect of exchange rate and GDP onstock return while inflation rate,employment rate and money supply havenegative relation with stock return.

Inegbedion (2012) carried out a study onthe macroeconomic determinants of stockprice in Nigeria. With the time series datafrom 2001 to 2009, the study disclosesthe significance of only one variable i.e.exchange rate out of three variables suchas interest rate, inflation rate and exchangerate which influences the stock pricebehaviour in Nigeria.

Darrat and Mukharjee (1986) in theirstudy applied a vector auto regressionmodel (VAR) on Indian data over 1948-1984 to find out the relationship betweenstock price and important macro economicvariables like exchange rate (rupee /dollar), prime lending rate, narrow moneysupply and index of industrial production.The results of the study reported weakcausality runs from IIP to share price index(SENSEX and Nifty) but not the otherway round. In other words it holds the viewthat the state economy affects stocksprices.

The study of Rao and Jose (1996)observed that the coefficient of total smallsaving with government on current and noncurrent account was found significant atone per cent level followed by other taskvariables such as index of industrialproduction, whole sale price index, foreignexchange reserve, aggregate deposits withcommercial banks, inter-bank call moneyrate etc at 5% level of significance.The results of the study conducted byPethe and Karnik (2000) disclosed thatonly index of industrial production affectsSENSEX and NIFTY. The studyhowever, found no evidence of casualtybetween other macroeconomic variablesand the stock price indices.Chakrabarti (2001) in his studyinvestigated the casual relationshipbetween FII and stock market returns.The result of the study disclosed that inthe pre Asian crisis period any change inFII had a positive effect on the equityreturns. But in post Asian crisis period, thecausation was reverse – equity returnsrather caused FII.Panda and Kamaiah (2001) in their studyinvestigated the casual relationship anddynamic interactions among monetarypolicy, expected inflation, real activity andstock returns in the post liberalisationperiod using a vector-auto regressionmodel. The study disclosed that, expectedinflation and real activity affect stockreturns, monetary policy losses itsexplanatory power for stock returns whenexpected inflation and real activity arepresent in the system.



Bhattacharya and Mukherjee (2002) intheir study used Toda and Yamamato’slong run Granger causality test to examinethe casual relationships between SENSEXand five macroeconomic variables vizmoney supply, index of industrialproduction, national income, interest rateand rate of inflation using monthly data from1992-93 to 2000-2001. The study resultdisclosed that index of industrial productioncauses SENSEX casuality, while thereexists a bi-directional casualty betweenSENSEX and rate of inflation.

Mukhopadhyay and Sarkar (2003)conducted a systematic analysis of theIndian stock market in the pre and postliberalization period and the influence ofmacroeconomic factors on stock returns.The study result revealed that specificallyfor the post liberalization period, the realeconomic activity, inflation, money supply,FDI and the NASDAQ index weresignificant in explaining variations in Indianstock returns.

Mishra (2004) investigated the relationshipbetween stock market and foreignexchange employing Granger causality testand vector auto regression tool for theperiod 1992-2002. The study disclosedthat there exists a unidirectional causalitybetween the exchange rate and interest rateand also between the exchange rate returnand demand for money. Further, the studyrevealed that there is no Granger causalitybetween exchange rate return and stockreturn.

The study of Kumar (2006) explained themarket movement using the direction ofthe funds flow from foreign institutionalinvestors and mutual funds in the Indianstock market. The result of the studyrevealed that institutional activity had aninfluence on the stock market and bothforeign institutional investors as well asmutual funds had a significant impact onthe market’s direction. Further, byemploying Granger causality test, the studydisclosed that Indian Mutual funds areleading the pack and are giving directionto the market and even foreign institutionalinvestors are following their direction.

In Sharma and Singh (2007)’s study,variables like foreign exchange reserve,exchange rate, index of industrialproduction, money supply and claim onprivate sector were found to have aconsiderable influence on the stock marketmovement. However, a few variables likeinterest rate and wholesale price indexshowed a very negligible influence on thestock market.

Sharma and Mahendru (2010) in theirstudy employed multiple regression modelsto test the effect of a selected number ofmacroeconomic factors on stock price.The key macro economic variables usedin the study were change in exchange rate,foreign exchange reserve, inflation rate andgold price. The study result disclosed thateconomic variables like exchange rate andgold price had significant effect on stockprice as a whole. However, the result ofthe study disclosed that inflation rate and

151

foreign exchange reserve had no influenceon the stock price.

The findings of the study of Srivastava(2010) conclude that emerging economicslike India in the long run are more affectedby domestic macroeconomic factors. Themain domestic macroeconomic factorsaffecting the Indian stock market in the longrun are industrial production, wholesaleprice index and interest rate.

The study of Hosseini, Ahmed and Lai(2011) on the relationship between marketindices and four macro economic variablesnamely crude oil price, money supply,industrial production and inflation rate inChina and India disclosed that, there existboth long and short term linkages betweenmacro economic variables and stockmarket indices in each of these twocountries.

Tripathy (2011) in her study reported thatthe Indian stock market is sensitive towardschanging behaviour of international market,exchange rate and interest rate of theeconomy.

Gupta (2011) in his study employed aregression model to identify the significanceof domestic and international factors onstock prices in India. He took SENSEXas the dependent variable and index ofindustrial production, rate of interest, rateof inflation and foreign institutionalinvestment as explanatory variables. Theempirical result disclosed that Indian stockmarket is mainly influenced by internationalfactors such as foreign institutionalinvestment. Domestic macro variables do

not have any significant influence on thestock market.

The study of Kalra (2012) on the impactof macroeconomic variables on Indianstock market is a comprehensive one.Considering explanatory variables such asForex rate, CRR, Reserve Repo Rate,Gold Price, Wholesale Price Index (WPI),Oil rate, Inflation rate and GDP, the studydisclosed the positive association of forexrate, inflation rate and gold price with themovement of Sensex.

The study of Trivedi and Behera (2012)on the determinants of equity prices ofIndia is one of the recent attempt toexamine the influencing role of Index ofIndustrial Production (IIP), WholesalePrice Index (WPI), Interest rate, MoneySupply, Foreign Institutional Investor (FII),Morgan Stanley Capital InternationalIndex (MSCI) on the equity prices.Cointegration tests demonstrate that equityprices (BSE Sensex) are significantlyrelated to all the macroeconomic variablesconsidered in this study.

RESEARCH METHODOLOGYObjective of the Study

The broad objective of the study is toidentify and quantify the influence ofselected macroeconomic factors on theequity share prices in the Indian stockmarket. Based on the review of empiricalstudies the prominent macro factorsinfluencing the variations in share price aregross domestic savings (GDS), grossdomestic product (GDP), inflation, foreigninstitutional investment (FII), net resources



mobilized by mutual funds (NRMF), goldrate (GR) and exchange rate (ER). Thepresent study has also made a modestattempt to examine the impact of theabove macroeconomic factors on thevariations in share price in Indian stockmarket. For accomplishing the aboveobjective, the study proposes to test thefollowing relations between share price ofselected industries and the macroeconomicvariables.1. Gross domestic saving (GDS) is

expected to have a positive influenceon share price.

2. Gross domestic product (GDP) isexpected to have a positive influenceon share price.

3. Inflation is expected to have a negativeinfluence on share price.

4. Foreign institutional investment (FII) isexpected to have a positive influenceon share price.

5. Net resources mobilized by mutualfunds (NRMF) is expected to have apositive influence on share price.

6. Gold Rate (GR) is expected to have anegative influence on share price.

7. Exchange rate (ER) is expected to havea negative relationship with the shareprice.

Hypothesis

For the purpose of the analysis, thefollowing null and alternative hypotheseshave been developed.

H0: Share prices are not affected by anyof the macroeconomic determinants.

H1: Share prices are affected by any ofthe macroeconomic determinants.The ModelBasing on the above hypothesis, thefollowing linear equation has beendeveloped for the purpose of the study.

Where:SP = Average Share PriceGDP = Gross Domestic ProductGDS = Gross Domestic SavingsER = Exchange RateIR = Inflation RateGR = Gold RateFII = Foreign Institutional InvestmentNRMMF=Net Resources Mobilised byMutual FundsUt = Error Term

Study Period and Data CollectionThe study was carried out by using the datafrom secondary sources such as theDatabase on Indian Economy maintainedby RBI as well as from the websites ofAMFI and SEBI for the purpose ofmacroeconomic variables. The share pricedata has been collected from the Prowessdatabase maintained by CMIE. For thepurpose of this research the data relatingto gross domestic savings (GDS), grossdomestic product (GDP), inflation, foreigninstitutional investment (FII), net resourcesmobilised by mutual funds (NRMMF),gold rate (GR) and exchange rate (ER)and share price of different companies

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belonging to selected industries arecollected, processed and analysed usingMS Excel and SPSS-14. As such, thesample finally holds only 104 companiesfor which the much needed financialinformation were available for the entirestudy period i.e. from 1997-98 to 2012-13. The classification of sample companiesbased on industry groups is as follows:Table-1 Industry Constituents for Sample Size

Industry Group No. of Sample Companies

Automobile 27

Pharmaceutical 20

Textile 20

Infrastructure 20

Cement 17

TOTAL 104

Limitations of the Study:

The study is based on share price dataobtained from CMIE Prowess data basefor the sample companies. Similarlymacroeconomic variables are collectedfrom the database maintained by RBI,AMFI and SEBI. As such, the studypossesses all the inherent limitations of thefinancial data collected from secondarysources. Non availability of the requiredfinancial data for the entire study periodhas restricted the size of the sample.Therefore, the limitations of the smallsample are very much prevalent in thisstudy. The presence or absence of auto-correlation problem in the study has been

tested by the DW statistics. However, noattempt has been made in the study toremove them, in case their existence is felt.It is also unlikely that, the multicolinearityamong independent variables might giverise to unexpected signs of the estimatedcoefficients. Further, the step wiseprocedure used in this study for selectingvariables to include in a model is anextreme example of brute empiricism. Italso suffers from being overly influencedby the specific characteristics of thevariables being examined. Thus while usingthe findings of the study, one should becareful and use the same judiciously bytaking the various limitations intoconsideration.

ANALYSIS OF DETERMINANTSHaving analysed the impact of microfactors on the share price behaviour, in thelast section, this section of the analysisseeks to examine the impact of a selectednumber of macro factors on the share pricebehaviour of selected sample industries.Like micro factors, the macro factors havea significant influence on the share price inthe market. This is an undeniable truth. Thereview of literature dealt in the previoussection confirms to this fact. In the presentanalysis, an attempt has been made toquantify the impact of a selected numberof macro factors on the share pricebehaviour of the sample industries, throughthe extensive use of stepwise regressionanalysis. It is a time series analysis,covering a time period of 16 years i.e. from1998 to 2013. The normality assumptionof the regression equation has also been



tested by using Normal P-P Plot of theresiduals which has been depicted in Fig.no-1 and it is shown at the end of the paper.For the purpose of analysis, regressionequation of the following form is estimatedto draw inferences.

Relevant data for estimation of the abovemodel are fed into the computer usingSPSS 14 software for drawing inferences.

Results for Automobile Sector:

It is evident from the results of theestimated regression model for theautomobile sector that, macro variablesnamely GDP, GDS and NRMMF haveturned out to be the most significantdeterminants of share price. Othervariables namely ER, IR, GR and FII havefailed to find place in the estimatedequation. The regression coefficients ofGDP, GDS and NRMMF have theappropriate positive signs and theytogether explain around 91% of thevariation in share price in auto sector. Theestimated regression model is also foundto be statistically significant at 1% level,which is well evident from its F value.Moreover, the DW value discloses noautocorrelation problem in the estimatedmodel.

Results for Pharmaceutical Sector:

It is evident from the Table – 1 that, theestimated regression model forpharmaceutical sector is found to be

statistically significant at 1% level andexplains satisfactorily the share pricebehaviour in pharmaceutical sector. Theregression coefficients of macro variablesnamely exchange rate (ER), foreigninstitutional investment (FII) and netresources mobilised by mutual funds(NRMMF) have the hypothesisednegative or positive signs. All the abovethree variables are found to be statisticallysignificant. The value of the coefficients ofdetermination (R2) is found to be 0.956.This implies that, around 95% of variationin share price in pharmaceutical sector isexplained by ER, FII and NRMMF.Moreover, there is no evidence ofautocorrelation problem in the estimatedequation.

Results for Textile Sector:In textile sector, the estimated regressionmodel is found to be statistically significantat 1% level and explains satisfactorily thevariations in share price (Table-1). It isfurther observed that, the regressioncoefficients of the macro variables namelygross domestic product (GDP), exchangeRate (ER) and net resources mobilised bymutual funds (NRMMF) have theappropriate signs. All the above macrovariables are found to be statisticallysignificant. The regression coefficients ofGDP and NRMMF are found to besignificant with their hypothesised positivesigns. However, the coefficient of exchangerate (ER) is found to be significant at 1%level with its hypothesised negative sign.The value of the coefficients ofdetermination (R2) is found to be 0.918.

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This states that around 91% of the variationin share price in textile sector is wellexplained by GDP, ER and NRMMF.Moreover, there is no evidence ofautocorrelation problem in the estimatedequation.

Results for Infrastructure Sector:

In infrastructure sector, the results of theestimated regression model disclose thatGDP, GDS and FII are the three prominentmacro factors influencing the variation inshare price. Other macro variablesconsidered for analysis namely ER, IR, GRand NRMMF have failed to find place inthe estimated equation. The regressioncoefficients of GDP, GDS and FII havethe appropriate positive signs and all ofthem turned statistically significant. Theestimated regression model is found to bestatistically significant at 1% level. The valueof the coefficient of determination is foundto be 0.892. This precisely states thataround 89% of variation in share price ininfrastructure sector is explained by GDP,GDS and FII together. Moreover, there isno evidence of autocorrelation problem inthe estimated equation.

Results for Cement Sector:It is evident from the regression resultsdisclosed in Table – 1 that, the key macrofactors influencing the share price in cementsector are gross domestic savings (GDS),exchange rate (ER) and net resourcesmobilised by mutual funds (NRMMF).The regression coefficients of all thesethree macro variables are found to bestatistically significant with their

hypothesised positive or negative signs.The estimated regression model is foundto be statistically significant at 1% level.The value of coefficient of determination(R2) is found to be 0.973. This implies that,around 97% of variation in share price incement sector is explained by the estimatedregression model.The above industry wise analysis ofstepwise regression tests for macro factorsdisclose that, the key macro factorsinfluencing the share price behaviour inselected sample industries are grossdomestic product (GDP), gross domesticsavings (GDS), exchange rate (ER),foreign institutional investment (FII) andnet resources mobilised by mutual funds(NRMMF). However, the analysis failedto establish the significance of variablesnamely inflation rate and gold rate. In noneof the industrial sector their impact wasfelt. It is observed from the regressionresults that, net resources mobilised bymutual funds (NRMMF) as a keydeterminant of share price is found inautomobile sector, pharmaceutical sector,textile sector and cement sector. Thesignificance of gross domestic savings(GDS) is found prominent in automobileand cement sector. Foreign InstitutionalInvestment (FII) turned out to be asignificant determinant of share price inpharmaceutical and infrastructure sector.Gross domestic product (GDP) is foundto be a significant determinant of shareprice in automobile, textile andinfrastructure sector. Moreover, theinfluence of exchange rate (ER) is foundprominent in pharmaceutical, cement andtextile sector.



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FINDINGS AND CONCLUSION:

Table- 2 Summary Results for Macro Factors

INDUSTRY GROUP/VARIABLES GDP GDS ER IR GR FII NRMMF

AUTO S* S** S* PHARMACEUTICAL -S** S** S* TEX S* -S* S** INFRA S* S* S* CEMENT S* -S** S* TOTAL 3 3 3 0 0 2 4

Source- Compiled from Table-1s* - Significant at 1% levels**- Significant at 5% levelThe summery results of industry wiseanalysis for the macro variables aredisplayed in the table- 2. From the table itcan be found that gross domestic product(GDP), gross domestic savings (GDS),exchange rate (ER), foreign institutionalinvestment (FII) and net resourcesmobilised by mutual funds (NRMMF) arethe key macro factors influencing shareprice behaviour in the selected sampleindustries. However, the analysis failed toestablish the significance of variablesnamely inflation rate (IR) and gold Rate(GR) in any one of the sample industrieschosen for the study. It is further observedfrom the regression results that, netresources mobilised by mutual funds(NRMMF) as a key determinant of shareprice is found in automobile,pharmaceutical, textile and cement sectors.The significance of gross domestic savings(GDS) is found prominent in automobileand cement sector. Foreign institutionalinvestment (FII) turned out to be asignificant determinant of share price in

pharmaceutical and infrastructure sector.Gross domestic product (GDP) is foundto be a significant determinant of shareprice in automobile, textile andinfrastructure sector. Moreover, theinfluence of exchange rate (ER) is foundprominent in pharmaceutical, cement andtextile sectors. The result of the studyshows the expected signs as discussed inthe objective section of this paper. Thecurrent study can be extended byanalysing more industries for theoreticaldevelopment.

Fig-1 Normal P-P Plot of RegressionStandardised Residuals for MacroVariables (TEXTILE SECTOR)



(PHARMACEUTICAL SECTOR) (AUTOMOBILE SECTOR)

(INFRASTRUCTURE SECTOR) (CEMENT SECTOR)

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Mukhopadhyay, D. and N. Sakar, (2003).Stock returns and MacroeconomicFundamentals in Model SpecificationFramework: Evidence from Indian StockMarket, Indian Statistical Institute,Economic Research Unit, ERU 2003-2005 Discussion Paper, pp1-28.Panda, C. and Kamaiah, B., (2001):Monetary Policy, Expected Inflation, RealActivity and Stock Return in India: AnEmpirical Analysis, Asian-AfricanJournal of Economics andEconometrics, 1,191-200Pethe, A. and Karnik, A., (2000): “DoIndian Stock Markets Matter? StockMarket Indices and MacroeconomicVariables”, Economic and PoliticalWeekly, 35 (5), 349-356.Rahman, A.A., Sidek, A.Z.M., and Tafri,F.H., (2009): MacroeconomicDeterminants of Malaysian Stock Market,African Journal of BusinessManagement, 3 (3), 95-106. Rao, K.C.S. and Jose, S. (1996):Relative Influence of Market Volatility,Economic Changes and CompanyFundamentals on Equity Return in India:A Study, Finance India, X (1) 27-48.Sen., S. (1996): “Role of Foreign Capitalin India’s Security Market Boom”,Finance India, X (3), 573–584.Sharma, G.D. and Mahendru, M. (2010):Impact of Macro-Economic Variables on

Stock Prices in India, Global Journal ofManagement and Business Research, 10(7), 19-26.Sharma S. and Singh, B.(2007):”Macroeconomic Variables andStock Index in India: An EmpiricalAnalysis”, Artha Vijnana, XLIX (2) 103-120.Singh, T., Mehta, S. and Varsha, M.S.(2011): Macroeconomic Factors andStock Returns: Evidence from Taiwan,Journal of Economics and InternationalFinance, April, Vol.2, No. 4, pp217-227.Somoye, R.O.C., Akintoye, I.R. andOseni, J.E. (2009): Determinants ofEquity Prices in the Stock Market,International Research Journal ofFinance and Economics, (30), 177-189.Srivastava, A. (2010): Relevance ofMacro Economic Factors for the Indianstock Market, Decision, 37 (3), 69-89.Tripathy, N. P., (2011): CasualRelationship between Macro-EconomicIndicator and Stock Market in India,Asian Journal of Finance &Accounting, 3(1), 208-226.Trivedi, P. and Behera, S.R.(2012):Macroeconomic Fundamentals asDeterminants of Equity Prices: AnEmpirical Analysis for India, The IUPJournal of Applied Finance,18 (3), 5-30.

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INFLUENCE OF CAPITAL STRUCTURE ONFINANCIAL PERFORMANCE

Chandrika Prasad DasLecturer, Department of Commerce, B.B. Mahavidyalaya, Jajpur, Odisha

[email protected]

Rabindra Kumar Swain,Assistant Professor, P.G. Dept. of Commerce Utkal University, Bhubaneswar

[email protected]


ABSTRACTFinancing decision is one of the important areas in financial management toincrease shareholders’ wealth. Firms can use either debt or equity capital tofinance their assets. The purpose of the study is to find out the determinants ofcapital structure and its impact on financial performance. We have used secondarydata and taken 50 top manufacturing companies for our study. Regression modelhas been used to study the relationship and impact of capital structure onprofitability. The study concludes that there is a significant relationship betweencapital structure and profitability and capital structure has significant impacton financial performance of sample companies.

Keywords: Financial Management, Shareholder’s Wealth, Equity Capital, Debt,Capital Structure, Financial Performance

INTRODUCTION

The basic aim of starting a business isearning profit for which the proprietor hasto sacrifice or invest some amount ofmoney in the business. Money investedhelps in acquiring resources i.e. assets.The assets of the business are used inprocess of production, distribution and inthe operation of the business. The fundsto be invested are procured from varioussources. The source can be promoterhimself or outsiders to the business. Thosefunds are the input to business which willprovide the expected output. This input is

termed as capital/financial capital. Thesource of financial capital can be of twotypes- owned capital and borrowedcapital. Owned capital is raised fromowners (promoters/shareholders) alsoknown as owner’s equity and borrowedcapital is raised from lenders or investorsknown as debt fund or outsider’s equity.The capital can be of various types on thebasis of time such as long term capital,medium term capital & short term capital.Long term capital is basically obtained byissuing share capital, debenture capital,



venture capital mortgage, retained earningsetc. The term loan, leasing, Bank overdraft,trade credit, factoring etc. are the sourcesof Medium and short term capital. All thesemix of sources of funds is known asfinancial structure. The portion of financestructure consisting of long term capital canbe said as capital structure.

The capital structure is the combination ofequity capital and debt capital. Theproportion of debt and equity in capitalstructure varies from firm to firm and timeto time. A firm can adopt a capital mix ofeither 100% equity and zero debt or100% debt with zero equity or anycombination of both. Equity financing isless risky in the sense of cash flowcommitments, but results in a dilution ofownership and earnings where as debtcapital creates an obligation or liability withlow-cost and high risk. It is a veryimportant component of corporatefinance. Long before 50 years financialmanagement has not got that muchimportance and deals with onlyprocurement of funds but at present it hastaken the basics of any business includingprocurement, utilization and control offinance. So it directly affects theperformance of business organization.That’s why finance manager should take adecision of optimal capital mix which willincrease the financial Performance.

REVIEW OF LITERATURE

Goyal, (2013) made a study entitled“Impact of Capital Structure onPerformance of listed Public Sector Banks

in India” with the purpose to measure theimpact of capital structure on bankingperformance. He has taken 19 PSU bankslisted on NSE as the sample for the study.It is concluded that the profitabilitymeasured by return on equity (ROE)reveals an average of 17.98 percent withmedian of 18.19 percent. This picture maysuggest a good performance during theperiod under the study. The average valueof TDC variable is 18.66 with median of17. This position reveals that the banksare financially leveraged with a largepercentage of total debt being short-term.The average growth is 21.29 and theaverage firm size is measured by logarithmof assets.

Mohamed & InunJariya, (2015)studied the “Effect of Capital structure onprofitability of Food and Beverage sectorsin Sri Lanka” by taking 14 companies ofthe Beverage, Food & Tobacco industryand 24 companies from the Manufacturingindustry. They conducted the study to findout the relationship between profitabilityof the listed Beverage, Food and Tobaccoindustry in Sri Lanka and capital structureand to recognize the impact of capitalStructure on the profitability of the Foodand Tobacco industry and listed Beverage,in Sri Lanka. The study revealed that totaldebt to asset (TDA) has a negative impacton return on equity (ROE) and return oncapital employed (ROCE) and issignificant at 0.05 significance levelwhereas leverage, measured by total debtto equity (TDE) shows a negativerelationship but not significant. TDA is also

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found out a negative impact on profitabilitymeasured by ROCE after controlling forLNS at 0.01 significant levels. It is clearthat both the measures of leverage (TDA& TDE) have negative impact on both themeasures of profitability (ROE & ROCE).The value is less than 0.01 for all the cases.Therefore, it could be concluded that at1% significance level, leverage/debt capitalhas a negative impact on the profitabilityof beverage, food and tobacco sectorfirms listed on Sri Lanka.

Babalola, (2012) in their research on“The Effects of Optimal Capital Structureon Firm’s Performances in Nigeria”examined an optimal capital structure tomaximize the performance of selectedfirms under the same systematic risk. Theyfound a strong curvilinear relation betweenROE and the debt-to-assets ratio. Thetheory predicts that the value of firms willfirst increase, then decrease, as debt ratioincreases. Most existing papers on capitalstructure require firm’s performance orfirm’s value to bear the linear relationwith debt ratio, but the empiricalevidence does not support this. Incontrast, there is an evidence that thequadratic relations are significant, yet thesehave not received much attention in thefinance literature

Kumar, (2015) made a study entitled“Capital Structure and its Impact onProfitability”. The study has made with theobjectives of identifying the relationshipbetween profitability and capital structureof SME, finding an optimal capital

structure that would be associated with thebest performance, finding an optimalcapital structure that would be associatedwith the best performance and finding outthe impact of capital structure on theprofitability. Data collected from somesecondary sources studied from 2008 to2013 and it is concluded that the debt/equity composition varies substantiallyamong the SME and there is significantrelationship between Debt to total fundsand ROE. There is no relation or there isinsignificance between debt to total fundsand ROCE.

Habib et al, (2016) made a study entitled“Impact of debt on profitability of firms;evidence from non-financial sector ofPakistan”. This study focuses onexpanding the existing empiricalknowledge on the impact of debt onprofitability of companies by taking 340firms listed on the KSE. The studyanalyzed the financial statements of all thesample companies to find out the influenceof debt on the profitability of concernedfirms. It is concluded that there is asignificant but negative relationshipbetween debt and profitability, thus, thehigher the debt, the lower the profitability.

Movalia, (2015) conducted a study on“ Capital structure analysis andprofitability of Indian Tyres Industry” withthe objective to know the Debt-Equityratio of listed Tyre Companies, tomeasure profitability of Tyre industry, tomeasure the impact of debt-equity ratioon profitability of listed companies in the

Influence of capital structure on financial performance


Tyre industry. The study was based ondescriptive and analytical research designwhich found out that debt-equity ratio ofthe company is having significant impacton profitability of Tyre companies in India.MRF, Apollo Tyres, Dunlop India andModi Rubber having Ideal capitalstructure, so respectively they are havinggood profitability.

RESEARH GAP

Many studies have been conducted on theimpact of management & control, Costingtechnique, marketing strategy, employeeperformance on profitability but very fewresearches have been made on impact ofcapital structure on profitability in India.Those studies made on this topic arebasically on different industries like SME,Food & beverages industry, IT industries,

Tyre industries etc but a few studies havebeen taken on manufacturing sector orservice sector in common.

STATEMENT OF THE PROBLEM

In India, a few studies have beenundertaken to establish the relationshipbetween optimum capital structure andperformance variables like ROE, ROA,and ROCE etc. So, the study is an attemptto analyze the relationship between capitalstructure and performance variables tounderstand and evaluate the impact ofcapital structure on various performancevariables.

IMPORTANCE OF THE STUDY

The present study mainly analyses howfar the capital structure affects theprofitability of corporate firms in India.

Table 1: STATIONERITY TEST RESULTSVariables ADF

Statistics P Value Order of

Integration ROA 8.54 0.0000 I(0) ROE 8.35 0.0000 I(0) ROCE 7.89 0.0000 I(0) EPS 20.63 0.0000 I(0) CURRENT RATIO 22.06 0.0000 I(0) DEBT EQUITY RATIO 20.78 0.0000 I(0) LD – TA 9.30 0.0000 I(0) TD - TA 9.15 0.0000 I(0)

Source: Author Computation from Computer outputTable 2: DESCRIPTIVE STATISTICS

ROA ROE ROCE EPS CR D/E LD-TA TD-TA Mean 9.46 22.63 15.59 54.27 1.88 0.75 13.56 27.80 Std. dev 7.35 16.96 14.51 238.53 5.73 2.00 13.12 24.61

Source: Author Computation from Computer output

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Asset size and business revenue wouldappear to be the important factors indetermining the profitability of corporatefirms. This is a benchmark of performanceby seeing which investors and lendersinvest in business. In India, a few studieshave analyzed the relationship betweenasset size and business revenues on theimpact of capital structure and Profitability.Though many research studies have beenundertaken in the field of capital structure,only a very few studies have beenundertaken to analyze the associationbetween capital structure and Profitability.

Therefore, this study is a maiden attemptto analyze the

• Profitability of the firms.

• Significant relationship among differentsized firms in terms of capital structureand Profitability.

The study constitutes an attempt to providean empirical support to the hypothesizedrelationship between capital structure andProfitability. Is there any significantdifference in the impact of capital structureon Profitability of manufacturing firms inIndia? How far does the capital structureaffect the business revenue of firms, andwhat is the inter-relationship betweencapital structure and Profitability.

OBJECTIVES OF THE STUDY

• To identify the determinants of capitalstructure.

• To measure the impact of capitalstructure on financial performance.

RESEARCH METHODOLOGY

Sources of DataSecondary data have been used for thestudy. The required data have beencollected from money control website. The

Table 3: Multicollinearity Test

Independent Variables Variance Inflation Factor Debt Equity Ratio 1.0557 Current Ratio 1.0023 Longterm Debt _ Total Asset 1.4398 Total Debt _ Total Asset 1.4510


Table 4: Regression ResultIndependent Multiple R R Square Adjusted R P Value

ROA 0.507441323 0.257496696 0.25149667 6.44e-31 < 0.05 ROE 0.31239629 0.09759144 0.09029925 2.31e-10 < 0.05 ROCE 0.461304 0.212801 0.20644 1.02e-24 < 0.05 EPS 0.072391 0.00524 -0.0028 0.625743




data have been taken from the financialreports of the sample companies.

Sample Design

Considering the availability of data, a studyperiod of 10 years has been taken. 20firms selected out of 100 listed firms onthe basis of market capitalization, 20 firmsout of top 100 firms on the basis of totalassets employed and 10 firms from list oftop 100 firms on the basis of revenue &growth have been selected. So, in total wehave taken 50 manufacturing companiesfor our study.VariablesDependent variables (FinancialPerformance variables)ROA- Return on AssetROE- Return on equityROCE – Return on Capital employedEPS- Earning per ShareIndependent variables (CapitalStructure)CR - Current ratioLD _ TA - Long term debt to Total assetsTD _ TA - Total debt to Total assetsDER - Debt equity ratioEconometric ModelYe = â0 + â1DER + â2CR + â3LD_TA+ â4TD_TA + å

Where,

Ye = Profitability Variables (ROA, ROE,ROCE, EPS)

â0 = constant or the value of Y when all

values of X are zero

â1, â2,……..= Slope of the independentvariables

DER = Debt – Equity Ratio

CR = Current ratio

LD_TA = Long Term Debt to Total Asset

TD_TA= Total Debt to Total Asset

Å= The error term

Statistical Measures

• Multicollinearity test- To study theinter-dependence among independentvariables

• Stationery Test – To find out whetherthe data has a unit root or not.

• Descriptive Statistics - Descriptivestatistics are used to describe the basicfeatures of the data in a study. SPSStest has been used to calculatedescriptive statistics.

• Multiple regression technique- foranalysis of degree of impact ofcapital structure on profitability.

Software used for Data Processing

• SPSS - SPSS helps to determineregression analysis, MulticollinearityTest and Descriptive Statistics.

• Eviews9.5 - It helps to determine theunit root test.

HYPOTHESIS

H10 There is no relationship betweenROA and capital structure variables.

H20 There is no relationship between

167

ROE and capital structure variables.H30 There is no relationship between

ROCE and capital structurevariables.

H40 There is no relationship betweenEPS and capital structure variables.

DETERMINANTS OF CAPITALSTRUCTURE

Financial Leverage: It means the use ofborrowed capital to increase the sales andearnings. The use of more debt componentin the business magnifies the earning ofshareholders. The more and more debt acompany uses, the higher its financialleverage but at the same time the risk ofhigh interes payment arises whichnegatively affect the company.Growth & Stability of Sales: The growthand stability in sales is a measure factorfor capital structure of firms. If a companyis having fair sales then it can raise a highlevel of debt and vice versa.Cost of Capital: It means minimum rateof return that one investor should expecton his investment. It should provideminimum cost of capital.Cash Flow: The firm which can generatestable cash inflows, they have moreopportunity to employ more debt in itscapital structure as compared to the onewhich has unstable and lesser ability togenerate cash inflow.

Nature and Size of a Firm: Nature andsize of a firm influence the capital structure.Public sector firms may employ more debtas comparison to private sector firms

because of stability and regularity of theirearnings.

Flexibility: It means the firm’s ability toadopt the capital structure according to thechanging conditions. The capital structureis flexible if it has no difficulty in changingits sources of funds.

Requirement of Investors: Therequirement of investors influences thecapital structure of a firm. It is necessaryto meet the requirements of bothinstitutional as well as private investorswhen debt financing is used.

Capital Market Conditions: CapitalMarket Conditions affects the firm’scapital structure. The conditions aredifferent as it is dependent on market andpessimistic business conditions.

Inflation: Inflation is a major factor thatshould be considered at the time offinancing decision. During the high inflationperiod if one company is using more debtfinancing then they have to repay the debtwith rupees more than what they havetaken.

DATA ANALYSIS

Stationery Test

This paper has used Augmented Dickey –Fuller test to find out the stationary of data.

H0: Data has unit root.

H1: Data has no unit root.

We have found all the data are stationeryat level because the test statistics is lowerthan the critical values. So, we will reject



null hypothesis H0. So, we can concludethat the above paper has no unit root.Therefore, we can run regression.

Descriptive Test

Table no 2 gives the summary of thedescriptive statistics of the data used in thisstudy. The above table shows that themean and standard deviation of EPS is54.27 and 238.53. It shows there is noconsistency in EPS. The TD-TA is notconsistent to some extent as the standarddeviation is more with comparison to meanvalue. Current ratio, Debt Equity ratio, LD-TA, ROA, ROCE, ROE showsconsistency as their standard deviation issatisfactory.

Multicollinearity TestIn the study four independent variableshave been taken. We first run regressionequation to find out if there is anyMulticollinearity among the independentvariables.From table no 1 it is observed that VIFvalue of independent variables is less thanthe rule of thumb 10. Hence there is noMulticollinearity between independentvariables and all the variables are eligiblefor running regression equation.Regression Results

From the regression table as given aboveit is found that there is a positiverelationship between ROA and allindependent variables (D/E, CR, LD_TA,TD_TA) as evident from R2 i.e.0.257496696. This indicates around 25

% (approx) of ROA is contributed byindependent variables. It can be said thata unit change in capital structure leads to achange of 25% in ROA which is verysignificant. Here p value is 6.44E-31 i.e.p<0.05. It implies that there is a significantrelationship between ROA and allindependent variables collectively.Hypothesis 1 predicts that “There is norelationship between ROA and CSvariables”. The above results confirm thatthis hypothesis is rejected and alternativehypothesis is accepted i.e. there is asignificant relationship between ROA andCS variables.

The above table propounds that there is apositive relationship between ROE and allindependent variables i.e. 0.09759144. Itmeans around 10 %( approx) of ROE iscontributed by independent variables. Soit can be said that change in a unit of capitalstructure will lead to 10% change in ROE.Return on equity is the basic indicator ofprofitability, but only 10% is affected bythese variables. The remaining 90%change may be due to other variables likecompetition from the market, state ofeconomy, promotion of the company whichinfluences volume of sales, cost of rawmaterials, labour etc., and the impact ofwhich is not considered in this study. Herep value is 2.31E-10 i.e. p<0.05. Itconcludes that there is a significantrelationship between ROE and allindependent variables. Hence H20 ‘Thereis no relationship between ROE and CSvariables is rejected and alternative

169

hypothesis is accepted i.e. There is asignificant relationship between ROE andindependent variables.

We find that there is a positive relationshipbetween ROCE and all independentvariables from the regression table i.e. R20.212801 i.e. this shows around 21%(approx) of ROCE is contributed byindependent variables. It also signifiesthe level of significance between ROCEand all independent variables is 1.02E-24i.e. p<0.05. It denotes that there is asignificant relationship between ROCEand all independent variables. The aboveresult concludes that the null hypothesisH30 is rejected. So, alternative hypothesisis accepted i.e. there is significantrelationship between ROCE andindependent variables.

There is a positive relationship betweenEPS and all independent variables asevident from adjusted R2 0.00524 i.e.this indicates around 1 %( approx) of EPSis contributed by independent variableswhich is very negligible. Here we can seethe effect of these variables on EPS is veryinsignificant. A change in capital mix doesnot incur much change in EPS. There may

be some other variables like dividenddecision, state of economy etc. which wehave not considered here in our study. Thep value is 0.625743 i.e. p>0.05. It signifiesthat there is no significant relationshipbetween EPS and all independentvariables collectively. Thus, we concludethat the null hypothesis is accepted.

ANOVA

ROA = 14.02 + 0.01 CR – 0.31 D/E –0.15 LDTA – 0.08 TDTA

Here C is the estimated constant of theregression and the value of C is 14.02.The current ratio shows positivecontribution towards return on asset. Thecurrent ratio co-efficient is 0.01, it means1 unit change in current ratio leads to 0.01unit change in ROA.. D/E, LDTA, TDTAcontributes negatively towards ROA.

ROE = 28.90 - 0.05 CR – 0.34 D/E –0.32 LDTA – 0.05 TDTA

The constant intercept is 28.90. All theindependent variables contributesnegatively towards return on equity. HereDebt Equity co-efficient is -0.34. It means1 % change in D/E leads to -0.34% changein ROE. The CR, LDTA, TDTA co-

Table 5: ROA



efficient is -0.05, -0.32, -0.05.

ROCE = 23.94 - 0.07 CR – 0.53 D/E –0.29 LDTA – 0.13 TDTA

The intercept value is 23.94. The CR, D/E, LDTA, TDTA co-efficient value is –o.07, -0.53, -0.29, -0.13. Debt equityratio impacted negatively towards ROCEmost. 1 unit change in D/E brings -0.53unit change in ROCE.

EPS = 73.13 - 0.60 CR + 4.16 D/E –0.61 LDTA – 0.45 TDTA

The constant co-efficient value is 73.13.Debt Equity ratio contributes positivelytowards Earning per share. The DebtEquity co-efficient is 4.16. It means 4.16unit changes in EPS due to 1 % change inD/E ratio. All other independent variablesaffected negatively towards EPS.

Table 7: ROCE

Table 8: EPS


Table 6: ROE

171

FINDINGS• There is a significant relationship

between ROA, ROE, ROCE andCapital Structure Variables.

• There is no relationship between EPSand Capital Structure variables.

• Capital structure variables haveapproximately 25% impact onprofitability variables on an average.

CONCLUSION

The study results reveal significant relationbetween capital structure and profitability.These findings imply that change in debtand equity position is associated with theprofitability. Every firm should followoptimum capital structure which maximizestheir profitability and reduce costs. Thedebt and equity capital should be selectedcarefully by organizations. The capitalstructure decision is crucial for any businessorganization. The capital structure of aconcern depends upon a large number offactors such as leverage or trading onequity, growth of the company, natureand size of business, the idea of retainingcontrol, flexibility of capital structure,requirements of investors, cost offloatation of new securities, timing of issue,corporate tax rate and the legalrequirements.

REFERENCESBabalola, Y.A. (2012). The effect ofoptimal capital structure on firm’sperformances in Nigeria. Journal ofEmerging trends in Economics and

Management Sciences, Vol. 3, Issue.2,131-133.Boadi, E.K., & Li, Y. (2015). An empiricalanalysis of leverage and financialperformance of listed non-financial firmsin Ghana. International Journal ofEconomics and finance, Vol. 7, No. 9,120-135.Goyal, A.M. (2013). Impact of capitalstructure on performance of listed publicsector banks in India. International Journalof Business and management Invention,Vol. 2, Issue. 10, 35-43.Habib, H.J., Khan, F., & Wazir, M.I.(2016). Impact of debt on profitability offirms; evidence from non-financial sectorof Pakistan. City University ResearchJournal, Vol. 6, No. 1, 70-80.Kumar, N.S. (2015). Capital structure andits impact on profitability. InternationalJournal of Science, Technology&nManagement, vol. 04, Issue. 02. 24-30.Mohamed, A., & Inunjariya. (2015). Effectof capital structure on profitability of foodand beverage sectors in Srilanka. EpraInternational Journal of Economic andBusiness Review, Vol. 3, Issue. 11, 57-63.Movalia, N.P. (2015). A study on capitalstructure analysis and profitability ofIndiantyres industry. Pacific Business ReviesInternatioanl, Vol. 8, Issue. 3, 78-82.Ullah, H., Abbas, A., & Iqbal, N. (2015).Impact of capital structure on profitabilityin the manufacturing and non-manufacturing industries of pakitan.International Letters of Social andHumanistic Sciences, Vol. 59, 28-39.

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SWACHHA BHARAT GRAMIN: A BUDGET ANALYSIS OF INDIA’SSANITATION PROGRAM, ODISHA STATE

Madhumita RayFaculty Member, KSRM, KIIT, Bhubaneswar, Odisha

[email protected]


ABSTRACTThis paper examines changes in spending patterns of Indian Government in theMinistry of Drinking Water & Sanitation for the period 2013-14 till 2015-16 andthe thrust moving from drinking water to sanitation; it also examines theexpenditure patterns of the different components in rural sanitation in the state ofOdisha specifically. It traces the trajectory of increased budgeting of the GOI since2014 on sanitation, but initially decreased spending in sanitation by the states,due to late release of funds; it also examines the sudden surge in expenditure inthe states particularly Odisha in the area of sanitation from 2015-16 whichtranslated into improved infrastructure and better coverage particularly inindividual household toilets.A component wise analysis shows the uneven patterns of expenditure with moreinvestment on infrastructure, particularly household toilets which has no doubthelped in combatting open defecation, but low spending in areas like InformationEducation and Communication (IEC) and a complete neglect of environmentalconsiderations by no spending in Solid And Liquid Waste management standingas obstacles in real behavioural change in the state of Odisha. The paper comesup with recommendations to review component wise spending and ensure greaterconvergence for better delivery.Key Words – Budget, Component, Expenditure, Health, Sanitation, Water

INTRODUCTION

Is there any relationship betweensanitation, health, nutrition, and our wellbeing? It has been found that drinkingcontaminated water and not appropriatelydisposing human excreta, lack of properhygiene and improper disposal of waste,both solid and liquid can be the majorcause of many diseases.

Governments in India have consistentlyspent sizeable allocations in the area ofdrinking water and sanitation, but in spiteof this around 595 million people, whichare nearly half the population of India,defecate in the open (UNICEF: 2011); andCensus 2011 (GOI: Census 2011) reportsthat that 22 % of rural households have towalk more than 500 metres to fetchdrinking water.

Case Study

173

India accounts for 90 percent of the peoplein South Asia and 59 percent of the 1.1billion people in the world who practiceopen defecation (Banerjee et al 2013).Though sanitation missions are as old asthe formation of the Indian state, and havein each 5 year plan addressed thecomponent of sanitation, but the emphasiswas first on drinking water and shiftedmajorly to sanitation only in 2015 with theSwaccha Bharat Mission (SBM). Thefigures in both areas (Drinking water andSanitation) still leave a lot to be desiredand India was one of the major defaultersin the Millennium Development Goals(MDGs).Since 2015-16 with increased allocationfor sanitation, there has been a markeddecline in the drinking water allocations ofthe Government of India (GOI) and thiscould have grim impacts, considering therecent drought- situation in India,increasing the drinking water crisis andeven leading to slip-backs in toilet usage.Further, the Parliamentary StandingCommittee on Rural Development in the23rd Report on the Ministry of DrinkingWater and Sanitation in May, 2016 takesnote of the repercussions of the decline inthe Union Budget allocation for drinkingwater programme in rural India. Concernshave also been expressed on the qualityof water which is being addressed by asub-mission of the National Rural DrinkingWater Programme, (NRDWP).(Agarwala: 2017)The sanitation missions at both the stateand national level have seen a major boostnot in just their budgets, but also in the

thrust of official attention. A Componentwise analysis of different budget headsunder sanitation, with the emphasis on thestate of Odisha, shows large increases intoilet coverage at the household level inthe state, and precipitous rise in totalspending on sanitation, but poor coveragein public toilets including schools andAnganwadis (Day care centres).Note must also be taken of previousfailures of missions like the Total SanitationCampaign launched in 1999 where it wasreported that 81 million householdsconstructed toilets at the end of the 11th

plan period. But this data wassubsequently found to be incorrect. Thedecade infact saw progress being turnedupside down and ironically an increase inthe number of rural households withoutlatrines by 8.3 million. (Arjun: 2015)Considering these statistics, more thaninfrastructure, behavioural change has tobe the key. And will a limited focus onhousehold infrastructure alone changebehaviour patterns when there is verylimited emphasis on public toilets.Hypotheses1. As a result of greater emphasis and

policy thrust on rural sanitation postSwacha Bharat Mission, there wasincreased spending in sanitation in thestate level at Odisha from 2015-16,inspite of delays in fund disbursement,following patterns of previous years.

2. Increased spending on sanitation sawan emphasis on building of householdlevel toilets, without concomitantspending on public utilities of sanitationand waste management.

Swachha Bharat Gramin: A budget analysis of India’s sanitation program....


Literature Survey

There has been substantial scholarshipestablishing the causal relationship betweenpoor sanitation and human health. JamieBartram et al, argue in their paper,“Focusing on Improved Water andSanitation for Health”, “that a silenthumanitarian crisis kills some 3900children every day and thwarts progresstowards the MDGs (now changed toSDGs- Goal 6) especially in Asia andAfrica”. They reiterate that the basis of thiscatastrophe is that 4 of every 10 people inthe world do not have access to even asimple pit latrine and almost 2 in 10 haveno access to safe drinking water. Theyreveal that far more people are victims ofthese conditions than terrorism or weaponsof mass destruction, but these have notcaptured the public and politicalimagination and public resources, the waythe more politically volatile issues have.(Bartram et al: 2005)

Mishra and Ghadai, in “Merit Goods,Education Public Policy– India At CrossRoads”, show that there is a significantreduction in the Indian budget in differentsectors including swacha bharat and statethat the reason given by the Indian FinanceMinister, is that with increased allocationsby the 14th Finance Commissions in areaslike education, health and sanitation, thestates should take the initiative. (Mishra,Ghadai: 2015)

In a study on, “Health, Nutrition andProsperity: A MicroeconomicPerspective”, Duncan Thomas and

Elizabeth Frankenberg put forth the viewthat “health and economic prosperity arecongruent”. They opine that in both microand macro data, ample evidence is presentthat a wide range of health indicators hasa positive correlation with diversedimensions of economic prosperity.“Isolating the causal pathways that linkhealth and economics has been a coreissue. Causality runs in both directions islikely”. They say that higher incomeindividuals invest more in human capital,including health: as incomes grow, more isinvested on better diets, improvedsanitation and good health care, leadingto better productivity. (Thomas,Frankenberg: 2002)

Lack of sanitation leads to disease, wasfirst noted scientifically in 1842 inChadwick’s seminal work. (Mara et al:2010) “Report on an inquiry into thesanitary condition of the labouringpopulation of Great Britain”. (Chadwik:1842) A less scientifically rigorous butnonetheless professionally significantindicator of the impact on health of poorsanitation was provided in 2007, whenreaders of the BMJ (British MedicalJournal) voted sanitation as the mostimportant medical milestone since 1840.(Ferriman: 2007)

Methodology

Based on the rationale of examining thespending patterns, to understand therelationship between money spent andtargets achieved, a detailed analysis of theMoDWS data for the State of Odisha was

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initiated with a look at a cross section ofperformance at a district level and budgetsspent on different heads. The achievementsof each district were tabulated against themoney spent.

The study in its’ nature is exploratory;carried on to develop an understanding ofwhether the significant decline in thebudgets of the MoDWS in 2015-16 anda precipitous decline in the drinking waterbudget, affect the outreach of drinkingwater to hitherto unreached areas, and intandem affect public health. It also exploresthe changing patterns of investment in waterand sanitation and the need to emphasiseon behavioral change to ensuresustainability, through the consideration ofexpenditure data. On this basis the districtswere ranked on the different componentsunder the water sanitation mission like HHscovered under toilets, Information,Education and Communication materialavailable (IEC), Solid and Liquid WasteManagement (SLWM), etc. After thedistricts were ranked, a secondstratification on performance andgeographical location was made to ensurethat the sample was inclusive from a geo-political perspective.

The data for the concerned study aresecondary in nature and collected from theMinistry of Drinking Water Sanitation(MDWS), Government of India, website(http://sbm.gov.in/sbm/). All the data hasbeen analyzed using simple arithmeticaltechniques such as percentages and withthe help of excel.

Sampling:

For the purpose of this analysis, initiallystratified sampling process was adopted,based on two stratification variables:

1. Performance - the first criterion takeninto consideration is performing, lessperforming and non performing districtswith regard to sanitation expenditure andtoilet construction. Districts chosen –Angul, Balasore for good performance andKoraput, Malkangiri for poorperformance.

A comparison of Odisha data with thestate of Rajasthan was done, as Rajasthanwas found to have incurred the maximumexpenditure in 2105-16, if seen from acomponent wise break up of sanitationdata, as well as overall spending patternsalso, followed by Odisha.

2. Geographical location (Zone)-Different geo- political regions was thesecond consideration, along with pocketsof high concentration of Scheduled tribesand castes. Samples were taken from allthe five geo-political zones, Southern,Western, Northern, Central and CoastalOdisha. The districts of Koraput,Malkangiri and Ganjam have been chosenas samples for South Odisha, and with thefirst two districts being entirely scheduledareas with more than 50% tribalpopulation; Sundergarh for NorthernOdisha also a scheduled district with hightribal population, and home to industrialinfrastructure and rapid urbanization.Balangir and Bargarh for Western Odishawith high Scheduled caste populations,



Kandhamal for Central Odisha andCuttack and Khordha from CoastalOdisha with Khordha also home to theState headquarters, Bhubaneswar.

A comparison with the expenditure dataof Jharkhand, which is bordering Odishaand also has similar composition of ethnicgroups, has been done to understand thepatterns of investment and thrust in twosimilar states.

After the initial stratified sampling process,the 11 districts and two states have beenchosen based on purposive samplingprocess. The criterion used for thepurposive sample was the best and theworst performers as regards toexpenditure and the geo-politicalrepresentation.

Discussions, Policy Implications

Declining trend in allocations forDrinking water in the Budgets:

From FY 2013-14 to FY 2014- 15, thetotal allocation of MoDWS was enhancedby less than 1 percent from Rs 12,006crore to Rs 12,107 crore. In FY 2013-14, the MoDWS budget was already just

0.11 percent of GDP at current prices. InFY 2015- 16, the budget further droppedto Rs 6,236 crore, which is a 48 percentreduction from FY 2014-15. (Kapur etal: 2015).

Though at the start of FY 2015-16, GOIallocated Rs 3,625 crore for ruralsanitation but the revised allocation wasenhanced that year by passingsupplementary budgets in July andDecember. One of the reasons for thisincrease is due to the introduction of a 0.5per cent Swachh Bharat cess introducedin November 2015. (Kapur, Srinivas andRaychoudhury: 2016)

With a proportionate increase in budgetallocations for rural sanitation, the shareof drinking water has been reduced evenfurther in 2015-16. A provision of Rs 2611crore was made for NRDWP (NationalRural Drinking Water Program) and ruralwater supply inclusive of Rs 261 crore forthe North-Eastern Region. 22% and 10%of the total allocation i.e., Rs 575 croreand Rs 261 crores, is earmarked forScheduled Caste Sub-Plan and TribalSub-Plan respectively for the year 2015-

Table 1- Annual allocations of The Ministry of Drinking water and Sanitation

Year MDWS – Annual allocation1

Swach Bharat Mission- (only sanitation)

Nirmal Bharat Mission (only sanitation)

2015 -2016 Rs. 6236 crores Rs – 3625 crores - 2014 -2015 Rs 12,107 crores Rs 2,850 crores 2013-2014 Rs 12,006 crore Rs 2,300 crores 2012-2013 Rs 13,005 crore Rs 2,500 crores 2011 -2012 Rs10,005 crores Rs 1500 crores

(Gopalakrishnan: 2015 & GOI: 2015)

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16. (GOI, MDWS: Notes on Demand-2015) This is a drop from 2014-15 by72 %, the budget for Drinking water in2014-15 being Rs 9192 crores.

Just 26.9 million of 167.8 millionhouseholds (16%) in rural India have pipedwater, as per the statistics of the MoDWSgiven to the Rajya Sabha on February 6,2017 as per newspaper reports.

Changing allocation patterns andpriorities:Total Sanitation Campaign (TSC)approach was adopted in 1999 and itspoke about behavioural change as the“prime driver” for sanitation. In 2012, theprogramme was again revamped as NirmalBharat Abhiyan (NBA). In 2014, it wasredesigned once again and renamed as theSwachh Bharat Mission (SBM). In FY2015-16, the budget for rural sanitationstood at 58% of the total MoDWSallocations, hiked from 24 percent in FY2014-15, a hike of 34% points.From Rs. 1,500 crore in FY 2011-12, theprovision for rural sanitation has beensteadily increasing, each year, with theexception of 2013-14, which saw a 8%decline. Rs 3,625 crore had beenearmarked for the SBM from the overallRs. 6,244 crores, which is 58% of theallotted fund to the MDWS in the financialyear (2015-16) which is an increase of27% over the previous financial year.But though allocation increased, spendingdecreased. Sizeable funds were allocatedto states for sanitation, but a large amountwas unspent. The principal reasons quoted

were “delay in central release of funds”.(Gopalakrishnan: 2015). In FY1 2013-14,30% of funds were released only at theend of the financial year, that is in the lastmonth (February- March); resulting inunder spending and the states spending amere 45% of funds allotted. Similar trendshad been observed in the previous financialyear (2012-13) which saw 36% fundsbeing released as late as March 2013.In FY 2014-15, till February 2015, as littleas 33% of the approved fund wasdisbursed by GOI and consolidated at theblock, district and state level. UptoFebruary 2016, only 49 per cent of thetotal allocation had been sanctioned byGovernment of India for the financial year.Release of SBM funds to states has beenquite slow. (GOI).Annual Implementation Plans see their finalsanction by the National SchemeSanctioning Committee of the MDWS.The funds get released based on approvals.The GOI2 releases for rural sanitation sawa decline. In FY 2010–11, GOI released97 percent of its allocations. This furtherdecreased to 94 percent in 2013–14.

Spending patterns in Odisha and acomparison with other states: Let uslook at the funds available in Odisha underSwach Bharat Mission (in lakhs) and thetotal Expenditure in 2015-2016.

The expenditure patterns of Odisha werevery low. While 2013 – 14 saw, Odishacarrying forward a balance of Rs 5608.75 lakhs and even with a minusculeallocation of Rs 30.99 lakhs, the state was



able to spend only 10.57% of the budget,leading to a carry forward of Rs 5112. 67(lakhs); but even this was one of thehighest amongst states of its size at thenational level. While 2014-15 definitelysaw improvement, but still only less than50% of the budget allocated (Rs 3641.38lakhs) was spent. This is poorperformance considering funds wereavailable, as balances show. The balancesin the year, 2013-14 was Rs 5112.67lakhs and in the year 2014-15 was at aslightly reduced Rs 3687.99 lakhs.

Angul district of Odisha had the highestavailable fund of Rs 859.13 lakhs (stateshare) and Rs 2585.228 lakhs (Centralshare) in 2014-15 but made a expenditureof a mere 36% of the state and centralallocation and Ganjam district with 18%expenditure in the state share and 29% ofthe central share showed one of the lowestspending.

There were a few exceptional performersinspite of the general tide of low spending.The districts of Bhadrak (95%),Sambalpur and Jagatsingpur with 100%expenditure of funds under the centralshare and the districts of Balangir, Bhadrak,Jagatsingpur and Sambalpur with 100%expenditure under State share, wereexceptions to the general rule of lowspending.

But in 2015 -16 Odisha showedunprecedented realization with the state

spending as much as Rs 39913.76 lakhs (101.98%) of the state share and Rs119706.30 lakhs (173%) of the centralshare. 15 of the 30 districts of the stateshowed 100% expenditure under stateshare, though the State capital,Bhubaneswar showed poor spending ofRs 33.93 lakhs and only in the componentIEC material . All the districts (with theexception of the state headquarters,Bhubaneswar) spend 100% of their fundsunder the Central share, withBhubaneswar spending Rs 53.35 lakhsand only under IEC.

The following districts of Odisha showedsome of the highest expenditures in thecountry. Angul district is also being showcased by the SBM, GOI as a modeldistrict for sanitation in the country. Thishas been a remarkable turn around story.1. Mayurbhanj - Rs 2565.06 lakhs (SS)

+ Rs 7694.36 lakhs (CS); =Rs 10259.42 lakhs

2. Baleswar - Rs 2495.90 lakhs (SS)+Rs 7483.37 lakhs (CS); = R s9979.27 lakhs

3. Sundergarh - Rs 2219.26 lakhs (SS)+ Rs 6653.68 lakhs (CS); =Rs 8872.94 lakhs

4. Bargarh - Rs 1951.02 lakhs (SS) +Rs 5865.15 lakhs (CS); = R s7816.17 lakhs

5. Ganjam - Rs 7567.57 lakhs (CS);= Rs 7567.57 lakhs

2 Financial Year3 Government of India

179

6. Angul - Rs 1625.07 lakhs (SS3) +Rs 4877.37 lakhs (CS4); =Rs 6502.44 lakhs

7. Dhenkanal - Rs 1612. 71 lakhs (SS)+ Rs 4838.56 lakhs (CS); =Rs 6451.27 lakhs

8. Keonjhar -Rs 4917.44 lakhs (CS)and = Rs 4917.44 lakhs

9. Balangir - Rs 4441.33 lakhs (CS);= Rs 4441.33 lakhs

10. Navarangpur - Rs 4395.46 lakhsCS) = Rs 4395.46 lakhs

11. Jagatsingpur - Rs 4189.45 lakhs(CS); = Rs 4189.45 lakhs

12. Cuttack - Rs 4066.48 lakhs (CS);= Rs 4066. 48 lakhs

13. Jajpur - Rs 4036.27 lakhs (CS);= Rs 4036. 27 lakhs

During this period (2015-16) the Indiaexpenditure stood at Rs 1246850.64(lakhs) (with Rajasthan spending the mostin absolute numbers at Rs 171302.8(lakhs) and Odisha following in secondposition with an expenditure of Rs159620.1 lakhs; and with Goa showing awhopping 1080.93% of expenditure underthe state share though the actualexpenditure stood at a mere Rs 160.95lakhs and Rs 482.85 lakhs (324%) underthe central share.In comparison in 2013-14 the Indiaexpenditure stood at a mere 39.35% ofthe allocation, with the total expenditureof all the states (centre + state share) at

Rs. 268820 (lakhs). In a mere two yearsthere was a rise of 363% in the nationallevel spending on sanitation. Bihar,Madhya Pradesh, Tamilnadu and UttarPradesh were some of the major spendersin 2013-14, though none of them crossed60% of their total budget with Tamilnaduat the top with 58.61%.

Consistently Jharkhand, Odisha’sneighbouring state with a sizeable tribalpopulation like Odisha, spent at ratesbelow the Odisha spending, with theexception of 2013-14, when Odishaexpenditure stood at 10.57% as againstJharkhand at 18.96%. But in 2015-16,Odisha had gone much ahead with101.98% spending (Rs 39913.76 lakhs)under the state share and (Rs 119706.30lakhs (173%) of the central share asagainst 32.43% (Rs 8829.44) ofJharkhand under the state share and Rs26276. 79 (157%) of the central share.(GOI, MDWS: SBM Gramin, 2013-14,2014-15, 2015-16)

What led to such an impetus in spendingin the area of rural sanitation, for a statewhich had been classified as a laggard inthe particular theme. Among the manyreasons that can be ascribed to theincreased spending, some of the foremostmay be ascribed to a greater nationalconsensus around “no open defecation”having been developed with the launch ofthe SBM, which saw greater bureacraticinvolvement and the second is bigger

4 State share5 Central share



allocations to sanitation as against drinkingwater also changed the thrust of thecampaign from 2014-15. But it isnoteworthy to see whether this percolatedto all the components of sanitation or hasbeen limited to a few areas.Component wise spending in 2015-16-Central and State Share.Under the component wise expenditure thepaper has examined some of the mainprogram components of sanitation underthe SBM (Gramin). They are1. Integrated Household Latrine (IHHL)2. Solid and Liquid Waste Management3. Sanitary Complex4. School Toilet5. Anganwadi Toilets6. IEC

I. IHHL

The situation of household toilets in theblock level survey conducted by theMinistry of Drinking Water and Sanitationin 2012 shows districts like Angul with lessthan 5% households with toilets. Districtslike Balasore (34%) Ganjam (20%) andKhordha (22%) HHs with access totoilets were some of the best performers,inspite of very low coverage, with tribaldistricts like Malkangiri and Koraputshowing toilet coverage as low as 2.4%and 2.7% respectively, of the HHs withaccess to toilets. The total increase inIntegrated Household Latrine (IHHL) from2012 to 2016 is of 14% points in Odisha,with the maximum coverage reported in2015-16.

Table 2- Changes in 2013-14 to 2015 -16 in IHHL Sl Districts No. of HH

covered in 2013-14

No. of Households covered 2014-15 (including unapproved

% change No.of HH reported in [2015-16]

Total Balance uncovered HHs

% of HHS left

(1) (2) (3) (4) (5) (6) (7) (8) 1. Angul 397 10601 328.58% 54125 221000 71% 2. Balangir 3956 2690 -38.58% 49191 308185 81% 3. Bargarh 2599 3872 39.86% 65048 264847 68% 4. Ganjam 1481 3301 80.15% 85044 497561 71% 5. Koraput 415 4694 242.58% 37445 232807 83% 6. Malkangiri 21 2254 467.59% 23670 105634 79% 7. Kandhamal 46 5661 481.27% 36532 120321 71% 8. Khordha 469 3907 211.99% 40757 177765 67% 9. Cuttack 575 3917 191.87% 44726 362306 75% 10. Balasore 10055 12070 18.27% 81970 224737 44% 11. Sundergarh 875 3783 146.4% 73756 206431 65%

(GOI-MDWS: Target vrs Achievement- 2017)

While certain districts like Balasore andAngul have taken very sizeable andsuccessful leaps forward to challenge opendefecation, but seven of the eleven sampledistricts still continue to show more than

70% HHs without toilets. Below PovertyLine (BPL) families must be incentivizedto make toilets. Availability of water standsas a major impediment in IHHL use, andavailability of water must be linked with

181

construction of toilets, or fall backs canbe anticipated as in previous missions.

Some Highlights of IHHL

1. The highest expenditure on IHHL inOdisha has been made by Mayurbhanjdistrict with an expenditure of Rs2562.11 lakhs under the state shareand Rs 7685.84 lakhs under the centralshare, followed by Ganjam with anexpenditure of Rs 2526.05 lakhsunder the state share and Rs 7560. 16lakhs under the central share andBalasore stood third with Rs 2459.07lakhs under the state share and Rs7376.85 lakhs under the central share.

2. The lowest expenditure under IHHLin Odisha has been made by the districtof Boudh (Rs 904.41 lakhs) under thecentral share and (Rs 300.87 lakhs)under the state share. Though lowexpenditure may not signify lowcoverage, as Boudh is the smallestdistrict of Odisha with just 3 CD1

blocks. Kalahandi and Malkangiridistricts also continue to be lowspenders under IHHL.

3. Balasore now shows the secondlowest (44%) HHs left without toilets,just below Deogarh district with 41%.Malkangiri and Koraput with lowexpenditure under this head also stillhave 79% and 83% HHs respectivelyto be covered.

II. Solid and Liquid WasteManagement:To create clean environs, it is essential tofocus on IEC interventions emphasising on

Solid and Liquid Waste Management(SLWM) for creating a felt need for suchwaste management amongst the people.This should lead towards setting up ofmethods for scientific disposal of wastematerial in manners that have visibleimpacts on populations. The local selfgovernment has to be encouraged todemand for a system to manage waste intheir environment, and also take theresponsibility to operate and maintain.All the 30 districts of Odisha have not spenta single rupee under this head, Solid andLiquid Waste Management under the stateor central share; and even Khordha district,whose headquarters is Bhubaneswar thestate capital, seems to have drawn a blankunder this for the last two financial years2014-15 and 2015-16.In 2014-15, Gujarat had the maximumexpenditure both from the central and thestate share under SLWM with anexpenditure of Rs 1324.68 lakhs (central+ state share). 9 states including Odishamade no expenditure under this head. In2015-16, Gujarat was replaced byHaryana who topped the expenditureunder this head from both the Central andState share with an expenditure of Rs1309.19 lakhs. 12 states including Odishadrew a blank under this head. (GOI-MoDWS- District Wise State and CentralShare: 2015-16)

Such management is urgent and mustbe made while adhering to the rules of

1. Municipal Solid Waste Managementand Handling 2000



2. Environmental Protection Act 1986 3. Biomedical Waste Management and

Handling Rules 19984. Hazardous Waste Management and

Handling Rules 1989, 2003, 2008

III. Sanitary Complex

With the exception of Cuttack district noother district has made a sanitary complexin 2015-16. Cuttack district has made anexpenditure of Rs 8.4 lakhs from thecentral share and Rs 4.2 lakhs from thestate share, which is the only expenditureunder this head in this financial year. Noneof the other major urban hubs in the statehave invested on sanitary complexes in theyear, inspite of the emphasis on creatingurban infrastructure around sanitation bythe SBM. In 2014-15, from the stateshare, Rs 4.67 lakhs and central share Rs9.35 lakhs was spent by Cuttack; and theonly other districts who spent underSanitary Complex are Balasore andDhenkanal. There is a decline of 45% inexpenditure between 2014-15 and 2015-16, under this head.

IV. School Toilet

Very low emphasis has been paid to schooltoilets, even though 21% of schools remainwithout toilets in the state. Only Balasoreand Kendrapada, of the 30 districts havespent Rs 74,000 and Rs 3.92 lakhsrespectively (central share) andSundergarh and Khordha have spent Rs

32,000 and Rs 1. 68 lakhs respectively(state share) on school toilets in 2015-16.

As against this in 2014-15, the state hadspent Rs 188.35 lakhs under CentralShare and Rs 82.08 lakhs under stateshare. There is a 75% drop in expenditureunder this head between 2014-15 and2015-16.

V. Anganwadi Toilet

Not a single district of Odisha has incurredany expenditure on Anganwadi toilets (daycare centres for children), either from theCentral or State share in 2015-16. This isinspite of the fact that only 48.49% ofAnganwadis in the state have toilets. In2014-15 the state had also spent a mereRs 1.60 lakhs (both central and state shareinclusive) under this head.

VI. IEC

Two districts of Odisha, Gajapati andNayagarh have not spent a single rupeeeither from the state or Central share underIEC. State headquarters, Bhubaneswarhas spent only on one head, IEC. The totalexpenditure in IEC has been Rs 562.62lakhs in the year 2015-16. Theexpenditure in the year 2014-15 was Rs564.98 lakhs. There is a decline of 0.4%from the previous year.

Interstate ComparisonIf we look at component wise spending inthe year 2015-16, under the head of

6 Community Development7 Integrated Child Development Scheme

183

IHHL, Odisha spending at Rs 39,680.98lakhs (SS) and Rs 119030.59 lakhs (CS),stood next to only Rajasthan at Rs41730.95 lakhs (SS) and Rs 126577.75lakhs (CS) .The lowest spending was recorded bySikkim among states at Rs 44.72 lakhs,(37.78%) under the state share (The threeUTs of A&N Islands, D&N Haveli andPuducherry) did not spend at all, and thelowest spending under the Central sharewas again by Sikkim with an expenditureof Rs 400. 12 lakhs. The 3 UnionTerritories of A&N islands, Puducherryand D&N Haveli, did not spend evenunder the Central share. But Sikkim’s lowspending does not reflect poor sanitationcoverage for Sikkim.Spending under the head of CommunityIncentive to GP was seen only in the stateof Chattisgarh and Gujarat which spent Rs166.31 lakhs and Rs 499 lakhsrespectively.Under the head of sanitary complexes, thehighest spender was West Bengalspending Rs 282.03 lakhs in the state shareand Odisha stood at a poor 22nd positionwith a spending of Rs 4.2 lakhs in the stateshare; as far as Central shares wasconcerned, Puducherry spending Rs 560.5lakhs was at the top and Odisha was at alowly 23rd position with a spending of onlyRs 5.93 lakhs.Himachal Pradesh topped spending underSchool toilets with an expenditure of Rs803.62 lakhs under the central share andRs 74.39 lakhs under the state share andwith Odisha showing a mere spending of

2 lakhs from the state share and marginallymore at Rs 4.66 lakhs from the centralshare. (Contradictory data about centralspending in school toilets in Odisha is seenin the MDWS website). But Odisha hasmobilized sizeable funds from PublicSector Undertakings and even someprivate companies under their mandatoryCSR expenditure for the Swach VidyalayaCampaign in 2015-16.In Anganwadi toilets, Jharkhand with anexpenditure of Rs 74.25 lakhs and Jammuand Kashmir with a spending of Rs 36.57lakhs top the central share expenditurecharts on this head. Rajasthan with a stateshare expenditure of Rs 31.9 lakh has thehighest spending from the state share.Odisha spent nothing from either the stateor central share on anganwadi toilets,though only 48.49% of anganwadis in thestate have toilets. The visualization of theICDS2 programme of the anganwadi asan ECD (Early Childhood Development)centre and to be the first health post forchildren cannot be fructified without basicsanitation and toilets in the centres. Urgentutilization of funds under this head isrequired to make the anganwadi centres’sfunctional in the true sense, and not tomerely work as food distribution points.The maximum spending from the stateshare on IEC was done by West Bengalwith a spending of Rs 508.53 lakhs andOdisha at the 10th position with a spendingof Rs 151.35 lakhs. As far as central sharewas concerned, West Bengal tops here toowith a spending of Rs 1500.83 lakhs andOdisha in comparison at the 12th positionwith a spending of Rs 411.26 lakhs.



One of the prime drivers for change alwayshas been behavior change, more so inpractices which have a culturalconnotation. Ablution practices socio –culturally have been based around publicbodies like ponds, streams, as it is oftenconnected to the ritual life cycle of a familyand an individual and has important socio-cultural implications. These behavioralpractices only change gradually. Thusrepeated links between morbidity andopen defecation through constant use ofIEC in local languages can play animportant role in changing the behaviorpatterns. But Odisha continues to showpoor expenditure patterns on IEC, withonly two districts in the sample,Balasore and Bhubaneswar (Khordha)crossing an expenditure of Rs 50lakhs. Odisha must take a leaf out of theexample set by its neighbouring state, WestBengal here which shows an expenditureof more than 2000 lakhs under this headin 2015-16.

Training and Extension on Health,Hygiene and Behavioural Change-Major investments on innovative extensionservices are required, with a special celldevoted to dissemination of IEC. Theextension services must be monitored andcoordinated with the panchayat to makeit more effective. Districts like Koraput,Malkangiri, Balangir which still have lowcoverage in IHHL and also in the othercomponents of SBM continue to alsoshow poor expenditure on IEC. They mustbe encouraged to use IEC moreextensively at effective points.

It is the role of village level extensionworkers, as well as the PRI functionariesto most effectively transmit information onpractices related to use of basic social andphysical infrastructure. Lack of training onthe causal relationship between morbidityand bad sanitation, stands as animpediment in working as an effectivechange agent in areas like sanitation.Training of all PRIs and extension workers

185

is an investment required to make thecampaign more effective.

Conclusion

The Swaccha Bharat Mission has clearlynot been just about increased budgets forsanitation, but States like Odisha whichhave long been laggards in the area ofsanitation have also seen clear increase innot just spending and expenditure, but inthe coming up of real time infrastructureboth at the household level and the publicinstitution level. But important areas likeSchool toilets, Anganwadi toilets whichhave an important role in not just checkinghigh IMR1 and CMR2, but also increasingenrolment and retention of girls in theschools- continue to be neglected.

And is the shift away from Drinking waterto sanitation, an appropriate mechanism;will shifting the emphasis away fromdrinking water not be just addressing theproblem in halves as clean drinking waterplays an equally important role, as bettersanitation for good health. Is it not essentialand appropriate to increase investmentsin both the areas, as a healthy workforcecan better contribute to economic growthand human development?

The importance of IEC in contributing tothe ultimate success of a sanitation programis clearly not seen in states like Odisha,whose focus in spite of several failedsanitation missions continue to be only onphysical infrastructure and not onbehavioral change. Behavioral change mayultimately be the key in the important area

of water and sanitation and its neglectcould be the missing link.

Acknowledgements: I thank UNICEF,Odisha for the support to conduct thisstudy and specifically my colleague MrSubhanil Banerjee for helping me to finalisemy sample and suggesting appropriatestatistical tools.

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GOI-MDWS, SBM Gramin. Format B2(b) District wise State ShareExpenditure(Approved) for Finance year2015-2016.. http://sbm.gov.in/tsc/Report/Financial/Rpt State District ExpYearwise.aspx?id=Home; (accessed 4April 2017).GOI-MDWS, Outcome Budget, 2015-16. Retrieved from http://www.mdws.gov.in/sites/default/files/outlay.pdf on 31/10/2017Gopalakrishnan S. BUDGET 2015:Sanitation and the Swachha BharatMission. http://sanitation.indiawaterportal.org/english/node/3234(accessed 15 November 2016).Kapur A, Iyer S, Accountability InitiativeResearch and Innovation for GovernanceAccountability. Budget Briefs 2015-16;7(5): http://accountabilityindia.in/sites/default/files/sbm_2015.pdf (accessed 26/11/2016).Mara D, Lane J, Scott B, Trouba D,Sanitation and Health. PLoS Med, (2010)7(11): e1000363. doi:10.1371/journal.pmed.1000363Mishra S.N, Ghadai S.K, Merit Goods,Education Public Policy– India At CrossRoads, Journal of Education and Practice,Vol.6, No.12, 2015. Available at http://files.eric.ed.gov/fulltext/EJ1080710.pdfThomas. D, Frankenberg. E, Health,nutrition and prosperity: a microeconomicperspective. Bull World Health Organ,Jan. 2002; Vol.80 n.2 Genebra : 1UNICEF India: newsletter: Eliminate OpenDefecation, Available at http://unicef.in/Whatwedo/11/El iminate-Open-Defecation.

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Reference from Journal:Alkaike, H. (1987). Factor analysis and AIC. Psychometrica, 52, 317-332.

Reference from Edited book:Browne, M. W. & Cudeck, R. (1999). Effects of Organizational Climate and CitizenshipBehavior on Organizational Effectiveness. In K.A. Bollen & J.S. Long (Eds.) HumanResource Management (pp. 136-147). Newsbury Park, CA: Sage.

Reference from Book:Luthans, F. (2002). Organisational Behaviour. New Delhi: McGraw-Hill International.Booth, W. C., Colomb, G. G., & Williams, J. M. (1995). The craft of research. Chicago:University of Chicago Press.

Reference from online resources:Hacker, D. (1997). Research and documentation in the electronic age. Boston: BedfordBooks. Retrieved October 6, 1998, from http://www.bedfordbooks.com/index.htmlMorse, S. S. (1995). Factors in the emergence of infectious diseases. Emerging InfectiousDiseases, 1(1). Retrieved October 10, 1998, from http://www.cdc.gov/ncidod/EID/eid.htm

Smith, E. E. (2001). Internet term paper mills: The case for mandatory expulsion[Electronic version]. Journal of Crime and Punishment, 6, 123–139.

Newspaper ArticleGoleman, D. (1991, October 24). Battle of insurers vs. therapists: Cost control pittedagainst proper care. New York Times, pp. D1, D9.

Newspaper Article (Online)Markoff, J. (1996, June 5). Voluntary rules proposed to help insure privacy for Internetusers. New York Times. Retrieved April 1, 1996, from http://www.nytimes.com/library/cyber/week/yo5dat.html

Newspaper Article (No Author)Undisclosed settlement reached out of court in Michigan Biodyne civil suit. (1992, March1). Psychiatric Times, p. 16.

Conference Paper (Published):Kuroda, S. Y. (1988). Whether we agree or not: A comparative syntax of English andJapanese. In W. J. Poser (Ed.), Papers from the second international workshop onJapanese syntax (pp. 103–143). Stanford, CA: CSLI.

Dissertation:Downey, D. B. (1992). Family structure, parental resources, and educational outcomes.Ph.D. dissertation, Department of Sociology, Indiana University, Bloomington, IN.

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