amity journal of marketing 2(1), (49–60) ©2017 admaa ... 5.pdfof female millennials while...

Volume 2 Issue 1 2017 AJM

49Amity Journal of Marketing ADMAA

IntroductionOnline shopping is buying products electronically using internet. It brings a plethora of

merchandise to consumers and a large reservoir of business opportunities to entrepreneurs (Guo June and Noor, 2011). India’s population is taking to online retail in a big way.

The Retail Industry Scenario in India

Progressive financial developments, increasing salary levels, urbanization, changes in demographic distribution and consumer preferences is triggering exponential expansion of retail market in Indian. Its development is significant in urban cities and metros, as well as in Tier-II and Tier-III cities. Key statistics -

A Boston Consulting Group study projected a consumption of about US$ 400 billion by 2025 leading India to be the world’s third largest consumer economy.

India’s retail market is expected to increase by 60 per cent by 2020 with a market size of

Amity Journal of Marketing2(1), (49–60)

©2017 ADMAA

Consumer Behaviour towards Online Shopping: Structural Equation Modeling Approach

Hemalatha J & Lalitha BalakrishnanM O P Vaishnav College for Women, Chennai, Tamilnadu, India

AbstractWith exponential growth in the retail market and internet usage in India’s Consumer economy, there is

tremendous avenues for online shopping. Keeping in mind the goal to survive and exceed expectations in this competitive situation, e-tailers need to comprehend buyer behaviour to tailor their product offering to guarantee customer satisfaction. This modern and convenient mode of shopping is a growing trend among people, especially the tech-savvy millennials who also appreciate that prudent use of technology is essential to ensure satisfactory online shopping experience. This study was undertaken to establish a relationship between three parameters - Consumer Prudence, Consumer Shopping Experience and its effect on Consumer Satisfaction in online shopping. The target demographic for this study was female millennials in Chennai city from whom 105 valid sets of questionnaire, out of 120 distributed, were used for hypothesis testing. The study confirms the positive relationship between the three parameters – Consumer Prudence, Consumer Shopping Experience and Consumer Satisfaction.

Key words: Online shopping, Millennials, Consumer Prudence, Consumer Satisfaction

JEL Classification: M31

Paper Classification: Research Paper

Volume 2 Issue 1 2017AJM

50 Amity Journal of MarketingADMAA

US$1.1 trillion from US$ 672 billion in 2017 (IBEF, 2018).

By 2025, India is the world’s fastest growing online retail and is set to be the world’s second largest with projections of US$ 220 billion in terms of gross merchandise value (GMV) and 530 million shoppers (IBEF, 2018).

Online Shopping – The Consumer Perspective

Shopping online gives numerous advantages and benefits because of which more people prefer buying things online over going into traditional brick and mortar stores.

Some reasons why people prefer this mode are

Convenience, as shopping can be done anytime, anywhere that suits the customer’s comfort, thus saving time, effort and the ordeals of crowded marketplaces (Sanjeev et el, 2014).

wide product choices in one location from a variety of products and brands from multiple dealers (Ashwini et el, 2016).

price comparisons are easier and

reviews and recommendations from other product users (Ashwini et el, 2016)

Need for Consumer Prudence

For all its benefits, however, online shopping has its pitfalls. Online scams are on the rise, and scammers are increasingly sophisticated in their ways. Since buyers are not able to check out the sellers and goods in person, online shopping also poses inherent risks which can be

product risk caused by deceptive online reviews, fake or defective products, non-arrival of order

financial risk that can result from misleading claims on costs or lack of secure system in online payment

privacy risk such as phishing or identity theft.

In order to secure the maximum benefits offered by Online Shopping and to avert risks, consumers need to take necessary precautions by exercising prudence.

Consumer prudence can be exercised by shopping online only at home and not on a public computer, which may be infected with malware; buying in secured sites from reputable retailers; using safe payment options; careful study of terms and conditions of sale and return policy.

Significance of StudyIndia’s huge population, the second in the world has 34 per cent millennials who are the

breadwinners of their households (Rajagopalan et al, 2018). Its growth as a consumer economy is accelerated by the young population, increasing literacy and income levels and standard of living. This technically-savy young population, with the catalystic power of easy availability of high-speed mobile wireless internet coupled with a range of attractive and convenient product offerings in the e-commerce platform, are leading major channel shifts from traditional offline to modern online shopping. (Lu et al, 2016; Joshua Lu, 2016).

To exploit the benefits of e-shopping offered by the digital media, shoppers need to be prudent while placing orders online and making online payments.



With India ready for boom in Online shopping and the millennials being catalytic in this exponential growth, the study aims to understand the habits, experiences and the satisfaction level of female millennials while shopping online.

Objectives The purpose of this study is:

1. To gain knowledge about millennials’ online shopping habits.

2. To observe the extent of prudence exercised while shopping online by the consumer. Observe its effect on the online shopping experience and the consequent level of consumer satisfaction.

3. To devise a Structural Equation Model to gauge Consumer Satisfaction in Online Shopping and examine its usefulness.

Literature ReviewConsumer behavior in online shopping is a complex socio-technical phenomenon. Prior

studies have identified different factors that affect online consumer behavior.

Koufaris (2002) emphasized on two aspects that influence online consumer shopping behaviour. Firstly, as a traditional shopper, it is important to ensure an enjoyable shopping experience for the online shopper. Secondly, as a computer user, both the web design and the consumer’s computer skills play a vital role to ensure smooth ease of operation.

Pavlou (2003) proposed an e-commerce acceptance model and subsequently Pavlou and Fygenson (2006) validated the variables. Other variables identified were - trust, website and product characteristics, consumer skills and consumer resources (time and money). Tonita et al. (2004) observed the influence of exogenous factors such as trust and past experiences in online shopping websites, product characteristics, consumers’ demographic and personality traits and situational factors facilitated by convenience and accessibility in online shopping. Balamurugan, Sathish and Sathyanarayanan (2013) confirmed that consumer’s shopping intent is affected by his perception regarding convenience and safety of internet usage, risk and product characteristics which has to be appropriately addressed by e-tailers. Jayasubramanian et al (2015) while exploring the level of consumer satisfaction in online shopping, observed that despite numerous advantages, fraud and privacy concerns caused due to web-hackers is a source of great concern to users though website users are doing their best to ensure secure portals. Yi Jin Lim et al. (2016) examined the influence of subjective norm (social pressure) and perceived usefulness on purchase intention that mediates online consumer behaviour. Pantos and Pariporas (2016) observed that secure online platforms support consumer’s lifestyle with advantages of saving time, money; supporting and quality service have motivated increasing number of people to shift from traditional shops to e-shopping using computer and mobile phones. Clemons et al. (2016) studied Trust perceptions on the Online Platform in developed and emerging economies. Their finding revealed that reputation of e-vendor, third-party assurances and legal protection are vital elements in less experienced markets. Kothari and Maindargi (2016) pointed out the importance of five factors - shopping enjoyment, comfort, security, usefulness and cognition impacted consumer attitude in Solapur city while shopping online. Khurana S and Kaur B (2017) conducted a detailed literature review to understand the evolution of consumer behavioural models using different variables pertinent



to different time periods. Senthilkumar and Chandramohan (2018) observed that demographic factors had a significant impact on satisfaction levels among Namakkal district’s online shoppers.

There is however, little literature on extent of prudence exercised by consumers to avert online shopping risks to secure satisfactory online shopping experience.

Theoretical Framework for the Study

A Structural Equation Model (SEM) was formulated to understand consumer behaviour in the online shopping behaviour of millennial consumers. The SEM verifies -

(1) the influence of Consumer Prudence on Consumer Shopping Experience

(2) the relationship between Consumer Shopping Experience and Consumer Satisfaction.

Research Methodology

Data collection, Sample and Analysis

Primary data for the study was collected from 120 young female college-going millennials in Chennai using questionnaire. Usable responses were 105 that was used for the analysis of the study using Analysis of a Moment Structures (AMOS) and SEM. Questions were designed to gauge three variables - Consumer Prudence, Consumer Shopping Experience and Degree of Consumer Satisfaction in Online Shopping. Articles from journals and online publications were also referenced to secure secondary data.

Results and Discussion

Profile of Respondents

The profiles of 105 young female millennial respondents was mapped based on annual income, frequency of online purchase and technical independence during online purchase transaction. Also their online shopping habits with respect to commodities shopped, websites and payment mode used was queried upon.

With respect to Annual Income, 6.7 per cent were below Rs. 2,50,000 ; 35.2 per cent were between Rs. 2,50,00 and Rs. 5,00,000 ; 36.2 per cent were between Rs. 5,00,000 to Rs. 10,00,000 and 21.9 per cent were above Rs, 10,00,000.Most respondents (48.6 per cent) had irregular frequencies in online shopping; 34.3. per cent shopped at least once a month; 10.5 per cent at least once every fortnight and 6.7 per cent shop online at least once every week. With regard to technical independence during online purchase, 37 per cent respondents always handle the complete online purchase transaction themselves, while 21 per cent did so often; 35 per cent said ‘sometimes’ and 10.5 per cent respondents never handled their online purchase transaction themselves.

Table 1 shows that most shopped commodity online was Apparels and Accessories (66.67 per cent) and Mobile Phones (37.14 per cent); and popular mode for payment is Cash On Delivery (79.05 per cent) and Credit Card (16.19 per cent). Out of the total respondents, 66.67 per cent respondents had faced problems while shopping online, most common being Delay in Delivery (32.38 per cent) and Cheap quality of Product (31.43 per cent).



Table 1.Online Shopping Habits of Young Female Millennials

Table 1.1 Commodities shopped

Commodities Frequency (out of 105)

Percentage

Apparels and Accessories

70 66.67

Mobile Phones 39 37.14

Books 26 24.76

Electrics and Electronics

22 20.95

Groceries 8 7.62

Health Supplements 2 1.9

Curios 1 0.95

Table 1.2 Payment Mode

Payment mode Frequency (out of 105)

Percentage

Cash On Delivery 83 79.05

Credit Card 17 16.19

Debit Card 6 5.71

Net banking 2 1.9

Mobile Money 83 0

Table 1.3 Problems faced

Problems faced Frequency (out of 105)

Percentage

Delay in Delivery 34 32.38

Cheap Quality of Product

33 31.43

Product Damage 20 19.05

Non-delivery 6 5.71

Reliability and Validity Analysis for Dimensions in Online Consumer Behaviour

Table 2 shows that reliability and consistency using Cronbachs alpha coefficient (Gliem and Gliem., 2003) of the three dimensions of Online Shopping, measured with Likert- type scales, used in the study are acceptable for Consumer Prudence and Consumer Satisfaction (0.8 > α≥0.7)andgood for Consumer Shopping Experience (0.9 > α≥0.8).

Table 2. Reliability Analysis for Online Consumer Behaviour Dimensions

Variables No. of Attributes Cronbachs Alpha

Consumer Prudence 19 0.7492

Consumer Shopping Experience 15 0.8605

Customer Satisfaction 5 0.7258

Structural equation modeling (SEM) of Consumer Behaviour in Online Shopping

The SEM variables are:

A. Observed, endogenous variables1. Consumer Shopping Experience

2. Consumer Satisfaction

B. Observed, exogenous variables 1. Website Safety

2. Payment Safety



3. Product Selection

4. Transaction Safety

These are also observed as dimensions of Consumer Prudence.

C. Unobserved, exogenous variables1. e1: Error for Consumer Shopping Experience

2. e2: Error for Consumer Satisfaction

Hence, the numbers (No.) of variables in the SEM are

Total No. of variables = 8

No. of variables that are observed and exogenous = 6

No. of variables that are unobserved and endogenous = 2

Table 3. Descriptive Statistics of Consumer Prudence Dimensions of Young Female Millennials Online Shoppers

Dimensions of Consumer Prudence Mean Standard Deviation

Dimension 1 – Website Safety

Use of only familiar websites 4.429 0.830

Get suggestions from known-trusted persons for online purchase websites 3.876 0.997

Ensure security locks (HTTPS:// instead of just HTTP://) in the website before placing order 3.714 1.238

Regularly update anti-virus software in Personal Computer system 4.038 1.143

Spontaneous use of Public Terminals (like in airports, coffee shops, etc.) to place online orders, in case of need

3.010 1.326

Dimension 2 – Payment Safety

Ensure that the vendor company has complete contact details including a street address 4.362 0.878

Compare prices and quality of products on different sites prior to making a purchase 4.257 0.821

Check terms and conditions carefully in order to rule out any restrictions or hidden costs 4.133 1.093

Ensure safe payment mode for online purchases 4.467 0.821

Regularly check electronic statements of personal Debit Card / Credit Card and Account status

3.486 1.210

Prefer online payment rather than cash on delivery 2.895 1.493

Immediately address errors in online bank statements 4.029 1.096

Dimension 3 –Product Selection

Examine a similar product in a retail outlet before placing online order 3.867 1.101

Always read the reviews and the ratings given for the product 4.171 0.893

Get influenced by advertisements in computer pop-ups and media 3.067 1.137

Compare the quotes from different online vendors for the product’s price 3.800 1.078

Dimension 4 –Transaction Safety

Can check the progress of online order in the vendor’s website 4.381 0.825

Keep copies of all documents and electronic records in case there is a problem later 4.086 1.020

Personal information given when placing orders online is secure and not misused 3.981 0.920



Table 4. Descriptive Statistics of Consumer Shopping Experience Dimensions of Young Female Millennials Online Shoppers

Dimensions of Consumer Shopping Experience Mean Standard Deviation

Dimension 1 – Product Satisfaction

Received the correct product(s) ordered, as per specifications 4.276 0.714

Product(s) was of satisfactory quality 3.943 0.853

Product(s) was not damaged 3.924 1.053

Order Tracking facility is easy, convenient and effective 4.114 1.059

Dimension 2 – Accurate Delivery

Received timely delivery of product(s) ordered 4.190 0.867

The time of delivery was convenient 4.000 0.899

Neat and appropriate packing of goods that ensured minimal to no damages 4.219 1.000

Dimension 3 – Safe Payment

The payment mode is safe 4.410 0.874

The payment mode is convenient 4.190 0.878

No experience of any wrong billing / payment secured 3.933 1.137

Dimension 4 – Response for Grievances for faulty goods

Shopping websites provide proper consumer desk to address grievances 4.267 0.858

Obtained proper redressal under appropriate desk 3.724 1.114

Collection of faulty / damaged goods at convenient time 3.886 1.050

Obtained corresponding credit for goods returned 3.705 1.082

The goods return policy is convenient 3.714 1.191

Table 5. Descriptive Statistics of Consumer Satisfaction Dimensions of Young Female Millennials Online Shoppers

Dimensions of Consumer Satisfaction Mean Standard Deviation

Online shopping is better preferred than Physical Retail Stores 3.638 0.972

Online shopping is Time Saving 4.219 0.734

Product prices are cheaper when purchased online 3.943 0.928

Comparison of prices is easier online 4.114 0.902

Online Shopping is more convenient than purchasing in a retail store 4.095 0.995

Figure 1. Structural Equation Model of Consumer Behaviour in Online Shopping



Table 6. Variables in SEM Analysis

Variables Unstandardised Co-efficient

S.E Standardised Co-efficent

t value P value

Consumer Shopping Experience

<--- Website Safety 0.570 0.165 0.289 3.446 <0.001**


<--- Payment Safety 0.525 0.151 0.291 3.469 <0.001**


<--- Product Selection 0.678 0.228 0.217 2.971 0.003**


<--- Transaction Safety 0.654 0.285 0.174 2.293 0.022*

Customer Satisfaction <--- Consumer Shopping Experience

0.234 0.036 0.640 6.516 <0.001**

Note: 1. ** Indicates 1% significant level 2. * Indicates 5% significant level

All the variables; website safety, payment safety, product selection, transaction safety and consumer shopping experience are statistically significant as all their p-values are lesser than 0.01 except for Transaction Safety whose p-value is less than 0.05 . The coefficients of all the variables are positive hence indicating a positive effect.

We can thus infer that Consumer Shopping Experience will increase by 0.570, 0.525, 0.678 and 0.654 for every 1 unit increase in Website Safety, Payment Safety, Product Selection and Transaction Safety respectively. Also statistically significant inference from results indicate that Consumer Satisfaction is augmented by 0.234 for a unit increase in Consumer Shopping Experience as the p-value is less than 0.01

Based on Standardised coefficient, to ensure good Consumer Shopping Experience, the most important factor is Payment Safety (0.291), followed by Website Safety (0.289), and Product Selection (0.217). The least important is Transaction Safety (0.174)

Test of Hypothesis

H0: The hypothesized model has a good fit. This implies that exercise of Consumer Prudence to ensure website safety, product safety, payment safety and transaction safety has a positive effect on the Consumer’s Shopping Experience and a satisfactory Consumer Shopping Experience will result in Consumer Satisfaction.

H1: The hypothesized model does not have a good fit.

Table 7. Model fit summary of Structural Equation Model

Indices Value Suggested value

Chi-square value 3.769 -

P value 0.288 > 0.05 ( Hair et al., 1998)

GFI 0.988 > 0.90 (Hu and Bentler, 1999)

AGFI 0.918 > 0.90 ( Hair et al., 2006)

CFI 0.998 > 0.90 (Daire et al., 2008)

RMR 0.034 < 0.08 ( Hair et al., 2006)

RMSEA 0.050 < 0.08 ( Hair et al., 2006)



Table 7 shows that the calculated values and that all the parameters are within the permissible limits. Therefore, the null hypothesis, H0 is accepted and inferred that the hypothesized model has a good fit.

Conclusion and ImplicationsInferences in study were made from the analysis of data from respondent-millennials, most of

them having an Annual Income between Rs. 5,00,000 to Rs. 10,00,000 with irregular frequencies in Online Shopping who are ‘technically independent’ to handle the complete online purchase transaction themselves. With regard to online shopping habits, it is observed that

the most shopped commodity online was Apparels and Accessories and Mobile Phones

popular mode for payment is Cash On Delivery

fewer used electronic methods of payment

The principle aim of developing and affirming a SEM is to gauge Consumer Satisfaction in Online Shopping. An empirical analysis was conducted using data collected from young female millennials in Chennai city to examine the relationship among three factors identified namely, Consumer Prudence, Consumer Shopping Experience and Consumer Satisfaction It is concluded that the proposed model (Figure 1) satisfactorily describes Consumer Behaviour using the three factors. Statistical results show a high level of reliability of the data used in analysis and also the proposed model.

The four dimensions of Consumer Prudence- Website Safety, Payment Safety, Product Selection and Transaction Safety greatly impact Consumer Shopping Experience that will affect the level of Consumer Satisfaction. When a customer has a good shopping experience in a safe online shopping platform, he gets satisfaction. To ensure good consumer shopping experience, consumers also need to exercise prudence to ensure safety – the most important areas being Payment Safety and Website Safety.

Many respondents had faced problems while shopping online, the most common being delay in delivery and cheap quality of product. These findings clearly throw light on areas in which e-tailers must be focusing on to devise strategies to provide good customer service when marketing to prospects online. E-tailers need to develop online portals that provide safe platforms for a satisfactory online shopping experience for customers with efficient delivery systems and redressal mechanisms. This will further boost consumer confidence in the system and boost online trade.

Limitations and Future ResearchThe study was confined to college-going young female millennials in Chennai city. Further

research to investigate the determinants of the Online Shopping Consumer Behaviour in other regions with different demographic backgrounds, incorporating more variables will facilitate better understanding of Consumer behavior.

ReferencesAmerican Express, (2016, April 12). Online Shopping Overtakes Social Networking in India - American Express -

Nielsen survey. Retrieved from www.americanexpress.com/in/content/news/

Ashwini, N. & Manjula, R. (2016), An Empirical Study On Consumers Perception Towards Online Shopping, International Journal of Management and Commerce Innovations, 3(2), 1103-1110.



Ajzen, I. (1991). The Theory Of Planned Behavior. Organizational Behavior and Human Decision Processes, 50, 179–211.

Balamurugan, R.N., Sathish, M. & Sathyanarayanan, R.S., (2013). Consumer Behavior towards Online Shopping: A Study with reference to Coimbatore City. TMC Academic Journal, 8, 43-53

Bentler, P.M. and Bonnet, D.C., (1980). Significance Tests and Goodness of Fit in the Analysis of Covariance Structures. Psychological Bulletin, 88(3), 588606.

Clemons E. K., Wilson J., Matt C, Hess T, Fei Ren, Fujie Jin. & Noi Sian Koh (2016). Global Differences in Online Shopping Behavior: Understanding Factors Leading to Trust. Journal of Management Information Systems, 33(4), 1117–1148.

Daire, H., Joseph, C., Michael, R.M., (2008). Structural Equation Modeling: Guidelines for Determining Model Fit. Electronic Journal of Business Research Methods, 6, 53-60.

Gliem, J.A. & Gliem, R.R., (2003). Calculating, Interpreting, and Reporting Cronbach’s Alpha Reliability Coefficient for Likert-Type Scales. Paper presented at 2003 Midwest research-to- practice conference in Adult, Continuing, and Community Education, Columbus, Ohio.

Guo, J. & Noor, I.J. (2011), A study on Consumers’ Attitude towards Online Shopping in China. International Journal of Business and Social Sciences, 2, 22.

Hair, J.F., Anderson, R.E., Tatham, R.L. & Black, W.C., (1998). Multivariate Data Analysis, 5th Edition. Prentice Hall : New Jersey.

Hair, J.F., Anderson, R.E., Tatham, R.L., Black, W.C. & Babin, B.J., (2006). Multivariate Data Analysis, 6th Edition., New Delhi : Pearson Education.

Hu, L.T., Bentler, P.M., (1999), Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria versus New Alternatives. Structural Equation Modelling: A Multidisciplinary Journal, 6, 1-55.

India Brand Equity Foundation, (2018, June). Retail Industry in India. Retrieved from https://www.ibef.org

Jarvenpaa, S.L. & Todd, P.A. (1997). Consumer Reactions to Electronic Shopping on the World Wide Web. Journal of Electronic Commerce, 1, 59-88.

Jayasubramanian, P., Sivasakthi, D. & Ananthi Priya, K. (2015), A Study on Customer Satisfaction towards Online Shopping. International Journal of Applied Research, 1(8), 489-495.

Joshua, Lu. (2016, July). The Rise of India’s Young Consumers, Retrieved from http://www.goldmansachs.com/our-thinking/pages/rise-of-the-india-consumer.html

Equity Research (2016). India Consumer Close-Up: Tapping the spending power of young, connected Urban Mass. Goldman Sachs Report. New York : Lu, J., Yiu, A. & Soman, A.

Khurana, S. & Kaur, B. (2017). Online Consumer Behaviour Models: A Literature Review, Biz and Bytes, 8(1), 209-217. Retrieved From: http://cbsmohali.org/img/journal_3-1-9.pdf

Kotler, P., Cunningham, M. H., & Turner, R. E., Marketing Management, Pearson Education Canada, 2001.Luarn, P., and Lin, H.H. (2003), Customer loyalty model for e-service context, Journal of Electronic Commerce, 4, 156-167.

Kothari P. Pritam, Maindargi S. Shivganga, (2016), A Study on Customers Attitude towards Online Shopping in India and its Impact: With Special Reference to Solapur City, International Journal of Advance Research , Ideas and Innovations in Technology, 2(6), 1-10. Retrieved From www.Ijariit.com



Koufaris, M., (2002), Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205-223

Luarn, P., & Lin, H.H. (2003), Customer Loyalty Model for E-Service Context. Journal of Electronic Commerce, 4, 156-167.

Li Na & Ping Zhang (2002). Consumer Online Shopping Attitudes and Behavior: An Assessment of Research. AMCS 2002 Proceedings. Retrieved from http:aisle.aisnet.org/amcis2002/74

Pankaj, A. (2012), Potential of Organised Retail in India. International Journal of Engineering and Management Sciences, 3, 456-460.

Pantos, E. & Pariporas, C.V. (2016). The effect of mobile retailing on consumers’ purchasing experiences: A dynamic perspective, Computers in Human Behaviour, 6, 548-555. Retrieved from https://doi.org/10.1016/j.chb.2016.03.071

Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 69-103.

Pavlou, P. A. & Fygenson, M. (2006), Understanding and predicting electronic commerce adoption: An extension of the theory of planned Behavior. MIS Quarterly, 30(1), 115-143.

Deloitte Report (February 2018). Trend-setting millennials - Redefining the consumer story. Retrieved from : rls.net.in/wp-content/uploads/2018/02/Trendsetting-Millennials-RAI-Deloitte.pdf

Reibstein, D. J., (2002), What attracts customers to online stores, and what keeps them coming back?. Journal of the Academy of Marketing Science, 30, 465-473.

Kumar., S.N., Chandramohan, K.L. (2018), A Study On Customer Satisfaction Towards Online Shopping with reference To Namakkal District, International Journal of Current Research and Modern Education, 3(1), 348-351.

Sanjeev K and Savita M, (December 2014). Status and Scope of Online Shopping: An Interactive Analysis through Literature Review. International Journal of Advance Research in Computer Science and Management Studies, 2(12), 100-108.

Schaupp, L. C., & Bélanger, F., (2005). A conjoint analysis of online consumer satisfaction. Journal of Electronic Commerce Research, 6, 95-111.

Taylor, J. W. (1974). The role of risk in consumer behavior. Journal of Marketing, 8,54-60.

Tonita, P.M., Benedict. G.C., Dellaert & Ko De Ruyter. (2004). What drives consumers to shop online? International Journal of Service Industry Management, 15, 102-121.

Lim, Y.J., A. Osman, A., Salahuddin, S.N., Romle, A.R., & Abdullah, S. (2016). Factors Influencing Online Shopping Behavior: The Mediating Role of Purchase Intention, Procedia Economics and Finance, 35, 401 – 410.

Yu-Kai, H. (2009). The Effect of Airline Service Quality on Passengers Behavioral Intentions Using SERVQUAL Scores, A TAIWAN Case Study. Journal of the Eastern Asia Society for Transportation Studies, 8, 4-5.



Authors’ Profile

Hemalatha J is currently pursuing her doctoral degree in Commerce from the University of Madras, Chennai, India under the guidance of Dr. Lalitha Balakrishnan. The area of study is Consumer Behaviour in Online Shopping. She has authored paper publications in two international and one national journal(s) in the area of Consumer Behaviour and Auditing. She has also two press releases in Gulf newspapers based on pilot study and research. After a brief career in corporates, she has moved on to pursue a teaching career since the last 15 years in schools and college. She has taught students from diverse age groups, cultures and education systems in India and the Gulf and has worked in International schools in Riyadh, Bahrain, Kuwait and India for over a decade. Her latest assignment was at MOP Vaishnav College in Chennai as Assistant Professor in the Department of Commerce.

Lalitha Balakrishnan, Principal and Head, Research Department of Commerce, M.O.P Vaishnav College for Women, Chennai, India is an educational administrator with 25 years of teaching experience. She is a University rank holder and gold medalist. She has authored 3 books – Human Resources Development, Organisational Development and Training & Development. She has produced 5 doctorates, has paper publications in many National and Inter-national journals and has also been an invited speaker in many reputed institutions such as IIT and GLIM apart from serving as resource person in international and national forums. She has been an invitee of the US Department of State as an Exchange Grantee under the prestigious IVLP – International Visitor Leadership Program. She has also won many accolades and awards like “Bharathi Kanda Pudumai Penn” and “Educational Achiever Award”

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