customers cognizance factors influencing …

www.tjprc.org SCOPUS Indexed Journal [email protected]

CUSTOMERS COGNIZANCE FACTORS INFLUENCING PURCHASING DECISION

OF DESIGNATED DAIRY PRODUCTS

Dr. S. SENTHILKUMAR1, Dr. SUDHAKAR KOTA2, K. SRIVIDYA3,

Dr. A. RADHIKA4 & Dr. B.JAYALAKSHMI5 1Professor in Finance & Management, Skyline University, Nigeria

2Vice Chancellor, Skyline University, Nigeria

3PhD Research Scholar in Statistics, Periyar University, India

4Assistant Professor in Statistics, Periyar University, India

5Asst Prof in Business Administration, Mahendra Arts & Science College, India

ABSTRACT

This study mainly deals with customer purchasing decision of leading dairy brands. The consumption pattern of dairy

products in India has some contrasting contours that do not align with the western world. In India Consumption is

primarily skewed towards traditional products: however, westernized products are gradually gaining momentum in the

urban areas. The study also measures the product knowledge and purchasing decision factors. The researcher

presented this study to find the customer’s product awareness of dairy brands, key factors involved in customers’

purchasing decision and to examine the essential information preferred by respondents while purchasing dairy

products. This study will be highly helpful to the business entities can succinctly understand consumers’ needs and

expectations towards leading brands of dairy products. The collected data was analyzed with hypothetical test by using

statistical tools such as percentage analysis, Henry Garrett Ranking method, ANOVA and Factor Analysis was also

used to find the respondents’ opinion towards the influencing factors on purchasing decisions of dairy products.

KEYWORDS: Purchase decisions, Product knowledge, Marketing mix & Innovative dairy products

Received: Jun 10, 2020; Accepted: Jun 30, 2020; Published: Jul 15, 2020; Paper Id.: IJMPERDJUN2020338

INTRODUCTION

Dairy industry inhabits an important place in Indian economy. It includes production of milk, its preparation for

sale as well as manufacturing of dairy products. The growth of Indian dairy as a part of primary activities has been

prodigious for the past three decades. The Indian dairy industry is not only a vital producer of an essential food

item but it also is the largest employer in the country in both the rural sector and in the semi urban and urban

regions as well. It gives an opportunity to about eighty million families in direct and indirect employment activities

across India. Effective demand will come mainly from middle and high income consumers in urban and metro city

areas in India. There are ways to mitigate the effects of unequal distribution of incomes. The researcher reviewed

current Indian dairy scenario and based on the gap from review of earlier studies finds the fissure and select this

title by connecting dairy product knowledge and factors behind for purchase decisions of dairy products.

METHODOLOGY

A good research work requires a clear scientific methodology because only through the application of correct

methodology in selection of sampling techniques, appropriate tools of data collection etc. the problem can be

Orig

ina

l Article

International Journal of Mechanical and Production

Engineering Research and Development (IJMPERD)

ISSN (P): 2249–6890; ISSN (E): 2249–8001

Vol. 10, Issue 3, Jun 2020, 3557-3568

© TJPR Pvt. Ltd.

3558 Dr. S. Senthilkumar, Dr. Sudhakar Kota, K. Srividya,

Dr. A. Radhika & Dr. B.Jayalakshmi

Impact Factor (JCC): 8.8746 SCOPUS Indexed Journal NAAS Rating: 3.11

identified. So that the well founded conclusion can be drawn on the phenomena under consideration. In the present study

though it an empirical format, the researcher collects the data through primary sources with the tool of structured

questionnaires.

Research Design - Descriptive Research Design

Sampling Design - Cluster sampling Design

Sampling Area – Salem District of Tamilnadu, India

Tools used for Analysis

Percentage analysis Analysis of Variance (ANOVA)

Henry Garrett Ranking Method Factor Analysis

Snapshot of Review of Literature

1. Maulik C. Prajapati and Ashish K. Makwana (2017) examine the impact of brand equity on purchase decision of dairy products in milk city Anand. The results suggest a remarkable relationship between brand equity

and purchase decision.

2. Renata Hrubá (2016) deals with the problem of analysis of the attitudes toward food that influence the

behavior and decision-making of consumer when buying food from particular processors. Study results, which

were obtained by Logit Regression Models, thus indicate that intension of buying from a particular processor is

positively associated with the place of origin of milk, safety, as well as with information about how food is

produced.

3. Krishna Sudheer et al., (2015) “An empirical determination of target consumer profile for dairy products”

aimed to know the target group of dairy products which is an essential element in designing various marketing

strategies for dairy farms. The findings of the study explore various factors that help the dairy firms to improve

the consumption level of dairy products and to develop brand image in the dairy market.

4. Narges Delafrouz et al., (2014) prepared a study titled, “Analysis of Affective Drives on Consumers Green

Purchase Decision” with the purpose of Analysis of affective drives on consumers green purchase decision of

Dairy and meat products of Kaleh Company in Guilan province. In this regard, a sample of 384 consumers of this

company were randomly selected and studied.

5. Bidyut Kumar Ghosh (2013) examined the impact and role of product packaging on the buying behaviour of

consumers for the dairy of products of government owned Mother Dairy. The study also makes the conclusion

that the visual appeal is more important than the qualitative aspect of packaging in the study area.

6. Bonaventure Boniface and Wendy Umberger (2012) “Factors influencing Malaysian consumers’

consumption of dairy products”, explains increasing demand for dairy products in Malaysia is driving

government initiatives and structural change in the domestic dairy industry in order to increase competitiveness

Customers Cognizance Factors Influencing Purchasing Decision of Designated Dairy Products 3559


and self-sufficiency. The results indicate that demographic variables such as age and ethnicity as well as other

attitudinal variables significantly influence consumers’ increasing consumption of dairy products.

7. Iliriana Miftari (2009) “Kosovo consumer buying behavior preferences and demand for milk and dairy

products” analyze the consumer buying behavior, preferences, attitudes, needs and wants toward dairy products.

The study was carried out in five Kosovo regions.

8. Santosh Singh Bais and Ramesh Agadi (2008) “Marketing of Branded Dairy Milk Products in Gulbarga

District in Karnataka – A Survey of Consumers and Milk Vendors” analyzed the demand and supply of the dairy

milk in Gulbarga. The result of the study shows Majority (59%) of the respondent preferred the home delivery for

their milk required avoiding the inconveniences and they are ready to bear bit additional cost for home delivery.

9. Hannah Jane McKnight (2007) “Organic Milk: Consumers and their purchasing patterns”, designed to

characterize consumer purchases of organic milk by differentiating consumers based on buying behavior. The

results of identifying consumers based on their milk buying behavior can be used by marketers and educators to

target individuals, based on group membership, for planning and guiding education and advertising campaigns

and programs.

10. Kubendran and Vanniarajan (2005) “Comparative analysis of Rural and Urban Consumers on Milk

Consumption” revealed that with a constant increase in disposable incomes among the strong middle-income

class. It could be noted that the demand for milk and milk products depends on consumer's willingness and

capacity to buy. Since the consumers are not homogeneous, the consumption pattern of milk like quantum of

purchase, mode of purchase, source of purchase, brand preference etc., are changing from consumer to consumer.

Statement of the Problem

The Indian dairy sector is categorized by high disintegration. The ever increasing rise in domestic demand for dairy

products and a large demand-supply gap could lead India to be a net importer of dairy products in the near future. Further,

purchasing decision also changes over a period of time, because of the change in age, income, occupation, education,

family size and so forth. Unless the purchasing decision factors, product knowledge especially new arrivals and fulfilling

the satisfaction are thoroughly understood from time to time, it would not be possible for the marketers and distributors to

design appropriate marketing mix to appeal and influence the varied segmented consumers. Thus, this study becomes

imminent for the marketers to withstand the onslaught from the competitors and survive in the market. Having reviewed

relevant dairy marketing studies, the present study has made a broad objective to explore the customer’s cognizance factors

influencing purchasing decision of designated dairy products in Salem district of Tamilnadu, India thereby enabling to

arrive at a consensus on the marketing strategies to be followed in the dairy market. Hence, the present study focuses

mainly on customers purchasing decisions of prominent dairy brands with position to product knowledge.

OBJECTIVES OF THE STUDY

To evaluate the applicable variables between socio economic statuses with level of awareness of customers about

various brands of dairy products.

To identify and interpret the key factors involved in customers’ purchasing decision intricate in leading dairy

product inclusions.

To ascertain and examine the essential information preferred by respondents while purchasing dairy products.




Analysis, Findings and Interpretation

Table 1: Socio-Demographic Profile of the Sample Respondents

Profile Particulars Frequency Percent

Gender Male 146 43.45

Female 190 56.55

Age

Below 20 years 52 15.48

21-30 years 67 19.94

31-40 years 67 19.94

41-50 years 80 23.81

Above 50 years 70 20.83

Educational

Qualification

Illiterate 65 19.35

School level 68 20.24

Diploma Level 74 22.02

Under Graduation 59 17.56

Post-Graduation 70 20.83

Occupation Status

Agriculture 81 24.11

Business 69 20.54

Professional/Self Employed 63 18.75

Govt. / Pvt. Employee 66 19.64

House maker / Unemployed 57 16.96

Monthly

Expenditure on Dairy Product

Less than Rs.1000 39 11.61

Rs.1001-Rs.1500 46 13.69

Rs.1501 - Rs.2000 47 13.99

Rs.2001-Rs.2500 106 31.55

Above Rs.2500 98 29.17

Total for Each Segment 336 100.00

Source: Computed from Primary Data

Gender - The table-1 reveals the socio-demographic profile of the respondents. The result shows that out of selected 336

respondents, 146 respondents (43.45%) were male and the remaining 190 respondents (56.55%) were female. Thus the

majority of the respondents were female.

Age - The age of the respondents were recorded into groups such as among the 336 respondents, a high of 80

respondents (23.81%) belong to the age category of 41-50 years and low of 52 respondents (15.48%) were below the age

category of 20 years.

Educational Qualifications - With regard to the educational qualifications of the respondents, it was identified that out of

336respondnets, a high of 74 of them (22.02%) were having the educational qualification of diploma level and low of 59

respondents (17.56%) were under graduates. In this study the researcher found only 19.35% of them are illiterates which

shows that Salem district is more than moderate in literacy rate.

Occupation - The occupational status of the respondents were classified as Agriculture, Business, Professional and

Self Employed, Government and Private employee, House maker and Unemployed. The result shows that out of 336

respondent, a high of 81 respondents (24.11%) were engaged in agriculture and low of 57 respondents (16.96%) were

house makers / unemployed.

Monthly Expenditure on Dairy Product - It can be noted from the above table, a high 106 (31.55%) of the respondents

were spending Rs.2001-2500 and low of 39 (11.61%) of the respondents spending less than Rs.1000.



Table 2: Respondents Preference on Dairy Brand

Brands Total Score Mean Score Rank

Aavin 43272 57.2 1

Arokia 42294 55.9 2

Cavin 41364 54.6 3

Sakthi 32471 42.9 4

Thirumala 31160 41.2 5

Source: Computed from Primary data

The above portrays respondents’ preference to purchase dairy brands in that mostly classified as Aavin, Arokia,

Cavin, Sakthi and Thirumala. The above table shows that out of the five brands listed; the mostly preferred brand of dairy

products pinpointed by the respondents was “Aavin”, which was ranked first with a Garrett score of 43272 points. It is

followed by “Arokia”, placed in the second rank with the Garrett score of 42294 points. The brands such as “Cavin”,

“Sakthi” and “Thirumala” were ranked in the third, fourth and fifth places with the Garret scores of 41364, 32471 and

31160 points respectively. It was identified from the above analysis that majority of the respondents pinpointed to the

brand that mostly preferred by the respondents was “Aavin” followed by “Arokia”.

Awareness of Customers about Various Brands of Dairy Products

ANOVA was employed to determine whether there is a difference in the level of awareness among different bands of dairy

products such as Aavin, Arokia, Cavin, Sakthi, Thirumala with reference to respondent’s profile (namely age, educational

background, occupation and monthly expenditure on dairy products). The researcher selected only four variables which are

unswervingly and intimately affecting the awareness of the respondents on dairy products.

Table 3: Age and Level of Awareness (ANOVA)

Source DF SS MS F S

Between Groups 2 764.4 382.2 4.772 Significant at 5% Level

Within Groups 12 961.2 80.1

Total 14 1725.6 462.3


H0: There is no significant difference between age of the respondents and their level of awareness towards dairy

brands.

It is highlighted from the above table that the calculated ‘F’ value is greater than the table value (4.772>3.885)

and the result is significant at 5% level. Hence, we accept the alternative hypothesis (H1), “There is a significant difference

between age of the respondents and their level of awareness towards Dairy brands”, holds well.

Table 4: Educational Qualification and Level of Awareness (ANOVA)

Source DF SS MS F S



Total 14 1899.6 476.8


H0: There is no significant difference between educational qualification of the respondents and their level of

awareness towards dairy brands.


and the result is significant at 5% level. Hence, we accept alternative hypothesis (H1), “There is a significant difference




between educational qualification of the respondents and their level of awareness towards Dairy brands”, does hold well.

Table 5: Occupation Status and Level of Awareness (ANOVA)

Source Df SS MS F S



Total 14 1253.6 402.97

Source: Computed From Primary Data

H0: There is no significant difference between occupation status of the respondents and their level of awareness

towards dairy brands.



between occupation status of the respondents and their level of awareness towards Dairy brands”, hold well.

Table 6: Monthly Expenditure on Dairy Product and Level of Awareness (ANOVA)

Source DF SS MS F S



Total 14 460.34 189.25

Source: Computed From Primary Data

H0: There is no significant difference between monthly expenditure on dairy product of the respondents and their

level of awareness towards dairy brands.



between monthly expenditure on dairy product of the respondents and their level of awareness towards Dairy brands”, hold

well.

Factors Influencing the Purchasing Decision – Factor Analysis

In this study, the researcher analyzed the factors influencing the purchasing decision of dairy product’s consumption-

choices. By using factor analysis the researcher tries to find the nearest and close substantial purchasing factors

influencing consumption of dairy products. Based on the responses of respondents through structured questionnaires and

outcomes obtained via statistical calculations, the following factor analysis model are depicted -

Table 7: Communalities – Before Removal of Low Loading Variables

Variable Initial Extraction

Quality 1.000 0.772

Quantity 1.000 0.799

Easy availability 1.000 0.771

Price 1.000 0.692

Convenience 1.000 0.631

Taste 1.000 0.521

Home delivery 1.000 0.61

Freshness 1.000 0.652

Special offers 1.000 0.559

Packaging 1.000 0.561

Hygiene factor 1.000 0.783

Keeping (shelf)life 1.000 0.537



Pleasant flavor 1.000 0.541

Brand image 1.000 0.692

Lack of alternative source 1.000 0.574

Suitable packing 1.000 0.653

Consistent Service 1.000 0.417

Promotional Concessions 1.000 0.618

Cronbach’s Alpha () = 0.8292

The above table enumerates that the communalities of the selected 18 variables had reliability of 0.8292 as good,

and are keenly checked that no variable had low loading. The appropriateness of the data for the factor analysis is

discussed in the following KMO and Bartlett’s test.

Table 8: KMO and Bartlett Test

Kaiser-Meyer-Oklin Measure of Sampling Adequacy 0.881

Bartlett’s Test of Sphericity

Approx. Chi-Square 7244.671

DF 136

Sig. 0.000

The Kaiser-Meyer-Oklin (KMO) Measure of Sampling Adequacy (MSA) and Bartlett test of Sphericity are

applied to verify the adequacy or appropriateness of the data for factor analysis. In this study, the value of KMO for overall

matrix is found to be excellent (0.881) and Bartlett test of Sphericity is highly significant (p < 0.001). The results thus

indicate that the samples taken are appropriate to proceed with the factor analysis. Also, the Bartlett Test of Sphericity, the

KMO measure of sampling adequacy and communality values of all the variables are observed. Further, to define the

factors clearly, it is decided to delete any variable that has loading below ± 0.50. With this criterion, a series of factor

analysis is performed on the data.

Total Variance Explained

The following table depicts the total variance explained with rotation. The Eigen values for the factors 1, 2, and 3 are

different and they are 7.145, 1.939 and 1.338 respectively. Percentage of variance after the rotation for the factors 1, 2 and

3 are 23.131, 22.045 and 16.127 respectively. Cumulative percentage for the factors 1, 2 and 3 after the rotation are 23.131,

45.176 and 61.303 respectively. It indicates that the 3 factors extracted from the total 18 factors have a cumulative

percentage up to 61.303% of the total variance.

Table 9: Total Variance Explained

Component

Initial Eigen values Extraction Sums of Squared

Loadings

Rotation Sums of Squared

Loadings

Total % of

variance

Cumulative

%

Total % of

variance

Cumulative

%

Total % of

variance

Cumulative

%

1 7.145 42.029 42.029 7.145 42.029 42.029 3.932 23.131 23.131

2 1.939 11.406 53.435 1.939 11.406 53.435 3.748 22.045 45.176

3 1.338 7.869 61.303 1.338 7.869 61.303 2.742 16.127 61.303

4 1.127 6.632 67.935

5 0.844 4.966 72.902

6 0.704 4.144 77.046

7 0.586 3.449 80.494

8 0.552 3.249 83.744

9 0.499 2.934 86.678

10 0.462 2.619 87.519

11 0.396 2.332 89.010




12 0.358 2.103 91.113

13 0.339 1.996 93.109

14 0.290 1.703 94.813

15 0.260 1.527 96.340

16 0.230 1.354 97.694

17 0.218 1.282 98.976

18 0.174 1.024 100.000

Extraction Method: Principal Component Ana

Rotated Component Matrix

After obtaining the factor solutions, in which all the variables have a significant loading on a factor, the researcher

attempted to assign a meaning to the pattern of factor loadings. Variables with higher loadings are considered more

important and have a greater influence on the name or the label selected to represent a factor. Researchers have already

examined all the variables for a particular factor and placed greater emphasis on those variables with higher loadings to

assign a name or a label to a factor that accurately reflects the variables’ loading on that factor. All the 3 factors are given

appropriate names on the basis of the variables represented in each case.

Table 10: Rotated Component Matrix

S. No. Factors Component

F1 F2 F3

1 Quality 0.688

2 Taste 0.593

3 Freshness 0.502

4 Hygiene 0.575

5 Keeping life 0.585

6 Consistent Service 0.673

7 Brand Image 0.588

8 Price 0.717

9 Quantity 0.704

10 Special offers 0.693

11 Promotional Concessions 0.612

12 Easily availability 0.604

13 Convenience 0.545

14 Home Delivery 0.694

15 Packaging 0.764

16 Pleasant flavor 0.607

17 Lack of alternatives 0.556

18 Suitable packing 0.536

Extraction Method: Principal Component Analysis. , Rotation Method: Varimax

with Kaiser Normalization., Rotation converged in 6 iterations.

The table above explains the rotated component matrix, in which the extracted factors were assigned and a new

name related together. Based on the fixing criteria, it was noted that all the loading factors that were having the loading

value greater than 0.5.were fixed

Factor 1 was the most important factor which explains 23.131% of the variation. The factors Quality (0.688), taste

(0.593), freshness (0.502), hygiene (0.575), keeping life 90.585), reliable service 90.673) and brand image (0.588)

were highly correlated with each other. These factors reflected the quality aspects of the dairy products; hence, the

researcher named this segment as quality seekers.



The Cronbach’s Alpha value is 0.938.

Second kind of factor explains 22.045% of the variances. In this segment, the researcher took another four

important variables, price (0.717), quantity (0.704), special offers (0.693) and promotional discounts (0.612).

These statements reflected the price related aspects of the products and hence the researcher named this segment

of competitive price seekers.

The Cronbach’s Alpha value is 0.927.

The third factor explains 16.127% of the variations. In this factor, the researcher took the seven important

variables - easy availability (0.604), convenience (0.545), home delivery (0.694), packaging (0.764), pleasant

flavor (0.607), lack of alternatives (0.556) and suitable packing (0.536). These statements reflected the

convenience aspects of the products; hence the researcher named this segment as convenience seekers.

Table 11: Information preferred to examine while Purchasing Dairy Products

Factors Total Score Mean Score Rank

Special offers and discounts 41911 55.4 1

Maximum retail price 38213 50.5 5

Quality eminence components 40844 54.0 3

Date of manufacturing 40848 54.0 2

Date of expiration 37327 49.3 8

Ingredients combination 37824 50.0 6

Directives usage manual 37503 49.5 7

Name of the company 33198 43.9 10

Quantity in gram or liter 40320 53.3 4

Place of manufacturing 36833 48.7 9


The above table revealed that out of the ten factors related to information preferred by respondents while

purchasing dairy products, “Special offers and discount”, which was ranked first with a Garrett score of 41911 points, It

was followed by “Date of manufacturing” and “Quality eminence components”, placed in the second and third rank with

the Garrett score of 40848 and 40844 points respectively. The factors such as “Quantity in grams or liter”, “Maximum

retail price” and “Ingredients combination” were ranked in the fourth, fifth and sixth places with the Garret scores of

40320, 38213 and 37824 points respectively. Further required information are, “Directives usage manual”, “Date of

expiation” and “Place of manufacturing” were ranked as seven, eight and ninth places with the Garret scores of 37503,

37327 and 36833 points respectively. Lastly, “Name of the company” was ranked in the tenth place with a Garrett score of

33198 points.

SUGGESTION AND RECOMMENDATION

During the survey, the researcher found that all most all age groups are consuming milk and dairy products, so

the company can introduce a bunch of pioneering products like baby milk, added nutrition for school children,

auxiliary nutrition for sports persons, diet milk for expectant mothers, Calorie conscious milk for patients and

aged persons.

Today in market variations of milk available in the market such as whole milk, skimmed milk, and toned milk and

double toned milk. The knowledge of the awareness of these products is very much essential to the consumers to

take a buying decision on his / her own rather than depending on the seller. Hence this education should be




imparted through mass media and advertisements.

Awareness of the availability of different types of dairy products in the selling point alone is not sufficient, so the

distributor can take initiative to spread the information and product description by social media and broad casting

channels.

Company can increase dairy products sales through milk supplier or agent who are very close the buyers and lot

of chances to interact with them which results creating new customers for dairy products too.

Some of the customers requesting the distributors of dairy product to inform the company to introduce packaged

instant food which may leads to greater value addition to the dairy product mix.

Taking the advantage of recent developments in E-Commerce, the distributors can try for alternative channels of

distribution to explore the possibilities of marketing the dairy products through new networks to reach the

customers in time.

The current study showed that the consumers give more priority to quality and taste. Hence, it is recommended

that the manufacturer should take due care on adding different flavours to milk and dairy products in organic way.

CONCLUSIONS

It is suggested that the manufactures affianced in producing dairy products should analyze their marketing mix components

to improve the marketing efforts so as to maintain loyal customer base and towards achievement of their targets. Supplier

and distributors should take additional responsibility to create awareness of new arrival of present dairy brands this will

improve the market/consumer result oriented purchasing decision. This study will help the manufactures to bridge the gap

between strategic change and market complexity in the next coming challenging environment. Consumers buy dairy

products including milk out of their functional, inspirational and nutritional benefits conveyed by the product. It is a well-

known from the current study that almost all consumer buying habits are influenced by the preference and expectations.

However the dairy products image is formed out of the knowledge the consumers have about the perceived benefits the

product offers and the value it delivers or other aspects of the products such as price, quality, availability and accessibility.

REFERENCES

1. Maulik C. Prajapati and Ashish K. Makwana (2017), “Impact of Brand Equity on Consumer Purchase Decision of Dairy

Products”, Vol.4, Issue 1, June 2017.

2. Karale, Sheetal S., and MAYUR M. Suryavanshi. "Dairy wastewater treatment using coconut shell activated carbon & laterite

as low cost adsorbents." Int. J. Civil, Struct. Environ. Infrastruct. Eng. Res. Dev 1 (2014): 9-14.

3. Renata Hrubá (2016), “Behavior of agents at food market, especially asymmetric information on the Dairy Market”, Journal

of Applied Economics and Business Research (JAEBR), Vol.6, No.1, pp.36-54.

4. Krishna Sudheer, A., Krishna Karthik, E., & Seetha Mahalakshmi, M., (2015), “An Empirical Determination of Target

Consumer profile for Dairy Products”, EPRA International Journal of Economic and Business Review, Vol.3, Issue 12,

pp.213-220.

5. Narges Delafrouz, Mahdieh Momenpour, Armin Goli & Fatemeh Momenpour, (2014), “Analysis of Affective Drives on

Consumers Green Purchase Decision”, Indian Journal of Fundamental and Applied Life Sciences, Vol.4, Issue 1, pp.1117-

1124.

6. Bidyut Kumar Ghosh (2013), “Impact of Packaging on Consumers’ Buying Behaviour: A Case Study of Mother Dairy,



Kolkata”, Parikalpana - KIIT Journal of Management, Vol.2, No.2, pp.27-34.

7. Al Hamed, S. G. K. "Dairy wastewater treatment using microalgae in Karbala city–Iraq." IJEEFUS 4 (2014): 13-22.

8. Bonaventure Boniface and Wendy Umberger (2012), “Factors influencing Malaysian consumers’ consumption of dairy

products”, Contributed paper prepared for presentation at the 56th AARES annual conference, Fremantle, Western Australia,

February7-10, 2012.

9. Iliriana Miftari (2009), “Kosovo Consumer Buying Behavior Preferences and Demand for Milk and Dairy Products”,

Unpublished Ph.D. Thesis, Department of International Environment and Development Studies, Norwegian University of Life

Sciences, 2009.

10. Santosh Singh Bais and Ramesh Agadi, (2008), “Marketing of Branded Dairy Milk Products in Gulbarga District in

Karnataka – A Survey of Consumers and Milk Vendors”, Journal of Contemporary Research in Management, Special Issue,

pp.1-27.

11. Hannah Jane McKnight (2007), “Organic Milk: Consumers and their purchasing patterns”, Unpublished Dissertation

submitted to Virginia Polytechnic Institute and State University, Blacksburg, Virginia.

12. Kubendran, V and T.Vanniarajan (2005), “Comparative analysis of Rural and Urban Consumers on Milk Consumption”.

Indian Journal of Marketing, Vol. XXXV, No.12, pp.67-74.

13. C.R.Kothari, Research methodology – Methods & Techniques, “Research Design”, New Age International, 2004, Page No.37

14. http://www.stat.yale.edu/Courses/1997-98/101/chigf.htm

15. http://www.biostathandbook.com/twowayanova.html

16. http://www.theanalysisfactor.com/factor-analysis-1-introduction

http://www.theanalysisfactor.com/factor-analysis-1-introduction

customers cognizance factors influencing …

Documents