Supervisor: Fred Håkon Johnsen

kosovo consumer buying behavior preferences and demand for milk and dairy products

iliriana miftari

Department of International Environment and Development Studies Master Thesis 30 credits 2009

Supervisor: Fred Håkon Johnsen

II

DECLARATION

I hereby declare that this thesis is accomplished with my own work and all sources of literature that I have used are cited. I also assure that this work has not been presented to any other university.

III

DEDICATION

This work is dedicated to my parents, and my two brothers, Artan and Arian, with much love and thanks.

IV

ACKNOWLEDGEMENT

My special gratitude goes to my supervisor Ass.Prof.Fred Håkon Johnsen for his wise advice and great support in accomplishment of my master thesis. Great acknowledge goes to Lånekassen, without its financial support my study program would be onerous manageable. I wish to acknowledge Prof. Mujë Gjonbalaj for his continues support and encouragement throughout my study. I also wish to thank my field assistant Rozafa Miftari for her sincerity and tireless during field work. Great thanks go to those surveyed for their time and patience during the interviews. My appreciation goes also to Ass.Prof.Mensur Vegara and Ass.Prof.

Hysen Bytyqi, who were the main initiator for my study program at University of Life Sciences. I also wish to thank my colleagues at University of Prishtina, Prof. Halim Gjergjizi, Prof. Mustafë Pllana, Prof. Shukri Fetahu, Prof.Skënder Muji, Jehona Shkodra. My special gratitude go to my dear parents who continuously made sacrifice to keep me in school, thanks a lot for all their love, support and encouragement that gave it to me. Special thanks go to my best friend Panadda Larpkern, Besim Gojnovci, Ilbrahim Mehmeti, Arbina Kaja, and Paul Okullo.

V

Abstract

The aim of this study was to analyse consumer buying behaviour, preferences, attitudes, needs and wants toward dairy products. The study was carried out in five Kosovo regions (Prishtina, Prizren, Mitrovica, Peja, and Gjilan). The stratified random sampling has been applied in selecting people who would be included in the sample. The data used in this study were obtained through direct interviews with Kosovo consumers aged 18 years and older.

Two associated statistical techniques, multiple linear function and binary logistic function have been used to explain the relationships between the quantity and expenditures on milk and other dairy products with demographic and socioeconomic household characteristics. The results show that milk, yoghurt, cream, curd, and cheese were the main dairy products consumed by majority of Kosovo consumers. Supermarkets and grocery stores were the most preferred market places by the consumers when buying milk and other dairy products. The consumer’s preference towards market place was significantly dependent on demographic and socioeconomic household characteristics Dairy products with shorter shelf life were bought more frequently by the consumers compared to those with longer shelf life. Apart from product life, other demographic and socioeconomic factors had significantly impact on the frequencies of buying milk and other dairy products. The consumers’ demand for milk and other dairy products was quite stable throughout the year. The consumers’ attitudes toward product features such as nutritive content, taste, product safety, price, brand, wrapping, package size, and the origin of product were significantly dependent on demographic and socioeconomic factors. Kosovo consumers preferred bigger packages for curd and cheese.

Smaller packages were predominantly more preferred for fruit yoghurt and butter. Majority of the Kosovo consumers had favourable bias towards domestic versus foreign dairy products.

Product attributes such as quality, safety, taste, and price were the main features motivating Kosovo consumers to purchase domestic dairy products. Television and newspapers were the media most often used by the consumers to get information about the dairy products. The preference towards new dairy products and innovation was dependent on respondent’s characteristics. The Household’s characteristics such as income, size, employment, the number of children, respondent’s age, and education were significant in explaining variation in quantity consumed and the expenditures on milk and other dairy products.

VI

TABLE OF CONTENTS

DECLARATION………... II DEDICATION……….. III ACKNOWLEDGEMENT……… IV ABSTRACT………. V TABLE OF CONTENTS………. VI

LIST OF TABLES………... VIII

LIST OF FIGURES……….. X LIST OF ACRONYMS……… XI

CHAPTER I……… 1

1. INTRODUCTION……… 1

1.1 Background………. 1

1.2 Overview of the Kosovo Dairy Sector………... 2

1.3 Agriculture Sector Strategy and Policies……… 5

1.4 Problem Statement……….. 8

1.5 Justification………. 9

1.6 Objectives and Research questions………. 9

CHAPTER II……….. 11

2. THEORETICAL BACKGROUND………. 11

2.1 Factor Influences Consumer Behaviour………. 11

2.2 The Stimulus model of the Consumer Behaviour……….. 12

CHAPTER III………. 15

3. METHODOLOGY………... 15

3.1 The Study Area………... 15

3.2 Sample Selection……… 16

3.3 Data Collection………... 18

3.4 Model Specification……… 19

3.4.1 Variable Description and Measurement……….. 21

3.4.2 Estimation procedure………... 23

CHAPTER IV………. 25

4. Results and Discussion………. 25

4.1 Descriptive Statistics on the Household Characteristics……… 25

VII

4.2 Descriptive Statistics on Consumer buying Behaviour……….. 29

4.3 Model Estimation………... 40

4.3.1 Binary Logistic linear Estimated Parameters……….. 40

4.3.2 Multiple linear Estimated Parameters……….. 43

CHAPTER V………... 53

5. Conclusion……… 53

LIST OF REFERENCES………... 59

APPENDIX……….. 62

Appendix A1/Questionnaire………. 62

Appendix A2/Tables………. 66

VIII LIST OF TABLES

Table 1. The estimated livestock situation in 2005………... 3

Table 2. Dairy farm structure in Kosovo……….. 3

Table 3. Evolution of the local processors on daily milk processing……… 4

Table 4. Dependent variables used in the estimation of the average quantity of the product i purchased in litre or kilogram in the HH_i……… 21 Table 5. Dependent variables used in the estimation of the average monthly expenditures on the product i in euro per month in the HH_i………. 21 Table 6. Independent variables used in the estimation of the quantity and the expenditures on milk and six other dairy products………... 22 Table 7. Dependent variables used in the estimation of the fitted model in the equation 1……….. 22 Table 8. Dependent variables used in the estimation of the fitted model in the equation 1……….. 22 Table 9. Independent variables (factors) used in the estimation of the fitted model in the equation 1………. 23 Table 10. Recoded variables used in the test of independence………. 23

Table 11. Summary statistics of the household characteristics………. 25

Table 12. Pairwise comparison between females and males……… 27

Table 13. Pairwise comparison between rural and urban household……… 27

Table 14. Pairwise comparison between regions……….. 28

Table 15. Summary statistics of the average quantity of milk and other dairy products purchased by the HHs………. 33 Table 16 The annual average per capita consumption……….. 33 Table 17. Summary statistics of the average expenditures on milk and other

dairy products by the HHs………

34

Table 18. Relationship of whether the respondent i buys milk and the

predictors included in the equation 1………

40

Table 19. Relationship of whether the respondent i buys yoghurt and the predictors included in the equation 1………

40

Table 20. Relationship of whether the respondent i buys fruit yoghurt and the predictors included in the equation 1………

41

Table 21. Relationship of whether the respondent i buys cream and the 41

IX

predictors included in the equation 1………

Table 22. Relationship of whether the respondent i buys curd and the

predictors included in the equation 1………

41

Table 23. Relationship of whether the respondent i buys cheese and the

predictors included in the equation 1………

41

Table 24. Relationship of whether the respondent i buys butter and the

predictors included in the equation 1………

42

Table 25. Relationship of whether the respondent i fulfils the demand for milk and dairy products and the predictors included in the equation 1………

42

Table 26. Relationship of whether the respondent i prefers domestic dairy products and the predictors included in the equation 1……….

42

Table 27. Relationship of whether the respondent i prefers foreign dairy

products and the predictors included in the equation 1……….

42

Table 28. Relationship of whether respondent i prefers new dairy products and the predictors included in the equation 1………..

43

Table 29. Relationship of whether respondent i started buying new dairy products last year and the predictors included in the equation 1………

43

Table 30. Test of independence between the market places and demographic and socioeconomic characteristics………

56

Table 31. Test of independence between the frequencies of buying milk, dairy products and demographic and socioeconomic characteristics……….

57

Table 32. Test of independence between evaluation of product attributes and demographic and socioeconomic characteristics………..

58

X LIST OF FIGURES

Figure 1. Stimulus-response model of the consumer behaviour………... 13

Figure 2. Stage model of the consumer buying process………... 14

Figure 3.Stratification of the sample size……….. 17

Figure 4. Respondents’ answers in terms of buying milk and six other dairy products………. 31 Figure 5.Market places preferred by consumers when buying milk and other dairy produces………... 32 Figure 6. Frequencies of buying milk and other dairy products………... 32

Figure 7. Seasonal consumption patterns on milk……… 35

Figure 8. Seasonal consumption patterns on yoghurt………... 35

Figure 9. Seasonal consumption patterns on fruit yoghurt………... 36

Figure 10. Seasonal consumption patterns on cream……… 36

Figure 11. Seasonal consumption patterns on curd………... 36

Figure 12. Seasonal consumption patterns on cheese………... 37

Figure 13. Seasonal consumption patterns on butter……… 37

Figure 14. The evaluation of product features in order of importance…………. 38

Figure 15. The level of the mass media used by the respondents………. 39

XI

LIST OF ACRONYMS

ANOVA Analysis of Variance

ARDP Agricultural Rural Development Plan CEFTA Central European Free Trade Agreement EU European Union

GDP Gross Domestic Product GMP Good Manufacturing Practices

HACCP Hazard Analysis Critical Control Points HH Household

KARDP Kosovo Agricultural Rural Development Plan KCBS Kosovo Cluster Business Support

KDPA Kosovo Dairy Processing Association

MAFRD Ministry of Agriculture Forestry and Rural Development MPS Ministry of Public Services

SOK Statistical Office of Kosovo

SWOT Strengths Weaknesses Opportunities and Threats UHT Ultra High Temperature

UN United Nations

UNMIK United Nations Mission in Kosovo VAT Value Added Tax

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CHAPTER I

1. INTRODUCTION

1.1 Background

After the end of the last war in 1999, the United Nations (UN) Security Council Resolution 1244 (UNSCR1244), placed Kosovo under temporary UN Administration (UNMIK – United Nations Mission in Kosovo). Building self-governed democratic institutions, economic re-activation, an effort to build the peace, inter-ethnic reconciliation and building new bridges of cooperation with the countries in the region were the main challenges accompanying Kosovo after the last conflict. The decline of the agriculture sector which started during the 1990s resulted from the emigration of the Kosovo population (18- 20%) to the Western European Countries. While overall stagnation culminated in 1999, most of the farms stopped production, having consequences to the food processing industry. The agriculture sector was heavily harmed by the last conflict. The total amount of the destruction and deprivation in rural areas was estimated to be 737 million dollars (MAFRD, 2003).

Despite the difficult circumstances after the last conflict, Kosovo has gone ahead in the building of its democratic institutions and macroeconomic stabilization. ‘’It experienced a strong recovery mostly based on an immense inflow of foreign assistance and external private inflows estimated to equal up to 50 percent of GDP’’ (Fock, 2007, p.4). The estimated average real GDP growth between 2002 and 2007 has been slow at less than one and half percent. ‘’This slow expansion was mainly due to a combination of low investment and the ongoing withdrawal of the international community in Kosovo’’ (World Bank, 2007, pp.1-2).

The poverty phenomenon has remained persistent and is widespread within the Kosovo society. According to the World Bank (2007) estimation, about 45% of the Kosovo population is considered to be poor, while a smaller fraction (18%) was in extreme poverty. In 2005 Kosovo had the highest poverty rate of the countries in the Western Balkans. This large fraction of the Kosovo population just around the poverty line reflects the socio-economic phenomenon where sources available to society are used to satisfy the wants of small fraction while many have not even met their basic needs (Chambers, 1983).

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Agriculture has historically been an important sector in Kosovo’s economy. It is characterized by small subsistence farms, high input costs, low productivity, poor infrastructure and poor advisory services (Ministry of Agriculture Forestry and Rural Development, MAFRD, 2006). The sector’s contribution to GDP during the period 2000- 2005 was 25-27%. The high contribution of the agriculture sector to GDP was not due to high productivity, but rather to the declining contribution of the other sectors in GDP. Given that majority (55%) of the Kosovo population is concentrated in rural areas, agriculture has remained an important sector in mitigating rural poverty. During the period 2000-2005, its contribution to the employment rate was between 25-30% (informal self-employed agriculture workers). The proportion of the Kosovo labour force engaged in agriculture sector/farming was the highest in the Western Balkans countries and it is around five times higher than in European Union (EU) countries. This high proportion of the labour force involved in agriculture clearly indicates the low efficiency of this sector. Despite its low efficiency and loss of traditional export markets, its contribution to the value of total exports in 2005 was 16%. Agriculture remains an important sector and an engine towards economic growth and EU accession.

1.2 Overview of the Kosovo Dairy Sector

The Kosovo dairy sector is one of the most promising sectors and has consistently performed well since the end of the last war. As with most other Kosovo sectors the last conflict in 1999 caused considerable damage to the agricultural sector. Particular damages affected the dairy sector, where approximately 50% of the livestock was killed and roughly 40% of the livestock infrastructure (stalls) was destroyed (MAFRD, 2003). Due to the creation of this situation there has been a market shortage in animal and dairy commodities.

Consequently, there has been a sharp increase of the imported animal and dairy products for market equilibrium to be established as well as to meet the market demand. Moreover, many donors helped in the restocking of the cattle herd. Since the end of the war ‘’up to the first quarter of 2003, 10,000 pregnant heifers were imported and distributed to farmers’’ (Rural Development Plan 2007-2013, 2006, p.19). The livestock census conducted by Statistical Office of Kosovo (SOK) in November 2003 was used as the determinative base of the animal numbers in Kosovo. Even though efforts were made to improve the livestock situation

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through import and donor support, livestock in Kosovo has still remained at a very low level.

Table represents the livestock census conducted by SOK in 2005.

Table 1. The estimated livestock situation in 2005

Livestock Cattle Milk cows Buffaloes Sheep and goats

Number 351,827 186,707 622 151,880

Source: Agriculture Household Survey, 2006, SOK.

It was estimated that 67.7% of rural households have dairy cows, with an average 1.2 dairy cows per household (HH) (Rural Development Plan 2007-2013, 2006). According to the MAFRD classification, the most common type of the dairy farms in Kosovo is the traditional/subsistence farm (94%), followed by the semi-commercial farm (5%) and the commercial farm (1%).

Table 2. Dairy farm structure in Kosovo

Type of farm No. of farms Percentage No. of cows

Traditional/Subsistence 78,124 94% < 5

Semi Commercial 4,378 5% 5 – 9

Commercial 787 1% > 10

Total 83,289 100%

Source: ASPAUK Project

Kosovo dairy sector is mainly dominated by milk, yoghurt and white cheese. Milk production in Kosovo is derived only from the private sector, since the public sector collapsed during the transition period between 1990 and 1999. According to the official statistical data, milk production in Kosovo was estimated to be approximately 257,500 tons/year. Local milk production is mainly intended for the domestic market. Of the total domestic milk produced, 45.6% is consumed on the farm, 41.4% is sold on the local green market¹ mostly as raw milk or white cheese, while only 13% is sold on the processing market. There are 19 dairy processors where commercial and semi-commercial farms have the possibility to sell the produced milk (Nushi and Selimi, 2009). The most important elements affecting marketability of the domestic milk produced to the processing market were milk collection cost, low technology and low milk quality. As is shown in table 2 most of the Kosovo dairy farms are small traditional/subsistence farms dispersed across the countryside, with low capacity for

1 Green market - signifies local markets where un-pasteurised milk and cheese is sold directly to consumers by farmers.

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milk production and low milk quality², which makes the milk collection procedure more expensive.

‘’Considering that milk quality has a big impact on the final product and shelf-life’’, two technical assistant projects worked in the improvement of the milk quality and ability of dairy processors to test quality when buying milk (Oldham, Bajraktari and Wittkowsky, 2006).

However, Kosovo milk quality at the farm level as well as dairy products has still remained at a poorer quality compared to the imported articles. Large market share and successful penetration in the market of some imported dairy products above Kosovo prices proved that consumers are willing to pay high prices for better quality. However, there is still not enough good milk quality coming to the processing plants.

During the period of 2003 through 2007 there was a remarkable investment by local investors in milk processing capacity. In 2003, the capacity of daily milk intake for processing was 30,800 litres, which increased to 114,000 litres in 2007. Yearly milk processing capacity was estimated to be 16,000 tons, but due to the evident impediments highlighted above, only 12,300 tons are processed in the dairy plants (Rural Development Plan 2007-2013, 2006).

Seasonal difference in the quantity of raw milk production is an additional obstacle for the local dairy processors, which renders them unable to steadily and fully utilize their capacities.

Fresh milk, yoghurt, kos³, and white cheese are the main items produced by the local dairy processors.

Table 3. Evolution of the local processors on daily milk processing

Year 2003 2004 2005 2006 2007

Milk in litres 30,800 71,000 74,800 92,200 114,000

Source: Kosovo Dairy Processing Association - KDPA

In Kosovo, dairy commodities are dominant in the daily diet and the main source of protein. A study conducted by Kosovo Cluster Business Support (KCBS, 2008) on dairy market assessment, proclaimed that among dairy commodities, ultra high temperature processed (UHT) milk, white cheese, sour cream, fresh milk and yoghurt, were most frequently dairy commodities purchased by Kosovo consumers. This study revealed that 89.7% of the Kosovo households occasionally buy milk. It was estimated that milk consumption per capita was approximately 170 litres per year. There are no estimations available with regard to the quantity consumed of other dairy commodities.

2 Low milk quality in terms of a high bacterial count.

3 Kos - milk drink between yoghurt and sour crème.

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Kosovo is considered to be a huge importer of dairy products. Of the total domestic milk demand, 76% was made up of Kosovo farms supply, while 24% was supplemented by import.

Among the imported dairy commodities, UHT milk accounts for the highest share of the total value of imports (about 40%) followed by cream and fruit yoghurt. Production of milk and other dairy products in Kosovo is relatively costly as most of the livestock is reared in a stall- feed system rather than pasture fed. Moreover, quality at farm and factory level is still considered to be at a lower level. This is why imported UHT milk and other dairy products and compete successfully on the local market. Export of Kosovo dairy products is limited to a few items, mostly UHT milk, cream and cheese. Export increases during the summer season, while the Albanian market is the main absorber of Kosovo’s dairy commodities.

1.3 Agriculture Sector Strategy and Policies

Administratively, the agriculture sector and policy is set at national level, while the execution of the policy is accomplished at national and municipality levels. The Ministry of Agriculture, Forestry and Rural Development (MAFRD) in partnership with other stakeholders such as the Farmers’ Associations, the Rural Advisory Service, and the Veterinary and Food Agency play major roles in policy formulation and implementation. In 2006 Kosovo launched its Agriculture and Rural Development Plan 2007-2013 (ARDP) (MAFRD, 2006) which outlines objectives and key measures for the agriculture sector. The aim of ARDP was to provide a framework to guide future agriculture sector policies. Its vision for Kosovo agricultural and rural development during 2007-2013 was to ‘’make a balanced contribution to the economic, environmental, social and cultural well-being of rural areas, and Kosovo as a whole, through effective and profitable partnerships between the private sector, central/local government and local communities within the European context’’.

Based on the Kosovo’s agri-rural situation and after SWOT (strengths, weaknesses, opportunities, and threats) analysis, general objectives for agricultural rural development in Kosovo were set as below:

(i) Additional income for farmers and rural population on purpose to improve living standards and working conditions in rural areas;

(ii) Improved competitiveness and efficiency of primary agricultural production in order to achieve import substitution and take advantage of export markets;

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(iii) Improved processing and marketing of agricultural produce, through increased efficiency and competitiveness;

(iv) Improved on-farm / in-factory quality and hygiene standards;

(v) Sustainable rural development and improved quality of life (including infrastructure) through promotion of farming and other environmentally sustainable economic activities;

(vi) Creation of employment opportunities in rural areas, particularly through diversification;

(vii) Alignment of Kosovo’s agriculture with that of the EU.

Two key approaches for achieving KARDP 2007-2013 objectives were set as below:

I. Undertake actions that overcome the bottlenecks that are holding back sustainable rural development in Kosovo, and

II. Start aligning Kosovo’s rural sector with four axes of current EU rural development strategy.

The achievement of the KARDP 2007-2003 was built on the following four axes with the eight key measures:

Axis 1: Competitiveness

Development of vocational training to meet rural needs (Measure 1) Restructuring physical potential in the agri-rural sector (Measure 2) Managing water resources for agriculture (Measure 3)

Improving the processing and marketing of agricultural products (Measure 4) Axis 2: Environment and improved land use

Improving natural resource management (Measure 5) Axis 3: Rural diversification and quality of rural life

Farm diversification and alternative activities in rural areas (Measure 6)

Improvement of rural infrastructure and maintenance of rural heritage (Measure 7) Axis 4: Community-based local development strategies

Support for local community development strategies (Measure 8)

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During the period 1999-2004, fiscal rates were was 10% for the standard import duty and 15% Value Added Tax (VAT) for agriculture inputs. Presently, the agriculture sector in Kosovo does not benefit from direct subsidies by the government. However, indirect subsidies are given to the sector in terms of zero VAT and zero import duty on agricultural inputs, reproductive material in animal production, mechanization and on most capital goods used in agriculture or agro-processing. Kosovo applies 10 percent customs duty on imports, while there is no encouraging instrument (export subsidy) that induces Kosovo’s export. In 2006, Kosovo joined the Central European Free Trade Agreement (CEFTA). The market created by CEFTA comprises nearly 30 million consumers and it was signed by ten countries⁴. This trade agreement resulted in market access at zero import duty for all participating countries.

Even though this trade agreement offered Kosovo the opportunity to be part of regional integration and EU association, there was also an increased pressure in terms of competitiveness on the local market.

The expectations of ARDP for Kosovo’s dairy sector were to have a modern dairy industry, by increasing the number of commercial farms with an average of 30 cows, an achievement of 100% ‘’A’’ grade milk quality, increasing the average of milk productivity up to 20/litres/cow/day, and increasing milk consumption from 170 to 190 litres/capita/year by the end of 2013. Due to an increase of milk consumption per capita, demand for milk at the end of 2013 was estimated at 28% higher than in 2005.

The following key actions were taken by government in order to achieve its objectives towards dairy sector: ‘’a 10-yearly strategy for livestock development, approval of Law on Livestock, U/A (Administrative Order) in proceeding, changes in fiscal policy, free trade agreements, flattening the customs entering price for imported products, improving animal nutrition, improving the breeding structure, increasing livestock production, lowering imports, improving quality production and place exemption of customs tariffs and VAT for the livestock inputs’’(Nushi and Selimi, 2009, p.12). Actually, although several actions were taken by the government, Kosovo’s dairy sector is still facing significant difficulties with regard to ‘’land availability, breed quality, high cost of milk production, transport and distribution, lack of knowledge on new technology and marketing strategies, unfair competition from import, lack of experience in processing and low marketing capacities due to small dairies’’ (Nushi and Selimi, 2009, p.11).

4 Member of CEFTA 2006: Kosovo, Albania, Bosnia and Herzegovina, Croatia, Macedonia, Montenegro, Moldova, Serbia. Except, Bulgaria and Romania (from January 1st 2007 are member of EU-27).

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Increasing farm size through land consolidation, a developing land market, decreasing interest rates for agricultural credits, implementing an integrated quality management system through Good Manufacturing Practices (GMP) and Hazard Analysis Critical Control Points (HACCP), were seen as key actions to be taken in order to improve the competitiveness of the Kosovo dairy sector on the local and regional markets.

1.4 Problem Statement

As highlighted in the above section, the dairy sector in Kosovo has performed well and seems to be one of the most promising agriculture sectors. However, the sector has passed through a very onerous period during the last decade. Significant economic changes after the last conflict had dramatically impacted consumers’ buying behaviour, their attitudes, needs and demand for dairy products. Moreover, there was an enormous increase of foreign competitors on the domestic dairy market. Therefore, new market approaches such as improved product quality, wider assortment of the dairy produce, new management on the sales system, an improved marketing information system, market segmentation, and price differentiation, were required for the local dairy processors to become a competitive on local and regional markets.

Previously, the market orientation of Kosovo’s dairy industry was to produce cheap bulk dairy commodities with a limited assortment. Nowadays marketing has broadened its concept, contemporary marketers include the study of transfer behaviour as well as transaction of consumer behaviour (Kotler, 2002). Having information on consumers’ buying behaviour, their preferences, attitudes, needs and demand for dairy products are considered to be key determinant factors for the efficiency of dairy. However, the dairy industry in Kosovo lacks information on consumers’ buying behaviour and demand for dairy products level. Thus, among other significant problems that the dairy sector is facing, lack of information is an additional disadvantage upon the sales opportunities and the efficiency of dairies in Kosovo.

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1.5 Justification

The consumers represent the last component within the food chain supply but they are set as a major player on the market, thus they deserve special attention (Kapsdorferová and Nagyová, 2005). Significant economic changes and continued evolution of consumers’

preferences, needs and wants for the dairy produce, makes the dairy market become more and more segmented as well as more complex. Therefore, a study of consumers’ buying behaviour, their preferences, attitudes, needs and wants towards dairy products helps the dairy industry (local processors) in their plan projections and development of their marketing strategies. An understanding of the consumers’ buying behaviour and identifying the major forces influencing structural changes in their consumption patterns, helps businesses of this industry to improve and get the most rational way to meet the consumers’ needs.

Currently, there is no data available or comprehensive study devoted to the dairy consumption patterns in Kosovo (Nushi and Selimi, 2009). There is no study on how consumers’ buying behaviour reacts to demographic and socio-economic factors. Moreover, no previous studies addressed the estimates of demand and household budget spent on dairy products with respect to demographic and socio-economic factors. It is thus very important to have good estimates of how the demand and household budget spent on dairy products reacts to demographic and socio-economic changes. Furthermore, analyses of changes in consumption patterns and consumption trends due to the changes of demographic and socio- economic factors (particularly income changes) are very important and applicable for policy modelling purposes. Having an accurate analysis and good estimates of demand for dairy products helps projection of the future development of the dairy sector in Kosovo.

1.6 Objectives and Research questions

The overall objective of this study was to assess the evolution of Kosovo consumers with regards to their new consumption patterns for dairy products. The study was carried out to determine factors that influence consumers’ buying behaviour, their preferences, attitudes, needs and wants towards dairy products. The following research questions were drawn in pursuit of the outlined objective:

1. ‘’What, Who, Where, How and When” do consumers buy milk and other dairy products such as yoghurt, fruit yoghurt, cream, curd, cheese and butter?

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2. What are the consumers’ preferences for the package size, country of origin, new dairy products and innovation?

3. What are the consumers’ attitudes toward product attributes such as brand, packing, nutritive content, economic value, taste, safety, and country of origin?

4. Do the consumers meet their needs for milk and six other dairy products with their current monthly income?

The aim of this study was also to estimate how the demand and household budget spent on milk and six other dairy products react to demographic and socio-economic changes. The following research questions were addressed in pursuit of this objective.

1. What is the average monthly quantity purchased of milk and other dairy products?

2. What is the average monthly expenditure for milk and other dairy products?

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CHAPTER II

2. THEORETICAL BACKGROUND

2.1 Factors Influences Consumer Behaviour

Cultural, social and personal factors are always considered to be the major forces influencing consumers’ buying behaviour (Kotler and Keller, 2006). An understanding of such factors helps businesses at tailoring products that meet consumers’ needs and wants.

Among important influences on consumer buying behaviour (culture, subculture, and social class) ‘’culture is the fundamental determinant of a person’s wants and behaviour’’ (Kotler and Keller, 2006, p.174). Given that ‘’all human societies exhibit social stratification’’, distinctive consumer buying behaviour and preferences exist as well among social classes (Kotler and Keller, 2006, p.175). These distinctive buying patterns and preferences among social classes are significantly determined by occupation, income, wealth, education etc.

Consumers can shift up and down the social strata but the extent of this mobility depends much on how rigid the social stratification is in a given society (Kotler and Keller, 2006).

An individual’s values, perceptions, preferences and behaviours in a direct or indirect way are significantly influenced by reference groups (family, friends, neighbours, and co-workers) to which they belong. Such reference groups expose an individual to new behaviours and lifestyles, and often have an effect on their attitudes, products or brand choices (Kotler and Keller, 2006). Family is considered to be one of the most important consumer buying groups in the society (Tour and Henthorne, 1995). It is thus very important for the marketers to identify the roles and influence of the family members in the purchase of products. Marketers may accurately address their marketing messages, only if they fully understand who of the family members is a leader and has direct influence on the buying decisions. ‘’In countries where parents live with grown up children, their influence can be substantial’’ (Kotler and Keller, 2006, p.177). The buyer’s characteristics such as age, stage in the life cycle, occupation, economic circumstances, personality, self-concept, lifestyle and values have a significant impact on the consumer behaviours and the buying decisions. The consumption patterns and taste in food are often shaped by the family life cycle and the number, age, and gender of people in the household, and occupation (Kotler and Keller, 2006). The consumer’s decisions in product and brand choices are greatly influenced by the income level, stability,

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personality, self-concept, core values and life style. The consumers’ characteristics, buying behaviour, and preferences vary over the consumers’ lifetime. This is why successful marketers make an attempt to follow carefully trends and changes of the consumers’

characteristics.

2.2 The Stimulus model of the Consumer Behaviour

Many theorists have addressed the issue of understanding the consumer behaviour in the decision buying processes and the purchase decisions. The marketing and environmental stimuli are key enter points of understanding the consumer buying behaviours. The consumer psychology combined with the consumer characteristics result in the buying decision process and the purchase decision. The crucial point of consumer behaviour is to understand what happens in the consumer’s consciousness between the arrival of outside stimuli (marketing and environmental) and the ultimate purchase decision (Kotler and Keller, 2006). The consumer responses to the outside stimuli are mainly influenced by the psychological processes such as motivation, perception, learning, and memory, and the consumer characteristics such as cultural, social, and personal.

An individual has different needs, biogenic needs that arise from physiological tension and psychogenic needs that arise from psychological tension. ‘’A need becomes a motive when it is aroused to a sufficient level of intensity’’ (Kotler and Keller, 2006, p.184).

The best-known theories of human motivation such as Sigmund Freud, Abraham Maslow, and Frederic Hezberg, are often used by the marketers for consumer analysis, understanding their behaviours and develop marketing strategies. Freud’s theory supposes that an individual may not completely understand his/her motivations, as psychological processes shaping his/her behaviour are mostly unconscious (Kotler and Keller, 2006). Maslow’s theory explains why people are driven by particular needs at particular times (Maslow, 1954). Based on the Maslow’s theory a person needs are in order of importance, starting from physiological, safety, social, esteem, and self actualization needs. This theory was used by the marketers in understanding of how products fit into the consumer’s plan, goal and life (Kotler and Keller, 2006). Herzberg’s theory distinguishes two-factor theory dissatisfiers and satisfiers factors (Herzberg, 1966). According to Herzberg’s theory, marketer’s task is first to avoid dissatisfiers factors and second to identify satisfiers or motivators of purchase in the market and then supply them (Kotler and Keller, 2006).

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Figure 1. Stimulus-response model of the consumer behaviour

Source: Kotler and Keller (2006).

The information about the product is one of the prime determinants of consumer decision making. Other psychological processes such as motivation, perception, learning, and memory have a significant impact in the consumer buying decisions. Key consumer behaviour questions such as “who, what, when, where, how, and why” are used by marketers to understand reality and every facet of the consumer behaviour (Kotler and Keller, 2006). The starting point of the buying process is problem recognition. The consumer starts buying, when he or she recognizes a problem or need (Kotler and Keller, 2006). There are mainly five stages that the consumer passes through during the buying decision process: problem recognition, information search, evaluation of alternatives, purchase decision, and post purchase behaviour. The consumer does not necessarily pass through all stages when he or she buys the product. He or she may skip some stages if he or she already is familiar with the product (Kotler and Keller, 2006). Figure 2 represents the five stages of the buying decision process.

Consumer Psychology

Motivation Perception Learning

Memory Buying Decision

Process

Problem recognition Information search Evaluation of alternatives Purchase decision Post-purchase behaviour

Purchase Decision

Product choice Brand choice Dealer choice Purchase amount Purchase timing Payment method

Consumer Characteristics

Cultural Social Personal

Marketing Other Stimuli Stimuli

Products Economic Services Technological Price Political Distribution Cultural Communications

- 14 - Figure 2. Stage model of the consumer buying process

Source: Kotler and Keller (2006).

Problem recognition

Information search

Evaluation of alternatives

Purchase decision

Postpurchase behaviour

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CHAPTER III

3. METHODOLOGY

3.1 The Study Area

Kosovo is situated in South-East Europe surrounded by Albania, Macedonia, Serbia and Montenegro, with a total land area of 10.908 km² and population density 193 people per km². Kosovo is divided into 5 regions and 30 municipalities with 1466 settlements (Law on Territorial Structure, 2004). Taking into account that the system of civil registration was not up to date and there has not been any census taken since 1981, it is difficult to provide reliable figures for the population as a whole (Ministry of Public Services-MPS, 2007). Referring to the latest registration conducted by Statistical Office of Kosovo (SOK) in 1981, the total number of inhabitants was estimated to be 1,959,714. In terms of population size, Prishtina is the biggest region with 25.5% of the total population, followed by Peja with 21%, Prizren with 19.6%, Gjilan with 19.6% and Mitrovica with 14.6%. Traditionally more of the population of Kosovo lives in the rural areas than in urban areas, with proportion 55:45%.

Kosovo is considered to have the youngest population in Europe, where 33% of the total population is less than 14 years old, 61% is between 15-64 years old, while only 6% of the population is over 65 years old. Ministry of Public Services (MPS, 2009a) states that for every 100 female births there are around 109 male births.

Statistics of Living Standard in 2007 indicated that households living in rural areas as well those less educated had lower general food consumption than household living in urban areas.

In 2008 food consumption per households living in urban areas was 2.144 euro or 35% of the total consumption, compared 2384 euro or 44% for those living in rural areas (MPS, 2009b).

Statistical data on the level of education in 2007 has shown that more than 40% of the males and about 60% of the females had not completed upper secondary education. The unemployment rate in 2007 for the labour force in the 15-64 age groups was denoted 33.7%

for males and up to 49.2 % for the females.

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3.2 Sample Selection

This section emphasizes the sampling principles and methods involved in selecting people (respondents) who would be asked questions by questionnaire. Before getting to the fieldwork, matters that concerned this survey were the definition of the population (N), sample size (n), type of sampling and formulation of the research instrument that suits the investigation of the topic. The intention of this study was to gain an understanding of consumers’ behaviours, their attitudes, preferences and demands towards milk and dairy products. The total number of inhabitants in Kosovo was the targeted population from which we were interested to draw a sample.

One of the most relevant and basic considerations in conducting a survey research by interview is the money and time consumed. It was impractical to examine each and every unit of the population, thus, sampling was needed. Even though a sampling approach was less costly in terms of money and time, other considerations came to the fore as well. Since the aim of this survey was to interview a sample drawn from the national population which was likely to be highly varied, there was a possibility of sampling error and bias. It was important to ensure that our drawn sample and findings reflected the national population accurately. One way in which it was possible to deal with the problem of sampling error and to minimize the bias was to perform stratified random sampling. It is important to emphasize that this does not mean that this type of sampling can eliminate bias and sampling error completely. According to Bryman (2004) stratified probability sampling keeps the sampling error in check better than non-probability sampling.

Another issue that is relevant to this survey relates to the choice of the sample size. A crucial criterion for the decision about the sample size was the level of standard error that we were prepared to tolerate in our findings. Considering this criterion we decided our sample size would be n = 385 (interviewees) out of 1.959.714 which was the total number of inhabitants in Kosovo. The calculation of the sample size was performed using a sample size calculator with a 5% margin of error, 95 % level of confidence and 50% response distribution.

The stratified random sampling has been applied as a type of probability sample in selecting people who would be included in the sample. One of the main reasons that we performed this type of sampling was that we wanted our sample to exhibit a proportional representation of the different strata of the population. Bryman (2004) states that by selecting a stratified sample, the standard error of the mean will be smaller since the variation between

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strata is eliminated and the population will be better represented in the sample in terms of the stratification criteria used. Moreover, this type of sampling permits us to employ a test of statistical significance and draw inferences about the whole population from which the sample was drawn.

The stratification of the sample was done according to three criteria: region, age and gender of the respondents. The sample size of n = 385 respondents was first stratified among regions according to the number of inhabitants in each region. The allocated number in each region was then stratified in terms of age and gender. The following figure illustrates the main stages involved in stratification of the sample units.

Figure 3.Stratification of the sample size

In spite of its advantages, this method of sampling could be feasible and economically reasonable only when it is relatively easy to identify and allocate units within strata. In our case stratification of the sample size into the strata entailed a great deal of work since there was no available list on distribution of the population by age and gender. Due to that, the actual respondents deviated slighlty in terms of these two strata compared to the one that is shown in Fig.3 (see Appendix A2 / Table 2).

n = 385

Prishtina Prizreni Mitrovica Peja

Gjilani Age 18-30

Age 31-40

Age 41-50

Age 51-60

Over 60

Total

Age 18-30

Age 31-40

Age 41-50

Age 51-60

Over 60

Total

Age 18-30

Age 31-40

Age 41-50

Age 51-60

Over 60

Total

Age 18-30

Age 31-40

Age 41-50

Age 51-60

Over 60

Total

Age 18-30

Age 31-40

Age 41-50

Age 51-60

Over 60

Total Female 16 Male 16

Female 11 Male 11

Female 10 Male 10

Female 8 Male 8

Female 3 Male 4

Female 48 Male 49

Female 13 Male 13

Female 9 Male 9

Female 7 Male 8

Female 6 Male 6

Female 3 Male 3

Female 38 Male 39

Female 9 Male 9

Female 7 Male 7

Female 6 Male 6

Female 4 Male 4

Female 2 Male 2

Female 28 Male 28

Female 13 Male 13

Female 10 Male 10

Female 8 Male 8

Female 6 Male 7

Female 3 Male 3

Female 40 Male 41

Female 12 Male 12

Female 9 Male 9

Female 7 Male 7

Female 6 Male 6

Female 3 Male 3

Female 37 Male 37

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3.3 Data Collection

In order to find out about the consumers’ behaviour, their attitudes, preferences and demand for milk and dairy products, a structured questionnaire was developed and used for the collection of data. The main reason for employing this method of interviewing was to provide exactly the same context of questioning to all interviewees. Given that replies of the interviewees are in the response to identical interview inducements, the interviewees’

responses can then be aggregated. The advantages of this type of interviewing go further than this. One advantage that is particularly significant is the reduction of error due to variation in the questions asked (Bryman, 2004). This method of interviewing also ensures greater accuracy and an easier way of processing the respondents’ answers.

The data used in this study were obtained through direct interviews (face to face) with Kosovo consumers aged 18 years and older. In order to avoid overestimation of the market demand for milk and dairy products, even those households who happen to have their own cows were included in the interviewing process. The survey was conducted during the period of January-February in 2009. A pre-test was conducted in order to ensure that survey questions and instrument as a whole functions well. Interviews with the respondents were administered by researcher and trained field assistants. Statistical Program for Social Sciences (SPSS) was employed for processing and analysing of data. The data is on a monthly basis and provides information on consumers’ buying behaviour, preferences, their attitudes toward product attributes, the quantity consumed and expenditures for milk and dairy products (yoghurt, fruit yoghurt, cream, curd, cheese and butter). The survey also provides data on respondents and households characteristics including sex, age, level of education, profession, number of family members, number of children aged 14 years and younger, respondent’s monthly income, HH income and number of employed family members.

Respondents were therefore asked to state whether they fulfil their needs for those products by monthly income available. The questionnaire also included retrospective questions on changes that had occurred over the previous year in consumers’ preferences towards milk and dairy products. These questions give responses about whether the consumers prefer new dairy products (innovation), what attracted them to start buying new dairy products and channels they used to become aware of the new dairy products. The main

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intention of asking these questions was to find out whether Kosovo consumers belong to conservative or progressive consumers category with regard to dairy products.

3.4 Model Specification

Two associated statistical techniques, multiple linear function and binary logistic function have been used to relate the dependent variable(s) to the independent variables. The model of multiple linear functions was performed for those dependent variables measured on continuous scales. There were, however, many dependent variables with binary responses that had to be evaluated for the effects of multiple independent variables on a dichotomous outcome. For the variables with dichotomous responses the model of binary logit-function was categorized to take on two values, Y = 1 when the response outcome for each subject is a

“success” and Y = 0 otherwise.

The logit- function with all the main effects is given as:

logit [(Y_i = 1)] = α + β_{1 Age}+ β2 Education+ β_{3 HH size} + β_{4 Children}+ β_5Employment + β6 HH income + β7p₁ + β₇r₁ + β₈r₂ + β₉r₃ + β₁₀r₄ + β₁₁e1 (1)

Where, Y_i indicates the exhibited preference of buying product i by jth respondent {1 = Yes, 0 = No}; α is intercept; β₁……….. β₁₁ are estimators coefficients; {p1} is the indicator variable for the first (of two) places; {r1, r2, r3, r4} are indicator variables for the first four (of five) regions; {e1} stands for the first indicator variable (of two) employment R. Consumers’

statements on the question as to whether they buy milk and other dairy products was defined as dependent variable Y (= 1 if the respondent buys milk and other dairy products and 0 if not). The statement of the consumers is then estimated as a function of respondent’s age, respondent’s education, household (HH) size, number of children below 14 years old, number of employed members within the HH, HH income, place as a factor with two indicator variables: Rural and urban, region as a factor with five indicator variables: Prishtina, Prizren, Peja, Gjilan, Mitrovica, respondent’s employment as a factor with two indicator variables:

Yes and no. The model treats place, region, and respondent’s employment as nominal-scale factors, whereas, respondent’s age, level of education, HH size, children below 14 years old, employed members within the HH, and HH income are treated as continuous-scale factors.

Similar models have been applied for the statement of the consumers on buying yoghurt, fruit

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yoghurt, cream, curd, cheese and butter. A full description of other variables with dichotomous outcome which are used as dependent variables and estimated with the same model and the same explanatory variables is presented in Table 8.

In the model of the multiple linear function the quantity of milk and other dairy products purchased by a household within a month is a function of respondent’s age and education, HH size, number of children aged 14 and younger, number of employed family members and HH income. The same model has been used for the total expenditure on milk and other dairy products.

Linear function equations are specified as follows:

Q i = b0 + b1Ag + b2De + b3Hh + b4Ch + b5Me + b6In + Ui (2)

E i = b0 + b1Ag + b2De + b3Hh + b4Ch + b5Me + b6In + Ui (3)

T = b₀ + b₁A_g + b₂D_e + b₃H_h + b₄C_h + b₅M_e + b₆I_n + U_i (4)

where, Q_i is the quantity of product i purchased in litre/month in the HH_i ; E _i is the expenditure on product i in euro/month in the HH_i; T is total expenditure on milk and six other dairy products in euro/month in the HH_i;(i = 1………..385); b₀ indicates the intercept;

A_g denotes age of the respondent i; D_e indicates education of the respondent i; H_h stands for the HH size; C_h indicates number of children below 14 years old in the HH_i; M_e stands for number of employed family members in the HH_i; I_n indicates average monthly income in the HHi; b1...b6 are estimated coefficients of the variable (s); and Ui is a random error term.

Other statistical models were employed in order to analyse the set of data obtained by the research study. Analysis of variance (ANOVA) has been used to find out whether there were significant differences between means of the HH size, number of children below 14 years old, number of employed family members, HH income, respondent’s income and education as a factor of gender, place and region. Test of independence was performed to study whether there was dependency between the market places that consumers preferred to buy dairy products, the frequencies of buying dairy products, and the evaluation of product attributes with demographic and socioeconomic characteristics.

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3.4.1 Variable Description and Measurement

Tables 4, 5, and 6 present a full description of all input variables that were accommodated into fitted models in the equation 2, 3, and 4, while Tables 7, 8, and 9 describe the variables used in equation 1.

Table 4. Dependent variables used in the estimation of the average quantity of the product i purchased in litre or kilogram in the HHi

Dependent Variable Description of Variable

Q Milk _(l/month) Quantity of milk purchased in the HH_i Q Yoghurt (l/month) Quantity of yoghurt purchased in the HHi

Q FruitYoghurt (kg/month) Quantity of fruit yoghurt purchased in the HHi

Q Cream (kg/month) Quantity of cream purchased in the HHi

Q Curd (kg/month) Quantity of curd purchased in the HHi

Q Cheese (kg/month) Quantity of cheese purchased in the HHi

Q Butter (kg/month) Quantity of butter purchased in the HHi Note: Q indicates quantity of the product i.

Table 5. Dependent variables used in the estimation of the average monthly expenditures on the product i in euro per month in the HH_i

Dependent Variable Description of variable

E Milk (euro/month) Expenditures on milk in the HHi

E Yoghurt (euro/month) Expenditures on yoghurt in the HH_i E Fruit yoghurt (euro/month) Expenditures on fruit yoghurt in the HHi

E Cream (euro/month) Expenditures on cream in the HH_i E Curd (euro/month) Expenditures on curd in the HH_i E Cheese (euro/month) Expenditures on cheese in the HH_i E Butter (euro/month) Expenditures on butter in the HH_i

E Total (euro/month) Expenditures on milk and dairy products in the HH_i

Note: E indicates expenditures on the product i.

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Table 6. Independent variables used in the estimation of the quantity and the expenditures on milk and six other dairy products

Independent Variable Description of variable

Age Respondent’s age given in years

Education Respondent’s education given in years HH size Number of members in the HH_i

Children Number of children in the HH_i aged 14 and younger Employment Number of employed members in the HH_i

HH income Average monthly income in the HH_i

Note: HH monthly income is given in euro

Table 7. Dependent variables used in the estimation of the fitted model in the equation 1 Dependent Variable Description of Variable

Product Exhibited statement on buying product i by jth respondent Milk Y = 1 if the respondent buys milk and Y = 0 otherwise Yoghurt Y = 1 if the respondent buys yoghurt and Y = 0 otherwise Fruit yoghurt Y = 1 if the respondent buys fruit yoghurt and Y = 0 otherwise Cream Y = 1 if the respondent buys cream and Y = 0 otherwise Curd Y = 1 if the respondent buys curd and Y = 0 otherwise Cheese Y = 1 if the respondent buys cheese and Y = 0 otherwise Butter Y = 1 if the respondent buys butter and Y = 0 otherwise

Table 8. Dependent variables used in the estimation of the fitted model in the equation 1 Dependent Variable Description of Variable

Fulfilment of the respondent’s needs

Y = 1 if the respondent fulfilled needs for the dairy products with his/her current monthly income and Y = 0 otherwise Preferring domestic

dairy products

Y = 1 if the respondent preferred domestic dairy products and Y = 0 otherwise

Preferring foreign dairy products

Y = 1 if the respondent preferred foreign dairy products and Y = 0 otherwise

Preferring new dairy products

Y = 1 if the respondent preferred new dairy products and innovation and Y = 0 otherwise

Buying new dairy products

Y = 1 if the respondent during the last year started buying new dairy products and Y = 0 otherwise

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Table 9. Independent variables (factors) used in the estimation of the fitted model in the equation 1

Factor Indicator Variable Place 1 = Rural; 0 = Urban

Region 1 = Prishtina; 2 = Prizren; 3 = Peja; 4 = Gjilan; 5 = Mitrovica Employment_R Respondent’s employment 1 = Yes; 0 = No

Table 10. Recoded variables used in the test of independence Variable Recoded Variable

Age 1= 18-30; 2 = 31-40; 3 = 41-50; 4 = 51-60; 5 = older than 60 Education 1 = Primary school; 2 = Secondary school;3 = University IncomeR 1= up to 200; 2 = 201-400; 3 = 401-600; 4 = more than 600 HH size 1 = up to 2 members; 2 = 3-4; 3 = 5-6; 4 = more than 6 Children 1 = 1 child in the HH; 2 = 2-3; 3 = 4 and more

Employment 1 = 1 employed family member; 2 = 2-3; 3 = 4 and more

HH income 1 = up to 200; 2 = 201-400; 3 = 401-600; 4 = 601-800; 5 = more than 800

Note: Variable Income_R indicates respondent’s income; HH income and respondent’s income are given in euro

3.4.2 Estimation Procedure

In view of the fact that this study was designed to answer certain questions about consumers’ behaviour, preferences and demands for milk and other dairy products, several predictor variables have been included in the models (equation 1, 2, 3 and 4). Models with several explanatory variables often suffer from multicollinearity, making it seem that no one variable is significant when all the others are in the model (Agresti, 2007). The selection process of the fitted model becomes more complex as the number of explanatory variables increases. The estimation procedure of the stated preference by consumers for buying milk and other dairy products began with a preliminary model presented in equation (1). Backward elimination procedure was used to select an optimal model that tends to have its fitted values closest to the true expected values. With this algorithm, the fitted model began with all explanatory variables presented in equation (1), and then the variable that produced the smallest decrease in residual variance was removed from the model. This method takes out terms successively, until there are no variables remaining in the equation that could be removed without significantly increasing the residual variance. Backward elimination uses the

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incremental sum of squares as a measure of the increase in the residual sum of squares associated with removing the variable (Glantz and Slinker, 2001).

The next stage of the model selection checked the model fit. The validity of the fitted model in the equation 1 was checked by using log-likelihood statistic, while Wald statistic was used in assessing the contribution of predictors. Multiple linear functions in the equation 2, 3, and 4 were judged by using the goodness of fit (R²) statistical tests of significance (F statistics for testing whether the fitted model reduced significantly residual variances, t- statistics for testing individual regression coefficients). χ²Statistics has been carried out for testing the independence between variables. The coefficient of Cramer’s V was used for measuring the strength of association between two categorical variables.