Consumer Preference and Willingness-To Pay for Locally Produced, Organic Food: A Stated Choice Approach. By Yihong Zheng

Transcription

1 Consumer Preference and Willingness-To Pay for Locally Produced, Organic Food: A Stated Choice Approach By Yihong Zheng A Thesis Presented to The University of Guelph In partial fulfilment of requirements for the degree of Master of Science In Food, Agricultural and Resource Economics Yihong Zheng, August, 2014

2 ABSTRACT IDENTIFYING THE MOTIVATION FOR PURCHASING PROCESSED ORGANIC FOOD BY USING STATED CHOICE MODEL Yihong Zheng University of Guelph, 2014 Advisor: Professor John Cranfield This study investigates Canadian consumers' preferences for organic and locally produced processed foods. The analysis is based on three choice experiments, one for pork tenderloin, one for whole grain bread and one for cheddar cheese, and implemented through an internet based survey. The choice experiments address two important research questions. First, what food attributes do Canadians associate with when they purchase locally produced organic foods? Second, which food attributes command a higher premium? Results from conditional logit regression models suggests that there is a disutility associated with food mileage, where respondents were willing to pay a premium of $ per kilometer per loaf of whole grain bread, $ per kilometer per kilogram of pork tenderloin and $ per kilometer per kilogram of cheddar cheese respectively. Respondents were also willing to pay a premium for the authentication of organic. More specifically, respondents are willing to pay a premium for certified organic whole grain bread ($0.076/loaf), certified organic pork tenderloin ($0.8299/kg) and certified organic cheddar cheese ($0.3381/kg).

3 ACKNOWLEDGEMENTS First and foremost, I would like to thank my advisor, Dr. John Cranfield for his invaluable guidance, inexhaustible patience and great encouragement throughout the process of this study. His mentorship and friendship have extended beyond more than a thesis. Without him, this thesis would not have been completed. I would also like to express my deepest gratitude to all the faculty and staff at the department of Food, Agricultural and Resource Economics, for their continual supports and help. Special thanks to my committee members, Dr. John Cranfield, Dr. Andreas Boecker, and Dr. Michael Von Massow for their constructive suggestions and feedback. I would like to thank OMAFRA for financial support. Thank Kelvin Tsang for developing the survey and his great help. In addition, I really appreciate the friendship and support from my amazing classmates. Last but not the least, to my parents, Dongmao Zheng and Bizhu Zhuang, my wife, Xiaoting Huang and my sister, Yinan Zhuang, whose dedications to my success are so meaningful to me. iii

4 TABLE OF CONTENTS Acknowledgements... iii Table of Contents... iv List of Tables... vi List of Figures... vii Chapter 1 Introduction...1 Chapter 2 literature review Introduction The Definition of Organic and/or Locally Produced Food Consumers Motives for Buying Organic and/or Locally Produced Food Physical Attributes Social Welfare Attributes Socio-Demographic Attributes Research Gap Summary...18 Chapter 3 conceptual framework Introduction Two Challenges of Choices Analysis Stated Preference Data and Revealed Preference Data Theoretical Foundation The Lancastrian Theory The Random Utility Model (RUM) Summary...27 Chapter 4 methods and data Introduction The Choice Experiment and the Survey Design Food Attributes and Respective Level D-optimal Design and Choice set Generation Survey Design Empirical Framework Statistical Model...42 iv

5 4.4.1 The conditional logit model ( CL) Estimating the Willingness to Pay Summary...45 Chapter 5 EMPRICAL RESULTS Introduction Survey Representativeness Distribution of the Survey Comparing the Survey Sample to the Canadian Population Influences on Organic and Local Food Choices Distribution Channel Food Values and Responses to Psychographic Questions Estimation Results of Conditional Logit Model Estimation Coefficients Results of Conditional Logit Model Estimation Results of Willingness to Pay Discussion Summary...72 Chapter 6 CONCLUTION Research problem Summary of Main Findings Implications for Food Producer and Supply Chain Members Limitation of the Research Suggestions for Future Research...81 Bibliography...83 Appendix...86 v

6 LIST OF TABLES Table4.1: Attributes and Levels in the Three Food Products Choice Experiments31 Table5.1: Socio-Demographic Characteristics of the Survey Respondents..48 Table 5.2: Distribution Channels Visited by the Respondents to Purchase Food Labelled as Conventional, Organic, and Local...51 Table 5.3: Food Attributes Consumers Believed to be Important for Purchasing Organic and Locally Produced Foods...53 Table 5.4: Conditional Logit Estimations of Whole Grain Bread Choice Experiment Block...57 Table 5.5: Conditional Logit Estimations of Pork Tenderloin Choice Experiment Block...59 Table 5.6: Conditional Logit Estimations of Cheddar Cheese Choice Experiment Block...61 Table 5.7: Post Estimation of Different Food Attributes Coefficient...63 Table 5.8: Willingness-to-pay for Whole Grain Bread Choice Experiment by Using Conditional Logit Model...65 Table 5.9: Willingness-to-pay for Pork Tenderloin Choice Experiment by Using Conditional Logit Model...66 Table 5.10: Willingness-to-pay for Cheddar Cheese Choice Experiment by Using Conditional Logit Model...68 Table 5.11:Willingness-To-Pay for Five Food Products..70 vi

7 LIST OF FIGURES Figure 5.1 The Linear Relationship is Between Conventional Whole Grain Bread and Certified Organic Whole Grain Bread and Food Miles 70 vii

8 CHAPTER 1 INTRODUCTION In recent years consumer has grown awareness and demand for organic food. In Canada, demand for organic food grew by 20 per cent annually over the last decade (AAFC, 2013). The total estimated retail sales of organic food was $ 651 million CAD in 2001 and $ 2987 million CAD in 2010 (AAFC, 2013). Organic food has become a large market with attractive prospects. Many previous studies have estimated a premium that consumers are willing to pay for organic food, as well as consumer motives for buying organic food. Some authors view food safety, health and nutrition as important consumers motives for buying organic food (Yue and Tong, 2009; Voon, Ngui and Agrawal, 2011; Moser et al, 2011). However, these studies did not distinguish certified organic food and non-certified organic food. In Canada, certified organic means that this product has already been verified by a third party and its production methods and ingredients are compliant with the Canadian Organic Standard which is made by the Canadian Federal government. Meanwhile, non-certified organic means that the production system or farm that produces the food products is not certified by a third party, but the farm still used organic produced methods. Furthermore, non-certified organic food products are only allowed to be sold within province in which the farm is located. If producers and supply chain members want to sell organic food between two different provinces or countries, organic food must be certified. Certified organic food can also be sold within the province in which the farm is located. Thus, the distribution of certified organic and non-certified organic 1

9 becomes important insofar as choice of where to sell is concerned i.e. within province or outside of the province in which the farm is located. Interprovincial or international sales require compliance with certified organic regulations promulgated by the Federal government; within province sales do not necessarily certification with Federal regulations (but could require compliance with any provincial regulations). Such differences may lead producers with non-certified organic food to focus only on local markets (e.g. with the province sales, thus qualifying as local food under the CFIA definition which are discussed later). Given that some retail venues, especially larger chains, require certified organic product to quality for consideration in their stores, the choice to certify or not could also affect the choice of distribution channel (i.e. to qualify for larger retail chains, farms must be certified). Therefore, food producers and supply chain members is watching distribution channel decision want to know whether consumers are willing to pay a premium for certified organic label, and whether that premium is higher than the cost of certified organic label. This study will divide food into three kinds: conventional food, certified organic, and noncertified organic, then this study will estimate premiums that consumers are willing to pay for each food type. In the organic food market, organic fruits and vegetables account for a larger share of the market than organic processed food. A number of studies have explored consumers motives for buying organic food, most of them are relative to organic fruits and vegetables. According to the Canadian Organic Standard, organically processed food must include at least 70% of its organic contents 2

10 (CFIA, 2013). Similar to other organic food products, a significant positive correlation was found between environment, animal welfare, and food safety on consumers willingness-to-pay for organic processed food (Yue and Tong, 2009). Others have reported that consumers have a declining willingness-to- pay (WTP) for organically processed foods as the percentage of organic content diminishes (Batte et al 2007). Given growth in the percentage of organic processed food, food producers and supply chain members might want to know whether consumers are willing to pay a premium for organic processed food. With the fast development of modern transport, consumers are able to purchase foods that are produced in a place that is further away from their living area. Due to further food miles, the term local food has been defined in order to distinguish international food. In Canada, the Canadian Food Inspection Agency determined an official definition for local food : 1.food produced in the province or territory in which it is sold; 2. food sold across provincial borders within 50 km of the originating province or territory (CFIA, 2013). Many previous studies have related the most important consumer motives for buying local food is a perception of higher food quality and freshness of local food (Thilmany, Bond and Bond, 2008; Yue and Tong, 2009; Zepeda and Deal, 2009; Cranfield et al, 2008; Costanigro et al; 2011). This is because locally produced food has fewer food miles and it fosters more direct contact between producers and consumers. Other motives include supporting locally owned or operated businesses and a perception that local is more friendly to the environment (Thilmany, Bond and Bond, 2008; Cranfield et al., 2008; Zepeda and Deal, 2009; Costanigro et al, 2011). In order to 3

11 encourage farmers to produce more local food, different regional governments have promulgated laws. In 2013, Ontario's legislature passed a Local Food law - Bill 36. The purpose of Bill 36 is to foster successful local food economies, to increase the awareness of local food and diversity, and to encourage new markets for food. The market for local food has become a significant market with attractive prospects, especially for Ontario s food producers and supply chains members. Therefore, food producers and supply chain members want to know whether consumers are willing to pay a premium for local food. As a final step of consumers food purchasing, the food distribution channel plays an important role in consumers food choose. Consumers have choice across different food distribution channel. Consumers who buy food products from cooperative and specialty stores are more likely to buy organic food (Yue and Tong, 2009). Consumers who buy food products from mass merchandisers and supermarkets are more likely to buy conventional food (Yue and Tong, 2009). Furthermore, consumers who buy food products from roadside stands and farmers markets are more likely to buy locally grown food (Yue and Tong, 2009). Therefore, food producers and supply chain members want to know whether consumers are willing to pay a premium for different distribution channel when they purchase food product. Above all, the research questions in this study are as following: First, which processed food product attributes (local, organic, or distribution channel) do consumers value? Second, which processed food product attributes command a higher premium? This study is aimed to estimate which processed food product 4

12 attributes command a higher premium that consumers willing to pay for processed food product. The objectives of this study are as following: 1. To provide a critical assessment of previous research on the motives of consumers willingness to pay for organic and/or locally produced food by reviewing the existing literature. 2. To develop a conceptual framework that can be used to measure Canadian consumer preferences related to organic and/or locally produced food products by adopting a suitable consumer choice framework. 3. To construct an empirical framework to measure consumer preferences for locally produced organic food. 4. To provide policy implications for food producers relevant stakeholders interested in producing or marketing organic and/or locally produced processed food by drawing conclusions from the empirical results. In this thesis, a survey and choice experiment were designed based on the literature review. There were three choice experiments. One for each of the following foods: whole grain bread, pork tenderloin and cheddar cheese. The food attributes were divided into three main parts: (1) food miles: 10km, 50km, 100km and 1000km; (2) production system: conventional food, certified organic and noncertified organic; (3) distribution channel: farmer direct, independent grocery stores, provincial-wide supermarkets and nation-wide supermarkets. The choice experiments was embedded in an internet survey, which were disseminated by IPSOS. After the data was collected, a conditional logit model was used to 5

13 estimate the coefficients of each food attributes. Then, these coefficients were used to estimate the premiums that Canadian consumers are willing to pay for each food attributes. Chapter Outline Chapter 1 Introduction This chapter will provide an introduction to my thesis. Firstly, it will present a background and context to the Canadian organic and/or locally produced food market, outlining the previous research surrounding the governing standards of Canadian organic and/or locally produced food. Secondly, the economic problems and the economic research problem will be stated, which identify who owns the economic problem, what is not known, and why this unknown is important. Last but not least, the purpose and objectives will be described in this chapter. Chapter 2 Literature Review A review of related literature will be presented in Chapter 2. I will introduce the motivations for consumers to buy organic and/or locally processed food, such as health motives, environmental motives and economic motives. I will also describe consumer determinants of demand for organic and/or locally food products across different product spaces. Finally, I will critically evaluate the published literature to identify ways in which my research will contribute to the broader body of knowledge. Chapter 3 Conceptual Framework This chapter will provide the details of the analytical framework. Two 6

14 challenges of choice analysis will be discussed and I will introduce the stated choice modeling framework which adopts the choice experiment technique. Additionally, two main theoretical foundation will be presented, which are the Lancastrian Theory and the Random Utility Model. Chapter 4 Methods and Data I will present the modified model based on the conceptual framework. The empirical model will be used to conduct my analysis. The survey design and data will be discussed in this chapter. Chapter 5 Empirical Results I will present the results of my analysis in this chapter. The estimation results will give some implications for food producers and supply chain menbers. Chapter 6 Conclusion I will summarize the results of my project. Additionally, I will identify areas of extension for research on organic food and make recommendations for future research in this area. 7

15 CHAPTER 2 LITERATURE REVIEW 2.1 Introduction This chapter gives a critical review of the previous literature related to consumers motives for buying organically grown and/or locally grown food. The second section will introduce a definition of organic and/or locally produced food. The third section will review literature on consumers motive for buying organic and/or locally produced food. The fourth section will review literature on the premiums that have been reported for consumers willingness to pay for organic and/or locally produced food, and discusses the research gaps. A summary is provided in the last section. 2.2 The Definition of Organic and/or Locally Produced Food Conventional food and organic food are two kinds of food production systems. In Canada, broadly speaking, certified organic means that this product is from a farm that use production methods and ingredients have been certified as being compliant with the Canadian Organic Standard. Meanwhile, non-certified organic means that production system or farm that produces the food product is not certified as organic by a third party, but the production system or farm still used organic produced methods. Organic processed food is a part of organic food. According to the Canadian Organic Standard, organically processed food must include at least 70% of its organic contents (CFIA, 2013). 8

16 The term local food has many definition. It can be defined in different ways, such as a distance or supply chain (Cranfield et al, 2008). The distance between the place of food production and the place of food consumption is the most general way to define local food. Local food may mean a 50 mile radius from the point of food consumption (Onozaka et al, 2010); it may also mean the area of food consumption within a country or state (Selfa & Qazi, 2005). Local food can be also defined by supply chain in which foods are consumed (Cranfield et al, 2008). Roadside stands and farmer markets are two important supply channels for local foods (Selfa & Qazi, 2005;Thilmany, Bond and Bond, 2008; Cranfield et al, 2008). In Canada, the Canadian Food Inspection Agency (CFIA) determines an official definition for local food : 1.food produced in the province or territory in which it is sold; 2. food sold across provincial borders within 50 km of the originating province or territory (CFIA, 2013). 2.3 Consumers Motives for Buying Organic and/or Locally Produced Food Many studies have reported consumers motives for buying organic and/or locally produced food. Consumers motives can be divided into three parts: physical attributes, social welfare attributes and socio-demographic attributes. Physical attributes are the food s own characteristics, for instance, appearance, pesticide free, taste, price, safety, convenience, nutrition, tradition, origins, naturalness and fairness and so on. Social welfare attributes include animal welfare and environmental benefit. Socio-demographic attributes are consumers own characteristics. For example, age, income, gender, education, distribute channel, and family size. 9

17 2.3.1 Physical Attributes Food safety Food safety is one of the most important consumers motives for buying organic food (Yue and Tong, 2009; Voon, Ngui and Agrawal, 2011; Moser et al, 2011). Consumers often have the perception that organic food is safer than conventional food, especially consumers who have infants and children, because organic food does not use artificial chemical fertilizers and pesticides. However, whether organic food is safer than conventional food is a controversial issue. Some studies argued that organic food is safer than conventional food (Yiridoe et al., 2005; Yue and Tong, 2009; Voon, Ngui and Agrawal, 2011; Moser et al, 2011; Onozaka and McFadden, 2011), while other studies argued that organic is not safer than conventional food (Van Loo et al., 2012). According to Yue and Tong (2009), approximately 83% of participants thought safe to eat was important for organic food, and over 71% of consumers said they bought organic food in order to avoid pesticides. Unlike results of Yue and Tong (2009), Van Loo et al. (2012) did not found any scientific evidence that proves organic food is safer than conventional food. Van Loo et al. (2012) argued that detectable chemical fertilizers and pesticides of organic food are not equal to zero even though organic production does not use artificial chemical fertilizers and pesticides, especially for organic processed food. Furthermore, Van Loo et al. (2012) noted that both organic and conventional food can have a level of chemical fertilizer and pesticide residue that is below the acceptable threshold level. Therefore, Van Loo et al. (2012) argued that organic food is not safer and healthier than conventional food. However, 10

18 chemical fertilizers and pesticides residue will increase as time or consumption food quantity increases. As time or consumption food quantity increases, the accumulative concentration of chemical fertilizers and pesticides which are different in organic food and conventional food may be higher than the safe threshold level for children. In this case, organic food is safer than conventional food. Similar to organic food, food safety is also one of the most important consumers motives for buying locally produced food (Yue and Tong, 2009; Zepeda and Deal, 2009; Moser et al, 2011; Onozaka and Mcfadden, 2011). According to Yue and Tong (2009), approximately 88% of participants thought safe to eat as important for locally produced food. There are two main reasons why locally produced food may be considered safer than conventional food. First, locally produced food has less food miles, so food contamination is reduced during transportation (Zepeda and Deal, 2009, Cranfield et al., 2012; Onozaka and Mcfadden, 2011). Second, locally produced food fosters more direct contact between producers and consumers. This direct contact between consumers and producers further reinforces a sense of trustworthiness in the safety of the food product (Zepeda and Deal, 2009). Freshness and nutrition Consumers also consider that organic food can improve their health (Zepeda and Deal, 2009; Moser et al., 2011; Thilmany et al., 2008; Kriwy and Mecking, 2012). Similar to food safety, whether organic food has more nutrition than conventional food is a controversial issue. Some studies argued that organic food is safer than 11

19 conventional food (Yiridoe et al., 2005; Yue and Tong, 2009; Voon, Ngui and Agrawal, 2011; Moser et al, 2011; Onozaka and McFadden, 2011), while other studies argued that organic is not safer than conventional food (Zepeda and Li, 2007; Dangour et al., 2010; Van Loo et al., 2012). According to Yue and Tong (2009), approximately 78% of participants thought nutrition was important for organic. Unlike results of Yue and Tong (2009), Zepeda and Li (2007) argued that there is no evidence that proves organic food has more nutrition than conventional food. Compared to nutrition, freshness is a more important consumers motive for buying locally produced food (Magnusson et al., 2001; Hu, Woods and Bastin, 2008; Zepeda and Deal, 2009; Costanigro et al., 2011; Yue and Tong, 2009; Onozaka and Mcfadden, 2011). Due to short food miles associated with local, locally produced food is often perceived to be fresher than non-local foods. Freshness is the most important consumers motive for buying locally produced food in Yue and Tong s study (2009). Price The price of organic food is higher than conventional food (Magnusson et al., 2001; Hu, Woods and Bastin, 2008; Zepeda and Deal, 2009; Costanigro et al., 2011; Yue and Tong, 2009; Onozaka and Mcfadden, 2011; Mesias et al., 2012; Darby et al.; 2008). Magnusson et al., (2001) argued that the high price premium is a major obstacle to buy organic food. Compared to organic food, locally produced food has lower price. Given the short distance travelled for local food, transport and storage cost of locally produced food is low. Locally produced food 12

20 has a low price can be an important consumer motive (Magnusson et al., 2001; Hu, Woods and Bastin, 2008; Zepeda and Deal, 2009; Costanigro et al., 2011; Yue and Tong, 2009) Social Welfare Attributes Environmental benefits and animal welfare are two organic food attributes that are difficult to determine by visual inspection. Environmental benefits (Yue and Tong, 2009; Zepeda and Deal, 2009; Onozaka and Mcfadden, 2011) and animal welfare (Selfa and Qazi, 2004; Zepeda and Deal, 2009; Moser et al., 2011) are more important consumers motives for buying organic food. According to Yue and Tong (2009), approximately 70% of participants thought environmentally friendly is important for organic food. Organic production methods can improve soil quality, reduce environmental pollution and enhance biodiversity (CFIA, 2013), because it is forbidden to use artificial chemical fertilizers and pesticides when producing or handling organic products. Consumers gaining environmental benefits through purchasing locally grown food are another motive for choosing locally grown food. Because local grown food is produce locally, sold locally, locally grown food and reduce significant transport energy cost (Zepeda and Deal, 2009). Therefore, purchasing locally grown food will reduce local environmental pollution (Zepeda and Deal, 2009). However, other studies argued that purchasing local grown food will increase local environmental pollution (Baranski, Babbie and Pirog, 2012), because greenhouses are usually used to produce food out of season in local. Greenhouse costs more energy than transport energy cost. Because of the short 13

21 growing seasons and longer winter in Canada, greenhouses are necessary for local farms to produce food. Therefore, many studies only consider local food transport energy cost as a factor which affect local environment. Thus, purchasing locally grown food will reduce local environmental pollution. Supporting local farms is the most important motive for choosing locally grown food (Thilmany, Bond and Bond, 2008; Cranfield et al.,2008; Zepeda and Deal, 2009; Costanigro et al, 2011). For example, due to a distrust of corporations, some Madison consumers purchased local food to support local farms in order to rally against corporations expanding (Zepeda and Deal, 2009). Local attributes build direct relations between the farmer and consumer in Colorado. Therefore, some Colorado consumers believe local food producers more than a third party (Costanigro et al. 2011). They trust the local food producers will create a better life circumstance for them and also treat animals better (Zepeda and Deal, 2009; Costanigro et al. 2011) Socio-Demographic Attributes Age A significant negative correlation was found between consumers age and the willingness to pay for organic food (Loureiro and Hine, 2002; Cranfield et al, 2008; Yue and Tong, 2009; Costanigro et al, 2011). This means that older consumers are less likely to pay a premium for organic food for organic food. As consumers age increases one year, their willingness-to-pay for organic potatoes will decrease by $0.16 per pound (Loureiro and Hine, 2002). This result may be 14

22 because when people become older, they become generally less concerned about the impacts of pesticides in the environment or food (Loureiro and Hine, 2002). Unlike organic food, previous studies did not find a significant relation between consumers' age and willingness-to-pay for locally grown food. Some studies stated that a consumers age has a negative effect on the willing-to-pay for locally grown food (Loureiro and Hine, 2002), while other studies claimed that consumers age has positive effect on WTP for locally grown food (Yue and Tong, 2009). However, not all of their results are significant. Gender A number of previous studies show that females are more willing-to-pay for organic grown food than males. Because females are primary household shoppers (Costanigro et al, 2011), they often have more concerns about food quality than males (Loureiro and Hine, 2002). However, no significant correlation was found between females and willingness to pay for organic food (Kirwy and Mecking, 2012). Similar to organic food, a number of previous studies show that females are more willing-to-pay for locally grown food than males. Because females are primary household shoppers (Costanigro et al, 2011) and they have more concerns about food quality than males (Loureiro and Hine, 2002). Income A significant positive correlation was found between consumers income and the willingness-to-pay for organic food (Loureiro and Hine, 2002; Yue and Tong, 15

23 2009; Zepeda and Deal, 2009; Costanigro et al, 2011). This means that wealthier consumers are more likely to buy organic food, because wealthier consumers have a greater budget to buy food (Loureiro and Hine, 2002; Yue and Tong, 2009; Costanigro et al, 2011). Unlike organic food, a number of previous studies found a positive but not significant correlation between consumers' income and willingto-pay for locally grown food (Loureiro and Hine, 2002; Yue and Tong, 2009; Costanigro et al, 2011). Education A significant positive correlation was found between consumers education background and consumers buying organic food (Magnusson et al., 2001; Voon, Ngui and Agrawal, 2011; Yue and Tong, 2009). More well-educated and wealthier consumers are more likely to buy organic food (Magnusson et al., 2001; Voon, Ngui and Agrawal, 2011; Yue and Tong, 2009). Unlike organic food, a positive but not significant correlation was found between consumers education and willingness to pay for locally grown food (Loureiro and Hine, 2002; Zepeda and Deal, 2009; Costanigro et al, 2011). Distribution Channel The type of store that consumers usual purchase food at also affects consumers decisions to buy organic food. Consumers who buy food products from cooperative and specialty stores are more likely to buy organic food (Yue and Tong, 2009). The type of store that consumers usually purchase food at also affects consumers decisions to buy locally grown food. Consumers who buy food products from roadside stands and farmers markets are more likely to buy locally 16

24 grown food (Yue and Tong, 2009). Consumers who buy food products from mass merchandiser and patronize supermarkets are more likely to buy conventional food (Yue and Tong, 2009). 2.4 Research Gap A number of previous studies have estimated consumers premium that consumers are willing-to-pay for organic food. The price premium for buying organically grown potatoes is cents/lb (Loureiro and Hine, 2002). The value of the organic label on apples ranged from $0.20 to $1.86 per pound in Colorado (Costanigro et al, 2011). Consumers willingness to pay for buying organic grown blueberry lies between $0.18 and $0.67 per pound in Kentucky (Hu, Woods, and Bastin, 2008). However, these studies did not distinguish certified organic food and non-certified organic food well. A premium consumers are willing to pay for certified organic may be different to non-certified organic. Besides that, whether consumers are willing to pay a premium for a certified organic label and whether that premium is higher than the cost of certified organic label is unknown. This study will divide food label into three parts: conventional food, certified organic and non- certified organic, then this study will estimate premiums that consumers are willing to pay for each. A number of previous studies have estimated the premium that consumers are willing to pay for locally produced food. Some studies shows that premium for locally grown food are greater than the premium for organically grown food. More specifically, locally grown (Colorado-grown) potatoes have a higher 17

25 premium compared with organic potatoes in Colorado (Loureiro and Hine, 2002). This result is consistent with another study by Costanigro et al (2011), who found that the value of the locally grown apple is much higher than for an organically grown apple in Colorado (Costanigro et al, 2011). Similarly, Hu, Woods, and Bastin (2008) found that the consumers willingness to pay for buying locally grown blueberry lies between $1.21 and $2.20 per pound, while the consumers willingness to pay for buying organic grown blueberry lies between $0.18 and $0.67 per pound (Hu, Woods, and Bastin, 2008). Although a number of studies have reported consumers motives for buying locally grown organic food, the difference between organic food and local food is still unclear. Consumers have similar motives for buying organic food and local food, such as food safety, quality, environment benefit, and support for small farmers and so on. As the global food industry develops, locally grown organically food will be a niche market. Therefore, it is important to determine consumers preferences and willingness-to-pay for organically grown and locally grown food 2.5 Summary This chapter provides definitions of organic food and local food and reviews previous literature related to consumers WTP for organic food and local food. Previous studies showed that consumer preferences are similar for local and organic food, as are the consumption motives (Thilmany et al., 2008; Zepeda and Deal, 2009; Van Loo et al., 2012). Although some studies have reported 18

26 consumers motives for buying local food and organic food, the differences between organic food and local food is still unclear. This thesis will use a stated choice model to assess the effects of distance and organic label on consumers preferences and WTP for purchasing organic food and/or local food. Furthermore, four different marketing channels, which are farmer direct, local independent grocery stores, provincial-wide supermarkets and national-wide supermarkets, will be used to identify consumers preferences and WTP for purchasing organic food and/or local food through different marketing channels. 19

27 CHAPTER 3 CONCEPTUAL FRAMEWORK 3.1 Introduction The conceptual framework will be introduced in this chapter. In the first section, two challenges of choices analysis will be discussed and presented. In the second section, revealed and stated preference methods will be discussed. The last section will introduce two theoretical foundations: the Lancastrian Theory and the Random Utility Model. 3.2 Two Challenges of Choices Analysis Choices are everywhere. From personal affairs to state affairs, people face and decide their choices every day, how do they make their choices? According to Louviere, Hensher and Swait (2000), individual s decisions process can be related to individual s preference building process. The initial awareness of individual s needs is the beginning of an individual s preferences building. In the initial awareness of individuals needs, people know very little about certain products that they need. Then, people start to search and learn the knowledge about certain products. After people know about certain products, they will gain utility from consuming certain products. Finally, individual s preferences of certain products are built. Therefore, people usually decide to purchase products that will maximize their utility. Some factors will affect individuals preferences, such as personal experiences and friend s recommendations. Therefore, individual choice is affected by those factors. According to Louviere, Hensher and Swait (2000), 20

28 individual choice is affected by external factors which include personal education level, personal experiences, personal preferences, family habits and friends recommendations and so on. These external factors have one trait in common: they will change over time. Therefore, individuals preferences will change over time. In other words, individuals preferences have a temporal nature. For example, individuals may love to eat an organic apple today, but they may not love to eat an organic apple one month later. The temporal nature of individuals preferences limits the choice analyst to only having access to data that captures information at a specific time and place. Therefore, the temporal nature of individual s preferences is a challenge for analysts to explain these factors through observed data. Another challenge for analysts to explain these factors through observed data is heterogeneity of individuals preferences (Louviere, Hensher and Swait, 2000). There are two main reasons for heterogeneity of individual s preferences. Firstly, individual preferences, which are identified from a single result that is analyzed by few sources, can be explained by the choice set such choice sets may vary spatially. This means, for instance, that the analysis results of Ontario individuals preference may not be suited to Quebec individuals preference. Secondly, heterogeneity of individual s preferences is a challenge for analysts to explain these factors through observed data. Due to limited resources, choice analysts have to survey a representative portion of the population in order to derive the reasoning for the underlying decisions of a choice outcome. This implies that choice analyst not only collect observed heterogeneity directly from the survey 21

29 but also unobserved heterogeneity from the rest of the population that was not in the survey. Therefore, the analyst has to capture explanatory power from the observed heterogeneity, but also account for the explanatory power from the unobserved heterogeneity. The Random Utility Theory can be used to capture the unobserved component (Hensher et al., 2005; Louviere, Hensher and Swait, 2000; Adamowicz et al., 1998), as discussed later in this thesis. 3.3 Stated Preference Data and Revealed Preference Data Two types of data are used in choice model: stated preference data and revealed preference data. Stated preference data is usually derived from consumer surveys, so stated preference data are made by considering a hypothetical situation. Revealed preference data are collected from purchase data from actual market transactions. The traditional economic approach used revealed preference data to evaluate individuals actual behavior. Revealed preference data are collected from actual transactions meant that hypothetical bias that normally occurs in stated preference studies will not be an issue. Revealed preference data has three big problems. First, revealed preference data is often not able to capture consumer socio-graphic characteristics. Second, revealed preference data cannot occur if new product or new service does not exist in real market. Last but not least, consumer preferences estimate using revealed preference data may be only driven by product availability at a particular store, which may be different from that in other stores (Goddard et al., 2007) 22

30 In contrast to revealed preference data, stated preference data is collected through contingent valuation surveys or choice experiments. Because stated preference data has some advantages over revealed preference data, stated preference data is more widely used than revealed preference data used to estimating consumer WTP. Stated preference data has a broader range than revealed preference data. For example, before a new product or a new service is provided to real market, analysts need to evaluate consumers preference for this new product or new service. In this case, there are no revealed preference data that is available for analysts to evaluate consumers preference for this new product or new service. However, stated preference data can be collected and used to evaluate consumers preference for this new product or new service. Besides that, some attributes of good are not traded in the real markets, but still have a social value, such as environmental benefit and animal welfare. These attributes may not trade in the real market, so they do not have revealed preference data. In this case, stated preference data can be collected and used to evaluate consumers preference for these attributes that have social value but do not trade in a real market. 3.4 Theoretical Foundation The stated preference methods will be used to evaluate consumer preferences in this project. Two theoretical foundations will be presented, which are the Lancastrian Theory and the Random Utility Model. 23

31 3.4.1 The Lancastrian Theory The Lancastrian Theory is an important theory in this thesis. It is different to neoclassic economic theory. In neoclassic economic theory, consumers select a bundle of goods to maximize their utility with a limited budget. The neoclassical utility maximization problem can be represented as follows: Max u(z) Subject to pz m (3.1) z Z Where: p is price of goods; Z is consumption set that includes all goods a consumer can choose. z is the quantity of good that consumers can buy; m is a limited budget. It is assumed that consumers gain utility from the good per se in the neoclassic utility maximization theory. Therefore, consumers have the same utility if they consume the same type and quantity of good in neoclassic economic theory. For example, consumers get utility from consuming some quantity of locally produced cheese, which is the same as the utility they get from consuming the same quantity of organically produced cheese. This is because locally produce cheese and organically produce cheese are the same type of good in neoclassic economic theory. Therefore, consumers will not buy organically produce cheese if the price of organically produce cheese is more expensive than locally produce cheese. But in the real market, the utility consumers gain from organically 24

32 produce cheese is different to what gain from locally produce cheese. Therefore, the neoclassic economic theory only evaluated the utility that is gained from the good per se, but fail to evaluate the change of utility when the attributes of the good change. Based on a neoclassic economic theory, Lancaster (1966) introduced the concept of characteristics" in consumer theory. In his theory, he deconstructed a good into several attributes and each attribute will give utility to consumers rather than good per se. Therefore, in the Lancastrian Theory, a good is made up by many attributes that have a specific value and the total value of the good is equal to the summation of each specific value of attributes (Lancaster, 1966). For example, vector z is the total quantities of the goods that consumers can buy and x k is the observable utility from the relevant attributes. The utility consumers gain from good x is given as follows: x k = A k z Where k is the attributes of good and A k is the vector of coefficients that are determined by k, k = 1, 2 K. Therefore, in the Lancastrian Theory, the utility maximization problem can be represented as follows: Max u(x)= Max u(x k ) =Max u(a k z) Subject to pz m (3.2) x, z 0 Where: x is a vector of observed attributes; k is the attributes of good; 25

33 good; A k is the vector of coefficients that are determined by the attributes of the p is price of good; z is the quantity of good that consumers can buy; m is a limited budget. Although the Lancastrian Theory defined the relevant attributes based on the properties of good, it fails to evaluate the differences which exist between consumers perception of objective attributes and the actual measure of utility based on the good s attributes (Louviere, Hensher and Swait, 2000). Therefore, Louviere, Hensher and Swait (2000) modified the Lancastrian model by adding an error term to the Lancastrian model. The error items captures the fact the choice analyst is unable to observe some consumers preferences. This approach leads to the Random Utility Model (RUM) The Random Utility Model (RUM) The Random Utility Model separated the utility, which a consumer obtains from purchasing a good, into two parts: an observed part and an unobserved part. There are n consumers to choose type J of processed food. Assume U ij is the ith consumer's utility obtained from the selection of processed food of type j. therefore, U ij can be represented as follows: U ij = V ij + ε ij (3.3) Where V ij is the observed part of ith consumer's utility. 26

34 ε ij is the unobserved part of ith consumer's utility. i = 1, 2 n j = 1, 2 J ε ij is the random utility choice term not included in the initial Lancastrian model, because Lancaster strictly derived utility based on product attributes only. In this project, utility is derived as not only product attributes but also unobserved consumers personal attributes. Therefore, ε ij is a very important part for the measurement of utility. The consumer i will choose alternative j only if U ij > U iq. Therefore, the probability of consumer i choosing j over q can be represented as follows: P ij = Prob (U ij U iq > 0) = Prob [ (V ij + ε ij ) ( V iq + ε iq ) > 0] = Prob (ε iq ε ij < V ij V iq ) (3.6) Where q j This equation (3.6) is called a random utility model (RUM). 3.5 Summary The temporal nature and heterogeneity of individual s preferences are two challenges for analysts to explain individuals decisions through observed data. The stated preference method will be used to evaluate the consumers preference of good. Compared to revealed preference data, stated preference data is better 27

35 suited to evaluate consumers preference for new products or environmental attributes of good. Two main theoretical foundations: the Lancastrian Theory and the Random Utility Model, were also presented in this chapter. 28

36 CHAPTER 4 METHODS AND DATA 4.1 Introduction This chapter will introduce the choice experiment, survey design and empirical model. In the first section, the choice experiment and the survey design will be discussed. It will introduce the structure of the survey and the attributes in the choice experiment. In the second section, the empirical model will be introduced. 4.2 The Choice Experiment and the Survey Design This section will introduce the choice experiment including discussion of the attributes varied in the choice experiment, as well as the survey Food Attributes and Respective Level In this survey, there were five different choice experiments, one for each of the five different food products: pork tenderloin, whole wheat bread, cheddar cheese, red tomatoes and gala apples. Red tomatoes and gala apples were chosen to represent the unprocessed food groups commonly bought in the Canadian diet, and pork tenderloin, whole wheat bread, and cheddar cheese were selected to represent processed food groups (Tsang, 2014). Each of the five products is characterized by the same attributes: price; total food miles from point of production to point of consumption at the home; production system; and distribution channel, as presented in Chapter 3. This study will only focus on examining the processed food groups: pork tenderloin, whole wheat bread, and cheddar cheese. How to vary the level of each food attributes of the processed 29

37 food products differs from the previous literature, especially for price level. Incorrectly listing the price levels may induce the wrong behavioral pattern in consumers that may lead to biased interpretations (Tsang, 2014). Since there are no guidelines on which price levels should be invoked, Tsang (2014) opted to survey the food market in Guelph, Ontario, Canada for the average prices listed in that city as baseline levels. The four attributes and their different levels are presented in the following tables 4.1. According to Table 4.1, the only difference between the three choices experiments is the base price levels, but percentage premiums for each food attributes are the same, while the rest of the attributes share the same levels. The production system attribute can be divided in three levels: (1) conventionally produced; (2) grown organically, but not certified; and (3) certified organic. The production system attribute is used to captures how consumers value different production techniques for different types of foods. Because "localness" is captured in the distance variable, local production was included as a level in the production system attribute. The decision to capture "localness" through the distance attribute allows for the consumer to express their perception of local food in terms of a continuous variable, rather than prescribing a standardized definition of local food (Tsang, 2014). The continuity nature of the distance attribute should reflect the heterogeneous nature of the definition of local food. The distribution channel attribute consist of four levels: farm direct; independent supermarkets; province-wide supermarket chains; and nation-wide supermarket chains. The purpose of the distribution channel attribute is to examine the effects of purchase 30

38 venue on the purchase decision for locally produced organic foods (Tsang, 2014). Price levels for each food product were calculated based on the average prices of three processed food products in the city of Guelph, Ontario, Canada, then scaling the base average price by 50%, 100%, and 200% yields the price levels. The purpose of scaling up the baseline average price is to reflect the higher premiums associated with food products such as organically produced or locally produced since these products often require higher cost of production (Tsang. 2014).The prices were collected between January 14th to 19th, 2013 from Walmart, Nofrills, Food Basics, Market Fresh and Metro, as reported in Tsang (2014). Since the demographics in Guelph, Ontario, Canada, resembles a typical city in Canada, the prices found in Guelph should be a close representative at the national level (CBC, 2007). Table4.1: Attributes and Levels in the Three Food Products Choice Experiments Attributes Production System Levels of Attribute Conventionally produced Grown organically, but not certified Certified organic Distribution Channel Farm direct Independent supermarkets Province-wide supermarket chains Nation-wide supermarket chains Total Food Miles by the Food Product 10 kilometers 50 kilometers 100 kilometers 31

39 1000 kilometers Prices Whole Grain Bread ($/loaf) Pork Tenderloin ($/kg) Cheddar Cheese ($/kg) Internet Survey Bias In this survey, some terms and concepts, such as the name of the retail venue and their characteristics may be new to respondents. If those concepts and terms are not explained to respondents clearly and effectively, the results may have bias. An online survey is used in this thesis. For online surveys, respondents have to read and remember all unfamiliar technical terms at once, which may put burden to respondents and may not be efficient. Therefore, the estimation results by using online survey may be misleading. In order to avoid bias, this survey provided clear definitions of technical terms in an information sheet to respondents at the beginning of the choice experiment. Given the case of stated choice methods, this thesis may have hypothetical bias. Hypothetical bias will causes the stated willingness-to-pay to be higher than the actual willingness-to-pay. A cheap talk" script, which reminds respondents their limited budget and the possibility of overestimating their WTP, was attached to the choice experiment will minimize hypothetical bias (Carlsson, Frykblom and Lagerkvist, 2005). Therefore, in order to reduce hypothetical bias, a cheap talk" 32

40 script is used in this study. A cheap talk script is presented to respondents before choice experiment as following: We would now like to ask you some hypothetical questions regarding what you might be willing to pay for Gala apples that are produced in different ways and sold in different retail venues. For each question, imagine that you are shopping for Gala apples and are faced with choosing apples with the characteristics described below. Whether or not you currently eat Gala apples, we would appreciate you completing the following choice comparisons. Even though the payment of money in this part of the survey is hypothetical, we ask that you respond to the questions as if it were an actual decision involving real cash payment. As you answer this question please keep in mind what you would normally pay for apples, how much you spend for food in general, and your interest in the products described D-optimal Design and Choice set Generation Experimental design is one of the fundamental part of the choice analysis. Choice analyst prefer to use an orthogonal factorial design in order to ensure the choice experiments are efficiently designed. When a linear model is implemented with an orthogonal design, the estimated parameters will be uncorrelated, independent from the other variables in the model and the variance of the estimated coefficients will be minimized (Tsang, 2014). The efficiency of an experimental design can be determined as a function of variance and covariances of the estimated parameters (Kuhfeld et al., 2010). The efficiency of the designed experiment will increase when the variance decreases. Therefore, the function of an orthogonal design is to minimize variance of the estimated parameters. Many studies used D-efficiency as the criterion for choosing the appropriate design for choice experiments involving foods (e.g Innes and Hobbs, 2011; Onozaka and McFadden, 2011; Lusk, 2011; and Loureiro and Umberger, 2007). 33

41 This thesis used a D-efficiency to determine whether the experimental design is efficient. In a D-optimal design, the attributes are nearly balanced and orthogonal and the determinant of the information matrix is maximized ([X X]). D-efficiency can be used to measure the efficiency of the design. D-efficiency scales from 0 to 100, where a D-efficiency score of 100 means the design is orthogonally balanced and the variance of the estimated coefficients ([X X] 1 ) is minimized (Tsang, 2014). According to Tsang (2014), the choice set design was created as a full factorial design that contained four attributes: with one three-level factor and three four-level factors. The full factorial design contained 192 possible combinations of alternatives (3 4 3 ) and with two alternatives available, this amounts to 96 possible choice sets. All main effects and specific two-way interaction factors are uncorrelated and estimable in the full factorial design (Tsang, 2014). However, subjecting the respondent to all 96 choice set imposes a response burden on respondents and is often impractical due to time and cost constraints. Therefore, the 96 possible choice sets were assigned to 12 blocks of randomized eight choice sets, with each choice set comprised of two alternatives and a third 'no-choice' option. According to Tsang (2014), the D-efficiency score of this experimental design was , while the relative D-efficiency score was The D-efficiency score is not high, but the blocking of a full factorial design and a large sample size (2000 observations) should compensate for the low D-efficiency score (Tsang, 2014). The 2000 completed surveys included five different version of the survey to reflect the five different food 34

42 products, so each food product choice experiment has 400 observations. Therefore, each choice experiments will have the same choice set design, and D- efficiency score, and the only difference between the five designs is the treatment of the price attribute and which product is assigned to the respondents (Tsang, 2014). Each respondent was randomly assigned on to one of the five different food product groups, then allocated to one of the 12 blocks of eight choice sets until each of the five groups has satisfied a quota of 400 respondents (Tsang, 2014). From the eight choice sets, the respondents were asked whether they prefer product one to product two, and which product they would purchase. no-choice or opt-out option A no choice or opt-out option, which allows the respondent to choose not to buy either produce one or produce two, was included in the choice experiment. An opt-out will make the choice decision more realistic thus resulting in better predictions of market penetration (Haaijer, Kamakura and Wedel, 2001; Hensher et al., 2005). Respondents will choose the opt-out option when either product 1 or product 2 is not attractive. As well, if two alternatives are equally attractive to the respondent, respondents will choose the opt-out option. According to Haaijer, Kamakura and Wedel et al., (2001), respondents preferences for the 'nochoice' alternative increases when two alternatives are equally attractive to the respondent. This may be because people have the tendency to avoid difficult choices (Tsang, 2014). In this case, an opt-out option may lead to biased estimations results in the coefficients of the interested attributes. However, if an opt-out option is not included in the choice experiment, respondents will be 35

43 forced to choose product 1 or product 2 even though they do not like either products or do not know how to value either products. In this forced situation, estimation results for food attributes will have bias. The results from choosing the 'no-choice' alternative are an indication for the choice analyst as to the overall performance of the selected attributes (Haaijer, Kamakura and Wedel, 2001; Hensher et al., 2005; and Tsang, 2014). Therefore, an opt-out option was included in the choice experiment in this thesis Survey Design The survey was created by Tsang (2014) and distributed online through a third party company: IPSOS. The surveys have five different versions which is related to five different food products: red tomatoes, gala apples, pork tenderloin, whole wheat bread and cheddar cheese. There were 2000 completed survey. The surveys can be divided into five main sections: (1) questions which are related to screening of respondents; (2) questions which are related to respondents knowledge and perception of organic foods; (3) questions which are related to respondents knowledge and perception of locally processed foods; (4) questions which are related to the choice experiment; and (5) questions which are related to respondents socio-demographic characteristics. The first section of the survey was designed to screen out respondents that were not in our sample frame. For example, respondents who were under 18 years old may not have clear opinion related to the purchase processed food, so they were not in our sample frame. The relative population size of Nunavut and Yukon are small and negligible, so respondents who were from these two territories were 36

44 not in our sample frame. Respondents who did not share the responsibility for grocery shopping for their household were also excluded. In the second section of survey, there were 14 statements related to respondents knowledge and perceptions on organic foods. These statements identified common psychometric attributes of organic food and respondents were asked to indicate their level of agreement to these 14 statements. This section was designed to measure the respondents' knowledge on the organic farm practices; production standards; and elicit their perception on organic foods. In order to ensure respondents take care in analyzing each statement, some statements were negative statements. The last part of section two takes the food value scale developed by Lusk (2011) and requires the respondent to allocate 100 points to the 12 "food values" they deemed most important for the a product to be organic. This allocation questions allow the consumers to express what they believe to be relatively more important when purchasing food that is organic (Tsang, 2014). Similar to the second section of survey, there were 12 statements related to respondents knowledge and perceptions of local food in the third section. These statements identified common psychometric attributes of local food and respondents were asked to indicate their level of agreement with each 12 statements. This section was designed to measure the respondents' perceptions of the local farm practices; production standards; and elicit their perception on local foods. Negative statements also were provided in the third section in order to motivate unbiased results. 37

45 In the fourth section, questions related to respondents choice experiment were provided. In order to provide some context prior for respondents to answering any of the choice questions, a brief descriptive definition of the attributes was provided. Besides that, in order to limit the order-effects, the order of the choice questions were randomized. In the last section, questions which are related to respondents sociodemographic were provided. These question included respondents gender, age, income, education and household size and so on. These socio-demographic variables help identify if the survey responses is representative of the Canadian population. 4.3 Empirical Framework The Random Utility Model will be used as the empirical model in this thesis. This section will extend the Random Utility Model. As chapter 3 mentioned, there are n consumers to choose type J of processed food. Assume U ij is the ith consumer's utility obtained from the selection of processed food of type j. Therefore, U ij can be represented as follows: U ij = V ij + ε ij (4.1) Where V ij is the observed part of ith consumer's utility. ε ij is the unobserved part of ith consumer's utility. i = 1, 2 n; j = 1, 2 J The probability of consumer i choosing j over q can be represented as follows: 38

46 P ij = Prob (U ij U iq ) = Prob (ε iq ε ij < V ij V iq ) q j (4.2) This equation (4.2) is called a random utility model (RUM). The distribution of the unobserved component ε ij must be defined in order to operate this model. As mentioned in Chapter 3, there will exist a distribution of the random unobserved sources of utility if the choice analyst surveys a representative portion of the population to derive amount of utility across the sampled population. Prior to discussing what functional form this distribution may take, it is important to state two basic assumptions. The first assumption is that the random, unobserved utility component from each individual must be located on some unknown distribution and be randomly allocated to each sampled individual (Louviere, Hensher and Swait, 2000; Swait, Adamowicz and Bueren, 2004; Hensher et al., 2005; Louviere, Flynn and Carson, 2010). The second assumption is the unobserved component is independently and identically distributed (IID), which implies that each alternative holds their own unobservable utility component that is located on some unknown distribution (Louviere, Hensher and Swait, 2000; Swait, Adamowicz and Bueren, 2004; Hensher et al., 2005; Louviere, Flynn and Carson, 2010). Furthermore, the random unobserved utility component is assumed to be independent and identically distributed with no cross-correlated terms (Hensher et al., 2005; Swait, Adamowicz and Bueren, 2004; Louviere et al., 2010; Louviere, Hensher and Swait., 2000). Under these specific assumptions, choice analysts are able to estimate the probabilities of choice outcomes based on the surveyed data. 39

47 It is important to identify key product attributes for evaluating individuals preference. The set of attributes that are observed in the systematic component of utility V ij can be presented as a linear and additive form of observed attributes for alternative. For example, if individual n chooses attribute j, then the systematic components of utility can be expressed as: V nj = β 0 x 0j + β 1 x 1j + β 2 x 1j + β 3 x 1j + + β i x ij Therefore, the total utility of individual n gain from choosing attribute j can be expressed as: U nj = β 0 x 0j + β 1 x 1j + β 2 x 2j + β 3 x 3j + + β i x ij + ε nj The total utility of individual n gain from choosing attribute j can be expressed using the attributes that considered here, as: U nj = β 0 Price nj + β 1 Distance nj + β 2 Cert n j + β 3 NonCertl nj + β 4 Conver nj + β 5 Farm nj + β 6 Indepen nj + β 7 Provin nj + β 8 Nation nj + ε nj Where: ε nj is the unobserved part of utility; Price nj is price of processed food; Distance nj is total processed food miles direct from producers to consumers ; Cert n j is certified organic processed food; NonCertl nj is non-certified organic processed food; Conver nj is conventional processed food; Farm nj is consumers purchase processed food from farm-direct; 40

48 Indepen nj is consumers purchase processed food from independent grocery stores; Provin nj is consumers purchase processed food from provincial-wide supermarkets; Nation nj is consumers purchase processed food from national-wide supermarkets; In order to address the issue of collinearity, the variables conventionally produced and purchased from national-wide supermarkets was chosen as the base alternatives and dropped from the regression. As well, effects coding is used in this thesis. Therefore, the final total utility of individual n gain from choosing attribute j can be expressed using the attributes that considered here, as: U nj = β 0 Price nj + β 1 Distance nj + β 2 NonCert nj + β 3 Cert nj + β 4 Farm nj + β 5 Indepen nj + β 6 Provin nj + ε nj Where: ε nj is the unobserved part of utility; Price nj is price of processed food (continuous variable); Distance nj is total processed food miles direct from producers to consumers (continuous variable); Cert n j is certified organic processed food (dummy variables; 1 if yes, -1 if conventional processed produced", 0 otherwise); NonCertl nj is non-certified organic processed food (dummy variables; 1 if yes, - 1 if conventional processed produced", 0 otherwise); 41

49 Farm nj is consumers purchase processed food from farm-direct (dummy variables; 1 if yes, -1 if consumers purchase processed food from national-wide supermarkets ", 0 otherwise); Indepen nj is consumers purchase processed food from independent grocery stores (dummy variables; 1 if yes, -1 if consumers purchase processed food from national-wide supermarkets ", 0 otherwise); Provin nj is consumers purchase processed food from provincial-wide supermarkets (dummy variables; 1 if yes, -1 if consumers purchase processed food from national-wide supermarkets ", 0 otherwise); 4.4 Statistical Model Three logit models are widely used to estimate consumers preference of different product or product attributes. These three logit models are as follows: the conditional logit model (CL), the multinomial logit model (MNL) and the mixed logit model (ML). The conditional logit model will be used to estimate consumer preference for buying proceed food. The conditional logit model is similar to the multinomial logit model. Both require two assumptions of the unobserved term. The first assumption is that the unobserved component ε ij is independent and identically distributed with a type I extreme value distribution. The second assumption is that the unobserved component ε ij must be independent of irrelevant alternatives (IIA). Besides that, both CL and MNL assume that individuals preferences are homogeneous. However, this assumption is not realistic assumptions in most cases. Although the 42

50 CL is similar to the MNL, the conditional logit model is more appropriate than the multinomial logit model in this thesis. The difference between the CL and the MNL is that using difference explanatory variables to estimate individuals preference. The MNL uses the individual s characteristics (i.e. socio-demographic attributes) as explanatory variable, while the CL uses alternatives attributes as explanatory variable. More specifically, the MNL focuses on the individual as the unit of analysis while the CL focuses on the alternatives as unit of analysis. In this thesis, we focus on the product attributes, so the attributes of the alternatives are used as explanatory variables to explain consumers choice outcomes. Therefore, the conditional logit model is more appropriate than the multinomial logit model in this thesis. The mixed logit model (ML) is more advanced model with increasing use when analyzing consumer choice outcomes. The most important difference between the CL and the ML is the assumption of the unobserved component ε ij. The conditional logit model requires the IIA property and assumes preference homogeneity which are not realistic assumptions in most cases (Hensher, Rose, and Greene, 2005). The mixed logit model does not need to require the IIA property and it captures preference heterogeneity, so the mixed logit model may be more appropriate method for estimating WTP. However, individual preference heterogeneity is not the focus of this study. Rather, the study is more concerned with the marginal WTP for processed food attributes. Moreover, one would also have to identify the variables in the mixed logit to be treated as random; in this respect, use of the CL model could be view as an intermediate step in this respect. 43

51 Compared to the mixed logit model, the conditional logit model is a straight forward and easy way to estimate the marginal WTP for processed food attributes. For the above reasons, conditional logit model is adopted in this study The conditional logit model ( CL) In this paper, the unobservable random component ε nj is assumed to be distributed as a type I extreme value (McFadden, 1974; Hoffman and Duncan, 1988): f (ε nj ) = P(ε i ε ) = e e ε nj Then the conditional logit model takes on the following expression if and only if the J alternatives are independent and identically distributed with the type I extreme value distribution for the nth individual selecting the jth alternative: P (y nj = j x nj ) = e V nj J e V nj j = eβ nx j J e β nx j j Where y nj is the value when alternative j is chosen by the nth individual; x nj is a column vector of explanatory variables Estimating the Willingness to Pay Willingness to pay can be explain by dividing the estimated coefficient of attribute j by the estimated coefficient of price: WTP j = β j β p 44

52 Where, β p is the estimated coefficient for the price of the alternative; β j is the estimated coefficient for attribute j. 4.5 Summary In this chapter, the choice experiment, survey design and empirical model were introduced. The survey can be divided into five main sections: (1) questions which are related to screening of respondents; (2) questions which are related to respondents knowledge and perception of organic foods; (3) questions which are related to respondents knowledge and perception of locally processed foods; (4) questions which are related to the choice experiment; and (5) questions which are related to respondents socio-demographic characteristics. The choice experiment had four attributes groups: production system, distribution channel, food travelled distance and price. In the empirical model part, the random utility framework, the conditional logit model and the willingness to pay framework were introduced. 45

53 CHAPTER 5 EMPRICAL RESULTS 5.1 Introduction The results from the analysis of the data survey and the choice experiment will be presented in this chapter. In the first section, the survey representativeness is discussed, with a focus on socio-demographic variables as a gauge of representativeness. In the second section, the factors that consumers consider when they purchase organically and/or locally produced foods will be presented and discussed. In the next section, conditional logit estimation results from the choice experiment will be presented and discussed. The final section includes a brief summary of the results. 5.2 Survey Representativeness In this section, a summary of the socio-demographic variables will be presented and compared with Census data from the Canadian population Distribution of the Survey The survey and the choice experiment was conducted on the internet from March 2013 to April 2013 by IPSOS. Respondents were randomly assigned to one version of the survey until the quota for each product's survey was met. Note that this study focused its investigation on the processed food products: pork tenderloin, whole grain bread and cheddar cheese. Each products survey had a quota of 400 responses. Across all food products, a total of 2000 complete survey 46

54 were collected after dropping all observations that were screened out, abandoned, and or incomplete Comparing the Survey Sample to the Canadian Population The socio-demographic characteristics of the full survey and the sub sample for the pork tenderloin choice experiment, the whole grain bread choice experiment, and the cheddar cheese choice experiment are compared with the general Canadian population (based on the 2011 Census of Canada) in Table 5.1. The proportion of males were under 21 percent in all four samples, while the proportion of females respondents were all above 80 percent. The low response rate from males could be due to the high likelihood that the female was responsible for most of the primary grocery shopping. This results is similar to previous studies which are related to organic or local food preferences (Onozaka et al., 2010; Costanigro et al., 2011; Cranfield et al., 2011). The distribution of regions in all four samples is almost same as that of the Canadian census, as expected given regional sampling quotas. A larger proportion of the respondents were located in the higher population density provinces of Ontario, British Columbia and Quebec. Descriptive results on the age groups in the four samples shows that the youngest aged group were under sampled by 8 percentage points compared with the Canadian census values, while the age group about three percentage point below than the Canadian census values. 47

55 Table 5.1: Socio-Demographic Characteristics of the Survey Respondents Socio- Demographics Full Sample (%) Pork Tenderlo in (%) Whole Grain Bread (%) Gender Cheddar Cheese (%) Canadian Census (%) Male Female Region AB BC MN/SK ON QC Atlantic Age Group Less than high school High school graduate Education College graduate Undergraduate degree Graduate degree Household Income 48

56 Less than $10, $10,000-$19, $20,000-$29, $30,000-$39, $40,000-$49, $50,000-$59, $60,000-$69, $70,000-$79, $80,000-$89, $90,000-$99, Prefer not to answer The average age groups aged group in the four samples were slightly higher than the Canadian census values. This observation of a higher response rate from the age group is often observed in other choice experiments involving organic and local foods as well (Yue and Tong, 2009; Costanigro et al. 2011, and Lusk 2011). The education level for all four samples broadly resembles the Canadian census, with the exception of the tail ends of the distribution. Those with less than a high school education were under the Canadian average, while those with a graduate degree were almost three to four percentage points higher than the Canadian average. The proportion of respondents with an undergraduate degree were about eleven to thirteen percentage points higher than the Canadian census. This observation of a higher average education is not unusual for an internet 49

57 based survey. Shih and Fan (2009) suggested that educated respondents were more responsive to internet based surveys. The distribution of the household incomes for all four samples were slightly different to those of the average Canadian population. More specifically, the proportion of the household incomes range from $40,000 to $59,999 and $90,000 to $99,999 are higher than those of the Canadian population, while income ranges of those in the sample are lower than those of the average Canadian population. This observation of different average household incomes may be due to the fact that some respondents preferred not to report their household income. Note that within the 2000 completed surveys, almost 18 percent of the respondents preferred not to report their household income. 5.3 Influences on Organic and Local Food Choices In this section, key factors for respondents what they consider purchasing organic and/or locally produced foods are presented and discussed. First, a summary of the distribution channel in which the respondents purchase their grocery stores is presented. Information on distribution channel choice helps to identify which channels are more relevant when purchasing conventionally, organically, or locally produced food products. The next section will address key factors respondents think about when purchasing organic and/or locally produced foods Distribution Channel Respondents were asked to indicate which store types they have visited to purchase conventionally produced foods, organic and locally produced foods. The 50

58 nine store types are: large chain grocery store (for example Loblaw's, Zhers, Dominion, Sobey's, Safeway, Metro, and Maxi etc.); discounted grocery stores (for example Food Basics, No Frills, and Price Choppers etc.); independent grocery stores (for example Longo's, Farm Boy, Highland Farms, Bruno's, Michael-Angelo's, and Dennigers etc.); ethnic grocery stores; health food stores; mass merchandisers or discount department stores (for example Zellers, and Walmart etc.); warehouse club stores (for example Costco, and Sam's Club); butcher shop; and farmers market (Tsang, 2014). As shown in Table 5.2, the majority of respondents (87 percent) visit large chain grocery stores to purchase conventionally produced foods, followed by mass merchandisers, discount departments and warehouse club stores at 59 percent, 49 percent and 48 percent respectively. The sample of respondents that do purchase food labelled as organic or local was significantly less than those who purchase conventionally produced foods (Tsang, 2014). More specifically, the majority of respondents (31 percent) visit large chain grocery stores to purchase organically produced foods, followed by farmers market and health food stores at 18 percent and 17 percent respectively. Different results were observed for locally produced food. More specifically, the majority of respondents (45 percent) visit farmers market to purchase locally produced foods, followed by large chain grocery stores, butcher shop and discounted grocery stores at 40 percent, 17 percent and 15 percent respectively. Table 5.2: Distribution Channels Visited by the Respondents to Purchase Food Labelled as Conventional, Organic, and Local Distribution Conventional Organic Foods Locally Produced 51

59 Channel Foods Foods Large chain grocery stores Discounted grocery stores Independent grocery stores Ethnic grocery stores No (%) Yes (%) No (%) Yes (%) No (%) Yes (%) Health food stores Mass merchandiser Warehouse club store Butcher shop Farmers market Food Values and Responses to Psychographic Questions Respondents were asked a variety of psychographic questions related to their perception, knowledge, opinions, and attitudes towards purchasing organically or locally produced food. The decision of consumers to purchase food that is organic and/or locally produced is significantly influenced by the individual's food values (Lusk, 2011). Therefore, Lusk (2011) divided individual's food values into twelve food attributes. These twelve food attributes were presented to respondents and they were asked to allocate 100 points amongst them, where more points would be assigned to the food attribute that was more important to the respondent. Respondents were asked to do this point assignment in two different contexts. The first was in the context of considering the purchase of an organically produced 52

60 food and the second was in the context of considering the purchase of a locally produced food. Table 5.3 reports the average score for each of the eleven factors in the two different contexts for four samples (full survey; pork tenderloin; whole grain bread and cheddar cheese). Across the full sample and three sub-samples, the three factors that are consider to be the most important were: price; taste; and freshness. The three factors consider to be the least important were: tradition, convenience and fairness. Table 5.3: Food Attributes Consumers Believed to be Important for Purchasing Organic and Locally Produced Foods Organically Produced Survey Sample Locally Produced Variable Mean Std. Dev. Mean Std. Dev. Freshness Taste Price Safety Convenience Nutritional Content Tradition Origin Fairness Appearance Environmental Impact Naturalness Organically Produced Pork Tenderloin Sample Locally Produced Variable Mean Std. Dev. Mean Std. Dev. Freshness Taste

61 Price Safety Convenience Nutritional Content Tradition Origin Fairness Appearance Environmental Impact Naturalness Whole Grain Bread Sample Organically Produced Locally Produced Variable Mean Std. Dev. Mean Std. Dev. Freshness Taste Price Safety Convenience Nutritional Content Tradition Origin Fairness Appearance Environmental Impact Naturalness Cheddar Cheese Sample Organically Produced Locally Produced Variable Mean Std. Dev. Mean Std. Dev. Freshness Taste Price

62 Safety Convenience Nutritional Content Tradition Origin Fairness Appearance Environmental Impact Naturalness Looking at the top three important food attributes (price, taste and freshness) and three least important food attributes (tradition, convenience and fairness), the means of freshness and convenience attributes in organically produced foods is less than the means of freshness and convenience attributes in locally produced foods. Difference in the means for the other two most important food attributes (price and taste) and two least important food attributes (tradition and fairness) were negligible. 5.4 Estimation Results of Conditional Logit Model The estimation results from the conditional logit model for whole grain bread, pork tenderloin and cheddar cheese choice experiments are presented and discussed in this section. Recall that three choice experiments have a no choice or opt-out option. In order to explain the opt-out option, Haaijer et al (2001) and Birol et al (2006) suggested that an alternative specific constant (ASC) should be included in the model. The ASC is specified as 0 for when the opt-out option is chosen and 1 for when the non- opt-out option is chosen (Birol, Karousakis, 55

63 and Koundouri, 2006). In this thesis, price and distance were treated as continuous variables, while all other variable were effects coded. The models were specified so that the probability of choosing a particular pork tenderloin, whole grain bread or cheddar cheese is a function of the attribute levels for that product and the ASC Estimation Coefficients Results of Conditional Logit Model Table 5.4, Table 5.5 and Table 5.6 represent the estimated coefficients and the level of significance for whole grain bread, pork tenderloin and cheddar cheese choice experiments. The variables conventionally produced and purchased from national-wide supermarkets was chosen as the base alternatives and dropped from the regression in order to address the issue of the dummy variable trap. Table 5.4 represents the estimated coefficients and the level of significance for whole grain bread choice experiment. The overall goodness of the model fit (Pseudo R 2 ) for whole grain bread is 0.25 which means 25 percent of the total variability can be explained with the current conditional logit model. A likelihood ratio test (LR Chi2 (8)) is performed to test the null hypothesis that all the coefficients in model are equal to zero. The p-value from the LR test is less than which means the coefficients are not jointly equal to zero in the current conditional logit model. Six coefficients are significant at the 95 percent level; these are coefficients on price, food miles, certified organic, purchased from independent grocery stores, purchased from provincial-wide supermarkets and the ASC, while coefficients on non-certified organic and purchased through farm direct are not significant. Insignificance of the coefficient on the farm direct 56

64 variable means that the choice of farm direct does not affect the likelihood of consumers to purchase whole grain bread. Coefficients on certified organic, purchased from a provincial-wide supermarkets and the ASC are positive, while coefficients on price and food miles are negative. The positive sign on certified organic implies that consumers prefer purchasing certified organic whole grain bread to purchasing conventional whole grain bread. Furthermore, non-certified organic is not significant. This implies that the likelihood of consumers to purchase whole grain bread is not different between non-certified organic food and conventional food. The positive sign for purchased from provincial-wide supermarkets means that consumers were more likely to purchase whole grain bread in provincial-wide supermarkets, while the negative sign for purchased from independent grocery stores means that consumers were less likely to choose whole grain bread in independent grocery stores. The positive sign for the ASC implies a positive impact on consumers utility when they choose the purchase alternative. The negative sign for price implies that consumers are less likely to purchase whole grain bread when its price increases. The negative sign for food miles implies that consumers are less likely to purchase whole grain bread when it travels longer distances. Table 5.4: Conditional Logit Estimations of Whole Grain Bread Choice Experiment Block Variables (y=choice) Coefficient p z Price *** Food miles (per 1km) *** ASC *** Non-certified organic

65 Certified organic *** Purchase from farm direct Purchase from independent grocery stores *** Purchase from provincial-wide supermarket *** N 9576 Log likelihood Pseudo R LR chi Prob > Chi *** significant at 1%, ** significant at 5%, * significant at 10% Table 5.5 represents the estimated coefficients and the level of significance for pork tenderloin choice experiment. The overall goodness of the model fit (Pseudo R 2 ) for pork tenderloin is 0.25 which means 25 percent of the total variability can be explained with the current conditional logit model. A likelihood ratio test (LR Chi2 (8)) is performed to test the null hypothesis that all the coefficients in model are equal to zero. The p-value from the LR test is less than which means the coefficients are not jointly equal to zero in the current conditional logit model. Six coefficients are significant at the 95 percent level; these are coefficient on price, food miles, certified organic, purchased from independent grocery stores, purchased from provincial-wide supermarkets and the ASC, while coefficients on non-certified organic and purchased through farm direct are not significant. Insignificance of the coefficient on the farm direct variable means that the choice of farm direct does not affect the likelihood of 58

66 consumers to purchase pork tenderloin. Coefficients on certified organic, purchased from a provincial-wide supermarkets and the ASC are positive, while coefficients on price and food miles are negative. The positive sign on certified organic implies that consumers prefer purchasing certified organic pork tenderloin to purchasing conventional pork tenderloin. Furthermore, non-certified organic is not significant. This implies that the likelihood of consumers to purchase pork tenderloin is not different between non-certified organic food and conventional food. The positive sign for purchased from provincial-wide supermarkets means that consumers were more likely to purchase pork tenderloin in provincial-wide supermarkets, while the negative sign for purchased from independent grocery stores means that consumers were less likely to choose pork tenderloin in independent grocery stores. The positive sign for the ASC implies a positive impact on consumers utility when they choose the purchase alternative. The negative sign for price implies that consumers are less likely to purchase pork tenderloin when its price increases. The negative sign for food miles implies that consumers are less likely to purchase pork tenderloin when it travels longer distances. Table 5.5: Conditional Logit Estimations of Pork Tenderloin Choice Experiment Block Variables (y=choice) Coefficient p z Price *** Food miles (per 1km) *** ASC *** Non-certified organic Certified organic ***

67 Purchase from farm direct Purchase from independent grocery stores *** Purchase from provincial-wide supermarket *** N 9576 Log likelihood Pseudo R LR chi Prob > Chi *** significant at 1%, ** significant at 5%, * significant at 10% Table 5.6 represents the estimated coefficients and the level of significance for cheddar cheese choice experiment. The overall goodness of the model fit (Pseudo R 2 ) for cheddar cheese is 0.25 which means 25 percent of the total variability can be explained with the current conditional logit model. A likelihood ratio test (LR Chi2 (8)) is performed to test the null hypothesis that all the coefficients in model are equal to zero. The p-value from the LR test is less than which means the coefficients are not jointly equal to zero in the current conditional logit model. Six coefficients are significant at the 95 percent level; these are coefficient on price, food miles, certified organic, purchased from independent grocery stores, purchased from provincial-wide supermarkets and the ASC, while coefficients on non-certified organic and purchased from the farm direct are not significant. Insignificance of the coefficient on the farm direct variable means that the choice of farm direct does not affect the likelihood of consumers to purchase cheddar cheese. Coefficients on certified organic, 60

68 purchased from a provincial-wide supermarkets and the ASC are positive, while coefficients on price and food miles are negative. The positive sign on certified organic implies that consumers prefer purchasing certified organic cheddar cheese to purchasing conventional cheddar cheese. Furthermore, non-certified organic is not significant. This implies that the likelihood of consumers to purchase cheddar cheese is not different between non-certified organic food and conventional. The positive sign for purchased from provincial-wide supermarkets means that consumers were more likely to purchase cheddar cheese in provincial-wide supermarkets, while the negative sign for purchased from independent grocery stores means that consumers were less likely to choose cheddar cheese in independent grocery stores. The positive sign for the ASC implies a positive impact on consumers utility when they choose the purchase alternative. The negative sign for price implies that consumers are less likely to purchase cheddar cheese when its price increases. The negative sign for food miles implies that consumers are less likely to purchase cheddar cheese when it travels longer distances. Table 5.6: Conditional Logit Estimations of Cheddar Cheese Choice Experiment Block Variables (y=choice) Coefficient p z Price *** Food miles (per 1km) *** ASC *** Non-certified organic Certified organic *** Purchase from farm direct

69 Purchase from independent grocery stores *** Purchase from provincial-wide supermarket *** N 9576 Log likelihood Pseudo R LR chi Prob > Chi *** significant at 1%, ** significant at 5%, * significant at 10% Across products, whole grain bread is the most sensitive to price, while cheddar cheese is the least sensitive to price. The variable food miles had roughly the same negative impact on whole grain bread as it does for pork tenderloin and cheddar cheese. The negative coefficient on distance implies that consumers are more likely to purchase locally produced food. Consumers are more likely to purchase these three products in provincial-wide supermarkets. There are two possible reasons. First, the premium price for these three products sold in the provincial-wide supermarket may be lower than the same products sold in the farmer markets and the independent grocery store. Second, these three products could have better appearance and quality in the provincial-wide supermarket. To explore differences or similarities across the estimated coefficients, a number of tests were conducted to test for parameter equality for certified organic versus not-certified organic, and across different combinations of the estimated distribution channel coefficients. Results from these tests are shown in Table 5.7. For all three products, the coefficient for certified organic was not significant 62

70 different from the coefficient for non-certified organic. As well, the difference between the different pairs of distribution channel coefficients were all different in all three product models. Such results reinforce that differences reported above are statistically valid. Table 5.7 Post Estimation of Different Food Attributes Coefficient Prob> Chi2 Certified Vs Noncertified Provincial Vs Independent Provincial Vs Farm direct Farm direct Vs Independent Pork Bread Cheese Estimation Results of Willingness to Pay Krinsky and Robb s (1986) parametric bootstrap method will be used to estimate willingness to pay (WTP) for whole grain bread, pork tenderloin and cheddar cheese in this section. Table 5.7, Table 5.8 and Table 5.9 represents the estimated WTP and the 95 percent confidence interval for whole grain bread, pork tenderloin and cheddar cheese. Similar to results for the whole grain bread model, WTP for purchased from a farm direct and non-certified organic are not significant, while there are significant WTP values for food miles, certified organic, purchased from independent grocery stores, and purchased from provincial-wide supermarkets. According to Table 5.8, for whole grain bread, purchased from provincial-wide 63

71 supermarkets has the highest premium, while purchased from independent grocery stores has the lowest premium. Positive WTP for purchased from provincial-wide supermarkets suggests that respondents are willing to pay for whole grain bread in provincial-wide supermarkets. Positive WTP for certified organic suggests that respondents are willing to pay a 9.5% price premium 1 for certified organic whole grain bread. Non-significance of WTP for non-certified organic suggests that respondents are not willing to pay any price premium for non-certified organic whole grain bread. In this case, food producers and food supply chain members have to consider whether to use the third-party to verify their organic food products. If they want to earn more profit by using organic production system, they have to use the third-party to verify their organic food product. Negative WTP for food miles suggests that respondents dislike whole grain bread that has travelled a long distance, which also means they are WTP for whole grain bread that is produced nearby. More specifically, respondents are willingness to pay a -0.75% price premium per increased 10 kilometers food miles for whole grain bread. Negative WTP for purchased from independent grocery stores suggests that respondents are not willing to pay for whole grain bread in independent grocery stores. Non-significance of WTP for purchased from a farm direct suggests that respondents are not willing to pay any price premium for whole grain bread from a farm direct. Compared to other distribution channels, farm direct is less convenient. If respondents want to buy whole grain bread from farm direct, they may face some problems which are restrictive in the 1 This is a percent price premium relative to base price. 64

72 location, travelling, and availability on certain days. Therefore, respondents may change their purchase decision due to inconvenience of farm direct. Table 5.8: Willingness-to-pay for Whole Grain Bread Choice Experiment by Using Conditional Logit Model Item WTP Lower Bound Upper Bound Food miles (1km) Non-certified organic Certified organic Purchase from farm direct Purchase from independent grocery stores ** ** ** Purchase from provincialwide supermarkets ** *** significant at 1%, ** significant at 5%, * significant at 10% Results for consumer WTP for pork tenderloin are similar to whole grain bread. According to Table 5.9, WTP for food miles, certified organic, purchased from independent grocery stores, and purchased from provincial-wide supermarkets are significant, while there are non-significant WTP value for purchased from a farm direct and non-certified organic. Positive WTP for certified organic suggests that respondents are willing to pay a 9.43% price premium for certified organic pork tenderloin. Non-significance of WTP for noncertified organic suggests that respondents are not willing to pay any price premium for non-certified organic pork tenderloin. This result suggests that food producers and food supply chain members have to use the third-party to verify their organic pork tenderloin in order to earn more profit by using organic production system. Negative WTP for food miles suggests that respondents are 65

73 less likely to purchase pork tenderloin that has travelled a long distance, which also means they are willing-to-pay for pork tenderloin that is produced nearby. More specifically, respondents are willing to pay a -0.75% price premium per increased 10 kilometers food miles for pork tenderloin. According to Table 5.9, for pork tenderloin, purchased from provincial-wide supermarkets has the highest premium, while purchased from independent grocery stores has the lowest premium. Positive WTP for purchased from provincial-wide supermarkets suggests that respondents are willing to pay for pork tenderloin in provincial-wide supermarkets. Negative WTP for purchased from independent grocery stores suggests that respondents are not willing to pay for pork tenderloin in independent grocery stores. Non-significance of WTP for purchased from a farm direct suggests that respondents are not willing to pay any price premium for pork tenderloin from a farm direct. Table 5.9: Willingness-to-pay for Pork Tenderloin Choice Experiment by Using Conditional Logit Model Item WTP Lower Bound Upper Bound Food miles(1km) Non-certified organic Certified organic Purchase from farm direct Purchase from independent grocery stores ** ** ** Purchase from provincialwide supermarkets ** *** significant at 1%, ** significant at 5%, * significant at 10% 66

74 Results of consumer WTP for cheddar cheese are similar to other two processed food. We can see form Table 5.10, purchased from a farm direct and non-certified organic have non-significant WTP value, while WTP for food miles, certified organic, purchased from independent grocery stores, and purchased from provincial-wide supermarkets are significant. Negative WTP for food miles suggests that respondents are less likely to purchase cheddar cheese that has travelled a long distance, which also means they are willing-to-pay for locally produced cheddar cheese. More specifically, respondents are willingness to pay a % price premium per increased 10 kilometers food miles for cheddar cheese. Positive WTP for certified organic suggests that respondents are willing to pay a 9.44% price premium for certified organic cheddar cheese. Nonsignificance of WTP for non-certified organic suggests that respondents are not willing to pay any price premium for non-certified organic cheddar cheese. This result suggests that food producers and food supply chain members have to use the third-party to verify their organic cheddar cheese unless they do not want to earn more profit by using organic production system. Table 5.10 shows that purchased from provincial-wide supermarkets has the highest premium, while purchased from independent grocery stores has the lowest premium for cheddar cheese. Positive WTP for purchased from provincial-wide supermarkets suggests that respondents are willing to pay for cheddar cheese in provincial-wide supermarkets. Negative WTP for purchased from independent grocery stores suggests that respondents are not willing to pay for cheddar cheese in independent grocery stores. Non-significance of WTP for purchased from a farm direct 67

75 suggests that respondents are not willing to pay any price premium for cheddar cheese from a farm direct. Table 5.10: Willingness-to-pay for Cheddar Cheese Choice Experiment by Using Conditional Logit Model Item WTP Lower Bound Upper Bound Food miles (1km) Non-certified organic Certified organic Purchase from farm direct Purchase from independent grocery stores ** ** ** Purchase from provincialwide supermarkets ** *** significant at 1%, ** significant at 5%, * significant at 10% 5.5 Discussion As mentioned above, all three processed foods have negative WTP for food miles. Cheddar cheese has the lowest WTP for food miles, while whole grain bread has the highest WTP for food miles. However, cheddar cheese has the highest base price and whole grain bread has the lowest base price. Therefore, these three processed foods have the very similar percentage price premiums for food miles. This implies that respondents dislike processed foods that have travelled a long distance, which also means they are WTP for processed foods that are produced nearby. In other words, respondents are more likely to purchase locally produced processed food. This model may only apply to when food miles are equal to or less than 1000 KM, because the food price value is negative when food miles is greater than 1333 KM. 68

76 Negative WTP for purchased from independent grocery stores suggests that respondents are less likely to purchase three processed foods in independent grocery stores than national-wide supermarkets. The possible reasons are as following: (1) Processed food products are always charged a higher premium when they are sold in independent grocery stores than national- wide supermarkets. (2) National-wide supermarkets are more convenient than independent grocery stores may be another reason. National-wide supermarkets sell more variety of food products than independent grocery stores, so consumers may have to go to many independent grocery stores to purchase food products that consumers only purchase one time in a national-wide supermarket. (3) Due to store side and management technology, national-wide supermarkets are seem to be cleaner and are perceived to have a higher degree of food safety than independent grocery stores. Compared to national-wide supermarkets, consumers may consider that the processed food product that is sold in independent grocery stores has less freshness and food safety. Using whole grain bread as an example, Figure 5.1 shows the linear relationship is between conventional whole grain bread and certified organic whole grain bread and food miles. The price of conventional whole grain bread produce at a location with no food miles is analyzed to 1. We can see from figure 5.1, the price premium for conventional whole grain bread and certified organic whole grain bread decreases when food miles increases. A price premium that respondents are willing to pay for certified organic whole grain bread price is 69

77 equal to 24% of conventional whole grain bread price. This amount of price premium can offset the negative price premium that whole grain bread travel 400 kilometers. Therefore, food producers and food supply chain members who do not want to sell their processed food in the locally area can produce certified organic processed food in order to offset the negative effect from food miles. Figure 5.1 The Linear Relationship is Between Conventional Whole Grain Bread and Certified Organic Whole Grain Bread and Food Miles Organic Bread Conventional Bread Food Miles (KM) Table 5.11 Willingness-To-Pay for Five Food Products Item Whole Grain Bread Pork Tenderloin Cheddar Cheese Red Tomatoes Gala Apples Food miles (10 km) ** (-0.75%) ** (-0.75%) ** (-0.757%) ** (-0.763%) ** (-0.587%) Noncertified organic (2.28%) (2.25%) (2.25%) ** (7.04%) (-0.55%) 70

78 Certified organic Purchased from farmers direct Purchased from independe nt grocers Purchased from provincial chains ** (9.53%) (2.73%) ** (-23.34%) ** (25.15%) ** (9.43%) (2.72%) ** (-23.25%) ** (24.94%) ** (9.44%) (2.72%) ** (-23.27%) ** (24.96%) ** (10.66%) (3.6%) ** (-9.48%) ** (14.8%) *** significant at 1%, ** significant at 5%, * significant at 10% (4.81%) (3.52%) (2.01%) (4.65%) Table 5.11 shows consumers WTP for five food products. Red tomatoes and gala apples are fresh food groups, while whole wheat bread, and cheddar cheese are processed food groups. The WTP results for fresh food groups (Tsang, 2014) are different to processed food group, especially gala apples. The WTP for gala apples is different to other food products, because gala apples appearance is similar in different distribution channels and other food products are more perishable than gala apples under normal temperature environment. Red tomatoes has a significant and positive WTP for non-certified organic. This may because consumers more often purchase red tomatoes than processed food products from local markets. The magnitude of price premiums for red tomatoes are less than processed food products, this may because red tomatoes appearance is more similar than processed food products appearance in different distribution channels. 71

79 5.6 Summary Results from the analysis of survey data are presented and discussed in this chapter. As the results show, the three most important food attributes that consumers consider when they consider purchasing organic or locally produced processed food products are price, taste and freshness. Meanwhile, the three least important food attributes that consumers consider when they purchase organically or locally produced food products are tradition, convenience and fairness. According to the estimation results, price, food miles, certified organic and purchased in the provincial-wide supermarkets or independent grocery stores have an impact on the likelihood of consumers to purchase whole grain bread, pork tenderloin and cheddar cheese. Non-certified organic and purchased from farm direct do not affect the likelihood of consumers to purchase whole grain bread, pork tenderloin and cheddar cheese. Purchased from provincial-wide supermarkets has the highest premium, while purchased from independent grocery stores has the lowest premium amongst the three processed food. The results also show that food miles has a negative impact on three food products which means that respondents prefer locally produced food. This implies that respondents are more likely to purchase locally produced food. The results also show that whole grain bread is the most sensitive to price and cheddar cheese is the least sensitive to price changes. Respondents prefer certified organic processed foods to conventional processed foods. More specifically, respondents are willing to pay a premium for certified organic whole grain bread ($0.076/loaf), certified organic pork tenderloin ($0.8299/kg) and certified organic cheddar cheese ($0.3381/kg). Food producers and food supply chain members 72

80 have to use the third-party to verify their organic food product in order to earn more profit by using organic production system. Besides that, food producers and food supply chain members who do not want to sell their processed food in locally area can produce certified organic processed food in order to offset the negative effect from food miles. 73

81 CHAPTER 6 CONCLUTION 6.1 Introduction The first section of this chapter will review the research questions, purpose and objectives of the study. The second section will summarize the main finding of this study. The third section will present and discuss the implications for food producer and supply chain members. The limitation of this study will discussed in the fourth section. The final section will provide some suggestions for future research. 6.2 Research Problem With the fast development of modern transport, consumers are able to purchase foods that are produced in a place that is further away from their living area. Due to further food miles, the term local food has been defined in order to distinguish locally produced food from food produced in other location. In Canada, the Canadian Food Inspection Agency determined an official definition for local food : 1.food produced in the province or territory in which it is sold; 2. food sold across provincial borders within 50 km of the originating province or territory (CFIA, 2013). Currently, Ontario's legislature has passed a Local Food law - Bill 36. The purpose of Bill 36 is to foster successful local food economies, to increase the awareness of local food and diversity, and to encourage new markets for food. Local has become an important market for some and holds attractive prospects, especially for Ontario s food producers and supply chains 74

82 members. They have to know whether the value of local food attribute are enhancing their opportunities or not. In the meantime, organic food industries have continued and grown rapidly. For example, the total estimated retail sales of organic food was $ 2987 million in 2010 in Canada (AAFC, 2013). Food producers and supply chain members also want to capture more value in organic food market. Conventional food and organic food are two kinds of food production systems. Many food producers will say that their food product is organic, but they may not say their food product is certified organic. This is because to use a certified organic label, producers need to spend money to ask a third-party to verify. Therefore, food producers and supply chain members want to know whether consumers are willing to pay a premium for certified organic label and whether that premium is higher than the cost of achieving certification. Finally, food producers and supply chain members wants to know which distribution channel consumers are more willing to pay for locally and/or organically produced food. Therefore, the research questions in this study are as following: Firstly, which food product attributes (Local, organic, or distribution channel) are consumers willing to pay? Secondly, which food product attributes command a higher premium? In order to answer these research questions, this study undertook the following. First, literature review was used to identify factors that has impact on consumers decision to purchase locally and/or organically produced food products; understand how the attributes of organically produced food and locally produced food interact; and indicate the relationship between food products and 75

83 food miles. Second, a survey with choice experiment was designed based on the literature review. There were three choice experiment. One for each of the following foods: whole grain bread, pork tenderloin and cheddar cheese. The food attributes were divided into three main parts: (1) food miles: 10km, 50km, 100km and 1000km; (2) production system: conventional food, certified organic and noncertified organic; (3) distribution channel: farmer direct, independent grocery stores, provincial-wide supermarkets and nation-wide supermarkets. The choice experiment was embedded in an internet survey, which was disseminated by IPSOS. Third, after the data was collected, a conditional logit model was used to estimate the coefficients of each food attributes. Then, these coefficients of each food attributes were used to estimate the premiums that Canadian consumers are willing to pay for each food attributes. 6.3 Summary of Main Findings The three most important food attributes that consumers consider when they consider purchasing organic or locally produced processed food products were price, taste and freshness. Meanwhile, the three least important food attributes that consumers consider when they purchase organically or locally produced food products were tradition, convenience and fairness. Similar estimation results were obtained for all three processed food products. In the three models, price and distance had negative and significant coefficients, which implied that an increasing price and/or food miles will decrease the consumers likelihood to purchase these three food product. Certified 76

84 organic had a positive and significant sign, while non-certified organic was not significant. This implies that consumers prefer purchasing these three organic food products to purchasing three conventional food products while the likelihood of consumers to purchase three food products between non-certified organic food and conventional food are same. Regarding distribution channel, purchased from provincial-wide supermarkets had a positive significant sign, while purchased from independent grocery stores had a negative significant sign, and purchased from farmers markets is not significant. This means that consumers were more likely to purchase these three products in provincial-wide supermarkets than national-wide supermarkets; consumers were less likely to purchase these three products in independent grocery stores than national-wide supermarkets; and the likelihood of consumers to purchase three food products from farmers markets is same as the likelihood of consumers to purchase three food products from national-wide supermarkets. Estimation results were used to calculate consumers WTP for food attributes which included three choice experiments. Food miles had negative premiums for all three products, equal to -$ /km in whole grain bread, - $ /km in pork tenderloin and -$ /km in cheddar cheese, respectively. Whole grain bread is the most sensitive to price changes and cheddar cheese is the least sensitive to price changes due to food miles changes. This may be because whole grain bread is more perishable than cheddar cheese. Furthermore, premiums for certified organic food products were: $0.076/loaf (9.53% price premium) for whole grain bread, $0.8299/kg (9.43% price premium) 77

85 for pork tenderloin and $0.3381/kg (9.44% price premium) for cheddar cheese. Consumers will not pay any premiums for purchasing these three non-certified organic food products. Regarding distribution channel, consumers were the most likely to buy these three food product from provincial-wide supermarkets while consumers were the least likely to buy these three food product from independent grocery stores. According to the estimation results, purchased from farm direct did not affect the likelihood of consumers to purchase whole grain bread, pork tenderloin and cheddar cheese. Purchased from provincial-wide supermarkets had the highest WTP which was that respondents were willing to pay a 25% base price premium, while purchased from independent grocery stores had the lowest WTP which was that respondents were willing to pay a -23% base price premium for three processed food. 6.4 Implications for Food Producer and Supply Chain Members Negative WTP for food miles suggests that respondents dislike these three food products that has travelled a long distance, which also means they are WTP for these three food products that is produced nearby. This implies that the shorter the food miles, the higher premiums that consumers are likely to pay for these three food products. Therefore, food producer and food supply chain members should sell their food products locally if possible. Especially Ontario food producer and food supply chain members should catch the opportunity that Ontario government set Bill 36 in order to develop local food markets. 78

86 Positive and significant WTP for certified organic and non-significant WTP for non-certified organic implies that food producers and food supply chain members should consider using third-party certification of their production system, but only if the benefits exceed the costs of doing so. If the cost of achieving organic certification higher than the benefit of certified organic food attribute value, producers and food supply chain members should not use the third-party to verify their organic food product. The positive and significant WTP for certified organic suggests that food producers and food supply chain members who do not want to sell their processed food in locally area can produce certified organic processed food in order to offset the negative effect from food miles. The result of this study also suggested that food products and food supply chain members are better off by selling their food products in provincial-wide supermarkets and not selling or selling less their food product in independent grocery stores. This is because provincial-wide supermarkets have a highest premium and independent grocery stores have a lowest premium which consumers are likely to pay for these three food products. Non-significant WTP for farm direct implied that farm direct did not have an impact on respondents food purchase decision. This may be because farm direct is perceived to be less convenient. Respondents will be more likely to buy food product from food direct if farmers can provide some convenience measures. For example, farmers can provide home delivery services or set their roadside sale at convenient place. 79

87 6.5 Limitation of the Research The first limitation is the assumption of preference homogeneity that is used in the conditional logit model. It is possible that respondents preferences are heterogeneous, in which case as alterative estimation should be used. As well, this study did not account for the role of socio-demographic variables and choice. That relationship may help processed food to find the potential consumers, or important segments of consumers. Besides that, In this thesis, localness is defined by using food miles that is the distance from point of production to point of consumption at the home. However, there are other ways to define localness. For instance, size of carbon footprints and radius away from the home. Different definition of localness will cause different results. The second limitation is that this study only examined traditional distribution channels. Today, new distribution channels have developed very rapidly, for instance online distribution channels. The online distribution channel will influence the traditional distribution channel, for example, ebay or amazon.ca. Therefore, result from this study may differ if the survey included an online distribution channel option. This study also only used traditional processed. However, other food may have different results compared to these three food products. The third limitation is the survey price of three food products. The average food prices are designed based on the price of Guelph and the survey was distributed on the internet across Canada. Therefore, the survey price may not be fully representative across other provinces in Canada. Besides that, the attributes 80

88 of locally produced food are similar to the attributes of organically produced food. Therefore, it is not easy to differentiate the locally produced food and organically produced food. The non-significant WTP for non-certified organic implies that the likelihood of consumers to purchase these three processed food between noncertified organic food and conventional food are not different. However, this result may only apply to national-wide supermarkets and provincial-wide supermarkets, because non-certified organic food is not allowed to be sold in national-wide supermarkets and provincial-wide. The WTP for non-certified organic may be significant when consumers purchase food product from farmdirect. Some previous studies mentioned that many consumers who like to buy organic food do not care whether these organic food is certified organic or not in local distribution channel, especially for farm-direct. This is because supporting local farms is the most important reason for these consumers choosing organic food in local distribution channel. 6.6 Suggestions for Future Research Some limitations that are presented in the previous section may be solved in the future studies. First, respondent preferences are homogeneity is assumed in this thesis. However, consumer preferences for these three processed food products may be different to each individual. Therefore, future studies may use some models (e.g. the mixed logit model) that assume every individual has different preferences. As well, future studies may account for the role socio-demographic 81

89 variables and choice. New distribution channels have developed rapidly these years and they have already influenced traditional distribution channels. In the future studies, new distribution channels should be considered as important distribution channels in survey, as well as a region s specialties. 82

90 BIBLIOGRAPHY Adamowicz, W., J. Louviere, and J. Swait Introduction to Attribute- Based Stated Choice Methods. NOAA-National Oceanic Athmospheric Administration, Washington, USA. Agriculture and Agri-Food Canada (AAFC) Organic Production. (Accessed July 20, 2014) Baranski, M., K. Babbie and R. Pirog A Consumers Guide to Local Food Systems and Greenhouse Gases. [Accessed July ]. Batte, M. T., N. H. Hooker, T. C. Haab and J. Beaverson Putting Their Mouths are: Consumer Willingness To Pay for Multi-ingredient, Processed Organic Food Products. Food Policy. 32(2): Birol, E., K. Karousakis, and P. Koundouri Using a Choice Experiment to Account for Preference Heterogeneity in Wetland Attributes: The Case of Cheimaditida Wetland in Greece. Ecological Economics 60: Canadian Broadcasting Corporation The Marketing Search for any Town, Canada. [Accessed July ]. Canadian Food Inspection Agency (CFIA) Organic Products. (accessed August 1, 2013). Carlsson, F., P. Frykblom, and C. Johan Lagerkvist Using Cheap Talk as a Test of Validity in Choice Experiments. Economics Letters 89: Costanigro, M., D. T. McFadden, S. Kroll, and G. Nurse An In-store Valuation of Local and Organic Apples: the Role of Social Desirability. Agribusiness, 27(4): Cranfield, J., S. Henson, and J. Blandon The Effect of Attitudinal and Sociodemographic Factors on the Likelihood of Buying Locally Produced ffood. Agribusiness, 28(2): Goddard, E., P. Boxall, J. Emunu, C. Boyd, A. Asselin, and A. Neall Consumer Attitudes, Willingness to Pay and Revealed Preferences for Different Egg Production Attributes: Analysis of Canadian Egg Consumers. Working paper, University of Alberta, Department of Rural Economy. Haaijer, R., W. Kamakura and M. Wedel The "no-choice" Alternative in Conjoint Choice Experiments. International Journal of Market Research. 43(1): Hensher, D.A., J.M. Rose, and W.H. Greene Applied Choice Analysis: A Primer. Cambridge University Press. 83

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93 APPENDIX 86

94 Ontario Agricultural College Department of Food, Agricultural and Resource Economics Consumer perceptions of locally grown organic foods Researchers in the Department of Food, Agricultural, and Resource Economics at the University of Guelph are exploring consumer perceptions of and attitudes toward various food issues. The intent of this research is to better understand the factors that motivate consumer purchases of locally grown organic foods. This on-line survey is expected to take no longer than 20 minutes to complete. You are free to participate or not in this survey and should you choose not to participate, you can withdraw from the survey at any time. As well, you are free to skip any question you would prefer not to answer. By completing and submitting this survey, you provide consent to participate in the study. Individual responses will be anonymously collected and no identifying information about you will be collected (including IP addresses). All data will be stored on a secure computer, and will only be used for academic research purposes. Further information on your consent to participate can be reviewed by clicking here. This study has been reviewed and received ethical clearance through the University of Guelph Research Ethics Board. If you have any questions contact the project leader, Dr. John Cranfield, at extension 53708, or via at jcranfie@uoguelph.ca. Should you wish to receive a copy of the results from this study, please the project leader directly at the above address. By clicking this box I acknowledge that I have read and understand the above informed consent document and that I agree to be a participant in the survey Consumer perceptions of locally grown organic foods. S1) Our survey includes people of all ages; can you please select your age category? (Please check one) Under 18 years years years years years years 65 years or older [If less than 18 years - thank and terminate] 87