CSR Determinants of Consumers' Purchase of Organic Food

Master’s thesis

CSR determinants of consumers’ purchase of organic food A cross-cultural comparison between China and Sweden

Author: Mohamad Khair Jandali Rifai and Yong Wang (Group 7) Supervisor: Rana Mostaghel Examiner: Anders Pehrsson Term: VT19 Subject: Business Administration with

specialization in Marketing, Degree Project Level: Master of science Course code: 5FE05E

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Abstract The purpose of this thesis is to describe the determinants of corporate social responsibility (CSR) that are: community support, diversity, employee support, environment, overseas operations, and product, on consumers’ attitude towards purchasing of Organic food brands with Individualism as a moderator. It obtains a quantitative method by the deductive approach. Also, the probability and non-probability sampling select random Chinese and Swedish people above the age of 18. Data collection is by a survey using online questionnaires. Independent sample T-Test compare the means of two samples, factor analysis determines CSR activities and dimensions, and multiple regression employs a description of determinants of CSR dimensions on consumers attitude and purchase. Not to mention the factor analysis and regression analysis are on both samples separately to demonstrate a cross- cultural comparison. The results support previous studies that CSR activities play a crucial role in consumers’ attitude. However, not purchase. Individualism has no impact that moderates this role. Also, demographics do not impact consumers’ purchase, but income impact consumers’ attitude. Cross-cultural comparison for this role shows that it is convergent in Overseas operations and income groups among Chinese consumers. However, it is not convergent among Swedish consumers. Also, the higher the income group of Chinese consumers, the better is their attitude. The thesis gains knowledge that Organic food brands can use CSR activities to influences consumers’ attitude but not purchasing behavior, and organic food brands can tailor their CSR activities according to the target market income group. There is no prior research covering Individualism as a moderator to this influence coupled with Chinese and Swedish as a cross-cultural comparison. Therefore, this thesis is a unique, original, and valuable opportunity to cover this limitation.

Keywords Corporate social responsibility, Organic food, Attitude, Purchase, Individualism.

Acknowledgments We want to thank Professor Anders Pehrsson, lecturer Pejvak Oghazi, Setayesh Sattari, and Rana Mostaghel. Also, we thank the LNU library and the academic support center at LNU. We want to thank professor Sankar Sen who is an author of one of the cited articles, we would like to thank Eva Fröman from Eko-mat centrum who is also an author of one of the cited articles, and we also would like to thank Robin Juhl from Statista for all their interaction with us. Finally, we thank all the participants in the survey. We very appreciate their support, advice, and time.

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Table of contents 1 Introduction 1 1.1 Background 1 1.2 Problem discussion 5 1.3 Purpose and delimitation 8 1.3.1 Purpose 8 1.3.2 Delimitation 8 1.4 Report structure 9 2 Literature review 10 2.1 Purchase and Attitude 10 2.2 Purchase of organic food 11 2.3 Determinants of organic food purchase 13 2.4 CSR activities in the organic food industry and market 14 2.4.1 Community support 15 2.4.2 Diversity 16 2.4.3 Employee support 17 2.4.4 Environment 18 2.4.5 Overseas operations 20 2.4.6 Product 21 2.5 Individualism 22 2.5.1 Horizontal Individualism 23 2.5.2 Vertical Individualism 24 3 Theoretical framework 25 3.1 Frame of reference 25 3.2 Conceptual model 29 4 Methodology 31 4.1 Research approach 31 4.1.1 Inductive versus deductive research 31 4.1.2 Quantitative versus Qualitative research 32 4.2 Research design 33 4.3 Data sources 34 4.4 Research strategy 35 4.5 Data collection method 36 4.6 Sample and population 37 4.7 Sampling frame and size 39 4.8 Data collection instrument 42 4.8.1 Questionnaire design 43 4.8.2 Pre-test 44 4.8.3 Operationalization 45 4.9 Survey design 51 4.10 Data analysis method 52 4.10.1 Data Coding 53 4.10.2 Sample demographics and descriptive analysis 53 4.10.3 Exploratory factor analysis 54 4.10.4 Regression analysis 56

4.11 Moderating and mediating effects 57 4.12 Quality criteria 58 4.12.1 Validity 58 4.12.2 Reliability 60 5 Results and analyses 63 5.1 Pilot study 63 5.1.1 Reliability 63 5.1.2 Validity 66 5.2 Descriptive statistics 69 5.2.1 Socio-demographic profile of respondents 69 5.2.2 Descriptive for other variables 72 5.3 Exploratory factor analysis from the Chinese cluster 79 5.4 Exploratory factor analysis from the Swedish cluster 84 5.5 Multiple regression analysis 90 6 Discussion 96 7 Conclusion 99 8 Implications 101 8.1 Theoretical implications 101 8.2 Managerial implications 101 9 Limitation and suggestion for future research 103 9.1 Limitation 103 9.2 Future research 104 10 Bibliography 105

Figure 1: Conceptual model ...... 29 Figure 2: Simplified conceptual model ...... 30 Figure 3: Gender ...... 69 Figure 4: Age ...... 70 Figure 5: Education ...... 71 Figure 6: Income ...... 72

Equation 1: Actual sample size (Saunders, et al., 2016)...... 40 Equation 2: Rule of thumb (Green, 1991)...... 41 Equation 3: Composite reliability (Raykov, 1997)...... 61 Equation 4: Error variance (Raykov, 1997)...... 61

Table 1: Operationalization...... 46 Table 2: Rules of thumb of correlation coefficient size (Hair Jr, et al., 2015)...... 59 Table 3: Rules of thumb of Cronbach's alpha coefficient size (Hair Jr, et al., 2015)...... 62 Table 4: Cronbach's alpha reliability ...... 63 Table 5: Factor analysis for composite reliability ...... 65 Table 6: Composite reliability...... 66 Table 7: Pearson’s Validity test 1 ...... 67 Table 8: Pearson’s Validity test 2 ...... 67 Table 9: Pearson’s Validity test 3 ...... 68 Table 10: Descriptive statistics ...... 73 Table 11: Rotated loadings 1 from the Chinese cluster ...... 80 Table 12: Rotated loadings 2 from the Chinese cluster after removing E 3 ...... 81 Table 13: Principle component from the Chinese cluster ...... 83 Table 14: Rotated loadings 1 from the Swedish cluster...... 84 Table 15: Rotated loadings 2 from the Swedish cluster after removing Diversity 186 Table 16: Rotated loadings 3 from the Swedish cluster after deleting CS 2 ...... 87 Table 17: Principle component from the Swedish cluster ...... 89 Table 18: Multiple regression from the Chinese cluster ...... 90 Table 19: Multiple regression from the Swedish cluster ...... 93

Appendix 1: Survey ...... 122 Appendix 2: Independent sample T-Test ...... 129 Appendix 3: Descriptive statistics for Chinese cluster ...... 131 Appendix 4: Descriptive statistics for Swedish cluster ...... 132 Appendix 5: Regression coefficients of model 7 from the Chinese cluster...... 133 Appendix 6: Regression coefficients of model 10 from the Chinese cluster...... 134 Appendix 7: Regression coefficients of model 7 from the Swedish cluster ...... 135 Appendix 8: Regression coefficients of model 10 from the Swedish cluster ...... 136

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1 Introduction This chapter will introduce the background of the thesis and its related problem, by illustrating previous examples and statistics to give the reader a general idea of the topic and discover the gap, which leads to the purpose and research question, followed by the delimitation that clarifies the chapter. Then, report structure that conveys the main points and emphasizing on the structure of the thesis.

1.1 Background As the reaction to the adverse health and environmental effects of the genetically modified organism, pesticides, and other non-natural chemical substances used in the conventional agriculture, the more and more people are interested in the organic agriculture (Teng & Wang, 2015; Xie, Wang, Yang, Wang & Zhang, 2015). Because, people usually regard organic food as the more environmentally friendly, more nutritious, as well as safer and healthier (Teng & Wang, 2015; Xie, et al., 2015). The growing consumption of organic food represents the multi-billion industry (Thogersen, 2010). Whereas, the competition between organic food companies abound in the sector and attract investment (Thogersen, 2010). The organic agricultural land worldwide is increasing from 43.09 million hectares in the year 2013 to 57.82 million hectares in the year 2016 (Organic Eprints, n.d.). Ideally, the worldwide net sales of organic food goes from 68.5 billion U.S dollars in the year 2013 to 90 billion U.S dollars in the year 2016 (FiBL & IFOAM, n.d.). And the estimation is that the market growth of organic food will continue (Helga & Kilcher, 2018). However, the organic food industry and market in some countries can face some issues. By comparison, in China, the Chinese food safety scandals such as the milk and baby formula adulterated with the harmful chemicals in order to increase its protein content, gives the organic food companies edge in

their vast and growing industry and market (Fenby, 2013). Hence, the consumers lose faith in the industry and market of the domestic food or even the traditional food in general. This may constrain the organic food industry and market (Fotopoulos & Krystallis, 2002). Therefore, to compromise by the nutrition substitute and safer alternative (Wang, Zhang, Mu, Fu, & Zhang, 2009). The industry and market of organic food in China should always be favored by the Chinese consumers of organic food especially that the per capita consumption of organic food differs substantially between countries worldwide (Lee, Lusk, Mirosa, & Oey, 2014; Helga & Kilcher, 2018). Whereby, China, with its vast population, has 4 U.S dollars spending per capita consumption of organic food in the year 2016 (Helga & Kilcher, 2018). Not to mention a large quantity of organic food in China is produced exclusively for the export market segment (Helga & Kilcher, 2018). The organic food market in China is the fourth largest and highest growth in the world in the year 2016 (Helga & Kilcher, 2018). In other words, China’s organic agricultural land is increasing from 2,094,000 hectares in the year 2013 to 2,281,215 hectares in the year 2016 (Helga & Kilcher, 2018). However, organic food sales in China is also increasing. But not steadily from around 53 billion U.S dollars in the year 2013 to around 64 billion U.S dollars in the year 2015 (CGFDC, n.d.). Notwithstanding, the sales of organic food decreased to 6.7 billion U.S dollars in the year 2016 (Helga & Kilcher, 2018). There is an estimation that China will experience strong growth in the sales of organic food at 14.3% compound annual growth rate (CAGR) from the year 2017-2022 (Global organic trade guide, n.d.b). On the other hand, in Sweden, the Swedish consumers of organic food are skeptical about the industrial food and consider the industries and markets to produce and sell the food ethically. Because, the high sugar, low-quality raw materials, and multitude of artificial additives in the industrial food. This may react organic food industry and market avoidance (Fotopoulos & Krystallis, 2002; Orkla, 2017). Therefore, to compromise by the nutrition

substitute and safer alternative (Wang, et al., 2009). Swedish consumers of organic food should always be motivated to buy organic food and increase their knowledge about the food they eat (Orkla, 2017) especially that Sweden is the third highest per capita consumption of organic food in the year 2016 worldwide (i.e., spending 224 U.S dollars) (Helga & Kilcher, 2018). Not to mention, a large quantity of organic food is produced exclusively for the export market segment (Helga & Kilcher, 2018). The organic food market in Sweden is the ninth highest growth in the world in the year 2016 (Helga & Kilcher, 2018). In other words, Sweden’s organic agricultural land is increasing from 500,996 hectares in the year 2013 to 552,695 hectares in the year 2016 (Helga & Kilcher, 2018). Ideally, the sales of organic food in Sweden is steadily growing from around 1.2 billion U.S dollars in the year 2013 to around 3.1 billion U.S dollars in the year 2017 (Ekoweb, n.d.). There is an estimation that Sweden will experience growth in the sales of organic food at 4.4% compound annual growth rate (CAGR) from the year 2017-2022 (Global organic trade guide, n.d.b). In this respect, companies’ competitors of organic food react, and it is essential to manage sustainable competitive advantages (Palmatier & Sridhar, 2017). Marketing strategies are evolving substantially, and consumers are also becoming aware of the companies’ social and environmental activities such as: corporate social responsibility (CSR) (Mohr, Webb & Harris, 2001; Bhattacharya & Sen, 2004). Whereby, this is even more important for the marketers of organic food companies when they create brands for their products. The industry and market they are doing business in has more environmentally conscious consumers (Honkanen, Verplanken & Olsen, 2006; Vermeir &Verbeke, 2006; Xie, et al., 2015; Muhammad, Fathelrahman & Tasbih Ullah, 2016), due to the scandals (Fenby, 2013), skepticism (Orkla, 2017), or in general greenwashing (Terrachoice, 2010) that is:

“Intentionally misleading or deceiving consumers with false claims about a firm’s environmental practices and impact” (Nyilasy, Gangadharbatla & Paladino, 2014, pg. 693).

In other words, the organic food companies can have a fictive brand name for their products when the environmentally conscious consumers expect the brand to have high-quality organic food products indeed (Muhammad, et al., 2016), but supposedly mislead the consumers with certainty that the brand is in fact socially sound (Vermeir & Verbeke, 2006). With this in mind, CSR generates trust. The consumers who perceive the organic food brands as socially oriented (i.e., achieve competitive advantages) demonstrate even more trust towards those brands (Pivato, Misani & Tencati, 2008). Therefore, the CSR activities by companies are becoming essential for the consumers when making decisions on which organic food brand to buy (Mohr, et al., 2001). CSR activities might determine help marketers to sustain increasing production and sale of organic food in the cross-cultural countries (i.e., China & Sweden) (Mohr, et al., 2001), which will eliminate the skepticism of Chinese and Swedish consumers. Not to mention, the term determine is a dynamic concept that connotes a moderate relationship to decision making (Myers & Alpert, 1968). Some marketers seem not to fully and honestly care about their companies’ social and environmental responsibilities (Vaaland, Heide & Gronhaug, 2008). In so, incidents such as the greenwashing, or environmental and social misconduct have been committed in the companies, and they are causing their brands to lose their consumers (Wang, et al., 2009; Fenby, 2013). 90% of the global consumers would avoid the company if they discover the irresponsible or deceptive business practices and switch to the brand that its company associates with the social or environmental cause (Cone, 2015). With this in mind, the theory of CSR in the companies focuses on justifying the sustainability performance of the social and environmental concerns in their business operations (Garriga & Malé, 2004; Hohnen, 2007). The CSR is the

crucial determinant in the decision making among the stakeholders, and one of the most immediate consequences is that CSR creates 90% trust, 88% loyalty, and 93% positive image for the company (Pivato, et al., 2008; Cone, 2015).

1.2 Problem discussion The social and environmental or the CSR activities are motivational factors that influence the consumers’ purchase (Mohr, et al., 2001; Bhattacharya & Sen, 2004; David, Kline & Dai, 2005; Anselmsson & Johansson, 2007; Björklund, 2010). However, consumers’ consideration for brands and product categories are different (Johnson & Lehmann, 1997).

“A category-level should invoke a more abstract, general set of needs or values while a brand-level should invoke a more concrete, specific set of needs or values” (Johnson & Lehmann, 1997, pg. 296).

Arguably, tobacco, oil, alcohol, gambling, firearm, military contracting, and nuclear power can be unfavorable by some consumers and damp the CSR initiative in the production and sales due to their adverse health, social, and environmental effects that contrast with consumers of some product categories (Mohr, et al., 2001; Bhattacharya & Sen, 2004; Leventis, Hasan, Dedoulis, 2013; Grougiou, Dedoulis & Leventis, 2016). But on the product brand-level, the CSR activities that may ideally determine the consumers’ purchase with respect to their health, social, and environmental motives are: Community support, Diversity, Employee support, Environment, Overseas operations, and Product (Sen & Bhattacharya, 2001; Bhattacharya & Sen, 2004; Anselmsson & Johansson, 2007). Coupled with, the degree of the CSR in the company is relevant to the degree of the consumers’ purchase (Mohr, et al., 2001; Zhou & Zhang, 2007). CSR activities can have different association power together and with the determinant outcome behavior (i.e., purchase). With this in mind, one category of the products for which its consumers may be more cautious about the companies CSR activities when buying is the

organic food (Mohr, et al., 2001; Bhattacharya & Sen, 2004; Pivato, et al., 2008; Ho, 2017). The consumers of this category are already socially and environmentally responsible, and it is essential for them that the brand of the product they buy is also responsible (Pivato, et al., 2008). Not to mention the importance of motives varies between the product categories (Padel & Foster, 2005). Whereby, the essential motivational qualities of organic food brands are personal health, well-being, quality of life, better taste, enjoyment, political, fair trade, and education (Lockie, Lyons, Lawrence & Mummery, 2002; Padel & Foster, 2005). Those motivational qualities of organic food brands anticipate the responsible implications interpreted by the companies that implement the CSR activities (i.e., Community support, Diversity, Employee support, Environment, Overseas operations, and Product) as the marketing strategy if they ideally determine their consumers to purchase their products. Whereas, customers differ, and there is heterogeneity among customers and their reaction to CSR initiatives. Marketers should be aware of the different customers’ segments (Bhattacharya & Sen, 2004; Palmatier & Sridhar, 2017). With this in mind, there seems to be a relationship between the perception of the CSR and the Hofstede’s cultural dimensions (Kim & Kim, 2010). The Hofstede’s cultural dimensions which are generally with stable scores and can be related to the sustainability, consumption, and work as moderator are: Power Distance, Individualism, Uncertainty avoidance, Masculinity, Long-term orientation, and Indulgence (Husted, 2005; Beugelsdijk, Maseland & Hoorn, 2015; Tascioglu, Eastman & Iyer, 2017). Arguably, high Individualism has a negative relationship with CSR. But low Individualism has a positive relationship with CSR (Kim & Kim, 2010). That is to say, the CSR associations on social self-connection to the corporate brands are not stronger in the high Individualistic culture. Swedish consumers have low social self-connection to organic food brands. However, personal self-concept connection to the corporate brands is stronger in the high

Individualistic culture. Chinese consumers have a low self-concept connection to organic food brands (Moon et al., 2015; Hofstede-insights, n.d.). Arguably, high Individualistic cultures have a positive attitude towards companies with CSR initiatives and work as a moderator for buying their brands. The statistics earlier illustrate that countries with different level of Individualism are both buying Organic food in high volume (Boulstridge & Carrigan, 2000). However, the level of Individualism impact innovativeness, service performance, and advertising appeals in international marketing and other consumers’ behavior (Soares, Farhangmehr & Shoham, 2007). Individualism may have different patterns (i.e., horizontal and vertical) (Triandis, McCusker & Hui, 1990; Triandis, Chan, Bhawuk, Iwao & Sinha, 1995). Therefore, the organic food marketers should be aware of Individualism with its two patterns as the moderator that influence the relationship between the mediating attitudes that are driven by CSR initiatives with purchasing of their organic food brands. It asses them to know their customers of the target market segment across different cultures who perceive their companies’ CSR initiatives in deciding on the type of the managerial activities and associations to build and invest, which its information will illustrate on the labels and other diversified advertising channels. Because, information about such activities may not always be visible to the consumers. The actual purchase is affected by package labels and appearance (Brown & Dacin, 1997; Rimal, Fletcher & McWatters, 1999; Sen & Bhattacharya, 2001; Teng & Wang, 2015). In summary, there seems to be a gap in the consumers’ purchase behavior towards organic food (Padel & Foster, 2005; Vermeir & Verbeke, 2006). Because, there are misleading practices committed by conventional and industrial food producers and marketers. There is skepticism by the Chinese and Swedish consumers of organic food products. Coupled with, organic food brands are the healthier and nutritious substitute for the attitude of low Individualistic cultures and high individualistic cultures. Their CSR activities are also motivational factors that influence consumers’ purchase. However

organic food brands’ marketers need to determine this to the cross-cultural Chinese and Swedish organic food consumers. In other words, most of the articles focus on the relationship between organic food brands with their consumers’ purchase. Other articles focus of the relationship between the CSR activities and their influence on the consumers' purchase. However, there is lack of articles on evaluating the determinants of attitudes from CSR activities in organic food companies on mediating their Chinese and Swedish consumers’ purchase of their brands with the role of the Hofstede’s national cultural dimension Individualism with its patterns in moderating this relationship with respect of the cross-cultural comparison of the results of this relationship.

1.3 Purpose and delimitation

1.3.1 Purpose This thesis will compare the relationship between the corporate social responsibility (CSR) activities in the organic food companies with the Chinese and Swedish consumers’ attitude towards purchasing their brands and evaluate the role of the Individualism patterns on moderating this relationship. In the review of the mentioned above, the research question is: What CSR activities in organic food brands determine consumers’ attitude to purchasing during the comparative relationship between China and Sweden?

1.3.2 Delimitation The thesis does not include consumption consciousness, and terms such as “Ethical consumption” and “Skepticism” as part of the influence on the purchase. Also the thesis does not include industries such as automobile, home appliance, and fashion. Instead, the thesis mainly focuses on what CSR activity determines the purchase of the Chinese and Swedish consumers in the organic food industry and market the most. However, the thesis will not include only the direct relationship between the CSR activities and the purchase, though it

suggests that the attitude driven by CSR activities and moderated by Individualism patterns mediate this relationship, without the other internal outcomes and other Hofstede’s culture dimensions. Not to mention, the thesis does not include industries that damp the CSR initiatives such as tobacco, alcohol, oil, gambling, firearm, military, and nuclear power, due to the hostile attribution that consumers often perceive such activities. The CSR activities that included in the thesis instead are community support, diversity, employee support, environment, overseas operations, and product. Notwithstanding, the thesis emphasizes data reduction by formulating basic fewer items into main dimensions through the factor analysis. The thesis also tests the relationship of those dimensions with the purpose of the study and test the hypotheses through the regression analysis.

1.4 Report structure The outline of the thesis will continue followed by the chapter 2, which provide the literature review on the Purchase and attitude, Purchase of organic food, Determinants of organic food purchase, CSR activities in organic food industry and market, Community support, Diversity, Employee support, Environment, Overseas Operations, Product, Individualism, Horizontal, and Vertical. In order to give the precise review for this thesis, the authors will collect and engage the related theories from the chapter 2 into the chapter 3 with the appropriate theoretical framework which includes Frame of reference, and Conceptual model. Chapter 4 will address the methods used in this thesis followed with chapter 5, which illustrate the results and analyses of the collected data. Then finally, discussion, conclusion, theoretical and managerial implications, limitation, and further research recommendation.

2 Literature review This chapter looks thoroughly into the previous chapter, by providing a critical assessment of the thesis in a literature review.

2.1 Purchase and Attitude Consumers’ attitude perceived by service quality and self-concept (Wu & Chan, 2011) that influence individuals’ behavior to purchase a brand possibly (Dodds, Monroe & Grewal, 1991; Spears & Singh, 2004). Whereas, consumers care about business ethics and firm behavior influence purchase decisions (Creyer, 1997). Companies surround the public’s beliefs and perceptions about their brands’ positive reputation by supporting a good cause (Boulstridge & Carrigan, 2000). Arguably, attitude is the correct mediator for marketers in order to get familiar with consumers’ buying behavior (Vahdati, Mousavi & tajik, 2015). However the high fit cause does not always affect attitude, and companies reputation can reflect a large issue (Spears & Singh, 2004; Lafferty, 2007). Fit is:

“The degree to which the information contained in the stimulus favors (or hinders) the identification of the theme or message being communicated” (Zdravkovic, Magnusson & Stanley, 2010, pg. 152) Therefore, a social structure is crucial in establishing and maintaining social order. Attitudes must change before the behavior (Chaiklin, 2011; Vahdati, et al., 2015). Also, when marketing researchers study the relationship between attitude and behavior. They refer to this as an evaluating process, where the behavior is formed subsequently after attitude (Riley, Rink & Harris, 1999; Vahdati, et al., 2015). Hence attitudes are only summary evaluations, which energizes behavior (Spears & Singh, 2004). Similarly, knowing attitudes help marketers to get familiar with the way customers think, feel and how inputs can affect them to choose brands. Understanding consumer buying behavior can help marketers get more familiar with their customers (Vahdati, et al., 2015). Hence attitude and behavior help marketers to develop appropriate marketing strategies (Vahdati,

et al., 2015). Also, if marketers are familiar with the consumers’ attitude and behavior, they will know how customers try to get information, what encourages them, and what influence their final decision to buy (Vahdati, et al., 2015). Moreover, for the individual to perform a behavior is linked to attitudes (Ajzen & Fishbein, 1980; Ajzen, 1991; Ajzen, 2002). There are other internal outcomes for the consumers (e.g., awareness, attributions, attachment, and well-being) (Bhattacharya & Sen, 2004; Anselmsson & Johansson, 2007). However, in order to not make researches questionnaires too long, because lengthy questionnaires reduce response rate (Burchell & Marsh, 1992; Sen & Bhattacharya, 2001). Attitude is the internal outcome. Moreover, there is a need to move beyond attitudes to the actual purchase situation (Anselmsson & Johansson, 2007), because the link between attitude and behavior is not always clear (Spears & Singh, 2004). Consumers may support an action related to ethics but not carry it out (Carrigan & Attalla, 2001). Also, when measures of actual behavior are available, a low correlation is shown between attitudinal measures and actual buying behavior (Foxall, 2005). Therefore, there should be a moderating effect, to increase the correlation between attitude and actual buying behavior. Furthermore, there are many indicators of actual purchase behavior such as: purchase incidence (i.e., buy or not buy), amount spent, number of visits, and number of types of products bought, because the best predictor of future behavior is past behavior (De Canniere, De pelsmacker, Geuens, 2009; Voon, Ngui, Agrawal, 2011; Abdeen, Rajah & Gaur, 2016). The following subchapters will interpret purchase behavior with the context of the study.

2.2 Purchase of organic food Organic food is generally perceived as more nutritious, as well as healthier, safer, and more environmentally friendly (Chen & Lobo, 2012). The definition of organic food is:

“Minimally processed to maintain the integrity of the food without artificial ingredients, preservatives or irradiation” (Essoussi & Zahaf, 2008, pg. 96).

With this in mind, the individual environmental concern is an essential fundamental part that is primarily a reflection on organic food consumption. The protection of the environment motivates the consumer of organic food consumption by the absence of agrochemicals through production methods to reduce the impact caused by farming on the environment. Moreover, the altruistic motives are concerns for the environment, animal welfare, and health benefits. They are becoming the most potent motivating factor for the purchase of organic food (Padel & Foster, 2005). Moreover, organic food is usually more expensive than conventional food (Hjelmar, 2011). Cost concerns are carried out with organic food consumption (Johnston, Szabo & Rodney, 2011). Whereby, consumers are more likely to pay a premium for the superior quality, health and sustainable attribute, and taste of organic food, as well as certified safeness (Chen & Lobo, 2012). The Europeans would pay 24% premium price for organic food in the year 2014 and Asians would pay 37% premium price for organic food in the year 2014 (Nielsen, n.d.; Nielsen, 2015). However, the high price of organic food products still could be considered as a barrier. There is development of the organic food market in some target segments. Whereby, the price has an effect on preference heterogeneity between conventional or organic food among different consumers segments (Stolz, Stolze, Hamm, Janssen & Ruto, 2011). Younger consumers (i.e., generation z under 20) and millennials consumers (i.e., between 21-34) are more willing to pay the premium for healthy attributes than other generations (Nielsen, 2015). Moreover, women are internally focused (e.g., on people), and men more externally focused (e.g., on payment) (Lakshmi, Niharika & Lahari, 2017). The higher consumers’ incomes are the more consumers’ demand for organic and high-quality food (Bekele, Zhou, Kidane & Haimanot, 2017). Whereas, the average monthly

income in Beijing, China is $1300 (Checkinprice, 2018). The average monthly income in Sweden is $2500 (Checkinprice, 2017). Therefore, the information on labels should be easy to understand and clear, because consumers read packaging labels carefully. The education of consumers segment should be a consideration (Nielsen, 2015). Moreover, purchasers of organic food can be classified as regular or occasional purchasers according to their buying frequency (Pino, Peluso & Guido, 2012). Marketers should consider consuming frequency as an item to measure the actual purchase, coupled with the amount and the willingness to pay more (Voon, et al., 2011). The next subchapters will interpret the theoretical strategy with the context of the study.

2.3 Determinants of organic food purchase With the increasing sales of organic food throughout the past decades but with significant differences between countries, organic food consumers have become a particular segment of individuals with environmentally and altruistic values. Whereby, attributes of organic food consumption can be related to security, hedonism, universalism, benevolence, stimulation, self-direction, and conformity (Aertsens, Verbeke, Mondelaers & Huylenbroeck, 2009). Health, food safety, and environmental respect are important motives to purchase organic food because organic food is natural, clean, and has no chemicals or additives (Shepherd, Magnusson & Sjödén, 2005). With this in mind, corporate social responsibility CSR activities are determinant factors when purchasing organic food brands (Anselmsson & Johansson, 2007). There is variation in considering CSR activities by organic food companies (Jones, Comfort & Hillier, 2005). Whereas, the harmful practices of companies on the environment, labor rights, interests, and animal protection have been exposed frequently in food processing. Consumers are increasingly paying attention to the impact of those and other practices by the companies besides their products only (Fortin, 2018).

With this in mind, there is a relationship between the egregiousness of the firm’s actions and boycott participations (Klein, Smith & John, 2004). Consumer boycott is:

“An attempt by one or more parties to achieve certain objectives by urging individual consumers to refrain from making selected purchases in the market place” (Friedman, 1985, pg. 97).

However, consumers may change or strengthen their purchasing options due to certain responsible behaviors of the company (Creyer, 1997; Carrigan & Attalla, 2001). The lack of CSR in companies makes consumers chose to refuse purchasing their organic food and even publicly resist (Tate, Ellram & Kickoff, 2010; Smith & Li, 2010).

2.4 CSR activities in the organic food industry and market Corporate social responsibility CSR used in the triple bottom line: people (society), profit (economic), and planet (environment), which is also the interaction by companies of social and environmental concerns in their business operations and in their interaction with stakeholders on voluntary basis (Wheeler & Elkington, 2001; Tate, et al., 2010; Björklund, 2010). Hence it is not surprising that the domains of corporate socially responsible behavior are many and diverse in organic food companies which influence the purchase of their brands (Sen & Bhattacharya, 2001). Whereas, there are six broad domains of CSR activities that can be related to the context of organic food which are: community support, diversity, employee support, environment, overseas operations, and product (Sen & Bhattacharya, 2001; Bhattacharya & Sen, 2004; Pomering, 2005; Anselmsson & Johansson, 2007; Siegel & Vitaliano, 2007). These domains are also crucial for organic food companies because they can be customized to meet the interests of a nonprofit investment (Johnson, 2001). Whereas, the stock or bond with a coupon rate of zero, which mean that the yield-to-maturity of a bond’s price from the time of receiving the unit until it is paid off at the later

time when the price is maturing and with zero interest (Dybvig, Ingersoll & Stephen, 1996). An individual can select a specific set criterion of the CSR domains in which the company will assess (Johnson, 2001). Not to mention, an auditor should monitor corporate agriculture, social change, environment, globalization, and human rights. To assure the investor that the investment is supporting socially responsible activities (Johnson, 2001). The following sections will review the six CSR domains (i.e., community support, diversity, employee support, environment, overseas operations, and product) that is relevant to the purpose of the thesis.

2.4.1 Community support Companies that build a positive relationship with the community is appreciated as the ethical player (Pivato, et al., 2008). With this in mind, most CSR activities in this area by organic food companies tend to target health promotion (i.e., physical, mental, and social wellbeing) by cultural activities. Because it is essential to understand the local cultures for building and developing brand goodwill (Schröder & McEachern, 2006). For examples, sponsorship of charities in the form of donations to charitable organizations (Bhattacharya & Sen, 2004; Anselmsson & Johansson, 2007). However, education and training other enterprises and individuals in advanced operations by different languages to also be used to suit the needs of students that are coming from overseas seeking organic food sector education (e.g., management, engineering, construction, and agriculture) (Vignali, 2001). This process could be stressful (Zaglul, Sherrard & Juma, 2006). Despite, sport, art, health programs, housing initiatives for the economically disadvantaged, generous, innovative giving, and local community projects and enterprise activities by the organic food company (Bhattacharya & Sen, 2004; Vives, 2006; Anselmsson & Johansson, 2007). Women in sport can be a sports issue because of cultural differences, also when developing sport as substance and cure for social issues such as crimes,

and art projects may associate with social exclusion (Jermyn, 2001; Calloway, 2004; Ware & Meredith, 2013). Hence, community participation is:

“The process by which individuals and families assume responsibility for their own health and welfare and for those of the community and develop the capacity to contribute to their and the community’s development” (WHO, 1978, pg. 20).

Community support activities in organic food companies involve the locals in the decision-making process to recognize the needs related to the agriculture sector by alienation and displacement, such as the need to inhibit the operations of oil exploration and exploitation in the community (Chilaka & Nwaneke, 2016). However, the charitable contribution judged as a strength in this domain but the other activities in this domain have had a negative impact on the community and was a subject of opposition. Organic food companies may turn neutral to philanthropic activities if the other activities are still unfavorable by the community. Because, the market does not reward companies that are over generous (Bird, Hall, Momentè & Reggiani, 2007). The unfulfilled promises, deprivation, inadequate compensation, and insufficiency of this domain’s activities in the community widespread social distrust (Edoho, 2008).

2.4.2 Diversity People are different and consist of a range of characteristics (Hacking, 2007; Emmott & Worman, 2008). With this in mind, this domain’s activities open up market opportunities that regulate labor market legislation by providing employment opportunities, and conditions that meet the unique needs of minorities (Bird, et al., 2007). Diversity set up regulations against discrimination of: sexual orientation, gender, race, family, religion, belief, age, disability, and minorities by governmental rules within and outside the firm hence among consumers, workers, and community (Sen & Bhattacharya,

2001; Bhattacharya & Sen, 2004; Anselmsson & Johansson, 2007; Emmott & Worman, 2008). With this in mind, CSR extends the personal and corporate background, personality, education function, and lifestyle (Von Bergen, et al., 2002). All talents fully utilized, and everyone harmoniously valued in a developed productive environment that is more creative, innovative, and which combat prejudice, stereotyping, harassment, and disrespectful behavior that meet the organic food companies’ goals (Sachs, 1992; Emmott & Worman, 2008). Hence it shows up clearly in companies that involved in acquisitions and mergers (Von Bergen, et al., 2002). Moreover, there is no one particular way to treat employees, because all individuals have their own needs, beliefs, values, and want to be recognized with the appreciation for what they do because if they do not, individual performance reduced (Emmott & Worman, 2008). Minorities do not represent senior positions in companies (Bird, et al., 2007). Hence, consumer support for diversity is usually varied (Sen & Bhattacharya, 2001). Marketers should consider organizational circumstances and tailor approaches to progressing and train diversity and affirmative action to deliver success (Von Bergen, et al., 2002; Emmott & Worman, 2008).

2.4.3 Employee support Employees refer to the internal members that have a group affiliation with the company, and who are the social publics that each company directly faced and most closely approached (Dau-Schmidt, Finkin & Convington, 2016). Whereas, Employee support in CSR is:

“The extent to which employees perceive the organization’s external CSR initiatives to be appropriate and are willing to contribute to their implementation” (Shen & Zhang, 2017, pg. 876).

The company must take responsibility for employees, respect employees, care for employees, improve the quality of employees, create the stage for employees to display the talent and achieve value (Almahamid,

McAdams & Kaladeh, 2010). Because, employees drive brands to deliver their promise to clients (Berger-Remy & Michel, 2015). This domain focus on the condition of workers and producers such as the abolishment of child labor and protecting fundamental human rights, coupled with, the concern for employees safety, their job security, and the relationship between workers and unions in a profit-sharing perception (Anselmsson & Johansson, 2007). Because, if companies adopt unethical employment policies. Consumers’ perceptions will be negative with the companies, somehow regardless of the quality of products (Folkes & Kamins, 1999). In other words, employees carry a big responsibility for implementing ethical behavior in the daily working life of the companies (Carroll, 1998). Hence, the achievement of those examples of employee support. Largely depend on employee willingness to collaborate (Collier & Esteban, 2007). Arguably, positive employee relations are demonstrated by involving workers within the company, sharing profits generously among the employees, excellent benefits of retirements, and a good record of safety. Companies might have bad union relations, poor records of safety, and poorly funded retirement plans (Bird, et al., 2007). Because, profit sharing with employees can do some harm (Estrin, Grout & Wadhwani, 1987), and social pressure may be a substitute in some cases (Levin & Tadelis, 2005). It is essential to investigate the perception of this dimension which implemented in organic food companies (Assiouras, Ozgen & Skourtis, 2013).

2.4.4 Environment The responsibility towards the environment represents the main activity of CSR (Sen & Bhattacharya, 2001; Bhattacharya & Sen, 2004; Anselmsson & Johansson, 2007). Because health and environmental issues are strongly related (e.g., pesticides and their effect on the environment and human health) (Kolk, 2005; Pivato, et al., 2008).

Coupled with, environmental CSR activities are hazardous waste management, including recycling programs to use life cycle assessment (Winkler & Bilitewski, 2007). Organic food brands should determine producing food in an environmentally friendly way to also avoid public criticism (Wiese & Toporowski, 2013). Moreover, sustainable alternatives that ban, control pollution, or reduce the emissions of substances that deplete the ozone layer which mostly found in refrigerators and air conditioners because biodiversity leads to the growing demand for organic food (Siegele & Ward, 2007). Animal testing from cancer and other diseases, also welfare by grain feed and appropriate selection of organic animal breeding, particularly animals that produce milk (that can be made into butter and cheese), beef, and eggs (Magkos, Arvaniti & Zampelas, 2006). Therefore, producing hazardous waste and environmentally unfriendly products will obtain a negative score in this CSR domain (Bird, et al., 2007). Environment in CSR defined as:

“The duty to cover the environmental implications of the company’s operations, products and facilities, eliminate waste and emissions, maximize the efficiency and productivity of its resources, and minimize practices that might adversely affect the enjoyment of the country’s resources by future generations” (Mazurkiewicz, 2004, pg. 2).

There should be a link between social responsibility, ethics, and environmental aspects, because corporate environmental reports and self- imposed environmental regulations included in social responsibility (Carrigan & Attalla, 2001). Whereby, consumers of organic food concerned about environmental protection and involved in green practices (Yin, Wu, Du & Chen, 2010; Sirieix, Kledal & Sulitang, 2011). Hence besides healthiness, the environment-related value is another reason to purchase organic food.

2.4.5 Overseas operations This activity combats overseas labor practices (i.e., sweatshops) in countries with human rights violations (Sen & Bhattacharya, 2001). Hence, Sweatshop is:

“Any workplace in which workers are typically subject to two or more of the following conditions: systematic forced overtime, systematic health and safety risks that stem from negligence or the willful disregard of employee welfare, coercion, systematic deception that places workers at risk, under-payment of earnings, and income for a 48-hour work week less than the overall poverty rate for that country” (Arnold & Hartman, 2003, pg. 453). The company is responsible for providing equal rights for the people of the world to get the chance to work among others by opening factories abroad (Kiran & Sharma, 2011). Not to mention, general agreement on universal responsibility should include through supplying educational alternative than the exploitation of child labor. That is to not to cause another people injury, assure health benefits, and retirement benefits for overseas labor (Sen & Bhattacharya, 2001; Anselmsson & Johansson, 2007). In other words, a great promotion in organic food company can happen by combating sweatshop conditions in overseas manufacturing by introducing an international fair labor partnership program for the organic food brand, with a description that detail the implications. Choosing a particular pricing option, which includes a donation to the nonprofit organization that has a promoting international fair labor practice as its goal is also essential (Lichtenstein, Drumwright & Braig, 2004). Because customers believe they have done their share of donation by supporting CSR with their purchasing (Lichtenstein, et al., 2004). Arguably, organic food international operations efficiency is essential for providing excellent value for clients (Rimmington, Carlton Smith & Hawkins, 2006; Kolk, Hong & Van Dolen, 2010), because better treatment of overseas employees provides and maintain a high-quality product (Bhattacharya & Sen, 2004). Some organic food companies have no overseas

operations, because changing practices can be challenging and takes time due to government regulations (Rimmington, et al., 2006; Kolk, et al., 2010).

2.4.6 Product A commitment to producing quality products may be viewed as a long-term commitment to sustainability and extended profitability for organic food companies (Johnson & Greening, 1999; Chen & Lobo, 2012). Therefore, it is crucial to manage the diffusion to sustainable products and deeply understand the product consumption in daily life context (Mylan, 2015). CSR activities in this domain can be done by research, development, innovation, marketing, and contracts to avoid controversies and antitrust disputes (Sen & Bhattacharya, 2001; Bhattacharya & Sen, 2004). But these activities can be expensive (Belz & Schmidt-Riediger, 2010; Tsai & Wright, 2015). Because, the product should be produced, designed, and commercialized in the least harmful way possible for the environment and which can easily recycle. The product reinforcements and evaluations are essential, especially in the food context where strong brands vouch for reliable products (Brown & Dacin, 1997; Anselmsson & Johansson, 2007). In other words, the organic food brand measured by high-quality products, and high innovation through the research of preservation of nature. This develops and co-create brand to cover the special needs of the disadvantages (Sen & Bhattacharya, 2001). Organic food companies may face issues such as product safety issues (Assiouras, et al., 2013). Whereby, products can have negative consequences for customers. Companies may withdraw products due to the accusation of poisoning. Also, companies graded as low product safety will have controversies on how the product advertised, and other related concerns that effect on overall product judgment and evaluation (Brown & Dacin, 1997; Sen & Bhattacharya, 2001; Anselmsson & Johansson, 2007; Bird, et al., 2007). The product must meet its information that is printed on the label and acquire

the requirements of the charters currently existing in the market by respecting the rules of manufacturing, understand consumption, and assure testing to enhance the product judgment and evaluation (Brown & Dacin, 1997; Sen & Bhattacharya, 2001; Jones, Comfort & Hillier, 2007; Pivato, et al., 2008).

2.5 Individualism The current study wants to describe the determinant factors that influence the purchase of organic food brands in a cross-cultural context. With this in mind, the cross-culture will be measured by Hofstede’s cultural dimension Individualism (Hofstede, 1980). This is even important because Individualism is one of the major cultural variables discussed by theorists across disciplines (Hofstede, 1980; Hui & Triandis, 1986), and have been widely used in behavioral studies in different contexts and different countries (Ramamoorthy & Carroll, 1998; Gelfand & Realo, 1999; Van Dyne, Vandewalle, Kostova, Latham & Cumming, 2000). Also, individualism assists marketing segmentation or standardizing and develops a target market. There are different levels and intensity of organic food consumption, and segmentation based on value system differences (Squires, Juric, Bettina Cornwell, 2001; De Maya, Lopez-Lopez, Munuera, 2011). Individualism is more independent and self-oriented in the environmental related purchase (Kim & Choi, 2005). Whereby, societies think of themselves as “I” instead of “We”. They depend on their own, do not expect help from no one, and feel no need for strong loyalty (Hofstede, 1994). Therefore, Individualism has been discussed in social science (Triandis, et al., 1995). Individualism have gained significant attention from scholars and marketers as converging measurement and antecedents of environmental behavior that affect the consumers’ purchase (Triandis & Gelfand, 1998; Lee & Choi, 2005). Because, it illustrates the values that consumers learn from society. Individualism moderate the relationship between CSR activities in organic food companies and the purchase of their brands.

Coupled with, Individualism influence consumers behavior and how they deal with ethical issues (Cho & Krasser, 2011). Individualism influences the perception of CSR (Kim & Kim, 2010). However, the judgment of what constitutes an ethical controversial varies depending on cultural orientation. The conceptions of what is right for individualism and society is also various (Belk, Devinney & Eckhardt, 2005). Whereas, China scores 20%. Sweden scores 71% (Hofstede-insights, n.d.). Therefore, it is essential to compare the moderating impact of Individualism among the two cross-cultures. The next section will review the patterns of Individualism that are Horizontal and Vertical.

2.5.1 Horizontal Individualism Horizontal individualism plays a distinct role in a person’s attitude, behavior, and detect differences in people’s cultural orientations (Williams & Rokeach, 1974; Lee & Choi, 2005). Hence, in horizontal individualism, people strive to be unique, do their own thing, distinct from groups, and are highly self- oriented and self-reliance (Triandis & Gelfand, 1998; Lee & Choi, 2005). This pattern may result in social isolation and not approve of what other individuals do (Triandis & Gelfand, 1998). However, the horizontal pattern emphasizes equality matching where oneself is more or less like every other self. People are not interested in becoming distinguished or in having high status, and this has shown in Sweden (Triandis & Gelfand, 1998; Lee & Choi, 2005). Therefore, this dimension is also related to market pricing and political system that highly value equality, freedom, and social democracy (Williams & Rokeach, 1974; Fiske, 1992; Triandis & Gelfand, 1998). There is less difference in the status of men and women in this pattern (Triandis & Gelfand, 1998). Whereas, students may be more horizontal in individualism. It is less competition among college students than other generation. Therefore it is essential to understand the variation in individualism (Lee & Choi, 2005).

2.5.2 Vertical Individualism Vertical individualism also plays a distinct role in a person’s attitude and to detect differences in people’s cultural orientation (Lee & Choi, 2005). Hence, in vertical individualism, people want to do their own thing and has self- serving biases (Triandis & Gelfand, 1998; Lee & Choi, 2005). Hierarchy emphasized by authority ranking, where people strive to be the very best, want to be distinguished, and acquire status through competition with others (Triandis & Gelfand, 1998; Lee & Choi, 2005). In so, oneself is different from every other self (Triandis & Gelfand, 1998). This pattern values great freedom but not equality, competitive capitalism, and market economies (Williams & Rokeach, 1974; Triandis & Gelfand, 1998). Because, this pattern may result in extreme stress after failures in competition. Emotions can have a negative effect, and peaceful societies base their views on the corporation and opposition to competition (Bonta, 1997; Totterdell, 1999). Whereas, there is more difference between the status of men and women in this pattern (Triandis & Gelfand, 1998). If women could reach the top of the hierarchy, it is more easily for men to do so (Triandis & Gelfand, 1998). Whereas, students may be less vertical in individualism. It is less competitive among college students than other generations. Whereby, individualism corresponds to market pricing. Verticality is the ratio of the incomes (Triandis & Gelfand, 1998). Furthermore, this pattern is likely to result in creativity and high effort (Triandis & Gelfand, 1998). Populations that are likely to be vertical are related to industrial settings in which downsizing is taking place (Triandis & Gelfand, 1998). Therefore it is also essential to understand the variation in individualism (Lee & Choi, 2005).

3 Theoretical framework This chapter synthesizes the literature review into three hypotheses and conceptual model for the study. Therefore, it assists the reader to understand the purpose of the study.

3.1 Frame of reference Previous studies summarized the main CSR activities in six broad domains (i.e., community support, diversity, employee support, environment, overseas operations, and product). Each of the CSR domains has activities that influence consumers’ purchase, and they can thoroughly evaluate in the context of organic food. This evaluation indicates that there is a positive relationship between CSR initiatives by brands and consumers’ attitude toward those brands (Brown & Dacin, 1997; Sen, Bhattacharya & Korschun, 2006; Vahdati, et al., 2015). Previous studies demonstrate that community support activities influence consumers’ attitude. Whereas, the unfavored activities in the community are subject to opposition. The sponsorship of charities and supporting the economically disadvantaged groups in the community can often enhance consumers’ attitude against such issue (Bhattacharya & Sen, 2004; Vives, 2006; Anselmsson & Johansson, 2007). Similarly, support for educational and training programs about agriculture for enterprises in the community (Anselmsson & Johansson, 2007). Support for sport, art, and cultural activities in the community also (Vives, 2006). Diversity activities influence consumers’ attitude. Whereas, reforming the unfair distribution of corporate contracts in the organic food sector enhance consumers attitude against such issue (Sen & Bhattacharya, 2001; Bhattacharya & Sen, 2004). Activities for respect to the mentioned above can be by providing minorities with more employment opportunities (Sen & Bhattacharya, 2001). Similarly, setting up regulations against the discrimination of age, gender, and race (Bhattacharya & Sen, 2004; Emmott

& Worman, 2008). Religion, belief, and culture also (Anselmsson & Johansson, 2007; Emmott & Worman, 2008). Employee support activities influence consumers’ attitude. Whereas, boycotting work-related issues in the organic food sector enhance consumers’ attitude against such issues (Sen & Bhattacharya, 2001; Anselmsson & Johansson, 2007). Activities for respect to the mentioned above can be by concern for employee safety, their job security, and profit sharing with employees (Sen & Bhattacharya, 2001; Bhattacharya & Sen, 2004). Environmentally friendly activities influence consumers’ attitude. Whereas, the boycotting of health-related issues in environment and animal welfare enhance consumers’ attitude against such issues (Lockie, Lyons, Lawrence & Grice, 2004; Yin, et al., 2010; Sirieix, et al., 2011; Voon, et al., 2011; Chen & Lobo, 2012; Thogersen & Zhou, 2012). Organic food brands should be environment-friendly (Bhattacharya & Sen, 2004). Similarly, recycling and hazardous waste management should be conducted (Bhattacharya & Sen, 2004). Animals should be under test from disease also (Bhattacharya & Sen, 2004). Overseas operations influence consumers’ attitude. Whereas, sweatshops in overseas countries are considered human rights violations. Human responsibility, and donation support enhance consumers attitude towards human welfare (Sen & Bhattacharya, 2001; Anselmsson & Johansson, 2007). Activities in this domain concern equal human rights in non-domestic operations (Anselmsson & Johansson, 2007). Similarly, exploiting child labor and supply education for them in non-domestic operations (Anselmsson & Johansson, 2007). Supporting donations to non-profit organizations in overseas also (Kolk, 2005). The product influence consumers’ attitude. Whereas, product safety is considered issues for organic food companies. Respecting the rules of manufacturing, consumption, food safety and testing by meeting the information printed in the label and charters in the market enhance consumers’

attitude against such issues (Huang, Kan & Fu, 1999; McEachem & Mcclean, 2002, Dunlap & Van Liere, 2008). Activities for respect to the mentioned above can be by research and development (Bhattacharya & Sen, 2004). Similarly, marketing and innovation (Bhattacharya & Sen, 2004). Contracts to avoid controversies and antitrust disputes also (Bhattacharya & Sen, 2004). In light of the mentioned above, the first hypothesis with multi-variables developed: H1: More favorable CSR activities are associated with consumers’ better attitude towards organic food brands.

Studies demonstrate that attitude develops a purchasing behavior. Whereas, the internal outcome from the inputs of CSR activities impact the external outcomes such as purchasing behavior. The link between attitude and purchasing behavior is not always clear (Carrigan & Attalla, 2001; Spears & Singh, 2004). Whereby, attitude can evaluate by perceived reputation, cause, and personal connection represented by the organic food brands’ CSR initiatives (Bhattacharya & Sen, 2004). The second hypothesis developed: H2: Consumers’ attitude towards CSR initiatives by organic food brands influence purchasing volume.

The national culture dimension Individualism has been investigated in multimethod and gained significant attention from scholars and marketers as a converging measurement (Triandis, et al., 1990; Triandis & Gelfand, 1998). Some measurements constructs are relevant to Individualism such as Horizontal and Vertical which can detect the differences in Individualism (Triandis, et al., 1995; Triandis & Gelfand, 1998; Lee & Choi, 2005). Arguably, horizontal patterns assume that oneself is more or less like every other self hence emphasize equality (Triandis, et al., 1995). Vertical patterns emphasize hierarchies whereby oneself is different from other selves (Triandis, et al., 1995). In so, horizontal Individualism emphasizes uniqueness.

People strive to be unique and do their own thing (Lee & Choi, 2005), On the other hand, vertical Individualism is achievement oriented. Where people want to do their own thing and strive to do the best (Lee & Choi, 2005). With this in mind, culture influence purchasing behavior (Kim & Kim, 2010). There are differences in the impact of CSR on consumers’ purchase because of consumers’ egocentric and identity (Russell & Russell, 2010; Kim & Kim, 2010). For instance, high level of Individualism has a negative relationship with CSR perception (Kim & Kim, 2010). Though consumers with individualism attitude prefer firms that have good behavior (Cho & Krasser, 2011). Therefore, the thesis suggests that Individualism patterns positively moderate the attitude driven by CSR activities to increase consumers’ purchase of organic food. The third hypothesis with multi- variables developed: H3: Individualism patterns moderate consumers’ attitude towards CSR initiatives by organic food brands to increase purchasing volume.

3.2 Conceptual model A model plays an essential role in research, and it represents and simplifies the relationship between concepts in theory (Ghauri & Gronhaug, 2005). This thesis model is developed from the previous model of Anselmsson and Johansson (2007). With this in mind, the conceptual model in Figure 1 will show a sophisticated analysis of hypothesized relationships between variables (i.e., from left to right sequence) that is referred to as constructs. Because each variable is latent and not directly measured (Hair Jr, Celsi, Money, Samouel & Page, 2015).

Figure 1: Conceptual model Consequently, figure 2 will simplify the model and portray the measured variable. x refers to independent variables, y refers to dependent variables, and z refers to moderation variables. Not to mention, several questions will measure the constructs which in so-called variables and will be shown further in the operationalization table 1 (Hair Jr, et al., 2015). Each construct in figure 2 the thesis will define it further in the operationalization table 1. Not to mention, some constructs in figure 2 have domains and patterns. This will also be defined in the operationalization table 1. Whereas illustrated in figure 2, the six domains of CSR activities on the left (i.e., community support, diversity, employee support, environment, overseas operations, and product) are constructs variables that are further measured by independent variables and also called predictors or exogenous variables which referred by x. The construct on the right (i.e., purchase) is the dependent variable measured by three variables, also called outcome or endogenous variable which referred by y. However, the construct attitude is

more complicated. Because it is both a dependent and independent variable. Whereas, it is the dependent variable because it predicted by the independent variables from the left. It is independent variable because it is predicting the measured construct to the right (i.e., purchase). Not to mention, the construct attitude can not be called exogenous, because it has arrows pointing to it and pointing from it. It can be called endogenous which referred by y and x (Hair Jr, et al., 2015). The plus and plus/minus sign by all the arrows indicate the direction of the relationships (Hair Jr, et al., 2015). Whereas, the direction from attitude to purchase is plus/minus sign. The two patterns of individualism (i.e., horizontal and vertical) are constructs variables that are further measured by moderating variables, which referred by z, affect the direction of the association between another independent variable (i.e., attitude) and an outcome variable (i.e., purchase) (Bennett, 2000). Notwithstanding, a mixture of horizontal and vertical items leads to dominant representations of a construct (Shulruf, Hattie & Dixon, 2003). The thesis will investigate the two patterns as two separate constructs because the distinction is useful when examining the management of social conflicts (Singelis, Triandis, Bhawuk & Gelfand, 1995).

Figure 2: Simplified conceptual model

4 Methodology This chapter explains the research methodology used in the thesis, by establishing considerations such as research approach, research design, data sources, research strategy, practical considerations, and quality criteria.

4.1 Research approach Research approaches primarily used for several reasons, and their process explained in the following section.

4.1.1 Inductive versus deductive research There are three approaches for theory development that are: deduction, abduction, and induction (Saunders, Lewis & Thornhill, 2016). When it is difficult to separate between induction and deduction (Perry, 1998), the abductive approach is a combination of both (Saunders, et al., 2016). On the one hand, inductive research that is also called grounded theory based on empirical data from which the researcher formulates models and theories based on different events in reality, which associate with a qualitative research approach, and it is essential to be aware that some researchers may end up with empirical generalization (Bryman & Bell, 2015; Hair Jr, et al., 2015; Saunders, et al., 2016). On the other hand, deductive research is an analytical approach that reaches to specific instance from a general case, and it is best suited for this thesis since quantitative models and hypotheses guide the empirical research constructed for this thesis before collection or analysis of data derived from pre-existing theories and previous research in the area. However, it is also essential to be aware that deductive research can produce unexpected findings. Because new theoretical ideas may publish, and the data will not be relevant to the hypotheses (Bryman & Bell, 2015; Hair Jr, et al., 2015; Saunders, et al., 2016). In other words, the inductive process in qualitative studies is another alternative position which develops a theory or ends up with empirical generalization after data collection and analysis (Bryman & Bell, 2015). The

deduction process in quantitative studies deduces from the theory that leads to hypotheses which are subject to data collection and translated to findings, the hypotheses are confirmed or rejected based on the revision of theory (Bryman & Bell, 2015). The next section compares the quantitative versus qualitative research.

4.1.2 Quantitative versus Qualitative research It is essential to distinguish between quantitative research and qualitative research because they are fundamentally different (Byrman, 2012; Hair Jr, et al., 2015). By contrast, quantitative data are measurements in which numbers are used directly to represent the properties of something, and the data collected are usually from financial records, sales records, or questionnaires (Hair Jr, et al., 2015). Qualitative data represent descriptions of things that are made without assigning numbers directly such as interviews (Hair Jr, Babin, Money & Samouel, 2003; Hair Jr, et al., 2015). Hence the research elements that are the strength of quantitative research are not typical in qualitative research in term of structure and representativeness (Onwuegbuzie & Leech, 2007). On one side, in the qualitative researcher, it is more unstructured, less representative, and prefers to conduct interviews as a way to go deep into an issue (Hair Jr, et al., 2015). Hence, the researcher cannot predict the specific direction of the interview since the respondents are free to choose their own words in the interview (Hair Jr, et al., 2015). The lack of structure allows identifying the issues that are not revealed by a structured questionnaire (Hair Jr, et al., 2015). Of equal importance, respondents should be highly involved in a desirable situation because discoveries should not be relatively extreme. The researcher subjective opinion must be used to resolve the meaning (Hair Jr, et al., 2003; Byrman, 2012; Hair Jr, et al., 2015). On the other side, in the quantitative research, it is more structured, more representative and quantitative data assist objectivity in which

hypotheses are tested by applying statistical criteria to the measures (Hair Jr, et al., 2015). Moreover, if the observed units supplied the numbers. The researcher opinion does not affect the hypotheses test (Hair Jr, et al., 2003; Hair Jr, et al., 2015). With this in mind, the thesis aims to examine the effect of CSR activities of organic food on consumers’ attitude to purchase in cross- cultures by test-out hypotheses based on gathered data. The deductive approach was used, since the main focus of deductive research is testing the relationships between theory and research analytically (Bryman, 2016; Hair Jr, et al., 2015).

4.2 Research design Research design is the core of a marketing study project (Malhotra, Hall, Shaw & Oppenheim, 2006). It formulates how the project will be carried out and how data will be gathered and analyzed (Malhotra, 2010). Research design can be viewed as a map that links every aspect of the research direction to the research purpose (Aaker, Kumar, Day & Leone, 2010). Whereas, Research designs are grouped into three types (i.e., exploratory, descriptive, and casual) (Hair Jr, et al., 2015). Exploratory research is particularly useful when the decision maker has very little information (Hair Jr, et al., 2003). Hence, it is discovery-oriented (Koua & Kraak, 2004; Malhotra, 2010), and it is involved within highly innovative industries (Hair Jr, et al., 2015). It is mainly utilized for situations where interviews, focus groups, case studies, and secondary data analysis will conduct (Hair Jr, et al., 2003). Moreover, the casual design which may also term as explanatory (Saunders, et al., 2016), is a form of conclusive research design (Malhotra, 2010). It tests whether one event causes the other (Hair Jr, et al., 2015). Whereas, the relationship is changing relatively (Hair Jr, et al., 2015). Several conditions affect this relationship, such as time sequence, covariance, nonspurious association, and theoretical support (Hair Jr, et al., 2015).

Moreover, the research questions focus on cause and effect (Malhotra, 2010). An experiment is appropriate for this design (Malhotra, 2010; Hair Jr, et al., 2015). The descriptive design is also a form of conclusive research design (Parasuraman, Grewal & Krishnan, 2006; Malhotra, 2010). Whereby, it is structured and designed to describe the characteristics of the topic that concern the study which can answer the research question (Hair Jr, et al., 2003; Malhotra, 2010; Saunders, et al., 2016). Hypotheses from theory guide the process to provide what should be measured. Hence, it is often confirmatory (Malhotra, 2010; Hair Jr, et al., 2015). It is also thought of like means and precursor to explanation (Saunders, et al., 2016). Moreover, survey and observation are main methods adopted in descriptive research designs. They involve a structured process (Malhotra, 2010; Hair Jr, et al., 2015). Ideally the thesis employed descriptive research design by measuring the characteristics described in the research question and conducting survey questionnaires.

4.3 Data sources Primary and secondary data are two different data sources (Saunders, Lewis & Thornhill, 2009). It is difficult where both data sources start and finish, because the researcher may decide to rework the data sometime later (Byrman, 2012). By comparison, in secondary data, secondary sources contain data that have been collected previously for a specific purpose (Saunders, et al., 2016). They consist of readily available compiled statistical statements and reports that can be used by the researcher (Krishnaswamy, 2010). Despite the growth of the internet, they might have access to complications (Hair Jr, et al., 2015). Hence several forms of analyses are considered when evaluating secondary sources such as: comparative, longitudinal, and cross-sectional (Hair Jr, et al., 2015). On the other hand, in primary data, it compromises the resource constraints (Hair Jr, et al., 2015). Because, they are more time-consuming,

costly, and lengthy process (Byrman, 2012; Hair Jr, et al., 2015). The collection is by interviews, research through case studies, survey, and experiments (Hair Jr, et al., 2015). With this in mind, they are the primary source of data collection that has not collected before. The data gathered is explicitly for the research project (Krishnaswamy, 2010; Hair Jr, et al., 2015). However, some documents can be data sources or used as a supplement to another source of data (Byrman, 2012; Hair Jr, et al., 2015). In this thesis only primary data will be collected using a web-based survey in order to test all proposed hypotheses and to measure the study’s reliability as well as validity. Hence, a research strategy is needed, to know how the data will be collected and analyzed. This can be done by summarizing the steps to be conducted to achieve the research purpose (Hair Jr, et al., 2015).

4.4 Research strategy After identifying the issue in the thesis, a research strategy is essential to collect information that illuminates the problem (Baker, 2000). In so, research strategy describes how the thesis will be conducted (Hair Jr, et al., 2015). Several strategies used for conducting research, such as formal theory, experiments, computer simulations, field studies, judgment tasks, survey, archival analysis, history, interview, and case study (McGrath, 1981; Yin, 1994). Thus, each strategy has its advantages and disadvantages. There is no such thing as the best strategy, but it is which strategy is more adapted to the study and research question (McGrath, 1981; Yin, 1994). To best use these strategies, three factors should be identified which include: the form of the research question, require control of behavioral events and focus on contemporary events opposed to historical phenomena (Yin, 1994). By considering the research purpose of this thesis and the research question format, the appropriate research strategy is a survey. Whereas, a survey examines the frequency and relationship between variables and describes the phenomenon that has not been observed directly before

(Håkansson, 2013). A survey is an even more appropriate strategy because this thesis investigates contemporary events (i.e., CSR) that are opposed to historical phenomena (i.e., greenwashing) to gain control of the actual behavioral event (i.e., actual purchase). Moreover, survey as a research strategy maximizes the represented sample of the population and generalizability but minimize the realism of context and precision of measurement (McGrath, 1981; Scandura & Williams, 2000). Surveys can be cross-sectional by collecting information from the population at a single point of time to compare findings and identify differences between various clusters or segments, or longitudinal by collecting data over a period of time to compare findings and identify trends (Håkansson, 2013; Hair Jr, et al., 2015). In so the methodology chapter should describe the research design, the variables to be measured, data collection approach, sample, how to collect the data, and the statistical technique which will analyze the data (Hair Jr, et al., 2015).

4.5 Data collection method The nature of the data to be collected depends upon the nature of the thesis along with its research objectives (Hair Jr, et al., 2003; Hair Jr, et al., 2015). If the thesis is exploratory, the researcher is likely to collect qualitative data through focus groups, personal interviews, or by observing behavior or events (Hair Jr, et al., 2003; Gill, Stewart, Treasure & Chadwick, 2008). For example, observation can be either narrative in the form of written description of behavior or recorded on audio or videotape or numerical data by recording events using a structured questionnaire or a device that counts or tracks a specific action (Hair Jr, et al., 2003; Gill, et al., 2008). This role, like others, helps to identify or refine research problems that may formulate and test conceptual frameworks (Kumar, 2019). On the other hand, if the thesis is descriptive, the researcher is likely to collect quantitative data through surveys (Hair Jr, et al., 2015). Whereas,

surveys classified into the telephone, personal interviewing, mail interviewing, and electronic interviewing through self-administration (Malhotra, 2010). The thesis will employ a survey as the main method to collect primary data by electronic interviewing through self-administrated questionnaires based on table 1 operationalization. Similarly, it is the appropriate method because the sample is not located close to the researchers and dispersed (Saunders, et al., 2009). A web-based sample will be collected as it is also fast, replacing traditional methods at a little cost (Pineau & Slotwiner, 2003; Hair Jr, et al., 2015). Hence, WeChat application users in China will be targeted by posting the electronic survey. Facebook is not available in China. Despite that, Facebook pages and groups in Sweden will target by posting the electronic survey. The thesis will also conduct personal interviewing (i.e., face-to-face) through a self-administrated questionnaire on iPad in Sweden and China. Not to mention a cross-sectional survey will collect at a single point of time, and the authors will compare the results from the different clusters (i.e., Sweden and China) (Håkansson, 2013). Whereas, surveys also well define the theoretical models and research problems (Kumar, 2019). Surveys are used to collect primary data from a large sample of individuals such as beliefs, opinions, attitude, lifestyle, and behavior, to general information such as gender, age, education, and income, or company characteristics like revenue and number of employees (Hair Jr, et al., 2003). No to mention, the principle approach of gathering information is to ask questions to people. Their answers formulate the database for analysis (Fowler Jr, 2014). Furthermore the next chapter will describe the sample and population in more details.

4.6 Sample and population Sampling is the preferred method of obtaining information when it is prohibitive in terms of cost and time to obtain such information from the population (Aaker, et al., 2010). The population is a sector of individuals or objects from among which samples selected for research (Singh, 2007).

Whereas, the population is the total elements that share some common set of characteristics. The sample is a relatively small subset of the population (Hair Jr, et al., 2003; Malhotra, 2010). In other words, sampling is the process of selecting such sample groups from a larger population for a survey (Hair Jr, et al., 2015). Researchers should make sure that the selected samples targeted and appropriate representatives of the population (Singh, 2007). Furthermore, sampling design determines whether the thesis should be using a particular sample or not, which sampling approach is best, and how large the sample (Hair Jr, et al., 2003). To achieve all that, the researcher must minimize errors that might occur due to the sampling process (Malhotra, 2010). Hence sampling process should include defining the target population, choosing the sampling frame, selecting the sampling method, determining the sample size, and implementing the sampling plan (Hair Jr, et al., 2003). There are various methods of sampling, one of them is probability sampling, which based on the proposition that each element of the target population has a known, but not necessarily equal probability of being selected, and this is the initial sampling method which will be used in this thesis by targeting Facebook groups and pages also WeChat application (Malhotra, 2010; Hair Jr, et al., 2015). Because of the large sample of elements in China and Sweden that represent the target population of organic food consumers worldwide (Hair Jr, et al., 2015). Not to mention there are different types of probability sampling (i.e., simple random, systematic, stratified, cluster, and multistage) (Hair Jr, et al., 2015). On the other hand, in nonprobability sampling, the exclusion of elements in a sample is left to the researcher’s cautious choice, and this is the additional sampling method which the thesis will use by interviewing people face to face in specific geographical areas that are easy to access by the author and could have high-quality values (Malhotra, 2010; Hair Jr, et al., 2015). Not to mention the nonprobability sampling methods are convenience sampling, judgment sampling, quota sampling, and snowball sampling (Malhotra, 2010;

Hair Jr, et al., 2015). Next, the following subchapter will continue to explain the relevant process of sampling in detail.

4.7 Sampling frame and size The sampling frame is a complete list of elements from which the sample have drawn from the target population (Hair Jr, et al., 2003; Malhotra, 2010; Saunders, et al., 2016). But the target population is not the same as the sampling frame in this thesis. Whereas, the target population is the complete group of elements that are relevant to the thesis (Hair Jr, et al., 2015). The sampling frame is the comprehensive list of elements from which the sample have drawn (Hair Jr, et al., 2015). With this in mind, the thesis will use multistage sampling, because it involves a sequence of stages (Hair Jr, et al., 2015). The first stage is to select the Chinese food consumers in China as a cluster and the Swedish food consumers in Sweden as another cluster. That is to say, in cluster sampling:

“The target population is viewed as being made up of heterogeneous groups, called clusters” (Hair Jr, et al., 2015, pg. 200). The second stage is to conduct probability sampling by selecting a random sample of Facebook groups, pages and ADs, Instagram hashtags and ADs, WeChat application, some telephone numbers, and some email addresses of individuals, private companies, and public sectors from the selected clusters. Not to mention the collected information is from all organic food consumers above the age of 18 and even random sample. Whereas, it is crucial to determine the sample size before the data collection (Hair Jr, et al., 2015; Saunders, et al., 2016). Chaoyang district in Beijing is chosen as a subgroup of the Chinese cluster to start conducting the random sampling because Beijing has the highest consumption expenditure of food that is unprocessed and edible (Stats, 2018a; Stats, 2018b). Specifically near the Lohao city organic goods and food store which its turnover of organic food is rising and is considered one of the largest producers and retailers

throughout China (DaxueConsulting, 2016; Thebeijinger, n.d.). Hence, the Chaoyang district of Beijing has a population of 3,545,000 (BeijingPopulation, 2018). The sample size at 95% confidence level and with a 5% margin of error for the respected population should roughly be 384 (Saunders, et al., 2016). On the other hand, Örebro county in Svealand region is chosen as a subgroup of the Swedish cluster to start conducting the random sampling. Because the public sector in the Örebro county has the highest share of organic food purchases in Sweden with 48% most recently (Mynewsdesk & EcoFoodCenter, n.d.). Specifically, in the city of Karlskoga Degerfors which has the highest percent (i.e., 40%) of organic food purchases in the Örebro county among the public sector (Mynewsdesk & EcoFoodCenter, n.d.). Karlskoga municipality and campus Alfred Nobel of Örebro University in Karlskoga initially targeted for random sampling. Hence, Örebro county has a population of 302 252 (SCB, 2019). The sample size at 95% confidence level and with a 5% margin of error for the respected population should roughly be 384 (Saunders, et al., 2016). With this in mind, when calculating the two populations together into one population, the result is 3 847 252. The sample size for the whole population at 95% confidence level and with a 5% margin of error is 384 (Saunders, et al., 2016). With respect of the cross-cultural comparison, this sample size will divide by two. The minimum sample size is roughly 192 for the Chinese cluster, and 192 for the Swedish cluster. However, the actual sample size ensures that the analysis is undertaken at the level required (Saunders, et al., 2016). The formula is as follow:

Equation 1: Actual sample size (Saunders, et al., 2016).

푎 푛 × 100 (1) 푛 = 푟푒%

In light of the equation above, na is the actual sample size required, n is the minimum sample size, re%, is the estimated response rate (Saunders, et

al., 2016). For most academic studies that involve individuals’ representatives, the response rate is approximately 52.7% with a standard deviation of 20.4 (Baruch & Holtom, 2008; Saunders, et al., 2016). With this in mind the actual sample size for the two cultures together will be 728. With respect of the cross- cultural comparison, the actual sample size will divide by two. The actual sample size is roughly 364 for the Chinese cluster, and 364 for the Swedish cluster. However, achieving the actual sample size or even the minimum sample size of the previous formula can be time-consuming or not possible. The thesis will use the thumb rule to determine sample size, and it is not less than 50 participants for a correlation or regression (Green, 1991; VanVoorhis & Morgan, 2007). The formula is as follow:

Equation 2: Rule of thumb (Green, 1991).

푁 > 50 + 8푚 (2) Whereby, m in the comprehensive equation 2 is the number of independent variables, The sample size should be more than 106, because there are seven independent variables in the thesis. However, in problem-solving research (e.g., pricing, product tests, test-marketing studies, and even TV/radio/print advertising per commercial or ad tested), the minimum sample size is from 150-200 (Malhotra, 2010). The thesis will settle for 200 responses with no missing answers. With respect of the cross-cultural comparison, the thesis will settle for 100 full responses for the Chinese cluster. And 100 full responses for the Swedish cluster. Moreover, the thesis will conduct snowball sampling which also called referral sampling as an additional sampling technique due to the actual sample size that could be difficult to identify (Hair Jr, et al., 2015; Saunders, et al., 2016). This technique will facilitate the location of a rare population (Hair Jr, et al., 2015). Whereby, the initial respondents of the probability sample will help identify other respondents within the target population. This process will continue iterating in the sense that the identified respondents at any stage in

the process are steadily spreading the survey on their own by making use of suitable referrals until the required sample size reached (Hair Jr, et al., 2015). However, this technique could have a bias problem and result in a homogeneous sample (Saunders, et al., 2016). The filter questions in the survey will assure the accuracy of the sampling frame. Furthermore, convenience sampling implies a non-probability sampling method where the sample is drawn according to a group of individuals that may contact easily. This method has criticized as the sampling process, which considered as not random enough (Neuman, 2002; Saunders, Lewis & Thornhill, 2007). But the credibility of results can be higher in gathering answers over a period of time and at different times of the week (Malhotra & Birks, 2007). With this in mind, the thesis will conduct a census on the Swedish cluster by convenience sampling through face-to-face exit interviews with individuals exiting grocery shops, also, face-to-face interviews with students in Örebro university campus and linneuniversitetet Växjö campus, and face- to-face interviews in Ronneby brunnspark. The data collection process started from 31/03/2019 until 23/04/2019 at different times. On the other hand, the thesis will also conduct a census on the Chinese cluster by convenience sampling through interviews with individuals in some office buildings in Chaoyang district. The data collection process started from 31/03/2019 until 18/04/2019 at different times. Moreover, the thesis will do this electronically on an iPad to save the environment. The thesis will also ask the respondents to forward the questionnaire.

4.8 Data collection instrument This subchapter will show sections that describe the questionnaire design, the questionnaire pre-testing, and the formation of the operationalization.

4.8.1 Questionnaire design Information from surveys is accurate only if the questionnaire is perfectly designed (Hair Jr, et al., 2003). Moreover, researchers should note that there is only one opportunity to interact with respondents, and a reasonable period of time is essential if the same respondent contacted again, when mainly it involves another topic or different approach of the exact topic, in so, the outcome is reliable and valid data (Hair Jr, et al., 2003; Hair Jr, et al., 2015). With this in mind the thesis will take two to three weeks’ time period to collect data from respondents. Whereas, Questionnaire design consists of interrelated steps that are used to improve decision making (i.e., initial consideration, clarification of concepts, typology of the questionnaire, pretesting a questionnaire, and administering a questionnaire) (Hair Jr, et al., 2003; Hair Jr, et al., 2015). Initial consideration clarifies the nature of the research problem and the objectives, develops research questions to converge research objectives, identifies potential respondents, determines sampling approach and size, and decides about the method of data collection (Hair Jr, et al., 2003; Hair Jr, et al., 2015). Ideally all these points considered in the thesis. Moreover, clarification of concepts ensures that the concepts can be clearly defined, chooses the indicators, variables to represent the concepts, and defines the level of measurement (Hair Jr, et al., 2003; Hair Jr, et al., 2015). Figure 1 and 2 earlier, clarifies the concept for the thesis. Furthermore, typology of questionnaire determines which type of questions should be included and their order, ensures the wording and coding of questions, decides on how to group the questions and the total length of the questionnaire, and determines the layout and structure of questionnaire (Hair Jr, et al., 2003; Hair Jr, et al., 2015). Ideally the operationalization in table 1 after the following section and the survey in Appendix 1 portrays the typology of the questionnaire. Whereas, the double-barreled question can be confusing and result in ambiguous responses because more than two questions combined

into one. To obtain the required information more than two distinct questions will be asked (Malhotra, 2010). Moreover, pretesting the questionnaire decides on the nature of pretesting the preliminary questionnaire, identifies limitations of the preliminary questionnaire by analyzing initial data, and refine the questionnaire (Hair Jr, et al., 2003; Hair Jr, et al., 2015). The questionnaire for this year will pre-test, and the following section will describe pre-testing in detail. Whereas, administering a questionnaire identifies the best practice to be utilized, audits and trains field works, ensures that the process is correct, and determines the follow-up and deadline methods (Hair Jr, et al., 2003; Hair Jr, et al., 2015). Administering questionnaire which the thesis will utilize includes mail, overnight delivery, face to face, and other internet channels (Hair Jr, et al., 2015).

4.8.2 Pre-test Pre-tests are administered to ensure that the questions asked are mirrors to the field of study, and link together with the study’s expectations (Aaker, et al., 2010). This assure that the collected data are reliable and valid (Hair Jr, et al., 2015). Therefore, scales should be adopted based on an expert’s evaluation (Hair Jr, et al., 2015). It is essential to discuss the questions with an expert within the field even if the researcher has an experience with the topic, mainly if it uses different respondents, if it is translating to another language, and if it is a lengthy questionnaire (Saunders, et al., 2009; Hair Jr, et al., 2015). Also, pretesting achieved by testing the questionnaires on a sample of respondents that has characteristics similar to the target population. This can be easily done because it is a consumer survey, hence its respondents are mostly available (Hair Jr, et al., 2015). Because, researchers can sometimes make mistakes while designing the questionnaires if they overlook some essential steps (Hair Jr, et al., 2015). While pre-testing open-ended questions should be asked on each part of the questionnaire, such as instructions, scaling, and wording to assure that the questions are relevant and precise (Malhotra, 2010; Hair Jr, et

al., 2015). Also, if it should use in a specific geographical location, whether an internet, telephone, or in person approach. If the sample size is appropriate, and if coding and analysis process of responses appropriate (Hair Jr, et al., 2015). Moreover, the questionnaire will evaluate by one lecturer from Linnaeus university to improve the survey design in order to avoid some misinterpretations in the survey from respondents. The authors will pre-test the questionnaire with a small sample of respondents from the two clusters. However, if the revision involves an extensive rewarding. A pilot test should also be conducted which will require a much larger sample of respondents for assessment (Hair Jr, et al., 2015).

4.8.3 Operationalization The theories and predictors for the variables in this thesis will present in the following operationalization in table 1. The operationalization will show which theories are used to support the questions that are observed and measured variables. The operationalization table 1 will consist of four columns: The theoretical concept that shows which theories selected for the thesis. Moreover, the conceptual definition of the theories. The operational definition that shows the relationship between the dependent variable which is the effect or what the thesis is trying to understand, explain or predict, and the independent variables which is the cause or the characteristics that explain or influence the dependent variable (Hair Jr, et al., 2015). Also, the operational definition will cite the studies which the items adopted. The questions of the survey will show in table 1. Notwithstanding, the moderator and mediator have shown in the operationalization table 1. The thesis will explain them in more details further in this chapter. However, control questions in the survey will not include in the operationalization, which about whether one has purchased organic food before or not, nationality, gender, age group, education level, and income group. Hereunder is table 1 operationalization.

Table 1: Operationalization.

Theoretical Conceptual definition Operational definition Questions concept Purchase Actual purchase Purchase is a dependent 1- How much have behavior is variable that measures you spent on “Individual’s readiness the degree to which one organic food in the and willingness to has a behavior of buying past week? purchase a certain organic food, using the 2- How much are product or service” following scale for three you willing to pay (Ajzen, 1985; Omar, items (Voon, et al., for organic food, Mat, Imhemed & Ali, 2011): compared to 2012). Q1- $0-6, $7-12, $13-18, conventional food? $19-24, more than $24 3- How many times Q2- 0-25%, 26-50%, 51- have you consumed 75%, 76-100%, more organic food in the than 100% past week? Q3- 0-1 time, 2-3 times, 4-5 times, 6-7 times, more than 7 times. Attitude “A person’s positive or Attitude is the mediating 1- I perceive organic negative feelings about variable that measures food brands to have an action in general” the conveying a better reputation. (Vahdati, et al., 2015) information from 2- I perceive organic independent variables food brands to have (i.e., CSR activities) to high fit cause. the dependent variable 3- I have a personal (i.e., purchase) using the connection to the 5-point Likert scale cause that is (Bhattacharya & Sen, represented by 2004): organic food 1- Strongly disagree. brands’ CSR 5- Strongly agree. initiatives. Community Community is Community support 1- Organic food support “Solidarity, which domain is the brands should implies a common independent variable determine

identity and set of that measures the sponsoring charities shared norms and influence of CSR and supporting the values” through community economically (Bhattacharyya, 2004; support activities in disadvantaged Bradshaw, 2008). organic food brands groups in the using the 5-point Likert community. scale (Bhattacharya & 2- Organic food Sen, 2004; Vives, 2006; brands should Anselmsson & determine Johansson, 2007): supporting 1- Strongly disagree. educational and 5- Strongly agree. training programs about agriculture for enterprises in the community. 3- Organic food brands should determine supporting sport, art, and cultural activities in the community. Diversity “Diversity includes all Diversity domain is the 1- Organic food characteristics and independent variable brands should experiences that define that measures the determine providing each of us as influence of CSR minorities with individuals” (Diversity through diversity more employment Task Force, 2001). activities in organic food opportunities. brands using the 5-point 2- Organic food Likert scale (Sen & brands should Bhattacharya, 2001; determine setting up Bhattacharya & Sen, regulations against 2004; Anselmsson & the discrimination Johansson, 2007; of age, gender, and race.

Emmott & Worman, 3- Organic food 2008): brands should 1- Strongly disagree. determine setting up 2- Strongly agree. regulations against the discrimination of religion, belief, and culture. Employee “Programs cultivate Employee support 1- Organic food support affective domain is the brands should organizational independent variable determine concerns commitment by that measures the for employees’ enabling employees to influence of CSR safety. receive support” through employee 2- Organic food (Grant, Dutton & support activities in brands should Rosso, 2008). organic food brands determine concerns using the 5-point Likert for employees’ job scale (Sen & security. Bhattacharya, 2001; 3- Organic food Bhattacharya & Sen, brands should 2004): determine concerns 1- Strongly disagree. for sharing profits 2- Strongly agree. with their employees. Environment “Whatever exist in the Environment domain is 1- Organic food surroundings of some the independent variable brands should being that is relevant to that measures the determine their the state of that being influence of CSR products to be at a particular through environment environmentally- moment” (Harvey, activities in organic food friendly. 1993). brands using the 5-point 2- Organic food Likert scale brands should (Bhattacharya & Sen, determine 2004): conducting 1- Strongly disagree. recycling and 2- Strongly agree.

hazardous waste management. 3- Organic food brands should determine testing animals from disease. Overseas “Multinational is the Overseas operations 1- Organic food operations presence of domain is the brands should international independent variable determine concerns production and the that measures the for equal human characteristics of the influence of CSR rights in non- parent company” through overseas domestic (Millington & Bayliss, operations activities in operations. 1990). organic food brands 2- Organic food using the 5-point Likert brands should scale (Kolk, 2005; determine concerns Anselmsson & for exploiting child Johansson, 2007): labor and supplying 1- Strongly disagree. education for them 2- Strongly agree. in non-domestic operations. 3- Organic food brands should determine supporting donations to non- profit organizations in overseas. Product “Any item introduced Product domain is the 1- Organic food into the stream of independent variable brands should commerce, including that measures the determine the intangible or influence of CSR conducting research intellectual aspects of through product and development. activities in organic food

the item” (Lannetti, brands using the 5-point 2- Organic food 2000). Likert scale brands should (Bhattacharya & Sen, determine 2004): conducting 1- Strongly disagree. marketing and 2- Strongly agree. innovation. 3- Organic food brands should determine conducting contracts to avoid controversies and antitrust disputes. Individualism “Political and social Individualism horizontal 1- I take care of horizontal philosophy that places is a positive moderator myself and the high value on the that moderate the immediate families freedom of the attitudes towards CSR only. individual and activities in organic food 2- I would rather generally stresses the brands on consumers’ depend on myself self-directed, self- purchase using the 5- than others. contained, and point Likert scale 3- I rely on myself comparatively (Triandis & Gelfand, most of the time and unrestrained individual 1998; Shulruf, et al., I rarely rely on or ego” (Realo, Koido, 2003; Lee & Choi, others. Ceulemans & Allik, 2005): 2002). Horizontal 1- Strongly disagree. pattern assumes that 2- Strongly agree. oneself is more or less like every other self (Triandis, et al., 1990; Triandis, et al., 1995).

Individualism “Political and social Individualism vertical is 1- It is important vertical philosophy that places a positive moderator that that I do my job high value on the moderate the attitude better than others. freedom of the towards CSR activities 2- Competition is individual and in organic food brands the law of nature. generally stresses the on consumers’ purchase 3- When another self-directed, self- using the 5-point Likert person does better contained, and scale (Triandis & than I do, I get tense comparatively Gelfand, 1998; Lee & and aroused. unrestrained individual Choi, 2005): or ego” (Realo, et al., 1- Strongly disagree. 2002). The vertical 2- Strongly agree. pattern consists of hierarchies and assumes that oneself is different from other selves (Triandis, et al., 1990; Triandis, et al., 1995)

4.9 Survey design In this thesis a survey is employed as the main method to collect primary data (Malhotra, 2010). The principle approach to gathering information is to ask questions to people, and their answers formulate the database for analysis (Fowler Jr, 2014). Whereas, the classification of surveys is: telephone, personal interviewing, mail interviewing, and electronic interviewing through self-administration (Malhotra, 2010). This thesis uses electronic self- administered questionnaires based on table 1 operationalization, which is the appropriate method because the sample is not located close to the researchers or is very dispersed (Saunders, et al., 2009). Also the web-based sample collected as it is fast, replacing traditional methods (Pineau & Slotwiner, 2003).

Whereas, the categorization of a survey can roughly be: census survey and sample survey (Singh, 2007; Malhotra, 2010). Census survey refers to the data collection process that is supposed to reach each of individuals of the population of interest, while sample survey refers to the data collection process that is conducting with the selected sample (Singh, 2007; Malhotra, 2010). In this thesis both categories employed because the data collection process with the selected sample is challenging to obtain. Furthermore, the structured-direct survey is the most widely applied data collection method in the field of marketing research. It is presented and formulated as an administrated questionnaire with fixed alternative questions (Malhotra, 2010). For this thesis questions the five-point Likert scale used, and the respondents will express their opinion from strongly disagree (1) to strongly agree (5) (Saunders, et al., 2016; Bryman, 2016). With this in mind, eighteen items are used to measure the activities of the independent variables. Which are: community support, diversity, employee support, environment, overseas operations, and product. Also, three items are used to measure the mediator, which is considered a dependent and an independent variable. Six items are used to measure the patterns of individualism, which used as a moderator on the relationship between the independent variable (i.e., mediator) and dependent variable (i.e., purchase). Moreover, three items are used to measure the dependent variable (i.e., purchase). All the items used in the survey uses multiple-choice questions and measured by previous scientific articles, which identify the main variables. Not to mention the questionnaire also uses multiple-choice questions regarding previous consumption experiences and for necessary personal information.

4.10 Data analysis method The survey will collect the primary data of the thesis, and then all the answers will be coded into the statistical program SPSS, to examine CSR domains as

determinant factors influencing consumers’ attitude to purchase organic food brands. The next section in the thesis will describe in details data coding and the appropriate data analyses methods.

4.10.1 Data Coding The respondents’ answers will be in SPSS added (Malhotra, 2010). Therefore, it is essential to code data of the thesis where the answers of the structured and unstructured questions will translate into numbers (Aaker, et al., 2010; Saunders, et al., 2016). This approach is called dummy variable coding (Hair Jr, et al., 2015). Hence, the coded information will be used in the thesis in order to facilitate quantitative analysis (Saunders, et al., 2009). Missing values eliminated from the data coding process. Coupled with, errors might accrue when completing the questionnaire, coding, or during data entry. The coded questionnaires and the actual database will be checked if there are any coding or data entry errors (Hair Jr, et al., 2015).

4.10.2 Sample demographics and descriptive analysis Sample demographic analysis is useful when describing the information about the study’s respondents (Aaker, et al., 2010). In this thesis the demographic information included is the respondents’ characteristics such as age, gender, nationality, education level, and income. All these information are illustrated in frequencies numbers by graph bars to describe and obtain an understanding of the data (Malhotra, 2010; Hair Jr, et al., 2015; Saunders, et al., 2016). Furthermore, the thesis will portray descriptive statistics of frequency distribution of all independent, moderator, mediator, and dependent variables with all their items to also describe and obtain an understanding of the data by measures of central tendency (i.e., mean), because these variables use metric scales (Hair Jr, et al., 2015). The descriptive statistic will illustrate the measures of dispersions which describe the tendency of responses to depart from central tendency by Skewness and Kurtosis, because skewness and kurtosis are also measures of shape, and they are useful in understanding the

nature and the shape of distribution (Malhotra, 2010; Hair Jr, et al., 2015). By comparison, skewness measures the departure from balanced, symmetrical distribution (i.e., 0), not to mention, larger than +1 or smaller than -1 substantially skewed distribution (Hair Jr, et al., 2015). While kurtosis measure if there is substantial peakedness (i.e., +1) or flatness (i.e., -1) of distribution for the normal curve (i.e., 0) and the original output from SPSS of each cluster is in appendix 3 and 4 (Hair Jr, et al., 2015). Not to mention, the thesis will illustrate the differences in two means using the t-test for independent samples (i.e., Chinese and Swedish). The original output from SPSS is in appendix 2 (Hair Jr, et al., 2015). Another key thing to remember, the one-tailed test is preferably more than the two-tailed test when the hypotheses have a direction (Malhotra, 2010; Hair Jr, et al., 2015). Hence there is no chance that a relationship does not exist when, in fact, one does (Hair Jr, et al., 2015). With respect of the theoretical framework, variables of hypotheses 1 and 3 will be compared using the one-tailed test. But variables of hypothesis 2 will be compared using the two-tailed test. Not to mention the mean levels should be significantly different by <.05 (Hair Jr, et al., 2015).

4.10.3 Exploratory factor analysis Factor analysis simplifies the understanding of data by summarizing the information from a large number of variables based on their latent relationships into a small number of factors, in so, variables are combined by exploring patterns to identify factors (Malhotra, 2010; Hair Jr, et al., 2015). With large data SPSS is needed to conduct factor analysis (Malhotra, 2010; Hair Jr, et al., 2015). For the thesis this technique will be used to analyze only the independent variables (i.e., CSR activities) into 6 factors (Malhotra, 2010; Hair Jr, et al., 2015), and the estimation based on the ability to logically name the resulting factors that are supportable and theoretically sound (Malhotra,

2010; Hair Jr, et al., 2015). In so, the items of each independent variable summarized in a factor (Malhotra, 2010; Hair Jr, et al., 2015). Each factor is a combination of the variables that account for the variance that is a linear combination of variables (Malhotra, 2010; Hair Jr, et al., 2015). Moreover, retaining factors should meet a minimum latent root criterion of 1 which also called eigenvalue, and total variance of all factors should be more than 60%, which also called trace (Malhotra, 2010; Hair Jr, et al., 2015). Communality refers to how much of variance in a particular variable (Hair Jr, et al., 2015). Arguably, the principal component factor analysis utilizes the entire variation in all the variables (i.e., error variance, unique variance, and common variance). The common factor analysis utilizes only the common variance in a factor solution (Malhotra, 2010; Hair Jr, et al., 2015). The common variance is the portion of the total variance which is shared by all the original variables in the analysis, the unique variance is the portion of the total variance that is specific to one variable, and the error variance is the portion of variance the is a result of an error (Hair Jr, et al., 2015). With this in mind the thesis will conduct principal component factor analysis because it is the most commonly used approach in business research (Hair Jr, et al., 2015). However, the initial principal component is unrotated. This produces factors that are uncorrelated and difficult to interpret (Malhotra, 2010). Notwithstanding, the rotated solution is relevantly essential. The orthogonal solution produces rotated factors that the correlation between them is 0 (Malhotra, 2010). Similarly, choosing the oblique solution permits the factors to be correlated (Malhotra, 2010; Hair Jr, et al., 2015). Varimax rotate the initial factor solution, but it is the most widely used (Hair Jr, et al., 2015). However, a negative loading means that there is no relationship. This is mostly orthogonally independent (Hair Jr, et al., 2015). Moreover, to interpret the factor solution. Values that are below .30 should not be shown, and this is called an easy read matrix (Hair Jr, et al., 2015). With this in mind, the factor loading determines to name the factors. If

loadings are relatively high in more than one factor, the variable should be excluded, and this situation is referred to as cross-loading (Hair Jr, et al., 2015). Furthermore, it is applicable to use the factors in multiple regression analysis to see if the factors accurately predict a single dependent variable (Hair Jr, et al., 2015). The next chapter will describe the regression analysis in detail.

4.10.4 Regression analysis Regression measures the linear relationship between two or more variables (Hair Jr, et al., 2015). There are different forms of regression (i.e., bivariate, multiple, and logistic regression). Whereby, Bivariate and multiple regression analyze metric variables. Logistic regression can have non-metric variables and similarly discriminant analysis (Hair Jr, et al., 2015). Bivariate regression, multiple regression, ANOVA and MANOVA are used for the interdependence techniques, after the independence technique of factor analysis which described in the earlier section (Hair Jr, et al., 2015). Whereby, multiple regression includes several metric independent variables and a single metric dependent variable (Malhotra, 2010; Hair Jr, et al., 2015). Multiple regression will measure the linear relationship between CSR activities and attitude. Not to mention, each CSR domain which has three variables will compute into one variable for each domain. There will be six independent variables, and the dependent attitude variables will compute into one variable. Similarly, another multiple regression will measure the linear relationship between attitude and purchase. The moderated attitude (i.e., by individualism patterns) and purchase also (Bennett, 2000). Not to mention, each individualism pattern, which has three variables, will compute into one variable for every pattern. Each of the computed individualism patterns will be computed with attitude. In so, the result will be two independent variables

that should have a positive relationship with the dependent variable purchase. Third independent variable that has an either negative or positive relationship with the same dependent variables (i.e., purchase) also. Not to mention the next subchapter will describe the moderating and mediating effects in detail. Moreover, regarding the other personal information (i.e., gender, age group, education level, and income group), they will be included in the multiple regression along with the other variables. Regression will describe whether the hypothesized relationships can confirm as being true and determine if these relationships differ between the two samples (i.e., Chinese consumers versus Swedish consumers) (Hair Jr, et al., 2015).

4.11 Moderating and mediating effects Many researchers have included mediation and moderation technique in their studies (Jose, 2013). Mediate is to settle the differences and serve as the medium for effecting a result or conveying information (Bennett, 2000; Jose, 2013). In so, mediating conveys information from the independent variable to the dependent variable (Jose, 2013). It is the conduit or medium information between the independent variable and dependent variable (Jose, 2013). Hence it helps to pass information from one part to another (Jose, 2013). On the other hand, to moderate is to make less extreme and preside over (Bennett, 2000; Jose, 2013). Moderation is buffering in a way that makes a relationship less strong or exacerbating in a way that makes something stronger (Jose, 2013). Hence, both moderator and mediator affect the relationship between the independent variable and dependent variable (Bennett, 2000). Both mediating and moderating can illustrate in regression (Jose, 2013). This thesis will use the Attitude as mediator and Individualism as moderator. Whereas, the mediating effect will compute in SPSS by referring to Attitude as a dependent variable then as an independent variable. The moderating effect will be computing in SPSS by multiplying Individualism Horizontal variables and Individualism Vertical variables with the

independent variable (i.e., attitude). The following subchapter will describe the quality criteria of the thesis.

4.12 Quality criteria The quality of findings is essential for every academic research. Hence it is crucial to use reasonable measures when applying quality standards. Whereby, the accuracy associated with the term validity. Consistency is associated with the term reliability (Hair Jr, et al., 2003). The following section will describe the validity and reliability in detail.

4.12.1 Validity There are various and different ways of testing measurement validity. In so, face validity involves a systematic but subjective assessment of a scale’s ability to measure what it is supposed to measure, hence encourage participation in the survey (Greener, 2008; Malhotra, 2010). Two scholars at Linnaeus university who are familiar with the field of research will check the questionnaire for face validity. Moreover, construct validity involves assessing what the scale is measuring, which conforms to the theoretical expectation (Hair Jr, et al., 2003; Malhotra, 2010). Internal validity involves causality when there is an association between two independent variables and the dependent variable (Greener, 2008). Not to mention the term validity itself refers to if the measurement of a concept or construct is accurate (Hair Jr, et al., 2015; Bryman, 2016). In so, the validly of the variables of this thesis will be tested further by the results of the Pearson’s correlation coefficients tests according to table 2, which can also be called validity criterion by evaluating the relationship between variables and to what extent this relationship is strong (Malhotra, 2010; Hair Jr, et al., 2015). Correlation techniques help to determine if there is a consistent and systematic relationship between two or more variables (Hair Jr, et al., 2015). Not to mention when the correlation coefficients asses this link, it is also called covariation (Hair Jr, et al., 2015). Arguably, the

correlation coefficient is standardized. But covariances are not standardized hence challenging to compare (Hair Jr, et al., 2015). Not to mention standardization is:

“A method of adjusting for different units of measure across variables” (Hair Jr, et al., 2015, pg. 381). Moreover, Pearson correlation is used in this thesis. It measures the linear association between two metric variables that are interval or ratio scaled measures (Malhotra, 2010; Hair Jr, et al., 2015). Whereas, four concepts should describe this relationship, such as presence, nature of the relationship, direction, and strength of association (Hair Jr, et al., 2015). The presence is that there is a relationship between variables that is statistical significance and labeled as p-value, not to mention, when the probability at least <.05, this mean that there are five chances of one hundred that it is wrong to say that there is a correlation, or in some instance <.01. The nature of the relationship means that whether the relationship is linear (i.e., the relationship between variables remain the same) or nonlinear (i.e., the relationship between variables change). The direction of the relationship is either negative (i.e., strongly disagree) or positive (i.e., strongly agree). The strength of association between two variables are either slight (i.e., the relationship is not present), small but definite, moderate, high, or very strong, and the rule of thumb about correlation coefficient size are described in table 2 to characterize the strength of association between variables.

Table 2: Rules of thumb of correlation coefficient size (Hair Jr, et al., 2015).

Coefficient range Strength of association ± (.91 – 1.00) Very strong ± (.71 - .90) High ± (.41 - .70) Moderate ± (.21 - .40) Small but definite relationship ± (.00 - .20) Slight, almost negligible

However, if the values in Pearson’s correlation analysis exceeded 0.9, this will indicate multicollinearity, which means that the constructs would correlate too much with each other (Malhotra, 2010). 0.8 will consider as valuable results (Malhotra, 2010; Bryman & Bell, 2015). Because, the results should be in a positive value and not slight. Some hypotheses emphasize a growing relationship. In so, if the correlation between variables is small. Factor analysis may not be appropriate (Malhotra, 2010). Not to mention variables that highly correlate with each other would also highly correlate with the same factor. Predetermined criteria will also assure through filter questions (Greener, 2008; Hair Jr, et al., 2015). Whereby, at the beginning of the questionnaire the respondents will be asked if they have purchased organic food before or not. The second question if they are Swedish or other nationality for the Swedish cluster survey and if they are Chinese or other nationality for the Chinese cluster survey. Neither, if they answered that they had not purchased organic food before, nor if the answer is neither Chinese nationality nor Swedish nationality. They will have to exit the survey. The term Reliability described in the next section.

4.12.2 Reliability The main concern of reliability is dealing with the measures’ consistency (Malhotra, 2010; Hair Jr, et al., 2015; Bryman, 2016). Hence, reliability is associated with multi-item scale (Hair Jr, et al., 2003; Malhotra, 2010). The scores for the items of the scales should correlate (Malhotra, 2010; Hair Jr, et al., 2015). Whereas, the stronger the correlation, the higher the reliability scale (Malhotra, 2010; Hair Jr, et al., 2015). The weaker the correlation, the less reliable the sale is (Malhotra, 2010; Hair Jr, et al., 2015). In so, internal consistency reliability is used to assess a summated scale where items are summed to form a total score for a construct (Malhotra, 2010;

Hair Jr, et al., 2015). There are different types of internal consistency reliability (Hair Jr, et al., 2015). Split-half reliability which the researcher split the scale items in half and correlate the two sets of items (Malhotra, 2010; Hair Jr, et al., 2015). The other type is called Cronbach’s alpha which calculates the coefficient of the split half (Malhotra, 2010; Hair Jr, et al., 2015). Hence, the composite reliability is considered more accurate than the coefficient alpha (Hair Jr, et al., 2015). The thesis will use this method if the Cronbach’s alpha has poor strength of association. Notwithstanding, it is similar to coefficient alpha. It calculates the items individually. Whereas, the standardized loadings should have a value of at least .7. Loadings below .4 removed (Hair Jr, et al., 2015). This method is suitable when a multiple-item measure is existing, and respondents have to answer multiple questions leading to an overall score that may increase the risk of non-relation between indicators. Therefore, criteria have to be done to avoid a lack of coherence. The formula for composite reliability is:

Equation 3: Composite reliability (Raykov, 1997).

2 (3) (∑ 휆픦) 퐶푅 = 2 (∑ 휆픦) + (∑ 휖픦) Whereas, 휆 is the standardized factor loading for 픦, and 휖 is the error variance for 픦. The formula for error variance is:

Equation 4: Error variance (Raykov, 1997).

2 (4) 휖픦 = 1 − 휆픦 Furthermore, there are different values for Cronbach’s Alpha coefficient. Their rules of thumb illustrated in table 3 below as an indicator to accept or reject the reliability in the thesis (Malhotra, 2010; Streiner, Norman & Cairney, 2015; Hair Jr, et al., 2015; Bryman & Bell, 2015).

Table 3: Rules of thumb of Cronbach's alpha coefficient size (Hair Jr, et al., 2015).

Alpha range coefficient Strength of association < .6 Poor .6 to < .7 Moderate .7 to <.8 Good .8 to <.9 Very good .9 to .95 Excellent ≥.95 Too high, items are redundant

5 Results and analyses This chapter breaks the results of the questionnaire into constituent parts and looks in depth at each of these parts.

5.1 Pilot study The authors used a pilot study to test the reliability and validity of the scales (Hair Jr, et al., 2015). Coupled with, the minimum sample size is at least two to one and preferably larger (Hair Jr, et al., 2015). Ten scaled items are going to be evaluated. Hence the pilot study compound of 30 responses with no missing values from 31-Mar-2019 18:11:01 until 4-Apr-2019 11:45:55.

5.1.1 Reliability Three items measure each construct in the thesis. Moreover, Cronbach’s alpha calculates the average of the coefficient from possible combinations (Hair Jr, et al., 2015). Table 5 below illustrates the Alpha values of each construct. Not to mention the thesis will conduct composite reliability on the constructs that have alpha value with poor strength of association.

Table 4: Cronbach's alpha reliability

Standardized construct Alpha value Community support .636 Diversity .712 Employee support .713 Environment .580 Overseas operations .736 Product .766 Individualism horizontal .637 Individualism vertical .759 Attitude .781 Purchase .867

Notwithstanding, table 4 illustrates that community support and individualism horizontal has alpha values that are less than .7. Mainly researchers consider an alpha of .7 as a minimum. Hence a lower coefficient may be acceptable (Hair Jr, et al., 2015). However, table 4 above illustrates that the environment construct has a poor strength of association. It is essential to conduct its composite reliability because it is a more accurate test (Hair Jr, et al., 2015). Moreover, the rotated factor analysis based on eigenvalues greater than 1. Table 5 below illustrates the standardized factor loadings of “Environment” which the thesis will use in the formula.

Table 5: Factor analysis for composite reliability

Rotated Component Matrix Component Items 1 2 3 4 5 6 Zscore: O O 1 .815 Zscore: Diversity 2 .760 Zscore: Diversity 3 .704 .353 Zscore: O O 2 .693 .354 Zscore: Attitude 2 .643 .455 Zscore: Attitude 1 .543 .326 .476 Zscore: Attitude 3 .494 .454 -.352 Zscore: E S 2 .824 Zscore: C S 3 .681 .359 Zscore: E S 1 .622 .542 Zscore: E S 3 .542 .437 Zscore: E 2 .842 Zscore: E 1 .777 Zscore: Product 2 .870 Zscore: Product 3 .329 .360 .740 Zscore: Product 1 .311 .306 .707 Zscore: E 3 .848 Zscore: Diversity 1 .719 Zscore: O O 3 .454 -.315 .545 -.337 Zscore: C S 1 .809 Zscore: C S 2 .385 .672

Whereas, from table 5 above, component 4 illustrates the standardized factor loadings of “Environment” that will be in the composite reliability formula. Table 6 below illustrates the composite reliability result.

Table 6: Composite reliability

Standardized measured construct Composite reliability Environment .81785108

Ideally, table 6 above illustrates that “Environment” scales are reliable. Researchers also consider .7 as a minimum coefficient to accept composite reliability (Hair Jr, et al., 2015).

5.1.2 Validity Pearson correlation coefficient will test the validity of the standardized constructs which have been measured by three questions and computed into one item for the correlation coefficient test. Table 7 below is the first validity test that illustrates the correlation coefficient of the standardized and measured constructs with the other standardized and measured constructs that should have a direct relationship and should all be statistically significance to demonstrate a presence of a relationship.

Table 7: Pearson’s Validity test 1

Correlations C S Diversity E S E O O Product Attitude C S 1 Diversity .415* 1 E S .432** .447** 1 E .243 .419* .366* 1 O O -.043 .465** .152 -.008 1 Product .368* .258 .334* .245 .207 1 Attitude -.023 .492** .173 .417* .387* .145 1 *. Correlation is significant at the 0.05 level (1-tailed). **. Correlation is significant at the 0.01 level (1-tailed).

Arguably, table 7 above illustrates that there is no presence of a relationship that is statistically significant between some variables. There is with other variables. Hence the questions are not entirely valid. Table 8 below is the second validity test that illustrates the correlation coefficient of the standardized and measured constructs with other standardized and measured constructs that has no direct relationship, but should all be statistically significant to demonstrate a presence of a relationship.

Table 8: Pearson’s Validity test 2

Correlations Attitude Purchase Attitude 1 Purchase .544** 1 **. Correlation is significant at the 0.01 level (2-tailed).

Ideally, table 8 above illustrates that there is a presence of a relationship that is statistically significant between the variables. The questions are valid.

Table 9 below is the third validity test that illustrates the correlation coefficient of the standardized and measured constructs with other standardized and measured constructs that has a moderated direct relationship and should be statistically significant to demonstrate a presence of a relationship.

Table 9: Pearson’s Validity test 3

Correlations Moderator Horizontal Moderator Vertical Purchase Moderator Horizontal 1 Moderator Vertical .654** 1 Purchase .254 .134 1 **. Correlation is significant at the 0.01 level (1-tailed).

Arguably, table 9 above illustrates that there is no presence of a relationship that is statistically significant between some variables. There is with other variables. hence the questions are not entirely valid. Despite the unexpected results of validity tests mentioned above, the questionnaire is still valid. They have been tested with a professional researcher and been tested face-to-face with few individuals from the targeted sample. Not to mention the questionnaire measured by previous studies cited in the operationalization table earlier in the methodology chapter.

5.2 Descriptive statistics The thesis will describe the demographic information and other variables, with respect of comparison between the Chinese cluster and the Swedish cluster.

5.2.1 Socio-demographic profile of respondents Figure 3 below portrays a graph bar for the gender of the respected clusters to assist the analysis and demonstrate a cross-cultural comparison.

Gender 70 59 60 57

50 43 41 40

0 China Sweden

Male Female

Figure 3: Gender By comparison, figure 3 above portrays that the Chinese cluster has the majority of male responses. The Swedish cluster has the majority of the female responses. Whereas, women internally focused on people and men are externally focused on payment (Lakshmi, et al., 2017). The Chinese culture externally focused on payment, and the Swedish culture internally focused on people.

Figure 4 below portrays a graph bar for the age groups of the respected clusters. it assists analysis and demonstrate a cross-cultural comparison.

Age 40 34 35 35 30 25 21 21 20 17 18 15 15 14 15 10 10 5 0 China Sweden

18-25 26-30 31-40 41-50 Above 50

Figure 4: Age By comparison, figure 4 above portrays that the Chinese cluster has the majority of responses that are from the age group 26-30 and 41-50. The Swedish cluster has the majority of responses that are from the age group 18- 25, 31-40, and above 50. Whereas, younger consumers who are from generation z and the millennial consumer are more willing to pay the premium for healthy attributes than other generations (Nielsen, 2015). The Chinese culture is less willing to pay a premium for organic food brands that employ CSR activities as a marketing strategy than the Swedish culture. Whereas, this demonstration is general because the imposed age group choices are different from the theoretical background. Willing to pay more is analyzed further in this chapter. Figure 5 below portrays a graph bar for the education level of the respected clusters to assist analysis and demonstrate a cross-cultural

comparison.

Education 60 51 50 43 40 31 30 27 21 21 20

10 5 1 0 China Sweden

Elementary school Upper secondary school Bachelor Master

Figure 5: Education By comparison, figure 5 above portrays that the Chinese cluster has the majority of responses that are from only the elementary and master’s educational levels. The Swedish cluster has the majority of responses that are from the upper secondary and bachelor educational level. Whereas, the education segment should consider because the information on the labels must be easy to understand and clear for the consumers (Nielsen, 2015). The Chinese culture are more able to understand the determinants of CSR in organic food brands than the Swedish culture, because the Chinese have the high educational level. Figure 6 next portrays a graph bar for the income groups of the respected clusters to assist analysis and demonstrate a cross-cultural

comparison.

Income 45 40 40 35 33

30 26 25 22 21 20 18 14 13 15 11 10 5 2 0 China Sweden

$0-1000 $1001-2000 $2001-3000 $3001-4000 Above $4000

Figure 6: Income By comparison, figure 6 above portrays that the Chinese cluster has the majority of responses that has a monthly income that is only between $0 to $2000. The Swedish cluster has the majority of responses that has a monthly income that is above $2000. Whereas, the higher consumers’ income is, the more consumers’ demand for organic and high-quality food (Bekele, et al., 2017). The Swedish culture has more demand for organic food brands that employ CSR activities as a marketing strategy than the Chinese culture.

5.2.2 Descriptive for other variables Table 10 below illustrates a comparison of the means that are measures of tendency using independent sample T-Test, and the shape of dispersion that departs from the central tendency in the Chinese cluster and the Swedish cluster. The questions that interpret the items in table 10 are coded as the following because it is difficult to fit the questions or even summarize them in the table.

Table 10: Descriptive statistics

Item Mean Skewness Kurtosis Chinese Swedish Chinese Swedish Chinese Swedish C S 1 .10164 -.10164 .054 -.104 -.855 .071 C S 2 -.21836 .21836 .374 -.752 -.615 .429 C S 3 .01344 -.01344 .377 .056 -.303 -.706 Diversity1 .07278 -.07278 -.086 -.205 -1.129 -.557 Diversity2 -.19748 .19748 .152 -.484 -.444 -.946 Diversity3 -.21031 .21031 .175 -.450 -.592 -.925 E S 1 -.26714 .26714 -.327 -1.622 -.633 1.949 E S 2 -.26141 .26141 -.242 -1.317 -.586 1.321 E S 3 .02766 -.02766 -.237 -.561 -.454 -.514 E 1 -.22961 .22961 -1.023 -3.472 .588 13.375 E 2 -.31870 .31870 -.611 -2.882 -.262 8.678 E 3 -.20894 .20894 -.098 -1.400 -.904 1.074 O O 1 -.31771 .31771 -.246 -1.309 -.308 .839 O O 2 -.34719 .34719 -.126 -1.631 -.503 1.928 O O 3 .12779 -.12779 -.320 -.250 -.512 -.666 Product 1 -.36366 .36366 .314 -.622 -.515 -.293 Product 2 -.04123 .04123 -.060 -.130 -.464 -.824 Product 3 -.16517 .16517 .050 -.541 -.297 .054 I H 1 .32250 -.32250 -.208 .333 -1.224 -.935 I H 2 -.05322 .05322 -.143 -.648 -1.270 -.269 I H 3 .07743 -.07743 -.131 -.394 -1.258 -.362 I V 1 -.01335 .01335 .142 -.179 -.823 -.640 I V 2 .19641 -.19641 -.272 -.141 -.337 -.922 I V 3 .35370 -.35370 .262 .707 -.833 -.014 Attitude 1 .10452 -.10452 -.249 -.593 -.532 -.551 Attitude 2 .13774 -.13774 -.278 -.372 .211 -.390

Attitude 3 .28657 -.28657 -.064 -.051 -.083 -.536 Purchase1 -.22337 .22337 .844 .250 .042 -1.056 Purchase2 -.02428 .02428 1.390 1.314 1.527 1.254 Purchase3 -.30197 .30197 .987 .344 .874 -1.001

The scales in the study are 5 points with 1 strongly disagree, and 5 strongly agree. Table 10 above illustrates that there are differences in the means of the standardized variables between the Chinese cluster and the Swedish cluster. Despite the means that are substantially departing from the central tendency. On the one hand, in China, arguably, companies that build a positive relationship with the community is appreciated as the ethical player (Pivato, et al., 2008). Organic food brands may turn neutral to philanthropic activities because the market does not reward companies that are over generous (Bird, et al., 2007). However, table 10 above illustrates that the Chinese cluster has the major degree of central tendency consumption with means that have symmetrical distribution and the normal curve shape of dispersion of organic food brands that determine “sponsoring charities and supporting the economically disadvantaged groups in the community”. This important result should further analyze this with the aim of the thesis. Arguably, companies that build a positive relationship with the community is appreciated as the ethical player (Pivato, et al., 2008). Women in sport can be a sport issue because of cultural differences, also when developing sport as a cure for social issues, and art projects may associate with social exclusion (Jermyn, 2001; Calloway, 2004; Ware & Meredith, 2013). However, table 10 above illustrates that the Chinese cluster has the major degree of central tendency consumption with means that have symmetrical distribution and the normal curve shape of dispersion of “supporting sport, art, and cultural activities in the community”. This important result should further analyze with the aim of the thesis.

Arguably, employees carry a big responsibility for implementing ethical behavior in the daily life of the companies (Carroll, 1998). Profit sharing with employees can do little harm and performance related pay is more effective (Estrin, et al., 1987). However, table 10 above illustrates that the Chinese cluster has the major degree of central tendency consumption with means that have symmetrical distribution and normal curve shape of dispersion of “sharing profits with employees”. This important result should be further analyzed with respect of the aim of the thesis. Arguably, combating sweatshop conditions in overseas operations is an exciting ethical policy by companies (Brunk, 2010). Donation price can have administrative inefficiency on donations to nonprofit organizations in overseas (Jacobs & Marudas, 2009). However, table 10 above illustrates that the Chinese cluster has the major degree of central tendency consumption with means that have symmetrical distribution and the normal curve shape of dispersion of “supporting donations to non-profit organizations in overseas”. This important result should further analyze with the aim of the thesis. Arguably, consumers with individualism attitude prefer companies that have good behavior (Cho & Krasser, 2011). But most of the peaceful societies base their views on the corporation and opposition to competition (Bonta, 1997). Although, the Chinese culture is not an individualistic society (Hofstede-insights, n.d.). Table 10 above illustrates that the Chinese cluster has the major degree of central tendency culture with means that have symmetrical distribution and the normal curve shape of dispersion of “competition” which is a vertical individualism value. Hence this important result should further analyze with the aim of the thesis. Arguably, consumers with individualism attitude prefer companies that have good behavior (Cho & Krasser, 2011). Aroused tense can have negative affect and distress (Totterdell, 1999). Although the Chinese culture is not an individualistic society (Hofstede-insights, n.d.). Table 10 above illustrates that the Chinese cluster has the major degree of central tendency

culture with means that have symmetrical distribution and the normal curve shape of dispersion of “getting tense and aroused when another person does better” which is a vertical individualism value. Hence this important result should further analyze with the aim of the thesis. Arguably, consumers’ attitude is perceived by service quality and self- concept that influence individuals’ behavior to possibly purchase a brand (Dodds, et al., 1991; Spears & Singh, 2004; Wu & Chan, 2011). Companies’ CSR reputation and consumers perception can reflect a large issue (Castaldo, Perrini, Misani & Tencati, 2009). However, table 10 above illustrates that the Chinese cluster has the major degree of central tendency attitude with means that have symmetrical distribution and the normal curve shape of dispersion of “perceiving organic food brands to have a better reputation”. This important result should further analyze with the aim of the thesis. Arguably, consumers’ attitude is perceived by service quality and self- concept that influence individuals’ behavior to possibly purchase a brand (Dodds, et al., 1991; Spears & Singh, 2004; Wu & Chan, 2011). The fit between the cause and the brand does not always affect perceptions of attitudes regardless of the companies’ credibility (Lafferty, 2007). However, table 10 above illustrates that the Chinese cluster has the major degree of central tendency attitude with means that have symmetrical distribution and the normal curve shape of dispersion of “perceiving organic food brands to have high fit cause”. This important result should further analyze with the aim of the thesis. Arguably, consumers’ attitude is perceived by service quality and self- concept that influence individuals’ behavior to possibly purchase a brand (Dodds, et al., 1991; Spears & Singh, 2004; Wu & Chan, 2011). Cultural values of individuals could have a positive or negative self-concept connection to the company (Moon, Lee & Oh, 2015). However, table 10 above illustrates that the Chinese cluster has the major degree of central tendency attitude with means that have symmetrical distribution and the normal curve shape of

dispersion of “personal connection to the cause that is represented by organic food brands’ CSR initiatives”. This important result should further analyze with the aim of the thesis. On the other hand, in Sweden, arguably, companies that build a positive relationship with the community is appreciated as the ethical player (Pivato, et al., 2008). Educational policies can stress the social development (Zaglul, et al., 2006). However, table 10 above illustrates that the Swedish cluster has the major degree of central tendency consumption with means that have symmetrical distribution and the normal curve shape of dispersion of “supporting educational and training programs about agriculture for enterprises in the community”. This important result should further analyze with the aim of the thesis. Arguably, diversity set up regulations against discrimination and open up market opportunities (Bird, et al., 2007). Different genders could have different ageist attitudes concerning appearance, race, or sexuality in employment (Duncan & Loretto, 2004). However, table 10 above illustrates that the Swedish cluster has the major degree of central tendency consumption with means that have symmetrical distribution and the normal curve shape of dispersion of “setting up regulations against the discrimination of age, gender, and race”. This important result should further analyze with the aim of the thesis. Arguably, diversity set up regulations against discrimination and open up market opportunities (Bird, et al., 2007). Unlike race, color, nationality and national or ethnic origin that marked as identification, some religions, beliefs, and cultures are discriminated to address and tackle political causes (Allen, 2016). However, table 10 above illustrates that the Swedish cluster has the major degree of central tendency consumption with means that have symmetrical distribution and the normal curve shape of dispersion of “setting up regulations against the discrimination of religion, belief, and culture. This important result should further analyze with the aim of the thesis.

Arguably, a commitment to producing quality products viewed as sustainable and extended profitability for organic food companies (Johnson & Greening, 1999; Chen & Lobo, 2012). Minimizing research and development is considered as a cost-saving method by organic food brands (Belz & Schmidt-Riediger, 2010). However, table 10 above illustrates that the Swedish cluster has the major degree of central tendency consumption with means that have symmetrical distribution and the normal curve shape of dispersion of “conducting research and development by organic food brands”. This important result should further analyze with the aim of the thesis. Arguably, a commitment to producing quality products viewed as sustainable and extended profitability for organic food companies (Johnson & Greening, 1999; Chen & Lobo, 2012). Innovation deals with marketing and can be challenging because they depend on the age and size of the company also regional economic performance (Avermaete, Viaene, Morgan & Crawford, 2003). However, table 10 above illustrates that the Swedish cluster has the major degree of central tendency consumption with means that have symmetrical distribution and the normal curve shape of dispersion of “conducting marketing and innovation by organic food brands”. This important result should further analyze with the aim of the thesis. Arguably, a commitment to producing quality products viewed as sustainable and extended profitability for organic food companies (Johnson & Greening, 1999; Chen & Lobo, 2012). Contractual provision can rise competition policy concerns because covering all aspects of contractual performance might be impossible (Tsai & Wright, 2015). However, table 10 above illustrates that the Swedish cluster has the major degree of central tendency consumption with means that have symmetrical distribution and the normal curve shape of dispersion of “conducting contracts to avoid controversies and antitrust disputes”. This important result should further analyze with the aim of the thesis.

Arguably, consumers with individualism attitude prefer companies that have good behavior (Cho & Krasser, 2011). The self can assume a variety of forms and functions (e.g., good or bad) (Markus & Kitayama, 2001). However, table 10 above illustrates that the Swedish cluster has the major degree of central tendency culture with means that have symmetrical distribution and the normal curve shape of dispersion of “rather depend on the self than others” which is a horizontal individualism value. This important result should further analyze with the aim of the thesis. Arguably, consumers with individualism attitude prefer companies that have good behavior (Cho & Krasser, 2011). Doing people work may be more vulnerable because of stress resulting from others’ emotional demands (Van Daalen, Willemsen, Sanders & Van Veldhoven, 2009). However, table 10 above illustrates that the Swedish cluster has the major degree of central tendency culture with means that have symmetrical distribution and the normal curve shape of dispersion of “importance to do the job better than others” which is a vertical individualism value. This important result should further analyze with the aim of the thesis. Furthermore, it is essential to test if the activities in table 10 above are ideally community support factor, diversity factor, employee support factor, overseas operations factor, product factor, and attitude factor. The next subchapter will employ an exploratory factor analysis to test if the respected CSR activities and the attitude values (i.e., independent variables) load perfectly together.

5.3 Exploratory factor analysis from the Chinese cluster KMO test if it appropriate to conduct factor analysis (Malhotra, 2010). Notwithstanding, factor analysis requests a large sample size. A value of KMO that is greater than .5 is desirable to conduct factor analysis (Malhotra, 2010). Ideally, table 11 below illustrates that the correlation coefficient is ok to conduct factor analysis from the Chinese cluster. Table 11 below illustrates

the loadings of 6 factors which could be independent variables (i.e., CSR dimensions) for the CSR activities from the Chinese cluster.

Table 11: Rotated loadings 1 from the Chinese cluster

Rotated Component Matrix Component 1 2 3 4 5 6 Zscore: E S 3 .825 Zscore: E S 1 .814 Zscore: E S 2 .787 Zscore: Product 3 .863 Zscore: Product 1 .358 .764 Zscore: Product 2 .756 Zscore: E 3 .524 .389 .432 Zscore: O O 3 .865 Zscore: O O 1 .834 Zscore: O O 2 .370 .635 .307 Zscore: C S 2 .823 Zscore: C S 3 .769 .334 Zscore: C S 1 .502 .596 .368 Zscore: Diversity 1 .774 Zscore: Diversity 3 .413 .749 Zscore: Diversity 2 .460 .612 Zscore: E 1 .857 Zscore: E 2 .841 KMO .782

The rotated component matrix in table 11 above includes all items (i.e., CSR activities) from the Chinese cluster. Therefore, looking at table 11 above, there are some residuals, and residuals do not provide a model good fit. The model should be reproduced (Malhotra, 2010). In other words, E 3 have scores that do not load correctly on the components. Since E 3 did not have sufficient loading on the components, it is possible to print another rotated component matrix from the Chinese cluster to assist the factor analysis by looking at loadings after deleting the item E 3. In so, table 12 below illustrates another

KMO test from the Chinese cluster. It illustrates if it is coefficient to conduct the new rotated component matrix after deleting E 3. Not with standing, factor analysis requests a large sample size. A value of KMO that is greater than .5 is desirable to conduct factor analysis (Malhotra, 2010). Ideally, table 12 below illustrates that the correlation coefficient is ok to conduct factor analysis. Table 12 below illustrates the loadings of 6 factors which are independent variables (i.e., CSR dimensions) after deleting the item E 3.

Table 12: Rotated loadings 2 from the Chinese cluster after removing E 3

Rotated Component Matrix Component 1 2 3 4 5 6 Zscore: E S 3 .831 Zscore: E S 1 .811 Zscore: E S 2 .786 Zscore: O O 3 .861 Zscore: O O 1 .835 Zscore: O O 2 .364 .628 .328 Zscore: Product 3 .861 Zscore: Product 1 .328 .794 Zscore: Product 2 .766 Zscore: Diversity 3 .833 .318 Zscore: Diversity 1 .744 Zscore: Diversity 2 .697 .372 Zscore: C S 2 .854 Zscore: C S 3 .332 .794 Zscore: C S 1 .490 .369 .615 Zscore: E 1 .882 Zscore: E 2 .839 KMO .793

Coupled with, E 3 removed from the second rotated component matrix. Table 12 above illustrates that all the items grouped with respect of their constructs, then loaded on the 6 components. In other words, despite that item O O 2, Product 1, Diversity 3, Diversity 2, C S 3 and C S 1 has scores which are considered loadings that are too low to be significant. Each component from 1 to 6 (i.e., CSR dimensions) has 3 perfect loadings (i.e., CSR activities), except component 6 that has 2 perfect loadings only (i.e., CSR activities). In light of the descriptive statistics table 10 in the earlier subchapter, determining the support of “charities and the economically disadvantaged groups in the community” and “sport, art, and cultural activities in the community” has more degree of central tendency in the Chinese cluster than the Swedish cluster. Table 12 above illustrates that community support in the Chinese culture is an essential factor of those activities. Hence it is essential to keep this motivating result in mind when further analyze this factor. In light of the descriptive statistics table 10 in the earlier subchapter, determining concerns for “sharing profits with the employees” has more degree of central tendency in the Chinese cluster than the Swedish cluster. Table 12 above illustrates that employee support in Chinese culture is an essential factor of this activity. Hence it is essential to keep this motivating result in mind when further analyze this factor. In light of the descriptive statistics table 10 in the earlier subchapter, determining support for “donations to non-profit organizations in overseas” has more degree of central tendency in the Chinese cluster than the Swedish cluster. Table 12 above illustrates that overseas operations are an essential factor of this activity. Hence it is essential to keep this motivating result in mind when further analyze this factor. Table 13 below will continue to conduct the principle component analysis to illustrates the variance to derive factor solutions.

Table 13: Principle component from the Chinese cluster

Total Variance Explained

Component Extraction Sums of Squared Rotation Sums of Squared Initial Eigenvalues Loadings Loadings

% of Cumulative % of Cumulative % of Cumulative Total Variance % Total Variance % Total Variance % 1 8.244 48.497 48.497 8.244 48.497 48.497 2.696 15.857 15.857 2 1.680 9.884 58.381 1.680 9.884 58.381 2.554 15.025 30.882 3 1.549 9.110 67.491 1.549 9.110 67.491 2.449 14.405 45.287 4 1.194 7.025 74.516 1.194 7.025 74.516 2.377 13.983 59.270 5 .944 5.550 80.066 .944 5.550 80.066 2.328 13.694 72.965 6 .730 4.294 84.361 .730 4.294 84.361 1.937 11.396 84.361 7 .518 3.044 87.405 8 .463 2.721 90.126 9 .410 2.410 92.536 10 .299 1.757 94.293 11 .245 1.440 95.733 12 .192 1.129 96.861 13 .185 1.089 97.951 14 .131 .771 98.721 15 .089 .526 99.248 16 .077 .454 99.702 17 .051 .298 100.000 Whereas, the factor solution should be a minimum of 60% of the total variance (Hair Jr, et al., 2015). Table 13 above illustrates that 17 variables reduced to 6 components that have 73% total variance, hence acceptable. Coupled with, to demonstrate a principle component analysis. The common variance is the .298% of 5.1% variance of 17 variables, the unique variance is 4.294% of 5.1% of 17 variables, and finally, the error variance is 11.396% of 19.37% of the CSR dimensions. In light of the mentioned above, the relationship of these factors with the aim of the study is unclear. Therefore, coupled with the next subchapter, which will conduct exploratory factor analysis from the Swedish cluster. Multiple regression analyses further will describe the relationship of these factors with the aim of the study.

5.4 Exploratory factor analysis from the Swedish cluster KMO test indicates if it is appropriate to conduct factor analysis (Malhotra, 2010). Notwithstanding, factor analysis requests a large sample size. A value of KMO that is greater than .5 is desirable to conduct factor analysis (Malhotra, 2010). Ideally, table 14 below illustrates that the correlation coefficient is ok to conduct factor analysis from the Swedish cluster. Table 14 below could illustrate the loadings of 6 factors which could be independent variables (i.e., CSR dimensions) from the Swedish cluster.

Table 14: Rotated loadings 1 from the Swedish cluster

Rotated Component Matrix Component 1 2 3 4 5 6 Zscore: Diversity 3 .837 Zscore: Diversity 2 .804 Zscore: C S 1 .854 Zscore: C S 3 .787 Zscore: O O 3 .393 .611 .342 Zscore: C S 2 .570 .375 Zscore: Diversity 1 .387 .468 .422 -.377 Zscore: E 2 .779 Zscore: E 1 .749 Zscore: O O 2 .354 .715 Zscore: O O 1 .542 .644 Zscore: Product 2 .849 Zscore: Product 1 .796 Zscore: Product 3 .732 .323 Zscore: E S 2 .921 Zscore: E S 1 .843 Zscore: E S 3 .380 .560 Zscore: E 3 .354 .811 KMO .723

The rotated component matrix in table 14 above includes all items (i.e., CSR activities) from the Swedish cluster. Therefore, looking at table 14 above, there are some residuals, and residuals do not provide a model good fit. The model should be reproduced (Malhotra, 2010). In other words, C S 2, and Diversity 1 have scores that do not load correctly on the components. Since they did not have sufficient loadings on the components, it is possible to print another rotated component matrix for one item at a time from the Swedish cluster to assist the factor analysis by looking at loadings after deleting the items Diversity 1 then CS 2. In so, table 15 below illustrates another KMO test from the Swedish cluster. It illustrates if it is coefficient to conduct the new rotated component matrix after deleting diversity 1. Notwithstanding, factor analysis request a large sample size. A value of KMO that is greater than .5 is desirable to conduct factor analysis (Malhotra, 2010). Ideally, table 15 below illustrates that the correlation coefficient is ok to conduct factor analysis from the Swedish cluster. Table 15 below illustrates the loadings of 6 factors which could be independent variables (i.e., CSR dimensions) after deleting the item Diversity 1.

Table 15: Rotated loadings 2 from the Swedish cluster after removing Diversity 1

Rotated Component Matrix Component 1 2 3 4 5 6 Zscore: Diversity3 .835 Zscore: Diversity2 .798 Zscore: E2 .754 Zscore: OO2 .337 .740 Zscore: E1 .716 .320 Zscore: OO1 .511 .675 Zscore: CS1 .862 Zscore: CS3 .796 Zscore: OO3 .427 .617 Zscore: CS2 .558 .373 .317 Zscore: ES2 .918 Zscore: ES1 .849 Zscore: ES3 .381 .559 Zscore: Product2 .857 Zscore: Product1 .793 Zscore: Product3 .744 Zscore: E3 .328 .808 KMO .705

Table 15 above illustrates that component 6 does not have sufficient loadings. However, as indicated earlier, the thesis will reproduce another component matrix. This is by removing the item CS 2. In so, table 16 below is another KMO test from the Swedish cluster. It illustrates if it is coefficient to conduct another rotated component matrix after deleting CS 2. Notwithstanding, factor analysis requests a large sample size. A value of KMO that is greater than .5 is desirable to conduct factor analysis (Malhotra, 2010). Ideally, table 16 below illustrates that the correlation coefficient is ok to conduct factor analysis from the Swedish cluster. Table 16 below illustrates the loadings of 6 factors which are independent variables (i.e., CSR dimensions) after deleting the item CS 2.

Table 16: Rotated loadings 3 from the Swedish cluster after deleting CS 2

Rotated Component Matrix Component 1 2 3 4 5 6 Zscore: Diversity3 .822 Zscore: Diversity2 .785 .333 Zscore: ES2 .924 Zscore: ES1 .861 Zscore: ES3 .425 .552 Zscore: Product2 .869 Zscore: Product1 .796 Zscore: Product3 .363 .744 Zscore: CS1 .850 Zscore: CS3 .838 Zscore: OO3 .414 .656 Zscore: OO2 .814 Zscore: OO1 .326 .767 Zscore: E3 .326 .834 Zscore: E1 -.322 .379 .668 Zscore: E2 .491 .629 KMO .706

Coupled with, Diversity 1 removed from the second rotated component matrix in table 15, and CS 2 that removed from the third rotated component matrix in table 16. Table 16 above illustrates that all the items are grouped with respect of their constructs then loaded on the 6 components. In other words, despite that item Diversity 2, E S 3, Product 3, O O 3, O O 1, E 3, E 1, and E 2 has scores which are considered loadings that are too low to be significant. Each component from 1 to 6 (i.e., CSR dimensions) has three prefect loadings (i.e., CSR activities), except component 1 and 5 that have only 2 perfect loadings (i.e., CSR activities). In light of the descriptive statistics table 10 in the earlier subchapters, determining support for “educational and training programs about agriculture

for enterprises in the community” has more degree of central tendency in the Swedish cluster than the Chinese cluster. Table 16 above illustrates that community support is an essential factor of this activity. Hence it is essential to keep this motivating result in mind when further analyze this factor. In light of the descriptive statistics table 10 in the earlier subchapters, determine “setting up regulations against the discrimination of age, gender, and race” and “setting up regulations against the discrimination of religion, belief, and culture” has more degree of central tendency in the Swedish cluster than the Chinese cluster. Table 16 above illustrates that diversity in Swedish culture is an essential factor of those activities. Hence it is essential to keep this motivating result in mind when further analyze this factor. In light of the descriptive statistics table 10 in the earlier subchapters, determine conducting “research and development”, “marketing and innovation”, and “contracts to avoid controversies and antitrust disputes” has more degree of central tendency in the Swedish cluster than the Chinese cluster. Table 16 above illustrates that product in the Swedish culture is an essential factor of those activities. Hence it is essential to keep this motivating result in mind when further analyze this factor. Table 17 below will conduct the principle component analysis to illustrates the variance to derive factor solutions.

Table 17: Principle component from the Swedish cluster

Total Variance Explained Component Extraction Sums of Squared Rotation Sums of Squared Initial Eigenvalues Loadings Loadings

% of Cumulative % of Cumulative % of Cumulative Total Variance % Total Variance % Total Variance % 1 4.507 30.046 30.046 4.507 30.046 30.046 2.218 14.790 14.790 2 1.894 12.628 42.674 1.894 12.628 42.674 2.177 14.514 29.304 3 1.807 12.047 54.721 1.807 12.047 54.721 2.102 14.012 43.316 4 1.485 9.902 64.623 1.485 9.902 64.623 2.045 13.633 56.949 5 1.064 7.096 71.719 1.064 7.096 71.719 1.874 12.494 69.443 6 .858 5.723 77.442 .858 5.723 77.442 1.200 7.999 77.442 7 .658 4.390 81.831 8 .551 3.676 85.507 9 .492 3.277 88.785 10 .431 2.875 91.660 11 .393 2.619 94.279 12 .313 2.086 96.365 13 .255 1.700 98.066 14 .150 1.003 99.069 15 .140 .931 100.000

Whereas, the factor solution should be a minimum of 60% of the total variance (Hair Jr, et al., 2015). Table 17 above illustrates that 15 variables reduced to 6 components that have 85.8% total variance, hence acceptable. Coupled with, to demonstrate a principle component analysis. The common variance is the .931% of 14% variance of 15 variables, the unique variance is 5.723% of 14% of 15 variables, and finally, the error variance is 7.999% of 12% of the CSR dimensions.

5.5 Multiple regression analysis In table 18 and table 19 showcased below, whereas, from model 1 to model 7 the dependent variable is “attitude”. Model 1 is multiple regression of (only control variables). Model 2 is for (control variables and community support). Model 3 is for (control variables and diversity). Model 4 is for (control variables and employee support). Model 5 is for (control variables and environment). Model 6 is for (control variables and overseas operations). Model 7 is for (control variables and product). Model 8 is for (control variables and all CSR dimensions). Whereby, from model 8 to model 11 the dependent variable is purchase. Model 9 is for (control variables and attitude). Model 10 is for (control variables and attitude moderated by horizontal individualism). Model 11 is for (control variables and attitude moderated by vertical individualism). Model 12 is for (control variables, attitude, attitude moderated by horizontal individualism, and attitude moderated by vertical individualism). Table 18 below is multiple regression conducted from the Chinese cluster.

Table 18: Multiple regression from the Chinese cluster

Model Model Model Model Model Model Model Model Model Model Model Model 1 2 3 4 5 6 7 8 9 10 11 12 Gender .070 .065 .164 .088 .095 .026 .057 .106 .060 .088 .079 .059 Age -.009 .017 -.034 -.059 -.065 .022 -.028 -.021 -.077 -.080 -.073 -.077 Education .106 .023 -.020 .058 -.026 .042 .003 -.082 .068 .112 .093 .063 Income .318* .266* .195 .291* .313** .272* .321** .216* .308** .434** .435** .324** C S .392** .114 Diversity .487** .241* E S .314** -.075 E .442** .333** O O .420** .255* Product .270** -.682 Attitude .424** .454** A - IH .037 -.126 A - IV .142 .043 R square .164 .303 .354 .256 .341 .327 .227 .494 .428 .279 .298 .440 Adjusted .129 .266 .320 .217 .306 .291 .186 .437 .398 .241 .260 .398 R square Change in .164 .303 .354 .256 .341 .327 .227 .494 .428 .279 .298 .440 R square Std. error .80749 .74134 .71356 .76560 .72059 .72829 .78072 .64926 .74057 .83131 .82077 .74055 of estimate F-value 4.657* 8.161* 10.302 6.480* 9.737* 9.136* 5.510* 8.676* 14.079 7.293* 7.967* 10.343 * * ** * * * * * ** * * ** Degree of 4 5 5 5 5 5 5 10 5 5 5 7 freedom regression *Sig of 0.05 or lower **Sig of 0.01 or lower

In order to test the multi-variable hypothesis 1 of the thesis, by looking at model 8 in table 18 above from the Chinese culture point of view. The F- value indicates that the overall regression model is statistically significant. Moreover, to avoid overestimation of R square since model 8 has different numbers of independent variables. Adjusted R square recalculates R square based on the predictor variables in the model (Hair Jr, et al., 2015). Whereas, diversity, environment, and overseas operations significantly associated with a better attitude towards organic food brands and the adjusted R square indicates that those CSR dimensions can explain 43.7% of Chinese consumers’ attitude with only .649 standardized error of the estimate. Community support, employee support, and product are not significantly associated with a better attitude towards organic food brands. Arguably, donation price can have administrative inefficiency on donations to nonprofit organizations in overseas (Jacobs & Marudas, 2009). Table 18 above and the factor analysis demonstrate that consumers income groups and determining support for donations to non-profit organizations in overseas is associated with a better attitude towards organic food brands with 10 degrees of freedom. Not to mention, with respect of the cross-cultural comparison. The independent sample T-test in table 10 in the previous subchapters illustrates that the Chinese culture ideally has more degree of central tendency than the Swedish culture of this activity and all attitude values. Hence hypothesis one is partly accepted. In order to test the hypothesis 2 of the thesis which could also be multi- variable because it is related to the previous hypothesis, by looking at model 12 in table 18 above from the Chinese culture point of view. The F-Value indicates that the overall regression model is statistically significant. Moreover, to avoid overestimation of R square since model 12 has different numbers of independent variables. Adjusted R square recalculates R square based on the predictor variables in the model (Hair Jr, et al., 2015). Whereas, the adjusted R square indicates that 39.8% of Chinese consumers’ purchasing

volume can be explained by consumers’ attitude towards CSR initiatives with only .740 standardized error of estimate. With respect of model 8 in table 18 above and factor analysis only determining support for donations to non-profit organizations in overseas and consumers income groups is associated with a better attitude. Not to mention CSR initiatives should include other activities as well. The link between attitude and purchasing behavior is not always clear (Carrigan & Attalla, 2001; Spears & Singh, 2004). Whereas, model 12 in table 18 above and the previous analysis in mind illustrates that attitude influence purchasing behavior with respect of consumers’ income groups and determining support for donations to non-profit organizations in overseas is associated with better attitude with 10 then 7 degrees of freedom. The independent sample T-Test in table 10 in the previous subchapters from the Chinese culture point of view consumers have higher degree than Swedish consumers of central tendency attitude of perceiving organic food brands to have a better reputation, high fit cause, and personal connection to determining support for donations to non-profit organizations in overseas, but both Chinese and Swedish consumers have a low degree of central tendency purchasing of organic food. Hence hypothesis 2 is rejected. In order to test the multi-variable hypothesis 3 of the thesis, by looking at model 12 in table 18 above from the Chinese culture point of view. The F- value indicates that the overall regression model is statistically significant. However, attitude moderated by individualism patterns (i.e., horizontal and vertical) are not significantly associated with increasing purchasing volume. Hence hypothesis 3 is rejected. In light of the mentioned above, Chinese consumers have a positive attitude of supporting donations to non-profit organizations in overseas with respect of their income groups. But will not carry out an actual purchasing behavior of organic food brands. Despite that, table 10 in the earlier subchapters illustrates that Chinese culture has a higher degree of central

tendency culture of competition and getting tens and aroused when someone else does better than the Swedish culture. These cultural values do not influence the relationship between attitude and purchase. Table 19 below is multiple regression conducted from the Swedish cluster.

Table 19: Multiple regression from the Swedish cluster

Model Model Model Model Model Model Model Model Model Model Model Model 1 2 3 4 5 6 7 8 9 10 11 12 Gender -.044 -.073 -.068 -.066 -.057 -.064 -.062 -.084 .068 .049 .068 .081 Age .136 .135 .133 .119 .164 .145 .120 .145 .169 .215 .232 .205 Education .034 .048 .056 .050 .040 .039 .021 .044 .121 .130 .117 .098 Income .042 .035 .042 .068 .008 .039 .050 .022 -.033 -.002 -.052 -.054 C S .351** .325** Diversity .129 -.041 E S .127 .034 E .158 .106 O O .184 .001 Product .189 .067 Attitude .321** .293** A – IH .077 .115 A - IV -.110 -.164 R square .032 .154 .048 .047 .056 .065 .067 .173 .177 .083 .088 .193 Adjusted -.009 .109 -.003 -.004 .006 .016 .018 .080 .133 .034 .040 .132 R square Change in .032 .154 .048 .047 .056 .065 .067 .173 .69381 .083 .088 .193 R square Std. error .72727 .68341 .72520 .72548 .72194 .71843 .71775 .69446 .69381 .73255 .73043 .69454 of estimate F-value .786** 3.429** .941** .926** 1.120** 1.315** 1.353** 1.864** 4.048** 1.695** 1.814** 3.143* * Degree of 4 5 5 5 5 5 5 10 5 5 5 7 freedom regression *Sig of 0.05 or lower **Sig of 0.01 or lower

On the other hand, in order to test the multi-variable hypothesis 1 of the thesis, by looking at model 8 in table 19 above from the Swedish culture point of view. The F-Value indicates that the overall regression model is statistically significant. Moreover, to avoid overestimation of R square since model 8 has different numbers of independent variables. Adjusted R square recalculates R square based on the predictor variables in the model (Hair Jr, et al., 2015). Whereas, model 8 in table 19 above illustrates that community support is significantly associated with a better attitude towards organic food brands and the adjusted R square indicates that this CSR dimension can explain 13.3% of Swedish consumers’ attitude with only .693 standardized

error of estimate. Diversity, employee support, environment, overseas operations, and product are not significantly associated with a better attitude towards organic food brands. Arguably, educational policies can stress the social development (Zaglul, et al., 2006). Table 19 above and the factor analysis in the previous subchapter demonstrate that determine supporting educational and training programs about agriculture for enterprises in the community is associated with a better attitude towards organic food brands with 10 degrees of freedom. However, with respect of the cross-cultural comparison. The independent sample T-Test in table 10 in the previous subchapters illustrates that the Swedish culture has a lower degree of central tendency attitude than the Chinese culture. Hence hypothesis 1 is rejected. In order to test the hypothesis 2 of the thesis which could also be multi- variable because it is related to the previous hypothesis, by looking at model 12 in table 19 above from the Swedish culture point of view. The F-Value indicates that the overall regression model is statistically significant. Moreover, to avoid overestimation of R square since model 12 has different numbers of independent variables. Adjusted R square recalculates R square based on the predictor variables in the model (Hair Jr, et al., 2015). Whereas, attitude significantly influence purchasing volume of organic food brands and the adjusted R square indicates that consumers’ attitude towards CSR initiatives can explain 13.2% of Swedish consumers’ purchasing volume with only .694 standardized error of estimate. With respect of table 19 above and the factor analysis in the previous subchapter only determine supporting educational and training programs about agriculture for enterprises in the community is associated with a better attitude towards organic food brands. Not to mention CSR initiatives should include other activities as well. The link between attitude and purchasing behavior is not always clear (Carrigan & Attalla, 2001; Spears & Singh, 2004). Whereas, model 12 in table 19 above with respect of the previous analyses illustrates that Swedish

consumers’ attitude of determine supporting educational and training programs about agriculture for enterprises in the community is significantly associated with their purchasing volume of organic food brands with 10 then 7 degrees of freedom. The independent sample T-Test in table 10 in the previous subchapters illustrates that the Swedish culture has a lower degree of central tendency of attitude and both cultures have a low degree of central tendency of purchase than the Chinese culture. Hence hypothesis 2 is rejected. In order to test the multi-variable hypothesis 3, by looking at model 12 in table 19 above from the Swedish culture point of view. The F-Value indicates that the overall regression is statistically significant with 7 degrees of freedom. However, attitudes moderated by each individualism patterns (i.e., horizontal and vertical) are not significantly associated with increasing purchasing volume. Hence hypothesis 3 is rejected. In light of the mentioned above, Swedish consumers do not have a positive attitude towards CSR initiatives. And will not buy organic food brands that employ any of the CSR initiatives that the thesis suggests as a marketing strategy. Despite that, table 10 in the earlier subchapters illustrates that Swedish culture has a higher degree of central tendency culture of rather depending on the self than others and the importance of doing the job better than others than the Chinese culture. These cultural values do not influence the relationship between attitude and purchase. The next chapter will provide a discussion regarding the study by using reasoning debate, backed up with the results from analyzed data with respect of control variables and hypothesis, and pointing out the advantages and disadvantages of the context.

6 Discussion The current thesis extends the academic body of research in the area of organic food consumption, CSR determinants of consumers’ purchase of organic food, and cross-cultural comparison between China and Sweden. In this regard it is on the thesis agenda to identify the CSR determinants concerning organic food consumption amongst people in China and Sweden. Based on the extensive literature review, the authors identify three predominant areas in academia (i.e., CSR activities, attitude, and individualism), with hypotheses to test what CSR activities in organic food brands determine attitude to purchasing during the comparative relationship between China and Sweden. The six domains of CSR activities constructed variables that are measured by independent variables. However, the construct attitude is more complicated because it is both a dependent and independent variable. The two patterns of individualism (i.e., horizontal and vertical) are constructs variables that are measured by moderating variables, which affect the direction of the association between attitude and purchase. The thesis synthesis three hypotheses. Coupled with, the cross-cultural comparison and with respect of the highest degree of freedom from the Chinese culture point of view. Hypothesis 1 is partly accepted by one factor (i.e., overseas operations) and one CSR activity (i.e., determine supporting donations to non-profit organizations in overseas). However, with only 5 degrees of freedom from the Chinese culture point of view. Hypothesis one can be accepted with 3 factors (i.e., community support, employee support, overseas operations) and three CSR activities (i.e., determine sponsoring charities and supporting the economically disadvantaged groups in the community, determine supporting sport, art, and cultural activities in the community, determine concerns for sharing profits with employees, and determine supporting donations to non-profit organizations in overseas). Coupled with, the cross-cultural comparison and with respect of the highest degree of freedom from the Chinese culture point of view. Hypothesis

2 is rejected. But the thesis can not argue this with less degree of freedom. Because, despite the high degree of central tendency of the attitude of Chinese consumers. Both Chinese and Swedish cultures have a low degree of central tendency purchase. Coupled with, the cross-cultural comparison and with respect of the highest degree of freedom from the Chinese culture point of view. Hypothesis 3 is rejected. Because, the thesis can not argue this with less degree of freedom. Attitude moderated by horizontal individualism and attitude moderated by vertical individualism are not statistically significant. On the other hand, the thesis tests the hypotheses from the Swedish culture point of view as well. Coupled with, the cross-cultural comparison and with respect of the highest degree of freedom from the Swedish culture point of view. Hypothesis one is rejected. Even with only 5 degrees of freedom, hypothesis one is still rejected. This is because that Swedish culture has lower degree of central tendency attitude than the Chinese culture. Coupled with, the cross-cultural comparison and with respect of the highest degree of freedom from the Swedish culture point of view. Hypothesis 2 is rejected. Because, the thesis can not argue this with less degree of freedom. Swedish consumers have a lower degree of central tendency attitude than the Chinese consumers. Also both Swedish and Chinese consumers have a low degree of central tendency purchase. Coupled with, the cross-cultural comparison and with respect of the highest degree of freedom from the Swedish culture point of view. Hypothesis 3 is rejected. Because, the thesis can not argue this with less degree of freedom. Attitude moderated by horizontal individualism and attitude moderated by vertical individualism are not statistically significant. Moreover, regarding control variables and with respect of high degree of freedom. Only Chinese consumers’ income groups significantly associated with the relationship between CSR activities that has high degree of central tendency and consumers’ attitude. Arguably, there is an association of Chinese

consumers’ income groups with the relationship between attitude and purchasing volume. This association is not sufficient because of the low degree of central tendency of purchasing among the Chinese consumers. Similarly, Chinese consumers income groups are not associated with the relationship between moderated attitudes by each individualism pattern and purchasing volume. With lower degree of freedom, Chinese consumers’ income groups are also not associated with the relationship between moderated attitudes by each individualism pattern and purchasing volume. With this in mind, the income groups graph bar is portrayed in figure 6 in the analysis chapter. It demonstrates that the income group $1001-2000 has the majority of responses. Hence Chinese with this monthly income group are significantly associated with supporting donations to non-profit organizations in overseas and better attitude. On the other hand, from the Swedish culture point of view. None of the control variables are associated with the relationship between CSR activities and consumers’ attitude. Similarly, not even the relationship between attitude and purchasing volume. Not even the relationship between moderated attitudes by each individualism pattern with purchasing volume.

7 Conclusion This thesis set out to compromise conventional food brands with organic food brands and to determine favorable CSR activities from unfavorable CSR activities. Because food safety is an issue for the heterogeneous consumers in China and Sweden, also purchasing volume of consumers is a priority for the sustainable competitive organic food brands. Chinese consumers within income group $1001-2000, which is not too high average monthly salary, have an association with their attitude and purchasing behavior of organic food brands. Whereas, CSR creates high trust, loyalty, and positive image for companies, the thesis has identified that Chinese consumers have a high degree of central tendency attitude towards CSR initiatives in companies. However, they have a low degree of central tendency of purchasing behavior of organic food brands. Hence CSR is sufficient, but the price inflation could be an issue for this segment. On the other hand, with the food and greenwashing skepticism of Swedish consumers, the thesis found that they have low degree of central tendency attitude and purchasing behavior towards CSR by organic food companies, also the thesis could not identify CSR and demographic relationship with attitude and purchasing behavior. This result indicates that organic food brands that employ such CSR activities, and target such demographics, should not target the Swedish segment. In sum, the initial purpose of this paper, is to investigate the relationship between the CSR activities and consumers’ purchase of their brands with the mediating effect of consumers’ attitude, also to evaluate the role of the individualism patterns on moderating the relationship between consumers’ attitude that is driven by companies’ CSR initiatives and consumers’ purchasing volume of their brands. With this in mind, CSR activities, attitude, and individualism tested concerning their relationship with purchasing behavior.

Thus, to answer the underlying research question. Both in China and Sweden, consumers’ attitude moderated by each individualism patterns (i.e., horizontal and vertical) are not significantly associated with increasing purchasing volume of organic food brands that employ CSR activities as a marketing strategy. Notwithstanding, there are only some CSR activities of community support, employee support, and overseas operations that are significantly associated with a better attitude towards organic food brands in China with a low degree of freedom. The thesis chose the higher degree of freedom as a benchmark because the hypotheses synthesized with multi-variables. Arguably, supporting donations to non-profit organizations in overseas are associated with a better attitude towards organic food brands in China. The description in the thesis could not explain the estimation of 14.3% compound annual growth rate from the year 2017-2022 in China (Global organic trade guide, n.d.a).

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8 Implications

8.1 Theoretical implications Theoretically, the thesis replicates the model of CSR activities (i.e., community support, diversity, employee support, environment, overseas operations and product) with the internal outcome (i.e., attitude) and external outcome (i.e., purchase) and consumers individualistic cultural characteristics as a moderator between the two outcomes (Sen & Bhattacharya, 2001; Bhattacharya & Sen, 2004; Anselmsson & Johansson, 2007). The framework function for cross-cultural samples. Whereas, consumers may support an action related to ethics but not carry it out (Carrigan & Attalla, 2001). The thesis implicates that Chinese consumers support ethical actions of CSR initiatives by organic food brands (i.e., overseas operations that support donations to non-profit organizations in non-domestics) more than Swedish consumers, but will not carry it out (i.e., purchase), and the reason for that is their low monthly income. Whereas, food safety issues took place in China (Fenby, 2013). Individualism attitude has antecedents of environmental behavior (Triandis & Gelfand, 1998; Lee & Choi, 2005). However, Cultural individualism patterns could not positively moderate the implication between attitude and purchase among Chinese consumers. The relationship between attitude and behavior is not always clear (Spears & Singh, 2004). Taken together, these findings, suggest a role for managerial implications. Demonstrated in the next subchapter.

8.2 Managerial implications The overall results of the thesis are expected to provide important insight for the business fields through the implication of social responsibility to shape a sound social image, improve corporate reputation and then attract and keep consumers to take a healthy and sustainable development path. In the marketing competition, the starting point and destination for measuring the

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success or failure of each company’s work are winning consumers by satisfying their needs, attaching importance to their rights and interests, and fulfilling their responsibilities. Because, if companies’ overseas operations have problems with social responsibility, it will also affect the company itself. Therefore, organic food brands should supervise their overseas operations in non-profit organizations by donations from consumers to combat sweatshops. Hence meeting various environmental protection requirements. Society is the stage for the company’s survival. For a social citizen, companies must integrate themselves into social groups, interact with various organizations, and develop harmoniously with organic food agriculture. Because, by undertaking social responsibilities. Companies can win reputations and non-profit organizational identities in overseas. For the long run, this is also a long-term investment on companies. It can better reflect cultural orientation, values, create a better social atmosphere for business development, enable companies to maintain their vitality, and achieve long- term sustainable development. The thesis also found that most participants of China from the income groups $1001-2000 are associated with the relationship between CSR initiatives and attitude. Therefore, they have a low degree of central tendency purchase. A segment with a higher income group in China could be targeted to purchase organic food brands that determine supporting donations to non- profit organizations in overseas operations. Whereby, individualism does not enhance consumers attitude to purchase. Organic food brands should show their initiatives of donations for non-profit organizations in overseas on their packaging labels and search for another moderator than individualism to determine their innovativeness in their advertising appeals.

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9 Limitation and suggestion for future research

9.1 Limitation This thesis contains some limitations. The generalizability in the targeted demographics lead to a certain limitation. The first limitation is regarding the research approach. Quantitative research was done using a web-based survey and opting for convenience sampling, which led to further snowball sampling. Therefore, this sample was not chosen entirely at random. It can not be viewed as entirely statistical. In so, initial efforts to launch the survey statistically by multiple stage sampling and on professional platforms were unsuccessful because the timeframe for the thesis is limited. The researchers decided to send out requests to take part in the survey through channels that were available for them such as specific social media channels, mailing and personally on the university campus, city center, and companies. In other words, besides that the targeted population in the thesis subdivided groups which are cities with the highest population of organic food consumption in China and Sweden, and conducted data collection through mailings, messages, and face-to-face interviewing in the city center, companies, and university campus. However, after paying many efforts. Researchers got limited responses. Because, the limited timeframe of the thesis. The researchers decided to select random sampling in all over China and Sweden. The second limitation is regarding the questionnaire. Although, the questionnaire was pre-tested by experts and representatives of the sample and almost passed the necessary validity tests. The researchers have received some feedback afterward from participants who had difficulties in comprehending every question, due to their limited pre-knowledge of the topic. Coinciding with this, the aspect that the survey conducted in English and the sample come from China and Sweden. It can not exclude that some participants may have misunderstood some questions. Hence this could affect the results. Also, the respondents were not aware about specific brands CSR activities, for example, “The Norr Company” sells rehydration drinks, and for every bottle a

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consumer buy, the company donates a rehydration-pack to a child in need. Whereas, the thesis focused only on organic food brands, in Sweden, brands have to fulfill a lot of different requirements to be able to label their products as organic, because some people feel that organic might be worse for the environment than locally produced products, therefore CSR can be equally important for products grown locally: gluten-free, vegan etc. without a specific chemical or likewise.

9.2 Future research The thesis has put up questions in need of further investigation. That is what national culture dimension could influence the Chinese segment characteristics to moderate their attitude towards purchasing organic food brands that determine supporting donations to non-profit organizations in overseas, Coupled with, the different income groups. Purchasing volume should be investigated as multiple dependent variables to know the relationship between price inflation and consumption frequency. The second question is what attitudes and demographics of Swedish consumers enhance their purchasing volume of organic food brands that determine supporting educational and training programs about agriculture for enterprises in the community.

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Appendix 1: Survey

Consumers' purchase of organic food Dear participants, We are two master students at Linnaeus University currently investigating the determinants of corporate social responsibility (CSR) on the consumers' purchase of organic food. We would appreciate it if you could answer the following questions. There will be a few statements, where you fill in to what extent you agree with them. One (1) is strongly disagree and five (5) is strongly agree. Filling out this questionnaire will take 5 minutes. We would like to thank you in advance for your time and assistance in helping us to collect data for this important thesis. Your opinion is highly valuable and greatly appreciated! We guarantee you that your responses will be strictly confidential and will only be used for analysis purposes. If you have any concerns regarding the questions, please contact us. Mohamad Khair, [email protected] Yong Wang, [email protected] "Organic foods are minimally processed to maintain the integrity of the food without artificial ingredients, preservatives or irradiation".

*Required Q1. Have you ever purchased organic food before? * Mark only one oval. ▪ Yes. ▪ No [if No, exit survey]. After the last question in this section, stop filling in this form. Q2. Please state your nationality. * Mark only one oval. ▪ Chinese. ▪ Swedish. ▪ Other [if other, exit survey]. Stop filling out this form. Corporate social responsibility (CSR) Corporate social responsibility is defined as "Companies' interaction in sustainability performance of social and environmental concerns in their business operations and their voluntary basis interaction with stakeholders". The main CSR activities are summarized into six broad domains (i.e. community support, diversity, employee support, environment, overseas operations, and product). "Determinance is a dynamic concept that connotes a moderate relationship to decision making". Community support "Community is Solidarity, which implies a common identity and set of shared norms and values". Q3. Organic food brands should determine sponsoring charities and supporting the economically disadvantaged groups in the community. * Mark only one oval. 1 2 3 4 5

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Strongly disagree Strongly agree Q4. Organic food brands should determine supporting educational and training programs about agriculture for enterprises in the community. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Q5. Organic food brands should determine supporting sport, art, and cultural activities in the community. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Diversity "Diversity includes all characteristics and experiences that define each of us as individuals". Q6. Organic food brands should determine providing minorities with more employment opportunities. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Q7. Organic food brands should determine setting up regulations against the discrimination of age, gender, and race. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Q8. Organic food brands should determine setting up regulations against the discrimination of religion, belief, and culture. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Employee support “Programs cultivate affective organizational commitment by enabling employees to receive support”. Q9. Organic food brands should determine concerns for employees’ safety. * Mark only one oval. 1 2 3 4 5

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Strongly disagree Strongly agree Q10. Organic food brands should determine concerns for employees’ job security. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Q11. Organic food brands should determine concerns for sharing profits with their employees. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Environment “Whatever exist in the surroundings of some being that is relevant to the state of that being at a particular moment”. Q12. Organic food brands should determine their products to be environmentally-friendly. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Q13. Organic food brands should determine conducting recycling and hazardous waste management. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Q14. Organic food brands should determine testing animals from disease. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Overseas operations “Multinational is the presence of international production and the characteristics of the parent company”. Q15. Organic food brands should determine concerns for equal human rights in non-domestic operations. * Mark only one oval. 1 2 3 4 5

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Strongly disagree Strongly agree Q16. Organic food brands should determine concerns for exploiting child labor and supplying education for them in non-domestic operations. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Q17. Organic food brands should determine supporting donations to non-profit organizations in overseas. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Product “Any item introduced into the stream of commerce, including the intangible or intellectual aspects of the item”. Q18. Organic food brands should determine conducting research and development. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Q19. Organic food brands should determine conducting marketing and innovation. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Q20. Organic food brands should determine conducting contracts to avoid controversies and antitrust disputes. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Individualism “Political and social philosophy that places high value on the freedom of the individual and generally stresses the self-directed, self-contained, and comparatively unrestrained individual or ego”. Horizontal "Horizontal patterns assume that one self is more or less like every other self". Q21. I take care of my self and my immediate families only. *

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Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Q22. I would rather depend on myself than others. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Q23. I rely on myself most of the time and I rarely rely on others. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Vertical "Vertical patterns consist of hierarchies, and one self is different from other selves". Q24. It is important that I do my job better than others. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Q25. Competition is the law of nature. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Q26. When another person does better than I do, I get tense and aroused. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Attitude "A person's positive or negative feelings about an action in general". Q27. I perceive organic food brands to have a better reputation. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Q28. I perceive organic food brands to have high fit cause. * Mark only one oval.

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1 2 3 4 5

Strongly disagree Strongly agree Q29. I have a personal connection to the cause that is represented by organic food brands' CSR initiatives. * Mark only one oval. 1 2 3 4 5

Strongly disagree Strongly agree Purchase Actual purchase behavior is “Individual’s readiness and willingness to purchase a certain product or service”. Q30. How much have you spent on organic food in the past week? * Mark only one oval. ▪ $0-6 ▪ $7-12 ▪ $13-18 ▪ $19-24 ▪ More than $24 Q31. How much are you willing to pay for organic food, compared to conventional food? * Mark only one oval. ▪ 0-25% ▪ 26-50% ▪ 51-75% ▪ 76-100% ▪ More than 100% Q32. How many times have you consumed organic food in the past week? * Mark only one oval. ▪ 0-1 time. ▪ 2-3 times. ▪ 4-5 times. ▪ 6-7 times. ▪ More than 7 times. Personal basic information Q33. Please state your gender. * Mark only one oval. ▪ Male. ▪ Female. Q34. Please state your age group. * Mark only one oval. ▪ 18-25

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▪ 26-30 ▪ 31-40 ▪ 41-50 ▪ Above 50 Q35. Please state your education level. * Mark only one oval. ▪ Elementary school. ▪ Upper secondary school. ▪ Bachelor. ▪ Master. ▪ PhD. Q36. Please state your monthly income group. * Mark only one oval. ▪ $0-1000 ▪ $1001-2000 ▪ $2001-3000 ▪ $3001-4000 ▪ Above $4000

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Appendix 2: Independent sample T-Test

Group Statistics Std. Error Question 2 N Mean Std. Deviation Mean Zscore: Question 3 Chinese 100 .1016447 .98697576 .09869758 Swedish 100 -.1016447 1.00752562 .10075256 Zscore: Question 4 Chinese 100 -.2183607 .96064379 .09606438 Swedish 100 .2183607 .99545892 .09954589 Zscore: Question 5 Chinese 100 .0134488 .91233893 .09123389 Swedish 100 -.0134488 1.08506834 .10850683 Zscore: Question 6 Chinese 100 .0727893 .93698738 .09369874 Swedish 100 -.0727893 1.05898634 .10589863 Zscore: Question 7 Chinese 100 -.1974821 .82128905 .08212890 Swedish 100 .1974821 1.12107051 .11210705 Zscore: Question 8 Chinese 100 -.2103115 .85083052 .08508305 Swedish 100 .2103115 1.09399866 .10939987 Zscore: Question 9 Chinese 100 -.2671425 .89269313 .08926931 Swedish 100 .2671425 1.03393812 .10339381 Zscore: Question 10 Chinese 100 -.2614152 .90861279 .09086128 Swedish 100 .2614152 1.02296990 .10229699 Zscore: Question 11 Chinese 100 .0276656 .86603014 .08660301 Swedish 100 -.0276656 1.12184962 .11218496 Zscore: Question 12 Chinese 100 -.2296123 .98071145 .09807114 Swedish 100 .2296123 .97046247 .09704625 Zscore: Question 13 Chinese 100 -.3187062 .96803133 .09680313 Swedish 100 .3187062 .93156700 .09315670 Zscore: Question 14 Chinese 100 -.2089457 .85152895 .08515289 Swedish 100 .2089457 1.09398393 .10939839 Zscore: Question 15 Chinese 100 -.3177138 .87030418 .08703042 Swedish 100 .3177138 1.02408415 .10240842 Zscore: Question 16 Chinese 100 -.3471964 .85606927 .08560693 Swedish 100 .3471964 1.01672044 .10167204 Zscore: Question 17 Chinese 100 .1277936 .88909086 .08890909 Swedish 100 -.1277936 1.08932370 .10893237 Zscore: Question 18 Chinese 100 -.3636680 .91488992 .09148899 Swedish 100 .3636680 .95178611 .09517861

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Zscore: Question 19 Chinese 100 -.0412326 .95492770 .09549277 Swedish 100 .0412326 1.04631711 .10463171 Zscore: Question 20 Chinese 100 -.1651776 .88794832 .08879483 Swedish 100 .1651776 1.08006034 .10800603 Zscore: Question 21 Chinese 100 .3225068 .92901180 .09290118 Swedish 100 -.3225068 .96794397 .09679440 Zscore: Question 22 Chinese 100 -.0532256 .96848456 .09684846 Swedish 100 .0532256 1.03267396 .10326740 Zscore: Question 23 Chinese 100 .0774393 .98935818 .09893582 Swedish 100 -.0774393 1.00953284 .10095328 Zscore: Question 24 Chinese 100 -.0133595 .97826191 .09782619 Swedish 100 .0133595 1.02603318 .10260332 Zscore: Question 25 Chinese 100 .1964122 .87438127 .08743813 Swedish 100 -.1964122 1.08056630 .10805663 Zscore: Question 26 Chinese 100 .3537000 .97856847 .09785685 Swedish 100 -.3537000 .89429865 .08942986 Zscore: Question 27 Chinese 100 .1045270 .86296436 .08629644 Swedish 100 -.1045270 1.11504306 .11150431 Zscore: Question 28 Chinese 100 .1377423 .83937013 .08393701 Swedish 100 -.1377423 1.12571293 .11257129 Zscore: Question 29 Chinese 100 .2865760 .80691236 .08069124 Swedish 100 -.2865760 1.09228325 .10922833 Zscore: Question 30 Chinese 100 -.2233722 .90501039 .09050104 Swedish 100 .2233722 1.04415467 .10441547 Zscore: Question 31 Chinese 100 -.0242859 .99566459 .09956646 Swedish 100 .0242859 1.00874254 .10087425 Zscore: Question 32 Chinese 100 -.3019792 .79607443 .07960744 Swedish 100 .3019792 1.09185227 .10918523

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Appendix 3: Descriptive statistics for Chinese cluster

Descriptive Statistics N Skewness Kurtosis Statistic Statistic Std. Error Statistic Std. Error Question 3 100 .054 .241 -.855 .478 Question 4 100 .374 .241 -.615 .478 Question 5 100 .377 .241 -.303 .478 Question 6 100 -.086 .241 -1.129 .478 Question 7 100 .152 .241 -.444 .478 Question 8 100 .175 .241 -.592 .478 Question 9 100 -.327 .241 -.633 .478 Question 10 100 -.242 .241 -.586 .478 Question 11 100 -.237 .241 -.454 .478 Question 12 100 -1.023 .241 .588 .478 Question 13 100 -.611 .241 -.262 .478 Question 14 100 -.098 .241 -.904 .478 Question 15 100 -.246 .241 -.308 .478 Question 16 100 -.126 .241 -.503 .478 Question 17 100 -.320 .241 -.512 .478 Question 18 100 .314 .241 -.515 .478 Question 19 100 -.060 .241 -.464 .478 Question 20 100 .050 .241 -.297 .478 Question 21 100 -.208 .241 -1.224 .478 Question 22 100 -.143 .241 -1.270 .478 Question 23 100 -.131 .241 -1.258 .478 Question 24 100 .142 .241 -.823 .478 Question 25 100 -.272 .241 -.337 .478 Question 26 100 .262 .241 -.833 .478 Question 27 100 -.249 .241 -.532 .478 Question 28 100 -.278 .241 .211 .478 Question 29 100 -.064 .241 -.083 .478 Question 30 100 .844 .241 .042 .478 Question 31 100 1.390 .241 1.527 .478 Question 32 100 .987 .241 .874 .478 Valid N (listwise) 100

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Appendix 4: Descriptive statistics for Swedish cluster

Descriptive Statistics N Skewness Kurtosis Statistic Statistic Std. Error Statistic Std. Error Question 3 100 -.104 .241 .071 .478 Question 4 100 -.752 .241 .429 .478 Question 5 100 .056 .241 -.706 .478 Question 6 100 -.205 .241 -.557 .478 Question 7 100 -.484 .241 -.946 .478 Question 8 100 -.450 .241 -.925 .478 Question 9 100 -1.622 .241 1.949 .478 Question 10 100 -1.317 .241 1.321 .478 Question 11 100 -.561 .241 -.514 .478 Question 12 100 -3.472 .241 13.375 .478 Question 13 100 -2.882 .241 8.678 .478 Question 14 100 -1.400 .241 1.074 .478 Question 15 100 -1.309 .241 .839 .478 Question 16 100 -1.631 .241 1.928 .478 Question 17 100 -.250 .241 -.666 .478 Question 18 100 -.622 .241 -.293 .478 Question 19 100 -.130 .241 -.824 .478 Question 20 100 -.541 .241 .054 .478 Question 21 100 .333 .241 -.935 .478 Question 22 100 -.648 .241 -.269 .478 Question 23 100 -.394 .241 -.362 .478 Question 24 100 -.179 .241 -.640 .478 Question 25 100 -.141 .241 -.922 .478 Question 26 100 .707 .241 -.014 .478 Question 27 100 -.593 .241 -.551 .478 Question 28 100 -.372 .241 -.390 .478 Question 29 100 -.051 .241 -.536 .478 Question 30 100 .250 .241 -1.056 .478 Question 31 101 1.314 .240 1.254 .476 Question 32 101 .344 .240 -1.001 .476 Valid N (listwise) 100

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Appendix 5: Regression coefficients of model 7 from the Chinese cluster

Coefficientsa Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig. 1 (Constant) .003 .066 .050 .960 Zscore: Question 33 .092 .074 .106 1.247 .216 Zscore: Question 34 -.019 .079 -.021 -.234 .815 Zscore: Question 35 -.074 .092 -.082 -.808 .421 Zscore: Question 36 .188 .087 .216 2.152 .034 ZCommunitySupport .112 .104 .114 1.070 .287 ZDiversity .239 .111 .241 2.161 .033 ZEmployeeSupport -.071 .094 -.075 -.747 .457 ZEnvironment .381 .106 .333 3.608 .001 ZOverseasOperations .245 .092 .255 2.651 .010 ZProduct -.061 .090 -.065 -.682 .497 a. Dependent Variable: ZAttitude

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Appendix 6: Regression coefficients of model 10 from the Chinese cluster

Coefficientsa Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig. 1 (Constant) .061 .075 .802 .424 Zscore: Question 33 .056 .080 .059 .702 .485 Zscore: Question 34 -.075 .087 -.077 -.856 .394 Zscore: Question 35 .063 .099 .063 .638 .525 Zscore: Question 36 .311 .101 .324 3.075 .003 ZAttitude .501 .103 .454 4.840 .000 ZHorizontalModerator -.144 .102 -.126 -1.411 .162 ZVerticalModerator .049 .100 .043 .488 .627 a. Dependent Variable: ZPurchase

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Appendix 7: Regression coefficients of model 7 from the Swedish cluster

Coefficientsa Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig. 1 (Constant) -.001 .069 -.008 .993 Zscore: Question 33 -.061 .072 -.084 -.847 .399 Zscore: Question 34 .105 .092 .145 1.145 .255 Zscore: Question 35 .031 .077 .044 .407 .685 Zscore: Question 36 .016 .097 .022 .168 .867 ZCommunitySupport .299 .100 .325 2.992 .004 ZDiversity -.035 .112 -.041 -.314 .754 ZEmployeeSupport .029 .103 .034 .281 .779 ZEnvironment .098 .102 .106 .963 .338 ZOverseasOperations .001 .118 .001 .011 .991 ZProduct .059 .096 .067 .611 .543 a. Dependent Variable: ZAttitude

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Appendix 8: Regression coefficients of model 10 from the Swedish cluster

Coefficientsa Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig. 1 (Constant) .034 .074 .457 .649 Zscore: Question 33 .060 .071 .081 .844 .401 Zscore: Question 34 .153 .092 .205 1.652 .102 Zscore: Question 35 .073 .076 .098 .954 .342 Zscore: Question 36 -.040 .096 -.054 -.423 .673 ZAttitude .302 .101 .293 2.976 .004 ZHorizontalModerator .136 .145 .115 .939 .350 ZVerticalModerator -.190 .143 -.164 -1.331 .187 a. Dependent Variable: ZPurchase

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