Organic foods purchase intention, food safety information, and information on organic foods: Value orientations as a mediator
Main Article Content
We explored the relationships of food safety information, information on organic foods, and Chinese consumers’ purchase intention, with value orientations proposed as a mediator. The research model was based on the stimulus–organism–response theoretical model and regulatory focus theory. Data were collected using a structured survey with 206 consumers of organic foods. We employed structural equation modelling for data analysis. The results show that information on organic food and information on food safety were significantly associated with environmental value orientation. Organic food information was significantly associated with both health value orientation and hedonic value orientation. In addition, information on food safety, information on organic food, environmental orientation, and hedonic orientation were all significantly associated with purchase intention. Moreover, both environmental orientation and hedonic orientation exerted mediating effects in the relationships between organic food information and consumers’ purchase intention. The results provide novel and valuable insights for understanding organic consumption and offer guidance for the development and promotion of China’s organic food industry.
Food safety incidents and environmental issues have prompted consumers to pay more attention to safer, healthier, and more environmentally friendly organic foods (Hsu & Chen, 2014; Teng & Lu, 2016). Therefore, the market for organic foods has grown rapidly throughout the world. The total market value of organic foods in China in 2019 was estimated to be 8.5 billion euros, making this the world’s fourth-largest organic food market (Willer et al., 2021). However, China’s per capita consumption was valued at approximately 6 euros, less than half the value of per capita consumption globally (Willer et al., 2021). In addition, compared with developed countries (e.g., the United States, Denmark, and Australia), China’s organic food market started late and consumers still lack understanding of organic foods (Liu et al., 2021), which hinders the development of the organic foods industry in this country.
The topic of consumption of organic foods has been widely discussed in previous studies. Some have expressed the belief that consumers’ value orientations play an important role in promoting their purchase of organic products (Hidalgo-Baz et al., 2017; Suh et al., 2015; X. Wang et al., 2019). Loebnitz and Aschemann-Witzel (2016) and Pagiaslis and Krontalis (2014) stated that environmental orientation is a key factor to explain purchase behavior in regard to organic foods. In addition, Basha and Lal (2019) and Yiridoe et al. (2005) showed that consumers’ health orientation is their main motivation to buy organic foods. Moreover, Cervellon and Carey (2014) indicated that hedonic orientation had a significant positive impact on consumers’ organic foods purchase intention.
With the rapid development of various social media in China (e.g., Microblog, WeChat, and Zhihu), consumers can obtain a variety of information through these websites. de-Magistris and Gracia (2016) expressed the view that as consumers obtain most of their information about organic foods from the media, they are more inclined to buy these products. In addition, Hjelmar (2011) observed that consumers who have seen reports of nonorganic food scandals on television tend to buy organic foods. However, the effects of information on consumption of organic foods have not yet been well studied; in particular, the impact of information in different dimensions on organic food consumption (i.e., promotion-focused goals of organic food information, prevention-focused goals of food safety information). Therefore, we used the stimulus–organism–response (SOR) theoretical model (Mehrabian & Russell, 1974) and regulatory focus theory (Higgins, 1997) to explore the relationships of information on organic foods and information on food safety with consumers’ organic-food purchase intention, and also examined value orientations as a mediator of these relationships.
Information on Organic Foods and on Food Safety, Value Orientations, and Organic Foods Purchase Intention
Mehrabian and Russell (1974) proposed the SOR theoretical model based on the perspective of environmental psychology. According to this model, all aspects of the environment play a stimulating role, affecting people’s internal states (e.g., perception, sensation, and value orientations), which drives their behavioral responses. The SOR theoretical model provides a simple and structured method to study consumer behaviors and has been extensively used in previous studies in this context (Liu & Zheng, 2019; Luqman et al., 2017). For example, Liu and Zheng (2019) applied the model to study the relationships between food safety incidents and consumer behavior. Therefore, we applied the SOR model to consumption of organic foods, proposing that with organic food information and food safety information as stimuli, consumers’ psychological changes (i.e., health orientation, environmental orientation, and hedonic orientation) would be affected, so as to drive them to make a behavioral response (i.e., organic foods purchase intention).
In China, food safety incidents have prompted consumers to seek healthier and safer foods (Hsu & Chen, 2014; Teng & Lu, 2016), and the rapid development of various social media means consumers can obtain various types of information (e.g., food safety information and organic food information) through these websites. Ruiz Mafé and Sanz Blas (2006) found that when consumers have been exposed to organic food information and food safety information through various information channels, this helps to change their cognition, attitude, and value orientations. Pham et al. (2019) pointed out that organic food information is positively related to environmental orientation. Therefore, we proposed the following hypotheses:
Hypothesis 1a: Food safety information will be positively associated with consumers’ health orientation.
Hypothesis 1b: Food safety information will be positively associated with consumers’ environmental orientation.
Hypothesis 1c: Food safety information will be positively associated with consumers’ hedonic orientation.
Hypothesis 2a: Organic food information will be positively associated with consumers’ health orientation.
Hypothesis 2b: Organic food information will be positively associated with consumers’ environmental orientation.
Hypothesis 2c: Organic food information will be positively associated with consumers’ hedonic orientation.
In addition, value orientations are considered important predictors of consumer purchase decision making (Hidalgo-Baz et al., 2017; Sheth et al., 1991). Nosi et al. (2020) found that environmental orientation had a significant positive impact on consumers’ purchase intention for organic products. In addition, Basha and Lal (2019) and Yiridoe et al. (2005) showed that consumers’ health orientation was their main motivation to buy organic foods. Moreover, Cervellon and Carey (2014) indicated that consumers perceive organic foods as tastier and having a better visual appearance and more attractive scent compared with conventionally produced foods. Therefore, we proposed the following hypotheses:
Hypothesis 3: Consumers’ health orientation will be positively associated with their purchase intention for organic foods.
Hypothesis 4: Consumers’ environmental orientation will be positively associated with their purchase intention for organic foods.
Hypothesis 5: Consumers’ hedonic orientation will be positively associated with their purchase intention for organic foods.
Information on Organic Foods and on Food Safety, and Organic Foods Purchase Intention
According to regulatory focus theory (Higgins, 1997), there are two coexisting but different self-regulatory processes: promotion-focused regulation and prevention-focused regulation. Through these processes, people approach pleasure and avoid pain (Higgins, 1997; Hu et al., 2015). Regulatory focus theory states that different motivations lead individuals to use either promotion- or prevention-focused regulation to achieve the same goal. Promotion-focused individuals seek the presence of positive outcomes to match their goals. In contrast, prevention-focused individuals seek the absence of negative outcomes to prevent their goals from being mismatched (Brockner & Higgins, 2001; Higgins, 1997). As already described, repeated food safety incidents relating to nonorganic foods in China, for example, Shuanghui “lean” events have led to consumers paying more attention to food safety issues (Hsu & Chen, 2014) and, alongside this, with the rapid development of various social media in China, consumers can obtain more information on food safety and on organic foods. Therefore, within the context of different information, consumers may make the decision to buy organic food based on their own regulatory-focused goals. Accordingly, we applied regulatory focus theory to consumption of organic foods.
Per regulatory focus theory, on the one hand, consumers who pay attention to food safety information may purchase organic food, which is generally considered to have higher nutritional value and is produced in a more natural way without chemicals or harmful pesticides compared with nonorganic food (de-Magistris & Gracia, 2016), in order to satisfy prevention-focused goals (i.e., preventing eating unsafe food). On the other hand, consumers who pay attention to organic food information may purchase organic food to meet their promotion-focused goals (i.e., eating healthier, safer, and more environmentally produced food). Previous researchers have reported that consumers may increase their purchase of organic foods after experiencing nonorganic food safety incidents, such as avian influenza and E. coli epidemics (Pagiaslis & Krontalis, 2014). Pham et al. (2019) pointed out that consumers who have paid attention to organic food information are more likely to buy organic foods. Therefore, we proposed the following hypotheses:
Hypothesis 6a: Food safety information will be positively associated with consumers’ purchase intention for organic foods.
Hypothesis 6b: Organic food information will be positively associated with consumers’ purchase intention for these foods.
Mediating Role of Value Orientations
Previous studies have indicated that value orientations are important predictors of consumer decision making (Hidalgo-Baz et al., 2017; Sheth et al., 1991). Nosi et al. (2020) found that having an environmental orientation had a significant positive impact on organic food purchase intention. In addition, C. Wang et al. (2019) showed that value orientations and beliefs mediated the relationship between consumer motivation and sustainable product purchase intention. Therefore, it can be postulated that value orientations are mediators linking the relationship between consumers’ purchase intention for organic foods, and information on organic food and on food safety. Accordingly, we proposed the following hypotheses:
Hypothesis 7a: Consumers’ health orientation will mediate the effect of food safety information on their purchase intention for organic foods.
Hypothesis 7b: Consumers’ health orientation will mediate the effect of organic food information on their purchase intention for organic foods.
Hypothesis 8a: Consumers’ environmental orientation will mediate the effect of food safety information on their purchase intention for organic foods.
Hypothesis 8b: Consumers’ environmental orientation will mediate the effect of organic food information on their purchase intention for organic foods.
Hypothesis 9a: Consumers’ hedonic orientation will mediate the effect of food safety information on their purchase intention for organic foods.
Hypothesis 9b: Consumers’ hedonic orientation will mediate the effect of organic food information on their purchase intention for organic foods.
Thus, using the SOR theoretical model (Mehrabian & Russell, 1974) and regulatory focus theory (Higgins, 1997) as the research framework, we applied structural equation modelling (SEM) to build a model of consumers’ organic foods purchasing intention (see Figure 1).
Figure 1. Research Framework
Method
Participants and Procedure
Data were collected at a university in Jiangxi, China, from 212 college students who completed a pen-and-paper survey in class. The students were first informed that we were conducting a scientific study on organic food consumption, and as their answers would have an important impact on the study results, they needed to respond carefully. Students were also told that their participation in the survey was voluntary and that they had the right to choose not to take part. Ethical approval was not required as per applicable institutional and national guidelines and regulations of China, and the informed consent of the participants was implied through survey completion.
After excluding outliers in the study, we analyzed data collected from 206 college students. Participants were aged between 18 and 30 years (M = 19.50, SD = 0.73). The demographic profile of the sample is shown in Table 1.
Table 1. Demographic Profile of the Sample
Note. N = 206. ¥ 1.00 = USD 0.16.
Measures
Except for control variables, all responses were made on a 5-point Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree). Higher scores indicate a higher level of the assessed variable. All measures were adopted from scales developed in the English language, and were translated into Chinese by two graduate students majoring in English. The divergence between the English and Chinese versions was resolved by careful checking with the back-translation procedure.
Food Safety Information
Three items measuring food safety information were developed using input from Bryła (2021), Lockwood et al. (2002), and Pham et al. (2019): “I’m very concerned about food safety information,” “I often pay attention to food processing information,” and “The quality and safety of food nowadays concern me.”
Organic Food Information
Three items measuring organic food information were developed using inputs from Bryła (2021), Lockwood et al. (2002), and Teng and Lu (2016): “I often pay attention to organic food information,” “I am willing to seek out organic food information,” and “Organic food information is continually of interest to me.”
Health Orientation
Three items were used to measure health orientation (Teng & Lu, 2016): “When I buy food, I consider the extent to which food affects health,” “I take responsibility for the state of my health,” and “I’m very self-conscious about my health.”
Environmental Orientation
Three items were used to measure environmental orientation (Hidalgo-Baz et al., 2017): “I’m very concerned about the environment,” “I think my behavior is eco-friendly,” and “I take into account the environmental impact when I buy food.”
Hedonic Orientation
Three items were used to measure hedonic orientation (Hidalgo-Baz et al., 2017): “I usually indulge in eating some kinds of food,” “Some food intake makes me feel better, happier,” and “When buying food, I mainly consider the taste of the food.”
Purchase Intention for Organic Foods
The items measuring purchase intention for organic foods were sourced from Pham et al. (2019) and Teng and Lu (2016): “I am glad to buy organic food,” “I plan to consume organic food,” and “I would buy organic food products.”
Results
Validity of Measurement Model
To evaluate the measurement model, all constructs were processed in a confirmatory factor analysis (CFA) using Amos 24.0. According to the results, all fit indices of the measurement model, including chi square (χ2), degrees of freedom (df), adjusted goodness-of-fit index (AGFI), goodness-of-fit index (GFI), comparative fit index (CFI), and root mean square error of approximation (RMSEA), reached the criteria of acceptable model fit (Chau & Hu, 2001), χ2 = 190.37, df = 123; χ2/df = 1.55; AGFI = .88, GFI = .91, CFI = .95, RMSEA = .05. Thus, the hypothesized model had a good fit to the data.
The internal consistency reliability, convergent validity, and discriminant validity were measured by Cronbach’s alpha, composite reliability (CR), standardized factor loadings, and average variance extracted (AVE). As shown in Table 2, Cronbach’s alpha and CR values were over .70; thus, internal consistency reliability was acceptable (Nunnally, 1978). In addition, the values for standardized factor loadings were over .60 and the values for AVE were over .50, indicating convergent validity was acceptable (Fornell & Larcker, 1981). Moreover, results in Table 3 show that the estimated intercorrelations among all constructs were less than the square roots of the AVE in each construct, providing support for discriminant validity (Fornell & Larcker, 1981).
Table 2. Coefficients for the Measurement Model
Note. CR = composite reliability; AVE = average variance extracted.
Table 3. Means, Standard Deviations, and Correlations of Study Variables
Note. Values in boldface denote the square root of average variance extracted for discriminant validity.
* p < .05. ** p < .01.
Hypothesis Testing
We used SEM to test the relationships between variables, including control variables. The resulting fit indices were as follows: χ2 = 243.30, df = 177; χ2/df = 1.38; AGFI = .87, GFI = .90, CFI = .95, RMSEA = .04. These indices demonstrated the model had a good fit to the data.
As shown in Table 4, the results of the hypothesis testing indicate that eight hypotheses were supported (Hypotheses 1b, 2a–2c, 4, 5, 6a, and 6b). Notably, food safety information and organic food information were significantly associated with environmental orientation, supporting Hypotheses 1b and 2b, respectively. Organic food information was significantly associated with health orientation and hedonic orientation, supporting Hypotheses 2a and 2c, respectively. Environmental orientation, hedonic orientation, food safety information, and organic food information showed significant associations with purchase intention, supporting Hypotheses 4, 5, 6a, and 6b, respectively.
Table 4. Results of Hypothesis Testing
Note. FSI = food safety information; HO = health orientation; EO = environmental orientation; HEO = hedonic orientation; OFI = organic food information; PI = purchase intention; CI = confidence interval; LL = lower limit; UL = upper limit.
To investigate the indirect effects of organic food information and food safety information (independent variables) on consumers’ purchase intention through value orientations (mediating variable), bootstrapping analysis was performed. Table 5 shows that organic food information had indirect effects on purchase intention, such that environmental orientation mediated the influence of organic food information on purchase intention and hedonic orientation mediated the influence of organic food information on purchase intention, supporting Hypotheses 8b and 9b. However, food safety information did not have an indirect effect on purchase intention; thus, Hypotheses 8a and 9a were not supported.
Table 5. Indirect Effects for the Model
Note. Number of bootstrapped resamples = 5,000. IE = indirect effect; FSI = food safety information; HO = health orientation; PI = purchase intention; OFI = organic food information; EO = environmental orientation; HEO = hedonic orientation.
Discussion
First, we found that food safety information and organic food information were both significantly associated with participants’ environmental orientation. Our findings are consistent with those reported in previous studies (Pham et al., 2019; Ruiz Mafé & Sanz Blas, 2006). In addition, we found that organic food information was positively associated with both health orientation and hedonic orientation, which is in line with the results reported in the extant literature (Hidalgo-Baz et al., 2017; Ruiz Mafé & Sanz Blas, 2006). In other words, the more organic food information consumers have, the stronger are their health and hedonic orientations. Moreover, food safety information and organic food information were positively associated with participants’ purchase intention for organic foods, which is in line with previous results (Hsu & Chen, 2014; Pham et al., 2019). Further, the more food safety information consumers obtained, the stronger was their tendency to buy organic foods to meet both prevention- and promotion-focused goals. However, we found that food safety information was not significantly associated with either health orientation or hedonic orientation, which is inconsistent with our predictions. One possible reason for this finding is that consumers may lack understanding regarding organic foods. Because the mainstream consumption of organic food in China is uncommon at present (Kushwah et al., 2019), most consumers lack full understanding of organic food (e.g., unaware of the healthy attributes of organic food). Moreover, Green and Knechtges (2015) pointed out that young consumers overall have little knowledge of organic food practices. Because our sample comprised young people, this may explain why we found that food safety information was not significantly associated with health orientation and hedonic orientation among our participants.
Second, regarding value orientations, we found that environmental orientation and hedonic orientation were positively associated with participants’ purchase intention for organic foods, which is in line with the results in prior literature (Hidalgo-Baz et al., 2017; Sheth et al., 1991). However, health orientation was not significantly associated with purchase intention for organic foods, which is inconsistent with previous research results (Bryła, 2016). Kuhn et al. (2007) found that older adults are more health-oriented than are young adults, which might explain the result in our study, because our sample consisted of young consumers aged between 18 and 30 years.
Finally, environmental orientation and hedonic orientation exerted mediating effects in the relationship between organic food information and participants’ purchase intention for these foods. As we had expected, there were relationships among organic food information, value orientations, and purchase intention for organic foods. However, value orientations did not exert a mediating effect in the relationship between food safety information and purchase intention in regard to organic foods. This was not in line with our prediction and may have occurred because after consumers obtain food safety information, this has a direct impact on their intention to buy organic food. Thus, value orientations may not be needed to affect organic consumption indirectly. We also found a significant positive correlation between food safety information and organic purchase intention.
Theoretical Contributions
This study offers three major theoretical contributions. First, we explored the relationship between consumers’ promotion-focused goals in regard to organic food information, prevention-focused goals in regard to food safety information, and organic foods purchase intention by applying regulatory focus theory. This may provide a new perspective for organic food consumption research. Second, the focus in previous studies has been either on the impact of food safety information on consumers’ organic food purchase intention or on the impact of organic food information on organic food purchase intention. However, few studies have focused on the joint impact of both food safety information and organic food information. To address this lack, we divided the information into two dimensions: food safety information and organic food information, according to consumers’ different regulatory-focused goals, and explored the relationship between information in these two different dimensions and consumers’ organic food purchase intention. This may enrich the existing research on organic food consumption. Finally, our study expands the emerging literature on the application of the SOR theoretical model in the context of organic food, providing insights into associations that had not been studied previously. The novelty of this study is our introduction of regulatory focus theory and examination of the interplay between information representing different dimensions, value orientations, and organic food purchase intention, which is a unique contribution to the marketing literature.
Practical Implications
This study offers two main practical implications. First, our results show that value orientations played an important role in promoting people’s purchase intentions for organic foods. Therefore, policymakers should formulate strategies to strengthen value orientations related to organic food consumption. Through education and publicity, policymakers can promote the concept of breeding and growing of organic crops as beneficial to ecology and human health, and enhance consumers’ value orientations to promote the development of China’s organic food industry. In addition, we found that food safety information and organic food information both have an important impact on people’s purchase intention for organic foods. Therefore, to promote the development of the organic food market, organic food producers, retailers, and policymakers should use various information channels to enhance consumers’ access to more organic food information and food safety information. For example, to promote the public’s understanding of organic food, producers and retailers can show consumers the organic food production process through a variety of media channels, such as the Internet and the WeChat social media platform. Policymakers can also display more authoritative food safety information to the public through the media.
Study Limitations and Directions for Future Research
This study has several limitations that provide directions for future research. First, we considered only organic food information and food safety information, so that other relevant types of information may have been ignored, such as environmental information and policy information, especially in the context of COVID-19. In future studies, researchers may consider other information to enrich the results we obtained. In addition, our results were based on research with a cross-sectional design, which does not allow for conclusions to be drawn regarding causality. Future researchers could use the Granger causality test of panel data to measure the causal links between variables.
References
Basha, M. B., & Lal, D. (2019). Indian consumers’ attitudes towards purchasing organically produced foods: An empirical study. Journal of Cleaner Production, 215, 99–111.
https://doi.org/10.1016/j.jclepro.2018.12.098
Brockner, J., & Higgins, E. T. (2001). Regulatory focus theory: Implications for the study of emotions at work. Organizational Behavior and Human Decision Processes, 86(1), 35–66.
https://doi.org/10.1006/obhd.2001.2972
Bryła, P. (2016). Organic food consumption in Poland: Motives and barriers. Appetite, 105, 737–746.
https://doi.org/10.1016/j.appet.2016.07.012
Bryła, P. (2021). The impact of consumer Schwartz values and regulatory focus on the willingness to pay a price premium for domestic food products: Gender differences. Energies, 14(19), Article 6198.
https://doi.org/10.3390/en14196198
Cervellon, M.-C., & Carey, L. I. (2014). Sustainable, hedonic and efficient: Interaction effects between product properties and consumer reviews on post-experience responses. European Journal of Marketing, 48(7/8), 1375–1394.
https://doi.org/10.1108/EJM-07-2012-0392
Chau, P. Y. K., & Hu, P. J.-H. (2001). Information technology acceptance by individual professionals: A model comparison approach. Decision Sciences, 32(4), 699–719.
https://doi.org/10.1111/j.1540-5915.2001.tb00978.x
de-Magistris, T., & Gracia, A. (2016). Consumers’ willingness-to-pay for sustainable food products: The case of organically and locally grown almonds in Spain. Journal of Cleaner Production, 118, 97–104.
https://doi.org/10.1016/j.jclepro.2016.01.050
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382–388.
https://doi.org/10.1177/002224378101800313
Green, E. J., & Knechtges, P. (2015). Food safety knowledge and practices of young adults. Journal of Environmental Health, 77(10), 18–24. https://bit.ly/3f6PkfT
Hidalgo-Baz, M., Martos-Partal, M., & González-Benito, Ó. (2017). Attitudes vs. purchase behaviors as experienced dissonance: The roles of knowledge and consumer orientations in organic market. Frontiers in Psychology, 8, Article 00248.
https://doi.org/10.3389/fpsyg.2017.00248
Higgins, E. T. (1997). Beyond pleasure and pain. American Psychologist, 52(12), 1280–1300.
https://doi.org/10.1037/0003-066X.52.12.1280
Hjelmar, U. (2011). Consumers’ purchase of organic food products. A matter of convenience and reflexive practices. Appetite, 56(2), 336–344.
https://doi.org/10.1016/j.appet.2010.12.019
Hsu, C.-L., & Chen, M.-C. (2014). Explaining consumer attitudes and purchase intentions toward organic food: Contributions from regulatory fit and consumer characteristics. Food Quality and Preference, 35, 6–13.
https://doi.org/10.1016/j.foodqual.2014.01.005
Hu, C., Zhao, L., & Huang, J. (2015). Achieving self-congruency? Examining why individuals reconstruct their virtual identity in communities of interest established within social network platforms. Computers in Human Behavior, 50, 465–475.
https://doi.org/10.1016/j.chb.2015.04.027
Kuhn, M., Prskawetz, A., Wrzaczek, S., & Feichtinger, G. (2007). Health, survival and consumption over the life cycle: Individual vs. social optimum and the role of externalities (Rostock Center Discussion Paper No. 16). Rostock Center for the Study of Demographic Change. https://bit.ly/3G9FXbr
Kushwah, S., Dhir, A. & Sagar, M. (2019). Understanding consumer resistance to the consumption of organic food. A study of ethical consumption, purchasing, and choice behaviour. Food Quality and Preference, 77, 1–14.
https://doi.org/10.1016/j.foodqual.2019.04.003
Liu, C., & Zheng, Y. (2019). The predictors of consumer behavior in relation to organic food in the context of food safety incidents: Advancing hyper attention theory within a stimulus-organism-response model. Frontiers in Psychology, 10, Article 02512.
https://doi.org/10.3389/fpsyg.2019.02512
Liu, C., Zheng, Y., & Cao, D. (2021). An analysis of factors affecting selection of organic food: Perception of consumers in China regarding weak signals. Appetite, 161, Article 105145.
https://doi.org/10.1016/j.appet.2021.105145
Lockwood, P., Jordan, C. H., & Kunda, Z. (2002). Motivation by positive or negative role models: Regulatory focus determines who will best inspire us. Journal of Personality and Social Psychology, 83(4), 854–864.
https://doi.org/10.1037/0022-3514.83.4.854
Loebnitz, N., & Aschemann-Witzel, J. (2016). Communicating organic food quality in China: Consumer perceptions of organic products and the effect of environmental value priming. Food Quality and Preference, 50, 102–108.
https://doi.org/10.1016/j.foodqual.2016.02.003
Luqman, A., Cao, X., Ali, A., Masood, A., & Yu, L. (2017). Empirical investigation of Facebook discontinues usage intentions based on SOR paradigm. Computers in Human Behavior, 70, 544–555.
https://doi.org/10.1016/j.chb.2017.01.020
Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. The MIT Press.
Nosi, C., Zollo, L., Rialti, R., & Ciappei, C. (2020). Sustainable consumption in organic food buying behavior: The case of quinoa. British Food Journal, 122(3), 976–994.
https://doi.org/10.1108/BFJ-09-2019-0745
Nunnally, J. C. (1978). Psychometric theory (2nd ed.). McGraw-Hill.
Pagiaslis, A., & Krontalis, A. K. (2014). Green consumption behavior antecedents: Environmental concern, knowledge, and beliefs. Psychology & Marketing, 31(5), 335–348.
https://doi.org/10.1002/mar.20698
Pham, T. H., Nguyen, T. N., Phan, T. T. H., & Nguyen, N. T. (2019). Evaluating the purchase behaviour of organic food by young consumers in an emerging market economy. Journal of Strategic Marketing, 27(6), 540–556.
https://doi.org/10.1080/0965254X.2018.1447984
Ruiz Mafé, C., & Sanz Blas, S. (2006). Explaining Internet dependency: An exploratory study of future purchase intention of Spanish Internet users. Internet Research, 16(4), 380–397.
https://doi.org/10.1108/10662240610690016
Sheth, J. N., Newman, B. I., & Gross, B. L. (1991). Why we buy what we buy: A theory of consumption values. Journal of Business Research, 22(2), 159–170.
https://doi.org/10.1016/0148-2963(91)90050-8
Suh, B. W., Eves, A., & Lumbers, M. (2015). Developing a model of organic food choice behavior. Social Behavior and Personality: An international journal, 43(2), 217–230.
https://doi.org/10.2224/sbp.2015.43.2.217
Teng, C.-C., & Lu, C.-H. (2016). Organic food consumption in Taiwan: Motives, involvement, and purchase intention under the moderating role of uncertainty. Appetite, 105, 95–105.
https://doi.org/10.1016/j.appet.2016.05.006
Wang, C., Ghadimi, P., Lim, M. K., & Tseng, M.-L. (2019). A literature review of sustainable consumption and production: A comparative analysis in developed and developing economies. Journal of Cleaner Production, 206, 741–754.
https://doi.org/10.1016/j.jclepro.2018.09.172
Wang, X., Xiong, Y., Yang, R., & Yu, P. (2019). Social psychological predictors of adoption intention for solar water heaters in rural China. Social Behavior and Personality: An international journal, 47(12), Article e8549.
https://doi.org/10.2224/sbp.8549
Willer, H., Trávníček, J., Meier, C., & Schlatter, B. (Eds.). (2021). The world of organic agriculture: Statistics and emerging trends 2021. Research Institute of Organic Agriculture FiBL, Frick, and IFOAM-Organics International. https://bit.ly/331VYSb
Yiridoe, E. K., Bonti-Ankomah, S., & Martin, R. C. (2005). Comparison of consumer perceptions and preference toward organic versus conventionally produced foods: A review and update of the literature. Renewable Agriculture and Food Systems, 20(4), 193–205.
https://doi.org/10.1079/RAF2005113
Basha, M. B., & Lal, D. (2019). Indian consumers’ attitudes towards purchasing organically produced foods: An empirical study. Journal of Cleaner Production, 215, 99–111.
https://doi.org/10.1016/j.jclepro.2018.12.098
Brockner, J., & Higgins, E. T. (2001). Regulatory focus theory: Implications for the study of emotions at work. Organizational Behavior and Human Decision Processes, 86(1), 35–66.
https://doi.org/10.1006/obhd.2001.2972
Bryła, P. (2016). Organic food consumption in Poland: Motives and barriers. Appetite, 105, 737–746.
https://doi.org/10.1016/j.appet.2016.07.012
Bryła, P. (2021). The impact of consumer Schwartz values and regulatory focus on the willingness to pay a price premium for domestic food products: Gender differences. Energies, 14(19), Article 6198.
https://doi.org/10.3390/en14196198
Cervellon, M.-C., & Carey, L. I. (2014). Sustainable, hedonic and efficient: Interaction effects between product properties and consumer reviews on post-experience responses. European Journal of Marketing, 48(7/8), 1375–1394.
https://doi.org/10.1108/EJM-07-2012-0392
Chau, P. Y. K., & Hu, P. J.-H. (2001). Information technology acceptance by individual professionals: A model comparison approach. Decision Sciences, 32(4), 699–719.
https://doi.org/10.1111/j.1540-5915.2001.tb00978.x
de-Magistris, T., & Gracia, A. (2016). Consumers’ willingness-to-pay for sustainable food products: The case of organically and locally grown almonds in Spain. Journal of Cleaner Production, 118, 97–104.
https://doi.org/10.1016/j.jclepro.2016.01.050
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382–388.
https://doi.org/10.1177/002224378101800313
Green, E. J., & Knechtges, P. (2015). Food safety knowledge and practices of young adults. Journal of Environmental Health, 77(10), 18–24. https://bit.ly/3f6PkfT
Hidalgo-Baz, M., Martos-Partal, M., & González-Benito, Ó. (2017). Attitudes vs. purchase behaviors as experienced dissonance: The roles of knowledge and consumer orientations in organic market. Frontiers in Psychology, 8, Article 00248.
https://doi.org/10.3389/fpsyg.2017.00248
Higgins, E. T. (1997). Beyond pleasure and pain. American Psychologist, 52(12), 1280–1300.
https://doi.org/10.1037/0003-066X.52.12.1280
Hjelmar, U. (2011). Consumers’ purchase of organic food products. A matter of convenience and reflexive practices. Appetite, 56(2), 336–344.
https://doi.org/10.1016/j.appet.2010.12.019
Hsu, C.-L., & Chen, M.-C. (2014). Explaining consumer attitudes and purchase intentions toward organic food: Contributions from regulatory fit and consumer characteristics. Food Quality and Preference, 35, 6–13.
https://doi.org/10.1016/j.foodqual.2014.01.005
Hu, C., Zhao, L., & Huang, J. (2015). Achieving self-congruency? Examining why individuals reconstruct their virtual identity in communities of interest established within social network platforms. Computers in Human Behavior, 50, 465–475.
https://doi.org/10.1016/j.chb.2015.04.027
Kuhn, M., Prskawetz, A., Wrzaczek, S., & Feichtinger, G. (2007). Health, survival and consumption over the life cycle: Individual vs. social optimum and the role of externalities (Rostock Center Discussion Paper No. 16). Rostock Center for the Study of Demographic Change. https://bit.ly/3G9FXbr
Kushwah, S., Dhir, A. & Sagar, M. (2019). Understanding consumer resistance to the consumption of organic food. A study of ethical consumption, purchasing, and choice behaviour. Food Quality and Preference, 77, 1–14.
https://doi.org/10.1016/j.foodqual.2019.04.003
Liu, C., & Zheng, Y. (2019). The predictors of consumer behavior in relation to organic food in the context of food safety incidents: Advancing hyper attention theory within a stimulus-organism-response model. Frontiers in Psychology, 10, Article 02512.
https://doi.org/10.3389/fpsyg.2019.02512
Liu, C., Zheng, Y., & Cao, D. (2021). An analysis of factors affecting selection of organic food: Perception of consumers in China regarding weak signals. Appetite, 161, Article 105145.
https://doi.org/10.1016/j.appet.2021.105145
Lockwood, P., Jordan, C. H., & Kunda, Z. (2002). Motivation by positive or negative role models: Regulatory focus determines who will best inspire us. Journal of Personality and Social Psychology, 83(4), 854–864.
https://doi.org/10.1037/0022-3514.83.4.854
Loebnitz, N., & Aschemann-Witzel, J. (2016). Communicating organic food quality in China: Consumer perceptions of organic products and the effect of environmental value priming. Food Quality and Preference, 50, 102–108.
https://doi.org/10.1016/j.foodqual.2016.02.003
Luqman, A., Cao, X., Ali, A., Masood, A., & Yu, L. (2017). Empirical investigation of Facebook discontinues usage intentions based on SOR paradigm. Computers in Human Behavior, 70, 544–555.
https://doi.org/10.1016/j.chb.2017.01.020
Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. The MIT Press.
Nosi, C., Zollo, L., Rialti, R., & Ciappei, C. (2020). Sustainable consumption in organic food buying behavior: The case of quinoa. British Food Journal, 122(3), 976–994.
https://doi.org/10.1108/BFJ-09-2019-0745
Nunnally, J. C. (1978). Psychometric theory (2nd ed.). McGraw-Hill.
Pagiaslis, A., & Krontalis, A. K. (2014). Green consumption behavior antecedents: Environmental concern, knowledge, and beliefs. Psychology & Marketing, 31(5), 335–348.
https://doi.org/10.1002/mar.20698
Pham, T. H., Nguyen, T. N., Phan, T. T. H., & Nguyen, N. T. (2019). Evaluating the purchase behaviour of organic food by young consumers in an emerging market economy. Journal of Strategic Marketing, 27(6), 540–556.
https://doi.org/10.1080/0965254X.2018.1447984
Ruiz Mafé, C., & Sanz Blas, S. (2006). Explaining Internet dependency: An exploratory study of future purchase intention of Spanish Internet users. Internet Research, 16(4), 380–397.
https://doi.org/10.1108/10662240610690016
Sheth, J. N., Newman, B. I., & Gross, B. L. (1991). Why we buy what we buy: A theory of consumption values. Journal of Business Research, 22(2), 159–170.
https://doi.org/10.1016/0148-2963(91)90050-8
Suh, B. W., Eves, A., & Lumbers, M. (2015). Developing a model of organic food choice behavior. Social Behavior and Personality: An international journal, 43(2), 217–230.
https://doi.org/10.2224/sbp.2015.43.2.217
Teng, C.-C., & Lu, C.-H. (2016). Organic food consumption in Taiwan: Motives, involvement, and purchase intention under the moderating role of uncertainty. Appetite, 105, 95–105.
https://doi.org/10.1016/j.appet.2016.05.006
Wang, C., Ghadimi, P., Lim, M. K., & Tseng, M.-L. (2019). A literature review of sustainable consumption and production: A comparative analysis in developed and developing economies. Journal of Cleaner Production, 206, 741–754.
https://doi.org/10.1016/j.jclepro.2018.09.172
Wang, X., Xiong, Y., Yang, R., & Yu, P. (2019). Social psychological predictors of adoption intention for solar water heaters in rural China. Social Behavior and Personality: An international journal, 47(12), Article e8549.
https://doi.org/10.2224/sbp.8549
Willer, H., Trávníček, J., Meier, C., & Schlatter, B. (Eds.). (2021). The world of organic agriculture: Statistics and emerging trends 2021. Research Institute of Organic Agriculture FiBL, Frick, and IFOAM-Organics International. https://bit.ly/331VYSb
Yiridoe, E. K., Bonti-Ankomah, S., & Martin, R. C. (2005). Comparison of consumer perceptions and preference toward organic versus conventionally produced foods: A review and update of the literature. Renewable Agriculture and Food Systems, 20(4), 193–205.
https://doi.org/10.1079/RAF2005113
Figure 1. Research Framework
Table 1. Demographic Profile of the Sample
Note. N = 206. ¥ 1.00 = USD 0.16.
Table 2. Coefficients for the Measurement Model
Note. CR = composite reliability; AVE = average variance extracted.
Table 3. Means, Standard Deviations, and Correlations of Study Variables
Note. Values in boldface denote the square root of average variance extracted for discriminant validity.
* p < .05. ** p < .01.
Table 4. Results of Hypothesis Testing
Note. FSI = food safety information; HO = health orientation; EO = environmental orientation; HEO = hedonic orientation; OFI = organic food information; PI = purchase intention; CI = confidence interval; LL = lower limit; UL = upper limit.
Table 5. Indirect Effects for the Model
Note. Number of bootstrapped resamples = 5,000. IE = indirect effect; FSI = food safety information; HO = health orientation; PI = purchase intention; OFI = organic food information; EO = environmental orientation; HEO = hedonic orientation.
This work was supported by the National Natural Science Foundation of China (71663038
72064027) and the Jiangxi Social Science 14th Five-Year Plan fund project (21ST03).
Yan Zheng, School of Management, Nanchang University, Nanchang 330031, People’s Republic of China. Email: [email protected]