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ISSN : 2288-4637(Print)
ISSN : 2288-4645(Online)
The Journal of Asian Finance, Economics and Business Vol.7 No.10 pp.949-957
DOI : https://doi.org/10.13106/jafeb.2020.vol7.no10.949

# Intention to Accept Organic Agricultural Production of Vietnamese Farmers: An Investigation Using the Theory of Planned Behavior

Van Hau NGUYEN1,Thi Phuong Linh NGUYEN2
*Acknowledgements:
This research is funded by National Economics University, Hanoi, Vietnam.
2Faculty of Business Management, National Economics University, Vietnam. Email: linhnp@neu.edu.vn

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
1First Author and Corresponding Author. Faculty of Political Theory, National Economics University, Vietnam [Postal Address: 207 Giai Phong Street, Hai Ba Trung District, Hanoi, 10000-14000, Vietnam] Email: nvhau@neu.edu.vn.
August 01, 2020 September 06, 2020 September 10, 2020

## Abstract

The purpose of this paper is to investigate the factors influencing the Vietnamese farmers’ intention to accept organic farming based on the theory of planned behavior (TPB). After in-depth interviews with five agricultural researchers and five farmers, the authors have identified a formal research model and built a complete survey. Data were collected from 318 farmers in Hanoi, Vietnam, by surveying directly at their homes or farms. Statistical methods, such as Cronbach’s alpha, exploratory factor analysis (EFA) and linear regression analysis, were used to analyze the data with the help of SPSS 22.0 and AMOS 24.0. The results show that attitudes, subjective norms, and perceived behavioral control have a positive influence on farmers’ intention to accept organic farming in Vietnam. Based on the degree of impact of these factors, the authors give a few suggestions to state management agencies to promote the intention to accept organic farming in Vietnam: (i) increasing awareness of the difference between organic farming and conventional farming, the role of organic farming in health and the environment; (ii) increasing the activities of guiding the organic farming practices and facilitating the farmers to access these guides through many channels; and (iii) holding sessions to share practices in organic farming practices.

JEL Classification Code: C91, E23, G28

## 1. Introduction

Organic farming, as an approach to agriculture that emphasizes the environment as well as other benefits and disrupts conventional farming patterns, has recently grown significantly (Alexopoulos et al., 2010). Organic farming is an important tool for achieving green yields and reducing the negative effects of conventional farming by eliminating synthetic chemical inputs during production, reducing air pollution (Asadollahpour et al., 2014).

Organic farming and the demand for organic food are constantly growing worldwide (Lohr, 2001; Padel & Foster, 2005; Siderer et al., 2005). Vietnam is one of the countries facing challenges in  terms  of  environmental  protection as well as sustainable development (Nguyen et al., 2017; Nguyen et al., 2020). Traditional organic farming has been practiced by farmers for thousands of years and this form of farming is also very important in the 1950s. In 2016, the area of organic cultivation has increased by 3.6 times compared to 2010 and reached about 77,000 hectares. However, this is still too small compared to the world’s 50.9 million hectares of organic farming and 11.53 million hectares of agricultural land in Vietnam (Khanh, 2020). In order to persuade Vietnamese farmers to switch from a conventional farming approach that relies on intensive chemical inputs to a purely organic approach, one needs to know and understand the factors of the farmers’ decision-making process (Morgan & Murdoch, 2000).

Previous research in different countries has analyzed the factors that influence farmers’ intention to accept organic farming in different sectors: avocado in Mexico (Hattam, 2006); organic farming and conventional farming in Western Greece (Alexopoulos et al., 2010); rice in Northeastern Thailand (Chouichom & Yamao, 2010); organic rice in Northern Thailand (Jierwiriyapant et al., 2012); organic farming in Nepal (Aoki, 2014); rice in Mazandaran, Northern Iran (Asadollahpour et al., 2014); organic farming in the Netherlands (Azam & Banumathi, 2015); organic farming in Peshawar-Pakistan (Ullah et al., 2015); organic farming in Giang To, China (Xi et al., 2015); rice in Sragen Regency, Indonesia (Sharifuddin et al., 2016); organic fresh fruit and vegetables in Syria (Issa & Hamm, 2017); organic farming in India (Azam & Shaheen, 2018).

The theory used when studying the intention to accept organic farming is the theory of planned behavior (TPB) (Laepple, 2008; Hattam, 2006; Issa & Hamm, 2017). The method used when studying the intention to accept organic farming is a combination of both qualitative and quantitative methods. Asadollahpour et al. (2014) chose to interview ten rice producers who received health product certification from the interviewed standards organization, then conducted a survey of 250 rice producers. Chouichom and Yamao (2010) interviewed 100 organic rice farmers and 100 non- organic rice farmers, then conducted Chi-Square and t-test to quantify correlations in the study. Jierwiriyapant et al. (2012) conducted in-depth surveys and interviews with organic rice farmers. Azam and Banumathi (2015) collected data through a structured questionnaire comprising a total of 160 organic and conventional farmers, then applied a logistic regression model to analyze the data. Ullah et al. (2015) interviewed 100 farmers in 4 cultivated areas, and then also applied a logistic regression model to analyze the data. Xie et al. (2015) conducted a survey on organic farming readiness of small farmers and applied a binary logistic regression model in data processing. Sharifuddin et al. (2016) conducted a survey of 600 rice farmers and in- depth interviewed two groups namely semi-organic farmers and conventional farmers. Issa and Hamm (2017) surveyed 266 conventional farmers in different districts to learn about their intentions and attitudes towards organic farming.

This study is conducted to examine the factors influencing farmers’ intention to accept organic farming in Vietnam by using TPB. The research contributes both theoretically and practically. Firstly, the study applies the theory of planned behavior to confirm the appropriateness of the application of this theory when studying the factors affecting the farmers’ intention to accept organic farming in Vietnam. Secondly, the study applies both qualitative and quantitative methods to determine the influence of each factor on the intention of farmers to accept organic farming in Vietnam. Thirdly, based on the research results, the authors give a few suggestions for state management agencies to promote the intention of organic farming in Vietnam.

## 2. Theoretical Basis and Hypotheses

According to Kilcher (2006), organic farming is agriculture  using  purely  organic  inputs,  which  is  also synonymous with sustainable agriculture. Traditionally, farmers cultivating in humid tropical regions using organic fertilizers often use fertile soils in agriculture. This creates agriculture that is both environmentally and economically sustainable. Katić et al. (2010) stated that organic farming as a special form of agricultural production, is the foundation for sustainable agricultural production when it best meets the requirements of the principles of protection and s environmental sustainability. According to Scialabba and Hattam (2002), organic farming is a form of agriculture that largely avoids or eliminates the use of synthetic chemical fertilizers, pesticides, crop growth regulators and additives in animal feed to reduce pollution, ensure human health and create clean agricultural products.

A psychosocial theory consistent with the analysis of farmers’ decisions and behavior is the theory of planned behavior (TPB), developed by Ajzen (1991), based on the theory of reasoned action (TRA). Because TRA is limited in predicting behavior in situations where they cannot fully control their behavior when attitudes toward the behavior and subjective norms are insufficient to explain for their behavior (Hansen et al., 2004). Therefore, TPB is built by Ajzen (1991) by adding perceived behavioral control to the TRA model. Meanwhile, farmers’ intentions are influenced by attitudes, subjective norms and perceived behavioral control. TPB has been widely accepted and used in studies for the purpose of predicting specific use intent and behavior by individuals.

TPB has attracted increasing attention from researchers in the agricultural sector to learn about farmers’ intentions/ behavior. TPB has been used to learn improved natural remedies (Borges et al., 2016); intention to engage in on- farm food safety practices (Rezaei et al., 2018), apply personal protective equipment (Rezaei et al., 2019); safe use of chemical fertilizers (Savari & Gharechaee, 2020); agricultural non-point source (Wang et al., 2019). For the conversion to organic farming, some studies also apply TPB model as the main theoretical framework like Hattam (2006); Issa and Hamm (2017).

Intent represents the individual’s motivation to make a conscious decision or plan to attempt to practice a particular behavior (Conner & Armitage, 1998). The TPB argues that an individual’s intent can be predicted with great accuracy by attitudes towards a certain behavior, perceived behavioral control and subjective norms (Ajzen, 1991).

Attitude expresses how well an individual judges a behavior to be favorable or unfavorable (Ajzen, 1991). Individuals form their attitudes based on their perception of what might be true about a particular subject and this perception may or may not be based on information, knowledge, or even an emotional response to the subject, sometimes supported by beliefs and values (Willock et al., 1999). Attitude can be seen as a fundamental determinant of an individual’s intentions (Yadav & Pathak, 2017; Li et al., 2018; Rezaei et al., 2018). Farmers will intend to adopt organic farming only if they believe that the practice is beneficial and yields positive results for them. A close relationship between farmer attitudes and intentions to conduct has been reported in the literature (Borges et al., 2016; Issa & Hamm, 2017; Rezaei et al. al, 2018; Rezaei et al, 2019; Savari & Gharechaee, 2020; Wang et al., 2019). Based on these studies, we posit the first hypothesis as the following:

H1: Attitude has a positive effect on farmers’ intention to accept organic farming in Vietnam.

Subjective norms were originally described as “a person’s perception of social pressure to perform or not perform a behavior under consideration” (Ajzen, 1988). Subjective norms show  the influence of  society  around individuals (family, friends, co-workers, neighbors, eminent individuals, status people) on the decision-making mechanism (Lopez- Mosquera, 2016). Subjective norms are the second most important variable affecting behavioral intent and this norm indicates that individuals intend to act on the basis of the consent or disapproval  of  certain  individuals  important to that person (Chen & Tung, 2014). Individuals often act on their perceptions of what others feel and their potential acceptance of their behavior is influenced by those with whom they have a close relationship (De Bruijn, 2010; Kaiser & Scheuthle, 2003). Subjective norms have been confirmed to have a relationship with farmers’ intent to perform behavior in a number of studies (Borges et al., 2016; Hattam, 2006; Issa & Hamm, 2017; Rezaei et al, 2018; Rezaei et al, 2019; Savari & Gharechaee, 2020; Wang et al., 2019). In view of these findings from earlier research, we offer the second hypothesis:

H2: Subject norms have a positive effect on farmers’ intention to accept organic farming in Vietnam.

Perceived behavioral control refers to how easy or difficult an individual is to perform behavior (Ajzen, 1991). Individuals’ strong intention to take a particular action is influenced by the degree of self-control (Gao et al., 2017). An individual’s perception of a person’s consent to an act is important enough to motivate the intent to perform the act (Shin & Hancer, 2016). High awareness of related subjective norms can increase the probability of performing a particular behavior (Gao et al., 2017). If farmers feel that they are under social pressure when producing organic farming, they are more likely to use those practices. Perceived behavioral control has been shown to have a relationship with farmer intentions in several previous studies (Borges et al., 2016; Hattam, 2006; Issa & Hamm, 2017; Rezaei et al, 2018; Rezaei et al, 2019; Savari & Gharechaee, 2020; Wang et al., 2019). As such, we propose the following hypothesis:

H3: Perceived behavioral control has a positive effect on farmers’ intention to accept organic farming in Vietnam.

## 3. Methods

### 3.1.   Sample and Procedure

The research applied both qualitative and quantitative methods. Firstly, the authors conducted in-depth interviews with five agricultural researchers and five farmers who randomly selected for the study in Hanoi, Vietnam. Interviews were held at the interviewee’s place of residence or workplace for about an hour. Contents of the interview about the factors affecting the farmers’ intention to accept organic agricultural production. Interview content was recorded, stored and encoded in the computer, then the tape was removed, synthesized and analyzed to compare the theoretical model and the actual responses of the people who was interviewed. From the results of in-depth interviews, the authors determined the official research model and built a complete survey. Secondly, the survey included two parts: the first part explores the characteristics including: gender, age, educational qualification, farming experience and farming annual income (Table 1); the second part explores the respondents’ consent to statements related to factors affecting the intention to produce organic farming. On the basis of focus group discussion and existing literature, in the second part, the survey included 20 items on a five-point Likert scale (Likert, 1932; Allen & Seaman, 2007) ranging from completely disagree to completely agree. The authors surveyed with a sample size of 400 questionnaires with the respondents who were farmers in Hanoi, Vietnam. The number of votes collected is 330 questionnaires (reaching 82.50%), after cleaning the data, the number of questionnaires used for analysis is 318 questionnaires (reaching 79.50%), the number of questionnaires are eligible for the entry objective of quantitative research.

The 318 observations in quantitative research showed that the research samples were male farmers (accounting for 55.03%) and female farmers (accounting for 44.97%); most of them are in the age group from 31 to 40 (accounting for 38.99%), followed by the age group from 20 to 30 (accounting for 35.85%); the surveyed farmers’ educational qualification mainly graduated from high school (accounting for 33.02%); the number of farmers with 11 to 15 years’ experience in farming accounts for the largest proportion of the total number of observations, namely 29.25%, followed by 6 to 10 years, accounting for more than a quarter of the total, 26.73%. Besides, farming annual income ranges US$15,000 to US$25,000, accounting for the largest rate of 30.19%.

### 3.2.   Measures

Intention (IN). For assessing intention, we adapted from Rezaei et al. (2019) with three-item scale. Each item of the scale was rated from 1 (strongly disagree) to 5 (strongly agree), and a sample item from the scale was “I intend to practice organic farming in my farm over the next year.” The Cronbach’s α value was 0.782.

Attitude (AT). We used Yanakittkul and Aungvaravong’s (2017) five-item measure. Each item of the scale was rated from 1 (strongly disagree) to 5 (strongly agree), and a sample item from the scale was “Quality of product from organic farming is better than conventional farming.” The results of analyzing the reliability Cronbach’s Alpha shows that item- total correlation coefficient of AT5 is less than 0.4, so AT5 removed from the AT scale. The Cronbach’s α value was 0.804.

Subjective norms (SN). The six-item scale by Yanakittkul and Aungvaravong (2017) was used to measure subjective norms (sample item: Other farmer neighbors will change to organic farming). Each item of the scale was rated from 1 (strongly disagree) to 5 (strongly agree). The Cronbach’s α for this study was 0.870.

Perceived behavioral control (PBC). We used the six- item measure by Yanakittkul and Aungvaravong (2017) to assess perceived behavioral control. Each item of the scale was rated from 1 (strongly disagree) to 5 (strongly agree), and a sample item from the scale was “Farmers know the difference between organic farming and conventional farming.” The results of analyzing the reliability Cronbach’s Alpha shows that item-total correlation coefficient of PBC6 is less than 0.4, so PBC6 removed from the PBC scale. The Cronbach’s α value was 0.861.

## 4. Results

### 4.1.   Exploratory Factor Analysis (EFA)

In order to group the  initial  observed  variables  into the significant ones, and at the same time  discover  the latent structure between the research concepts, the authors conducted an exploratory factor analysis (EFA) with four factors: intention, attitude, subjective norms, and perceived behavioral control. The KMO coefficient calculated from the survey sample is 0.835, greater than 0.5, which shows that the sample size is suitable for factor analysis. To determine the main factors, the authors use the factor extraction method based on eigenvalue values. The factors that have an eigenvalue value greater than 1 can be kept in the analytical model. Using Kaiser criterion, the eigenvalue = 1.529 greater than 1 is consistent with all 4 factors, explaining 64.280 percent of variance.

### 4.2.   Means, Standard Deviations and Zero-Order Correlations

Table 3 presents the means, standard deviations, and zero- order correlations. As shown in the table 3, attitude, subject norms, perceived behavioral control were significantly related to intention of the farmers (r = 0.294, 0.185 and 0.290 respectively, p < 0.01). Ngoài ra, age and educational qualification có mối quan hệ với intention of the farmers (r =-0.069, 0.035 respectively, p < 0.05).

### 4.3. Linear Regression Analysis

The R Square value in the model summary depicts the degree to which the independent variables explain intention of the farmers. Adjusted R Square is shown in detail in Table 4 is 0.640 meaning that the independent variables influence 64.0% of the variation of the dependent variable, the remaining 36% is due to the variables outside the model and random errors.

Attitude, subject norms, perceived behavioral control have a positive relationship with intention of the farmers (β = 0.277, 0.167 and 0.232 respectively, p < 0.05). Attitude with a beta of 0.277 has the strongest positive impact on intention of the farmers. Age and educational qualification has also been shown to have relationships with the intention of the farmers (β = -0.034 and 0.027 respectively, p < 0.05). Thus, hypotheses H1, H2 and H3 are accepted.

## 5. Discussion and Implications

### 5.1.   Discussion

Research results show that attitude, subjective norms, and perceived behavioral control are factors that affect farmers’ intention to accept organic farming in Vietnam. All theories given in the TPB-based research model are accepted.

Firstly, attitude is positively related with farmers’ intention to accept  organic  farming  in  Hanoi,  Vietnam (β = 0.277, p <0.001). Farmer’s attitude is related to the notion that the quality of produce from organic farming is better than conventional farming, organic farming is good for farmers and the health of family members, organic farming products are good for the health of the consumer and for the environment. This result is consistent with some previous studies on farmers (Borges et al., 2016; Issa & Hamm, 2017; Rezaei et al, 2018; Rezaei et al, 2019; Savari & Gharechaee, 2020; Wang et al., 2019).

Secondly, subjective norms have a proportional relationship with farmers’ intention to accept organic farming in Hanoi, Vietnam (β = 0.167, p <0.05). Farmers are interested in choosing to convert to organic farming based on the intentions and decisions of their neighbors, farmer groups and family members. In addition, information introduced from the media such as television, radio or newspaper is also a channel to help farmers intend to practice organic farming. These results are consistent with studies of Afroz et al. (2019); Borges et al. (2016); Hattam (2006); Issa and Hamm (2017); Rezaei et al (2018); Rezaei et al. (2019); Savari and Gharechaee (2020); and Wang et al. (2019).

Thirdly, perceived behavioral control is positively related with farmers’ intention to accept organic farming in Hanoi, Vietnam (β = 0.232, p <0.001). Farmers are motivated to adopt organic farming when they know the difference between organic farming and conventional farming, their knowledge of organic farming techniques and processes. Once aware of the differences and knowledge of organic farming, farmers will have the confidence to practice organic farming, receive organic certification, control yield with organic farming contributing to the intention to adopt organic farming. This result is consistent with research by Borges et al. (2016); Hattam (2006); Issa and Hamm (2017); Rezaei et al (2018); Rezaei et al. (2019); Savari and Gharechaee (2020); and Wang et al. (2019).

Fourthly, age influences farmers’ intention to accept organic farming in Hanoi, Vietnam. The results show that, in Vietnam, the younger the age, the higher the intention to accept farming. However, Sarker and Itohara (2008) and Karki et al. (2011) also found that older farmers were able to cope with organic farming than younger farmers.

Fifthly, educational qualification affects farmers’ intention to accept organic farming in Hanoi, Vietnam. Issa and Hamm (2017) also argue that the intention to adopt production is particularly strong with those with better education in Syria. Meanwhile, some studies from other developing countries show that farmers who intend to apply tend to have lower levels of education such as Hattam (2006) in Mexico; Sarker et al. (2009) in Bangladesh; Pornpratansombat et al. (2011) in Thailand and Karki et al. (2011) in Nepal.

### 5.2.   Implications

Based on the impact of the factors in the research model of factors affecting the farmers’ intention to accept organic farming in Hanoi, Vietnam, the authors give a few suggestions to the state management agencies to promote the intention of adopting organic farming through influencing the farmers’ attitude, subject norms, perceived behavioral control.

Firstly, increasing awareness of the difference between organic farming and conventional farming, the role of organic farming in health and the environment for farmers through the media and materials distributed directly to farmers in Hanoi, Vietnam.

Secondly, increasing  the  activities of guiding the organic farming practices for farmers, and at the same time facilitating the farmers to access these guides through many channels such as Internet, short courses, field trips, and direct training/mentoring from experts, farmers who have successfully practiced organic farming.

Thirdly, holding sessions to share practices in organic farming practices from start of implementation to successful consumption between experts, farmers who have implemented organic farming and farmers who are working on conventional farming.

### 5.3.   Limitations

The study still contains some limitations that need to be improved in the future. Firstly, the study only focuses on farmers’ intention to accept organic farming in the Hanoi, the findings are therefore not generalizable to all farmers in the country. Secondly, the study just stops at understanding the intention to accept organic farming, in the future, it is necessary to continue to explore the relationship between intentions and practices of organic farming. Thirdly, using the model based on the theory of TPB with three factors: attitude, subject norms and perceived behavioral control do not cover enough factors and only explain 64.0% of the farmer’s intention towards organic farming. Next research can use a combination of theories and other factors to integrate the understanding of farmers’ intention to accept organic farming.

## Reference

1. Afroz, R., Muhibbullah, M., & Morshed, M. N. (2019). Factors Affecting the Intention of the Rice Farmers to Adopt the Integrated Cash Waqf Environmental Protection Model: An Empirical Study in Kedah Malaysia. Journal of Asian Finance, Economics and Business, 6(4), 189-199. https://doi. org/10.13106/jafeb.2019.vol6.no4.189
2. Ajzen, I. (1988). Attitudes, personality, and behavior. Homewood, IL: Dorsey Press.
3. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
4. Alexopoulos, G., Koutsouris, A., & Tzouramani, I. (2010). Should I stay or should I go? Factors affecting farmers’ decision to convert to organic farming as well as to abandon it. In: 9th European IFSA Symposium (pp. 1083-1093). Vienna, Austria.
5. Allen, I. E., & Seaman, C. A. (2007). Likert scales and data analyses. Quality Progress, 40(7), 64-65.
6. Aoki, M. (2014). Motivations for organic farming in tourist regions: a case study in Nepal. Environment, Development and Sustainability, 16(1), 181-193. https://doi.org/10.1007/s10668-013-9469-6
7. Asadollahpour, A., Najafabadi, M. O., & Hosseini, S. J. (2016). Modeling behavior pattern of Iranian organic paddy farmers. Paddy and Water Environment, 14(1), 221-229. https://doi.org/10.1007/s10333-015-0492-0
8. Asadollahpour, A., Omidinajafabadi, M., & Jamalhosseini, S. (2014). Factors affecting the conversion to organic farming in Iran: A case study of mazandaran rice producers. Science International, 26(4), 1844-1860.
9. Azam, M. S., & Banumathi, M. (2015). The role of demographic factors in adopting organic farming: A logistic model approach. International Journal, 3(8), 713-720.
10. Azam, M. S., & Shaheen, M. (2019). Decisional factors driving farmers to adopt organic farming in India: a cross-sectional study. International Journal of Social Economics, 46(4), 562-580. https://doi.org/10.1108/IJSE-05-2018-0282
11. Borges, J. A. R., Tauer, L. W., & Lansink, A. G. O. (2016). Using the theory of planned behavior to identify key beliefs underlying Brazilian cattle farmers’ intention to use improved natural grassland: A MIMIC modelling approach. Land Use Policy, 55, 193-203. https://doi.org/10.1016/j.landusepol.2016.04.004
12. Chen, M. F., & Tung, P. J. (2014). Developing an extended theory of planned behavior model to predict consumers’ intention to visit green hotels. International Journal of Hospitality Management, 36, 221-230. https://doi.org/10.1016/j.ijhm.2013.09.006
13. Chouichom, S., & Yamao, M. (2010). Comparing opinions and attitudes of organic and non-organic farmers towards organic rice farming system in north-eastern Thailand. Journal of Organic Systems, 5(1), 25-35.
14. Conner, M., & Armitage, C. J. (1998). Extending the theory of planned behavior: A review and avenues for further research. Journal of Applied Social Psychology, 28(15), 1429- 1464. https://doi.org/10.1111/j.1559-1816.1998.tb01685.x
15. De Bruijn, G. J. (2010). Understanding college students’ fruit consumption. Integrating habit strength in the theory of planned behaviour. Appetite, 54(1), 16-22. https://doi.org/10.1016/j. appet.2009.08.007
16. Gao, L., Wang, S., Li, J., & Li, H. (2017). Application of the extended theory of planned behavior to understand individual’s energy saving behavior in workplaces. Resources, Conservation and Recycling, 127, 107-113. https://doi.org/10.1016/j. resconrec.2017.08.030
17. Hansen, T., Jensen, J. M., & Solgaard, H. S. (2004). Predicting online grocery buying intention: a comparison of the theory of reasoned action and the theory of planned behavior. International Journal of Information Management, 24(6), 539-550. https:// doi.org/10.1016/j.ijinfomgt.2004.08.004
18. Hattam, C. (2006). Adopting certified organic production: evidence from small-scale avocado producers in MichoacaÌ n, Mexico. Doctoral dissertation, University of Reading. https:// ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.437136
19. Hattam, C. (2006). Adopting organic agriculture: An investigation using the Theory of Planned Behaviour (No. 1004-2016- 78538). https://doi.org/10.22004/ag.econ.25269
20. Issa, I., & Hamm, U. (2017). Adoption of organic farming as an opportunity for Syrian farmers of fresh fruit and vegetables: An application of the theory of planned behaviour and structural equation modelling. Sustainability, 9(11), 2024. https://doi. org/10.3390/su9112024
21. Jierwiriyapant, P., Liangphansakul, O. A., Chulaphun, W., & Pichaya-satrapongs, T. (2012). Factors affecting organic rice production adoption of farmers in northern Thailand. Chiang Mai University Journal of Natural Sciences, 11(1), 327-333.
22. Kaiser, F. G., & Scheuthle, H. (2003). Two challenges to a moral extension of the theory of planned behavior: Moral norms and just world beliefs in conservationism. Personality and Individual Differences, 35(5), 1033-1048. https://doi. org/10.1016/S0191-8869(02)00316-1
23. Karki, L., Schleenbecker, R., & Hamm, U. (2011). Factors influencing a conversion to organic farming in Nepalese tea farms. Journal of Agriculture and Rural Development in the Tropics and Subtropics, 112(2), 113-123. http://nbn-resolving. de/urn:nbn:de:hebis:34-2012011740355
24. Katic, B., Savic, M., & Popovic, V. (2010). Organic livestock production - an untapped chance for Serbia. Ekonomika Poljoprivrede, 57(2), 245-256.
25. Khanh, T. Q. (2020). Organic Agriculture in Vietnam - Capital needs and mobilization solutions. Journal of Financial and Monetary Market Review, 1-2. http://thitruongtaichinhtiente. vn/nong-nghiep-huu-co-o-viet-nam-nhu-cau-von-va-giai- phap-huy-dong-28411.html
26. Kilcher, L. (2006). 11 The Contribution of Organic Farming to Sustainable Development. Journal of Agriculture and Rural Development in the Tropics and Subtropics, 89.
27. Laepple, D. (2008, December). Farmer attitudes towards converting to organic farming. In: Teagasc Organic Production Research Conference Proceedings (pp. 114-121). Teagasc, Ireland.
28. Li, D., Ma, G., Li, C., He, W., Mei, J., & Ge, S. S. (2018). Distributed attitude coordinated control of multiple spacecraft with attitude constraints. IEEE Transactions on Aerospace and Electronic Systems, 54(5), 2233-2245.
29. Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology, 22(140), 55.
30. Lohr, L. (2001). Factors affecting international demand and trade in organic food products. Faculty Series 16674, University of Georgia, Department of Agricultural and Applied Economics. DOI: 10.22004/ag.econ.16674
31. López-Mosquera, N. (2016). Gender differences, theory of planned behavior and willingness to pay. Journal of Environmental Psychology, 45, 165-175.
32. Morgan, K., & Murdoch, J. (2000). Organic vs. conventional agriculture: knowledge, power and innovation in the food chain. Geoforum, 31(2), 159-173.
33. Nguyen, P. N. D., Nguyen,V.T., &Vo, N. N.T. (2019). Key Determinants of Repurchase Intention towards Organic Cosmetics. Journal of Asian Finance, Economics and Business, 6(3), 205-214. https:// doi.org/10.13106/jafeb.2019.vol6.no3.205
34. Nguyen, T. K. C., Nguyen, D. M., Trinh, V. T., Tran, T. P. D., & Cao, T. P. (2020). Factors Affecting Intention to Purchase Green Products in Vietnam. Journal of Asian Finance, Economics and Business, 7(4), 205-211. https://doi.org/10.13106/jafeb.2020. vol7.no4.205
35. Nguyen, V. D., Nguyen, N. D., Nguyen, T. H. A., & Vu, H. P. (2017). Impact of fdi and co2 emission on economic growth: Evidence of some Asian countries. External Economics, 91, 59-66.
36. Padel, S., & Foster, C. (2005). Exploring the gap between attitudes and behaviour: understanding why consumers buy or do not buy organic food. British Food Journal, 107(8), 606-625.
37. Pornpratansombat, P., Bauer, B., & Boland, H. (2011). The adoption of organic rice farming in Northeastern Thailand. Journal of Organic Systems, 6(3), 4-12.
38. Rezaei, R., Mianaji, S., & Ganjloo, A. (2018). Factors affecting farmers’ intention to engage in on-farm food safety practices in Iran: Extending the theory of planned behavior. Journal of Rural Studies, 60, 152-166. https://doi.org/10.1016/j. jrurstud.2018.04.005
39. Rezaei, R., Seidi, M., & Karbasioun, M. (2019). Pesticide exposure reduction: extending the theory of planned behavior to understand Iranian farmers’ intention to apply personal protective equipment. Safety Science, 120, 527-537. https://doi. org/10.1016/j.ssci.2019.07.044
40. Sarker, M., & Itohara, Y. (2008). Factors influencing the extent of practice of organic farming technologies: a case study of Tangail district in Bangladesh. American Journal of Agricultural and Biological Sciences, 3(3), 584-590. http://www.scipub.org/ fulltext/AJAB/AJAB33584-590.pdf
41. Sarker, M. A., Itohara, Y., & Hoque, M. (2009). Determinants of adoption decisions: The case of organic farming (OF) in Bangladesh. Extension Farming Systems Journal, 5(2), 39. https://search.informit.com.au/documentSummary;dn= 733506527698660;res=IELHSS
42. Savari, M., & Gharechaee, H. (2020). Utilizing the theory of planned behavior to predict Iranian farmers’ intention for safe use of chemical fertilizers. Journal of Cleaner Production, 121512. https://doi.org/10.1016/j.jclepro.2020.121512
43. Scialabba, N., & Hattam, C. (Eds.). (2002). Organic agriculture, environment and food security. Food and Agriculture Organization of the United Nations (FAO). http://www.fao.org/ family-farming/detail/en/c/285489/
44. Senger, I., Borges, J. A. R., & Machado, J. A. D. (2017). Using the theory of planned behavior to understand the intention of small farmers in diversifying their agricultural production. Journal of Rural Studies, 49, 32-40. https://doi.org/10.1016/j. jrurstud.2016.10.006
45. Sharifuddin, J., Mohammed, Z. A., & Terano, R. (2016). Rice farmers’ perception and attitude toward organic farming adoption. Jurnal Agro Ekonomi, 34(1), 35-46. http://dx.doi. org/10.21082/jae.v34n1.2016.35-46
46. Shin, Y. H., & Hancer, M. (2016). The role of attitude, subjective norm, perceived behavioral control, and moral norm in the intention to purchase local food products. Journal of foodservice business research, 19(4), 338-351. https://doi.org/10.1080/15378020.2016.1181506
47. Siderer, Y., Maquet, A., & Anklam, E. (2005). Need for research to support consumer confidence in the growing organic foodmarket. Trends in Food Science and Technology, 16(8), 332- 343. https://doi.org/10.1016/j.tifs.2005.02.001
48. Shi, H., Fan, J., & Zhao, D. (2017). Predicting household PM2. 5-reduction behavior in Chinese urban areas: An integrative model of Theory of Planned Behavior and Norm Activation Theory. Journal of Cleaner Production, 145, 64-73. https://doi. org/10.1016/j.jclepro.2016.12.169
49. Ullah, A., Shah, S. N. M., Ali, A., Naz, R., Mahar, A., & Kalhoro, S. A. (2015). Factors affecting the adoption of organic farming in Peshawar-Pakistan. Agricultural Sciences, 6(6), 587. https:// doi.org/10.1016/j.jclepro.2020.121512
50. Wang, Y., Liang, J., Yang, J., Ma, X., Li, X., Wu, J., ... & Feng, Y. (2019). Analysis of the environmental behavior of farmers for non-point source pollution control and management: An integration of the theory of planned behavior and the protection motivation theory. Journal of Environmental Management, 237, 15-23. https://doi.org/10.4236/as.2015.66057
51. Willock, J., Deary, I. J., Edwards‐Jones, G., Gibson, G. J., McGregor, M. J., Sutherland, A., ... & Grieve, R. (1999). The role of attitudes and objectives in farmer decision-making: business and environmentally-oriented behaviour in Scotland. Journal of Agricultural Economics, 50(2), 286-303. https://doi. org/10.1111/j.1477-9552.1999.tb00814.x
52. Xie, B., Wang, L., Yang, H., Wang, Y., & Zhang, M. (2015). Consumer perceptions and attitudes of organic food products in Eastern China. British Food Journal, 117(3), 1105-1121. https://doi.org/10.1108/BFJ-09-2013-0255
53. Yadav, R., & Pathak, G. S. (2017). Determinants of consumers’ green purchase behavior in a developing nation: Applying and extending the theory of planned behavior. Ecological Economics, 134, 114-122. https://doi.org/10.1016/j.ecolecon.2016.12.019
54. Yanakittkul, P., & Aungvaravong, C. (2017). Proposed conceptual framework for studying the organic farmer behaviors. Kasetsart Journal of Social Sciences. https://doi.org/10.1016/j. kjss.2017.09.001