Các yếu tố tác động tới hành vi gia nhập hệ thống sản xuất rau an toàn tại các hợp tác xã của nông dân trên địa bàn Thành phố Hà Nội

Nội dung text: Các yếu tố tác động tới hành vi gia nhập hệ thống sản xuất rau an toàn tại các hợp tác xã của nông dân trên địa bàn Thành phố Hà Nội

1. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 FACTORS AFFECTING THE BEHAVIOR OF JOINING THE SAFE VEGETABLE PRODUCTION SYSTEM IN FARMERS’ COOPERATIVES IN HANOI CÁC YẾU TỐ TÁC ĐỘNG TỚI HÀNH VI GIA NHẬP HỆ THỐNG SẢN XUẤT RAU AN TOÀN TẠI CÁC HỢP TÁC XÃ CỦA NÔNG DÂN TRÊN ĐỊA BÀN THÀNH PHỐ HÀ NỘI PhD. Nguyen Bao Ngoc - MBA. Nguyen Hoang Nam Thuongmai University namqtcl@tmu.edu.vn Abstract The study aims to assess the impact of some factors on the farmers’ behavior to join safe vegetable cooperatives in Hanoi. Through primary data collected from 177 farmer households participating in safe vegetable production, by qualitative and quantitative research methods, the research results have shown expected benefits, images enterprises, environmental concerns, knowledge barriers and subjective norms have an impact on the behavior of farmers joining be - haviour safe vegetable production in Hanoi. Keywords: Safe vegetables; Farmer’s Behaviour; Development of safe vegetable produc - tion systems. Tóm tắt Nghiên cứu có mục đích đánh giá tác động của một số yếu tố tới hành vi gia nhập hợp tác xã sản xuất rau an toàn của người nông dân trên địa bàn Hà Nội. Thông qua bộ dữ liệu sơ cấp được thu thập từ 177 chủ hộ nông dân đang tham gia sản xuất rau an toàn, bằng phương pháp nghiên cứu định tính và định lượng, kết quả nghiên cứu đã chỉ ra lợi ích kì vọng, hình ảnh doanh nghiệp, kiến thức về môi trường, rào cản kiến thức và chuẩn chủ quan có tác động tới hành vi gia nhập sản xuất rau an toàn của người nông dân trên địa bàn Hà Nội. Từ khóa: Rau an toàn; Hành vi gia nhập; Phát triển hệ thống sản xuất rau an toàn. 1. Introduction Implementing Decision No. 2261 / QD-TTG dated December 15, 2014, on the Program to support the development of cooperatives in the period 2015 - 2020 and developing the Program to support the development of collective economy and cooperatives. in the 2021 - 2025 period by December 2018, 1,350 cooperatives (cooperatives) were established, of which 817 accounted for over 60% of the total number of members in the agriculture-forestry-fishery sector, on average 126 members/cooperatives; in the handicraft industry, there were 265 cooperatives, accounting for 20%; trade, service and other fields 268 cooperatives; by 2020, there will be 130,000 cooperative groups mainly operating in the fields of agriculture, credit, and services. The maintenance and development of cooperative groups are becoming a necessary issue to create high efficiency, especially in the application of high technology in agricultural production 262
2. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 according to Decision No. 34/2019 / QD-TTG is an important project of the Government. Safe vegetables Hanoi has 1000 hectares, the production value reaches 1 billion / VND / ha/year and formed several chains from production to consumption, with stamps, identification labels, traceability, being consumed through 18 businesses, 17 cooperatives supplying retail stores, distribution points, collective kitchens and supermarkets with the production of nearly 20,000 tons/year (accounting for 5% of safe vegetable output, 3% production of vegetables, 2% of consumption demand). Safe vegetables without stamps, labels identifying traceability for consumption in wholesale markets, residential markets, residential areas with an output of over 370,000 tons/year (accounting for 92.5% of the production of safe vegetables, 61,67% of vegetable production, 37% of consumption demand). The scale of the cooperative has been somewhat recovered and the cooperative itself has the desire to achieve high efficiency in safe vegetable production in the market of safe vegetables in big cities such as Hanoi, Ho Chi Minh City. Da Nang has not met the quantity and quality of safe vegetables and the Government’s expectations for this product. The topic of safe agricultural products is a topic of national stature and safe vegetables belonging to a group of products are among the topics of interest to both producers, distributors, consumers, and consumers. policy managers. Taking advantage of the traditional form of production with a long history of being a cooperative is very practical to ensure income sources for farmers and make use of long-standing communication agricultural production. So, the topic of research on the behavior of joining the safe vegetable production system in the cooperatives in Hanoi is even more practical. 2. Theoretical rramework and hypothese 2.1. Theory Reasoned Action and Theory of Planned Behavior Theory Reasoned Action was developed by the Fishbein and Ajzen (1975) and tested in many studies by groups of authors such as Bagozzi (1992); Cordano et al (2011) In this theory, to affect to the behavior, the process is built on the following factors: Behavioral Intention; Subjective Norms and Attitude Toward the Behavior. Figure 1: Theory Reasoned Action Model (TRA) Source: Fishbein and Ajzen, 1975 263
3. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 The study of Ajzen (1991) indicated that the TRA model of Fishbein and Ajzen (1975) was not complete, with the view that the TRA model was incomplete due to the lack of perceived behavior control. According to Ajzen’s point of view, sometimes behavior is not dependent on non-motivational factors such as resources, abilities So the perceived control behavior is considered as a necessary role. Behavioral intention factors indicate how difficult it is to proceed with behavior and the appropriate level from intentions to behaviors. The planned behavioral theory adds Perceived Behavioral Control, and this factor not only affects behavior indirectly through behavioral intent (Intention) but also live-action. Figure 2: Theory of Planned Behavior (TBP) Source: Ajzen (1991) 2.2. Some decisive factors to the behavior of joining safe vegetable production 2.2.1 Expected Benefit The benefit is considered an important criterion affecting human behavior. Benefits are assessed under many criteria such as monetary benefits, non-monetary benefits such as reputation, market share For research in the agricultural sector, Mamudu (2012) through 300 farmers in Bawku West District (Ghana) pointed out the expected benefit has a strong impact on the decision to adopt technologies in agricultural cultivation. Mohammed Al-Ali et al. (2015) pointed out that money benefits have an impact on customer behavior. Issues are considered to measure commercial interest related to profitability, business-oriented fit, resource suitability, and benefits committed by stakeholders. From the above analysis, the authors propose the research hypothesis. H1: The expected benefit has positive impact to joining behaviour of farmer. 2.2.2. Environmental Concern According to modern marketing opinion, social ethics is an issue that is concerned not only from the corporate perspective but also from the customer perspective. According to Dunlap and Jone (2012), environmental awareness is related to the level of awareness of environmental problems and efforts to assist in solving those problems. According to Albayrak (2013), customers 264
4. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 are willing to pay for environmentally friendly products and knowledge of the environment has a positive impact on this problem. According to N.H. Viet et al (2019), knowledge about the en - vironment has a positive influence on the behavior of re-buying organic meat products in Vietnam. From the above analysis, the authors propose the research hypothesis. H2: Knowledge of the environment has a positive impact on the behavior of participating in safe vegetable production 2.2.3. Subjective Norms The Subjective norm in studies of planned behavioral theory (TPB) or rational action theory (TRA), the subjective norm is the main factor and influences intent (Intention). According to Fishbein and Ajzen (1975), the subjective norm is defined as an individual’s perception, with his or her important references to whether a behavior should or should not be performed. The per - formance of subjective standard measurement is determined by normative beliefs for the expec - tation of appropriately performing individual behavior. From the above analysis and synthesis, the authors propose the research hypothesis. H3: Subjective standards have a positive impact on the behavior of participating in safe veg - etable production 2.2.4. Knowledge Barriers Issues of barriers implementing behaviors are mentioned in the studies as knowledge bar - riers, price barriers, geographical barriers In the research on the agricultural production im - plementation. Raju Pinire et al (2018) has shown that knowledge barriers influence technology application in rice production in Cambodia. The knowledge barrier problem is shown through several specific issues as follows: The lack of knowledge for the new production process; The lack of skills to operate a new production system; Lack of confidence in a new production model. From the above analysis and synthesis, the authors propose the research hypotheses . H4: The knowledge barrier has a negative impact on the behavior of entering the production of safe vegetables 2.2.5. Farmers’ Cooperatives Image Organizational image is the result of many factors such as experiences, beliefs, knowledge, emotions, or impressions that people give to the organization (Kazoleas et al, 2001). A business can create many messages to the public. The image of an organization is its striking power and what is communicated (Kotler and Fox, 1995). According to Kenedy (1977), the organizational image has two distinct components: function (related to intangible motivation) and emotional (related to psychology). In the Vietnamese market, when participating in the safe vegetable pro - duction system, farmers tend to learn about the business they join through the level of prestige, support for farmers, and brands. In Vietnam, the cooperatives are considered as a business model (same as a company), including production and business From the above analysis, the research team proposed the research hypothesis. H5: Farmers’ image has a positive impact on the behavior of entering into safe vegetable pro - duction 265
5. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 3. Research model and Research Methodology 3.1. Research Model Based on the mentioned research hypotheses and combined with the studies of Fishbein and Ajzen (1975) as well as Ajzen (1991). The authors propose the research model that described in Figure 1. Figure 1: The Proposal Research Model Source: Authors 3.2. Research Methodokogy Research methods applied include qualitative and quantitative research methods. In which qualitative research is used in secondary data analysis and interviewing experts and farmers in the process of conducting preliminary research. Quantitative research is used with primary data analysis with IBM SPSS 22 software. The reliability test of the scale includes the EFA test, Cron - bach Alpha test, correlation analysis Pearson, descriptive statistical analysis, and multiple regres - sion analysis were conducted to evaluate the significance of the impact of the independent variables on the dependent variables. 3.3. Measures The research scale is built on the foundation of past studies and is considered the suitability of the safe vegetable production environment in Hanoi. Also, to ensure the objectivity of the scale, the research team conducted interviews with experts and conducted preliminary research with the scale n = 24. After summarizing opinions and analyzing, the scale is extracted to 19 ob - served variables, including 5 independent variables and 1 dependent variable. The scale are de - scribed in Table 1 . 266
6. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 Table 1: Scale No Variable Content variable observed Source Expected Benefit 1 BEN1 I believe that safe vegetable production will bring high profits in the future Zhou (2006) 2 BEN2 Safe vegetable production is the right direction for my family’s production 3 BEN3 Vegetable production will bring higher profits with my family’s current production method 4 BEN4 The benefits that businesses are committed to are really attractive 4 SNO1 People important to me all think that I should produce safe vegetables López-Mosquera et al (2012); Wang (2014) 5 SNO2 People important to me willingly support me in safe vegetable production 6 SNO3 My relatives expect me to produce safe vegetables Knowledge Barrier 7 KNOB1 I don’t think I have enough knowledge about growing safe vegetables Raju Ghimire and Murari Suvedi (2018) 8 KNOB2 I lack skills to operate safe vegetable production 9 KNOB3 I do not really believe in this production model Environmental Concern 10 ENCO1 Nature’s balance is fragile and can be easily disturbed Dunlap and Jones (2012) 11 ENCO2 People are seriously abusing the environment 12 ENCO3 Man must maintain a balance with nature in order to survive 13 ENCO4 Human intervention in nature often has disastrous consequences Farmers’ Cooperatives Image 14 IMA1 The safe vegetable production enterprise has a good reputation Zeithaml (1988) 15 IMA2 Enterprise is rated prestige 16 IMA3 The enterprise is known for quality and value Farmer’s Behaviour 17 BEHA1 I myself have time to learn consider joining a network of safe vegetable production Ajzen (2002) 18 BEHA2 I can join the safe vegetable chain if I want to 19 BEHA3 For me, joining a network of safe vegetable production is easy Source: Results of data pro - cessing using SPSS 22 3.4. Collection of research data and samples Research data includes secondary data collected from 2017-2020 on issues of the current situation of safe vegetable production development. Primary data is collected through the direct interview method through questionnaires. The study questionnaire was designed as an answer on a 5-point Likert scale with values from 1-Strongly Disagree to 5-Strongly Agree. With the 267
7. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 support of the cooperatives producing safe vegetables in Hanoi, the number of research papers issued was 210 surveys and 197 surveys were collected. After reviewing and checking, 20 surveys are not valid, so the official sample is 177. Applying sample collection method from Hair et al (2006), at least 5 responses for each observed variable. For members, the minimum sample size is 19x5 = 95, so the sample size is guaranteed. The sample characteristics are shown in Table 2. Table 2. Demographic profile of the respondents. Demographic Characteristic Frequency % Gender Male 93 52.54 Female 84 47.46 Age 25-35 Years old 51 28.81 35-45 Years old 87 49.15 > 45 Years old 39 22.04 Experience 1-3 Years 54 30.51 3-5 Years 78 44.07 > 5 Years 45 25.42 4. Data analysis 4.1 Testing the reliability of the scale a. Explore factor analysis (EFA) According to Hair and et al (1998), “Factor analysis is a statistical analysis method used to reduce a set of many observed variables into a group so that they are more meaningful but still contain most of the information. News of the original variable “ Principal Components extraction was used in conjunction with Varimax rotation, Bartlett Test was performed to analyze the factors affecting the dependent variables, showing that in the first analysis, the observed variable ECO4 has a Factor loading coefficient less than 0.5, the variable ECO4 is excluded from the scale. The second EFA analysis results gave results KMO coefficient = 0.799 (in the range of 0.5 -1), Sig’s Bartlett test is 0,000 (less than 0.05), the total variance extracted is 70,287% (large more than 50%), factor loading coefficients of observed variables are greater than 0.5. For the EFA analysis with the dependent variable being the behavior of entering the production of safe vegetables, the coefficient KMO = 0.733 (in the range of 0.5 - 1), Bartlett-tested Sig = 0,000 (less than 0.05), the total Extracted variance is 78.852% (greater than 50%), factor loading coefficients of observed variables are greater than 0.5. b. Tested by Cronbach’s Alpha coefficients The test results show that 19 observed variables all meet the requirements for reliability 268
8. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 due to Cronbach Alpha coefficient> 0.6, Corrected item-total Correlation index is greater than 0.3, and Cronbach’s Alpha value if the variable type is not Cronbach’s Alpha is larger than the independent variable Table 3. Result of Cronbach Alpha and EFA Test Factor Variable Content variable observed Loading Expected Benefit. a = 0,833 BEN1 I believe that safe vegetable production will bring high profits in the future 0,719 BEN2 Safe vegetable production is the right direction for my family’s production 0,764 BEN3 Vegetable production will bring higher profits with my family’s current production 0,828 method BEN4 The benefits that businesses are committed to are really attractive 0,870 Subjective Norms. a = 0,814 SNO1 People important to me all think that I should produce safe vegetables 0,883 SNO2 People important to me willingly support me in safe vegetable production 0,864 SNO3 My relatives expect me to produce safe vegetables 0,786 Knowledge Barriers. a = 0,723 KNOB1 I don’t think I have enough knowledge about growing safe vegetables 0,781 KNOB2 I lack skills to operate safe vegetable production 0,863 KNOB3 I do not really believe in this production model 0,753 Environment Concern. a = 0,771 ENCO1 Nature’s balance is fragile and can be easily disturbed 0,813 ENCO2 People are seriously abusing the environment 0,834 ENCO3 Man must maintain a balance with nature in order to survive 0,743 Farmers’ Cooperatives Image. a = 0,824 IMA1 The safe vegetable production cooperatives has a good reputation 0,789 IMA2 Farmers’ Cooperatives is rated prestige 0,821 IMA3 The cooperatives is known for quality and value 0,792 Farmer’s Behavior. a = 0,866 BEHA1 I myself have time to learn consider joining a network of safe vegetable production 0,905 BEHA2 I can join the safe vegetable chain if I want to 0,880 BEHA3 For me, joining a network of safe vegetable production is easy 0,878 Source: Results of data processing using SPSS 22 Through EFA analysis for groups of observed variables in the group of independent vari - ables and a group of observed variables in the group of dependent variables as well as testing Cronbach’s Alpha coefficient, according to Hair et al. (2010), the model is consistent with the collected data. security and reliability. 269
9. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 4.2. Correlation analysis Pearson’s correlation analysis will help check the linear relationship between the compo - nent variables through EFA factor analysis, which shows that the results of the correlation coef - ficient are all less than 0.85, indicating that potentially exists between 2 pairs of variables. In addition to the correlation relationship of Knowledge Barrier with a Sig greater than 0.05, it means that there is no correlation between this factor to the other variables, the result has a Sig value of less than 0.05. The pairs of variables are correlated and statistically significant excluding pairs of variables related to the Knowledge Barrier. However, in order to conclude whether or not the multicollinearity occurs, the study will clarify in the next section when relying on the VIF coefficient in multiple regression analysis. The results of the correlation analysis are described in Table 4. Table 4: Pearson correlation analysis IMA SNO BEN ENCO KNOB BEHA IMA Pearson Correlation 1 Sig. (2-tailed) SNO Pearson Correlation .385 1 Sig. (2-tailed) .000 BEN Pearson Correlation .368 .322 1 Sig. (2-tailed) .000 .000 ENCO Pearson Correlation .458 .191* .217 1 Sig. (2-tailed) .000 .011 .004 KNOB Pearson Correlation .143 .099 .052 .058 1 -.010 Sig. (2-tailed) .057 .189 .490 .443 .898 BEHA Pearson Correlation .645 .509 .573 .411 -.010 1 Sig. (2-tailed) .000 .000 .000 .000 .898 Source: Results of data processing using SPSS 22 4.3. Multiple regression analysis Linear regression models are used to test and explain causality. Multiple linear regression is often used as a conclusion tool to test hypotheses and predict research population values in addition to descriptive functions. Therefore, regression is a suitable method to test research hypotheses. Detailed results are illustrated in Table 4 270
10. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 Table 4: Results of multiple regression analysis Variable Beta Sig T-value VIF Dependent Independent BEHA BEN 0,315 0,000 6,344 1,214 ENCO 0,110 0,025 2,255 1,269 KNOB -0,102 0,000 -2,374 1,023 SNO 0,237 0,019 4,563 1,231 IMA 0,378 0,000 6,699 1,531 R2 adjusted= 0,604; F-value=54,915; Sig F=0,000 Source: Results of data processing using SPSS 22 The results of the regression analysis showed that all 5 independent variables have an impact on the independent variable and meet the requirement of the Sig value. <0.05. F-value = 54,915, F-test significance = 0,000. The VIF indexes are all less than 2, so it can be concluded that the multicollinearity phenomenon does not occur. Based on the standardized beta coefficient, the order of impact on the independent variables in descending order is: Enterprise image with = 0.378; Expected benefit with = 0.315; Subjective standards with = 0.237; Knowledge of the en - vironment with = 0.110 and finally the knowledge barrier affects the negative beta coefficient (= - 0.10). That is, the knowledge barrier has the effect of hindering the farmers’ behavior to join safe vegetable production. Index R 2 = 0.604 shows that the independent variables can explain 60.4% of the variation of the dependent variable, while 39.6% of the remaining variation is due to errors and other factors. Based on the results of the regression analysis, the standardized re - gression equation is: BEHA= 0,315*BEN + 0,110*ENCO - 0,102*KNOB + 0,237*SNO + 0,378*IMA 4.4. Thống kê mô tả N Mean Std. Deviation IMA 178 3.8670 .65175 SNO 178 3.4794 .63375 BEN 178 3.3174 .65931 ENCO 178 3.5150 .68347 KNOB 178 3.7004 .70162 BEHA 178 3.6442 .62747 Valid N (listwise) 178 Source: Results of data processing using SPSS 22 271
11. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 Enterprise image has an average value of 3,867, the highest value among the variables shows that the importance of enterprise image is a factor of great concern by the cooperative pro - ducing safe vegetables. Knowledge barriers in the production of safe vegetables account for a rather high value of 3,7004, claiming that the cooperatives pay attention to knowledge to produce standard safe vegetables. The behavior of joining the safe vegetable production chain is desirable and the cooperative itself has enough confidence to supply safe vegetables to the market with a value of 3.6442. Environmental concern factors have been fully explored by the cooperatives be - cause the environmental concern impact has a great impact on safe vegetable products with a value of 3,515. The values of the cooperative subjective standard with the value 3.4794 showed a change in attitude and the importance of safe vegetables to the cooperative. Safe vegetables and market requirements affecting cooperatives with the lowest expected benefit value among 6 variables with the value 3.3174. 5. Some conclusions, policy implications, and further research directions 5.1. Conclusion The study has completed the task of assessing the impact of 5 groups of factors on the be - havior of farmers joining safe vegetable production. The results show that 5 research hypotheses are accepted, of which 4 independent variables have a positive effect and the other one has a neg - ative impact on the dependent variable. From the research results, some important conclusions are drawn including: Firstly, corporate image and expected benefits are playing an important role in the entry behavior of farmers with a much higher coefficient than others. Second, subjective standards have significant impact showing that farm owners always consult with those around them in making final decisions. Third, environmental awareness positively influences accession behavior, showing that farmers are not only interested in benefits, but also have perceptions of business development associated with environmental benefits. Fourthly, knowledge limitations are becoming a barrier to the farmers’ entry into safe veg - etable production. 5.2. Implications Based on research results, the authors propose a number of policy implications to help co - operatives develop safe vegetable production systems: Firstly, building a business image on the basis of development orientation is associated with social responsibility. Second, focus on cooperation to ensure benefits not only for farmers but also to ensure en - vironmental issues. Third, taking measures to ensure environmental conditions when conducting farming and operating production models. Fourth, focus on activities to guide and supplement knowledge for farmers in the operation 272
12. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 and improve farming skills to break down the knowledge barrier of farmers intending to join the system. safe vegetable production system. 5.3. Further research orientation Despite trying to complete the research objectives, but due to the time and space limitations, there are still limitations, from these limitations opening up many research directions in the future. Firstly, the sample size is limited and the type of research considered is a cooperative model. Therefore, the research results are not highly representative. Therefore, in the future, it would be ideal if the research is to be modeled and to conduct research on other diverse subjects besides a cooperative model. Second, the index R 2 = 0.604 shows that nearly 40% of the variation of the independent variable has not been discovered. This means that it is necessary to consider adding new factors to the model such as the resources of farmers, support from agricultural development policies Thirdly, the study has not been able to conduct multi-group tests to assess the differences between study groups. Criteria of years of farming experience, age, financial capacity, and cul - tivated land area have many potential discoveries if they are conducted in multi-group tests. REFERENCES 1. Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes , 50 (2), 179-211. 2. Ajzen, I. (2002). Perceived behavioral control, selfefficacy, locus of control, and the theory of planned behavior 1. Journal of applied social psychology , 32 (4), 665-683. 3. Al-Ali, M., Bazin, N. E. N., & SHAMSUDDIN, S. (2015). KEY DETERMINANTS OF CUSTOMER SATISFACTION: EVIDENCE FROM MALAYSIA GROCERY STORES. Journal of Theoretical & Applied Information Technology , 74 (3). 4. Albayrak, T.; Aksoy, S .; Caber, M. The effect of environmental concern and scepticism on green purchase behaviour. Mark. Intell. Plan. 2013 , 31 , 27–39. 5. Bagozzi, R. P. (1992). The self-regulation of attitudes, intentions, and behavior. Social psychology quarterly , 178-204. 6. Cordano, M., Welcomer, S., Scherer, R. F., Pradenas, L., & Parada, V. (2011). A cross- cultural assessment of three theories of pro-environmental behavior: A comparison between busi - ness students of Chile and the United States. Environment and Behavior , 43 (5), 634-657. 7. Dunlap, R.; Jones, R. Environmental concern: Conceptual and measurement issues. In Handbook of Environmental Sociology; Dunlap, R.E., Michelson, W., Eds.; Greenwook Press: London, UK, 2012; pp. 482–542. 8. Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduc - tion to Theory and Research. Reading, MA: Addison-Wesley. 273
13. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 9. Ghimire, R., & Suvedi, M. (2018). FARMERS’ADOPTION OF IMPROVED RICE VA - RIETIES IN CAMBODIA. Journal of ISSAAS (International Society for Southeast Asian Agri - cultural Sciences) , 24 (1), 41-57. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate data analysis (Vol. 5, No. 3, pp. 207-219). Upper Saddle River , NJ: Prentice hall. 10. Kazoleas, D., Kim, Y., & Moffitt, M. A. (2001). Institutional image: a case study. Cor - porate Communications: an international journal . 11. Kotler, P. and Fox, K. (1985), Strategic Marketing for Educational Institutions, Pren - tice-Hall, Englewood Cliffs, NJ. 12. López-Mosquera, N., & Sánchez, M. (2012). Theory of Planned Behavior and the Value-Belief-Norm Theory explaining willingness to pay for a suburban park. Journal of envi - ronmental management , 113 , 251-262. 13. Mamudu Abunga Akudugu1* Emelia Guo1 Samuel Kwesi Dadzie2 (2012), Adoption of modern agricultural production technologies by farm households in Ghana: What factors in - fluence their decisions?, Journal of Biology, Agriculture and Healthcare www.iiste.org ISSN 2224-3208 (Paper) ISSN 2225-093X (Online)Vol 2, No.3, 2012 14. Nguyen, H. V., Nguyen, N., Nguyen, B. K., Lobo, A., & Vu, P. A. (2019). Organic food purchases in an emerging market: The influence of consumers’ personal factors and green mar - keting practices of food stores. International journal of environmental research and public health , 16 (6), 1037. 15. Wang, Y. (2014). Consumers’ purchase intentions of shoes: theory of planned behavior and desired attributes. International Journal of Marketing Studies , 6(4), 50. 16. Zhou, Y., Wang, X., Zeng, X., Qiu, R., Xie, J., Liu, S., & Ran, P. (2006). Positive benefits of theophylline in a randomized, doubleblind, parallelgroup, placebocontrolled study of lowdose, slowrelease theophylline in the treatment of COPD for 1 year. Respirol - ogy , 11 (5), 603-610. 17. Zeithaml, V.A. (1988), “Consumer perceptions of price, quality, and value: a means- end model and synthesis of evidence”, Journal of Marketing , Vol. 52, July, pp. 2-22. 18. Zeithaml, V.A. et al. (1988), “Communication and control processes in the delivery of service quality”, Journal of Marketing, April. 274