Organic food is said to have a positive impact on people's health and wholesome to the environment due to its ecological nature. However, there are challenges for organic food retailers in Malaysia to create a marketing strategy since the number of consumers of organic foods is quite low compared to other countries. This aims of this research is to study factors and sub-factors influencing consumer buying behaviour for organic food in Kuantan, Pahang to firmly grasp the nature of organic food business industry. To achieve such objective, Fuzzy Delphi Method has been utilised to analyse the five factors considered which are price, behavioural intention, subjective norm, attitude, and consumer knowledge. The findings shown that the most influential sub-factor affecting consumer purchasing behaviour towards organic food under behavioural intention was that people usually consider purchasing organic food that meets their taste, while for subjective norms, the concept of organically grown food is the most influential sub-factor. Furthermore, the reasonable price, familiarity with products and health and fitness reasons are the leading sub-factors for price, consumer knowledge and attitude factors, respectively.
Adler, M., & Ziglio, E. (1996). Gazing into the Oracle: The Delphi Method and its Application to Social Policy and Public Health. London: Jessica Kingsley Publication.
Arora, A., Rani, N., Devi, C., & Gupta, S. (2022). Factors affecting consumer purchase intentions of organic food through fuzzy AHP. International Journal of Quality and Reliability Management, 39(5), 1085–1103. https://doi.org/10.1108/IJQRM-01-20210019
Bai, L., Wang, M., & Gong, S. (2019). Understanding the antecedents of organic food purchases: The important roles of beliefs, subjective norms, and identity expressiveness. Sustainability (Switzerland), 11(11). https://doi.org/10.3390/su11113045
Chen, C.T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems 2000, 114: 1-9.
Cheng, C. H., & Lin, Y. (2002). Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation. European Journal of Operational Research 2002, 142 (1) 74-86.
Chu, H. C., & Hwang, G. J. (2008). A Delphi-based approach to developing expert systems with the cooperation of multiple experts. Expert Systems with Applications 2008; 34: 28 26-40.
Ciptono, A., Setiyono, S., Nurhidayati, F., & Vikaliana, R. (2019). Fuzzy Delphi method in education: A mapping. Journal of Physics: Conference Series, 1360(1).
https://doi.org/10.1088/1742-6596/1360/1/012029
Di Zio, S., Bolzan, M., & Marozzi, M. (2021). Classification of Delphi outputs through robust ranking and fuzzy clustering for Delphi-based scenarios. Technological
Forecasting and Social Change, 173, 121140.
https://doi.org/10.1016/j.techfore.2021.121140
Ebrahimi, S., & Bridgelall, R. (2021). A fuzzy Delphi analytic hierarchy model to rank factors influencing public transit mode choice: A case study. Research in
Transportation Business and Management, 39, 100496.
https://doi.org/10.1016/j.rtbm.2020.100496
Jones, H., & Twiss, B. L. (1978). Forecasting Technology for Planning Decisions. New York: Macmillan.
Jouzi, Z., Azadi, H., Taheri, F., Zarafshani, K., Gebrehiwot, K., Van Passel, S., & Lebailly, P. (2017). Organic Farming and Small-Scale Farmers: Main Opportunities and Challenges. Ecological Economics, 132, 144–154.
https://doi.org/10.1016/j.ecolecon.2016.10.016
Kamarulzaman, N., Jomhari, N., Raus, M. N., & Yusoff, Z. M. M. (2015).
Applying the Fuzzy Delphi Method to Analyse the user Requirement for user Centred Design Process in Order to Create Learning Applications. Indian Journal of Science and Technology, 8(32). https://doi.org/10.17485/ijst/2015/v8i32/92146
Kuzniar, W., Surmacz, T., & Wierzbinski, B. (2021). The impact of ecological knowledge on young consumers' attitudes and behaviours towards the food market. Sustainability
(Switzerland), 13(4), 1–21. https://doi.org/10.3390/su13041984
Mosayebi, A., Ghorbani, S., & Masoomi, B. (2020). Applying fuzzy delphi and best-worst method for identifying and prioritising key factors affecting on university-industry collaboration. Decision Science Letters, 9(1), 107–118.
https://doi.org/10.5267/j.dsl.2019.7.001
Qasim, H., Yan, L., Guo, R., Saeed, A., & Ashraf, B. N. (2019). The defining role of environmental self-identity among consumption values and behavioral intention to consume organic food. International Journal of Environmental Research and Public Health, 16(7). https://doi.org/10.3390/ijerph16071106
Sadiq, M., Paul, J., & Bharti, K. (2020). Dispositional traits and organic food consumption.
Journal of Cleaner Production, 266, 121961.
https://doi.org/10.1016/j.jclepro.2020.121961
Taghva, M. R., Taghavifard, M. T., Pouti, N., & Fathian, M. (2022). Determining the factors affecting the acceptance of social commerce in service-oriented businesses using the fuzzy Delphi method. International Journal of Electronic Business, 17(2), 135. https://doi.org/10.1504/ijeb.2022.10044964
Tang, C. W., & Wu, C. T. (2010). Obtaining a picture of undergraduate education quality: a voice from inside the university, Springer. Higher Education 60: 269-286.
Wang, X., Pacho, F., Liu, J., & Kajungiro, R. (2019). Factors influencing organic food purchase intention in Tanzania and Kenya and the moderating role of knowledge. Sustainability (Switzerland), 11(1). https://doi.org/10.3390/su11010209
Zheng, G. W., Akter, N., Siddik, A. B., & Masukujjaman, M. (2021). Organic foods purchase behavior among generation y of bangladesh: The moderation effect of trust and price consciousness. Foods, 10(10). https://doi.org/10.3390/foods10102278
