E-commerce Adoption for Rice Selling in Thailand: An Empirical Study


  • Jesada Arromdee International College, National Institute of Development Administration (NIDA), Thailand
  • Sid Suntrayuth International College, National Institute of Development Administration (NIDA), Thailand


Thai rice farmer, E-commerce (EC) adoption for rice selling, Unified theory of acceptance and use of technology (UTAUT)


The objective of this research was to analyze the factors that influence e-commerce (EC) adoption by Thai rice farmers. The study employed a conceptual model, based on four main constructs of the unified theory of acceptance and use of technology (UTAUT) model (i.e., performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC)), as well as four additional constructs (perceived implementation cost (IC), perceived risks (PR) sufficient information technology knowledge (IT) and government supports (GOV)), to test Thai rice farmers’ behavioral intention (BI) and their acceptance and adoption (AA) of EC for rice selling. In the context of EC adoption for rice selling in Thailand, the study found that behavioral intention (BI) tends to have a significant relationship with acceptance and adoption (AA) of EC for rice selling. Statistical supporting evidence demonstrated that performance expectancy (PE), social influence (SI), sufficient IT knowledge (IT) and government supports (GOV) (independent variables) have a positive influence on behavioral intention (BI) to adopt EC for rice selling, while effort expectancy (EE) has a negative influence. Consequently, the results of this study are expected to provide initial guidance for Thai rice farmers in further adoption of EC for rice selling. These outcomes are also expected to guide relevant government agencies in adjusting their corporate strategies and plans to not only encourage greater focus by Thai rice farmers on EC adoption for rice selling, but also to assist them in successful EC adoption.


Abrahão, R.D.S., Moriguchi, S.N., & Andrade, D.F. (2016). Intention of adoption of mobile payment: An analysis in the light of the Unified Theory of Acceptance and Use of Technology (UTAUT). RAI Revista de Administração e Inovação, 13(2016), 221-230.

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.

Alenezi, A.R., Karim A.M.A. and Veloo, A. (2010). An empirical investigation into the role of enjoyment, computer anxiety, computer self-efficacy and internet experiment in influencing the students’ intention to use e-learning: A case study from Saudi Arabian Governmental Universities, The Turkish Online Journal of Educational Technology, 9(4), 22-34.

Alhilali, A. (2013). Technology adaptation model and road map to successful implementation of ITIL. Journal of Enterprise Information, 26(5), 553-576.

Alkhunaizan, A., & Love, S. (2012). What drives mobile commerce? An empirical evaluation of the revised UTAUT model. International Journal of Management and Marketing Academy, 2(1), 82-99.

Alshehri, M., Drew, S., Alhussain, T., & Alghamdi, R. (2012). The effects of website quality on adoption of e-government service: An empirical study applying UTAUT model using SEM. Proceedings of the 23rd Australasian Conference on Information Systems, Geelong, Australia.

Bhatiasevi, V. (2016). An extended UTAUT model to explain the adoption of mobile banking. Information Development, 32(4), 799-814.

Biucky, S.T., Abdolvand, N., & Harandi, S.R. (2017). The effects of perceived risk on social commerce adoption based on the TAM model. International Journal of Electronic Commerce Studies, 8(2), 173-196.

Casey, T., & Wilson-Evered, E. (2012). Predicting uptake of technology innovations in online family dispute resolution services: An application and extension of the UTAUT. Computer Human Behavior, 28, 2034-2045.

Carpio, C.E., Isengildina-Massa, O., Lamie, R.D., & Zapata, S.D. (2013). Does e-commerce help agricultural markets? The case of market maker. The magazine of food, farm, and resource issues 4th Quarter, 28(4).

El-fitouri, M.O. (2015). E-commerce in developing countries: A case study on the factors affecting e-commerce adoption in Libyan companies. International Journal of Engineering Research and Applications, 5(1), 102-115.

Etikan, I., Alkassim, R., & Abbakar, S. (2016). Comparison of snowball sampling and sequential sampling technique. Biometrics & Biostatistics International Journal, 3(1), 1-2.

Field, A. (2009). Discovering statistics using SPSS (3rd ed.). London, UK: Sage Publication Ltd. Fornell, C., & Larcker, D. (1981). Structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1): 39–50.

Gefen, D., & Straub, D. (2000). The relative importance of perceived ease of use in IS adoption: A study of e-Commerce adoption. Journal of the Association for Information Systems, 1(8), 1-28.

Ghobakhloo, M., & Tang, S.H. (2013). The role of owner/manager in adoption of electronic commerce in small businesses: The case of developing countries. Journal of Small Business and Enterprise Development, 20(4), 754-787.

Hair, J.F., Black, W.C., Babin, B.J., & Anderson, R.E. (2010). Multivariate data analysis (7th ed.). Upper Saddle River, NJ: Prentice Hall.

Ilin, V., Ivetić, J., & Simić, D. (2017). The determinants of e-business adoption in ERP-enabled firms and non-ERP-enabled firms: A case study of the Western Balkan Peninsula. Technological Forecasting & Social Change, 125(2017), 206-223.

Im, I., Kim, Y., & Han, H.J. (2008). The effect of perceived risk and technology type on users’ acceptance of technologies. Information & Management, 45, 1-9.

Jamaluddin, N. (2013). Adoption of e-commerce practices among the Indian farmers, A survey of Trichy District in state of Tamilnadu, India. Procedia Economics and Finance, 7(2013), 140-149.

Kabango, C.M., & Asa, A.R. (2015). Factors influencing e-commerce development: implications for the developing countries. International Journal of Innovation and Economic Development, 1(1), 64-72.

Kapurubandara, M., & Lawson, R. (2006). Barriers to adopting ICT and e-commerce with SMEs in developing countries: An exploratory study in Sri Lanka. Proceedings of the Conference on Collaborative Electronic Commerce Technology and Research, Adelaide, Australia.

Kyobe, M. (2011). Investigating the key factors influencing ICT adoption in South Africa, Journal of Systems and Information Technology. 13(3), 255-267.

Lawrence, J.E., & Tar, U.A. (2010). Barriers to ecommerce in developing countries. Information, Society & Justice, 3(1), 23-35.

Looi, H.C. (2005). E-commerce adoption in Brunei Darussalam: A quantitative analysis of factors influencing its adoption. Communications of the Association for Information Systems, 15(3), 61–81.

Martín, H.S., & Herrero, A. (2012). Influence of the user’s psychological factors on the online purchase intention in rural tourism: Integrating innovativeness to the UTAUT framework. Tourism Management, 33, 341-350.

National Statistical Office (2014). 2013 Agricultural census whole Kingdom. Retrieved from http://web.nso.go.th/en/census/agricult/cen_agri03.htm

Office of Agricultural Economics (2019). Agricultural statistics of Thailand 2018. Retrieved from http://www.oae.go.th/assets/portals/1/files/jounal/2562/yearbook 2561.pdf

Pett, M., Lackey, N., & Sullivan, J. 2003. Making sense of factor analysis. Thousand Oaks, CA: Sage Publications, Inc.

Sahavacharin, N., & Srinon, R. (2016). The influence of price transmission on Thai Hom Mali rice supply chain. Proceedings of the International MultiConference of Engineers and Computer Scientists 2016, (Vol. 2).

Saunders, M., Lewis, P., & Thornhill, A. (2009). Research methods for business

students (5th ed.). Essex: Prentice Hall.

Slade, E.L., Dwivedi, Y.K., Piercy, N.V., & Williams, M.D. (2015). Modeling consumers’ adoption intentions of remote mobile payments in the United Kingdom: Extending UTAUT with innovativeness, risk, and trust. Psychology & Marketing, 32(8), 860–873.

Straub, E.T. (2009). Understanding technology adoption: Theory and future directions for informal learning. Review of Educational Research, 79(2), 625-649.

Tan, K.S., Chong, S.C., & Lin, B. (2013). Intention to use internet marketing: A comprehensive study between Malaysians and South Koreans. Kybernetes, 42(6), 888-905.

Tarhini, A., El-Masri, M., Ali, M., & Serrano, A. (2016). Extending the UTAUT model to understand the customers’ acceptance and use of internet banking in Lebanon: A structural equation modeling approach. Information Technology & People, 29(4), 830-849.

Terzis, V., & Economides, A.A. (2011). The acceptance and use of computer based assessment. Computer and Education, 56, 1032-1044.

Titapiwatanakun, B. (2012). The rice situation in Thailand (Project Number: TA-REG 7495). Technical Assistance Consultant’s Report. Asian Development Bank. Retrieved from https://www.adb.org/sites/default/files/project-document/73082/ 43430-012-reg-tacr-03.pdf

Venkatesh, V., Morris, M.G., Davis, G.B., & Davis, F.D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.

Vogt, L., Gröger, T., & Zimmermann, R. (2007). Automated compound classification for ambient aerosol sample separations using comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry. Journal of Chromatography A, 1150(1-2), 2-12.

Wang, H.Y., & Wang, S.H. (2010). User acceptance of mobile internet based on the unified theory of acceptance and use of technology: Investigating the determinants and gender differences. Social Behavior and Personality, 38(3), 415-426.

Wattanutchariya, W., Tansuchat, R., & Ruennareenard, J. (2016). Supply chain management of Thai parboiled rice for export. International Conference on Industrial Engineering and Operations Management, 504-510.

Wu, Y.L., Tao, U.H., & Yang, P.C. (2007). Using UTAUT to explore the behavior of 3G mobile communication users. IEEE, 199-203.

Yamane, T. (1973). Statistics: An introductory analysis (3rd ed.). New York, NY: Harper and Row.

Yu, C.S. (2012). Factors affecting individuals to adopt mobile banking: Empirical evidence from the UTAUT model. Journal of Electronic Commerce Research, 13(2), 104-121.

Zhao, F., & Khan, M.S. (2013). An empirical study of e-government service adoption: Culture and behavioral intention. International Journal of Public Administration, 36, 710–722.




How to Cite

Arromdee, J., & Suntrayuth, S. . (2020). E-commerce Adoption for Rice Selling in Thailand: An Empirical Study. Thailand and The World Economy, 38(2), 88–118. Retrieved from https://so05.tci-thaijo.org/index.php/TER/article/view/234917