CCTA 2008: Computer and Computing Technologies in Agriculture II, Volume 3 pp 1845-1853 | Cite as
FARMERS' INFORMATION USAGE INTENTION IN CHINA BASED ON THE TECHNOLOGY ACCEPTANCE MODEL
Abstract
Information technology acceptance has received much attention, but little research has been conducted to assess farmers’ information adoption. Despite the importance of information, its value will not be realized if farmers are reluctant to accept it. This research aims to study farmers’ information adoption in China, in order to provide some decision-making advice for the people and organization who supply the agriculture information. The model of information usage intention has been established based on the Technology Acceptance Model (TAM). A sample of 231 farmers participated in this study. The results show that the factors which influence the usage willingness for information are perceived usefulness, perceived ease of use, learning intention, risk preference and experience in information before. In addition, income and education may also affect the decision.
Keywords:
information demand usage intention technology acceptance model perceived usefulness perceived ease of use perceived riskReferences
- Fred D. Davis, Richard P. Bagozzi, Paul R. Warshaw. User Acceptance of Computer Technology: A Comparison Of Two Theoretical Models, Management Science, 1989, 35: 982–1003CrossRefGoogle Scholar
- Fred D. Davis.Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology, IS Quarterly, 1989, 9:319–340Google Scholar
- Hyun-Hwa Lee, Ann Marie Fiore, Jihyun Kim. The role of the technology acceptance model in explaining effects of image interactivity technology on consumer responses, International Journal of Retail & Distribution Management, 2006, 8: 621–644Google Scholar
- J. Alberto Castaneda, Francisco Munoz-Leiva, Teodoro Luque.Web Acceptance Model(WAM):Moderating effects of user experience, Information& Management, 2007, 44: 384–396CrossRefGoogle Scholar
- Juan Carlos Roca,Chao-Min Chiu,Francisco Jose Martinez. Understanding e-learning continuance intention:An extension of the Technology Acceptance Model, Human-Computer Studies,2006,64:683–696CrossRefGoogle Scholar
- Mattew K.O. Lee, Christy M.K, Cheung, Zhaohui Chen. Acceptance of Internet-based learning medium:the role of extrinsic and intrinsic motivation, Information & Management,2005,42:1095–1104CrossRefGoogle Scholar
- Sally McKechnie, Heidi Winklhofer, Christine Ennew. Applying the technology acceptance model to the online retailing of financial services, International Journal of Retail & Distribution Management, 2006, 34:388–410CrossRefGoogle Scholar
- William R. King, Jun He. A meta-analysis of the technology acceptance model, Information & Management, 2006, 43:740–755CrossRefGoogle Scholar
- Yi-Shun Wang, Hsiu-Yuan Wang, Daniel Y. Shee. Measuring e-learning systems success in an organizational context:Scale development and validation, Computers in Human Behavior, 2007,23:1792–1808CrossRefGoogle Scholar