Work place: School of Information Technology, Sripatum University, Bangkok 10900, Thailand
E-mail: rathjairak@gmail.com
Website:
Research Interests: Information Systems, Multimedia Information System, Information Theory
Biography
Rath Jairak received his B.Sc. in Photographic Science and Printing Technology from Chulalongkorn University, Bangkok, Thailand, in 1999, and his M.S. in Information Technology and Management from Chiang Mai University, Chiang Mai, Thailand, in 2005. He is currently a Ph.D candidate in Information Technology, Doctor of Philosophy Program in Information Technology, School of Information Technology, Sripatum University, Thailand. Rath is also a lecturer at Chiang Mai Rajabhat University. His research interests include e-Commerce, e-Services, and trust management. His current focus is on trust development in B2C e-Commerce services. In addition, he published more than ten papers in these areas.
By Rath Jairak Prasong Praneetpolgrang Nivet Chirawichitchai
DOI: https://doi.org/10.5815/ijieeb.2014.05.01, Pub. Date: 8 Oct. 2014
Trust has been reported as a key role in e-business, especially for a monetary based system like e-commerce. Therefore, many previous studies have been conducted to investigate the antecedents and consequences of consumer trust. But there has been little work done on establishing sensible solutions for leveraging consumer trust. Furthermore, previous studies in managerial trust have not demonstrated trust management that can illustrate a method to link their solutions with the consumers' point of view. In this paper, we therefore propose a practical roadmap for establishing trust management strategy that is consistent with consumer perceptions. Within this roadmap, firstly, a component extraction is performed on survey data in order to identify the quality criteria that actually impact buying decision process. Based on these criteria, the sensible factors for establishing trust and satisfaction are discovered from the regression analysis. Then, the prediction equations for trust and satisfaction are generated. After that the results of prediction equations are applied with a fuzzy linguistic approach in order to convert these results in linguistic terms. Finally, trust management strategy is established. By using our proposed method, website managers can identify which are the quality criteria that are consistent with their customer perceptions and they can use these criteria as a basis for improving trust and satisfaction in their websites.
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