Measuring Web-based business-to-business support system success based on user satisfaction

This research draws on the Delone and McLean's Model of IS Success, the technology acceptance model, the Garrity and Sanders' model of IS success, and social influence theories in order to examine the dimensions and theoretical relationships related to Web-based B2B support systems success.; This study has found partial support for the Web-Based Business-to-Business Support Systems Success Model. Behavioral Intention to use a Web-based B2B support system is primarily explained via Task Support Satisfaction and Quality of Work Life Satisfaction which are mediating the effects of the other four independent variables (Interface Satisfaction, Decision Support Satisfaction, Subjective Norms, and Perceived Network Externalities). By bringing Quality of Work Life Satisfaction to the IS success model, this study extends Davis, et al.'s (1989) findings and other user satisfaction studies. Subjective Norms turn out to affect Behavioral Intention to use a Web-based B2B support system indirectly through Quality of Work Life Satisfaction. The impact of Interface Satisfaction on Behavioral Intention to use a system appears to be mediated by both Quality of Work Life Satisfaction and Task Support Satisfaction, as expected.; However, in the context of business-to-business transactions, Interface Satisfaction does not seem to influence Decision Support Satisfaction. This result is in contrast to the previous research. The findings of this study do not support the relationships between Perceived Network Externalities, Task Support Satisfaction, and Behavioral Intention to use a Web-based B2B support system.; The contributions of this research are three fold. First, the current research is one of the first investigations of Web-based B2B system success. Second, this study identifies the dimensions of B2B system success and develops a set of validated measurements for Web-based B2B support system success in the context of user satisfaction. Third, this research will provide valuable implications to managers and academics regarding technology adoption criteria.