Earticle

People tend to resist changing their software even alternatives are better then the current one. This study examines the resistance to change in the use of software from the switching costs perspective based on status quo bias theory. For this study, we select Web Browsers as software. Based on the classification of switching costs into three groups (psychological, procedural, and loss), this study identifies six types of switching costs (uncertainty, commitment, learning, setup, lost performance, and sunk costs). This study tests the effects of six switching costs on user resistance to change based on the survey of 204 web browser users. The results indicate that lost performance costs and emotional costs have significant effects on user resistance to change. This research contributes towards understanding of switching costs and the effects on user resistance to change. This study also offers suggestions to software vendors for retaining their users and to organizations for managing user resistance in switching and adopting software.

In this paper, we study the relationships among task-technology fit (TTF), performance, and information system (IS) continuance in the different levels of Software-as-a-service (SaaS) maturity. Two-hundred-and-seven survey responses from Korea were analyzed using partial least square. The results indicate that the more a user evaluates TTF, a user gets higher performance. The results also show that performance factors significantly influence SaaS continuance intention, which is moderated by SaaS maturity. This is important because research on IS use and performance primarily examine technologies that are novel or may not be fully mature at the time of implementation. Technology maturity warrants should be investigated in future studies.