Given that adoption of a new system often implies fully or partly replacing an incumbent system, resistance is often manifested as failure of a user to switch from an incumbent technology to a newly introduced one. Thus, a potential source of resistance to adopting a new system lies in the use of an incumbent system. Using the status quo bias and habit literatures as theoretical lenses, the study explains how use of an incumbent system negatively impacts new system perceptions and usage intentions. We argue that habitual use of an incumbent system, rationalization due to perceived transition costs, and psychological commitment due to perceived sunk costs all encourage development of inertia. Inertia in turn fully mediates the impact of these incumbent system constructs on constructs related to acceptance of the new system via psychological commitment based on cognitive consistency and by increasing the importance of normative pressures. Specifically, we hypothesize that inertia leads to decreased perceptions of the ease of use and relative advantage of a newly introduced system and has a negative impact on intentions to use the new system, above and beyond its impact through perceptions. Finally, we hypothesize that inertia moderates the relationship between subjective norm and intention, such that normative pressures to use a new system become more important in the presence of inertia. Empirical results largely support the hypothesized relationships showing the inhibiting effect of incumbentsystem habit, transition and sunk costs, and inertia on acceptance of a new system. Our study thus extends theoretical understanding of the role of incumbent system constructs such as habit and inertia in technology acceptance, and lays the foundations for further study of the interplay between perceptions and cognition with respect to the incumbent system and those with respect to a new system.

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Social network analysis (SNA) offers a richer and more objective way of examining individual journal influence and relationships among journals than studies based on individual perceptions, since it avoids personal biases. This article demonstrates how SNA can be used to study the nature of the IS discipline, by presenting results from an exploratory SNA of 125 previously ranked journals from IS and allied disciplines. While many of the most prominent journals in the network are still associated with IS's foundational disciplines, we identify several IS journals that play important roles in disseminating information throughout different subcomponents of the network. We also identify related groups of journals based not only on patterns of information flow, but also on similarity in citation patterns. This enables us to identify the core set of journals that is important for "pure IS" research, as well as other subsets of journals that are important for specialty areas of interest. Overall, results indicate that the IS discipline is still somewhat fragmented and is still a net receiver, as opposed to a net provider, of information from allied disciplines. Like other forms of analysis, SNA is not entirely free from biases. However, these biases can be systematically researched in order to develop an improved, consistent tool with which to examine the IS field via citations among member journals. Thus, while many challenges remain in applying SNA techniques to the study of IS journals, the opportunity to track trends in the discipline over time, with a larger basket of journals, suggests a number of valuable future applications of SNA for understanding the IS publication system.