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Individual-level information systems adoption research has recently seen the introduction of expectation-disconfirmation theory (EDT) to explain how and why user reactions change over time. This prior research has produced valuable insights into the phenomenon of technology adoption beyond traditional models, such as the technology acceptance model. First, we identify gaps in EDT research that present potential opportunities for advances-specifically, we discuss methodological and analytical limitations in EDT research in information systems and present polynomial modeling and response surface methodology as solutions. Second, we draw from research on cognitive dissonance, realistic job preview, and prospect theory to present a polynomial model of expectation-disconfirmation in information systems. Finally, we test our model using data gathered over a period of 6 months among 1,143 employees being introduced to a new technology. The results confirmed our hypotheses that disconfirmation in general was bad, as evidenced by low behavioral intention to continue using a system for both positive and negative disconfirmation, thus supporting the need for a polynomial model to understand expectation disconfirmation in information systems.

Prior research has extensively studied individual adoption and use of information systems, primarily using beliefs as predictors of behavioral intention to use a system that in turn predicts system use. We propose a model of acceptance with peer support (MAPS) that integrates prior individual-level research with social networks constructs. We argue that an individual's embeddedness in the social network of the organizational unit implementing a new information system can enhance our understanding of technology use. An individual's coworkers can be important sources of help in overcoming knowledge barriers constraining use of a complex system, and such interactions with others can determine an employee's ability to influence eventual system configuration and features. We incorporate network density (reflecting "get-help" ties for an employee) and network centrality (reflecting "give-help" ties for an employee), drawn from prior social network research, as key predictors of system use. Further, we conceptualize valued network density and valued network centrality, both of which take into account ties to those with relevant system-related information, knowledge, and resources, and employ them as additional predictors. We suggest that these constructs together are coping and influencing pathways by which they have an effect on system use. We conducted a 3-month long study of 87 employees in one business unit in an organization. The results confirmed our theory that social network constructs can significantly enhance our understanding of system use over and above predictors from prior individual-level adoption research.

Employees' underutilization of new information systems undermines organizations' efforts to gain benefits from such systems. The two main predictors of individual-level system use in prior research-behavioral intention and facilitating conditions-have limitations that we discuss. We introduce behavioral expectation as a predictor that addresses some of the key limitations and provides a better understanding of system use. System use is examined in terms of three key conceptualizations: duration, frequency, and intensity. We develop a model that employs behavioral intention, facilitating conditions, and behavioral expectation as predictors of the three conceptualizations of system use. We argue that each of these three determinants play different roles in predicting each of the three conceptualizations of system use. We test the proposed model in the context of a longitudinal field study of 321 users of a new information system. The model explains 65 percent, 60 percent, and 60 percent of the variance in duration, frequency, and intensity of system use respectively. We offer theoretical and practical implications for our findings.

Individual adoption of technology has been studied extensively in the workplace. Far less attention has been paid to adoption of technology in the household. In this paper, we performed the first quantitative test of the recently developed model of adoption of technology in households (MATH). Further, we proposed and tested a theoretical extension of MATH by arguing that key demographic characteristics that vary across different life cycle stages would play moderating roles. Survey responses were collected from 746 U.S. households that had not yet adopted a personal computer. The results showed that the integrated model, including MATH constructs and life cycle characteristics, explained 74 percent of the variance in intention to adopt a PC for home use, a significant increase over baseline MATH that explained 50 percent of the variance. Finally, we compared the importance of various factors across household life cycle stages and gained a more refined understanding of the moderating role of household life cycle stage.

Agency theory has served as a key basis for identifying drivers of offshore information system project success. Consequently, the role of relational factors in driving project success has been overlooked in this literature. In this paper, we address this gap by integrating the social embeddedness perspective and the culture literature to theorize how and why relational factors affect the success of offshore IS projects that are strategic in nature. We identify organizational and interpersonal cultural differences as critical success factors in this context. Using data from a longitudinal field study of 155 offshore IS projects managed by 22 project leaders, we found evidence of a relationship between hypothesized relational factors and two measures of offshore IS project success--namely, project cost overruns and client satisfaction-- over and above the effects of project characteristics and agency factors. Specifically, we found that information exchange, joint problem solving, and trust reduce project cost overruns and improve client satisfaction. We also found a relationship between cultural differences at the organizational and team level, and offshore IS project success. The model explained 40 percent and 41 percent of the variance in project cost overruns and client satisfaction, respectively, for projects with a client representative. For projects with no client representative, the model explained 35 percent and 37 percent of the variance in project cost overruns and client satisfaction, respectively. Collectively, the results have important theoretical and practical implications for how client-- vendor relationships should be managed when partnering with offshore firms and designing offshore IS project teams.

Collaborative technologies are widely used to enable teams to function effectively in today's competitive business environment. However, prior research has been inconclusive regarding the impacts of collaborative technologies on team performance. To address the inconsistencies in prior work, this paper seeks to understand the mediational mechanisms that transmit the effect of collaborative technologies on team performance. Specifically, we theorize that there is a relationship between design features and knowledge contextualization. We further theorize relationships between knowledge contextualization and a team's capability for collaboration, specifically examining collaboration know-how and absorptive capacity, both of which are expected to influence team performance. We conduct a field study including 190 software project teams from a large organization in China. The results support our theoretical model and demonstrate that design features have an impact on performance outcomes, mediated by collaboration know-how and absorptive capacity.