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Since its inception, the software industry has been in crisis. As Blazer noted 20 years ago, "[Software] is unreliable, delivered late, unresponsive to change, inefficient, and expensive … and has been for the past 20 years" [4]. In a survey of software contractors and government contract officers, over half of the respondents believed that calendar overruns, cost overruns, code that required in-house modifications before being usable, and code that was difficult to modify were common problems in the software projects they supervised [22]. Even today, problems with software systems are common and highly-publicized occurrences.

104 S's of apparently Italian descent in New Haven who were registered voters were interviewed by 8 experimenters. They were asked to give their preference among a number of real & imagined candidates seeking political office. The purpose was to determine whether preelection interviewing stimulates voting among the least stimulated voters. The results show that being interviewed in a PO survey does increase the probability that the R would vote in the following election. 1 Table. S. Karganovic.

This book seeks to establish an interdisciplinary, applied social scientific model for researchers and students that advocates a cooperative effort between machines and people. After showing that basic research on social processes offers much needed guidance for those creating technology and designing tools for group work, its papers demonstrate the mutual relevance of social science and information system design, and encourage better integration of these disciplines. This comprehensive collection closely examines the variety of electronic tools being deployed to solve traditional problems in

Addresses questions that relate to how people use computers, cell phones, and the internet, how they integrate their use of new technology into daily routines, and how family function, social relationships, education, and socialization are changing as a result. This book is intended for professionals and students in human-technology interaction

Objective: The objective of the paper is to understand leadership in an online community, specifically, Wikipedia. Background: Wikipedia successfully aggregates millions of volunteers' efforts to create the largest encyclopedia in human history. Without formal employment contracts and monetary incentives, one significant question for Wikipedia is how it organizes individual members with differing goals, experience, and commitment to achieve a collective outcome. Rather than focusing on the role of the small set of people occupying a core leadership position, we propose a shared leadership model to explain the leadership in Wikipedia. Members mutually influence one another by exercising leadership behaviors, including rewarding, regulating, directing, and socializing one another. Method: We conducted a two-phase study to investigate how distinct types of leadership behaviors (transactional, aversive, directive, and person-focused), the legitimacy of the people who deliver the leadership, and the experience of the people who receive the leadership influence the effectiveness of shared leadership in Wikipedia. Results: Our results highlight the importance of shared leadership in Wikipedia and identify trade-offs in the effectiveness of different types of leadership behaviors. Aversive and directive leadership increased contribution to the focal task, whereas transactional and person-focused leadership increased general motivation. We also found important differences in how newcomers and experienced members responded to leadership behaviors from peers. Application: These findings extend shared leadership theories, contribute new insight into the important underlying mechanisms in Wikipedia, and have implications for practitioners who wish to design more effective and successful online communities.

While prior research has found that familiarity is beneficial to team performance, it is not clear whether different kinds of familiarity are more or less beneficial when the work has different types of complexity. In this paper, we theorize how task and team familiarity interact with task and team coordination complexity to influence team performance. We posit that task familiarity is more beneficial with more complex tasks (i.e., tasks that are larger or with more complex structures) and that team familiarity is more beneficial when team coordination is more difficult (i.e., for larger or geographically dispersed teams). Finally, we propose that the effects of task familiarity and team familiarity on team performance are complementary. Based on a field study of geographically distributed software teams, two of our hypotheses are disconfirmed: Our results show that the beneficial effects of task familiarity decline when tasks are more structurally complex and are independent of task size. Conversely, the hypotheses for team familiarity are confirmed as the benefit of team familiarity for team performance is enhanced when team coordination is more challenging—i.e., when teams are larger or geographically dispersed. Finally, surprisingly, we find that task and team familiarity are more substitutive than complementary in their joint effects on team performance: Task familiarity improves team performance more strongly when team familiarity is weak and vice versa. Our study contributes by revealing how different types of familiarity can enhance team performance in a real-world setting where the task and its coordination can be highly complex.

This natural experiment investigates the introduction and use of a pair of competing video telephone systems in a company over a period of 18 months. Both quantitative, time-series analyses and in-depth interviews demonstrate that employees adopted and used the video systems for both utility and normative reasons. Consistent with utility explanations, people in the most communication-intensive jobs were the most likely to use video telephony. Consistent with social influence explanations, people used a particular system more when more people in general were using it and when more people in their work group were using it. There were two conceptually distinct, but empirically entangled, types of social influence. First, use by other people changed the objective benefits and costs associated with using the systems, and thus their utility. Second, use by others changed the normative environment surrounding the new technology. Both utility and normative influences were stronger in one's primary work group. Implementers, users, and researchers should consider both utility and normative factors influencing both the success and failure of new organizational communication systems.