Survival of Open-Source Projects: A Population Ecology Perspective

In the last few years, open source (OS) software development has become a viable alternative to commercial software. OS developers form virtual teams and the goal of this study is to examine the viability of the projects as organizational forms. We draw from the population ecology literature and propose that such factors as project reliability, size, age, and niche focus will be related to the survival of OS projects. Specifically, the purpose of this research is to test the applicability of some basic theorems of population ecology to open source projects. In this research we focus on short-term survival of OS projects. If the population ecology paradigm is useful, we can expand our analyses. The study uses archival project data available at SourceForge to test the theoretical propositions

Why Should I Provide Social Support? A Social Capital Perspective of Individual Helping Behavior in Healthcare Virtual Support Communities

The phenomenon of online social support has been studied for years. However, little is known about the factors that drive individual online helping behavior. While the Information systems literature provides rich insights into the determinants of online social support, the emphasis has been exclusively on the provision of informational help. By contending the need to expand our investigation to different types of support, this paper studies individual provisions of both informational and emotional social support in healthcare virtual support communities (HVSCs). Drawing on social capital theory, the structural, relational, and cognitive dimensions of social capital are conceptualized as the social support determinants. The results show that the social capital dimensions can be both facilitators and inhibitors of the two types of social support. This study can contribute not only to the literature on HVSCs, but also to studies of other types of virtual communities such as electronic networks of practice

Applying the Transtheoretical Model of Behavior Change to Online Self-Disclosure

End users’ behaviors that compromise security and privacy put both individuals and organizations at risk. In this study, we focus on online self-disclosure and propose a staged model that describes how individuals can move towards reduced online self-disclosure. We recognize that information privacy and security behavior is a dynamic process that unfolds over time, making stage theories applicable. Specifically, we apply the transtheoretical model (TTM) of behavior change, which has been widely used in the public health domain to change high risk behaviors, such as smoking as well as behaviors related to physical security, such as seat belt use. We also consider the mechanisms of changing behavior in the context of online self-disclosure and propose various hypotheses about the dynamic impacts of the mechanisms based on the stage an individual is in. Our proposed model can be used to develop stage-based interventions to promote safer behaviors regarding online self-disclosure

Investigating Insensitivity to Prior Probabilities in Merger and Acquisition (M&A) Decision Making

In this paper we investigate the high failure rates of Mergers and Acquisitions (M&As) over the last several decades, despite greater access to data, sophisticated business intelligence (BI) and data analytics (DA) tools, and work by industry professionals and academics to improve outcomes. We explore the possibility that the representativeness heuristic could play a role, and specifically, if prior probabilities are being ignored or discounted in M&A evaluations. We confirm our hypothesis using a regression discontinuity in time (RDiT) model and a two-way fixed effects model. By highlighting the negative consequences of this heuristic on management decisions, we promote the use of data-driven decision making and the role of analytics in formulating business strategy

Received Support, Perceived Support, and Social Support Observation and Provision in Virtual Communities

While the concept of online social support, and its sources and outcomes, have been studied extensively in the IS literature, there is some conceptual ambiguity about the two aspects of social support – social support that is actually received from partners (received support) and the psychological belief of the availability of supportive others (perceived support). Additionally, the literature on online social support has largely neglected the effects of observing other people’s social support exchange (support observation) on the attitude and behavior of the self. Drawing on social support research and social exchange theory, this study proposes a model that integrates these related social support concepts – perceived support, received support, support observation, and social support provision, and examines their inter-relationships to clarify these ambiguities. Through analyzing the structural model and social support exchange networks, our goal is to expand the IS literature on, and improve our understanding about, online social support

Supporters in Deed – Studying Online Support Provision from the Perspective of Social Capital

The phenomenon of social support – aid and assistance exchanged through social relationships and interpersonal transactions – has been studied for decades with a focus on discovering the mechanism that lies between support exchange and personal well-being. In the age of the Internet, researchers also have shifted their focus to online support exchange. However, little attention has been paid to conceptualizing the determinants of support provision in virtual support communities. Drawing from social capital theory, this study attempts to bridge this gap by presenting a model that applies the structural, relational, and cognitive dimensions of social capital to theorize the determinants of the provision of informational and emotional support in virtual support communities. Through the use of social network analysis and machine learning techniques, messages from a virtual support community for women with breast cancer are analyzed. The analysis results are used for empirically testing the framework modeling support provision