Network Effects: The Influence of Structural Capital on Open Source Project Success

Singh, Param Vir; Tan, Yong; Mookerjee, Vijay

doi:10.2307/41409962

Cited by 141 publications

(108 citation statements)

References 50 publications

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“…Our findings show that experience diversity, participant independence, and network decentralization are all positively related to crowd performance, which are consistent with the theory of crowd wisdom. Our study particularly shows the benefit of decentralization, which was neglected in prior research related to crowd network (Deschamps, ; Singh et al, ; Temizkan & Kumar, ; Wu et al, ; Zhang & Wang, ) for crowd performance. What is missing from the crowd wisdom theory is the consideration of the moderating effect of crowd size.…”

Section: Conclusion and Discussionmentioning

confidence: 73%

Crowd characteristics and crowd wisdom: Evidence from an online investment community

Hong

et al. 2019

Asso for Info Science & Tech

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Fueled by the explosive growth of Web 2.0 and social media, online investment communities have become a popular venue for individual investors to interact with each other. Investor opinions extracted from online investment communities capture “crowd wisdom” and have begun to play an important role in financial markets. Existing research confirms the importance of crowd wisdom in stock predictions, but fails to investigate factors influencing crowd performance (that is, crowd prediction accuracy). In order to help improve crowd performance, our research strives to investigate the impact of crowd characteristics on crowd performance. We conduct an empirical study using a large data set collected from a popular online investment community, StockTwits. Our findings show that experience diversity, participant independence, and network decentralization are all positively related to crowd performance. Furthermore, crowd size moderates the influence of crowd characteristics on crowd performance. From a theoretical perspective, our work enriches extant literature by empirically testing the relationship between crowd characteristics and crowd performance. From a practical perspective, our findings help investors better evaluate social sensors embedded in user‐generated stock predictions, based upon which they can make better investment decisions.

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Section: Conclusion and Discussionmentioning

confidence: 73%

Crowd characteristics and crowd wisdom: Evidence from an online investment community

Hong

et al. 2019

Asso for Info Science & Tech

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“…A final group of studies, (8), addressed a wide range of miscellaneous problems, from the effects of social cohesion on the outcomes of open source software development projects (Singh et al . ), to the effects of social relationships on the value creation of firms (Molina‐Morales and Martinez‐Fernandez ), to the moderating effects of low absorptive capacity in accentuating the negative effects of SC on the IPO value of firms (Xiong and Bharadwaj ), among other topics. Each of the first seven topic categories contains multiple studies, spanning a diverse range of contexts and/or employing varying methods of data collection and analysis, whereas, with the notable exception of the two studies examining the impact of SC on the relative career progression of women and men (Grugulis and Stoyanova ; Lutter ), the topics addressed by the work summarized within the miscellaneous category comprise a series of standalone studies.…”

Section: Reviewing the Negative Effectsmentioning

confidence: 99%

The Negative Effects of Social Capital in Organizations: A Review and Extension

Pillai

Hodgkinson

Kalyanaram

et al. 2015

Int J Management Reviews

132

100

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Numerous studies have examined the positive effects of social capital in organizations, whereas the possible negative effects have attracted considerably less scholarly attention. To rectify this imbalance, this paper first undertakes a rigorous review of the published scholarly empirical evidence pertaining to the negative effects of social capital in organizations through a search of Web of Knowledge and Scopus, and then enumerates six potentially negative effects arising from increased levels of social capital. The review focuses on negative effects arising from bonding social capital and those arising from dense networks and closure, advancing new theory to elucidate the generative mechanisms that give rise to the proposed negative effects. Finally, the authors identify potential moderators of the negative effects thus theorized. Using the lens of social identification theory, the authors argue that dysfunctional identification processes restrict the processing of information and stimulate over-commitment to established relationships, diluting in turn the dialectical process, and inhibiting individual learning within organizations, culminating in groupthink, the postponement of structural adjustments, the non-rational escalation of commitment, and the blurring of firms' boundaries. This review thus furthers the agenda of a more balanced inquiry into the effects of social capital in organizations.

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“…The number of code commits is an objective measure of project performance enacted by the key social actors (development teams) with respect to the main technical element (software code) of an OSS project. It has been repeatedly used by prior studies regarding effects of social processes on technical success of OSS projects [10], [62], [63]. These studies indicate that the number of code commits is particularly suited for an examination of both social and technical factors in OSS development.…”

Section: B Construct Operationalization 1) Collaboration Network Strmentioning

confidence: 96%

“…Prior research on OSS development has employed various OSS project performance measures such as OSS developers' perceived project success [58], developer' decisions in joining an OSS project team [5], [11], [59], the percentage of resolved bugs [12], increase in lines of code (LoC) [60], promotion to higher ranks in an OSS project [3], the number of subscribers associated with a project [61], the percentage of closed change requests [4], and number of code commits [10], [62], [63].…”

Section: B Construct Operationalization 1) Collaboration Network Strmentioning

confidence: 99%

Joint Effect of Team Structure and Software Architecture in Open Source Software Development

Nan

Kumar

2013

IEEE Trans. Eng. Manage.

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In this study, we seek to understand socio-technical interactions in a system development context via an examination of the joint effect of developer team structure and open source software (OSS) architecture on OSS development performance. Using detailed data collected from code repositories from SoureForge.com, we find that developer team structure and software architecture significantly moderate each other's effect on OSS development performance. Larger teams tend to produce more favorable project performance when the project being developed has a high level of structural interdependency while projects with a low level of structural interdependency require smaller teams in order to achieve better project performance. Meanwhile, centralized teams tend to have a positive impact on project performance when the OSS project has a high level of structural interdependency. However, when a project has a low level of structural interdependency, centralized teams can impair project performance. This study extends our understanding of information technology's deep engagement in organizational life and provides directions for open source practitioners to better organize their projects to achieve greater performance.Index Terms-Collaboration network, open source software, social network analysis, software architecture, software project performance.

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Network Effects: The Influence of Structural Capital on Open Source Project Success

Cited by 141 publications

References 50 publications

Crowd characteristics and crowd wisdom: Evidence from an online investment community

Crowd characteristics and crowd wisdom: Evidence from an online investment community

The Negative Effects of Social Capital in Organizations: A Review and Extension

Joint Effect of Team Structure and Software Architecture in Open Source Software Development

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