Lessons Learned from Applying Social Network Analysis on an Industrial Free/Libre/Open Source Software Ecosystem

TL;DR

This study investigates collaboration patterns in the OpenStack open source ecosystem, revealing that rivalry and diverse actor types do not hinder cooperation, and providing insights into social structures and business models in high-networked software communities.

Contribution

It applies a multi-method approach combining qualitative analysis, mining software repositories, and social network analysis to explore collaboration dynamics among competing firms in an open source ecosystem.

Findings

Competition for revenue models does not prevent collaboration.

Homophily among developers from the same firm was not observed.

Heterogeneous actors jointly develop complex infrastructure for big data.

Abstract

Many software projects are no longer done in-house by a single organization. Instead, we are in a new age where software is developed by a networked community of individuals and organizations, which base their relations to each other on mutual interest. Paradoxically, recent research suggests that software development can actually be jointly-developed by rival firms. For instance, it is known that the mobile-device makers Apple and Samsung kept collaborating in open source projects while running expensive patent wars in the court. Taking a case study approach, we explore how rival firms collaborate in the open source arena by employing a multi-method approach that combines qualitative analysis of archival data (QA) with mining software repositories (MSR) and Social Network Analysis (SNA). While exploring collaborative processes within the OpenStack ecosystem, our research contributes to Software Engineering research by exploring the role of groups, sub-communities and business models within a high-networked open source ecosystem. Surprising results point out that competition for the same revenue model (i.e., operating conflicting business models) does not necessary affect collaboration within the ecosystem. Moreover, while detecting the different sub-communities of the OpenStack community, we found out that the expected social tendency of developers to work with developers from same firm (i.e., homophily) did not hold within the OpenStack ecosystem. Furthermore, while addressing a novel, complex and unexplored open source case, this research also contributes to the management literature in coopetition strategy and high-tech entrepreneurship with a rich description on how heterogeneous actors within a high-networked ecosystem (involving individuals, startups, established firms and public organizations) joint-develop a complex infrastructure for big-data in the open source arena.