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Open Collaboration for Innovation: Principles and Performance (1406.7541v1)

Published 29 Jun 2014 in cs.CY

Abstract: The principles of open collaboration for innovation (and production), once distinctive to open source software, are now found in many other ventures. Some of these ventures are internet-based: Wikipedia, online forums and communities. Others are off-line: in medicine, science, and everyday life. Such ventures have been affecting traditional firms, and may represent a new organizational form. Despite the impact of such ventures, questions remain about their operating principles and performance. Here we define open collaboration (OC), the underlying set of principles, and propose that it is a robust engine for innovation and production. First, we review multiple OC ventures and identify four defining principles. In all instances, participants create goods and services of economic value, they exchange and reuse each other's work, they labor purposefully with just loose coordination, and they permit anyone to contribute and consume. These principles distinguish OC from other organizational forms, such as firms or cooperatives. Next, we turn to performance. To understand the performance of OC, we develop a computational model, combining innovation theory with recent evidence on human cooperation. We identify and investigate three elements that affect performance: the cooperativeness of participants, the diversity of their needs, and the degree to which the goods are rival (subtractable). Through computational experiments, we find that OC performs well even in seemingly harsh environments: when cooperators are a minority, free riders are present, diversity is lacking, or goods are rival. We conclude that OC is viable and likely to expand into new domains. The findings also inform the discussion on new organizational forms, collaborative and communal.

Citations (214)

Summary

  • The paper presents an agent-based model that reveals open collaboration maintains robust performance even when cooperators are in the minority.
  • It identifies that need heterogeneity and resource rivalry significantly influence collaborative efficiency across various sectors.
  • The study challenges conventional views by demonstrating that participant homogeneity is not essential for achieving innovation success.

Understanding Open Collaboration for Innovation: Principles and Performance

The paper "Open Collaboration for Innovation: Principles and Performance" by Sheen S. Levine and Michael J. Prietula offers an in-depth analysis of open collaboration (OC) as a system of innovation and production. Rooted in the context of open source software, OC has transcended industries and sectors, affecting various domains, including scientific research and commercial enterprises. This paper aims to articulate the principles underpinning OC and evaluate its performance using empirical data and agent-based modeling.

Fundamentals of Open Collaboration

Open collaboration is described as a system marked by goal-oriented yet loosely coordinated participants who contribute to creating a product or service of economic value. Notably, contributions are accessible to both contributors and non-contributors, defining the inclusive and often non-monetary nature of OC. The paper further explores the transition from traditional innovation models to those embracing open, community-based frameworks, such as Peer Production and Wikinomics, which underscore large-scale, decentralized participation.

Factors Influencing Performance

The paper posits several factors influencing the performance of OC, largely revolving around human cooperation, participant heterogeneity, and the nature of goods involved.

Cooperative Behavior

A central tenet of OC is cooperative behavior, where contributors voluntarily share resources without direct compensation. This behavior challenges traditional economic postulations of narrow self-interest, positing a more nuanced understanding of human motivation, characterized by three cooperative types: Cooperators, Reciprocators, and Free Riders. The paper highlights that individual behavioral consistency can predict cooperative outcomes within a group setting.

Need Heterogeneity

The heterogeneity of needs among participants is explored as another determinant of performance. While diverse needs might lead to robust OC performance by dispersing demand across various goods, the paper also acknowledges opposing views where homogenous needs expedite problem-solving. Empirical examination within the paper aims to reconcile these differing claims by assessing their impact on innovation efficiency.

Rivalry of Goods

The rivalry, or subtractability, of goods is analyzed concerning OC’s efficacy. While non-rival goods, such as digital resources, have traditionally been deemed ideal for OC, the paper acknowledges the nuanced reality where even non-rival goods may possess rival aspects if they necessitate effort in distribution. Thus, understanding the rivalry in OC contexts is crucial for evaluating collaborative project success.

Empirical Insights and Results

Levine and Prietula employ an agent-based model to synthesize the interaction of cooperation, need heterogeneity, and rivalry, articulating several noteworthy results:

  • OC maintains robust performance even in challenging environments where cooperators are a minority.
  • The necessity of participant homogeneity in immediate benefits is debunked.
  • OC efficiency persists amidst rival resources or non-diverse needs, albeit challenges arise when both conditions are coupled.

These findings underscore that many assumptions about necessary conditions for effective OC may not be as stringent as traditionally thought. The model elucidates the disparity in contributions within OC settings and highlights the potential for OC to proliferate across various fields.

Implications and Future Directions

From a practical standpoint, the research implies vast implications for organizational strategy, as entities might increasingly harness OC mechanics across multifarious industries. Theoretically, it augments the dialogue on organizational forms, suggesting a shift towards more collaborative and communal structures that leverage loosely coordinated human efforts. As the trajectory of OC continues to evolve, embracing diverse participant compositions and understanding goods rivalry will be essential for future research in this domain, potentially fostering untapped innovation trajectories across sectors.

This paper contributes substantially to the understanding of open collaboration by providing a nuanced exploration of its principles and efficacies, offering a template for anticipating future trends and challenges in the collaborative innovation landscape.