Reference Hub19
Adoption, Improvement, and Disruption: Predicting the Impact of Open Source Applications in Enterprise Software Markets

Adoption, Improvement, and Disruption: Predicting the Impact of Open Source Applications in Enterprise Software Markets

Michael Brydon, Aidan R. Vining
Copyright: © 2008 |Volume: 19 |Issue: 2 |Pages: 22
ISSN: 1063-8016|EISSN: 1533-8010|ISSN: 1063-8016|EISBN13: 9781615200429|EISSN: 1533-8010|DOI: 10.4018/jdm.2008040104
Cite Article Cite Article

MLA

Brydon, Michael, and Aidan R. Vining . "Adoption, Improvement, and Disruption: Predicting the Impact of Open Source Applications in Enterprise Software Markets." JDM vol.19, no.2 2008: pp.73-94. http://doi.org/10.4018/jdm.2008040104

APA

Brydon, M. & Vining , A. R. (2008). Adoption, Improvement, and Disruption: Predicting the Impact of Open Source Applications in Enterprise Software Markets. Journal of Database Management (JDM), 19(2), 73-94. http://doi.org/10.4018/jdm.2008040104

Chicago

Brydon, Michael, and Aidan R. Vining . "Adoption, Improvement, and Disruption: Predicting the Impact of Open Source Applications in Enterprise Software Markets," Journal of Database Management (JDM) 19, no.2: 73-94. http://doi.org/10.4018/jdm.2008040104

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

This article develops a model of open source disruption in enterprise software markets. It addresses the question: Is free and open source software (FOSS) likely to disrupt markets for commercial enterprise software? The conventional wisdom is that open source provision works best for low-level system-oriented technologies, while large, complex enterprise business applications are best served by commercial software vendors. The authors challenge the conventional wisdom by developing a two-stage model of open source disruption in enterprise software markets that emphasizes a virtuous cycle of adoption and lead-user improvement of the software. The two stages are an initial incubation stage (the I-Stage) and a subsequent snowball stage (the S-Stage). Case studies of several FOSS projects demonstrate the model’s ex post predictive value. The authors then apply the model to SugarCRM, an emerging open source CRM application, to make ex ante predictions regarding its potential to disrupt commercial CRM incumbents.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.