Defining decision making strategies in software ecosystem governance
Research output: Book/Report › Report › Research
Documents
- Decision-Making
Final published version, 198 KB, PDF document
Making the right decisions is an essential part of software ecosystem governance. Decisions related to the governance of a software ecosystem can influence the health of the ecosystem and can result in fostering the success or greatly contributing to the failure of the ecosystem. However, very few studies touch upon the decision making of software ecosystem governance. In this paper, we propose decomposing software ecosystem governance into three activities: input or data collection, decision making, and applying actions.
We focus on the decision making activity of software ecosystem governance and review related literature consisted of software ecosystem governance, organizational decision making, and IT governance. Based on the identified studies, we propose a framework for defining the decision making strategies in the governance of software ecosystems. We identify five decision areas for software ecosystem governance and four archetypes describing the way decisions are taken for each decision area. We explain this matrix-based framework by providing examples from existing software ecosystems.
We focus on the decision making activity of software ecosystem governance and review related literature consisted of software ecosystem governance, organizational decision making, and IT governance. Based on the identified studies, we propose a framework for defining the decision making strategies in the governance of software ecosystems. We identify five decision areas for software ecosystem governance and four archetypes describing the way decisions are taken for each decision area. We explain this matrix-based framework by providing examples from existing software ecosystems.
Original language | English |
---|
Publisher | Department of Computer Science, University of Copenhagen |
---|---|
Edition | 01 |
Number of pages | 6 |
Publication status | Published - 2015 |
Series | Koebenhavns Universitet. Datalogisk Institut. Rapport |
---|---|
Volume | 2015/01 |
ISSN | 0107-8283 |
Links
- https://www.diku.dk/forskning/Publikationer/tekniske_rapporter/2015/Decision-Making.pdf
Final published version
Number of downloads are based on statistics from Google Scholar and www.ku.dk
No data available
ID: 168290720