Abstract
The social relationships between development agencies, non-governmental organizations, private companies, and other groups working on development projects play an important role in the overall success of projects. However, traditional project selection and prioritization processes ignore the organizational relationships. This paper proposes to integrate social network analysis into multi-criteria decision-making processes to enhance the effectiveness of project selection. A set of topological metrics of social network are used to quantitatively measure the organizational relationships and integrated into the analytic network process (ANP) to form a multi-criteria ANP project selection model. Utilizing empirical social network data of a water and food security research for development network in the Mekong River Basin, we investigate the effectiveness of the proposed model. The results show that it will offer companies, government agencies, and other donor organizations the opportunity to prioritize strategic network goals simultaneously with research and development priorities, and help companies and research organizations to increase their impact and reach within networks.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 5128-5138 |
| Number of pages | 11 |
| Journal | Expert Systems With Applications |
| Volume | 42 |
| Issue number | 12 |
| DOIs | |
| State | Published - Jul 15 2015 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 2 Zero Hunger
All Science Journal Classification (ASJC) codes
- General Engineering
- Computer Science Applications
- Artificial Intelligence
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