Selfish Cooperation & Altruistic Competition
Description
We provide files needed to reproduce the results from the paper “Selfish Cooperation & Altruistic Competition: Impacts of Multi-motivated Coopetition in Community Development.” Cooperation is a fundamental assumption and condition of community development programs. However, like other cooperative relationships, sometimes community development programs may incorporate competition because communities participating in the program would find themselves (formally or informally) comparing to (and also trying to excel) other communities. What makes community development more complicated is the various motivations behind coopetition behaviors—selfishness and altruism. With this in mind, the research question we pursue is: how the combinations of multiple motivations and coopetition behaviors are associated with the community development performances. To answer the question, this study examined a CDD (community-driven development) case implemented by the Korea International Cooperation Agency and the Myanmar Ministry of Agriculture, Livestock and Irrigation where the CDD leaders of 100 villages were surveyed and interviewed. The analyses present some common patterns of the association between coopetition type and CDD performances, and there are two major findings. First, “selfish cooperation” is likely to associate with the worse CDD performances (than “selfish competition” and “altruistic competition”). The second major finding is that “altruistic cooperation” works best for CDD performance. Such findings may suggest that not only win-win “action” but also win-win “mentality” is crucial to CDD outcomes, because the genuinely motivated cooperation may lead to (1) internal alignment through a shared vision within the villages, and (2) trust and reciprocal support from other villages. We conclude with the synergic combinations of motivation and behavior for the constructive coopetition in community development.
Files
Steps to reproduce
Please, see the Readme file in the Dataset for replication.