Reputation, trust, and norms as mechanisms leading to academic reciprocity in data sharing: An empirical test of theory of collective action

Abstract

ABSTRACTThis research investigated how scientists' academic reputation, community trust, and norms regarding data sharing all influence their academic reciprocity in data sharing, which eventually leads to the scientists' data sharing intentions. This research employed Ostrom's (2003) theory of collective action to better understand scientists' data sharing behaviors from the perspective of cooperation in a community. This research empirically evaluated the research model and related hypotheses by using the Structural Equation Modeling (SEM) method on a total of 456 survey responses from biologists in the U.S. The results suggest that biologists' perceived academic reputation significantly increases their perceived community trust, norm of data sharing, and academic reciprocity. Along with perceived academic reputation, both perceived community trust and norms of data sharing also significantly increases biologists' academic reciprocity in data sharing. This research also found that biologists' academic reciprocity and norms of data sharing significantly affect their data sharing intentions. The results of this research show that the theory of collective action provides new insight to scientists' data sharing behaviors. These results suggest how we can facilitate scientists' data sharing behaviors within a research community by increasing academic reciprocity through the mechanisms of reputation, trust, and norm.