Reputation, trust, and norms as mechanisms forming academic reciprocity in data sharing: an empirical test of theory of collective action

Purpose This research investigated how biological scientists' perceived academic reputation, community trust, and norms all influence their perceived academic reciprocity, which eventually leads to their data sharing intentions. Design/methodology/approach A research model was developed based on the theory of collective action, and the research model was empirically evaluated by using the Structural Equation Modeling method based on a total of 649 survey responses. Findings The results suggest that perceived academic reputation significantly increases perceived community trust, norm of data sharing, and academic reciprocity. Also, both perceived community trust and norm of data sharing significantly increases biological scientists' perceived academic reciprocity, which significantly affect their data sharing intentions. In addition, both perceived community trust and norm of data sharing significantly affect the relationship between perceived academic reciprocity and data sharing intention. Research limitations/implications This research shows that the theory of collective action provides a new theoretical lens for understanding scientists' data sharing behaviors based on the mechanisms of reputation, trust, norm, and reciprocity within a research community. Practical implications This research offers several practical implications for facilitating scientists' data sharing behaviors within a research community by increasing scientists' perceived academic reciprocity through the mechanisms of reputation, trust, and norm of data sharing. Originality/value The collective action perspective in data sharing has been newly proposed in this research; the research sheds light on how scientists' perceived academic reciprocity and data sharing intention can be encouraged by building trust, reputation, and norm in a research community.