Extending the technology readiness and acceptance model to research data sharing in biomedical sciences

Purpose This study aims to examine biomedical scientists’ intentions to share research data by drawing on the technology readiness and acceptance model (TRAM). This study conceptualizes data sharing as a technology-mediated research practice and investigates how task-specific perceptions of data sharing influence acceptance beliefs, which in turn affect data sharing intention. Design/methodology/approach Using survey data from 530 biomedical scientists in the Republic of Korea, structural equation modeling was used to examine the model of biomedical scientists’ data sharing intentions. Findings The results indicate that task-specific perceptions of data sharing influence perceived usefulness and ease of use in distinct ways. Perceived academic benefit, innovation and effort influence perceived usefulness, while perceived innovation and effort influence perceived ease of use, both of which drive data sharing intention. Research limitations/implications This research advances theory by demonstrating that biomedical scientists’ data sharing intentions are formed through the structured interplay between task-specific perceptions and technology acceptance beliefs. Practical implications This research highlights the importance of simultaneously strengthening perceived values of data sharing and minimizing operational complexity to facilitate data sharing behavior. Originality/value This research contributes to the literature by integrating TRAM-informed task-specific perceptions to explain biomedical scientists’ data sharing intentions, highlighting how task-specific perceptions systematically translate into acceptance beliefs and behavioral intentions. While prior research on biomedical scientists’ data sharing has examined relevant factors largely as individual predictors, this study integrates these factors within the TRAM-informed framework and examines their structural relationships in the context of data sharing.