Factors influencing authors’ intention to continue publishing in data journals: a cross-sectional survey

Purpose: This study investigated the factors influencing data paper authors’ continuance intention to publish in data journals, drawing on the post-acceptance model and the unified theory of acceptance and use of technology. Based on these theoretical frameworks, four factors—perceived usefulness, satisfaction, effort expectancy, and social influence—were hypothesized to be associated with authors’ continuance intention. Methods: A cross-sectional survey was conducted using an online questionnaire distributed to authors who had published in eight data journals where data papers constituted more than 20% of all publications. In total, 453 responses were collected, resulting in a 6.2% response rate. Ordered logistic regression analysis was employed to identify significant influencing factors. Results: The ordered logistic regression analysis indicated that satisfaction and perceived usefulness were positively associated with authors’ continuance intention, while effort expectancy was negatively associated. Among these, satisfaction with a data journal exerted the strongest influence on continuance intention. Conclusion: These findings underscore the importance for data journal publishers to actively manage authors’ satisfaction throughout the submission and peer review processes. The identification of perceived usefulness as another significant factor suggests that funders and academic institutions should incentivize authors to publish in data journals. Authors who perceived that publishing in a data journal required excessive time were less likely to intend to publish there again. Training in research data management best practices, provided by academic libraries, may help reduce the time burden associated with data preparation and sharing.