How to promote the participation of enterprises using open government data? Evolutionary game analysis by applying dynamic measures

Abstract

As the development of smart cities, driven by emerging technologies, enters a new phase, the focus shifts towards sustaining operations rather than building new infrastructures. In the era of big data, one crucial factor for the sustainability of smart cities is the innovation and economic value generated through open government data (OGD). Local governments often adopt incentive policies to encourage participation, recognizing that most emerging technologies are driven by innovation and promotion from enterprises. This raises a fundamental question: how do the strategies of local governments and enterprises interact in the context of open government data development? In this study, we have developed an approach based on evolutionary game theory to examine the interactions of OGD participants, such as local governments and enterprises, in shaping their long-term decisions. Specifically, we have explored the effectiveness and efficiency of combinations involving hybrid subsidies and data access fees by simulating Evolutionarily Stable Strategies (ESS) based on empirical cases from enterprises. Our findings indicate that dual dynamic measures are more effective and efficient in encouraging stakeholder participation in open government data initiatives over the long term. The results underscore the preference for flexible policies over rigid ones and highlight the critical role of positive interactions between enterprises and local governments in fostering the sustainable operation of OGD.