Identifying factors and configurations influencing the effectiveness of government data openness in China based on fsQCA

Abstract

Engaging government data openness is of great significance to economic development and social services. As the government data openness process continues to deepen in China, it is worth studying the factors that affect government data openness and the development paths leading to the high performance of data opening. Based on the Technology-Organization-Environment (TOE) theory, this paper proposes a government data open analysis framework including five condition variables (i.e., data support, technical support, government support, economic development, and social development). Using Fuzzy-set Qualitative Comparative Analysis (fsQCA) to analyze data from 25 provincial governments, we discover the key influencing factors and configurations leading to high-level and non-high-level data openness. Experimental results show that a single factor does not determine the level of government data opening. Instead, it is jointly affected by multiple factors in technology, organization, and environment. Three configuration paths are found in developing China’s provincial government data openness, including technology-environment-driven, technology-organization-environment-driven, and technology-organization-driven modes. The analysis results of this paper provide inspiration and suggestions for provincial governments to improve the level of government data opening according to local characteristics.