Can e-government online services offer enhanced governance support? A national-level analysis based on fsQCA and NCA - Yuanyuan Chen; Zhipeng Chen (Journal of Innovation & Knowledge (JIK), 2024)
Government online services are often considered a core component of e-government, generating significant interest not only among practitioners and scholars but also among policymakers because of their crucial role in enhancing a country's governance capacity. This study, which is based on the United Nations E-Government Survey's Online Service Index, the World Bank's Worldwide Governance Indicators, and the Global Innovation Index, investigates how e-government online services' technology, institutional frameworks, content provision, e-participation, and service provision, as well as innovation, enhance the national governance capacity and offer governance support. The research uses principal component analysis (PCA) for data preprocessing and combines necessary condition analysis (NCA) with fuzzy set qualitative comparative analysis (fsQCA) to provide empirical evidence. The study confirms the critical role of the aforementioned factors in boosting governance capacity and offers three mutually nonexclusive solution types that enhance governance support. These solutions support governance by improving the closeness of interactions between the government and the public, the potential for public participation in governance, and the government's own influence. Additionally, the study reveals that innovation can enhance the impact of e-government online services on national governance capacity, thereby providing a more comprehensive perspective on how e-government online services influence national governance. This study advances our understanding of how e-government enhances a nation's governance capability and offers supplementary insights into the fields of interdisciplinary innovation research and mixed-methods research.
Keywords: O30; L86; 650; E-government; Qualitative comparative analysis (QCA); Necessary condition analysis (NCA); Principal component analysis (PCA)