A configurational perspective on design elements and user governance engagement in blockchain platforms
本研究采用模糊集定性比较分析（fsQCA），识别出区块链平台促进用户治理参与的五个关键设计要素，并揭示了三种高生成性参与和一种高评价性参与的理想组态。
Abstract Blockchain technology offers the potential to create an open, decentralised governance structure that empowers stakeholders to participate in decentralised engagement. However, how blockchain platforms configure their design elements to establish and maintain decentralised systems with high levels of user governance engagement requires further research. This study investigates the key design elements of blockchain platforms and their ideal configurations for promoting user governance engagement. Due to the complex and interdependent nature of the design elements, we adopt a configurational perspective accompanied by a fuzzy set qualitative comparative analysis (fsQCA) to uncover complex nonlinear relationships among key conditions that are relevant to decentralised governance. Our research identifies five key design elements that facilitate distributed governance ( Access to decision rights , Process visibility , Protocol automation , Incentives for developers/miners , and Incentives for other stakeholders ) based on existing blockchain governance literature. We analyse 14 unique blockchain platform cases that adopted on‐chain governance. Our fsQCA results reveal three ideal types of blockchain governance configurations that are sufficient for high generative user governance engagement: Centralised incentive model , Impartial incentive model , and Automation‐driven model , whereas achieving high evaluative governance engagement requires the presence of all the design elements ( Comprehensive model ). Also, we found Access to decision rights and Protocol automation are necessary conditions for generative governance engagement, and Access to decision right s together with Process visibility is a combined necessary condition for evaluative governance engagement. Relevant theoretical and practical implications for platform designers as well as methodological implications for applying QCA to emerging IS phenomena are discussed.