本研究探討紮根理論在商業模式創新研究中的應用，特別針對事件分析與因果關係建構的挑戰，設計了一套支援商業模式創新研究的質性分析方法與架構。本研究強調事件為主要分析單元，透過訪談資料建構因果關係，以揭示商業模式創新過程中關鍵活動與理論探針的互動機制，並確保研究方法能夠適應不同產業與情境。 本研究方法採用開放編碼與主軸編碼，並整合商業模式創新的關鍵理論，建構一套適用於商業模式創新研究的事件分析架構。該架構不僅有助於識別商業模式創新過程中的關鍵決策點，還能有效捕捉企業在變革過程中的動態調整模式，進一步提升對創新機制的理解。此外，本研究強調事件與理論探針之間的互動，以探索企業如何透過不同策略推動商業模式的演變。 本研究的分析架構為學術界與企業界提供了一套有效的研究工具，不僅有助於學術研究者更精確地建構商業模式創新理論，亦能幫助企業理解創新過程中的關鍵變數，進而發展更具適應性的經營策略。此外，本研究亦對紮根理論的應用進行了延伸，透過質性分析方法的最佳化，使其更適用於動態變革環境，提供研究者更完整的理論構建工具。;This study explores the application of grounded theory in business model innovation research, specifically addressing the challenges of event analysis and causal relationship construction. To support business model innovation studies, this research develops a qualitative analysis framework that emphasizes events as the primary analytical unit. By leveraging interview data, the framework constructs causal relationships to uncover the interactions between key activities and business components, ensuring adaptability across various industries and contexts. This study employs open coding and axial coding, integrating key theories of business model innovation to establish an event-based analytical framework. The proposed framework not only helps identify critical decision points in business model innovation but also effectively captures the dynamic adjustments made by companies during transformation processes, thereby enhancing the understanding of innovation mechanisms. Furthermore, this research emphasizes the interactions between events and business components, exploring how companies drive business model evolution through different strategic approaches. The analytical framework proposed in this study provides a valuable research tool for both academia and industry. It enables researchers to construct business model innovation theories with greater precision, while also helping companies identify key variables in the innovation process to develop more adaptive business strategies. Additionally, this study extends the application of grounded theory by optimizing qualitative analysis methods, making them more suitable for dynamic transformation environments and offering researchers a more comprehensive theoretical construction tool.
