Does the Starting Point Matter? The Literature‐Driven and the Phenomenon‐Driven Approaches of Using Corporate Archival Data in Academic Research
从实用角度出发，基于学者与企业建立数据访问关系的经验，提出与文献驱动方法并行的现象驱动方法，指导研究者利用企业档案数据进行探索性和扎根理论开发。
Despite recent and perhaps myopic criticisms of archival data with regard to supporting causal theoretical claims, it would be folly to disregard the exploratory and grounded theory development potential that these substantial, rich, and timely archives hold. The question then becomes one of how academics might tap into such archives. This paper considers this issue from a pragmatic perspective, drawing on the experiences of various academics with extensive experience in constructing data‐access relationships with industry. With the support of scholars who published their work using corporate archival data in leading academic journals, we suggest a phenomenon‐driven approach paralleled with the traditional literature‐driven approach in academic studies. This paper highlights best practices, pitfalls, and future opportunities, with the aim of serving as a guide for intrepid scholars interested in capitalizing on contemporary big data initiatives supported at many firms.