The digital transformation of Chinese companies offers a new frontier for organizational research. Widespread use of workplace platforms creates rich archives of unobtrusive data, providing continuous, real-time insights into organizational life that traditional surveys cannot capture. The central challenge for scholars is turning this data abundance into meaningful theory. This special issue highlights three studies that meet this challenge by using innovative methods to convert granular data into valuable knowledge. The papers employ digital-context experiments, real-time behavioral tracking, and machine-learning-assisted theory building to study phenomena from interpersonal dynamics to crisis productivity. Looking ahead, we explore the potential of unstructured multimodal data and new AI tools to make complex analysis more accessible. We conclude with a research agenda calling for methodological rigor, interdisciplinary collaboration, and a firm balance between technological innovation and theoretical depth.
