边疆
知识管理
数字化转型
人际交往
组织变革
管理科学
社会学
平衡(能力)
组织行为学
数据科学
计算机科学
业务
组织结构
组织发展
数据收集
信息技术
组织研究
颠覆性创新
研究方法
商业模式
组织绩效
数字经济
工程伦理学
测量数据收集
定性性质
公共关系
作者
Ning Li,Wei He,Kai Chi Yam,Helen H. Zhao
标识
DOI:10.1017/mor.2025.10103
摘要
Abstract 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.
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