业务
大数据
价值(数学)
服务(商务)
价值创造
中国
控制重构
人道主义后勤
透视图(图形)
共同创造
知识管理
营销
过程管理
产业组织
计算机科学
机器学习
嵌入式系统
人工智能
操作系统
法学
政治学
作者
Qiaohong Pan,Wenping Luo,Yi Fu
标识
DOI:10.1016/j.techsoc.2022.102114
摘要
This study aims to explore the logistics service value creation using big data in the collaboration between logistics service companies and stakeholders. Based on the dynamic capability theory (DCT), this paper constructs a theoretical framework of value creation in logistics collaboration with six big data-driven factors, namely connection, interaction, integration, synergy, reconfiguration, and innovation. The clear set qualitative comparative analysis (csQCA) method examines the value creation paths of logistics service companies in China through combinations of big data-driven elements in collaboration with stakeholders (e.g., suppliers, manufacturers, retailers, and customers). The results show that combinations of six factors driven by big data form three paths to create value for logistics service companies and these factors play unequal roles in improving the value of logistics services. This study provides considerable insight for logistics service managers, practitioners, and scholars that organizations should attach importance to the role of big data for value creation in logistics collaboration.
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