摘要
面对日益增多的突发事件,提升物流服务供应链的应急能力成为增强产业链韧性的重要举措。数字技术被视为突破应急能力提升瓶颈的关键引擎,然而其赋能机理与实现路径仍缺乏系统深入的探究。为弥补现有研究局限,首先厘清数字技术影响物流服务供应链应急能力提升的多维度赋能机理:第一,基于数字基础设施建设,数字技术赋能应急物流实现效率变革;第二,基于“情景—应对”运作模式,数字技术赋能应急物流实现能力重构;第三,基于数字信任底座,数字技术赋能应急物流实现生态协同。在此基础上,提出数字技术赋能物流服务供应链应急能力提升的实现路径,具体包括三个阶段:构建“数据为基、创新引领”的智慧应急决策支持系统,规范“场景适配、智能优化”的应急物流标准处置流程,以及打造“联动支撑、平急结合”的应急物流生态协同体系。
Facing the escalating frequency of emergencies,enhancing the emergency capability of logistics service supply chains has become an important measure to strengthen the resilience of industrial chains.Digital technologies are recognized as pivotal engines to break through the bottlenecks in improving the emergency capability of the logistics industry.However,the mechanisms and pathways for the empowerment remain underexplored.To address existing research gaps of digital technologies in enhancing emergency capabilities of logistics service supply chains,this study begins with the multi-dimensional empowerment mechanisms,that is,the empowerment of efficiency transformation based on the construction of digital infrastructure,the empowerment of capability reconfiguration built upon the“scenario-response”operational mode and the empowerment of ecological collaboration grounded in a foundation of digital trust.In light of this framework,a three-stage implementation pathway is proposed,which includes constructing an intelligent emergency decision support system that is“data-driven and innovation-led”,standardizing an emergency logistics process that is“scenario-adaptive and intelligently optimized”and developing an emergency logistics ecosystem that is“collaboratively supported and integrated for both normal and emergency operations”.
作者
王迪
WANG Di(Shanxi University of Finance and Economics,Taiyuan,Shanxi 030006,China)
出处
《物流技术》
2025年第5期61-72,共12页
Logistics Technology
基金
国家自然科学基金青年项目“考虑供需扰动和数字技术赋能的物流服务供应链应急运作决策研究”(72301164)
山西省高等学校青年学术带头人项目“基于大数据治理的物流服务供应链应急能力提升研究”(2024Q019)
山西省哲学社会科学规划青年项目“科技创新引领山西应急物流能力提升的作用机理与实现路径研究”(2024QN081)。
关键词
物流服务供应链
应急能力
数据技术
人工智能
logistics service supply chain
emergency capability
data technologies
artificial intelligence
