摘要
遵循“发现问题—分析问题—解决问题”的逻辑脉络,构建“探本析流—谋新验效”双阶段研究框架。第一阶段“探本析流”聚焦供应链问题诊断,指出数据割裂导致的信息孤岛、企业间零和博弈思维等问题。第二阶段“谋新验效”聚焦供应链优化方案的构建与验证,构建数据融合与关系重构的双轨机制,以数据融合打造供应链协同优化的技术基座,以成本共担和双向激励机制增强合作黏性;通过效能验证评估数据融合驱动的供应链协同优化机制的实施效果。本研究通过“问题识别—机制设计—效果反馈”闭环研究体系,为供应链协同优化提供新的思路和方法。
Following the logical framework of“identifying problems-analyzing problems-solving problems”,this study constructs a dual-phase research framework of“root cause exploration—innovation and validation”.The first phase of“root cause exploration”focuses on diagnosing supply chain issues,highlighting problems such as information silos caused by data fragmentation and zero and game thinking among enterprises.The second phase of“innovation and validation”centers on the construction and verification of supply chain optimization solutions.It establishes a dual-track mechanism for data fusion and relationship reconstruction,leveraging data fusion to build a technological foundation for supply chain collaborative optimization while enhancing partnership cohesion through cost-sharing and bidirectional incentive mechanisms.The effectiveness of the data fusion-driven supply chain collaborative optimization mechanism is evaluated through performance validation.This research provides new ideas and methods for the collaborative optimization of the supply chain through a closed-loop research system of“problem identification-mechanism design-effect feedback”.
作者
郭孟珂
周雅欣
许婉婉
周晋伊
樊臻
GUO Meng-ke;ZHOU Ya-xin;XU Wan-wan;ZHOU Jin-yi;FAN Zhen(School of Digital Commerce,Jiangsu Vocational Institute of Commerce,Nanjing 211168,Jiangsu,China)
出处
《江苏经贸职业技术学院学报》
2025年第4期19-23,共5页
Journal of Jiangsu Vocational Institute of Commerce
关键词
供应链协同优化
数据融合
关系重构
collaborative optimization of supply chain
data fusion
relationship reconstruction
