Collaborative-commerce in supply chains: A review and classification of analytical models

Xiaoyan Xu, Tsan Ming Choi, Sai Ho Chung, Shu Guo

Research output: Journal article publicationReview articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

In the sharing economy era with the development of Industry 4.0, collaborative-commerce (C-Commerce) is getting increasingly important in supply chain management (SCM). However, there is currently a lack of consolidated view on the topic. This paper aspires to fill this gap by conducting a comprehensive review of analytical modeling SCM studies in C-Commerce, aiming at providing guidance on “what it is”, “what to do”, and “how to do”, collectively called the 2W1H framework, for this topic. Based on a deep systematic survey of the literature, we establish a novel classification framework for SCM C-Commerce in two dimensions, i.e., research domains and supply chain (SC) structure. We examine the critical research issues and analytical models following this classification framework. We specifically include the relevant works which highlight (i) collaborative innovation in product development, (ii) collaborative branding and promotion, and (iii) collaborative planning, forecasting and replenishment (CPFR). Based on our review findings, we uncover the important supply chain operational issues in C-Commerce and highlight key modeling elements. We further present the evolution of the C-Commerce related studies in the SCM literature and propose a future research agenda that can fill the gaps between the current state of research and real-world needs in business operations.

Original languageEnglish
Article number108922
Number of pages21
JournalInternational Journal of Production Economics
Volume263
DOIs
Publication statusPublished - Sept 2023

Keywords

  • Analytical models
  • Collaborative commerce (C-Commerce)
  • Production economics
  • Supply chains

ASJC Scopus subject areas

  • General Business,Management and Accounting
  • Economics and Econometrics
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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