Competition and evolution in multi-product supply chains: An agent-based retailer model

Zhou He, Shouyang Wang, Edwin Tai Chiu Cheng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

34 Citations (Scopus)

Abstract

Facing such issues as demand uncertainty and in- and cross-channel competition, managers of today's retail chains are keen to find optimal strategies that help their firms to adapt to the increasingly competitive business environment. To help retail managers to address their challenges, we propose in this paper an agent-based retail model (ARM), grounded in complex adaptive systems, which comprises three types of agents, namely suppliers, retailers, and consumers. We derive the agents' optimal behaviours in response to competition by evaluating the evolutionary behaviour of the ARM using optimisation methods and genetic algorithm. We find that consumers' ability to collect pricing information has a significant effect on the degree of competition in retail chains. In addition, we find that the everyday low price (EDLP) strategy emerges from the evolutionary behaviour of the ARM as the dominant pricing strategy in multi-product retail chains.
Original languageEnglish
Pages (from-to)325-336
Number of pages12
JournalInternational Journal of Production Economics
Volume146
Issue number1
DOIs
Publication statusPublished - 1 Nov 2013

Keywords

  • Agent-based modelling
  • Competition
  • Complex adaptive system
  • Retailer
  • Supply chain

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Economics and Econometrics
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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