Agent-based simulation of pricing strategy for agri-products considering customer preference

Chang, Xue, Li, Jing, Rodriguez, Daniel and Su, Qun (2015) Agent-based simulation of pricing strategy for agri-products considering customer preference. International Journal of Production Research, 54 13: 1-19. doi:10.1080/00207543.2015.1120901


Author Chang, Xue
Li, Jing
Rodriguez, Daniel
Su, Qun
Title Agent-based simulation of pricing strategy for agri-products considering customer preference
Journal name International Journal of Production Research   Check publisher's open access policy
ISSN 1366-588X
0020-7543
Publication date 2015-12-13
Sub-type Article (original research)
DOI 10.1080/00207543.2015.1120901
Open Access Status Not Open Access
Volume 54
Issue 13
Start page 1
End page 19
Total pages 19
Place of publication Abingdon, Oxfordshire United Kingdom
Publisher Taylor & Francis
Collection year 2016
Language eng
Abstract Agri-products typically have short life cycles and are perishable. The price of perishable goods is influenced by many factors. Customers in a market have different preferences with regard to price, the quality of the product and the brand. Though studies on pricing strategies that consider customer preference are rare, this paper addresses the problem of optimal pricing strategy for retailers considering customer preferences. Traditional mathematical methods cannot adequately describe the complexities of customer preference. Due to these complexities, this paper proposes an agent-based simulation model composed of six retailers and hundreds of customers, each with personal preferences. The different retailers set prices according to freshness, inventory, cost and other factors. Due to the perishable nature of the products considered, this paper proposes a new categorising price strategy that sets prices according to different degrees of treatments. By comparing the final profit of all retailers at the end of a simulation, the categorising price strategy is demonstrated to be the optimal strategy if customers with different preferences are randomly distributed. Furthermore, based on the model, the paper studies how optimal strategies are influenced by the proportion of customers with different preferences.
Keyword Customer preference
Agri-products pricing strategy
Agent-based simulation
Categorising price strategy
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Queensland Alliance for Agriculture and Food Innovation
Official 2016 Collection
 
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