Improving the operational efficiency of outbound retail logistics using clustering of retailers and consumers
Journal of Modelling in Management
ISSN: 1746-5664
Article publication date: 17 September 2018
Issue publication date: 15 October 2018
Abstract
Purpose
The purpose of this paper is to investigate ways to improve operational efficiency of outbound retail logistics considering retailers and consumers by using clustering approach. The retailers are allocated to serve a cluster of consumers. This study demonstrates economic and environment benefits that are achieved in terms of reduced delivery time, transportation cost and carbon emissions.
Design/methodology/approach
This study is based on modeling the outbound logistics of a retail chain by using Kohonen self-organizing map (KSOM). KSOM is an unsupervised learning and data analysis method for vector quantization, which is based on Euclidean distance method to form clusters.
Findings
Appropriate clustering of retailers and consumers provides efficient locations of retailers that are identified using the KSOM training algorithm. It provides optimum distance with lesser delivery time, transportation cost and carbon emissions.
Research limitations/implications
The implication of research includes modeling of operational procedures in a retail supply chain, which is a crucial task for a business. These operations positively affect the reduction in inventory and distribution costs, improvement in customer service and responsiveness to the ever-changing markets of consumer durables. Overall results are insightful and practical in the sense that implementation would result in consumer convenience, eco-friendly environment, etc.
Originality/value
There is not enough research available on outbound retail logistics considering retailers and consumers using clustering approach.
Keywords
Citation
Mohanty, M., Singh, R. and Shankar, R. (2018), "Improving the operational efficiency of outbound retail logistics using clustering of retailers and consumers", Journal of Modelling in Management, Vol. 13 No. 3, pp. 646-674. https://doi.org/10.1108/JM2-12-2016-0137
Publisher
:Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited