Journal article
Customer-driven investment decisions in existing multiple sales channels: A downstream supply chain analysis
International journal of production economics, v 204, pp 44-58
01 Oct 2018
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
A supply chain employing multiple sales channels, needs to continually enhance these channels for achieving competitive advantage. The purpose of this paper is to provide a channel-level benefit-cost analysis, through an integration of operations and marketing perspectives to ultimately provide a systematic procedure for optimal investment decisions towards improving existing sales channels. This study is motivated by the decision for improvement, on the part of many established firms that typically utilize multiple channel structures. In pursuing our objective, an analytic network process (ANP), that considers both customer priorities and demand correlations among channels, is suggested, for obtaining customer input data. Utilizing a proposed benefit-cost ratio metric for each channel, incorporating customer input information, as well as relevant operating costs, we outline a mathematical programming procedure for determining the optimal allocation of a limited investment budget among these channels. Our suggested methodological approach is illustrated by a realistic numerical example and some selected sensitivity analysis.
Metrics
Details
- Title
- Customer-driven investment decisions in existing multiple sales channels: A downstream supply chain analysis
- Creators
- Yasamin Salmani - Drexel UniversityFariborz Y. Partovi - Drexel UniversityAvijit Banerjee - Drexel University
- Publication Details
- International journal of production economics, v 204, pp 44-58
- Publisher
- Elsevier
- Number of pages
- 15
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:000446289700004
- Scopus ID
- 2-s2.0-85053062152
- Other Identifier
- 991019168893804721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Engineering, Industrial
- Engineering, Manufacturing
- Operations Research & Management Science