Collaboration in multi-tier supply chains for reducing empty running: a case study in the UK retail sector

Abstract

This research aims to explore ways to improve transport efficiency in retail multi-tier supply chains by integrating raw material sourcing of suppliers into the transport network. The performance of the proposed scenario is assessed using a discrete-event simulation (DES) model that includes the additional pick-up and drop-off points of an extended transport network. The results suggest an improvement in the transport network efficiency, evidenced in the reduction of empty running levels and costs. This study supports the idea that the integration of raw material sourcing of suppliers into a retailer's transport network can bring significant benefits.

Publication DOI: https://doi.org/10.1080/13675567.2020.1812054
Divisions: College of Engineering & Physical Sciences > School of Infrastructure and Sustainable Engineering > Engineering Systems and Supply Chain Management
College of Engineering & Physical Sciences > Aston Logistics and Systems Institute
College of Business and Social Sciences > Aston Business School > Operations & Information Management
Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis Group in International Journal of Logistics Research and Applications on 26 Aug 2020, available online at: http://www.tandfonline.com/10.1080/13675567.2020.1812054
Uncontrolled Keywords: Collaboration,discrete-event simulation,empty running,multi-tier supply chains,retail sector,transport efficiency,Management Information Systems,Control and Systems Engineering,Information Systems,Computer Science Applications,Management Science and Operations Research
Full Text Link:
Related URLs: https://www.tan ... 67.2020.1812054 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2020-08-26
Published Online Date: 2020-08-26
Accepted Date: 2020-08-13
Authors: Venegas Vallejos, Melissa
Matopoulos, Aristides (ORCID Profile 0000-0002-5083-0534)
Greasley, Andrew (ORCID Profile 0000-0001-6413-3978)

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