IMDS SI on KB-DSS - IMDS-09-2016-0410 - Final draft.pdf (262.07 kB)
Download file

Decision support systems for sustainable logistics: A review and bibliometric analysis

Download (262.07 kB)
journal contribution
posted on 20.04.2017, 13:30 authored by Fahham Qaiser, Karim Ahmed, Martin SykoraMartin Sykora, Alok ChoudharyAlok Choudhary, Mike Simpson
Purpose: Decision-making in logistics is an increasingly complex task for organizations as these involve decisions at strategic, tactical and operational levels coupled with the triple bottom line (TBL) of sustainability. Decision support systems (DSS) played a vital role in arguably solving the challenges associated with decision making in sustainable logistics. This review is a systematic attempt to explore the current state of the research in the domain of DSS for logistics while considering sustainability aspects. Design/methodology/approach: A systematic review approach using a set of relevant keywords with several exclusion criteria was adopted to identify literature related to DSS for sustainable logistics. A total of 40 papers were found from 1994 to 2015, which were then analysed along the dimensions of publishing trend, geographic distribution and collaboration, the most influential journals, affiliations and authors as well as the key themes of identified literature. The analysis was conducted by means of bibliometric and text mapping tools, namely BibExcel, gpsvisualizer, and VOSviewer. Findings: The bibliometric analysis showed that DSS for sustainable logistics is an emerging field; however, it is still evolving but at a slower pace. Furthermore, most of the contributing affiliations belong to the United States and the United Kingdom. The text mining and keyword analysis revealed key themes of identified papers. The inherent key themes were decision models and frameworks to address sustainable logistics issues covering transport, distribution and third party logistics. The most prominent sustainable logistics issue was carbon footprinting. Social impact has been given less attention in comparison to economic and environmental aspects. The literature has adequate room for proposing more effective solutions by considering various types of MCDA (multi-criteria decision analysis) methods and DSS configurations while simultaneously considering economic, environmental and social aspects of sustainable logistics. Moreover, the field has potential to include logistics from wide application areas including freight transport through road, rail, sea, air as well as inter-modal transport, port operations, material handling and warehousing. Originality/value: To the best of the authors’ knowledge, this is the first systematic review of DSS for sustainable logistics using bibliometric and text analysis. The key themes and research gaps identified in this paper will provide a reference point that will encourage and guide interested researchers for future study, thus aiding both theoretical and practical advancements in this discipline.

Funding

This research has been made available through the European Union EuropeAid funded Project “EU-India Research & Innovation Partnership for Efficient and Sustainable Freight Transportation (REINVEST)”, Contract Number: R/141842.

History

School

  • Business and Economics

Department

  • Business

Published in

Industrial Management & Data Systems

Citation

QAISER, F.H. ...et al., 2017. Decision support systems for sustainable logistics: A review and bibliometric analysis. Industrial Management & Data Systems, 117 (7), pp. 1376-1388.

Publisher

© Emerald

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

27/03/2017

Publication date

2017-08-14

Notes

This paper was accepted for publication in the journal Industrial Management & Data Systems and the definitive published version is available at https://doi.org/10.1108/IMDS-09-2016-0410

ISSN

0263-5577

Language

en