Anglia Ruskin Research Online (ARRO)
Browse
Pasqualino_2015.docx (75.08 kB)

A review of decision-support tools and performance measurement and sustainable supply chain management

Download (75.08 kB)
journal contribution
posted on 2023-08-30, 15:43 authored by Paolo Taticchi, Patrizia Garengo, Sai S. Nudurupati, Flavio Tonelli, Roberto Pasqualino
In recent years, interest on sustainable supply chain management has risen significantly in both the academic and business communities. This is confirmed by the growing number of conferences, journal publications, special issues and websites dedicated to the topic. Within this context, this paper reviews the existing literature related to decision-support tools and performance measurement for sustainable supply chain management. A narrative literature review is carried out to capture qualitative evidence, while a systematic literature review is performed using classic bibliometric techniques to analyse the relevant body of knowledge identified in 384 papers published from 2000 to 2013. The key conclusions include: the evidence of a research field that is growing, the call for establishing the scope of current research, i.e. the need for integrated performance frameworks with new generation decision support tools incorporating triple bottom line (TBL) approach for managing sustainable supply chains. There is a need to identify a wide range of specific industry-related TBL metrics and indexes, and assess their usefulness through empirical research and case-base analysis. We need mixed methods to thoroughly analyse and investigate sustainable aspects of the product life cycle across the supply chains, through empirical evidence, building and/or testing theory from and in practice.

History

Refereed

  • Yes

Volume

53

Issue number

21

Page range

6473-6494

Publication title

International Journal of Production Research

ISSN

1366-588X

Publisher

Taylor & Francis

File version

  • Accepted version

Language

  • eng

Legacy posted date

2018-10-22

Legacy creation date

2018-10-19

Legacy Faculty/School/Department

ARCHIVED Faculty of Science & Technology (until September 2018)

Usage metrics

    ARU Outputs

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC