Green supply chain performance measurement using fuzzy ANP-based balanced scorecard:a collaborative decision-making approach
Data(s) |
11/06/2014
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Resumo |
The purpose of this paper is to delineate a green supply chain (GSC) performance measurement framework using an intra-organisational collaborative decision-making (CDM) approach. A fuzzy analytic network process (ANP)-based green-balanced scorecard (GrBSc) has been used within the CDM approach to assist in arriving at a consistent, accurate and timely data flow across all cross-functional areas of a business. A green causal relationship is established and linked to the fuzzy ANP approach. The causal relationship involves organisational commitment, eco-design, GSC process, social performance and sustainable performance constructs. Sub-constructs and sub-sub-constructs are also identified and linked to the causal relationship to form a network. The fuzzy ANP approach suitably handles the vagueness of the linguistics information of the CDM approach. The CDM approach is implemented in a UK-based carpet-manufacturing firm. The performance measurement approach, in addition to the traditional financial performance and accounting measures, aids in firms decision-making with regard to the overall organisational goals. The implemented approach assists the firm in identifying further requirements of the collaborative data across the supply-cain and information about customers and markets. Overall, the CDM-based GrBSc approach assists managers in deciding if the suppliers performances meet the industry and environment standards with effective human resource. © 2013 Taylor & Francis. |
Formato |
application/pdf |
Identificador |
http://eprints.aston.ac.uk/22449/1/Green_supply_chain_performance_measurement.pdf Bhattacharya, Arijit; Mohapatra, Priyabrata; Kumar, Vikas; Dey, Prasanta K.; Brady, Malcolm; Tiwari, Manoj K. and Nudurupati, Sai S. (2014). Green supply chain performance measurement using fuzzy ANP-based balanced scorecard:a collaborative decision-making approach. Production Planning and Control, 25 (8), pp. 698-714. |
Relação |
http://eprints.aston.ac.uk/22449/ |
Tipo |
Article PeerReviewed |