Title: Framework for engineering supply chain performance in manufacturing sector

Authors: Fatima Maryum; Syed Mehmood Hasan; Satya Shah; Elmira Naghi Ganji

Addresses: Department of Industrial Manufacturing and Engineering, NED University of Engineering and Technology, Karachi, 74720, Pakistan ' School of Engineering, Physical and Mathematical Sciences, Royal Holloway, University of London, London, TW200EX, UK ' School of Engineering, Physical and Mathematical Sciences, Royal Holloway, University of London, London, TW200EX, UK ' School of Engineering, Physical and Mathematical Sciences, Royal Holloway, University of London, London, TW200EX, UK

Abstract: Supply chain disruptions caused by COVID-19 have dramatically altered the performance of the supply chain as measured. Some companies were unable to keep their supply chain running despite being rated as "excellent" in the traditional supply chain performance rating system. Considering modern dynamics, this study develops a standard framework for measuring integrated supply chain performance. The developed framework consists of six elements that are flexibility, quality, resource utilisation, customer satisfaction, delivery lead time, and reduced cost as ideal parameters. This framework is validated by taking two large-scale manufacturing industries as the case. The collected data is then analysed using a regression method to show the correlation between Supply chain performance and the six parameters in the sustainable supply chain network. Finally, a paired comparison matrix is produced using an analytic hierarchy process (AHP) multicriteria decision analysis to evaluate the outcomes across important parameters like reduced cost, quality, flexibility, customer satisfaction, delivery lead time, and resource utilisation. The purpose of this analysis is to determine how Pakistan's industrial sectors are positioned in a thematic conceptual framework.

Keywords: analytic hierarchal process modelling; PMS; performance measurement system; supply chain indicators; supply chain performance drivers; AHP; analytic hierarchy process; sustainable supply chain performance.

DOI: 10.1504/IJBPSCM.2024.144928

International Journal of Business Performance and Supply Chain Modelling, 2024 Vol.15 No.2, pp.130 - 163

Received: 12 Aug 2023
Accepted: 24 Jul 2024
Published online: 11 Mar 2025 *

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