Sustainable warehouse evaluation with AHPSort traffic light visualisation and post-optimal analysis method

ISHIZAKA, Alessio, KHAN, Sharfuddin Ahmed, KUSI-SARPONG, Simonov and NAIM, Iram (2022). Sustainable warehouse evaluation with AHPSort traffic light visualisation and post-optimal analysis method. Journal of the Operational Research Society, 73 (3), 558-575.

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Sustainable warehousing is essential for organisations to achieve overall supply chain sustainability. Warehousing facilities have the greatest potential for reducing socio-environmental impact. Yet, both research and practice have given relatively less attention to considering all aspects of sustainability in warehouses. In order to address this gap, this study proposes combining both input from professionals and from a literature survey of triple-bottom-line theory in order to develop a sustainable warehouse criteria framework, thus contributing to sustainable organisational warehouse evaluation. The method supporting the evaluation of this framework is based on the integration of a multicriteria AHPSort traffic light visualisation technique and novel post-optimal analysis. Furthermore, the authors deployed this framework and integrated methodology in an Indian manufacturing company to evaluate and classify seven of their warehouses for decision making. The traffic light visualisation technique presents and conveys the results better than numbers. Finally, the new post-optimal analysis provides recommendations for cost efficient improvements. The findings of this study present valuable insights and guidelines for industrial managers and practitioners, especially those from the Indian manufacturing industry, for sustainable warehouse decision-making, and for improving their overall corporate sustainability performance.

Item Type: Article
Uncontrolled Keywords: 01 Mathematical Sciences; 08 Information and Computing Sciences; 15 Commerce, Management, Tourism and Services; Operations Research; 35 Commerce, management, tourism and services; 46 Information and computing sciences; 49 Mathematical sciences
Identification Number:
Page Range: 558-575
SWORD Depositor: Symplectic Elements
Depositing User: Symplectic Elements
Date Deposited: 11 Oct 2023 16:08
Last Modified: 11 Oct 2023 16:15

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