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Inventory management of perishable health products: a decision framework with non-financial measures

Linh Nguyen Khanh Duong (University of Lincoln, Lincoln, UK)
Lincoln C. Wood (Department of Management, University of Otago, Dunedin, New Zealand) (Curtin University Bentley Campus, Perth, Australia)
William Yu Chung Wang (Waikato Management School, University of Waikato, Hamilton, New Zealand)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 10 April 2020

Issue publication date: 4 May 2020




This research proposes a decision framework for using non-financial measures to define a replenishment policy for perishable health products. These products are perishable and substitutable by nature and create complexities for managing inventory. Instead of a financial measure, numerous measures should be considered and balanced to meet business objectives and enhance inventory management.


This research applies a multi-methodological approach and develops a framework that integrates discrete event simulation (DES), analytic hierarchy process (AHP) and data envelopment analysis (DEA) techniques to define the most favourable replenishment policy using non-financial measures.


The integration framework performs well as illustrated in the numerical example; outcomes from the framework are comparable to those generated using a traditional, financial measures-based, approach. This research demonstrates that it is feasible to adopt non-financial performance measures to define a replenishment policy and evaluate performance.


The framework, thus, prioritises non-financial measures and addresses issues of lacking information sharing and employee involvement to enhance hospitals' performance while minimising costs. The non-financial measures improve cross-functional communication while supporting simpler transformations from high-level strategies to daily operational targets.



Duong, L.N.K., Wood, L.C. and Wang, W.Y.C. (2020), "Inventory management of perishable health products: a decision framework with non-financial measures", Industrial Management & Data Systems, Vol. 120 No. 5, pp. 987-1002.



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