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

Publication Date09 Apr 2020
Pages987-1002
DOIhttps://doi.org/10.1108/IMDS-11-2019-0594
AuthorLinh Nguyen Khanh Duong,Lincoln C. Wood,William Yu Chung Wang
SubjectInformation & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems
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 and
Curtin University Bentley Campus, Perth, Australia, and
William Yu Chung Wang
Waikato Management School, University of Waikato, Hamilton, New Zealand
Abstract
Purpose This research proposes a decision framework for using non-financial measures to define a
replenishmentpolicy for perishable health products. Theseproducts are perishable and substitutableby 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.
Design/methodology/approach 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.
Findings 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 thatit is feasible to adopt non-financial performance measures to define a replenishment
policy and evaluate performance.
Originality/value The framework, thus, prioritises non-financial measures and addresses issues of lacking
information sharing and employee involvement to enhance hospitalsperformance while minimising costs. The
non-financial measures improve cross-functional communication while supporting simpler transformations
from high-level strategies to daily operational targets.
Keywords Perishable inventory management, Substitutable, Decision systems
Paper type Research paper
1. Introduction
Management of inventories involving health products, which are typically perishable and
substitutable, is a difficult problem with many particular challenges (Salehi et al., 2019). These
challenges come from the fact that these products have a limited lifetime and the requirement
for the trade-off between inventory costs and the fill rate (Dreyfuss and Giat, 2019). For
example, consider blood platelets, which are a standard product in hospitals. Blood platelets
can be stored up to seven days before their function is destroyed (Lin et al., forthcoming). An
inventory manager aims to lower the inventory level of blood platelets to lower inventory
costs and the loss from outdated stock. On the other hand, when required, patients should be
able to be transfused with the same blood platelet as their own or a compatible platelet;
otherwise, lives may be lost. In dealing with this challenge, the objective of hospital inventory
management is to develop a framework that enables information sharing (Yu and Cao, 2019)
and identifies replenishment policy that reduces inventory levels without lowering the fill
rate level (Moons et al., 2019).
Management
of perishable
health
products
987
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0263-5577.htm
Received 10 November 2019
Revised 29 January 2020
Accepted 29 February 2020
Industrial Management & Data
Systems
Vol. 120 No. 5, 2020
pp. 987-1002
© Emerald Publishing Limited
0263-5577
DOI 10.1108/IMDS-11-2019-0594
Hospitals often generate replenishment policies by minimising total cost or maximising
total profit functions, which may include some or all relevant financial factors (e.g. holding
cost, ordering cost) (Lin et al., forthcoming). This financial approach is based on the inventory
theory in which cost factors are assumed to be known exactly. However, the exact value of
these factors could be challenging to define. Consequently, the optimal policy may not result
in the minimum cost or maximum profit (Elgazzar et al., 2019). Additionally, financial
measures have been criticised as too one-dimensional (Micheli and Mura, 2017); e.g. focusing
too much on the fill rate level may lead to high inventory level or high expired quantity.
Rather than optimising a financial measure, researchers (e.g. Dreyfuss and Giat, 2019;
Dweekat et al., 2017;Vidalis et al., 2014) have called for the use of non-financial measures
when generating replenishment policies. Using non-financial measures enables the
connection of performance measures to strategy and hence provides enhanced control of
the overall performance in a more cooperative and integrated routine (Dweekat et al., 2017).
Motivated by that call, this research aims at answering questions: is it possible (RQ1) and
how (RQ2) to use non-financial measures to define a replenishment policy for perishable
health products? To answer the RQ1, we base on the work of Cannella et al. (2013), who
proposed a set of non-financial measures to evaluate performance for a whole supply chain.
We identify the most common costs in perishable inventory models, namely, holding cost,
purchase cost, lost sales cost and outdated cost (Kouki et al., 2014). These costs are translated
into non-financial measures including fill rate (FR), average inventory (AI) and order rate
variance ratio (ORVR) by using the definition of non-financial measures from Cannella
et al. (2013).
To answer the RQ2, we develop a framework including simulation, analytic hierarchy
process (AHP) and data envelopment analysis (DEA) to use these non-financial measures and
identify a replenishment policy. A simulation tool is useful for evaluating various
performance measures of complex systems (Heidary and Aghaie, 2019). These measures
usually conflict with each other. Furthermore, the preferences for which performance
measures to use vary between managers. Therefore, the simulation tool should be combined
with other multi-criteria decision-making (MCDM) methods (Choi et al., 2016). Among MCDM
methods, AHP has been used widely as its abilities in quantifying criteria (Moktadir et al.,
2019). The AHP has been integrated with DEA to avoid difficulties when having too many
alternatives (Ho and Ma, 2018). The integration of simulation, AHP and DEA can take
advantage of the strengths of each method (Choi et al., 2016) and support framework for
complex systems (Bonney and Jaber, 2014;Ho and Ma, 2018). The framework is demonstrated
with a numerical example. The results are shown to be comparable with those from Kouki
et al. (2014), where a similar system is studied with financial measures, and thus the similarity
confirms the contribution of this research to the literature. The results prove that non-
financial measures can be used effectively to generate replenishment policies.
Two interesting findings emerged from this research. First, this research uses non-
financial measures (AI, FR, and ORVR) by themselves to define a replenishment policy. These
are the most common measures in the blood supply chain problem, i.e. the number of outdated
units, the number of units short of demand and the stock level (Ahmadi et al., 2019). The direct
use of non-financial measures helps stakeholders better understand the overall performance
of a company or its subordinates (Esch et al., 2019). While Vidalis et al. (2014) demonstrated
the transformation of non-financial measures into a profit function and selection of the
replenishment policy that maximised total profit, it is not easy in practice to transform all
non-financial measures into a profit function due to delays in collecting information or the
inaccuracy of information over the supply chain (Moons et al., 2019). In contrast to Vidalis
et al. (2014), this research does not transform non-financial measures into cost factors;
therefore, replenishment policies are easily communicated and comprehended. The
framework, therefore, prioritises non-financial measures and addresses issues of lacking
IMDS
120,5
988

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