Imprecise DEA Models to Assess the Agility of Supply Chains

Purpose Evaluating the performance of supply chains is a convoluted task because of the complexity that is inextricably linked to the structure of the aforesaid chains. Therefore, the purpose of this paper is to present an integrated approach for evaluating and sizing real-life health-care supply chains in the presence of interval data. Design/methodology/approach To achieve the objective, this paper illustrates an approach called Latin hypercube sampling by replacement (LHSR) to identify a set of precise data from the interval data; then the standard data envelopment analysis (DEA) models can be used to assess the relative efficiencies of the supply chains under evaluation. A certain level of data aggregation is suggested to improve the discriminatory power of the DEA models and an experimental design is conducted to size the supply chains under assessment. Findings The newly developed integrated methodology assists the decision-makers (DMs) in comparing their real-life supply chains against peers and sizing their resources to achieve a certain level of production. Practical implications The proposed integrated DEA-based approach has been successfully implemented to suggest an appropriate structure to the actual public pharmaceutical supply chain in Morocco. Originality/value The originality of the proposed approach comes from the development of an integrated methodology to evaluate and size real-life health-care supply chains while taking into account interval data. This developed integrated technique certainly adds value to the health-care DMs for modelling their supply chains in today's world.

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Measurement of Dyadic Supply Chains Efficiency under New Assumptions Using DEA Models

Journal of Applied Sciences ◽

10.3923/jas.2016.445.453 ◽

2016 ◽

Vol 16 (10) ◽

pp. 445-453

Author(s):

Walid Abdelfatta ◽

Abdelwaheb Rebai

Keyword(s):

Supply Chains ◽

Dea Models

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Developing an inverse range directional measure model to deal with positive and negative values

Management Decision ◽

10.1108/md-11-2017-1089 ◽

2019 ◽

Vol 57 (9) ◽

pp. 2520-2540 ◽

Cited By ~ 2

Author(s):

Sara Yousefi ◽

Reza Farzipoor Saen ◽

Seyed Shahrooz Seyedi Hosseininia

Keyword(s):

Supply Chains ◽

Cash Flow ◽

Efficiency Score ◽

Negative Data ◽

Flow Management ◽

Content Type ◽

Cash Flow Management ◽

Input And Output ◽

Decision Making Unit ◽

Dea Models

Purpose To manage cash flow in supply chains, the purpose of this paper is to propose inverse data envelopment analysis (DEA) model. Design/methodology/approach This paper develops an inverse range directional measure (RDM) model to deal with positive and negative values. The proposed model is developed to estimate input and output variations such that not only efficiency score of decision making unit (DMU) remains unchanged, but also efficiency score of other DMUs do not change. Findings Given that auto making industry deals with huge variety and volumes of parts, cash flow management is so important. In this paper, inverse RDM models are developed to manage cash flow in supply chains. For the first time, the authors propose inverse DEA models to deal with negative data. By applying the inverse DEA models, managers distinguish efficient DMUs from inefficient ones and devise appropriate strategies to increase efficiency score. Given results of inverse integrated RDM model, other combinations of cash flow strategies are proposed. The suggested strategies can be taken into account as novel strategies in cash flow management. Interesting point is that such strategies do not lead to changes in efficiency scores. Originality/value In this paper, inverse input and output-oriented RDM model is developed in presence of negative data. These models are applied in resource allocation and investment analysis problems. Also, inverse integrated RDM model is developed.

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Incorporation of Preferences into Supply Chains DEA Efficiency: A Geometric Attribution Approach

Pakistan Journal of Statistics and Operation Research ◽

10.18187/pjsor.v16i4.2578 ◽

2020 ◽

pp. 761-774

Author(s):

Walid Abdelfattah ◽

Mohammed Sadok Cherif

Keyword(s):

Supply Chain ◽

Supply Chains ◽

Optimal Allocation ◽

Research Area ◽

Decision Makers ◽

Weight Restrictions ◽

Geometric Decomposition ◽

Dea Models ◽

Dea Efficiency ◽

Using Data

Among many applications, several studies using Data Envelopment Analysis (DEA) have examined and studied the efficiency of supply chains. However, the majority of existing approaches dealing with this research area have ignored the important factor of decision makers’ preferences. The main objective of this article is to provide consistent DEA models that allow for efficiency analysis in order to determine the optimal allocation of resources according to these preferences. We propose three cases that are inspired from the geometric decomposition of preference attributions: (1) horizontal attribution, which is when decision makers treat each supply chain as a single non-detachable entity; (2) vertical attribution, which is when decision makers consider supply chains detachable and (3) combined attribution, which is when decision makers concurrently assign weights to the supply chain and to its members. Based on this suggested decomposition, new DEA models are developed, and an illustrative example is applied. The obtained results are relevant and show that DEA is capable of easily incorporating the preferences of decision-makers without resorting to weight restrictions on inputs or outputs.

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An online cost allocation model for horizontal supply chains

Transportation Research Part C Emerging Technologies ◽

10.1016/j.trc.2020.102888 ◽

2021 ◽

Vol 122 ◽

pp. 102888

Author(s):

Han Zou ◽

Maged M. Dessouky ◽

Shichun Hu

Keyword(s):

Supply Chains ◽

Cost Allocation ◽

Allocation Model

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Codes of Conduct: Lieferantenkodizes: Sinnvolles Instrument zur Lieferantensteuerung oder reine Marketingmaßnahme?

Klinik Einkauf ◽

10.1055/s-0040-1715327 ◽

2020 ◽

Vol 02 (03/04) ◽

pp. 60-61

Author(s):

Jörg Schlüchtermann ◽

Johannes Heller

Keyword(s):

Supply Chains ◽

Codes Of Conduct

Insbesondere in komplexen Supply Chains ist es heute üblich, dass Kunden ihre Lieferanten über Selbstverpflichtungserklärungen (Codes of Conduct) steuern. Forschungen aus anderen Industrien zeigen die Möglichkeiten, aber auch Grenzen der Arbeit mit diesem Instrument des Lieferantenmanagements. Davon können auch Krankenhauseinkäufer profitieren.

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