Supplier selection for global service providers: a decision support system

Abstract

In this paper, we develop a decision support system (DSS) aimed at solving a real-world supplier selection problem (SSP) for a global service provider (GSP) operating in the facility management (FM) industry. The GSP provides its customers with FM services, which are subcontracted to external suppliers selected on the basis of multiple criteria, like economic soundness, quality of service, capacity, and closeness. The SSP is formulated as a multi-objective generalized assignment problem, where the quality and the closeness of the selected suppliers are maximized, whereas a penalty produced by overcapacity assignments is minimized. The quality of each supplier is computed by applying a weighted sum method, resulting from a multi-criteria decision analysis in which the criteria weights are determined through an Analytic Hierarchy Process. The DSS is developed using a modular architecture with a relational database, a supplier evaluator, and a simulator, as well as an additional user-friendly interface. The simulator relies on a rolling horizon algorithm and three alternative configurations to assign contracts to suppliers. The effectiveness of the DSS is assessed by means of extensive computational experiments on historical data. The results show a significant average improvement of 25% compared to the solution adopted by the company.

Keywords:

• Decision support system
• supplier selection problem
• global service providers
• integrated multi-criteria decision analysis

Acknowledgements

We thank H2H Facility Solutions SpA for the support given to this project. We also thank the reviewers for their comments, which helped improve the paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data is not available due to commercial restrictions.

Notes

1 Note that the use of small size evaluation scales is a rather common practice in the computation of composite indexes. For example, a three-level scale was adopted (within a weighting procedure simpler than ours) for the 2016 European Digital City Index (Bannerjee et al. 2016).

Additional information

Funding

This work was funded under the National Recovery and Resilience Plan (NRRP), Mission 04 Component 2 Investment 1.5--NextGenerationEU, Call for tender n. 3277 dated 30/12/2021, Award Number: 0001052 dated 23/06/2022, by the Brazilian research agency Conselho Nacional de Desenvolvimento Científico e Tecnológico, Grant: 432014/2018-7, and by Universidade Federal da Paraíba through the Public Call n. 03/2020 “Produtividade em Pesquisa PROPESQ/PRPG/UFPB”, proposal code PVL13394-2020.