Strategic Supplier Selection in Payment Industry: A Multi-Criteria Solution for Insufficient and Interrelated Data Sources

Siavash Hekmat (), Maghsoud Amiri () and Golshan Madraki
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Siavash Hekmat: FANAP Studies & Research Center, Pardis Technology Park Pardis, Tehran, Iran
Maghsoud Amiri: Department of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran
Golshan Madraki: Engineering and Management, David D. Reh School of Business, Clarkson University, Potsdam, NY, USA

International Journal of Information Technology & Decision Making (IJITDM), 2021, vol. 20, issue 06, 1711-1745

Abstract: Our goal is to address the complicated problem of strategic supplier selection with interrelated and insufficient data. To achieve this goal, we proposed our Strategic Supplier Selection Methodology (SSSM). First, SSSM formulates the enterprise strategies and evaluation criteria. Then, we developed a novel method called Grey Principal Component Analysis-Data Envelopment Analysis (GPCA-DEA) to evaluate suppliers in SSSM. GPCA-DEA overcomes the major disadvantages and limitations of former methodologies (e.g., DEA) while dealing with insufficient and interrelated data. Finally, SSSM applies Multiple Attribute Decision-Making (MADM) methods to select suppliers based on the ranking score. The application of SSSM is illustrated in the payment industry to select Payment Initiation Service Providers (PISP). For the first time, we considered the payment industry-specific criteria in compliance with the latest regulation (PSD2). The Spearman rank correlation statistical test showed that our method (GPCA-DEA used in SSSM) yields more reliable results than a former version of DEA.

Keywords: Strategic supplier selection; principal component analysis; grey theory; insufficient data; payment industry (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1142/S0219622021500474

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