An enhanced supplier selection model based on optimized analytic network process towards sustainable information technology outsourcing

Information Technology Outsourcing (ITO) has become part of the organization’s strategy as it offers benefits such as high-quality products, cost reduction, and increased productivity. Essentially, ITO is a complex process in which selecting the right supplier involves evaluation of multi criteria....

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Bibliographic Details
Main Author: Fusiripong, Prashaya
Format: Thesis
Language:eng
eng
Published: 2022
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Online Access:https://etd.uum.edu.my/9750/1/permission%20to%20deposit-grant%20the%20permission%2099036.pdf
https://etd.uum.edu.my/9750/2/s99036_01.pdf
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Summary:Information Technology Outsourcing (ITO) has become part of the organization’s strategy as it offers benefits such as high-quality products, cost reduction, and increased productivity. Essentially, ITO is a complex process in which selecting the right supplier involves evaluation of multi criteria. To ensure the sustainable of the ITO project, the evaluation criteria should consider risk factors and other sustainability criteria of the project. However, existing ITO supplier selection models lack of sustainability criteria and risk factors. Moreover, these methods rely on human judgment in weight allocation. Therefore, this study proposes an Enhanced Supplier Selection Model (ESS) for sustainable ITO mainly to eliminate human judgment in Analytical Network Process (ANP) method. The ESS Model was constructed through theoretical, exploratory and experimental studies. The exploratory study was carried in Thailand using survey which involved 45 respondents. Findings from the study was used to construct evaluation criteria and become datasets for ESS. The proposed ESS Model was evaluated using expert reviews and case studies in Thailand. The ESS model contains two main components: evaluation criteria and a decision-making method. The first has nineteen (19) sustainability criteria and seven (7) risk factors. While the latter is an enhanced ANP with Firefly Algorithm (ANP-FA). The evaluation results indicate that the Consistency Ratio (CR) for ANP-FA is smaller than ANP, which is 0.003 compared to 0.031. This outcome shows that the ESS model is feasible in removing human judgment in supplier selection of ITO projects. The study’s contributions can be interpreted from two perspectives. The proposed ESS model is a theoretical contribution in Multi-Criteria Decision-Making and Supplier Selection in ITO project. In terms of practicality, the model has been realized in Thailand organizations to ensure the sustainability of ITO projects.