Abstract
To sustain competitive advantage, nowadays more than ever, outsourcing is crucially important for international and domestic firms. However, making the right outsourcing decision is not a just a simple multiple-factors decision making problem.
The aim of this paper is to construct an outsourcing hierarchy model based on the concept of the analytic hierarchy process with four levels of the most concerned attributes: competitiveness, human resources, business environment, and government policies. With respect to these factors, six typical alternatives in the Southeast Asian region were selected to compare with China. In this study, the authors attempt to investigate the best outsourcing service destination among these seven typical outsourcing service countries.
This study carries out the comparison between the AHP and Fuzzy-AHP approaches to see which one is more acceptable. Theoretically, the higher the priorities weight, the more important the factor or the alternative would be. The findings show that China is the optimal outsourcing service destination. Besides China, other Southeast Asian nations like Vietnam, Thailand, or the Philippines are emerging to be attractive locations. Regarding the main factors to select such the best country, cost competitiveness is the most important attribute. Furthermore, the comparison between the AHP and Fuzzy AHP show some significant differences which allow the study to conclude that the FAHP technique is more suitable to use for the research problem.
This study bridge a gap to enrich the existing literature to provide managers and policy makers a comprehensive view on how to construct an outsourcing hierarchy model based on the analytic hierarchy process and a Fuzzy-AHP approach with competitiveness, human resources, business environment, and government policies.
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Van Kien, P., Thach, N.N. (2018). A Study on Optimal Outsourcing Service Nation in the East and Southeast Asian Region: A Comparison Between AHP and Fuzzy AHP Approach. In: Anh, L., Dong, L., Kreinovich, V., Thach, N. (eds) Econometrics for Financial Applications. ECONVN 2018. Studies in Computational Intelligence, vol 760. Springer, Cham. https://doi.org/10.1007/978-3-319-73150-6_62
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