Fuzzy multi‐criteria risk‐benefit analysis of business process outsourcing (BPO)

Fuzzy multi‐criteria risk‐benefit analysis of business process outsourcing (BPO) Purpose – The objective of this paper is to present the employment of the new hierarchical fuzzy technique for order preference by similarity to ideal solution (TOPSIS) approach to evaluate the most suitable business process outsourcing (BPO) decision. Design/methodology/approach – The paper explains the importance of selection criteria for evaluation of BPO. It then describes briefly the fuzzy hierarchical TOPSIS methodology. There then follows a discussion of the application of the fuzzy hierarchical TOPSIS with some sensitivity analysis to the BPO evaluation problem. Finally, some concluding remarks and perspectives are offered. Findings – Use of the hierarchical fuzzy TOPSIS methodology offers a number of benefits. It is a more systematic method than the other fuzzy multi‐criteria decision‐making (FMCDM) methods and it is more capable of capturing a human's appraisal of ambiguity when complex multi‐criteria decision‐making problems are considered. The hierarchical fuzzy TOPSIS is superior to the other FMCDM methods, such as fuzzy analytic hierarchy process (FAHP) and classical fuzzy TOPSIS methods, since the hierarchical structure without making pairwise comparisons among criteria, sub‐criteria, and alternatives is considered. Hierarchical fuzzy TOPSIS is an excellent tool to handle qualitative assessments about BPO evaluation problems, and its calculations are faster than FAHP. Also, hierarchical fuzzy TOPSIS makes it possible to take into account the hierarchical structure in the evaluation model. However, there are drawbacks. The classical fuzzy TOPSIS is a highly complex methodology and requires more numerical calculations in assessing the ranking order of the alternatives than the hierarchical fuzzy TOPSIS methodology and hence it increases the effort, thus limiting its applicability to real world problems. Originality/value – The proposed model will be very useful to managers in the manufacturing sector, as this method makes decision making easier, systematic, efficient and effective. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Information Management & Computer Security Emerald Publishing

Fuzzy multi‐criteria risk‐benefit analysis of business process outsourcing (BPO)

Information Management & Computer Security, Volume 16 (3): 22 – Jul 18, 2008

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Publisher
Emerald Publishing
Copyright
Copyright © 2008 Emerald Group Publishing Limited. All rights reserved.
ISSN
0968-5227
DOI
10.1108/09685220810893180
Publisher site
See Article on Publisher Site

Abstract

Purpose – The objective of this paper is to present the employment of the new hierarchical fuzzy technique for order preference by similarity to ideal solution (TOPSIS) approach to evaluate the most suitable business process outsourcing (BPO) decision. Design/methodology/approach – The paper explains the importance of selection criteria for evaluation of BPO. It then describes briefly the fuzzy hierarchical TOPSIS methodology. There then follows a discussion of the application of the fuzzy hierarchical TOPSIS with some sensitivity analysis to the BPO evaluation problem. Finally, some concluding remarks and perspectives are offered. Findings – Use of the hierarchical fuzzy TOPSIS methodology offers a number of benefits. It is a more systematic method than the other fuzzy multi‐criteria decision‐making (FMCDM) methods and it is more capable of capturing a human's appraisal of ambiguity when complex multi‐criteria decision‐making problems are considered. The hierarchical fuzzy TOPSIS is superior to the other FMCDM methods, such as fuzzy analytic hierarchy process (FAHP) and classical fuzzy TOPSIS methods, since the hierarchical structure without making pairwise comparisons among criteria, sub‐criteria, and alternatives is considered. Hierarchical fuzzy TOPSIS is an excellent tool to handle qualitative assessments about BPO evaluation problems, and its calculations are faster than FAHP. Also, hierarchical fuzzy TOPSIS makes it possible to take into account the hierarchical structure in the evaluation model. However, there are drawbacks. The classical fuzzy TOPSIS is a highly complex methodology and requires more numerical calculations in assessing the ranking order of the alternatives than the hierarchical fuzzy TOPSIS methodology and hence it increases the effort, thus limiting its applicability to real world problems. Originality/value – The proposed model will be very useful to managers in the manufacturing sector, as this method makes decision making easier, systematic, efficient and effective.

Journal

Information Management & Computer SecurityEmerald Publishing

Published: Jul 18, 2008

Keywords: Outsourcing; Risk analysis; Fuzzy logic; Decision making; Production processes; Turkey

References

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