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Risk assessment in IT outsourcing using fuzzy decision-making approach: An Indian perspective
Affiliation:1. Nagoya Institute of Technology, Department of Computer Science, Gokisho, Showa, Nagoya, Aichi, 466-8555, Japan;2. University of the Ryukyus, Department of Electrical Engineering, Nakagami, Nishihara, Okinawa, 903-0213, Japan;1. Department of Computer Languages and Systems, University of Seville, Av Reina Mercedes S/N, 41012 Seville, Spain;2. School of Information Systems, Computing and Mathematics, Brunel University, Uxbridge, Middlesex UB7 7NU, United Kingdom;1. School of Economics and Management, Free University of Bozen-Bolzano, Bolzano, Italy;2. Institute of Mathematics, University of Warsaw, Warszawa, Poland;3. Department “Methods and Models for Economics, Territory and Finance”, Sapienza University of Rome, Rome, Italy
Abstract:Outsourcing of Information Technology (IT) is a common practice in global business today. IT Outsourcing (ITO) refers to the contracting out of IT services (or functions) with the objective of achieving strategic advantages as well as cost benefits. Recently, many IT industries are facing daunting challenges in terms of healthy alliances on their ITO strategy due to existence of inherent risks. These risks must be recognized and properly managed towards successful establishment of effective ITO strategy. Therefore, risk assessment appears to be an important contributor to the success of an ITO venture. In this paper, a hierarchical ITO risk structure representation has been explored to develop a formal model for qualitative risk assessment. The basic parameters for defining risks have been presented including the metrics for measuring likelihood and impact that aid to achieve consistent assessment. An improved decision making method using fuzzy set theory has been attempted for converting linguistic data into numeric risk ratings. In this study, the concept of ‘Incentre of centroids method’ for generalized trapezoidal fuzzy numbers has been used to quantify the ‘degree of risk’ in terms of crisp ratings. Finally, a framework for categorizing different risk factors has been proposed on the basis of distinguished ranges of risk ratings (crisp). Consequently, an action requirement plan has been suggested for providing guidelines for the managers to successfully manage the risk in the context of ITO exercise.
Keywords:IT outsourcing  Risk assessment  Risk categorization  Fuzzy set theory  Incentre of centroids
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