An integrated fuzzy DEMATEL, TOPSIS, and ELECTRE approach for evaluating knowledge transfer effectiveness with reference to GSD project outcome

The offshore/onsite teams’ knowledge transfer (KT) effectiveness is one of the key determinants for achieving the outcome of global software development (GSD) projects. In this study, the significance of offshore/onsite teams (GSD teams) KT effectiveness in GSD projects is measured through various factors: knowledge, team, technology, and organization factors. Moreover, the assessment framework for the integration of knowledge, team, technology, and organization factors for evaluating KT effectiveness in GSD projects has not been adequately available in the existing literature. For this motivation, the main objective of this study is to propose the assessment framework to evaluate offshore/onsite teams KT effectiveness with reference to GSD project outcome. For evaluating KT effectiveness of GSD teams, we have integrated three Fuzzy Multi-Criteria Decision Making (FMCDM) methodologies: (a) Fuzzy Decision Making Trial and Evaluation Laboratory Model (DEMATEL), (b) Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) and (c) Elimination Et Choix Traduisant la REaite (ELECTRE). Further, the hybridization of fuzzy DEMATEL, TOPSIS, and ELECTRE has not available in the existing literature. Based on this research gap, we have integrated fuzzy DEMATEL, TOPSIS, and ELECTRE approach for evaluating KT effectiveness of offshore/onsite teams in the context of GSD project outcome. Subsequently, the applicability and capability of proposed framework has been validated by software experts at Inowits Software Organization in India.

[1]  Ravi Kant,et al.  A hybrid approach based on fuzzy DEMATEL and FMCDM to predict success of knowledge management adoption in supply chain , 2014, Appl. Soft Comput..

[2]  Arun Kumar Sangaiah,et al.  An adaptive neuro-fuzzy approach to evaluation of team-level service climate in GSD projects , 2013, Neural Computing and Applications.

[3]  S. A. Kumar,et al.  Factors affecting the outcome of Global Software Development projects: An empirical study , 2013, 2013 International Conference on Computer Communication and Informatics.

[4]  Robert LIN,et al.  NOTE ON FUZZY SETS , 2014 .

[5]  Li-Jun Yang,et al.  An extension of ELECTRE to multi-criteria decision-making problems with multi-hesitant fuzzy sets , 2015, Inf. Sci..

[6]  Tomasz Wachowicz,et al.  Application of fuzzy TOPSIS to scoring the negotiation offers in ill-structured negotiation problems , 2015, Eur. J. Oper. Res..

[7]  Arun Kumar Sangaiah,et al.  A combined fuzzy DEMATEL and fuzzy TOPSIS approach for evaluating GSD project outcome factors , 2014, Neural Computing and Applications.

[8]  I-Shuo Chen,et al.  Using a novel conjunctive MCDM approach based on DEMATEL, fuzzy ANP, and TOPSIS as an innovation support system for Taiwanese higher education , 2010, Expert Syst. Appl..

[9]  Arun Kumar Sangaiah,et al.  An exploration of FMCDM approach for evaluating the outcome/success of GSD projects , 2013 .

[10]  Arun Kumar Sangaiah,et al.  Towards Identifying the Knowledge Codification Effects on the Factors Affecting Knowledge Transfer Effectiveness in the Context of GSD Project Outcome , 2015 .

[11]  Mehmet Sevkli,et al.  An application of the fuzzy ELECTRE method for supplier selection , 2010 .

[12]  Serhat Burmaoglu,et al.  A fuzzy hybrid MCDM approach for professional selection , 2012, Expert Syst. Appl..

[13]  Adil Baykasoglu,et al.  Integrating fuzzy DEMATEL and fuzzy hierarchical TOPSIS methods for truck selection , 2013, Expert Syst. Appl..

[14]  Gülçin Büyüközkan,et al.  A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers , 2012, Expert Syst. Appl..

[15]  Arun Kumar Sangaiah,et al.  Integrating Knowledge, Team, Technology and Organizational Factors: Mediating the Role of Knowledge Transfer Effectiveness with Reference to GSD Project Outcome , 2015 .

[16]  Cengiz Kahraman,et al.  An integrated fuzzy AHP-ELECTRE methodology for environmental impact assessment , 2011, Expert Syst. Appl..

[17]  Wei-Wen Wu,et al.  Segmenting critical factors for successful knowledge management implementation using the fuzzy DEMATEL method , 2012, Appl. Soft Comput..

[18]  Jindong Qin,et al.  An analytical solution to fuzzy TOPSIS and its application in personnel selection for knowledge-intensive enterprise , 2015, Appl. Soft Comput..

[19]  N. Anbazhagan,et al.  An ANFIS approach for evaluation of team-level service climate in GSD projects using Taguchi-genetic learning algorithm , 2015, Appl. Soft Comput..

[20]  Gwo-Hshiung Tzeng,et al.  Defuzzification within a Multicriteria Decision Model , 2003, Int. J. Uncertain. Fuzziness Knowl. Based Syst..