Fuzzy Cognitive Maps-Based IT Projects Risks Scenarios

Firms have spent billions of dollars in IT projects. Therefore, IT risk management is a critical issue. According to this context, the applied efforts to look for the correct IT implementation should be accompanied by mechanisms for managing the implementation risks. The goal is to reduce the risk of implementation failure. This paper analyzes IT projects implementation risks and the relationships between using an innovative soft computing technique called Fuzzy Cognitive Map. Through this proposal, it is possible to observe which the most relevant risks are, and, above all, which have a greater impact on the IT projects. Finally, three what-if analyses are done.

[1]  Panagiotis Chytas,et al.  Intelligent impact assessment of HRM to the shareholder value , 2008, Expert Syst. Appl..

[2]  Ayodele Mobolurin,et al.  Generating consensus fuzzy cognitive maps , 1997, Proceedings Intelligent Information Systems. IIS'97.

[3]  Kun Chang Lee,et al.  Fuzzy implications of fuzzy cognitive map with emphasis on fuzzy causal relationship and fuzzy partially causal relationship , 1998, Fuzzy Sets Syst..

[4]  J. Crisp,et al.  The Delphi method? , 1997, Nursing research.

[5]  Amin Hakim,et al.  A practical model on controlling the ERP implementation risks , 2010, Inf. Syst..

[6]  Suzanne D. Pawlowski,et al.  The Delphi method as a research tool: an example, design considerations and applications , 2004, Inf. Manag..

[7]  Jose L. Salmeron,et al.  Fuzzy modeling Enterprise Resource Planning tool selection , 2008, Comput. Stand. Interfaces.

[8]  Jiho Choi,et al.  Using fuzzy cognitive map for the relationship management in airline service , 2004, Expert Syst. Appl..

[9]  Bart Kosko,et al.  Fuzzy Engineering , 1996 .

[10]  Murray Turoff,et al.  The Delphi Method: Techniques and Applications , 1976 .

[11]  Delvin Grant,et al.  Using Fuzzy Cognitive Maps to Assess MIS Organizational Change Impact , 2005, Proceedings of the 38th Annual Hawaii International Conference on System Sciences.

[12]  Jose L. Salmeron,et al.  Benchmarking main activation functions in fuzzy cognitive maps , 2009, Expert Syst. Appl..

[13]  Voula C. Georgopoulos,et al.  A fuzzy cognitive map approach to differential diagnosis of specific language impairment , 2003, Artif. Intell. Medicine.

[14]  V. Mitchell,et al.  Problems and Risks in the Purchasing of Consultancy Services , 1994 .

[15]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[16]  David Levy,et al.  Book review: Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence by Bart Kosko (Prentice Hall 1992) , 1992, CARN.

[17]  Panagiota Spyridonos,et al.  Advanced soft computing diagnosis method for tumour grading , 2006, Artif. Intell. Medicine.

[18]  Elisabeth J. Umble,et al.  Enterprise resource planning: Implementation procedures and critical success factors , 2003, Eur. J. Oper. Res..

[19]  Henri Barki,et al.  Rethinking the Concept of User Involvement , 1989, MIS Q..

[20]  N. Dalkey,et al.  An Experimental Application of the Delphi Method to the Use of Experts , 1963 .

[21]  Tzvi Raz,et al.  Comparison of estimation methods of cost and duration in IT projects , 2009, Inf. Softw. Technol..

[22]  Ingoo Han,et al.  Fuzzy cognitive map for the design of EDI controls , 2000, Inf. Manag..

[23]  Jose L. Salmeron,et al.  Augmented fuzzy cognitive maps for modelling LMS critical success factors , 2009, Knowl. Based Syst..

[24]  Rossitza Setchi,et al.  Modelling IT projects success: Emerging methodologies reviewed , 2007 .

[25]  James Cadle,et al.  Project Management for Information Systems , 1996 .

[26]  Ralph L. Kliem,et al.  Reducing Project Risk , 1997 .

[27]  Bart Kosko,et al.  Virtual Worlds as Fuzzy Cognitive Maps , 1994, Presence: Teleoperators & Virtual Environments.

[28]  Clare Brindley,et al.  The information‐risk conundrum , 2001 .

[29]  Matthew K. O. Lee,et al.  A framework of ERP systems implementation success in China: An empirical study , 2005 .

[30]  Michalis Glykas,et al.  Fuzzy cognitive maps in business analysis and performance-driven change , 2004, IEEE Transactions on Engineering Management.

[31]  Y. Kwak,et al.  Project risk management: lessons learned from software development environment , 2004 .

[32]  Michael J. Gallivan,et al.  A framework for ex ante project risk assessment based on absorptive capacity , 2006, Eur. J. Oper. Res..

[33]  Prasad Bingi,et al.  Critical Issues Affecting an ERP Implementation , 1999, Inf. Syst. Manag..

[34]  Ben Light,et al.  A Critical Success Factors Model for ERP Implementation , 1999, IEEE Softw..

[35]  Benjamin B. M. Shao,et al.  The relationship between user participation and system success: a simultaneous contingency approach , 2000, Inf. Manag..

[36]  Louis Raymond,et al.  Project management information systems: An empirical study of their impact on project managers and project success , 2008 .

[37]  Dong-Hwan Kim,et al.  Principal-agent problem: a cognitive map approach , 2002, Electron. Commer. Res. Appl..

[38]  Yasser Saleh,et al.  An alternative model for measuring the success of IS projects: the GPIS model , 2005, J. Enterp. Inf. Manag..

[39]  Li-Min Fu.  CAUSIM: A rule-based causal simulation system , 1991, Simul..

[40]  Prasad Bingi,et al.  Critical issues affecting an ERP implementation : Entreprise computing , 1999 .

[41]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[42]  L. Richard Ye,et al.  Information technology and firm performance: Linking with environmental, strategic and managerial contexts , 1999, Inf. Manag..

[43]  Catherine Griffiths.  Assessing the risks in major IT projects , 1995 .

[44]  Witold Pedrycz,et al.  Genetic learning of fuzzy cognitive maps , 2005, Fuzzy Sets Syst..

[45]  Starr Roxanne Hiltz,et al.  The impacts of Delphi communication structure on small and medium sized asynchronous groups: preliminary results , 2003, 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the.

[46]  Michalis Glykas,et al.  Intelligent modeling of e-business maturity , 2007, Expert Syst. Appl..

[47]  Bart Kosko,et al.  Neural networks and fuzzy systems , 1998 .

[48]  Amit Konar,et al.  Reasoning and unsupervised learning in a fuzzy cognitive map , 2005, Inf. Sci..

[49]  Kweku-Muata Osei-Bryson,et al.  Generating consistent subjective estimates of the magnitudes of causal relationships in fuzzy cognitive maps , 2004, Comput. Oper. Res..

[50]  Bart Kosko,et al.  Fuzzy Cognitive Maps , 1986, Int. J. Man Mach. Stud..