Fuzzy Causal Maps in Business Modeling and Performance-Driven Process Re-engineering

Despite the rhetoric surrounding performance-driven change (PDC), articulated mechanisms that support intelligent reasoning on the effect of the re-design activities to the performance of a business model are still emerging. This paper describes an attempt to build and operate such a reasoning mechanism as a decision support supplement to PDC exercises. Fuzzy Cognitive Maps (FCMs) are employed as the underlying performance modeler in order to simulate the operational efficiency of complex and imprecise functional relationships and quantify the impact of process re-engineering activities to the business model. Preliminary experiments indicate that the proposed hierarchical and dynamic network of interconnected FCMs forms a sound support aid for establishing performance quantifications that supplement the strategic planning and business analysis phases of typical PDC projects.

[1]  Wenhua Wang,et al.  A‐pool: An agent‐oriented open system shell for distributed decision process modeling , 1994 .

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

[3]  Thomas J. Crowe,et al.  Quantitative risk level estimation of business process reengineering efforts , 2002, Bus. Process. Manag. J..

[4]  Michalis Glykas,et al.  Critical review of existing BPR methodologies: The need for a holistic approach , 1999, Bus. Process. Manag. J..

[5]  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..

[6]  C.E. Pelaez,et al.  Applying fuzzy cognitive-maps knowledge-representation to failure modes effects analysis , 1995, Annual Reliability and Maintainability Symposium 1995 Proceedings.

[7]  Robert T. Jones,et al.  Matching process choice and uncertainty: Modeling quality management , 2002, Bus. Process. Manag. J..

[8]  Voula C. Georgopoulos,et al.  Introducing the theory of fuzzy cognitive maps in distributed systems , 1997, Proceedings of 12th IEEE International Symposium on Intelligent Control.

[9]  Kun Chang Lee,et al.  Strategic Planning Simulation Based on Fuzzy Cognitive Map Knowledge and Dif ferential Game , 1998, Simul..

[10]  Zhi-Qiang Liu Fuzzy Cognitive Maps: Analysis and Extensions , 2000 .

[11]  Thomas F. Burgess,et al.  Modelling the impact of reengineering with system dynamics , 1998 .

[12]  Karl Perusich,et al.  Fuzzy cognitive maps for policy analysis , 1996, 1996 International Symposium on Technology and Society Technical Expertise and Public Decisions. Proceedings.

[13]  Michalis Glykas,et al.  A case study on reengineering manufacturing processes and structures , 2000 .

[14]  Michalis Glykas,et al.  A fuzzy cognitive map approach to support urban design , 2004, Expert Syst. Appl..

[15]  Jonathan H. Klein,et al.  Cognitive Maps of Decision-Makers in a Complex Game , 1982 .

[16]  Kun Chang Lee,et al.  A Fuzzy Cognitive Map‐Based Bi‐Directional Inference Mechanism: An Application to Stock Investment Analysis , 1997 .

[17]  Kee-Young Kwahk,et al.  Supporting business process redesign using cognitive maps , 1999, Decis. Support Syst..

[18]  Christer Carlsson,et al.  DSS: directions for the next decade , 2002, Decis. Support Syst..

[19]  Mary Ann Murray,et al.  Nonlinearity as a tool for business process reengineering , 2000, Bus. Process. Manag. J..

[20]  Xiaoou Li,et al.  Adaptive fuzzy petri nets for dynamic knowledge representation and inference , 2000 .

[21]  Kun Chang Lee,et al.  Fuzzy cognitive map approach to web-mining inference amplification , 2002, Expert Syst. Appl..

[22]  Masafumi Hagiwara,et al.  Extended fuzzy cognitive maps , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[23]  A. Kandel,et al.  Constructing fuzzy cognitive maps , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

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

[25]  Robert O. Briggs,et al.  A model of cognitive information retrieval for ill-structured managerial problems and its benefits for knowledge acquisition , 1994, 1994 Proceedings of the Twenty-Seventh Hawaii International Conference on System Sciences.

[26]  Fu-Ren Lin,et al.  A generic structure for business process modeling , 2002, Bus. Process. Manag. J..

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

[28]  Paul Harmon,et al.  Expert systems: artificial intelligence in business , 1985 .

[29]  Bill Karakostas,et al.  The use of fuzzy cognitive maps to simulate the information systems strategic planning process , 1999, Inf. Softw. Technol..

[30]  Zhi-Qiang Liu,et al.  Contextual fuzzy cognitive map for decision support in geographic information systems , 1999, IEEE Trans. Fuzzy Syst..

[31]  Shinhong Kim,et al.  A case-based reasoning approach to cognitive map-driven tacitknowledge management , 2000 .

[32]  P. C. Silva New forms of combined matrices in fuzzy cognitive maps , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[33]  J. Philip Craiger,et al.  Modeling Organizational Behavior With Fuzzy Cognitive Maps , 1996 .

[34]  Kun Chang Lee,et al.  A Strategic Planning Simulation Based on Cognitive Map Knowledge and Differential Game , 1999 .

[35]  Kostas S. Metaxiotis,et al.  Integrating fuzzy logic into decision suppport systems: current research and future prospects , 2003, Inf. Manag. Comput. Secur..