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Dynamic MCDM, Habitual Domains and Competence Set Analysis for Effective Decision Making in Changeable Spaces

In: Trends in Multiple Criteria Decision Analysis

Author

Listed:
  • Po-Lung Yu

    (National Chiao Tung University
    University of Kansas)

  • Yen-Chu Chen

    (National Chiao Tung University)

Abstract

This chapter introduces the behavior mechanism that integrates the discoveries of neural science, psychology, system science, optimization theory and multiple criteria decision making. It shows how our brain and mind works and describes our behaviors and decision making as dynamic processes of multicriteria decision making in changeable spaces. Unless extraordinary events occur or special effort exerted, the dynamic processes will be stabilized in certain domains, known as habitual domains. Habitual domains and their expansion and enrichment, which play a vital role in upgrading the quality of our decision making and lives, will be explored. In addition, as important consequential derivatives, concepts of competence set analysis, innovation dynamics and effective decision making in changeable spaces will also be introduced.

Suggested Citation

  • Po-Lung Yu & Yen-Chu Chen, 2010. "Dynamic MCDM, Habitual Domains and Competence Set Analysis for Effective Decision Making in Changeable Spaces," International Series in Operations Research & Management Science, in: Matthias Ehrgott & José Rui Figueira & Salvatore Greco (ed.), Trends in Multiple Criteria Decision Analysis, chapter 0, pages 1-35, Springer.
    • Handle: RePEc:spr:isochp:978-1-4419-5904-1_1
    DOI: 10.1007/978-1-4419-5904-1_1
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    Citations

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    Cited by:

    1. Chi-Yo Huang & Jih-Jeng Huang & You-Ning Chang & Yen-Chu Lin, 2021. "A Fuzzy-MOP-Based Competence Set Expansion Method for Technology Roadmap Definitions," Mathematics, MDPI, vol. 9(2), pages 1-26, January.
    2. Zhan, Yuanzhu & Tan, Kim Hua, 2020. "An analytic infrastructure for harvesting big data to enhance supply chain performance," European Journal of Operational Research, Elsevier, vol. 281(3), pages 559-574.
    3. T. Q. Bao & B. S. Mordukhovich & A. Soubeyran, 2015. "Variational Analysis in Psychological Modeling," Journal of Optimization Theory and Applications, Springer, vol. 164(1), pages 290-315, January.
    4. Xinwei Ye & Lei Ma & Junwen Feng & Yang Cheng & Zheng Liu, 2018. "Impact of Technology Habitual Domain on Ambidextrous Innovation: Case Study of a Chinese High-Tech Enterprise," Sustainability, MDPI, vol. 10(12), pages 1-21, December.
    5. Paweł Ziemba, 2022. "Energy Security Assessment Based on a New Dynamic Multi-Criteria Decision-Making Framework," Energies, MDPI, vol. 15(24), pages 1-18, December.

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