IDEAS home Printed from https://ideas.repec.org/a/wsi/ijitdm/v11y2012i02ns0219622012400111.html
   My bibliography  Save this article

Empower Mcdm By Habitual Domains To Solve Challenging Problems In Changeable Spaces

Author

Listed:
  • YEN-CHU CHEN

    (Department of Information Management, Hsiuping University of Science and Technology, 11 Gongye Rd, Dali Dist., Taichung City, Taiwan)

  • HUNG-SHUN HUANG

    (Institute of Information Management, National Chiao Tung University, 1001, Ta Hsueh Road, HsinChu City, Taiwan)

  • PO-LUNG YU

    (Institute of Information Management, National Chiao Tung University, 1001, Ta Hsueh Road, HsinChu City, Taiwan;
    School of Business, University of Kansas Lawrence, Kansas, USA)

Abstract

Challenging decision problems in changeable spaces are characterized by existence of complex decision parameters that are changing with time and situations, including criteria and alternatives. Some of these parameters may be critical for their effective solutions, but hidden in the depth of potential domains. In this rapidly changing world, including technology and attitude, without paying attention to the problems in changeable spaces, we could easily commit serious mistakes due to decision blinds, decision traps and/or decision shocks. The article starts with a brief description of the evolution of MCDM toward challenging problems in changeable spaces. Then it briefly sketches a dynamic human behavior mechanism and habitual domain theory which provide an effective list for us to search relevant decision parameters and pave the way for latter discussion. Competence set analysis, derived from habitual domain, is then introduced to exemplify decision blinds, decision traps and decision shocks in challenging decision problems. Checking lists and methods for discovering blinds and traps and for dealing with shocks are also provided. Innovation dynamics, a systematic network of thoughts, is introduced to further look out relevant key parameters in dynamic challenging problems. The related academic subjects in each link of the innovation dynamics are also explained, which allow us to see the complexity and interconnectivities among different challenging problems in changeable spaces. Finally we introduce three habitual domain tool boxes to empower ourselves to expand and enrich our thoughts into the depth of the potential domains of the challenging problems, which allows us to more effectively identify hidden parameters, problems and competence sets to reduce decision blinds, avoid decision traps and solve the problems, or dissolve the problems before they occur.

Suggested Citation

  • Yen-Chu Chen & Hung-Shun Huang & Po-Lung Yu, 2012. "Empower Mcdm By Habitual Domains To Solve Challenging Problems In Changeable Spaces," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 11(02), pages 457-490.
  • Handle: RePEc:wsi:ijitdm:v:11:y:2012:i:02:n:s0219622012400111
    DOI: 10.1142/S0219622012400111
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219622012400111
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S0219622012400111?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yong Shi, 2001. "Multiple Criteria and Multiple Constraint Levels Linear Programming:Concepts, Techniques and Applications," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 4000, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ming Hung Lin & Mei Hua Huang & Wan Chun Hsiung, 2014. "The Learning Feature of Deep Knowledge and Its Relationship With Exercise," SAGE Open, , vol. 4(2), pages 21582440145, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wikil Kwak & Yong Shi & Gang Kou, 2012. "Bankruptcy prediction for Korean firms after the 1997 financial crisis: using a multiple criteria linear programming data mining approach," Review of Quantitative Finance and Accounting, Springer, vol. 38(4), pages 441-453, May.
    2. Yong Shi & Yi Peng & Gang Kou & Zhengxin Chen, 2005. "Classifying Credit Card Accounts For Business Intelligence And Decision Making: A Multiple-Criteria Quadratic Programming Approach," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 4(04), pages 581-599.
    3. K.-J. Tseng & Y.-H. Liu & Jow-Fei Ho, 2008. "An Efficient Algorithm For Solving A Quadratic Programming Model With Application In Credit Card Holders' Behavior," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 7(03), pages 421-430.
    4. Jing He & Xiantao Liu & Yong Shi & Weixuan Xu & Nian Yan, 2004. "Classifications Of Credit Cardholder Behavior By Using Fuzzy Linear Programming," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 3(04), pages 633-650.
    5. Gang Kou & Yi Peng & Yong Shi & Morgan Wise & Weixuan Xu, 2005. "Discovering Credit Cardholders’ Behavior by Multiple Criteria Linear Programming," Annals of Operations Research, Springer, vol. 135(1), pages 261-274, March.
    6. Po-Lung Yu & Yen-Chu Chen, 2012. "Dynamic multiple criteria decision making in changeable spaces: from habitual domains to innovation dynamics," Annals of Operations Research, Springer, vol. 197(1), pages 201-220, August.
    7. Wasim Akram Mandal, 2023. "Bipolar Pythagorean Fuzzy Sets and Their Application in Multi-attribute Decision Making Problems," Annals of Data Science, Springer, vol. 10(3), pages 555-587, June.
    8. Muhammad Aslam & Rahila Yousaf & Sajid Ali, 2020. "Bayesian Estimation of Transmuted Pareto Distribution for Complete and Censored Data," Annals of Data Science, Springer, vol. 7(4), pages 663-695, December.
    9. Chaofang Hu & Shaoyuan Li, 2006. "Enhanced Interactive Satisfying Optimization Approach To Multiple Objective Optimization With Preemptive Priorities," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 47-63.
    10. Jianping Li & Xiaolei Sun & Fei Wang & Dengsheng Wu, 2015. "Risk integration and optimization of oil-importing maritime system: a multi-objective programming approach," Annals of Operations Research, Springer, vol. 234(1), pages 57-76, November.
    11. Xi Zhao & Yong Shi & Jongwon Lee & Heung Kee Kim & Heeseok Lee, 2014. "Customer Churn Prediction Based on Feature Clustering and Nonparallel Support Vector Machine," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 13(05), pages 1013-1027.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wsi:ijitdm:v:11:y:2012:i:02:n:s0219622012400111. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijitdm/ijitdm.shtml .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.