Skip to main content
SpringerLink
Log in

Human-Centric Cognitive Decision Support System for Ill-Structured Problems

  • Chapter
  • First Online:
Human-Centric Decision-Making Models for Social Sciences

Part of the book series: Studies in Computational Intelligence ((SCI,volume 502))

Abstract

The solutions to ill-structured decision problems greatly rely upon the intuition and cognitive abilities of a decision maker because of the vague nature of such problems. To provide decision support for these problems, a decision support system (DSS) must be able to support a user’s cognitive abilities, as well as facilitate seamless communication of knowledge and cognition between itself and the user. This study develops a cognitive decision support system (CDSS) based on human-centric semantic de-biased associations (SDA) model to improve ill-structured decision support. The SDA model improves ill-structured decision support by refining a user’s cognition through reducing or eliminating bias and providing the user with validated domain knowledge. The use of semantics in the SDA model facilitates the natural representation of the user’s cognition, thus making the transfer of knowledge/cognition between the user and system a natural and effortless process. The potential of semantically defined cognition for effective ill-structured decision support is discussed from a human-centric perspective. The effectiveness of the approach is demonstrated with a case study in the domain of sales.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    The description of ill-structured decision problems is given in Sect. 2.

  2. 2.

    For the scope of this chapter, we shall refer to them as mental models.

  3. 3.

    Please refer to Nonaka’s [36] knowledge spiral model for the definition of internalization.

  4. 4.

    A model-driven DSS emphasizes access to and manipulation of financial, optimization and/or simulation models.

  5. 5.

    A data-driven DSS emphasizes access to and manipulation of a time-series of internal company data and sometimes external and real-time data.

  6. 6.

    Communication-driven DSS use network and communication technologies to facilitate decision-relevant collaboration and communication. Tools used include groupware, video conferencing, and computer-based bulletin boards.

  7. 7.

    A document-driven DSS uses computer storage and processing technologies to provide document retrieval and analysis. Documents may include scanned documents, hypertext documents, images, sounds and video.

  8. 8.

    A web-based DSS is simply a system which is implemented using web-based technologies. A web-based DSS can be any type of DSS, such as a communication-driven, model-driven or data-driven system.

  9. 9.

    AdventureWorks is a sample database which comes with SQL Server installation [1]

References

  1. AdventureWorks Database’ 2005, AdventureWorks Database, Microsoft (2011) http://msftdbprodsamples.codeplex.com/

  2. Alter, S.L.: Decision Support Systems: Current Practice and Continuing Challange, 1st edn. Addison-Wesley, Mass (1980)

    Google Scholar 

  3. Ariely, D.: Predictably Irrational: The Hidden Forces That Shape Our Decisions, 1st edn. HarperCollins, Canada (2008)

    Google Scholar 

  4. Arnott, D.: A Taxonomy of Decision Biases (Technical report. No. 2002/01) Decision support systems laboratory. Monash University, School lof Information Management and Systems, Melbourne (2002)

    Google Scholar 

  5. Barnes, J.H.: Cognitive biases and their impact on strategic planning. Strateg. Manage. J. 5(2), 129–137 (1984)

    Article  Google Scholar 

  6. Bhandari, G., Hassanein, K., Deaves, R.: Debiasing investors with decision support systems: an experimental investigation. Decis. Support Syst. 46(1), 399–410 (2008)

    Article  Google Scholar 

  7. Chandrasekaran, B.: Designing decision support systems to help avoid biases and make robust decisions, with examples from army planning. Paper presented to the proceedings of army science conference 2008

    Google Scholar 

  8. Chen, J.Q., Lee, S.M.: An exploratory cognitive DSS for strategic decision making. Decis. Support Syst. 36(2), 147–160 (2003)

    Article  Google Scholar 

  9. Craik, K.: The Nature of Explanation, 1st updated edition edn. Cambridge University Press, Cambridge (1943)

    Google Scholar 

  10. Croskerry, P.: Achieving quality in clinical decision making: cognitive strategies and detection of bias. Acad. Emer. Med. 9(11), 1184–1204 (2002)

    Article  Google Scholar 

  11. Das, T.K., Teng, B.S.: Cognitive biases and strategic decision processes: an integrative perspective. J. Manage. Stud. 36(6), 757–778 (1999)

    Article  Google Scholar 

  12. Feldman, S.: NLP meets the jabberwocky: natural language processing in information (1999) Retrieval, http://www.scism.lsbu.ac.uk/inmandw/ir/jaberwocky.htm

  13. Ferguson, R.L., Jones, C.H.: A computer aided decision system. Manage. Sci. 15(10), 550–562 (1969)

    Google Scholar 

  14. Fujita, H., Hakura, J., Kurematsu, M.: Virtual doctor system (VDS): medical decision reasoning based on physical and mental ontologies. Paper presented to the proceedings of the 23rd international conference on industrial engineering and other applications of applied intelligent systems—Volume Part III. Cordoba, Spain, 2010

    Google Scholar 

  15. Gorini, A., Pravettoni, G.: An overview on cognitive aspects implicated in medical decisions. European J. Intern. Med. 22(6), 547–553 (2011)

    Article  Google Scholar 

  16. Greeno, J.G.: Natures of problem-solving abilities. In: Handbook of Learning and Cognitive Processes: V, pp. 239–270. Human information, Lawrence Erlbaum, Oxford (1978)

    Google Scholar 

  17. Grief, I.: Computer-supported cooperative work: A book of readings, vol. 1, 1st edn. Morgan Kaufmann Publishers, Inc., San Mateo (1988)

    Google Scholar 

  18. Hicks, E.P., Kluemper, G.T.: Heuristic reasoning and cognitive biases. Am. J. Orthod. and Dentofac. Orthop. 139(3), 297–304 (2011)

    Article  Google Scholar 

  19. Hilbert, M.: Toward a synthesis of cognitive biases: how noisy information processing can bias human decision making. Psychol. Bull. 138, 211–237 (2012)

    Article  Google Scholar 

  20. Hodgkinson, G.P., Bown, N.J., Maule, A.J., Glaister, K.W., Pearman, A.D.: Breaking the frame: an analysis of strategic cognition and decision making under uncertainty. Strateg. Manage. J. 20(10), 977–985 (1999)

    Article  Google Scholar 

  21. Janser, M.J.: Army War College. Senior Service College Fellowship, P., Center for, S. and International, S: Cognitive biases in military decision making. Army War College, U.S. (2007)

    Google Scholar 

  22. Johnson-Laird, P.: The history of mental models. In: Manktelow, K., Chung, M.C. (eds.) Psychology of Reasoning: Theoretical And Historical Perspectives, p. 382. Psychology Press, New York (2004)

    Google Scholar 

  23. Johnson-Laird, P.N.: Mental models: Towards a Cognitive Science of language, inference, and Consciousness. Harvard University Press, Cambridge (1983)

    Google Scholar 

  24. Kahneman, D., Lovallo, D., Sibony, O.: The big idea: before you make that big decision. Harvard Bus. Rev. 89, 50–60 (2011)

    Google Scholar 

  25. Kahneman, D., Tversky, A.: Subjective probability: a judgment of representativeness. Cogn. Psychol. 3(3), 430–454 (1972)

    Article  Google Scholar 

  26. Korte, R.F.: Biases in decision making and implications for human resource development. Adv. Develop. Hum. Resources 5(4), 440–457 (2003)

    Article  Google Scholar 

  27. Krause, T.R., Hidley, J.H.: Protecting your decision making from cognitive bias. In: Taking the Lead in Patient Safety, pp. 149–176. John Wiley & Sons, Inc., New York (2008)

    Google Scholar 

  28. Liddy, E.D.: Enhanced text retrieval using natural language processing. Bull. Am. Soc. Inform. Sci. Technol. 24(4), 14–16 (1998)

    Article  Google Scholar 

  29. Lucas, H.C.: Computer-Based Information Systems in Organization. Science Research Associates, Chicago (1973)

    Google Scholar 

  30. Lucchiari, C., Pravettoni, G.: Cognitive balanced model: a conceptual scheme of diagnostic decision making. J. Eval. Clin. Pract. 18(1), 82–88 (2012)

    Article  Google Scholar 

  31. Maqsood, T., Finegan, A.D., Walker, D.H.T.: Biases and heuristics in judgment and decision making: the dark side of tacit knowledge. Issues Inform. Sci. Inform. Technol. 1, 295–301 (2004)

    Google Scholar 

  32. Memon, T., Lu, J., Hussain, F. K.: Semantic de-biased associations (SDA) model to improve ill-structured decision support. In: Huang, T., Zeng, Z., Li, C., Leung, C. (eds.), Neural Information Processing. Lecture notes in computer science, vol. 7664, Springer berlin heidelberg, 483–490 (2012)

    Google Scholar 

  33. Mintzberg, H.: The Nature of Managerial Work. Harper and Row, New York (1973)

    Google Scholar 

  34. Nemati, H.R., Steiger, D.M., Iyer, L.S., Herschel, R.T.: Knowledge warehouse: an architectural integration of knowledge management, decision support, artificial intelligence and data warehousing. Decis. Support Syst. 33, 143–161 (2002)

    Article  Google Scholar 

  35. Niu, L., Lu, J., Zhang, G.: Cognition-driven decision support for business intelligence, SpringerLink, Heidelberg (2009)

    Google Scholar 

  36. Nonaka, I.: The knowledge-creating company. Harvard Bus. Rev. 69, 96–104 (1991)

    Google Scholar 

  37. Pedrycz, W., Gomide, F.: Fuzzy Systems Engineering: Towards human-centric computing, John Wiley & Sons, Inc., United states (2007)

    Google Scholar 

  38. Pervan, G., Arnott, D., Dodson, G.: Trends in the study of group support systems, In: Proceedings of Group Decision and Negotiation 2005. INFORMS/University of Vienna, Vienna, 2005

    Google Scholar 

  39. Power, D.J.: A Brief History of Decision Support Systems. DSS, DSSResources.com, viewed Oct 2, 2009 http://dss.cba.uni.edu/dss/dsshistory.html (1999). Version 2.8, 31 May 2003

  40. Power, D.J.: Decision support systems: A historical overview. In: Handbook on Decision Support Systems 1, vol. 1. Springer Berlin, Heidelberg (2008)

    Google Scholar 

  41. Rentsch, J.R., Hall, R.J.: Members of great teams think alike: A model of team effectiveness and schema similarity among team members. In: Beyerlein, M.M., Johnson, D.A. (eds.), Advances in interdisciplinary studies of work teams: Theories of self-managing work teams, vol. 1, Elsevier Science/JAI Press, (1994)pp. 223–261.

    Google Scholar 

  42. Rentsch, J.R., Klimoski, R.J.: Why do ‘great minds’ think alike?: antecedents of team member schema agreement. J. Organ. Beh. 22(2), 107–120 (2001)

    Article  Google Scholar 

  43. Schwenk, C.R.: The cognitive perspective on strategic decision making. J. Manage. Stud. 25(1), 41–55 (1988)

    Article  MathSciNet  Google Scholar 

  44. Scottmorton, M.S.: Management Decision Systems—Computer-Based Support for Decision Making—Morton, MSS. Sloan Manage. Rev. 12(3), 103–104 (1971)

    Google Scholar 

  45. Simon, H.A.: The structure of ill structured problems. Artif. Intell. 4(3–4), 181–201 (1973)

    Article  Google Scholar 

  46. Simon, H.A.: Information-processing theory of human problem solving. In: Estes, W.K. (ed.) Handbook of Learning and cognitive Process, p. 318. Lawrence Erlbaum, HIllsdale (1978)

    Google Scholar 

  47. Simon, H.A., Newell, A.: Heuristic problem solving: the next advance in operations research. Oper. Res. 6(1), 1 (1958)

    Article  Google Scholar 

  48. Swanson, E.B., Culnan, M.J.: Document-based systems for management planing and control: a classification, survey, and assessment. MIS Q. 2(4), 31–46 (1978)

    Article  Google Scholar 

  49. Tversky, A., Kahneman, D.: Judgment under uncertainty: heuristics and biases. Science 185(4157), 1124–1131 (1974)

    Article  Google Scholar 

  50. Tversky, A., Kahneman, D.: The framing of decisions and the psychology of choice. Science 211(4481), 453–458 (1981)

    Article  MathSciNet  MATH  Google Scholar 

  51. Ubel, P.A., Smith, D.M., Zikmund-Fisher, B.J., Derry, H.A., McClure, J., Stark, A., Wiese, C., Greene, S., Jankovic, A., Fagerlin, A.: Testing whether decision aids introduce cognitive biases: results of a randomized trial. Patient Educ. Couns. 80(2), 158–163 (2010)

    Article  Google Scholar 

  52. Vosniadou, S.: Mental models in conceptual development. In: Magnani, L., Nersessian, N. (eds.) Model-Based Reasoning: Science, Technology, Values. Springer, New York (2002)

    Google Scholar 

  53. Yadav, S.B., Khazanchi, D.: Subjective understanding in strategic decision making: an information systems perspective. Decis. Support Syst. 8(1), 55–71 (1992)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. The Decision Systems and e-Service Intelligence (DeSI) Laboratory, The Centre for Quantum Computation and Intelligent Systems (QCIS), School of Software, Faculty of Engineering and Information Technology, University of Technology, Sydney, NSW, Australia

    Tasneem Memon, Jie Lu & Farookh Khadeer Hussain

Authors
  1. Tasneem Memon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jie Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Farookh Khadeer Hussain
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tasneem Memon .

Editor information

Editors and Affiliations

  1. Faculty of Business Administration, Yokohama National University, Yokohama, Japan

    Peijun Guo

  2. Department of Electrical & Computer Engineering, University of Alberta, Edmonton, Alberta, Canada

    Witold Pedrycz

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Memon, T., Lu, J., Hussain, F.K. (2014). Human-Centric Cognitive Decision Support System for Ill-Structured Problems. In: Guo, P., Pedrycz, W. (eds) Human-Centric Decision-Making Models for Social Sciences. Studies in Computational Intelligence, vol 502. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39307-5_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-39307-5_12

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39306-8

  • Online ISBN: 978-3-642-39307-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation