IDEAS home Printed from https://ideas.repec.org/a/wly/isacfm/v14y2006i3p129-155.html
   My bibliography  Save this article

Strategic diagnostics and management decision making: a hybrid knowledge‐based approach

Author

Listed:
  • Luiz Moutinho
  • Paulo Rita
  • Shuliang Li

Abstract

A conceptual model is introduced whereby the focus is placed on environmental scanning, diagnostics and decision‐making on the basis of managerial judgement through the application of tools such as intelligent agents, hybrid intelligent systems, scenario analysis and knowledge‐based systems. The model has a critical stage as an antecedent to the strategic advice that encompasses the issues of strategic fit to purpose (theme, industry, company and strategic business unit‐driven). A number of applications dealing with these four layers are shown, as well as an illustration of hybrid intelligent systems for strategic marketing planning. Copyright © 2007 John Wiley & Sons, Ltd.

Suggested Citation

  • Luiz Moutinho & Paulo Rita & Shuliang Li, 2006. "Strategic diagnostics and management decision making: a hybrid knowledge‐based approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 14(3), pages 129-155, July.
  • Handle: RePEc:wly:isacfm:v:14:y:2006:i:3:p:129-155
    DOI: 10.1002/isaf.281
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/isaf.281
    Download Restriction: no

    File URL: https://libkey.io/10.1002/isaf.281?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
    ---><---

    References listed on IDEAS

    as
    1. Gary L. Lilien & Arvind Rangaswamy & Gerrit H. Van Bruggen & Katrin Starke, 2004. "DSS Effectiveness in Marketing Resource Allocation Decisions: Reality vs. Perception," Information Systems Research, INFORMS, vol. 15(3), pages 216-235, September.
    2. Cowan, Robin, 2001. "Expert systems: aspects of and limitations to the codifiability of knowledge," Research Policy, Elsevier, vol. 30(9), pages 1355-1372, December.
    3. Patricia M. West & Patrick L. Brockett & Linda L. Golden, 1997. "A Comparative Analysis of Neural Networks and Statistical Methods for Predicting Consumer Choice," Marketing Science, INFORMS, vol. 16(4), pages 370-391.
    4. Levy, Joshua B. & Yoon, Eunsang, 1995. "Modeling global market entry decision by fuzzy logic with an application to country risk assessment," European Journal of Operational Research, Elsevier, vol. 82(1), pages 53-78, April.
    5. Mark P. Sharfman & James W. Dean Jr, 1997. "Flexibility in Strategic Decision Making: Informational and Ideological Perspectives," Journal of Management Studies, Wiley Blackwell, vol. 34(2), pages 191-217, March.
    6. Gerrit H. van Bruggen & Ale Smidts & Berend Wierenga, 1998. "Improving Decision Making by Means of a Marketing Decision Support System," Management Science, INFORMS, vol. 44(5), pages 645-658, May.
    7. Levin, Nissan & Zahavi, Jacob & Olitsky, Morris, 1995. "AMOS -- A probability-driven, customer-oriented decision support system for target marketing of solo mailings," European Journal of Operational Research, Elsevier, vol. 87(3), pages 708-721, December.
    Full references (including those not matched with items on IDEAS)

    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. Clayton Arlen Looney & Andrew M. Hardin, 2009. "Decision Support for Retirement Portfolio Management: Overcoming Myopic Loss Aversion via Technology Design," Management Science, INFORMS, vol. 55(10), pages 1688-1703, October.
    2. Shuliang Li & Jim Zheng Li, 2009. "A multi‐agent‐based hybrid framework for international marketing planning under uncertainty," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 16(3), pages 231-254, July.
    3. Yongping Bao & Ludwig Danwitz & Fabian Dvorak & Sebastian Fehrler & Lars Hornuf & Hsuan Yu Lin & Bettina von Helversen, 2022. "Similarity and Consistency in Algorithm-Guided Exploration," CESifo Working Paper Series 10188, CESifo.
    4. Ho‐Uk Lee & Jong‐Hun Park, 2008. "The Influence of Top Management Team International Exposure on International Alliance Formation," Journal of Management Studies, Wiley Blackwell, vol. 45(5), pages 961-981, July.
    5. Shao, Wei & Lye, Ashley & Rundle-Thiele, Sharyn, 2009. "Different strokes for different folks: A method to accommodate decision -making heterogeneity," Journal of Retailing and Consumer Services, Elsevier, vol. 16(6), pages 495-501.
    6. Haarhaus, Tim & Liening, Andreas, 2020. "Building dynamic capabilities to cope with environmental uncertainty: The role of strategic foresight," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    7. Kayande, U. & de Bruyn, A. & Lilien, G.L. & Rangaswamy, A. & van Bruggen, G.H., 2006. "How Feedback Can Improve Managerial Evaluations of Model-based Marketing Decision Support Systems," ERIM Report Series Research in Management ERS-2006-039-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    8. Luss, Hanan & Rosenwein, Moshe B., 1997. "Operations Research applications: Opportunities and accomplishments," European Journal of Operational Research, Elsevier, vol. 97(2), pages 220-244, March.
    9. Fabio Luis Marques dos Santos & Paolo Tecchio & Fulvio Ardente & Ferenc Pekár, 2021. "User Automotive Powertrain-Type Choice Model and Analysis Using Neural Networks," Sustainability, MDPI, vol. 13(2), pages 1-15, January.
    10. Hruschka, Harald & Fettes, Werner & Probst, Markus, 2004. "An empirical comparison of the validity of a neural net based multinomial logit choice model to alternative model specifications," European Journal of Operational Research, Elsevier, vol. 159(1), pages 166-180, November.
    11. Bengt-åke Lundvall, 2012. "One Knowledge Base or Many Knowledge Pools?," Chapters, in: Richard Arena & Agnès Festré & Nathalie Lazaric (ed.), Handbook of Knowledge and Economics, chapter 13, Edward Elgar Publishing.
    12. Aksoy, Lerzan & Cooil, Bruce & Lurie, Nicholas H., 2011. "Decision Quality Measures in Recommendation Agents Research," Journal of Interactive Marketing, Elsevier, vol. 25(2), pages 110-122.
    13. Caroli, Eve, 2007. "Internal Versus External Labour Flexibility: The Role of Knowledge Codification," National Institute Economic Review, National Institute of Economic and Social Research, vol. 201, pages 107-118, July.
    14. Ercan Özen, 2019. "The Concept of Trust in Socio-Economic Life," European Journal of Marketing and Economics Articles, Revistia Research and Publishing, vol. 2, May - Aug.
    15. Armstrong, J. Scott & Brodie, Roderick J., 1999. "Forecasting for Marketing," MPRA Paper 81690, University Library of Munich, Germany.
    16. Steven M. Ramsey & Jason S. Bergtold, 2021. "Examining Inferences from Neural Network Estimators of Binary Choice Processes: Marginal Effects, and Willingness-to-Pay," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1137-1165, December.
    17. Bioch, J.C. & Groenen, P.J.F. & Nalbantov, G.I., 2005. "Solving and interpreting binary classification problems in marketing with SVMs," Econometric Institute Research Papers EI 2005-46, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    18. Grant Samkin & Annika Schneider, 2008. "Adding scientific rigour to qualitative data analysis: an illustrative example," Qualitative Research in Accounting & Management, Emerald Group Publishing Limited, vol. 5(3), pages 207-238, October.
    19. David Opresnik & Maurizio Fiasché & Marco Taisch & Manuel Hirsch, 2017. "An evolving fuzzy inference system for extraction of rule set for planning a product–service strategy," Information Technology and Management, Springer, vol. 18(2), pages 131-147, June.
    20. Zhang, Heping, 2004. "Recursive Partitioning and Tree-based Methods," Papers 2004,30, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).

    More about this item

    Statistics

    Access and download statistics

    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:wly:isacfm:v:14:y:2006:i:3:p:129-155. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1099-1174/ .

    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.