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A statistical framework for strategic decision making with AHP: Probability assessment and Bayesian revision

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  • Hughes, Warren R.

Abstract

A probability assessment framework is outlined for an organizational decision involving a conditioning event (CE). The decision may, for example, involve a new-product launch (strategic decision) dependent on the outcome of market research (CE). The framework illustrates how Bayesian revision could be employed as related "news" arrives intermittently to revise current probabilities prior to decision implementation. A unique contribution of this paper is its utilization of the analytic hierarchy process to ascertain a set of consistent and coherent probabilities for the event/sample spaces at all stages of the decision process.

Suggested Citation

  • Hughes, Warren R., 2009. "A statistical framework for strategic decision making with AHP: Probability assessment and Bayesian revision," Omega, Elsevier, vol. 37(2), pages 463-470, April.
  • Handle: RePEc:eee:jomega:v:37:y:2009:i:2:p:463-470
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    References listed on IDEAS

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    1. Partovi, Fariborz Y., 2006. "An analytic model for locating facilities strategically," Omega, Elsevier, vol. 34(1), pages 41-55, January.
    2. Hauser, David & Tadikamalla, Pandu, 1996. "The Analytic Hierarchy Process in an uncertain environment: A simulation approach," European Journal of Operational Research, Elsevier, vol. 91(1), pages 27-37, May.
    3. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    4. James E. Smith & Detlof von Winterfeldt, 2004. "Anniversary Article: Decision Analysis in Management Science," Management Science, INFORMS, vol. 50(5), pages 561-574, May.
    5. Jharkharia, Sanjay & Shankar, Ravi, 2007. "Selection of logistics service provider: An analytic network process (ANP) approach," Omega, Elsevier, vol. 35(3), pages 274-289, June.
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    Cited by:

    1. Ramanathan, Usha, 2013. "Aligning supply chain collaboration using Analytic Hierarchy Process," Omega, Elsevier, vol. 41(2), pages 431-440.
    2. Peng, Yi & Kou, Gang & Wang, Guoxun & Shi, Yong, 2011. "FAMCDM: A fusion approach of MCDM methods to rank multiclass classification algorithms," Omega, Elsevier, vol. 39(6), pages 677-689, December.

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