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A communication mix for an event planning: a linear quadratic approach

  • Alessandra Buratto

    ()

  • Luca Grosset

    ()

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    The communication mix is a relevant decision issue for an organization that plans the advertising campaign for a fixed future event. It is assumed that the objectives of the organization are to minimize the cost of the advertising campaign and to drive the final demand as close as possible to a target value. Two different advertising channels are available: the first affects deterministically the consumers’ demand, whereas the second presents some stochastic aspects which are out of decision-maker’s control. Some recent mathematical developments on the stochastic linear quadratic control problem allow to formulate and solve some interesting instances of the problem. A comparative analysis of the efficiency of deterministic and stochastic controls is done and the optimal feedback policies are discussed. The trade-off between efficiency and risk of an advertising channel is essential to understand the features of the optimal solutions. Copyright Physica-Verlag 2006

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    File URL: http://hdl.handle.net/10.1007/s10100-006-0002-y
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    Article provided by Springer & Slovak Society for Operations Research & Hungarian Operational Research Society & Czech Society for Operations Research & Österr. Gesellschaft für Operations Research (ÖGOR) & Slovenian Society Informatika - Section for Operational Research & Croatian Operational Research Society in its journal Central European Journal of Operations Research.

    Volume (Year): 14 (2006)
    Issue (Month): 3 (September)
    Pages: 247-259

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    Handle: RePEc:spr:cejnor:v:14:y:2006:i:3:p:247-259
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    1. Luca Grosset & Bruno Viscolani, 2004. "Advertising for a new product introduction: A stochastic approach," TOP- An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 12(1), pages 149-167, June.
    2. Gustav Feichtinger & Richard F. Hartl & Suresh P. Sethi, 1994. "Dynamic Optimal Control Models in Advertising: Recent Developments," Management Science, INFORMS, vol. 40(2), pages 195-226, February.
    3. S. Illeris & G. Akehurst, 2002. "Introduction," The Service Industries Journal, Taylor & Francis Journals, vol. 22(1), pages 1-3, January.
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