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A chance constraints goal programming model for the advertising planning problem

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  • Bhattacharya, U.K.
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    Abstract

    This paper presents a model which has been designed to decide the number of advertisement in different advertising media and the optimal allocation of the budget assigned to the different media. The main objective of this problem is to maximize the reach to the desired section of people for different media within their maximum allowable budget without violating the max and min number of advertisement goals. The media have been considered as different newspapers and different channels in Televisions. Here in this article the model has been formulated in such a way that the advertisement should reach to those who are suitable for the product instead of going to those section who are not considered suitable for the product as well. A chance constrained goal programming model has been designed after considering the parameter corresponding to reach for different media as random variables. The random variables in this case has been considered as values which have known mean and standard deviations. A case for an upcoming institution who are interested to advertise for its two years Post Graduate Diploma in Management (PGDM) programme to the different newspapers and television channels has been designed to illustrate the solution methodology.

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    File URL: http://www.sciencedirect.com/science/article/B6VCT-4PV2RXM-4/2/4d605b7ea9b5d8467de18b15325088bc
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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 192 (2009)
    Issue (Month): 2 (January)
    Pages: 382-395

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    Handle: RePEc:eee:ejores:v:192:y:2009:i:2:p:382-395

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    Web page: http://www.elsevier.com/locate/eor

    Related research

    Keywords: Advertising and media planning Stochastic programming Multi-objective decision making Goal programming;

    References

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    1. Fruchter, Gila E. & Kalish, Shlomo, 1998. "Dynamic promotional budgeting and media allocation," European Journal of Operational Research, Elsevier, vol. 111(1), pages 15-27, November.
    2. A. Charnes & W. W. Cooper & R. O. Ferguson, 1955. "Optimal Estimation of Executive Compensation by Linear Programming," Management Science, INFORMS, vol. 1(2), pages 138-151, January.
    3. Aouni, Belaid & Ben Abdelaziz, Foued & Martel, Jean-Marc, 2005. "Decision-maker's preferences modeling in the stochastic goal programming," European Journal of Operational Research, Elsevier, vol. 162(3), pages 610-618, May.
    4. A. Charnes & W. W. Cooper, 1959. "Chance-Constrained Programming," Management Science, INFORMS, vol. 6(1), pages 73-79, October.
    5. A. Charnes & W. W. Cooper & D. B. Learner & E. F. Snow, 1968. "Note on an Application of a Goal Programming Model for Media Planning," Management Science, INFORMS, vol. 14(8), pages B431-B436, April.
    6. Kwak, N. K. & Lee, Chang Won & Kim, Ji Hee, 2005. "An MCDM model for media selection in the dual consumer/industrial market," European Journal of Operational Research, Elsevier, vol. 166(1), pages 255-265, October.
    7. Sang M. Lee & Edward R. Clayton, 1972. "A Goal Programming Model for Academic Resource Allocation," Management Science, INFORMS, vol. 18(8), pages B395-B408, April.
    8. A. Charnes & W. W. Cooper & J. K. Devoe & D. B. Learner & W. Reinecke, 1968. "A Goal Programming Model for Media Planning," Management Science, INFORMS, vol. 14(8), pages B423-B430, April.
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    Cited by:
    1. Beltran-Royo, C. & Zhang, H. & Blanco, L.A. & Almagro, J., 2013. "Multistage multiproduct advertising budgeting," European Journal of Operational Research, Elsevier, vol. 225(1), pages 179-188.

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