Multi-product dynamic advertisement planning in a segmented market
DOI:
https://doi.org/10.2298/YJOR170117016AKeywords:
media planning, segmented market, multiple products, cross-product effect, retention factor, dynamic modelAbstract
In this paper, a dynamic multi-objective linear integer programming model is proposed to optimally distribute a firm’s advertising budget among multiple products and media in a segmented market. To make the media plan responsive to the changes in the market, the distribution is carried out dynamically by dividing the planning horizon into smaller periods. The model incorporates the effect of the previous period advertising reach on the current period (taken through retention factor), and it also considers cross-product effect of simultaneously advertising different products. An application of the model is presented for an insurance firm that markets five different products, using goal programming approach.References
Gensch, D.H., "Media factors: A review article", Journal of Marketing Research, 7 (2) (1970) 216–225.
Higgins, J.C., "Some applications of operational research in advertising", European Journal of Marketing, 7 (3) (1973) 166–175.
Reid, L.N., King, K.W., Martin, H.J., and Soh, H., "Local advertising decision maker’s perceptions of media effectiveness and substitutability", Journal of Media Economics, 18 (1) (1993) 35–53.
Dou, W., Wang, G., and Zhou, N., "Generational and regional differences in media consumption patterns of Chinese generation X consumers", Journal of Advertising, 35 (2) (2006) 101–110.
Kotler, P., Keller, P., Koshy, A., and Jha, M., Management-A South Asian Perspective. Dorling Kindersley (India) Pvt. Ltd. Licensees of Pearson Education in South Asia, India, 2009.
Beltran-Royo, C., Zhang, H., Blanco, L.A., and Almagro, J., "Multistage multiproduct advertising budgeting", European Journal of Operational Research, 225 (1) (2013) 179–188.
Bass, F.M., and Lonsdale, R.T., "An exploration of linear programming in media selection", Journal of Marketing Research, 3 (2) (1966) 179–188.
Charnes, A., Cooper, W.W., De Voe, J.K., Learner, D.B., and Reinecke, W., "A goal programming model for media planning", Management Science, 14 (8) (1968) B-423.
Wiedey, G., and Zimmermann, H.J., "Media selection and fuzzy linear programming", Journal of Operational Research Society, 29 (11) (1978) 1071–1084.
De Kluyver, C.A., "An exploration of various goal programming formulations with application to advertising media scheduling", Journal of Operational Research Society, 30 (2) (1979) 167–171.
Basu, A.K., and Batra, R., "ADSPLIT: a multi-brand advertising budget allocation model", Journal of Advertising, 17 (2) (1988) 44–51.
Doyle, P., and Saunders, J., "Multiproduct advertising budgeting", Marketing Science, 9 (2) (1990) 97–113.
Nowak, G.J., Cameron, G.T., and Krugman, D.M., "How local advertisers choose and use advertising media", Journal of Advertising Research, 33 (6) (1993) 39–49.
Danaher, P.J., and Rust, R.T., "Determining the optimal return on investment for an advertising campaign", European Journal of Operational Research, 95 (3) (1996) 511–521.
Fruchter, G.E., and Kalish, S., "Dynamic promotional budgeting and media allocation", European Journal of Operational Research, 111 (1) (1998) 15–27.
Rojas, C. and Peterson, E.B., "Demand for differentiated products: Price and advertising evidence from the US beer market", International Journal of Industrial Organization, 26 (1) (2008) 288–307.
Hsu, T.H., Tsai, T.N., and Chiang, P.L., "Selection of the optimum promotion mix by integrating a fuzzy linguistic decision model with genetic algorithms", Information Sciences, 179 (1) (2009) 41–52.
Albadvi, A., and Koosha, H., "A robust optimization approach to allocation of marketing budgets", Management Decision, 49 (4) (2011) 601–621.
Bhattacharya, U.K., "A chance constraints goal programming model for the advertising planning problem", European Journal of Operational Research, 192 (2) (2009) 382–395.
Jha, P.C., Aggarwal, R., and Gupta, A., "Optimal media planning for multi-products in segmented market", Applied Mathematics and Computation, 217 (16) (2009) 6802–6818.
Aggarwal, S., Kaul, A., Gupta, A., and Jha, P.C., "Multi Period Advertising Media Selection in a Segmented Market", in Advances in Intelligent Systems and Computing (ed: M. Pant, Kusum Deep, Atul Nagar and Jagdish Bansals), Springer, Singapore, 905-928, 2014.
Beltran-Royo, C., Escudero, L.F., and Zhang, H., "Multi period Multi product Advertising Budgeting Part II: Stochastic Optimization Modeling", Omega, 59 (PA) (2016) 26-39.
Schniederjans, M., Goal Programming: Methodology and Applications. Springer Science Business Media, Massachusetts, 1995.
Khan, S.A., and Baqer, M., "Goal programming approach for multi-criteria decision-making for an energy efficient event recognition scheme", in Computational Intelligence in Multi-Criteria Decision-Making (MCDM), 2013, IEEE Symposium on, IEEE Chicago, 56-60, 2013.
Georion, A.M., "Proper Efficiency and Theory of Vector Maximization", Journal of Mathematical Analysis and Applications, 22 (1968) 618–630.
Jha, P.C., Aggarwal, S., Gupta, A., and Sarker, R., "Multi-criteria media mix decision model for advertising a single product with segment specific and mass media", Journal of Industrial and Management Optimization, 12 (4) (2016) 1367–1389.
Belgaonkar, P.J., and Dash, M., "Comparative Effectiveness of Radio, Print Web Advertising", Asia Pacific Journal of Marketing and Management Review, 2 (7) (2013) 12–19.
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