Advertising budget allocation strategies considering uncertain consumer preferences

ZHANG Yao, ZHAO Cui, GUAN Xin

Systems Engineering - Theory & Practice ›› 2018, Vol. 38 ›› Issue (4) : 920-937.

PDF(1557 KB)
PDF(1557 KB)
Systems Engineering - Theory & Practice ›› 2018, Vol. 38 ›› Issue (4) : 920-937. DOI: 10.12011/1000-6788(2018)04-0920-18

Advertising budget allocation strategies considering uncertain consumer preferences

  • ZHANG Yao, ZHAO Cui, GUAN Xin
Author information +
History +

Abstract

With respect to the problem of advertising budget allocation considering uncertain consumer preferences, firstly, a multi-attribute utility function is used to measure the consumer utility. Secondly, the advertising response function is built to specify the relationship between advertising expenditure and consumer demand. Based on this, the consumer purchase decision model and the expected profit model of the enterprise are established, respectively. Lastly, a two-period game-theoretic model with incomplete information is built and analyzed. The outcomes show that as the uncertain degree of consumer preference information is reduced, the allocation strategy of the advertising budget is more targeted and thus to gain greater profits for the enterprise; for the consumer, only when the product that the consumer preferred can bring relatively larger profits, could he/she benefit from the advertising budget allocation. Besides, the expected profit of the enterprise increases, as the product profit increases. In addition, through further analysis of the game model, under different conditions, with increase of the product profit, the marginal profit of the enterprise gained decreases or increases.

Key words

advertising budget allocation / incomplete information dynamic game / consumer preferences / uncertainty / unobserved product attributes

Cite this article

Download Citations
ZHANG Yao , ZHAO Cui , GUAN Xin. Advertising budget allocation strategies considering uncertain consumer preferences. Systems Engineering - Theory & Practice, 2018, 38(4): 920-937 https://doi.org/10.12011/1000-6788(2018)04-0920-18

References

[1] Kwark Y, Chen J, Raghunathan S. Online product reviews:Implications for retailers and competing manufacturers[J]. Information Systems Research, 2014, 25(1):93-110.
[2] Chen Y, Xie J. Third-party product review and firm marketing strategy[J]. Marketing Science, 2005, 24(2):218-240.
[3] Lu J. Study of informative advertising competition model in duopolistic market with relative profit object[J]. Journal of Service Science and Management, 2017, 10:105-111.
[4] Hariharan V G, Talukdar D, Kwon C. Optimal targeting of advertisement for new products with multiple consumer segments[J]. International Journal of Research in Marketing, 2015, 32(3):263-271.
[5] Chan S L, Ip W H, Cho V. A model for predicting customer value from perspectives of product attractiveness and marketing strategy[J]. Expert Systems with Applications, 2010, 37(2):1207-1215.
[6] Chan S L, Ip W H. A dynamic decision support system to predict the value of customer for new product development[J]. Decision Support Systems, 2011, 52(1):178-188.
[7] 卜祥智, 赵泉午, 黄庆, 等. 易逝商品最优广告投入与订货策略的博弈分析[J]. 系统工程理论与实践, 2004, 24(11):100-105.Bu X Z, Zhao Q W, Huang Q, et al. Game analysis of optimal advertising investment and order policy for perishable goods[J]. Systems Engineering-Theory & Practice, 2004, 24(11):100-105.
[8] Bigne J E. Advertising budget practices:A review[J]. Journal of Current Issues & Research in Advertising, 1995, 17(2):17-31.
[9] 罗卫, 张子刚, 欧阳明德. 基于一个博弈论方法的简单供应链合作广告模型[J]. 系统工程理论与实践, 2004, 24(2):31-36.Luo W, Zhang Z G, Ouyang M D. Co-op advertising models in simple supply chain based on a game theory approach[J]. Systems Engineering-Theory & Practice, 2004, 24(2):31-36.
[10] Fischer M, Albers S, Wagner N, et al. Practice prize winner-dynamic marketing budget allocation across countries, products, and marketing activities[J]. Marketing Science, 2011, 30(4):568-585.
[11] Yang Y, Zeng D, Yang Y, et al. Optimal budget allocation across search advertising markets[J]. INFORMS Journal on Computing, 2015, 27(2):285-300.
[12] Pun H, Heese H S. A note on budget allocation for market research and advertising[J]. International Journal of Production Economics, 2015, 166:85-89.
[13] Dorfman R, Steiner P O. Optimal advertising and optimal quality[J]. The American Economic Review, 1954, 44(5):826-836.
[14] Hanssens D M, Parsons L J, Schultz R L. Market response models:Econometric and time series analysis[M]. 2nd ed. Boston:Kluwer Academic Publishers, 2001.
[15] Bass F M, Krishnamoorthy A, Prasad A, et al. Advertising competition with market expansion for finite horizon firms[J]. Journal of Industrial and Management Optimization, 2005, 1(1):1-19.
[16] 齐洁, 汪定伟. 广告竞争模型的最优控制策略研究[J]. 系统工程理论与实践, 2007, 27(1):39-44.Qi J, Wang D W. Optimal control strategies for an advertising competing model[J]. Systems Engineering-Theory & Practice, 2007, 27(1):39-44.
[17] Rajiv S, Dutta S, Dhar S K. Asymmetric store positioning and promotional advertising strategies:Theory and evidence[J]. Marketing Science, 2002, 21(1):74-96.
[18] Erickson G M. Dynamic models of advertising competition[M]. 2nd ed. Norwell:Kluwer Academic Publishers, 2003.
[19] Doyle P, Saunders J. Multiproduct advertising budgeting[J]. Marketing Science, 1990, 9(2):97-113.
[20] Chintagunta P K. Investigating the sensitivity of equilibrium profits to advertising dynamics and competitive effects[J]. Management Science, 1993, 39(9):1146-1162.
[21] Beltran-Royo C, Zhang H, Blanco L A, et al. Multistage multiproduct advertising budgeting[J]. European Journal of Operational Research, 2013, 225(1):179-188.
[22] Beltran-Royo C, Escudero L F, Zhang H. Multiperiod multiproduct advertising budgeting:Stochastic optimization modeling[J]. Omega, 2016, 59:26-39.
[23] Sethi S P. Dynamic optimal control models in advertising:A survey[J]. SIAM Review, 1977, 19(4):685-725.
[24] Rao A G, Rao M R. Optimal budget allocation when response is S-shaped[J]. Operations Research Letters, 1983, 2(5):225-230.
[25] Holthausen Jr D M, Assmus G. Advertising budget allocation under uncertainty[J]. Management Science, 1982, 28(5):487-499.
[26] Du R, Hu Q, Ai S. Stochastic optimal budget decision for advertising considering uncertain sales responses[J]. European Journal of Operational Research, 2007, 183(3):1042-1054.
[27] Bass F M, Bruce N, Majumdar S, et al. Wearout effects of different advertising themes:A dynamic Bayesian model of the advertising-sales relationship[J]. Marketing Science, 2007, 26(2):179-195.
[28] Gatignon H, Hanssens D M. Modeling marketing interactions with application to salesforce effectiveness[J]. Journal of Marketing Research, 1987, 24(3):247-257.
[29] Villas-Boas J M. Communication strategies and product line design[J]. Marketing Science, 2004, 23(3):304-316.
[30] Raman K, Mantrala M K, Sridhar S, et al. Optimal resource allocation with time-varying marketing effectiveness, margins and costs[J]. Journal of Interactive Marketing, 2012, 26(1):43-52.
[31] Berger P D, Bechwati N N. The allocation of promotion budget to maximize customer equity[J]. Omega, 2001, 29(1):49-61.
[32] Amaldoss W, He C. Product variety, informative advertising, and price competition[J]. Journal of Marketing Research, 2010, 47(1):146-156.
[33] Sun M. Disclosing multiple product attributes[J]. Journal of Economics & Management Strategy, 2011, 20(1):195-224.
[34] Anderson S P, Renault R. The advertising mix for a search good[J]. Management Science, 2013, 59(1):69-83.
[35] Raman K. Boundary value problems in stochastic optimal control of advertising[J]. Automatica, 2006, 42(8):1357-1362.
[36] Naik P A, Raman K. Understanding the impact of synergy in multimedia communications[J]. Journal of Marketing Research, 2003, 40(4):375-388.
[37] Dehghani M, Tumer M. A research on effectiveness of Facebook advertising on enhancing purchase intention of consumers[J]. Computers in Human Behavior, 2015, 49:597-600.
[38] Hoban P R, Bucklin R E. Effects of internet display advertising in the purchase funnel:Model-based insights from a randomized field experiment[J]. Journal of Marketing Research, 2015, 52(3):375-393.
[39] Anderl E, Schumann J H, Kunz W. Helping firms reduce complexity in multichannel online data:A new taxonomy-based approach for customer journeys[J]. Journal of Retailing, 2016, 92(2):185-203.
[40] 周永务, 肖旦, 李绩才. 损失规避零售商订货量与广告费用的联合决策[J]. 系统工程理论与实践, 2012, 32(8):1727-1738.Zhou Y W, Xiao D, Li J C. Joint decision-making of order quantities and advertising expenditure for loss-averse retailers[J]. Systems Engineering-Theory & Practice, 2012, 32(8):1727-1738.
[41] Schlosser R. Stochastic dynamic pricing and advertising in isoelastic oligopoly models[J]. European Journal of Operational Research, 2017, 259(3):1144-1155.
[42] Jang S, Prasad A, Ratchford B T. How consumers use product reviews in the purchase decision process[J]. Marketing Letters, 2012, 23(3):825-838.
[43] Hauser J R. Consideration-set heuristics[J]. Journal of Business Research, 2014, 67(8):1688-1699.
[44] Park S, Nicolau J L. Differentiated effect of advertising:Joint vs. separate consumption[J]. Tourism Management, 2015, 47:107-114.
[45] Bishop C M. Pattern recognition and machine learning[M]. New York:Springer-Verlag, 2006.

Funding

National Natural Science Foundation of China (71471032); Liaoning BaiQianWan Talents Program ([2015] 18)
PDF(1557 KB)

503

Accesses

0

Citation

Detail

Sections
Recommended

/