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A hybrid advertising media selection model using AHP and fuzzy-based GA decision making

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Abstract

Advertising media selection is the process of analyzing and choosing the most cost-effective media for advertising and promotions campaign. It is generally challenging because of the multiplicity of alternatives, the variations in objectives, and the budgetary limits of organizations. Hence, developing a media selection within the framework of a decision-making procedure is a vital function of advertising. Most of the traditional media selection procedures could be simply placed in two categories: (1) models based on judgment of decision makers who have not enough ability to consider the very large number of media combinations; (2) or quantitative models which could not incorporate imprecise, uncertain and subjective criteria. In this paper, a two-phase methodology is developed for advertising media selection in which by integrating qualitative and quantitative models, human-based information is incorporated in the decision process, while the complexity associated with the media selection decision is responded. In the first phase, the top media for an advertising campaign is identified by applying analytic hierarchy process based on four criteria of AIDA’s hierarchy of effects model (AIDA stands for: A = Attention, I = Interest, D = Desire, A = Action), and then in the second phase, by integrating a fuzzy linguistic decision model with a genetic algorithm searching process, the optimum media mix of the top media is extracted under satisfying expected advertising objectives and budgetary limitations. In the end, the proposed methodology is implemented empirically in a real-world case with satisfactory results.

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Notes

  1. Standard currency of Iran is Rial with abbreviation IRR.

References

  1. Aczel J, Saaty TL (1983) Procedures for synthesizing ratio judgements. J Math Psychol 27(1):93–102

    Article  MathSciNet  MATH  Google Scholar 

  2. Ahmed NU (1984) An efficient 0–1 integer programming algorithm for advertising media selection. J Acad Mark Sci 12(1–2):191–204

    Article  Google Scholar 

  3. Bahmani N, Javalgi RG, Blumberg H, Toshtzar M (2015) The selection of advertising media an application of the analytical hierarchy process. In: Hawes JM, Glisan GB (eds) Proceedings of the 1987 academy of marketing science (AMS) annual conference, pp 525

  4. Barry TE (1987) The development of the hierarchy of effects: an historical perspective. Curr Issues Res Advert 10(1–2):251–295

    Google Scholar 

  5. Barry TE, Howard DJ (1990) A review and critique of the hierarchy of effects in advertising. Int J Advert 9(2):121–135

    Article  Google Scholar 

  6. Bass FM, Lonsdale RT (1966) An exploration of linear programming in media selection. J Mark Res 3(2):179–188

    Article  Google Scholar 

  7. Bhattacharya UK (2009) A chance constraints goal programming model for the advertising planning problem. Eur J Oper Res 192(2):382–395

    Article  MathSciNet  MATH  Google Scholar 

  8. Blech GE, Blech MA (2003) Advertising and promotion: an integrated marketing communications perspective, 6th edn. McGraw-Hill, New York

    Google Scholar 

  9. Bonissone PP, Decker KS (1985) Selecting uncertainty calculi and granularity: An experiment in trading-off precision and complexity. In: Kanal LN, Lemmer JF (eds) Uncertainty in artificial intelligence, pp 217–247

  10. Bovee C, Thill JV, Dovel G, Wood M (1995) Advertising excellence. McGraw-Hill, New York

    Google Scholar 

  11. Buratto A, Grosset L, Viscolani B (2006) Advertising channel selection in a segmented market. Automatica 42(8):1343–1347

    Article  MATH  Google Scholar 

  12. Calantone RJ, Todorovic VD (1981) The maturation of the science of media selection. J Acad Mark Sci 9(4):490–524

    Article  Google Scholar 

  13. Charnes A, Cooper WW, Devoe JK, Lerner DB, Reinecke W (1968) A goal programming model for media planning. Manag Sci 14(8):423–430

    Article  Google Scholar 

  14. Dalrymple DJ, Parsons LJ (1986) Marketing management: strategy and cases, 6th edn. Wiley, New York

    Google Scholar 

  15. Danaher PJ, Lee J, Kerbache L (2010) Optimal internet media selection. Mark Sci 29(2):336–347

    Article  Google Scholar 

  16. Day RL (1962) Linear programming in media selection. J Advert Res 2:40–44

    Google Scholar 

  17. De Kluyver CA (1979) An exploration of various goal programming formulation with application to advertising media scheduling. J Oper Res Soc 30(2):167–171

    Google Scholar 

  18. Deckro RF, Murdock GW (1987) Media selection via multiple objective integer programming. Omega 15(5):419–427

    Article  Google Scholar 

  19. Delgado M, Vila MA, Voxman W (1998) A canonical representation of fuzzy numbers. Fuzzy Sets Syst 93(1):125–135

    Article  MathSciNet  MATH  Google Scholar 

  20. Dyer RF, Forman EH, Mustafa MA (1992) Decision support for media selection using the analytic hierarchy process. J Advert 21(1):59–72

    Article  Google Scholar 

  21. Engel JF, Warshaw MR (1964) Allocating advertising dollars by linear programming. J Advert Res 4(3):42–48

    Google Scholar 

  22. Engel JF, Wales HG, Warshaw MR (1975) Promotional strategy, 3rd edn. R.D. Irwin, Homewood

    Google Scholar 

  23. Gensch DH (1968) Computer models in advertising media selection. J Mark Res 5(4):414–424

    Article  Google Scholar 

  24. Ghirvu AI (2013) The AIDA model for AdverGames. USV Ann Econ Public Adm 13(1(17)):90–98

    Google Scholar 

  25. Goldberg ED (1989) Genetic algorithms in search, optimization and machine learning. Addison-Wesley, Boston

    MATH  Google Scholar 

  26. Hassan S, Nadzim SZA, Shiratuddin N (2015) Strategic use of social media for small business based on the AIDA model. Proc Soc Behav Sci 172:262–269

    Article  Google Scholar 

  27. Herrera F, Herrera-Viedma E (1997) Aggregation operators for linguistic weighted information. IEEE Trans Syst Man Cybern Part A Syst Hum 27(5):646–656

    Article  Google Scholar 

  28. Herrera F, Lopez E, Rodriguez MA (2002) A linguistic decision model for promotion mix management solved with genetic algorithms. Fuzzy Sets Syst 131(1):47–61

    Article  MathSciNet  MATH  Google Scholar 

  29. Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor

    Google Scholar 

  30. Hsu T-H, Tsai T-N, Chiang P-L (2008) Selection of the optimum promotion mix by integrating a fuzzy linguistic decision model with genetic algorithms. Inf Sci 179(1–2):41–52

    Google Scholar 

  31. Hu X, Jiang F (2014) Advertising media selection and delivery decision-making using influence diagram. In: Wong WE, Zhu T (eds) Computer engineering and networking, pp 855–863

  32. Jha PC, Aggarwal R, Gupta A (2011) Optimal media planning for multi-products in segmented market. Appl Math Comput 217(16):6802–6818

    MATH  Google Scholar 

  33. Keown AJ, Duncan CP (1979) Integer goal programming in advertising media selection. Decis Sci 10(4):577–591

    Article  Google Scholar 

  34. Kotler P, Armstrong G (2008) Principles of marketing, 14th edn. Pearson Prentice Hall, Upper Saddle River

    Google Scholar 

  35. Kumar S, Jacob V, Sriskandarajah C (2006) Scheduling advertisements on a web page to maximize revenue. Eur J Oper Res 173:1067–1089

    Article  MATH  Google Scholar 

  36. Lee SM (1972) Goal programming for decision analysis. Auerbach, Philadelphia

    Google Scholar 

  37. Lee SM, Nicely RE (1974) Goal programming for marketing decisions: a case study. J Mark 38(1):24–32

    Article  Google Scholar 

  38. Li J, Yu H (2013) An innovative marketing model based on AIDA:-a case from e-bank campus-marketing by China Construction Bank. iBusiness 5(3):47–51

    Article  Google Scholar 

  39. Little J, Lodish L (1969) A media planning calculus. Oper Res Int Journal 17(1):1–35

    Google Scholar 

  40. Liu L, Wang ZS, Huang ZJ, Zhang HG (2016) Adaptive predefined performance control for MIMO systems with unknown direction via generalized fuzzy hyperbolic model. IEEE Trans Fuzzy Syst. doi:10.1109/TFUZZ.2016.2566803

    Google Scholar 

  41. Malthouse EC, Qiu D, Xu J (2012) Optimal selection of media vehicles using customer databases. Expert Syst Appl 39:13035–13045

    Article  Google Scholar 

  42. Miller DW, Starr MK (1960) Executive decsions and operations research. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  43. Mohammadi S, Esmaeily N, Salehi N (2012) Prioritization of promotion tools based on AIDA model by analytic hierarchy process in production sector of sport industry. Arch Appl Sci Res 4(4):1670–1675

    Google Scholar 

  44. Mokhtari H (2016) Research on group search optimizers for a reconfigurable flow shop sequencing problem. Neural Comput Appl. doi:10.1007/s00521-015-1963-3

    Google Scholar 

  45. Mokhtari H, Kazemzadeh RB, Salmasnia A (2011) Time-cost tradeoff analysis in project management: an ant system approach. IEEE Trans Eng Manage 58(1):36–43

    Article  Google Scholar 

  46. Ngai EWT (2003) Selection of web sites for online advertising using the AHP. Inf Manag 40(4):233–242

    Article  Google Scholar 

  47. Paech SJ (2005) Understanding media planning practice, Master’s Thesis, University of South Australia, Retrieved from Unisa Research Archive

  48. Pérez-Gladish B, González I, Bilbao-Terol A, Arenas-Parra M (2010) Planning a TV advertising campaign: a crisp multiobjective programming model from fuzzy basic data. Omega 38(1):84–94

    Article  Google Scholar 

  49. Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, New York

    MATH  Google Scholar 

  50. Saaty TL (2008) Decision making with the analytic hierarchy process. Int J Serv Sci 1(1):83–98

    Google Scholar 

  51. Stasch SF (1965) Linear programming and space-time considerations in media selection. J Advert Res 5(4):40–46

    Google Scholar 

  52. Steuer RE, Oliver RL (1976) An application of multiple objective linear programming to media selection. Omega 4(4):455–462

    Article  Google Scholar 

  53. Strong EK (1925) The psychology of selling and advertising. McCraw-Hill, New York

    Google Scholar 

  54. Tavana M, Momeni E, Rezaeiniya N, Mirhedayatian SM, Rezaeiniya H (2013) A novel hybrid social media platform selection model using fuzzy ANP and COPRAS-G. Expert Syst Appl 40:5694–5702

    Article  Google Scholar 

  55. Ur Rehman F, Javed F, Nawaz T, Ahmed I, Hyder S (2014) Some insights in the historical prospective of hierarchy of effects model: a short review. Inf Manag Bus Rev 6(6):301–308

    Google Scholar 

  56. Viscolani B (2009) Advertising decisions for a segmented market. Optimization 58(4):469–477

    Article  MathSciNet  MATH  Google Scholar 

  57. Weilbacher WM (2001) Point of view: does advertising cause a hierarchy of effects? J Advert Res 41(6):19–26

    Article  Google Scholar 

  58. Widey G, Zimmerman HJ (1978) Media selection and fuzzy programming. J Oper Res Soc 29(11):1071–1084

    Article  Google Scholar 

  59. Wijaya BS (2012) The development of hierarchy of effects model in advertising. Int Res J Bus Stud 5(1):73–85

    Article  Google Scholar 

  60. Yager RR (1988) On ordered weighted averaging aggregation operators in multicriteria decision making. IEEE Trans Syst Man Cybern 18(1):183–190

    Article  MATH  Google Scholar 

  61. Yager RR (1993) Families of OWA operators. Fuzzy Sets Syst 59(2):125–148

    Article  MathSciNet  MATH  Google Scholar 

  62. Zadeh LA (1975) The concept of a linguistic variable and its applications to approximate reasoning. Inf Sci 8(3):199–249

    Article  MathSciNet  MATH  Google Scholar 

  63. Zadeh LA (1983) A computational approach to fuzzy quantifiers in natural languages. Comput Math Appl 9(1):149–184

    Article  MathSciNet  MATH  Google Scholar 

  64. Zangwill WI (1965) Media selection by decision programming. J Advert Res 5(3):30–36

    Google Scholar 

  65. Zolfani SH, Rezaeiniya N, Pourhossein M, Zavadskas K (2012) Decision making on advertisement strategy selection based on life cycle of products by applying FAHP and TOPSIS GREY: growth stage perspective; a case about food industry in IRAN. Eng Econ 23(5):471–484

    Google Scholar 

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Correspondence to Hadi Mokhtari.

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Javan, H.T., Khanlari, A., Motamedi, O. et al. A hybrid advertising media selection model using AHP and fuzzy-based GA decision making. Neural Comput & Applic 29, 1153–1167 (2018). https://doi.org/10.1007/s00521-016-2517-z

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