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2024 | OriginalPaper | Buchkapitel

Inhomogenous Marketing Mix Diffusion

verfasst von : Luís G. Pinto, Luís Cavique, Orlando Gomes, Jorge M. A. Santos

Erschienen in: Complex Networks XV

Verlag: Springer Nature Switzerland

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Abstract

In this article we extend the Marketing Mix Diffusion (MMD) model to inhomogenous networks (i.e. complex networks of arbitrary topology). The (Homogenous) MMD model is an innovation diffusion model, similar to the Bass model, which includes four decision variables (the 4Ps of Marketing: Product, Price, Place, Promotion). We introduce the Inhomogenous MMD (IMMD) model and we conduct two separate experiments: one based on simulation and another one relying on empirical evidence. The simulation study compares the behavior of the IMMD model with the classic Bass diffusion model. Results suggest that the classic Bass model is able to represent the IMMD curves quite well in most cases. The IMMD is more general and capable of representing extreme scenarios. The empirical study focuses on the geographic diffusion of mobile broadband technology in Japan, combining adoption data with a spatial network of municipalities. The in-sample performance of the model is comparable to the existing methods, which suggests a good explanatory power of the IMMD model.

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Fußnoten
1
The use of the hyperbolic tangent (tanh) ensures that the outputs are contained between –1 and 1, such that when combined with the ReLU function on Eqs. 3 and 4, only positive outputs will flow into the neighboring nodes. This simulates the adoption dynamic of each individual node.
 
Literatur
1.
Zurück zum Zitat Akamai.: State of Internet Reports (2014) Akamai.: State of Internet Reports (2014)
2.
Zurück zum Zitat Bass, F.M.: A new product growth for model consumer durables. Manag. Sci. 50(12_Supplement), 1825–1832 (2004) Bass, F.M.: A new product growth for model consumer durables. Manag. Sci. 50(12_Supplement), 1825–1832 (2004)
3.
Zurück zum Zitat Bass, Frank M., Krishnan, Trichy V., Jain, Dipak C.: Why the Bass model fits without decision variables. Market. Sci. 13(3), 203–223 (1994)CrossRef Bass, Frank M., Krishnan, Trichy V., Jain, Dipak C.: Why the Bass model fits without decision variables. Market. Sci. 13(3), 203–223 (1994)CrossRef
4.
Zurück zum Zitat Bertotti, M.L., Brunner, J., Modanese, G.: The Bass diffusion model on networks with correlations and inhomogeneous advertising. Chaos, Solitons Fractals 90, 55–63 (2016)MathSciNetCrossRef Bertotti, M.L., Brunner, J., Modanese, G.: The Bass diffusion model on networks with correlations and inhomogeneous advertising. Chaos, Solitons Fractals 90, 55–63 (2016)MathSciNetCrossRef
5.
Zurück zum Zitat Dentsu.: Advertising Expenditures in Japan (2020) Dentsu.: Advertising Expenditures in Japan (2020)
6.
Zurück zum Zitat Godes, D., Mayzlin, D.: Using online conversations to study word-of-mouth communication. Market. Sci. 23(4), 545–560 (2004)CrossRef Godes, D., Mayzlin, D.: Using online conversations to study word-of-mouth communication. Market. Sci. 23(4), 545–560 (2004)CrossRef
7.
Zurück zum Zitat Hamrick, B.: Discrete Calculus (2007) Hamrick, B.: Discrete Calculus (2007)
8.
Zurück zum Zitat Holtz, G.: An individual level diffusion model, carefully derived from the Bass-model (2004) Holtz, G.: An individual level diffusion model, carefully derived from the Bass-model (2004)
9.
Zurück zum Zitat Kempe, D., Kleinberg, J., Tardos, É.: Maximizing the spread of influence through a social network. In: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD ’03, p. 137. ACM Press, New York (2003) Kempe, D., Kleinberg, J., Tardos, É.: Maximizing the spread of influence through a social network. In: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD ’03, p. 137. ACM Press, New York (2003)
10.
Zurück zum Zitat Kempe, D., Kleinberg, J., Tardos, É.: Maximizing the spread of influence through a social network. Theory Comput. 11(4), 105–147 (2015)MathSciNetCrossRef Kempe, D., Kleinberg, J., Tardos, É.: Maximizing the spread of influence through a social network. Theory Comput. 11(4), 105–147 (2015)MathSciNetCrossRef
11.
Zurück zum Zitat Kermack, W.O., McKendrick, A.G.: A contribution to the mathematical theory of epidemics. Proc. R. Soc. Lond. Ser. A, Contain. Papers Math. Phys. Charact. 115(772), 700–721 (1927) Kermack, W.O., McKendrick, A.G.: A contribution to the mathematical theory of epidemics. Proc. R. Soc. Lond. Ser. A, Contain. Papers Math. Phys. Charact. 115(772), 700–721 (1927)
12.
Zurück zum Zitat Li, M., Wang, X., Gao, K., Zhang, S.: A survey on information diffusion in online social networks: models and methods. Inf. (Switzerland) 8(4) (2017) Li, M., Wang, X., Gao, K., Zhang, S.: A survey on information diffusion in online social networks: models and methods. Inf. (Switzerland) 8(4) (2017)
13.
Zurück zum Zitat Mesak, H.I.: Incorporating price, advertising and distribution in diffusion models of innovation: some theoretical and empirical results. Comput. Operat. Res. 23(10), 1007–1023 (1996)CrossRef Mesak, H.I.: Incorporating price, advertising and distribution in diffusion models of innovation: some theoretical and empirical results. Comput. Operat. Res. 23(10), 1007–1023 (1996)CrossRef
14.
Zurück zum Zitat Morone, F., Makse, H.A.: Influence maximization in complex networks through optimal percolation. Technical report (2015) Morone, F., Makse, H.A.: Influence maximization in complex networks through optimal percolation. Technical report (2015)
15.
Zurück zum Zitat Morone, F., Min, B., Bo, L., Mari, R., Makse, H.A.: Collective Influence Algorithm to find influencers via optimal percolation in massively large social media. Sci, Rep (2016)CrossRef Morone, F., Min, B., Bo, L., Mari, R., Makse, H.A.: Collective Influence Algorithm to find influencers via optimal percolation in massively large social media. Sci, Rep (2016)CrossRef
16.
Zurück zum Zitat Narasimhan, R., Ghosh, S., Mendez, D.: A dynamic model of product quality and pricing decisions on sales response. Decis, Sci (1993)CrossRef Narasimhan, R., Ghosh, S., Mendez, D.: A dynamic model of product quality and pricing decisions on sales response. Decis, Sci (1993)CrossRef
17.
18.
Zurück zum Zitat Niu, S.-C.: A stochastic formulation of the Bass model of new-product diffusion. Math. Probl. Engin. 8(3), 249–263 (2002)MathSciNetCrossRef Niu, S.-C.: A stochastic formulation of the Bass model of new-product diffusion. Math. Probl. Engin. 8(3), 249–263 (2002)MathSciNetCrossRef
19.
Zurück zum Zitat OECD. Mobile broadband subscriptions (2018) OECD. Mobile broadband subscriptions (2018)
20.
Zurück zum Zitat Pinto, L., Cavíque, L., Santos, J.M.A.: Marketing mix and new product diffusion models. Proc. Comput, Sci (2022)CrossRef Pinto, L., Cavíque, L., Santos, J.M.A.: Marketing mix and new product diffusion models. Proc. Comput, Sci (2022)CrossRef
23.
Zurück zum Zitat Pyo, T.-H., Gruca, T.S., Russell, G.J.: A new bass model utilizing social network data (2017) Pyo, T.-H., Gruca, T.S., Russell, G.J.: A new bass model utilizing social network data (2017)
24.
Zurück zum Zitat Richardson, M., Domingos, P.: Mining knowledge-sharing sites for viral marketing, p. 61 (2002) Richardson, M., Domingos, P.: Mining knowledge-sharing sites for viral marketing, p. 61 (2002)
25.
Zurück zum Zitat Everett, M.: Rogers. Free Press, Diffusion of Innovation (2003) Everett, M.: Rogers. Free Press, Diffusion of Innovation (2003)
27.
Zurück zum Zitat Wang, W., Liu, Q.H., Liang, J., Hu, Y., Zhou, T.: Coevolution spreading in complex networks. Phys. Rep. 820, 1–51 (2019)MathSciNetCrossRef Wang, W., Liu, Q.H., Liang, J., Hu, Y., Zhou, T.: Coevolution spreading in complex networks. Phys. Rep. 820, 1–51 (2019)MathSciNetCrossRef
28.
Zurück zum Zitat Zonghan, W., Pan, S., Chen, F., Long, G., Zhang, C., Philip, S.Y.: A comprehensive survey on graph neural networks. IEEE Trans. Neural Netw. Learn. Syst. 32(1), 4–24 (2021)MathSciNetCrossRef Zonghan, W., Pan, S., Chen, F., Long, G., Zhang, C., Philip, S.Y.: A comprehensive survey on graph neural networks. IEEE Trans. Neural Netw. Learn. Syst. 32(1), 4–24 (2021)MathSciNetCrossRef
29.
Zurück zum Zitat Zhong, Y.D., Leonard, N.E.: A continuous threshold model of cascade dynamics. In: Proceedings of the IEEE Conference on Decision and Control, 2019, pp. 1704–1709 (2019) Zhong, Y.D., Leonard, N.E.: A continuous threshold model of cascade dynamics. In: Proceedings of the IEEE Conference on Decision and Control, 2019, pp. 1704–1709 (2019)
Metadaten
Titel
Inhomogenous Marketing Mix Diffusion
verfasst von
Luís G. Pinto
Luís Cavique
Orlando Gomes
Jorge M. A. Santos
Copyright-Jahr
2024
DOI
https://doi.org/10.1007/978-3-031-57515-0_3

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