A Coupled Dynamic Model of Brand Acceptance and Promotive Information Spreading
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When people try to decide to buy or not to, they are often influenced by both their inherent opinions and the social marketing activities e.g. advertising, social news with strong point of view. Then people will make their final choice, or even convince other people to buy. After all, this is the brand acceptance formation process. Factually, the dynamics of brand acceptance is essentially an interwoven dynamics of endogenous opinion dynamics disturbed by an information diffusion process. To have a better understanding of the dynamics of brand acceptance, we propose and analyze a coupled agent-based dynamic model that combines the Majority-Rule-based Voter model in opinion dynamics with the SI Model for information spreading to analyze the dynamics of brand acceptance in social media. We focus on two important parameters in diffusion dynamics: the decayed transmission rate (β) and the diffusion frequency (f). When the system is stable, the order parameter of the system is the duration time (τ). In the absence of opinion interaction, the simulation results indicate that, when a brand tries to occupy a larger market share through social marketing approaches, it is always effective to let the opponent to be the propaganda target. While with the Majority-Rule-based Voter Model included, we observe that the opinion interaction could have a dual function, which shows that a brand holding a small market share in the first place needs to adopt diverse marketing approaches according to different marketing environment types.
KeywordsCoupled dynamics social marketing dynamics of brand acceptance opinion dynamics diffusion dynamics
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This work is partly supported by the National Natural Science Foundation of China under grant Nos. 71401024, 71371040 and 71533001, respectively.
- Wang C., & Tang X. (2016) “The Online Debate Networks Analysis: A Case Study of Debates at Tianya Forum”. In: Chen J., Nakamori Y., Yue W., Tang X. (eds.): Knowledge and Systems Sciences, Proceedings of 17th International symposium on knowledge and systems sciences, KSS 2016, Springer, pp. 140–150.Google Scholar
- Stauffer, D. (2005). “Sociophysics simulations II: opinion dynamics”.Google Scholar
- Lafley, A.G. & Charan, R. (2008), “The Game–Changer: How You Can Drive Revenue and Profit Growth with Innovation”, Enterprise/salt Lake City. 26(5), 97–99.Google Scholar
- Zanette, D.H. (2001), “Dynamics of rumor propagation on small–world networks”, Physical Review E Statistical Nonlinear & Soft Matter Physics. 65(4 Pt 1), 041908.Google Scholar
- Frachebourg, L. & Krapivsky, P.L. (1995), “Exact Results for Kinetics of Catalytic Reactions”, Physical Review E Statistical Physics Plasmas Fluids & Related Interdisciplinary Topics. 53(4), R3009–R3012.Google Scholar
- Kivelä, M., Arenas, A., Barthelemy, M., Gleeson, J.P., Moreno, Y. & Porter, M.A. (2013), “Multilayer networks”, Ssrn Electronic Journal. 2(3), 261–268.Google Scholar
- Rachaniotis, N., Dasaklis, T.K. & Pappis, C. (2017), "Controlling infectious disease outbreaks: A deterministic allocation–scheduling model with multiple discrete resources", Journal of Systems Science and Systems Engineering. 26(2), 219–239.Google Scholar
- Kotler, P. & Zaltman, G. (1975), “Social marketing: an approach to planned social change”, In: Inter–Governmental Coordinating Committee. 35(3), 3–12.Google Scholar
- Chen, P. & Redner, S. (2005), “Majority rule dynamics in finite dimensions”, Physical Review E Statistical Nonlinear & Soft Matter Physics. 71(3 Pt 2A), 036101.Google Scholar
- Lambiotte, R., Saramäki, J. & Blondel, V.D. (2009), “Dynamics of latent voters”, Physical Review E Statistical Nonlinear & Soft Matter Physics. 79(4 Pt 2), 046107.Google Scholar
- Galam, S. (2000), “Real space renormalization group and totalitarian paradox of majority rule voting”, Physica A Statistical Mechanics & Its Applications. 285(1–2), 66–76.Google Scholar
- Galam, S. (2002), “The September 11 attack: A percolation of individual passive support”, The European Physical Journal B. 26(3), 269–272.Google Scholar
- Milgram, S. (1974), “Obedience to Authority: An Experimental View”, London. 8(5), 312.Google Scholar
- Wang, W., Tang, M., Yang, H., Do, Y., Lai, Y.C. & Lee, G.W. (2014), “Asymmetrically interacting spreading dynamics on complex layered networks”, Scientific Reports. 4(7502), 5097.Google Scholar
- H. Xia, Wang H, Xuan Z. (2011), Opinion dynamics: A multidisciplinary review and perspective on future research. International Journal of Knowledge and Systems Sciences, 2(4), 72–91.Google Scholar
- Moreno, Y., Nekovee, M. & Pacheco, A.F. (2004), “Dynamics of rumor spreading in complex networks”, Physical Review E Statistical Nonlinear & Soft Matter Physics. 69(6 Pt 2), 066130. QianGoogle Scholar