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Targeted Allocation of Marketing Resource in Networks Based on Opinion Dynamics

Author

Listed:
  • Ningning Lang

    (School of Management Science and Real Estate, Chongqing University, Chongqing 400044, China)

  • Lin Wang

    (School of Management Science and Real Estate, Chongqing University, Chongqing 400044, China)

  • Quanbo Zha

    (School of Management Science and Real Estate, Chongqing University, Chongqing 400044, China)

Abstract

Recent advances in information technology and the boom in social media provide firms with easy access to the data of consumers’ preferences and their social interactions. To characterize marketing resource allocation in networks, this paper develops a game theoretical model that allows for each firm’s own utility, action strategies of other firms and the inner state (self-belief and opinions) of consumers. In this model, firms can sway consumers’ opinions by spending marketing resources among consumers under budget and cost constraints. Each firm competes for the collective preference of consumers in a social network to maximize its utility. We derived the equilibrium strategies theoretically in a connected network and a dispersed network from the constructed model. These reveal that firms should allocate more marketing resources to some of consumers depending on their initial opinions, self-belief and positions in a network. We found that some structures of consumer networks may have an innate dominance for one firm, which can be retained in equilibrium results. This means that network structure can be as a tool for firms to improve their utilities. Furthermore, the sensitivities of budget and cost to the equilibria were analyzed. These results can provide some reference for resource allocation strategies in marketing competition.

Suggested Citation

  • Ningning Lang & Lin Wang & Quanbo Zha, 2022. "Targeted Allocation of Marketing Resource in Networks Based on Opinion Dynamics," Mathematics, MDPI, vol. 10(3), pages 1-21, January.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:3:p:394-:d:735465
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    References listed on IDEAS

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    5. Tavasoli, Ali & Shakeri, Heman & Ardjmand, Ehsan & Young, William A., 2021. "Incentive rate determination in viral marketing," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1169-1187.
    6. Snyder, James M, 1989. "Election Goals and the Allocation of Campaign Resources," Econometrica, Econometric Society, vol. 57(3), pages 637-660, May.
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