Targeted Allocation of Marketing Resource in Networks Based on Opinion Dynamics

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.

Opinion dynamics in social networks under competition: the role of influencing factors in consensus-reaching

“…Increased effort of each contestant improves his/her probability of winning, while reducing the opponents' chances [41]. The CSF is widely used in fields of political election [37,42,43], sports events [44][45][46] and marketing management [1,6,47], and many different variants of it have been developed over the long-term course of its application [48,49]. To the best of our knowledge, the CSF was first proposed by Luce to explore individual choice behaviour [50].…”

“…Opinion dynamics are manifest in diverse application areas [4,5], including marketing campaigns [1,6], public sentiment [7,8], political elections [9,10] and group decision-making [11,12]. These studies can be summarized under five topics: (i) opinion dynamics in different expression formats [13][14][15], (ii) modelling different evolution rules [16][17][18], (iii) opinion dynamics in heterogeneous environments [19][20][21], (iv) strategies and optimization for opinion control [22][23][24], and (v) opinion dynamics integrated with traditional group decision-making problems [25][26][27].…”