Network modeling of consumers’ selection of providers based on online reviews

Tian Gan, Rishita Das,Maurizio Porfiri

IEEE Transactions on Network Science and Engineering(2024)

引用 0|浏览0
暂无评分
摘要
Information spreading over online review systems affects people's opinions and choices. In this work, we study consumers’ decision-making process with respect to provider selection, accounting for the providers’ online reviews and accessibility. We propose a network-based dynamical system of providers, in which the consumers switch between providers based on online reviews, as the time-varying online review system is continuously updated by the consumer fluxes. We apply the model to various network structures, capturing providers’ accessibility: i) random, canonical networks and ii) a real-world network of medical doctors in New York City. We examine the emerging correlations and causal relationships between the success of providers and the topological properties of the networks. Across a wide range of networks of varying size, we consistently find that online reviews have an important role in providers’ success. The satisfaction of the consumers in the online review systems, together with the market share, influences consumer fluxes between providers and the overall quality of service experienced by consumers. The study of the network of doctors reveals some causal mechanisms in the decision-making processes, with the doctor's success impacting on the providers’ quality of service and the consumer fluxes.
更多
查看译文
关键词
Complex systems,decision-making,Markov chain,online reviews,urban data
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要