Evolution of trust in the sharing economy with fixed provider and consumer roles under different host network structures

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We present an evolutionary trust game to investigate the formation of trust in sharing economy situations, where participants have a fixed provider or consumer role, and can only choose between trustworthy or untrustworthy behaviour. There are a variety of sharing economy platforms catering for differing goods and services, the properties of which may affect the degree to which these roles are variable for users. To the best of our knowledge, this is the first time the evolution of trust in sharing economy situations with fixed provider and consumer roles is being studied in the literature. Our trust model comprises four player types: trustworthy consumer, trustworthy provider, untrustworthy consumer, and untrustworthy provider. Five scenarios with varying initial population ratios of these player types under different host network structures are systematically investigated. Our results show that, in contrast to previous work that allowed switching roles between providers and consumers, trust declines monotonically as the reward for trustworthy behaviour is reduced, with a critical transition point for inversion of trustworthy/untrustworthy populations. In addition, the initial population of trustworthy providers is shown to significantly affect the point at which trustworthy behaviour most declines, with a high proportion resulting in the persistence of trustworthiness even when the reward for such behaviour is significantly low. Our results also show that, when different host network structures are considered, the average degree of the underlying network is an important factor in determining the level of trustworthiness in the population. Our findings may be of importance for understanding the emergence and maintenance of trust in sharing economy platforms where user roles are completely or predominantly rigid.

论文关键词:Evolutionary game theory,Sharing economy,Trust,Social networks

论文评审过程:Received 20 January 2021, Revised 8 September 2021, Accepted 13 September 2021, Available online 24 September 2021, Version of Record 29 December 2021.

论文官网地址:https://doi.org/10.1016/j.knosys.2021.107496