Users and potential users of the sharing economy need to place a considerable amount of trust in both the person and the platform with which they are dealing. The consequences of transaction partners’ opportunism may be severe, for example damage to goods or endangered personal safety. Trust is, therefore, a key factor in overcoming uncertainty and mitigating risk. However, there is no thorough overview of how trust is developed in this context. To understand how the trust of users in the sharing economy is influenced, we performed a systematic literature review. After screening, 45 articles were included in a qualitative synthesis in which the results were grouped according to a well‐established trust typology. The results show various antecedents of trust in the sharing economy (e.g. reputation, trust in the platform, and interaction experience) related to multiple entities (i.e. seller, buyer, platform, interpersonal, and transaction). Trust in this economy is often reduced to the use of reputation systems alone. However, our study suggests that trust is much more complex than that and extends beyond reputation. Furthermore, our review clearly shows that research on trust in the sharing economy is still scarce and thus more research is needed to understand how trust is established in this context. Our review is the first that brings together antecedents of trust in online peer‐to‐peer transactions and integrates these findings within an existing framework. Additionally, the study suggests directions for future research in order to advance the understanding of trust in the sharing economy.
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Understanding infection dynamics of respiratory diseases requires the identification and quantification of behavioural, social and environmental factors that permit the transmission of these infections between humans. Little empirical information is available about contact patterns within real-world social networks, let alone on differences in these contact networks between populations that differ considerably on a socio-cultural level. Here we compared contact network data that were collected in the Netherlands and Thailand using a similar online respondent-driven method. By asking participants to recruit contact persons we studied network links relevant for the transmission of respiratory infections. We studied correlations between recruiter and recruited contacts to investigate mixing patterns in the observed social network components. In both countries, mixing patterns were assortative by demographic variables and random by total numbers of contacts. However, in Thailand participants reported overall more contacts which resulted in higher effective contact rates. Our findings provide new insights on numbers of contacts and mixing patterns in two different populations. These data could be used to improve parameterisation of mathematical models used to design control strategies. Although the spread of infections through populations depends on more factors, found similarities suggest that spread may be similar in the Netherlands and Thailand.
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