The Implications of Trust in the Sharing Economy: An Empirical Analysis of Uber

Mittendorf, Christoph

doi:10.24251/hicss.2017.703

Cited by 53 publications

(104 citation statements)

References 49 publications

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“…Several studies conducted recently to investigate different aspects of sharing economy including intentions to participate (Kim et al 2015;Zhang et al 2016), positive impact of trust on sharing economy participation (Mittendorf 2017), positive sustainability motivation influence on attitude toward sharing economy (Hamari et al 2016), community belonging relationship with sharing economy selection (Möhlmann 2015), and locational amenities' impact on service providers' actual participation (Koohikamali et al 2017). Gutierrez et al (2016) is one of relatively few studies focusing on spatial distribution of Airbnb accommodations.…”

Section: Literature Reviewmentioning

confidence: 99%

Spatiotemporal Patterns and Socioeconomic Dimensions of Shared Accommodations: The Case of Airbnb in Los Angeles, California

Sarkar

Koohikamali

Pick

2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:In recent years, disruptive innovation by peer-to-peer platforms in a variety of industries, notably transportation and hospitality have altered the way individuals consume everyday essential services. With growth in sharing economy platforms such as Uber for ridesharing and Airbnb for short-term accommodations, interest in examining spatiotemporal patterns of participation in the sharing economy by suppliers and consumers is increasing. This research is motivated by key questions: who are the sharing economy workers, where are they located, and does their location influence their participation in the sharing economy? This paper is the first systematic effort to analyze spatiotemporal patterns of participation by hosts in the shared accommodation-based economy. Using three different kinds of shared accommodations listed in a 3-year period in the popular short-term accommodation platform, Airbnb, we examine spatiotemporal dimensions of host participation in a major U.S. market, Los Angeles CA. The paper also develops a conceptual model by positing associations of demographic, socioeconomic, occupational, and social capital attributes of hosts, along with their attitudes toward trust and greener consumption with hosts' participation in a shared accommodation market. Results confirm host participation to be influenced by young dependency ratio, the potential of supplemental income, as well as the sustainability potential of collaborative consumption, along with finance, insurance, and real estate occupation, but not so much by trust for our overall study area. These results add new insights to limited prior knowledge about the sharing economy worker and have policy implications.

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Section: Literature Reviewmentioning

confidence: 99%

Spatiotemporal Patterns and Socioeconomic Dimensions of Shared Accommodations: The Case of Airbnb in Los Angeles, California

Sarkar

Koohikamali

Pick

2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…A sharing platform is an enabler for interpersonal trust among providers and consumers, which plays a mediating role between institutional guarantees and trust [11]. Mittendorf [39] confirmed that passenger's trust in the Uber platform has a positive impact on trust in drivers. Möhlmann [11] found that guests' trust in Airbnb can significantly affect their trust in the hosts on the platform.…”

Section: Relationship Between Trust In the Platform And Trust In Consmentioning

confidence: 92%

The Effects of Online Trust-Building Mechanisms on Trust in the Sharing Economy: The Perspective of Providers

Wang

2020

Sustainability

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Trust is considered to be one of the key factors influencing the sustainable development of the sharing economy. In this paper, we focus on the trust issue of peer-to-peer accommodation models like Airbnb and Xiaozhu, which are among the most common examples of a sharing economy. This research divides trust into two types from the perspective of an accommodation provider in the context of peer-to-peer accommodation sharing: trust in the sharing platform and trust in consumers. The purpose of this paper is to provide a comprehensive view of how the three types of online trust-building mechanisms affect providers’ trust in the sharing platform and trust in consumers. The structural equation modelling with partial least square method was used to empirically test the influence of the online trust-building mechanisms of a sharing economy platform on provider’s trust in the platform and provider’s trust in consumers, based on a sample of 209 providers on online short-term rental platforms in China. The empirical results show that perceived personal safety mechanisms, perceived property safety mechanisms, and perceived review mechanisms are positively related to a provider’s trust in the platform. Provider’s trust in the platform has a positive effect on trust in consumers, while perceived personal safety and review mechanisms have a positive effect on provider’s trust in consumers by the mediation of trust in the platform. This study has theoretical and practical significance for the promotion of the research and development of trust mechanisms in the sharing economy.

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“…For our research, we adopted the research model of Mittendorf (2017), which investigates the building and implications of trust and risk on the sharing economy platform Uber. In addition, we follow the theory of 'Trust and Power' by Luhmann (1979), which comprises the fundamental conditions of trust and distrust as a functional equivalent and extension of trust.…”

Section: Rq: How Does Trust and Distrust Influence The Customers' Intmentioning

confidence: 99%

“…In particular, the need for trust increases with the rising dependency on other entities and growing vulnerability to their misconduct [11,36]. Researchers argue that trust plays a key role especially in the online environment respectively has been repeatedly identified as one of the most formidable barriers of people engaging in ecommerce [39,47,56], crowdsourcing [59], virtual teams [28], or the sharing economy [23,40,41].…”

Section: Trust and Distrustmentioning

confidence: 99%

“…This statement seems inevitable and has previously conceptualized in related research streams, such as in the collaborative environment, where trust has been identified as an important influential factor [43], or in the ecommerce industry, where trust is stated to be a key component that influences the customers' intentions to transact [29,48]. Regarding sharing economy literature, researchers [24,41] lately found that trust in the platforms is one of the main drivers why people engage in service encountersin the following, we refer to service encounters in the sharing economy as "sharing encounters"; hence people do not engage in selling or commercial renting practices. Most of the current sharing economy research relies on trust (respectively the lack of trust [57]) towards the platform or the corresponding sharing partners [31,40] rather than including the concept of distrust despite the findings of McKnight and Choudhury (2006) who argue that distrust is an additional factor that influences the users' intentions in the online environment and therefore fosters the understanding of user behavior.…”

Section: Introductionmentioning

confidence: 99%

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Trust and Distrust in Two-sided Markets: An Example in the Sharing Economy

Mittendorf

2018

Proceedings of the 51st Hawaii International Conference on System Sciences

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Mobile applications and Internet-based platforms continuously foster the rise of the sharing economy business model that can nowadays be found in various industries. In this paper, we focus on potential customers in the ridesharing industry. We use the setting of 'BlaBlaCar', a popular ridesharing platform, to investigate the implications of 'trust' and 'distrust' on the users' intention to engage in a sharing encounter. In particular, we extend the research model by Mittendorf (2017) which investigates the influence of trust and risk in the sharing economy. In this regard, we differentiate between the platform and the sharing partners, while incorporating both trust and distrust. Our study employs survey data (n = 238) and structural equation modeling (PLS-SEM). Our results provide empirical evidence that trust and distrust have unequal effects on the respective user intention, which contributes to the understanding of two-sided market platforms. Academic and practical implications are discussed.

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The Implications of Trust in the Sharing Economy: An Empirical Analysis of Uber

Abstract: Abstract

Cited by 53 publications

References 49 publications

Spatiotemporal Patterns and Socioeconomic Dimensions of Shared Accommodations: The Case of Airbnb in Los Angeles, California

Spatiotemporal Patterns and Socioeconomic Dimensions of Shared Accommodations: The Case of Airbnb in Los Angeles, California

The Effects of Online Trust-Building Mechanisms on Trust in the Sharing Economy: The Perspective of Providers

Trust and Distrust in Two-sided Markets: An Example in the Sharing Economy

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