Understanding the Platform Economy: Signals, Trust, and Social Interaction
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Proceedings of the 53rd Hawaii International Conference on System Sciences | 2020 Understanding the Platform Economy: Signals, Trust, and Social Interaction Maik Hesse Fabian Braesemann Einstein Center Digital Future | TU Berlin Saïd Business School | University of Oxford [email protected] [email protected] David Dann Timm Teubner Karlsruhe Institute of Technology Einstein Center Digital Future | TU Berlin [email protected] [email protected] Abstract variety of markets, work arrangements, as well as value creation and capture [3]–[5]. Two-sided markets are gaining increasing As platform-based business models rely on the importance. Examples include accommodation and car realization of transactions among peers, a central sharing, resale, shared mobility, crowd work, and aspect to virtually all platforms are the creation and many more. As these businesses rely on transactions maintenance of peer-trust [6]–[9]. While recent among users, central aspects to virtually all platforms research has considered the effects of trust-building are the creation and maintenance of trust. While mechanisms on different platforms separately (e.g., research has considered effects of trust-building on how profile images and star ratings affect trust and diverse platforms in isolation, the overall platform booking intentions on Airbnb; [10]), the overall landscape has received much less attention. However, platform landscape as a whole has received much less cross-platform comparison is important since research attention [11]. platforms vary in their degree of social interaction, We suggest that a broader assessment of trust and which, as we demonstrate in this paper, determines the reputation across platforms is urgently needed. adequacy and use of different trust mechanisms. Based Comprehending how platform operators act to govern on actual market data, we examine the mechanisms and guide user behavior and usage patterns in digital platforms employ and how frequent users rely on them. platform ecosystems can allow for better understanding We contrast this view against survey data on users’ of resulting behaviors and outcomes—and vice versa. perceptions of the context-specific importance of these By offering mechanisms to build trust and reputation, trust-building tools. Our findings provide robust platforms acknowledge that economic transactions are evidence for our reasoning on the relation between “socially embedded” [12]. Ratings, reviews, and platforms’ degree of social interaction and the expressive user profiles function as “systems of associated expressive trust cues. control” [13] to counter opportunism in digital environments, as they inform about the “identity and Code and Data: past relations of individual transactors” [12, p. 491]. http://bit.ly/UnderstandingPlatformEconomy Based on this reasoning, we conjecture that platforms’ degree of social interaction (DoSI; i.e., the extent to which personal interactions between platform users 1. Introduction become part of the overall value proposition and may enable positive social experiences; [14]) represents a Two-sided platforms have gained accelerating key driver of the adequacy and use of trust cues. importance and research attention over the last couple Our research objective, thus, is threefold. First, of years [1], [2]. Examples from the consumer-to- based on actual market data crawled from the Internet, consumer domain include services for accommodation we provide a cross-platform overview and propose a (e.g., Airbnb, Homestay) and carsharing (e.g., Drivy, categorization for the different mechanisms platforms Turo), mobility (e.g., BlaBlaCar, Uber, Wingly), e- employ to build and maintain trust between users. In commerce (e.g., eBay, Gumtree), crowd work (e.g., addition to uncovering this full palette of trust-building Helpling, TaskRabbit), and many more. Such platforms tools available to platform users, we also highlight the have caused significant changes in many incumbent frequency of utilizing said mechanisms. Second, based businesses along with the reorganization of a wide URI: https://hdl.handle.net/10125/64373 978-0-9981331-3-3 Page 5139 (CC BY-NC-ND 4.0) on self-reported data from a consumer survey, we Research from the domains of economics, analyze how the available mechanisms are actually information systems, and electronic commerce has perceived and evaluated—and thus shaped—by the studied the role of online reputation for trust-building, specific platforms’ users while also investigating realization of transactions, and prices for almost two which additional trust cues they would like to see. In decades [7], [18], [19]. The positive economic effects this sense, we juxtapose the availability (platform of transaction-based trust cues (e.g., star ratings and perspective) with the usage frequency (user text reviews; see [9] for a definition) have been broadly perspective: provider) and perceived importance (user investigated across a range of platforms: from earlier perspective: consumer) of trust-building on two-sided work on realized price premiums for providers on eBay markets. These perspectives help us to better [20], [21] to more recent investigations of effects on understand which of the many striking observations are sharing economy platforms such as Airbnb [22], [23] specific to certain platforms—and which point to more or BlaBlaCar [24]. fundamental phenomena of the platform economy as a In view of the ever-increasing importance of whole. Third, thanks to the multi-platform perspective platform business models and the emergence of C2C presented here, we are able to compare the use and platforms with private individuals in the role of perceived importance of trust-building mechanisms providers, online reputation and user representation are with respect to a platform’s degree of social charged with particular meaning. Personal aspects and interaction. individual characteristics are essential to many C2C To evaluate our reasoning, we draw on two platforms and transactions [25], and that is for at least independent and unique data sets: To start with, by two reasons. First, contingent on the specific platform considering eleven platforms from various domains type, social interactions between users do take place. and assessing several characteristic statistics, including Certainly, the extent of these encounters can vary— rating scores, activity concentration, and profile images from mere online communication to co-usage sharing. from a total of over 42,000 user profiles. Next, by In the latter case, personal interactions between users combining this empirical market data with quantitative are a prerequisite for the transaction to materialize. and qualitative survey data that we collected from 187 Second, scenarios that involve personal interactions participants. They evaluated the importance of may create additional, social value for consumers. This different trust-building mechanisms across several implies that providers themselves are part of the platform types (e.g., accommodation, mobility, etc.). overall value proposition of the platform (pleasant and In a nutshell, our results show that most of the locally versed Airbnb hosts or entertaining BlaBlaCar investigated platforms make use of a variety of means drivers) [14], [26], [27]. for trust-building—yet that there exist marked Research has thus focused on the role of social differences in how users actually utilize them. Both, experience and benefits beyond economic and usage and perceived importance depend on context: the product-related considerations for platform usage. In higher a platform’s degree of social interaction, the fact, social motives are frequently reported as a driver more trust cues are used and deemed important. of consumption on C2C platforms [28]–[30]. Moreover, consumers’ intention to use said platforms 2. Related work is shown to be positively influenced by social utility [31]–[34]. In consequence, providers can benefit from users’ expectations of social value and accordingly Typical users of consumer-to-consumer (C2C) market their product and themselves as a centerpiece of platforms are non-professional individuals with neither the overall usage experience [35], [36]. Thus, the an established brand image nor global recognition. prospect of interpersonal trust from social contact Consumption on these platforms requires different enables these providers to become their own brand [8]. levels of trust [15], yet many C2C transactions yield However, this works only, if the transacted product or high economic, social, and physical exposure [16]. service is related to personal interaction. If the Users of BlaBlaCar (rides) and Wingly (flights), for interaction is limited to the exchange of standardized instance, literally put their lives into the hands of their goods on an e-commerce platform, for example, there respective driver or pilot. Trust (into the prospective is little need in providing “brand-building” trust cues. good/service provider) is hence of utmost importance, In cases where the degree of social interaction is as the degree of interaction between users is very high high, platforms provide dedicated means to create [17]. As recent research shows, high levels of trust can expressive user profiles. Trust towards a prospective be achieved without prior in-person encounters [8]. We interaction partner, therefore, hinges on what is will now review which levers specifically create trust conveyed through the platforms’ user interfaces— and propose a taxonomy