Consumer Motivations to Create Alternative Consumption Platforms

Sharing platforms are becoming increasingly common, transforming how organisations and customers interact across diverse categories. While there is clear demand for the sharing economy, less is known about heterogeneity of consumer preferences and the varying demand that exists for sharing experiences across different categories of consumption. In order to help brands better understand who shares, this research takes a step forward in the profiling of users of the sharing economy. Drawing on social psychology, this research investigates how social norms can be employed as a form of social influence and nudge consumers to engage in higher levels of shared consumption. We find three clear segments of sharing consumers, representing 86% of all consumers: the mobility-focused sharer, the diverse-platform sharer, and the power-platform sharer. The last segment (accounting for 14%) comprises consumers who do not engage with sharing platforms. Moreover, social norms influenced the future behaviours of only one segment of consumers: the diverse-platform sharer. We discuss how sharing platform providers can better understand, target, and convert consumers to engage in sharing.

Section: Theoretical Backgroundmentioning

confidence: 99%

Who Shares? Profiling Consumers in the Sharing Economy

Sands

Ferraro

Campbell

et al. 2020

“…For example, the world's largest sharing economy platforms, such as Airbnb and Uber, are commercial. Consequently, users typically do not perform the role of platform operator (e.g., Airbnb) (Bajaj et al, 2020) but perform as one-sided users as either providers or consumers.…”

Section: Literature Reviewmentioning

confidence: 99%

How to Grow the Sharing Economy? Create Prosumers!

Lang

Botha

Robertson

et al. 2020

The sharing economy has changed many rules of business. One of those rules is the role of the firm and – importantly – the role of consumers, who can perform two roles and become both providers and consumers, i.e. “prosumers”. Therefore, the key network effect to leveraging the power of the sharing economy is for one-sided users, those who are consumers (e.g., Airbnb guests) or providers (e.g., Airbnb hosts), to add the second role and perform as providers and consumers and become prosumers (e.g., those who are Airbnb guests and hosts). Surprisingly, no studies have investigated this important phenomenon and measured how one-sided users may become prosumers. An online survey of 305 Airbnb users showed that trust and gratitude had a significant positive influence on service providers’ and consumers’ intentions to adopt the respective other role and become prosumers, and that those with high gratitude and trust had the highest intentions to become prosumers. However, consumers and providers differed markedly in how trust and gratitude influenced their intention to become prosumers. This study expands our understanding of trust and gratitude and highlights the potential for sharing platforms to create prosumers from both pools of one-sided users. Furthermore, it also makes a valuable contribution to the prosumer and sharing economy literatures by being the first to empirically measure users’ intentions to become prosumers in the sharing economy. We discuss the implications of the findings for practitioners, and suggest how future research could help leverage the sharing economy.

“…Platform businesses create repeated opportunities for peer-to-peer interactions including seeking and providing information, customizing offerings, completing transactions, allowing feedback on sellers and buyers, and publishing reviews and word-of-mouth recommendations. Many rating systems are bidirectional, with providers and purchasers rating each other (Jøsang, 2007), effectively making consumers into content creators (Bajaj et al, 2020). These ratings tend to be high and biased (Aral, 2014).…”

Section: Introductionmentioning

confidence: 99%

Peer-To-Peer Interactions in the Sharing Economy: Exploring the Role of Reciprocity within a Chinese Social Network

Starr

Zhu

Frethey‐Bentham

et al. 2020

Peer-to-peer interactions play an important role in the sharing economy and more specifically within Internet social networking sites (SNSs). However, little is known about the nature of these interactions and the role of reciprocity in the peer-to-peer exchanges facilitated by SNSs. We use the context of the Chinese Weibo SNS to explore this issue. Our research develops a conceptual model and hypotheses to examine the effects of reputation and emotion on reciprocal behaviours in the Chinese Weibo SNS. We conduct a study to test the influence of reputation on reciprocity and emotion in these peer-to-peer interactions. Our study shows that bridging behaviours, which create social status across heterogeneous groups, generate increased reciprocation as a direct effect. A second indicator of reputation, bonding behaviours that promote social resources within homogenous groups, do not have significant direct effects on intention to reciprocate. Both bridging and bonding behaviors create direct effects on evoked emotions, and emotions in turn have significant effects on the intention to reciprocate. We found that evoked emotions are an important mediator between bridging and bonding actions by one party in the sharing economy and the resulting intention to reciprocate by another party. Our findings contribute to developing a theoretical understanding of the role of reciprocity in peer-to-peer interactions in the sharing economy and more specifically in virtual environments. We show the functioning and appeal in the Chinese Weibo SNS depend heavily on reciprocal user behaviors including the exchange of emotional support, information and knowledge. Our findings show peer-to-peer interaction in SNSs create emotional responses, and these emotions mediate reciprocation. Actions by users with stronger reputations and higher status have stronger effects, which is consistent with the importance of social standing in China for fostering reciprocity in non-virtual business interactions. This suggests that offline habits are being emulated on the Internet.