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The purpose of this paper is to analyze why people have become suppliers in the sharing economy (SE) as Uber drivers in a developing country.

From a background on SE, car sharing and gig economy, the authors carried out a qualitative research. The analysis was based on 20 semi-structured interviews conducted with Uber drivers, and on the authors’ participant observation as Uber drivers and passengers in the third largest Brazilian city, Belo Horizonte.

Empirical evidence shows that becoming an Uber driver is more a matter of solving unemployment on a more permanent way rather than a search for a temporary and flexible work to supplement income. Although there are benefits related to flexibility, income and social interactions, negative externalities identified herein lead to the conclusion that the overall work relations and conditions are negative.

Much in the literature of the SE is focused on understanding consumer behavior; this research, on the contrary, is focused on understanding producers, which indicates an incipient perspective. The contributions of this paper show that the SE merges into different distributive decentralized means of production that are seeing as profit/income generated from shareable assets.

This study aims to explore the antecedents that generate value co-destruction, the negative outcomes resulting from interactive value formation, in the sharing economy context, particularly taxi services. The focus of the study is on customers’ Uber reviews that are written in English and posted online. Three keywords, “bad”, “terrible” and “awful”, were used to capture online narratives linked to customers’ negative experiences with Uber. Out of the 758 online reviews, 75 negative reviews were analysed in this study.

A grounded theory approach was used for data analysis.

Two distinct themes resulted in value co-destruction: Uber drivers’ bad behaviour and poor customer service. The managerial implications include that Uber clearly should invest more resources to minimise the negative experiences of its customers by clearly defining the taxi drivers’ tasks and responsibilities. In addition, when customers report their dissatisfaction, they should be dealt with promptly and effectively through good customer service.

First, the netnography study, by its nature, was restricted to those customers who shared their reviews online. The study did not consider those customers who have not posted their reviews online. Second, the focus of the study was on customer reviews that were written in English. Third, only three keywords (“bad”, “terrible” and “awful”) were used in the data selection process, limiting the number of review posts (75) that were analysed in this study. In addition, even if this study does not produce statistically generalizable findings, the findings are valuable in an analytical sense.

From a managerial perspective, Uber clearly should invest more in resources to minimise the negative experiences of its customers (both domestic customers and tourists) by clearly defining the taxi drivers’ tasks and responsibilities. If the drivers’ tasks are unclear, then customers cannot be served in an effective manner and with consistent service quality. The taxi drivers, regardless of their full-time or part-time work shifts, should ensure that quality services are offered to customers. Providing high-quality service might reduce the number of complaints and result in positive comments and compliments.

This study addresses the gap in previous literature by examining customers’ negative experiences during the overall service encounter and antecedents of value co-destruction in the context of Uber. This study contributes to a better understanding of value co-destruction within the sharing economy.

The aim of this article is to test the hypothesis that peer-to-peer technology platforms (Uber) are associated with disruption in the institutional environment, affecting beliefs, norms and users' ways of thinking and acting.

Probability sample comprising 843 users (446 passengers; 397 drivers) in the city of Belo Horizonte, Brazil, using a set of indicators was specifically designed for this study.

Uber triggers significant changes in the systems of rewards and sanctions, in social preferences, and in entrepreneurial structure and governance, and promotes the coexistence of an institutional logic, hitherto dominant, with new believes, rules, norms and regulatory systems.

This is a pioneer study that associates institutional approach's elements with technology platforms; the authors also elaborated and utilized an analysis model consisting of a set of completely original indicators capable of mapping and measuring different dimensions of the phenomenon under analysis.

This paper aims to examine the types of user misbehaviours in the sharing economy (SE) context. SE offers a fruitful study setting due to the scope of potential misbehaviour and the expanded role of consumers.

The study drew on online archival data from the AirbnbHell.com website, where people share their stories about their Airbnb-related negative experiences. The authors reviewed 405 hosts’, guests’ and neighbours’ stories and coded the identified forms of misbehaviours into categories. The typology thus developed was validated in the context of the Uber Rides service.

User misbehaviours in the SE context can be distinguished based on the domain in which the user role is violated and the nature of violated norms. These two conceptual distinctions delineate a four-fold typology of user misbehaviours: illegal, unprofessional, unbefitting and uncivil behaviours.

The trustworthiness of the stories could not be assessed.

The presented typology can be used as a mapping tool that facilitates detection of the full scope of misbehaviours and as a managerial tool that provides ideas for effective management of misbehaviours that correspond to each category.

The paper presents the first empirically derived comprehensive typology of user misbehaviours in SE settings. This typology enables classification of a broad set of misbehaviours, including previously overlooked unprofessional behaviours carried out by peer-service providers. The study also puts forward a revised definition of consumer misbehaviours that encompasses the impact of misbehaviours on parties not directly involved in the SE-mediated exchange.

The purpose of this paper is to examine peer-to-peer sharing platform business models, their sources of competitive advantage, and the roles, motivations and behaviors of key actors in their ecosystems.

This paper uses a conceptual approach that is rooted in the service, tourism and hospitality, and strategy literature.

First, this paper defines key types of platform business models in the sharing economy anddescribes their characteristics. In particular, the authors propose the differentiation between sharing platforms of capacity-constrained vs capacity-unconstrained assets and advance five core properties of the former. Second, the authors contrast platform business models with their pipeline business model counterparts to understand the fundamental differences between them. One important conclusion is that platforms cater to vastly more heterogeneous assets and consumer needs and, therefore, require liquidity and analytics for high-quality matching. Third, the authors examine the competitive position of platforms and conclude that their widely taken “winner takes it all” assumption is not valid. Primary network effects are less important once a critical level of liquidity has been reached and may even turn negative if increased listings raise friction in the form of search costs. Once a critical level of liquidity has been reached, a platform’s competitive position depends on stakeholder trust and service provider and user loyalty. Fourth, the authors integrate and synthesize the literature on key platform stakeholders of platform businesses (i.e. users, service providers, and regulators) and their roles and motivations. Finally, directions for further research are advanced.

This paper helps platform owners, service providers and users understand better the implications of sharing platform business models and how to position themselves in such ecosystems.

This paper integrates the extant literature on sharing platforms, takes a novel approach in delineating their key properties and dimensions, and provides insights into the evolving and dynamic forms of sharing platforms including converging business models.

This study aims to explore the chicken and egg paradox in the taxi e-hailing business contributing to define a condition of system emergence. This paradox is a meaningful one as these platforms represent a system where the passengers systems have no reason to participate if they have no drivers-systems to answer their call, but, at the same time, the platform is not useful to the drivers-system if there are no passengers-systems using the platform.

To understand how this paradox has been dealt with in the taxi e-hailing business, this study focused on a case study on a best practice in Italian taxi e-hailing industry (i.e. MyTaxi/FreeNow). This study wants to comprehend which actions have been implemented to solve this paradox and has tried to identify the interconnections between the various strategies to create a closed loop diagram for further testing.

This study has found that the company did not choose a single “subsystem” (passenger or driver), but it has stimulated the creation of several mutually reinforcing motivation for have both subsystems interact to help the company grow.

To the best of the authors’ knowledge, this paradox has never been studied using the complex adaptive system perspective. This perspective is particularly useful in this case and in the similar ones with several different interacting factors that cannot be really studied without using a higher order perspective.

In this paper, the authors study the effect of consumers' fairness preferences on dynamic pricing strategies adopted by platforms in a non-cooperative game.

This study applies fair game and repeated game theory.

This study reveals that, in a one-shot game, if consumers have fairness preferences, dynamic prices will slightly decline. In a repeated game, dynamic prices will be reduced even when consumers do not have fairness preferences. When fairness preferences and repeated game are considered simultaneously, dynamic prices are most likely to be set at fair prices. The authors also discuss the effect of platforms' discounting factors, the consumers' income and alternative choices of consumption on the dynamic prices.

The study findings illustrate the importance of incorporating behavioral elements in understanding and designing the dynamic pricing strategies for platforms and the implications on social welfare in general.

The authors developed a theoretical model to incorporate consumers' fairness preference into the decision-making process of platforms when they design the dynamic pricing strategies.