Search Results (7)

Ridesharing platforms have gained a strong foothold as an alternative transportation option to vehicle ownership for consumers while being contested for causing widespread market disruption. They continue to foster business model innovation and unveil new opportunities for delivering goods and services within the broader sharing economy. However, relatively little is known about the comparative value of services provided by the numerous ridesharing platforms available today. We, therefore, analyze three exemplars within the broader sharing economy: Uber^®, BlaBlaCar^®, and Zimride^®. We find that these ridesharing platforms are unique service systems with different designs for facilitating peer-to-peer service interactions, which are reflected in their technology features, affordances, and constraints. Our analysis offers researchers and platform owners new ways to conceptualize and understand these two-sided, digital markets with a range of participants, user goals, and service experiences. In particular, we demonstrate that platforms can be designed to cultivate entrepreneur dependency or enable prosumer communication and collaborative consumption. Given pending legislation to regulate platform-based work, platform owners should be mindful about creating an asymmetrical power imbalance with providers given assumptions about service interactions and technology features. Furthermore, researchers should account for service design differences, as well as the technology affordances and constraints, of platforms. Full article

A sharing platform is a digital platform that facilitates access to underutilized goods by renting or lending them to others. Users become less dependent on ownership which improves efficiency, sustainability, and the sense of community. The Sharing Economy (SE) is considered a complex domain because value co-creation can occur between multiple types of platform users. Developing platform software that offers the right functionality for the intended digital platform is therefore challenging. To address this complexity, an ontology can be utilized, which is an explicit specification of a conceptualization that provides a controlled vocabulary and shared meaning regarding a domain. The use of a sharing platform ontology allows for more effective communication and knowledge sharing amongst stakeholders in platform development and eventually drives the platform software development process. However, currently, it is not known how to develop such an ontology. In previous research, we developed the Digital Platform Ontology (DPO) and an extension of the DPO for describing platform business model choices. The DPO describes the digital platform domain in terms of digital platform types, including sharing platforms. However, a method to use the DPO and its business model extension for developing an organization-specific ontology that describes the functionality and business model of a specific existing or intended sharing platform was lacking. In this paper, we develop such a method using the Design Science Research Methodology (DSRM) and demonstrate it using a proof-of-concept based on the BlaBlaCar and Couchsurfing platforms. Full article

Sharing Economy platforms have expanded their operations all around the globe at an unexpected rate. Due to its “asset-lite” nature, traditional internationalisation theories may not be able to fully explain or predict their expansion patterns. This lack of theoretical background puts at risk the phenomenon’s future and stops traditional companies from coming up with a solid plan to compete against platforms. To ease the creation of a Sharing Economy internationalisation paradigm, this paper intends to review the existing research regarding the internationalisation of sharing platforms as well as the applicability of existing theories. Through a systematic literature review, the existing research was reviewed, and afterwards, internationalisation theories and their distinct factors extracted were noted to address the applicability of these within the singularities of the sharing phenomenon. This classification of factors was done according to the exiting literature in the field. After this research, we can confirm the lack of explanatory power of traditional theories regarding sharing platforms and confirm the insufficient research regarding these operations. We propose a list of factors that should be considered for future research as a guideline for the further development of the Sharing Economy internationalisation theory. Additionally, the factors classification is tested upon the case of the internationalisation of Blablacar, the most extensive carpooling network operating, to check if the theoretical and the practical approaches converge. Full article

The work aims to achieve a better understanding of firms’ green strategy, and specifically, in the false green strategy called greenwashing, and the relationships between greenwashing (GW) and behaviour intention (BI), and how this relationship is affected by word of mouth (WOM) and corporative social responsability (CRS). A survey was conducted and 198 valid and complete online questionnaires were collected from users of urban mobility apps (Blablacar and Amovens) in Spain. The structural equation modeling technique partial least squares (PLS-SEM) was used to test the proposed research model and hypothesized relationships. The results of our study indicate that the direct relationship between GW and BI is not supported, although the indirect relationship through WOM and CRS is significant, so that both become mediating variables of the GW and BI relationship. The paper also analyzes the direct relationships between GW, CRS, WOM and BI, so that the direct effects GW and CRS; CRS and WOM; and WOM and BI are significant. This empirical study analyzes the effect of GW, which has not been studied much, especially in empirical research. The study analyzes several variable consequences of GW and analyzes mediating effects of CRS and WOM on the GW and BI relationship. The study also includes two behavioral indicators, WOM and BI, in a research model, and, additionally, the study demonstrates the relationship between GW and perceived CRS. Full article

Peer-to-peer markets are especially suitable for the analysis of online ratings as they represent two-sided markets that match buyers to sellers and thus lead to reduced scope for opportunistic behavior. We decompose the online ratings by focusing on the customer’s decision-making process in a leading peer-to-peer ridesharing platform. Using data from the leading peer-to-peer ridesharing platform BlaBlaCar, we analyze 17,584 users registered between 2004 and 2014 and their online ratings focusing on the decomposition of the explicit determinants reflecting the variance of online ratings. We find clear evidence to suggest that a driver’s attitude towards music, pets, smoking, and conversation has a significantly positive influence on his received online ratings. However, we also show that the interaction of female drivers and their attitude towards pets has a significantly negative effect on average ratings. Full article

In recent years, the sharing economy has become popular, with outstanding examples such as Airbnb, Uber, or BlaBlaCar, to name a few. In the sharing economy, users provide goods and services in a peer-to-peer scheme and expose themselves to material and personal risks. Thus, an essential component of its success is its capability to build trust among strangers. This goal is achieved usually by creating reputation systems where users rate each other after each transaction. Nevertheless, these systems present challenges such as the lack of information about new users or the reliability of peer ratings. However, users leave their digital footprints on many social networks. These social footprints are used for inferring personal information (e.g., personality and consumer habits) and social behaviors (e.g., flu propagation). This article proposes to advance the state of the art on reputation systems by researching how digital footprints coming from social networks can be used to predict future behaviors on sharing economy platforms. In particular, we have focused on predicting the reputation of users in the second-hand market Wallapop based solely on their users’ Twitter profiles. The main contributions of this research are twofold: (a) a reputation prediction model based on social data; and (b) an anonymized dataset of paired users in the sharing economy site Wallapop and Twitter, which has been collected using the user self-mentioning strategy. Full article

The present study analyzes four well-known online platforms used in the tourist industry for travelling, accommodation, eating, and touring (Blablacar, Airbnb, Eatwith, and Trip4real). The objective is to analyze the utility of the portals, intentions for future use and recommendation (prospective), and reputation. The method is an experimental design with a control group and experimental group. Within both groups, three scales were applied. The results indicate clear differences between the control and experimental groups, valuing above all the utility and the intent to use again when the group is exposed to the portals from a needs-based situation (experimental group). The analysis demonstrates a factorial structure that validates the model. At the same time, the results indicate a greater interest in using Trip4Real over BlaBlaCar. Generation Z, the youngest generation, shows greater confidence in the services and greater interest in using tourism related collaborative consumption platforms in the future. Full article