Consumer acceptance, barriers and success factors of peer-to-peer carsharing in perspective of connected car services and autonomous vehicles

Until now, car ownership has been a symbol of wealth and personal freedom. The high value of the car in society has been enforced by the powerful automotive industry with their well-funded marketing budgets. Currently, there are one billion cars worldwide, possibly increasing to 2,8 billion by 2050. However, the awareness of the negative consequences of car ownership on the environment, cities, and individuals in terms of reduced personal and financial freedom is increasing. The trend towards collaborative consumption involving activities like sharing and trading is leading to a shift from ownership to the access of goods and services. In this context, carsharing is receiving more and more attention and the number of users for B2C carsharing models is increasing exponentially. The least-developed business model with the biggest opportunities in terms of environmental benefits is peer-to-peer carsharing (P2P carsharing). Providers face daunting problems in reaching critical mass, due to a lack of consumer acceptance. Academic contributions on the topic are rare. The goal of this dissertation is to capture the acceptance factors, barriers and success factors for P2P carsharing. Additionally, the phenomenon is explored within the perspective of disruptive technologies, including the connected car and autonomous vehicles. A comprehensive literature review including collaborative consumption, carsharing, and in particular P2P carsharing, has been conducted. A mixed-method approach has been used. Qualitative interviews with leading academic and industry experts in the field of collaborative consumption and shared mobility, as well as a focus group discussion, have been executed. In the quantitative survey, the identified factors have been integrated into the Technological Acceptance Model (TAM), the theoretical foundation of the work. A representative survey was conducted in Austria with 801 respondents. The results were generated by applying a partial least squares analysis.