In face of high-investment and low-revenue crisis, it is critical for new-born car-sharing companies to focus on niche market. Existing literatures have already discussed the niche market of car sharing based on people’s irregular travel demands and scenarios; however, current research findings are still lack of adequate travel data support. Aiming to solve this problem, we develop a travel scenarios mining method that first define land usage types of travel Origin-Destination (OD) locations using spatial clustering analysis of city’s Points of interests (POI) data, and then discover the most representative travel scenarios using association rules mining method with car-sharing records data. Applying this approach to the car-sharing service case in Beijing, China, we find that: day-time business trips and evening entertainment trips around the city centre, commuting trips in off-peak time, and short-distance city travel for tourism are three travel scenarios suitable for car sharing’s niche in the initial stage of market entering. Furthermore, spatio-temporal consumption profiles and competitive advantages of car sharing in the three travel scenarios are analyzed. Finally, theoretical and managerial implications are discussed. In this study, we address the question of finding niche market and suggest that it is critical for car sharing industry treading through the crisis in the early stage of development.

The concept of convenient, comfortable, private, low-carbon and environmental protection has made time-sharing lease car sought after by the industry and capital since its launch. However, as an emerging travel mode, it faces problems such as low market penetration, low user interest and low willingness to sustain consumption. In order to promote its long-term stable development, this study will use the Means-End Chain Model (MEC) as the analysis model. Based on the tweets of three time-sharing lease car enterprises, namely More Fun, EVCARD and GoFun, and the comments of consumers in Baidu Tieba, three core value paths are extracted from enterprises and consumers. Through comparison, we found that: the publicity positioning of time-sharing lease car on convenient and cost-effective travel is consistent with consumers' post-use experience, but there is still a gap between them. Consumers are more concerned about the external attributes and benefits of time-sharing lease car, while enterprises lack consideration in this regard. This paper proposes a comparative analysis of the consistency between the strategic positioning points of enterprises and the positioning points perceived by consumers, aiming to provide a reference for the strategic optimization of shared mobility enterprises and the strategy formulation and execution of all enterprises.

Mobility as a service (MaaS) has emerged as a means to promote multimodal public transport and shared mobility trips, with the “Metro+” integrated mobility approach being its primary form. However, it has recently witnessed major global providers’ bankruptcies. Therefore, this study aims to identify factors driving users’ substitution of ride-hailing by “Metro+” MaaS intermodal trips. Specifically, we took ride-hailing trips as the baseline and constructed a multinomial logit (MNL) model incorporating travel-scenario factors, including trip purpose, weather, and urgency. The results show that travel-scenario factors significantly affected “Metro+” MaaS intermodal trip adoption for urban medium–long-distance trips. Users preferred MaaS intermodal trips for long-distance trips amid clear weather and no time pressure, and they favored ride-hailing in extreme weather conditions or for time-sensitive trips. Therefore, MaaS providers should emphasize travel scenarios in their marketing messaging. Finally, marginal rate of substitution (MRS) and elasticity analyses were conducted, and several strategies were proposed: (1) increasing ride-hailing availability; (2) improving transfer facilities and conditions; and (3) implementing dynamic demand matching. The study facilitates the identification of market opportunities for MaaS instead of car usage, contributes to MaaS marketing and service strategy optimization, and promotes sustainable urban transportation system development.

A deficit in comprehensive academic research on user feedback for time-sharing cars exists. This study addresses this shortfall by examining 123.8 thousand user posts from Baidu Post Bar’s social media. Within a customer journey framework, it gathers and assesses user feedback to chart the progression, repercussions, and triggers of negative experiences. The analysis shows that feedback clusters around car usage, return, settlement, and after-sales stages. Key issues, such as inadequate vehicle conditions, filthy interiors, and post-use violation misassessments, frequently lead to dissatisfaction and distrust, spurring negative word-of-mouth. The study further pinpoints the obsolescence of user supervision technology as a primary cause of user liability risks, including unruly customer behavior and hygiene concerns. This technological lag not only compounds these issues but also triggers a broken window effect through negative word-of-mouth, creating a vicious cycle of deteriorating service quality. Finally, the paper evaluates the efficacy of current service strategies in the time-sharing car industry and suggests strategic directions for future improvement.