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This study aims to explain the influence of four socio-psychological variables: social comparison orientation, face saving (FS), status consumption (STC) and frugality (FGL) on consumers’ value perception toward ride-sharing services – one of the most widely used collaborative consumption models. Furthermore, it assesses how perceived value affects consumers’ intention to use (IU) the ride-sharing services and intentions to substitute ride-sharing services for using a personally owned car. It also assesses the moderating effect of psychographics on the relationship between consumers’ perception and behavioral intention.

A structured questionnaire was developed using existing scales adapted from the literature to test the hypothesized relationships. The data for the study were collected from 489 users of ride-sharing services in India. Structural equation modelling was performed to test the proposed model using AMOS 18 and moderation analysis was performed using PROCESS MACRO.

The findings of the study suggest that social comparison, FS, STC and FGL have a significant influence on consumers’ value (utilitarian and hedonic) perception. Furthermore, the results supported the effect of consumers’ value perception on their IU the ride-sharing services as well as their intention to substitute ride-sharing services for using a personally owned car. Lastly, the results also evidenced the moderating role of psychographic variables.

Very few studies have examined the role of psychographics in the adoption of collaborative consumption services. The paper attempts to fill this gap. It assesses the effect of four relevant consumer traits on perceived value in the ride-sharing services context. Furthermore, it expands the understanding of the role of psychographics by measuring their moderating effects apart from direct effects. The results of the study bear important implications for academicians, policymakers and marketers.

The sharing economy is changing the way people use products and services, and the success of sharing-based apps like bicycle and automobile sharing has drawn a lot of interest across the world. The purpose of this research is to investigate the factors affecting the consumer's adoption of ride-sharing services.

With this aim, the current study integrates the Technology Acceptance Model (TAM) and Expectancy Confirmation Model (ECM) with a further extension of consumer trust and social norms. Using a survey-based research design, data were collected from 558 respondents using multi-stage convenience sampling on 5 point Likert scale. Confirmatory factor analysis is conducted followed by structural equation modelling using IBM AMOS-22.

The findings of the study report crucial determinants for the consumer's continuance intention and actual use of these services. Perceived usefulness, consumer satisfaction, trust and subjective norms were found positively associated with the continuous intention to use ride-sharing services, whereas perceived ease of use was found to be insignificant. This study also highlights antecedents for the consumer's trust towards these services and found reputation, propensity to trust as a significant contributor whereas structural assurance was found insignificant to establish the trust among the users.

The research on consumer adoption towards ride-sharing services are meagre and this study adds the value to the field by integrating TAM and ECM model with further extension of consumer trust and social norms and empirically test the proposed model.

Identifying the complementary effects of ride-sharing on public transit is critical to understanding the potential value of growing partnerships between public transit agencies and ride-sharing platforms. The purpose of this paper is to investigate whether and how ride-sharing services complement public transit.

Taking advantage of a natural experiment whereby subway Line 2 opened after the entry of ride-sharing services in Xiamen, this study uses a difference-in-differences approach to identify the complementary effects of ride-sharing on public transit based on a proprietary fine-grained trip-level data set from a large ride-sharing platform.

This study obtained the encouraging finding that ride-sharing has a significant complementary effect on the subway, as the number of ride-sharing pickups and drop-offs at subway stations increased by 130% and 117.9%, respectively, after the subway opening. Moreover, mechanism analysis shows that the complementary effect of ride-sharing services is stronger when connection distance is short (i.e. under 6 km) and when the transportation availability is limited (i.e. at night or in the areas with low transit supply and low population density).

The findings provide guidelines for promoting cooperation between public transit agencies and ride-sharing platforms to build an efficient and sustainable urban transport system.

This study is the first to examine the complementary effect of ride-sharing services on public transit via unique fine-grained ride-sharing trips data, and further reveal the underlying mechanism behind this effect.

In the modern era of transportation, using a ride-sharing service can add an extra value to the lifestyles of women. Also, women are thinking about the ride-sharing service, what are the factors they consider while purchasing the service and so on. The purpose of this study is to find out women’s perception of ride-sharing services.

This paper is based on deductive research approach and descriptive research design. This paper has followed mixed research method by using qualitative and quantitative data. By dividing the larger population into subgroups, the researchers have conducted a survey on 240 respondents. To select these respondents, researchers have applied simple random technique. Based on a survey on consumers’ buying behaviour of ride-sharing service, the researchers tested the impact of tangibility, reliability, safety, fare, efficiency and convenience as the factors for choosing ride-share rather than other public transportation.

The study results indicate that reliability which includes consistency, punctuality and schedule routes are the major concerning issue for women while choosing ride-share service. Women are also concerned about efficiency which includes global positioning system tracking, smartphone technology and so on. One of the important criteria for choosing a ride-sharing service is safety, which includes verified drivers, and drivers review scores. So, reliability, efficiency and safety are the most effective issues. On the other hand, tangibility, fare and convenience do not affect that much.

To the best of the authors’ knowledge, this is the first research to scrutinize the sharing economy service in Dhaka city towards women’s perception of commuting.

The COVID-19 pandemic has generated unprecedented public fear, impeding both individuals’ social life and the travel industry as a whole. China was one of the first major countries to experience the COVID-19 outbreaks and recovery from the pandemic. The demand for outings is increasing in the post-COVID-19 world, leading to the recovery of the ride-sharing industry. Integrating protection motivation theory and the theory of reasoned action, this study aims to investigate ride-sharing customers’ self-protection motivation to provide anti-pandemic measures and promote the resilience of ride-sharing industry.

This study followed a two-phase mixed-methods design. In the first phase, the authors executed a qualitative study with 30 interviews. In the second phase, the authors used the results of the interviews to inform the design of a survey, with which 272 responses were collected. Both studies were conducted in China.

The present results indicate that customers’ perceived vulnerability of COVID-19 and perceived COVID protection efficacy (self-efficacy and response efficacy) are positively correlated with their attitude toward self-protection, thus leading to their self-protection motivation during the rides. Moreover, subjective norms and customers’ distrust appear to also impact their self-protection motivation during the ride-sharing service.

The present research provides one of the first in-depth studies, to the best of the authors’ knowledge, on customers’ protection motivation in ride-sharing services in the new normal. The empirical evidence provides important insights for ride-sharing service providers and managers in the post-pandemic world and promote the resilience of ride-sharing industry.

Despite the growing popularity of ride-sharing in China, our understanding regarding users' trust and behavioral intention toward this new type of hailing service is still limited. This study aims to examine the joint influences of institution-based, process-based and characteristic-based antecedents on customers' trust and continuance intention toward ride-sharing. Furthermore, the study aims to investigate if the relative influences of institution-based and process-based antecedents on trust are contingent upon customers' prior experience.

Drawing upon trust-building literature and the elaboration-likelihood model, we developed a research model and conducted an online survey to users of Didi, the largest ride-sharing platform in China. We used the structural equation modeling technique to analyze the collected data and examine the proposed research model.

Ther major research findings of the study suggest that structural assurance, government support, platform reputation and disposition to trust exhibit significant and different degrees of influences on customers' trust beliefs and continuance intention toward ride-sharing. A multi-group analysis further suggests that customers with less use experience focus more on government support and platform reputation, while customers with more use experience are more likely influenced by structural assurance.

The study contributes to the extant literature by identifying the joint influences of institutional-based, process-based and characteristic-based antecedents on users' continuance intention of ride-sharing service and uncovers the mediation mechanism of trust and perceived risk. Moreover, the study refines the boundary condition of the proposed research model by revealing the moderating effect of use experience.

A rash of security incidents in ride-sharing have made discovering the mechanisms to repair consumers' trust essential for the information technology (IT)-enabled ride-sharing platforms. The purpose of this paper is to explore how the two response strategies (i.e. security policies [SPs] and apologies) of platforms repair passengers' trust and whether the two implementation approaches of SPs (i.e. pull and push) lead to different results in repairing passengers' trust in the platforms.

A field survey based on a real scenario (n = 238) and an experiment (n = 245) were conducted to test the hypotheses empirically. Structural equation modeling and one-way analysis of variance (ANOVA) are employed in the data analyses.

This study finds that (1) both SPs and apologies aid in repairing trust; (2) repaired trust fully mediates the influence of SPs on continuance usage and partially mediates the influence of apologies on continuance usage; (3) security polices and the three dimensions of apologies play different roles in repairing trust and retaining passengers and (4) both pull-based and push-based SPs can repair the violated trust; however, the effect of the pull approach is greater than that of the push approach.

The findings provide guidelines for ride-sharing platforms in taking appropriate actions to repair users' trust after security incidents.

The findings reveal the mechanism of trust repairing in the fields of ride-sharing and extend the contents of the trust theory and pull–push theory.

This study aims to investigate how customers’ perceived risks of sharing economy (SE) affect their self-protective behaviors when using SE, leading to their future behavioral intention. Additionally, this study looks into whether there are any differences between accommodation-sharing and ride-sharing customers in the aforementioned relationships.

An online survey targeting two groups of SE customers (i.e. accommodation sharing and ride sharing) was used. Using partial least squares structural equation modeling, the mechanism of how SE customers’ perceived risks of SE affect their self-protective behaviors, which in turn influence their future behavior intention. A multigroup analysis was performed to assess the difference between the two groups of SE customers. Finally, a multivariate analysis of variance (MANOVA) was conducted to see the potential differences between the five classifications of self-protective behaviors in their perceived risks.

SE customers’ psychological risks positively affected their hygiene protective behaviors and social protective behaviors, influencing their behavior intention and relative intention (compared with traditional services). Social risk had a negative impact on SE customers’ hygiene protective behaviors. There was a significant difference between accommodation sharing and ride sharing customers in their psychological mechanism of how perceived risks influence their self-protective behaviors.

The findings of this study help SE platforms and service providers better understand their customers’ perceived risks of their services and suggest them to promote their customers’ self-protective behaviors so that perceived risks can be mitigated, thereby generating strong behavior intentions. As the results indicated that there is a significant difference between the two major forms of SE (i.e. accommodation sharing and ride sharing) in their customers’ perceived risks and self-protective behavior, SE platforms can further refine their operational and marketing efforts based on the findings.

This study offers a comprehensive understanding of SE customers’ self-protective behaviors by examining the effects of SE customers’ different perceived risks on their self-protective behaviors during the unprecedented pandemic. Furthermore, the comparison of the two most popular forms of SE (i.e. accommodation sharing and ride sharing) provides new perspectives to understand customers’ behavior in the SE context.

This study aims to analyze the effect of service quality on trust, satisfaction and loyalty by adopting two models, namely, conventional service quality model from Parasuraman and information systems (IS) success model from Delone and McLean.

Respondents of this study were users of shared-motorcycle services who filled out a complete questionnaire totaling 507. This research used a second-order structural equation model. All question items had quite high reliability and validity based on the result of confirmatory factor analysis with a value of average variance extracted and composite reliability which was higher than 0.70. The goodness of fit was quite good with the values x²/df = 2.493, incremental fit index = 0.921, Tucker-Lewis index = 0.917, comparative fit index = 0.921 and root-mean-square error of approximation = 0.054.

Online and offline ride-sharing services reveal a strong and positive influence on trust and satisfaction. Trust reveals a strong and positive influence on satisfaction and loyalty. Finally, satisfaction reveals a strong and positive influence on loyalty. The research in general shows that the quality of offline service is more influential than the quality of online service in the case of ride-sharing service provided by two companies in Indonesia.

The sampling frame of the research was diverse, including students of various collages and junior high schools, various private company workers and government employees. So, the results cannot be generalized to all populations especially to all Indonesian customers. It is recommended to increase the number of samples by focusing on the community groups of customers of public motorbikes, so that these groups can be compared. Next, the research finds that both service quality based on IS and service quality models reveal a strong and positive influence on loyalty both directly and indirectly.

The research uses respondents who use motorcycle services both online and offline. The findings of the research are important for online and offline ride-sharing motorbike service providers. They have to maintain their excellent services to the customers.

The proliferation of ride-hailing businesses brings significant considerations for improving the driver's operational performance. Informed by the literature on sharing economy, general deterrence theory and protection motivation theory this research investigates the behavioral factors impacting ride-hailing drivers' operational performance.

The authors empirically test the antecedents impacting a ride-hailing driver's operational performance using an online survey dataset comprising 513 ride-hailing drivers working for Uber and Lyft in the United States.

Ride-hailing drivers' intention to comply with the ride-hailing company guidelines results in better operational performance for the driver. Moreover, drivers believe that ride-hailing companies have effective penalties to deter drivers from violating company guidelines. However, drivers also believe that the chances of being caught while ignoring the company guidelines are low.

The results of this research support the decision-making processes of ride-hailing company managers and offer insights on how managers can enhance the operational performance of their drivers.

This study provides unique contributions to emerging research at the intersection of peer-to-peer asset sharing, behavioral studies and technology management. This research is one of the first to explore the role of behavioral factors such as coping mechanisms on the operational performance of sharing economy workers.