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This study explores how sharing platforms achieve platform loyalty through various operation management strategies.

A multiple case study method has been conducted in two Chinese sharing economy industries: ride- and bike-sharing. Data were collected through 30 semi-structured interviews with managers from four platform companies (DiDi, Uber China, ofo and Mobike). Individual case studies were developed from the triangulation of all existing data. Concurrent with the development of these individual case studies was a cross-case analysis. Emerging patterns have been identified and compared to previous findings in the literature to build upon and modify the existing knowledge base and to formulate a series of propositions.

Platform asset characteristics and mergers and acquisitions affect supply network readiness and operational capacity, respectively, and this effect would consequently contribute to achieving platform loyalty through user satisfaction. Moreover, externality, as a moderator, may influence the strength of the relationship between satisfaction and platform loyalty.

The proposed theoretical model provides an overarching framework for sharing platform companies to design and operate their businesses while carefully examining the situations, contexts and actions of users and other stakeholders and choosing an appropriate strategic mechanism to drive platform growth.

This study is one of the first to empirically explain how firms in a sharing economy sector could gain platform loyalty by adopting an expectation–confirmation theory perspective.

In China, with the rapid dissemination of mobile communications technology along with congested traffic and increasingly expensive transportation costs, consumers are turning to smartphone-enabled, ride-sharing services. Sharing economy requires trust in strangers. Based on trust transfer theory and a dyadic conceptualization of trust from cognitive to affective, the purpose of this study is to examine trust building through the use of Didi, a third-party, ride-sharing platform that mediates exchanges among strangers.

Structural equation modeling (SEM) results based on 242 observations indicate that the platform functions as an important enabler of trust, which influences a consumer's behavioral intention.

Specifically, Didi's reputation and security assurance have a positive influence on passengers' cognitive trust in drivers. There is also evidence that the interaction as mediated by the app between passengers and drivers helps the formation of affective trust, while the results do not support a relationship between cognitive and affective trust.

The research findings address trust transference between participants in the sharing economy and its effects, which have significant theoretical and practical implications and offer opportunities for future research in other sectors of the sharing economy.

Drawing upon institution-based trust theory, the purpose of this paper is twofold: firstly, to examine the joint influences of legally binding and market-driven institutional mechanisms in promoting customers’ trust and continuance intention in the ridesharing platform; and secondly, to examine if there exists a trust transfer mechanism between institution-based trust and interpersonal trust.

An online survey was conducted in China and data were collected from 307 customers in DiDi, which is one of the largest ridesharing platforms in China. Structural equation modeling statistical method was used to test the theoretical model and research hypotheses.

The empirical results suggest that market-driven institutional mechanisms, regarding feedback and surge pricing, have strong influences on customers’ trust in the ridesharing platform. In addition, legally binding institutional mechanisms, regarding payment security and driver certification, are also beneficial to promote customers’ trust. Furthermore, there is a trust transfer between customers’ trust in the platform and trust in the driver.

This study provides guidelines to the administrators of the ridesharing platform to establish effective institutional mechanisms. In particular, the platform can appropriately adopt and implement the legally binding mechanisms combined with market-driven mechanisms on the platform, in order to enhance customers’ trust and promote their subsequent transaction behaviors.

This study enriches and extends the extant literature of institution-based trust from e-commerce to the sharing economy by identifying four significant institutional mechanisms. Furthermore, this study presents a new perspective of customer trust (one-to-many) in the context of ridesharing and uncovers the transfer mechanism between institution-based trust and interpersonal trust.

Many newly established Internet loss-making enterprises (NEILEs) are always willing to expand overseas within a very short time from their establishment. This phenomenon is becoming a hot research area. This paper aims to explore why these enterprises are always willing to expand overseas rapidly even if they are facing severe and persistent losses, and to study the different rapid internationalization modes and the international market entry ways for NEILEs.

This paper constructs a theoretical framework with the dual situation of negative attainment discrepancy and advantageous slack resources to explain the rapid internationalization of NEILEs. Furthermore, cross-case comparative analysis method, based on interviews, questionnaires and secondary data collection, is adopted to reveal the rapid internationalization modes and the international market entry ways of such enterprises.

Whether blocking competitors or seeking opportunities or both, NEILEs' goal of rapid internationalization depends on the severity and persistence of negative attainment discrepancy. When the severity and persistence of negative attainment discrepancy are very significant, moderate and mild, NEILEs choose sniper-type, opportunity-type and dual-type internationalization target mode in turn; it is very important for NEILEs to match advantageous slack resources and international market entry ways to achieve specific internationalization goals.

This paper enriches the understanding of NEILEs' transnational entrepreneurial behavior in the era of digital economy. The theoretical contribution of this paper is that the authors build a theoretical framework based on the logical starting point, the logical fulcrum and the logic ending point for understanding the rapid internationalization of NEILEs.

This study demonstrates that NEILEs can also expand into foreign markets according to their own characteristics. Undoubtedly, they need to choose appropriate internationalization target mode and international market entry way in line with the extent and duration of their losses, and their advantageous slack resources.

In this paper, the authors construct the rapid internationalization theory of NEILEs based on the dual situation of negative attainment discrepancy and advantageous slack resources in digital economy era. Moreover, the authors discover the behavioral characteristics and patterns of NEILEs' transnational entrepreneurship.

This study examines how customer loyalty among DiDi users in China is affected by two types of online social interaction (transactional and interpersonal) and how the online interaction–customer loyalty relationship is mediated by three kinds of perceived benefits (functional, social-hedonic and safety).

This study empirically examines research hypotheses based on a questionnaire survey of 428 DiDi consumers.

The results reveal that transactional interactions significantly enhance customer loyalty among DiDi users via the partial mediating effects of customers' perceived functional, social-hedonic and safety benefits. By contrast, interpersonal interactions do not directly influence customer loyalty, and only social-hedonic benefits fully mediate the positive influence of interpersonal interactions on loyalty.

This study contributes to the theoretical development of interactive marketing management by examining how two types of online social interactions contribute to customer loyalty on sharing economy platforms by influencing the perception of benefits. It also provides useful managerial insights to help ride-sharing platforms design online social interaction functions that improve customer perceptions and loyalty.

Over the past decade, research into sharing economy platforms has gained prominence. The purpose of this study is to investigate the role of perceived value (both hedonic and utilitarian) in attracting consumer engagement in the sharing economy, as well as its link with trust.

This study used a survey method to empirically tested the proposed model using the partial least squares approach to structural equation modeling on data from 320 DiDi app users.

The study's findings revealed that both hedonic and utilitarian value had a significant effect on satisfaction and trust in the platform. Although the results showed no effect of hedonic and utilitarian values on trust in driver, the authors found trust in driver and platform, and satisfaction had significant influences on users’ continued intention to use the Taxi-hailing app. Interestingly, this study suggests that trust in the platform is transferred to trust in the driver.

The results from the Necessary Condition Analysis shows that satisfaction and utilitarian value are necessary conditions of continuance intention.

Underpinned by the legitimacy perspective, this study explores how ride-hailing services are legitimized through resource exchange among the industry players. The authors explore the types of legitimacy involved in the legitimation process. The authors also examine the political games being played by the actors to attain legitimacy.

This qualitative study involves thirty-one stakeholders/interviewees from emerging Asia. The interview data are supported by online documents and observations.

Thematic analysis shows that the industry players collaborate to achieve political, market, alliance, social, and investment legitimacy. The collaborations also legitimize industry players' existence through an eclectic mix of the numerous stakeholders' actions. This study shows how Dacin's proposed four types of legitimacy are coexisting and interconnected. It also highlights the neglected political legitimacy.

The findings guide the policymakers and ride-hailing operators experiencing competing requests to legitimize sustainable ride-hailing service development in urban cities.

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.

Motivated by a problem in the context of DiDi Travel, the biggest taxi hailing platform in China, the purpose of this paper is to propose a novel facility location problem, specifically, the single source capacitated facility location problem with regional demand and time constraints, to help improve overall transportation efficiency and cost.

This study develops a mathematical programming model, considering regional demand and time constraints. A novel two-stage neighborhood search heuristic algorithm is proposed and applied to solve instances based on data sets published by DiDi Travel.

The results of this study show that the model is adequate since new characteristics of demand can be deduced from large vehicle trajectory data sets. The proposed algorithm is effective and efficient on small and medium as well as large instances. The research also solves and presents a real instance in the urban area of Chengdu, China, with up to 30 facilities and demand deduced from 16m taxi trajectory data records covering around 16,000 drivers.

This study examines an offline and single-period case of the problem. It does not consider multi-period or online cases with uncertainties, where decision makers need to dynamically remove out-of-service stations and add other stations to the selected group.

Prior studies have been quite limited. They have not yet considered demand in the form of vehicle trajectory data in facility location problems. This study takes into account new characteristics of demand, regional and time constrained, and proposes a new variant and its solution approach.