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The purpose of this study is to propose and test an integrated model to explain how trust is built in sharing economy (SE) transactions.

Initially, prior literature was systematically selected and synthesized to develop a comprehensive framework applicable to multiple trust-building perspectives and categories of SE platforms. Then, a survey was conducted to validate the constructs and test the model with Airbnb guests. A sample of 351 responses was collected and analyzed using structural equation modeling.

The results indicate that the cues an individual assesses to infer their counterpart’s trustworthiness and the reasons the individual has for engaging in the SE transaction can explain a large variance in their trust in the counterpart. In addition, the individual’s propensity to trust moderates this relationship.

The proposed model can help identify the most effective trust-building mechanisms. It can be taken as a common knowledge base for scholars to compare the four trust-building perspectives and different categories of SE platforms, as well as to investigate the subject over time and across cultures.

This research can also help practitioners understand the complexity of building trust and design platform features to do so.

A unified model clarifies trust in the SE, aiding platform growth and community bonding. This insight guides platforms in feature enhancement and policymakers in drafting balanced regulations.

To the best of the authors’ knowledge, for the first time, there is a comprehensive and parsimonious model applicable to the four trust-building perspectives and different categories of SE platforms.

We investigate the extended service strategy choices of competing manufacturers and examine their impact on the retail platform.

We construct a supply chain model with a retail platform as the leader and manufacturers as the followers. Manufacturers face differential consumer preferences on the same agency retail platform, and they can sell a bundled extended service product and sell a separate product without any extended service.

The sale of extended warranty services on the retail platform leads to lower pricing of the manufacturers' products and changes in the product market structure in response to differences in consumer preferences. The retailing platform tends to provide an extended warranty conditionally. The sale of extended warranty services on a retail platform would be detrimental to the interests of the manufacturer who sells products with extended warranty services and in favor of the manufacturer who sells products without them.

The equilibrium results of the retail platform’s non-sales and sales of extended warranty services for the no-extended warranty product under the same commission rate and differential commission rate models are discussed, and the product structure of the market is investigated, respectively.

We consider a joint optimization problem of product platform design and scheduling on unrelated additive/subtractive hybrid machines, and seek to find efficient solution approaches to solve such problem.

We propose a mathematical formulation for the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines, and develop a simulated annealing-based hyper-heuristic algorithm with adjustable operator sequence length to solve the problem.

The simulated annealing-based hyper-heuristic algorithm with adjustable operator sequence length (SAHH-osla) that we proposed can be quite efficient in solving the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines.

To the best of our knowledge, we are one of the first to consider both cost-related and time-related criteria for the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines.

Based on the perspective of knowledge management capability, this paper aims to reveal the internal mechanism of the digital empowerment of mobile social platforms to improve the operational performance of Chinese traditional retail enterprises. Such improvements have crucial theoretical value and practical implications for Chinese traditional retail enterprises to achieve transformation and sustainable development.

This study applied the typical analysis method, selected China’s leading mobile social platform, WeChat, as a typical case, and observed and analyzed the public data of the traditional retail industry and social platforms and interviews with relevant enterprises. On this basis, this study used the inductive and deductive methods of qualitative research to conduct an in-depth analysis of the mechanism by which WeChat’s digital empowerment improves the operational performance of Chinese traditional retail enterprises. It also discussed the critical role and path knowledge management capabilities play in this mechanism.

This research demonstrated that mobile social platforms empower Chinese traditional retail enterprises to build diversified digital channels, enhance the knowledge acquisition capability of enterprises and thus improve their performance; empower Chinese traditional retail enterprises to build digital community networks, enhance the knowledge diffusion capability of enterprises and thus improve their performance; and empower Chinese traditional retail enterprises to integrate online and offline businesses, enhance the knowledge integration capability of enterprises and thus improve their performance.

This study clarifies the internal mechanism of how the digital empowerment of mobile social platforms can improve the performance of Chinese traditional retail enterprises. This mechanism implies that knowledge management capabilities (knowledge acquisition, diffusion and integration capability) are the underlying logic for Chinese traditional retail enterprises to achieve higher performance levels. This has important practical implications for managers of Chinese traditional retail enterprises to leverage the digital infrastructure of mobile social platforms to achieve the sustainable development of enterprises.

This study provides an in-depth analysis of how the traditional retail industry uses digital social platforms to improve operational performance from the perspective of knowledge management capabilities, which can further promote the theoretical research and practical development of digitalization and knowledge management. At the same time, this study explored the research on the operational performance of Chinese traditional retail enterprises from the perspective of knowledge management capabilities and expanded the research on knowledge management in related fields. The authors have initially sorted out the impact of knowledge management capabilities on the operational performance of Chinese traditional retail enterprises in the digital era. This will help better understand the role and function of knowledge management in strategic transformation and expand the application of knowledge management theory.

The importance of service firms cooperating with digital platforms is widely acknowledged. The authors study three contractual relationships (fixed-cost, cost-sharing, and profit-sharing) between service firms (specifically hotels) and digital platforms in a highly fragmented service supply chain to examine which of these contract types optimizes profits.

The authors extend prior models analyzing the optimal expected total profit from the travel service firm (hotel)–digital platform relationship, providing new insights into each contract type’s ability to coordinate decentralized systems and optimize profits for both parties.

This study finds that fixed cost contracts cannot coordinate the decentralized system. Cost-sharing contracts can coordinate the decentralized system but only allow one channel profit split. In contrast, profit-sharing contracts may not always perfectly coordinate the decentralized system but support alternative profit allocations. Practically, both profit-sharing and cost-sharing contracts are preferable to fixed-cost contracts.

The paper includes implications for travel service firm managers to consider when structuring contracts with digital platforms to focus on profit optimization. Profit-sharing contracts are most preferable when cost and revenue data are fully shared between parties, while cost-sharing contracts are preferable over fixed-cost contracts.

This study extends prior investigations into the utility of different contract types on the optimal profit of a travel service firm (hotel)-digital platform provider relationship. The research fills a gap in the literature concerning the contracts used in these relationship types.

Algorithms are widely used to manage various activities in the gig economy. Online car-hailing platforms, such as Uber and Lyft, are exemplary embodiments of such algorithmic management, where drivers are managed by algorithms for task allocation, work monitoring and performance evaluation. Despite employing substantially, the platforms face the challenge of maintaining and fostering drivers' work engagement. Thus, this study aims to examine how the algorithmic management of online car-hailing platforms affects drivers' work engagement.

Drawing on the transactional theory of stress, the authors examined the effects of algorithmic monitoring and fairness on online car-hailing drivers' work engagement and revealed the mediation effects of challenge-hindrance appraisals. Based on survey data collected from 364 drivers, the authors' hypotheses were examined using partial least squares structural equation modeling (PLS-SEM). The authors also applied path comparison analyses to further compare the effects of algorithmic monitoring and fairness on the two types of appraisals.

This study finds that online car-hailing drivers' challenge-hindrance appraisals mediate the relationship between algorithmic management characteristics and work engagement. Algorithmic monitoring positively affects both challenge and hindrance appraisals in online car-hailing drivers. However, algorithmic fairness promotes challenge appraisal and reduces hindrance appraisal. Consequently, challenge and hindrance appraisals lead to higher and lower work engagement, respectively. Further, the additional path comparison analysis showed that the hindering effect of algorithmic monitoring exceeds its challenging effect, and the challenge-promoting effect of algorithmic fairness is greater than the algorithm's hindrance-reducing effect.

This paper reveals the underlying mechanisms concerning how algorithmic monitoring and fairness affect online car-hailing drivers' work engagement and fills the gap in the research on algorithmic management in the context of online car-hailing platforms. The authors' findings also provide practical guidance for online car-hailing platforms on how to improve the platforms' algorithmic management systems.

Drawing on information foraging theory and the SERVQUAL model, this study built a research model to investigate the roles of middle-aged and elderly short-video creators' online attributes in attracting short-video viewers to be their followers.

Taking Douyin (a famous short-video platform in China) as an example, this study used a sequential triangulation mixed-methods approach (quantitative → qualitative) to examine the proposed model by investigating both creators and viewers.

Viewers who clicked the “like” button for the middle-aged and elderly creators' videos are more likely to follow the creators. Viewers will believe that middle-aged and elderly creators who received more likes are more popular. Thus, middle-aged and elderly creators with more likes usually have more followers. Viewers usually believe that middle-aged and elderly creators who more frequently publish professional and high-quality videos have invested more effort and who have official verification also have a high level of authority and are recognized by the platform. Thus, middle-aged and elderly creators with more professional videos and verification usually have more followers. Moreover, verification, the number of videos and the professionalism of videos can enhance the transformation of viewers who liked middle-aged and elderly creators' videos into their followers, and thus strengthen the positive relationship between the number of likes and the number of followers; however, the number of bio words will have an opposite effect.

These findings have implications for platform managers, middle-aged and elderly creators and the brands aiming to develop a “silver economy” by attracting more followers.

This study researches short-video platforms by using a mixed-methods approach to develop an understanding of viewers' decision-making when following middle-aged and elderly creators based on information foraging theory and the SERVQUAL model from the perspectives of both short-video creators and viewers.

Digital platforms (DP) are transforming service delivery and affecting associated actors. The position of DPs is impacted by the regulations. However, emerging economies often lack the regulatory environment to support DPs. This paper aims to explore the regulatory developments for DPs using the multi-level perspective (MLP).

The paper explores regulatory developments of ride-hailing platforms (RHPs) in India and their impacts. This study uses qualitative interview data from platform representatives, bureaucrats, drivers, experts and policy documents.

Regulatory developments in the ride-hailing space cannot be explained as a linear progression. The static institutional assumptions, especially without considering the multi-actors and multi-levels in policy formulation, do not serve associated actors adequately in different times and spaces. The RHPs regulations must consider the perspective of new RHPs and the support available to them. Non-consideration of short- and long-term perspectives of RHPs may have unequal outcomes for established and new RHPs.

This research has implications for the digital economy regulatory ecosystem, DPs and implications for policymakers. Though the data from legal documents and qualitative interviews is adequate, transactional data from the RHPs and interviews with judiciary actors would have been insightful.

The study provides insights into critical aspects of regulatory evolution, governance and regulatory impact on the DPs’ ecosystem. The right balance of regulations according to the business models of DPs allows DPs to have space for growth and development of the platform ecosystem.

This research shows the interactions in the digital space and how regulations can impact various actors. A balanced policy can guide the paths of DPs to have equal opportunities.

DP regulations have a complex structure. The paper studies regulatory developments of DPs and the impacts of governance and controls on associated players and platform ecosystems.

The sharing economy has evolved as a result of the diffusion of information and communication technology and facilitates collaborative consumption and production otherwise known as value co-creation. The present research aims to explore the consumer responses to value co-creation in sharing economy such as satisfaction, brand preference and enduring buyer–platform relationships, amid consumer's CSR concerns.

Drawing on the sharing economy and value co-creation literature and rooted in the stimulus-organism-response framework, an online panel data provider was employed to recruit 393 actual sharing economy consumers from the United States. Empirical analyses are performed using structural equation modeling through Amos, version.27.

Findings confirm that value co-creation intentions contribute to consumers' satisfaction, brand preference and sustainable social relationships in the sharing economy. As expected, heightened concerns of corporate social responsibility (CSR) led to decreased consumer satisfaction with the sharing economy platform.

The study contributes to the digital sharing economy literature by emphasizing the role of CSR perceptions for building long-term relationships (buyer–platform relationships) where value co-creation is crucial.

This paper aims to propose the mechanism of cross-network effect embedded, which can help cross-border e-commerce (CBEC) platforms strengthen cooperative relationships with sellers more equitably and effectively by using the network structural characteristics of the platforms themselves.

A two-stage evolutionary game model has been used to confirm the influence factors. The mathematical derivation of evolutionary game analysis is combined with the simulation method to examine the role of cross-network effect in cooperation. The evolutionary game model based on the cross-network effect is proposed to achieve better adaptability to the study of cooperation strategy from the two-sided market perspective.

The evolutionary game model captures the interactions of cross-network effect and the influence factors from a dynamic perspective. The cross-network effect has a certain substitution on the revenue-sharing rate of SMEs. CBEC platforms can enhance the connection between consumers and the website by improving the level of construction, which is a good way to attract sellers more cost-effectively and efficiently.

This study provides a new method for the validation of the cross-network effect, especially when data collection is difficult. But this method is only a numerical simulation. So the conclusions still need to be further tested empirically. Besides, researchers are advised to explore the relationship between the added user scale and the cross-network effect in some specificCBEC platforms.

This study provides a new method for the validation of the cross-network effect, especially when data collection is difficult. But this method is only a numerical simulation. So the conclusions still need to be further tested empirically. Besides, researchers are advised to explore the relationship between the added user scale and the cross-network effect in some specific CBEC platforms.

Investigations that study cooperation strategy from the cross-network effect perspective in CBEC are limited. The research figured out which influence factors are affected by the cross-network effect in cooperation. A two-stage evolutionary game model was proposed to explain the interaction of the factors. The evolutionary game analysis with a simulation method was combined to highlight the role of cross-network effect on cooperation strategy to give a deeper investigation into the sustainable cooperation ofCBEC.