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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.

Artificial intelligence (AI) used in service has sparked fundamental changes in how enterprises engage their customers. AI specifically designed for customer service is denoted as service-oriented AI. Through the lens of social information processing theory and the pleasure-arousal-dominance (PAD) emotional state model, this study aims to examine the underlying mechanisms for service-oriented AI anthropomorphism to influence customers' propensity for value co-creation.

Our data were collected from hotel customers who had experienced interactions with service-oriented AI. Through purposive sampling, 350 survey responses were collected. We analyzed the survey data using covariance-based structural equation modeling (CB-SEM).

This study has two key findings. Firstly, customers' propensity for value co-creation is favorably facilitated by the anthropomorphism of service-oriented AI. Secondly, the anthropomorphism of service-oriented AI can strengthen customers' perceptions of cuteness and service capacity, elicit a sense of novelty, and enhance customers' propensity to collaborate with service-oriented AI to create value. These findings address the research gaps by focusing on customer engagement through service-oriented AI and provide a theoretical basis for subsequent practical endeavors in the field.

Integrating the PAD emotional state model with the social information processing theory, this study explores the effects of service-oriented AI's anthropomorphism on customers' propensity for value co-creation.

The space industry has experienced rapid development over the last few years. Activities such as building things in space, learning about our Earth and exploring outer space are satisfying people's fantasies and achieving humanity's ambitions. Such activities have also generated many issues that belong to several information systems (IS) research domains. In this article, the authors discuss the challenges and opportunities associated with the space economy.

The authors discuss why the emerging space economy opens a new frontier of e-commerce and data analytics. Linking three important IS research areas (i.e. digital commerce, data analytics and information security) to the space economy, this study motivates scholars to pay close attention to this promising new frontier for IS research.

The authors identify new research opportunities within several IS research contexts (digital commerce, data analytics and information security). The authors highlight the potential for opening a robust, interdisciplinary field in the IS domain that could provide valuable insights for practitioners and academics.

Because of the unique characteristics of the space economy, this article presents some promising avenues, research opportunities and implications for several IS fields (digital commerce, data analytics, decision science, information sharing and information security and new business models). Indeed, many opportunities are interdisciplinary in scope, with overlaps occurring between IS and other disciplines.

A smart city is a potential solution to the problems caused by the unprecedented speed of urbanization. However, the increasing availability of big data is a challenge for transforming a city into a smart one. Conventional statistics and econometric methods may not work well with big data. One promising direction is to leverage advanced machine learning tools in analyzing big data about cities. In this paper, the authors propose a model to learn region embedding. The learned embedding can be used for more accurate prediction by representing discrete variables as continuous vectors that encode the meaning of a region.

The authors use the random walk and skip-gram methods to learn embedding and update the preliminary embedding generated by graph convolutional network (GCN). The authors apply this model to a real-world dataset from Manhattan, New York, and use the learned embedding for crime event prediction.

This study’s results show that the proposed model can learn multi-dimensional city data more accurately. Thus, it facilitates cities to transform themselves into smarter ones that are more sustainable and efficient.

The authors propose an embedding model that can learn multi-dimensional city data for improving predictive analytics and urban operations. This model can learn more dimensions of city data, reduce the amount of computation and leverage distributed computing for smart city development and transformation.

The study aims to measure the contribution rate of scientific and technological progress of Shaanxi province and find out the main driving force of its economic development, which has important reference significance for formulating and implementing the economic and social development strategy of Shaanxi Province and other regions.

By comparing and referring to the advantages and disadvantages of existing research methods, this paper combined C-D production function and Solow residual method to calculate the elastic coefficient through neural network algorithm, and then calculated the contribution rate of technological innovation to economic growth in Shaanxi province as a whole and in various regions, analyzed and put forward reasonable suggestions.

The results show that the economic growth is mainly depends on capital investment, and the contribution rate of technological innovation to economic growth is low and fluctuates greatly. In the future, each region of Shaanxi should improve the ability of technological innovation to speed up the economic transformation to the intensive type.

To make the technological innovation in Shaanxi province and other regions play a more significant role in promoting economic growth and accelerate the productivity and economic transformation of Shaanxi Province, the following suggestions are put forward, strengthen the coordinated development of innovation and economy in all regions of Shaanxi. Second, this paper need to give full play to the role of policy support and incentives. Third, this paper need to improve the market system and vigorously support enterprise innovation. Fourth, use new and high technology to transform and upgrade industrial technology. Fifth, this paper need to speed up the development of high-quality personnel.

Livestreaming, as a relatively new online marketing model, has generated numerous business opportunities for e-commerce and social commerce. The purpose of this paper is to investigate to what degree livestreaming content impacts online users' cognitive and emotional reactions and whether their cognitive and emotional responses affect their purchase intention.

Through the lens of regulatory focus theory (RFT) and stimulus–organism–response (S–O–R) theory, the authors empirically examine the influencing mechanisms of livestreaming on online consumers' purchase intentions. Structural equation models are used to analyze the relationships in the proposed research model.

The results of this study show that information-task fit positively affects consumers' perceived usefulness of livestreaming. Both visual effects and sociability positively affect consumers' perceived value and social presence. Furthermore, perceived usefulness and perceived joy positively affect consumers' purchase intentions in a livestreaming environment. This study’s results also demonstrate that the regulatory focus of consumers has a moderating effect on the influence of their perceived joy on shopping intentions.

This study contributes to the relevant literature by simultaneously examining the role of e-commerce platform characteristics and online consumer psychology in influencing behavioral intention. With a better understanding of their role, platform operators and sellers can refine their livestreaming marketing tools and strategies. Highlighting the interplays among external stimuli, user reactions and user motivational styles, this study contributes to mobile e-commerce literature and the broader literature on digital marketing and human–computer interaction.

This study explores the factors influencing the value of enterprise social media (ESM) from the perspective of compatibility. Establishing a theoretical model based on compatibility theory, the authors examine the effects of two dimensions of compatibility and the mediating effects of employees' intrinsic motivations. ESM is an important tool that helps companies to enhance knowledge sharing and cross-department collaboration. Thus, it is important to understand factors that can facilitate the role of ESM in improving enterprise operating performance.

The authors conducted a survey among 353 users of a leading ESM platform and empirically investigated how compatibility influences ESM value through employees' intrinsic motivations. Structural equation modeling (SEM) was applied to study the relationship among compatibility, employees' intrinsic motivations and ESM value.

The empirical research results indicate that compatibility of self-interest with group interest influences the value of ESM, and intrinsic motivations toward collaboration and toward knowledge management partially mediate the effects of the two dimensions of compatibility on ESM value.

First, the empirical analysis relies on data from surveying employees of Chinese companies. Therefore, one direction for future research is to reexamine the model using data from other countries. Second, the effects of compatibility identified in the study may vary among different ESM platforms. In addition, the findings may change for organizations having different sizes.

This finding suggests that managers should pay close attention to potential conflicts of interest when implementing ESM to enhance group communication and collaboration. This study also highlights the importance of compatibility of new working processes with experience in practice. In addition, intrinsic motivations towards both cooperation and knowledge management in ESM are important factors influencing the value creation of ESM. Therefore, to cultivate employees' intrinsic motivation, managers and organizations need to facilitate the formation of a collaborative atmosphere and habits of cooperative adoption.

Although previous studies show that compatibility is a strong belief salient to technology acceptance and continuance usage behavior, the operational definition of compatibility developed by prior studies has generally been limited to the technology perspective and the individual level. However, the primary benefit of ESM is enabling online team collaboration and knowledge sharing across various departments. Thus, the level of compatibility between employees' self-interests and group interests may influence their intrinsic motivations toward ESM usage. From this perspective of individual–group interest conflicts, the authors propose a conceptual research model based on the theory of compatibility in innovation diffusion.

This paper aims to explore the influence of marketing investment on drug diffusion processes, to analyze the heterogeneity of the diffusion characteristics and to understand the drug diffusion patterns in the prescription and over-the-counter (OTC) markets.

The study introduces marketing investment into the Bass model. The authors use the Generalized Bass Model (GBM) to examine the influence of marketing efforts on drug diffusion in Chinese prescription and OTC markets.

The results of this study suggest that the imitation effect in the prescription drug market is greater than that in the OTC drug market; drug diffusion in the OTC market reaches saturation earlier in the diffusion process. Before reaching the critical state, the effect of marketing investment on drug diffusion in the OTC market is greater than that in the prescription market, and after the critical state, drug diffusion in the prescription market is more sensitive to marketing investment.

The study demonstrates the value of the GBM in empirical analyses of drug diffusion across two distinct markets, and the marketing regulation policies governments adopt have a powerful impact on the speed at which drugs become available in different markets. It enriches the extant product diffusion literature by highlighting the different diffusion patterns of the two segments of pharmaceutical market.

The purpose of this perspective article is to identify the developmental trajectory of human resource management (HRM) research in the Mainland China as well as the major research gaps to be filled in the future. In particular, the paper focuses on the current challenges as well as the emerging research trends by reviewing the literature in HRM research in the Mainland China.

The paper takes a geocentric perspective of HRM theory development to analyze the status quo as well as the emerging trends of the future HRM research in the Mainland China.

HRM research in the Mainland China exhibited an obvious tendency of adopting an etic approach at the early stage of research, but displaying an emerging trend toward an emic approach at a later stage. However, the current HRM research in the Mainland China, including both etic and the emic approaches, falls seriously short of meeting the high-quality standards of the international academic community.

Through analyzing the status quo of HRM research in the Mainland China, the paper identified an emerging trend toward an integration of both etic and emic approaches in which the two approaches constitute a yin-yang duality as a unity-in-opposites toward a geocentric HRM research framework with a holistic, dynamic and duality etic-emic balance.