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The purpose of this study is to explore how digital transformation helps enterprises achieve high-quality development, including the mediating mechanism of information transparency, innovation capacity and financial stability, the moderating role of financing constraints and government subsidies, and the heterogeneous effects of property rights, size and growth.

This study conducts two-way fixed-effect model using 780 samples of China's Shanghai-Shenzhen A-share listed companies from 2012 to 2019.

The results show that digital transformation can effectively improve the total factor productivity (TFP) of enterprises through the triple channels of information transparency, innovation capability and financial stability. Meanwhile, financing constraints significantly inhibited the contribution of digital transformation to TFP, while government subsidies significantly increased the contribution of digital transformation to TFP. In addition, state-owned enterprises (SOEs), large enterprises and high-growth enterprises are more able to achieve high-quality development by increasing their digital transformation.

In the process of implementing digital transformation, companies should actively improve information transparency, financial stability and innovation capabilities, and choose differentiated paths based on intrinsic characteristics such as property rights, scale and growth. At the same time, the government should actively improve not only the digital institutional environment but also the financial policy and credit system.

This study enriches the theoretical research framework of digital transformation and high-quality development by identifying the channel mechanisms and boundary conditions through which digital transformation affects high-quality development and expands the consequences of digital transformation and the antecedents of high-quality development.

This study aims to investigate the intersection of financial technology (fintech) and credit risk exploring the impact of fintech on credit risk within the banking and financial sector.

Using a bibliometric analysis approach, this study comprehensively reviews existing literature to understand the evolving landscape of fintech and credit risk. Data were extracted from the Scopus database using a comprehensive query encompassing various fintech-related keywords and their synonyms.

This study pinpoints six research streams on fintech and credit risk, spanning credit risk management, risk-sharing, credit scoring, regulatory challenges, small business lending impact and consumer credit market influence. It also examines recent advancements like artificial intelligence, blockchain and big data analytics in managing risk obligations.

While this study offers a comprehensive assessment, limitations include the ever-evolving nature of technology and potential biases in the retrieval process. Researchers should consider these factors when building on this study's findings.

The findings have practical implications for financial institutions, policymakers and researchers, offering insights into the opportunities and challenges presented by fintech in credit risk management. This study highlights potential areas for the application of advanced technologies in risk assessment and mitigation.

This study underscores the transformative impact of fintech on financial services, emphasizing the potential for more inclusive access and improved risk management. It encourages further exploration of fintech's societal implications, including its role in small business lending and consumer credit markets.

This study contributes to the existing body of knowledge by conducting a thorough bibliometric review, surpassing previous analyses in scope. It encompasses an extensive set of keywords to ensure the comprehensive retrieval of relevant papers, providing a foundation for future research in the dynamic field of fintech and credit risk.

Waiting time, as an important predictor of queue abandonment and patient satisfaction, is important for resource utilization and patient experience management. Medical institutions have given top priority to reforming the appointment system for many years; however, whether the increased information transparency brought about by the appointment scheduling mechanism could improve patient waiting time is not well understood. In this study, the authors examine the effects of information transparency in reducing patient waiting time from an uncertainty perspective.

Leveraging a quasi-natural experiment in a tertiary academic hospital, the authors analyze over one million observational patient visit records and design the propensity score matching plus the difference in difference (PSM-DID) model and hierarchical linear modeling (HLM) to address this issue.

The authors confirm that, on average, improved information transparency significantly reduces the waiting time for patients by approximately 6.43 min, a 4.90% reduction. The authors identify three types of uncertainties (resource, process and outcome uncertainty) in the patient visit process that affect patients' waiting time. Moreover, information transparency moderates the relationship between three sources of uncertainties and waiting time.

The authors’ work not only provides important theoretical explanations for the patient-level factors of in-clinic waiting time and the reasons for information technology (IT)-enabled appointment scheduling by time slot (ITASS) to shorten patient waiting time and improve patient experience but also provides potential solutions for further exploration of measures to reduce patient waiting time.

By investigating trust in the organization as a mediator and traditionality as a moderator, this study aims to examine the effect perceived organizational exploitation poses on frontline hotel employees’ service performance.

A three-wave survey that targets 219 supervisor–subordinate dyads from four Chinese hotels was conducted to test the hypotheses. The authors used SPSS 20.0 and AMOS 21.0 to analyze the data and verify the theoretical model.

This study found that perceived organizational exploitation exerts a destructive impact on frontline hotel employees’ service performance. Trust in the organization is a full mediator of the link connecting perceived organizational exploitation to service performance. Furthermore, traditionality weakens perceived organizational exploitation’s impact on trust in the organization and subsequent service performance.

The authors’ findings remind hotels to cease exploiting their employees to avoid compromising service performance. Hotels should also endeavor to instill trust among employees toward the hotel and allocate more attention to employees with lower levels of traditionality.

First, to the best of the authors’ knowledge, this study is among the first to explore the impact of perceived organizational exploitation on frontline hotel employees’ service performance. Second, this study reveals a novel mechanism underlying the connection between perceived organizational exploitation and service performance. Finally, this study identifies frontline hotel employees’ traditionality as a vital moderator that mitigates the negative relationships among perceived organizational exploitation, trust in the organization and service performance.

This study aimed to investigate the impact of benevolent leadership on proactive customer service performance by creating a moderated mediation model. The model focuses on the role of harmonious passion as a mediator in the relationship between benevolent leadership and proactive customer service performance as well as the moderating influence of proactive personality on this mediation.

The model was tested using data from 339 immediate supervisor-subordinate pairs in eight five-star hotels in Egypt. Frontline service employees and their immediate supervisors completed separate questionnaires, and the responses were matched using identification numbers.

The results indicate that harmonious passion fully mediates the positive relationship between benevolent leadership and proactive customer service performance. Additionally, proactive personality was found to moderate the mediated relationship between benevolent leadership and proactive customer service performance through harmonious passion, such that the mediation was stronger for employees with higher proactive personalities.

By testing the moderated mediation model, this study contributes to our theoretical understanding of the motivational mechanism through which benevolent leadership influences proactive customer service performance.

This research offers initial evidence of the mediating role of harmonious passion in the positive relationship between benevolent leadership and proactive customer service performance. The moderated mediation model extends existing findings by incorporating proactive personality as a significant moderator in explaining the impact of benevolent leadership on proactive customer service performance.

The purpose of this research is to investigate how the negative effect of litigation risk on firm performance could be controlled through the channel of voluntary disclosure and under the condition of institutional ownership.

To get the objectives, the study analyzed an unbalanced panel of 918 non-financial listed Chinese firms from 2010 to 18. To capture any expected unobserved heteroscedasticity and autocorrelation in the unbalanced sample, the authors have applied fixed effect regression with robust standard errors clustered at the firms' levels as suggested by Newey and West (1987).

The research provides that the good disclosure practices and presence of institutional ownership in corporations raise the trust of the investors by making the corporate operation clear in the eyes of the stakeholders. This increases the corporate credibility and as consequence corporations are protected against litigation risk. Thus, in the light of the information asymmetry and signaling theories, voluntary disclosure practices, and financial institutions' ownership, bridges the information gap and transmit a positive signal in the market regarding the better financial performance of the corporations.

These findings are helpful for the corporate managers for effective strategic decisions, regulatory authorities for policy formulation, and individual investors for developing a diversified investment portfolio.

By applying the mediation and moderation effects, the research enhances the understanding of the underlying causes of the association between a firm's litigation risk and its performance. The current research contributes to the literature, that agency issues which create litigation risk could be settled internally with voluntary disclosure practices and externally with institutional ownership.

In this essay, a new NDAGM(1,N,α) power model is recommended to resolve the hassle of the distinction between old and new information, and the complicated nonlinear traits between sequences in real behavior systems.

Firstly, the correlation aspect sequence is screened via a grey integrated correlation degree, and the damped cumulative generating operator and power index are introduced to define the new model. Then the non-structural parameters are optimized through the genetic algorithm. Finally, the pattern is utilized for the prediction of China’s natural gas consumption, and in contrast with other models.

By altering the unknown parameters of the model, theoretical deduction has been carried out on the newly constructed model. It has been discovered that the new model can be interchanged with the traditional grey model, indicating that the model proposed in this article possesses strong compatibility. In the case study, the NDAGM(1,N,α) power model demonstrates superior integrated performance compared to the benchmark models, which indirectly reflects the model’s heightened sensitivity to disparities between new and old information, as well as its ability to handle complex linear issues.

This paper provides a scientifically valid forecast model for predicting natural gas consumption. The forecast results can offer a theoretical foundation for the formulation of national strategies and related policies regarding natural gas import and export.

The primary contribution of this article is the proposition of a grey multivariate prediction model, which accommodates both new and historical information and is applicable to complex nonlinear scenarios. In addition, the predictive performance of the model has been enhanced by employing a genetic algorithm to search for the optimal power exponent.

The advent of online live streaming platforms (OLSPs) and online health communities (OHCs) has expedited the integration of traditional medical services with Internet new media technology. Since the practice of physicians conducting live streaming is a relatively new phenomenon, the potential cross-platform effects of such physicians’ live streaming have not received adequate attention.

This study collected data from 616 physicians specializing in cardiology, obstetrics and gynecology and neurology between April and November 2022 on Live.Baidu.com and WeDoctor.com. It constructed a panel data set comprising a total of 4,928 observations over an 8-month period and validated the model using empirical analysis with the fixed-effects method.

We find evidence of cross-platform influence in online healthcare. Physicians’ live streaming behavior (whether live or not and the heat of their streams) on OLSPs positively impacts both their consultation and reputation on OHCs. Additionally, physicians’ ability positively moderates the relationships between live streaming heat and their performance (in terms of consultation volume and reputation) on OHCs. However, ability does not moderate the relationship between physicians’ live streaming status (live or not) and their performance (in terms of consultation and reputation) on OHCs. Furthermore, the attractive appearance of the physicians also significantly moderates the impact in a positive way.

This is one of the pioneering studies on physicians’ live streaming. The study offers vital guidance for physicians and patients utilizing dual platforms and holds significant reference value for platform operators (such as OLSPs and OHCs) aiming to optimize platform operations and for the government in policy formulation and industry regulation.

Drawing on appraisal theory of emotion, this study aims to establish and test a moderated mediation model underlying the process of exploitative leadership by investigating the mediating role of job anxiety and the moderating role of psychological entitlement.

We collected two-wave questionnaire data from 355 supervisors with matched responses from 1,065 subordinates in Hubei province of China. Hierarchical multiple regression and PROCESS macro were applied to test our hypotheses.

The results indicated that supervisor perceived overqualification prompted supervisor job anxiety, which then led to raised exploitative leadership. Additionally, we found that supervisor psychological entitlement intensified the direct effect of supervisor perceived overqualification on supervisor job anxiety as well as the indirect effect of supervisor perceived overqualification on exploitative leadership through supervisor job anxiety.

Although researchers have documented a growing number of consequences of exploitative leadership, less focus has been placed on its antecedents. The study extends our understanding of why, how and when supervisors engage in exploitative behaviors.