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The purpose of this paper is to propose the pressure fluctuation to further evaluate and predict the dynamic and static characteristics of the aerostatic slider and improve the calculation accuracy of the aerostatic slider.

First-order velocity slip is introduced into the traditional gas-film fluid equation, and the numerical analysis method is used to solve the static performance of the aerostatic slider. The finite element analysis method is used to solve its dynamic characteristics.

It can be concluded from the simulation and experimental results that the model considering the velocity slip in the gas film flow is more accurate. The errors between the modal detection results and the vibration detection results (0.8%–5.8%) under speed slip are smaller than the traditional cases (23.7%–210%), which also verifies the correctness of the above conclusions.

In this paper, the method of simulation and experiment is used to prove that the first-order velocity slip model is more suitable to predict the dynamic response of the aerostatic slider than the condition without slip.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2020-0059/

This paper aims to examine the housing market responses to two outbreaks of respiratory diseases in Hong Kong during the Information Era – the 2003 SARS and COVID-19 outbreaks.

The authors first investigate the aggregate housing price changes during SARS and COVID-19. Next, the authors conduct a battery of univariate analyses pertaining to the relationship between district-level housing price movements and geographic and demographic patterns during the pandemic periods. Finally, to shed light on the housing price dynamics at the micro level, the authors conduct an estate-level analysis with the data of 234 residential estates from 2003 to 2020, focusing on the impacts of SARS and COVID-19 on the idiosyncratic volatility of residential estates.

Overall, SARS and COVID-19 outbreaks are negatively associated with housing prices. However, unlike SARS, the impact of COVID-19 on housing prices was moderate and transient. The geographic imbalances of the epidemic-induced underperformance are observed at the district and estate levels. Finally, the estate-level analysis presented in this paper indicates that the average idiosyncratic volatility of residential estates is 1.5% higher during the SARS period but 3.7% lower during the COVID-19 period. Lower volatility during COVID-19 is likely explained by household learning from the SARS period.

Regulators and investors could resort to efficient information disclosure to attenuate idiosyncratic volatility's adverse impact on housing market returns.

To the best of the authors’ knowledge, the authors are among the first to examine housing market responses to the 2003 SARS and COVID-19 outbreaks using the Hong Kong housing market as a laboratory.

This study investigated the effect of adding a customer's name onto a standard product on the customer's product attitude from the perspective of the name-letter effect and psychological ownership theory.

A 2 × 2 experiment was conducted to test the name effect in customization services. The main effects, mediation effects and moderation effects were analyzed using SPSS 22.0 and PROCESS 2.16.3.

Adding customers' personal names onto a standard product positively affected their attitude toward the product, and these effects were mediated by psychological ownership. Furthermore, customers' responses were moderated by self-threat, whereby threatening customers' self-concept enhanced their attitude toward the product that had their name on it.

This study found a positive name effect that is applicable to customization services. It also identified mediating and moderating mechanisms underlying this effect. Therefore this study extends previous studies on customization services that have solely focusing on complex product personalization by focusing on a service that requires less effort and a more basic customization service. This study also extends previous findings about name-letter effects by focusing on the associations between an individual and an object that are induced by shared name letters and by studying how directly adding a personal name onto an object can influence these associations.

This paper aims at the problem of surrounding rock excavation damage zone of tunneling in the rich water region, this paper aims to propose a new seepage-stress-damage coupling model and studied the numerical algorithm. This reflects the characteristics of rock damage evolution, accompanied by plastic flow deformation and multi-field interaction.

First of all, rock elastoplastic damage constitutive model based on the Drucker–Prager criterion is established, the fully implicit return mapping algorithm is adopted to realize the numerical solution. Second, based on the relation between damage variation and permeability coefficient, the rock stress-seepage-damage model and multi-field coupling solving iterative method are presented. Finally, using the C++ language compiled the corresponding programs and simulated tunnel engineering in the rich water region.

Results show that difference evolution-based back analysis inversed damage parameters well, at the same time the established coupling model and calculating program have more advantages than general conventional methods. Multiple field coupling effects should be more considered for the design of tunnel support.

The proposed method provides an effective numerical simulation method for the construction of the tunnel and other geotechnical engineering involved underground water problems.

An alliance portfolio can help latecomer firms to acquire the necessary knowledge and resources to catch up with market leaders. However, how latecomer firms construct an alliance portfolio in terms of the nature of windows of opportunity has not been fully analyzed. This paper aims to explore how latecomer firms can build appropriate coalitions according to the nature of the window of opportunity to achieve technological catch-up in different catch-up phases.

Based on a longitudinal case study from 1984 to 2018 of Sunny Group, now a leading manufacturer of integrated optical components and products, this paper explores the process of technological catch-up of latecomer firms building different types of alliance portfolio in different windows of opportunity.

This paper finds that there is a sequence when latecomers build an alliance portfolio in the process of catch-up. When the uncertainty of opportunity increases, the governance mechanism of the alliance portfolio will change from contractual to equity-based. Also, latecomer firms build market-dominated and technology-dominated alliance portfolios to overcome their market and technology disadvantages, respectively.

These conclusions not only enrich the theory of latecomer catch-up from the perspective of windows of opportunity but also expand research on alliance portfolio processes from a temporal perspective.

Recently, the concept of financial technology (FinTech) has attracted extensive attention from international organisations and regulators, in particular, how to achieve a “win–win” situation between financial institutions' FinTech innovation and effective regulation has become a hot topic. This study purposes to explore the evolutionary game relationship between FinTech innovation and regulation by constructing both static and dynamic earmarking game models.

A simulation experiment was conducted using primary data obtained from a commercial bank in China.

The results of the theoretical analysis of evolutionary game models were consistent with the corresponding simulation results, proving the validity of the proposed evolutionary game models. It was also found that the dynamic earmarking game model was more stable and effective than the static earmarking game model in promoting FinTech innovation and regulation. Furthermore, when the regulators utilised a dynamic earmarking mechanism, the evolutionary path of financial institutions and regulators' behaviour strategies took the shape of a spiral and eventually converged to a central point, indicating the existence of an evolutionary stable strategy and Nash equilibrium. Finally, because the behaviour strategies of financial institutions were mainly influenced by the regulators' policies, the regulators were inspired to adjust the corresponding regulation policies on FinTech innovation.

This study bridges the knowledge gap in the existing literature on financial innovation and regulation, in particular by establishing evolutionary game models from the perspective of financial earmarking policies. Also, the case study for simulation experiments can gain a more intuitive insight into FinTech innovation and financial earmarking policies.

Student approaches to studying were explored in business courses with samples in China, Kuwait and the USA. Information on approaches to studying is critical as delivery and content of educational practices are increasingly adapted to different world regions.

The Revised Approaches to Studying Inventory (RASI) was administered to address the extent to which students focused studying on deep learning of concepts, surface learning/memorization of material or strategic maximization of grades.

Results suggested (1) acceptable reliability for the RASI scales, (2) higher mean scores on deep, surface and strategic approaches for the Kuwait versus the China or USA samples, and (3) an interaction effect between country sample and strategic studying on the dependent variable of reported grade point average.

The research focuses on student initiative in the educational process. Also, comparative evidence from the Middle Eastern context is provided. This area has received relatively little attention in the literature.

This study aims to investigate whether and how artificial intelligence (AI) awareness affects work withdrawal.

This survey garners participation from a total of 305 hotel employees in China. The proposed hypotheses are examined using Hayes’s PROCESS macro.

The results indicate that AI awareness could positively affect work withdrawal. Negative work-related rumination and emotional exhaustion respectively mediate this relationship. Furthermore, negative work-related rumination and emotional exhaustion act as chain mediators between AI awareness and work withdrawal.

Given the growing adoption of AI technology in the hospitality industry, it is imperative that managers intensify their scrutiny of the psychological changes experienced by frontline service employees and allocate more resources to mitigating the impact of AI on their work withdrawal.

This study contributes to the burgeoning literature on AI by elucidating the chain mediating roles of negative work-related rumination and emotional exhaustion. It also makes a significant forward in examining mediating mechanisms, notably the chain-mediated mechanism, through which AI awareness impacts employee outcomes.

The defect detection problem of color-patterned fabric is still a huge challenge due to the lack of manual defect labeling samples. Recently, many fabric defect detection algorithms based on feature engineering and deep learning have been proposed, but these methods have overdetection or miss-detection problems because they cannot adapt to the complex patterns of color-patterned fabrics. The purpose of this paper is to propose a defect detection framework based on unsupervised adversarial learning for image reconstruction to solve the above problems.

The proposed framework consists of three parts: a generator, a discriminator and an image postprocessing module. The generator is able to extract the features of the image and then reconstruct the image. The discriminator can supervise the generator to repair defects in the samples to improve the quality of image reconstruction. The multidifference image postprocessing module is used to obtain the final detection results of color-patterned fabric defects.

The proposed framework is compared with state-of-the-art methods on the public dataset YDFID-1(Yarn-Dyed Fabric Image Dataset-version1). The proposed framework is also validated on several classes in the MvTec AD dataset. The experimental results of various patterns/classes on YDFID-1 and MvTecAD demonstrate the effectiveness and superiority of this method in fabric defect detection.

It provides an automatic defect detection solution that is convenient for engineering applications for the inspection process of the color-patterned fabric manufacturing industry. A public dataset is provided for academia.

In recent years, with the steady growth of China’s economy and world’s vacation market, and powered by the growing and significant large demands of Chinese overseas travel, an emergent trend of international development by major Chinese tourism groups has attracted notice by scholars and practitioners and this is obvious especially in the private sector. With this as the background, this paper aims to explore how China’s leading tourism companies expand their business internationally through a case study approach.