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The purpose of this study is to solve the Reynolds equation for finite journal bearings by using the physics-informed neural networks (PINNs) method. As a meshless method, it is unnecessary to use big data to train the neural networks, but to satisfy the Reynolds equation and the corresponding boundary conditions by using the known physics information.

Here, the boundary conditions are enforced through the loss function firstly, i.e. the soft constrain method. After this, an equation was constructed to build a surrogate model for satisfying the corresponding boundary conditions naturally, i.e. the hard constrain method.

For the soft one, in brief, the pressure results agree well with existing results, apart from the ones on the boundaries. While for the hard one, it can be noted that the discrepancies on the boundaries are reduced significantly.

The PINNs method is used to solve the Reynolds equation for finite journal bearings, and the error values on the boundaries for the results of the soft constrain method are improved by using the hard constrain method. Therefore, the hard constraint maybe also a good option when the pressure results on the boundaries are emphasized.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2023-0045/

In the post-pandemic era urban ecosystem planning has become critically important. Given the emphasis on relevant issues concerning the complex interactions between human civilizations and natural systems within urban environments in the new normal, this article aims to enrich the field of knowledge management developing a cross-cultural analysis for clarifying the role of knowledge in planning and urban ecosystems.

This paper is conceptual in nature. Based on a theoretical foundation built by a critical literature review and data from the China Statistical Yearbook and China’s National Bureau of Statistics, this paper introduces some emerging real-impact topics regarding the connections between humanistic knowledge and urban planning. A comparative analysis between the capital city of Chang’an in the Tang dynasty of China and the capital city of Athens in Ancient Greek was used for explaining the influence of knowledge on successful urban planning.

The understanding the role of cross-cultural differences in knowledge management and practices for urban ecosystems offer the opportunities for rethinking consolidated approach to the interaction among social, economic, and environmental dimensions in urban settings.

This paper implies a new inter-disciplinary research field of great interest for the real impact KM community by illuminating how knowledge management is central in urban planning and across cultures.

With the rapid development of railway-intelligent video technology, scene understanding is becoming more and more important. Semantic segmentation is a major part of scene understanding. There is an urgent need for an algorithm with high accuracy and real-time to meet the current railway requirements for railway identification. In response to this demand, this paper aims to explore a variety of models, accurately locate and segment important railway signs based on the improved SegNeXt algorithm, supplement the railway safety protection system and improve the intelligent level of railway safety protection.

This paper studies the performance of existing models on RailSem19 and explores the defects of each model through performance so as to further explore an algorithm model dedicated to railway semantic segmentation. In this paper, the authors explore the optimal solution of SegNeXt model for railway scenes and achieve the purpose of this paper by improving the encoder and decoder structure.

This paper proposes an improved SegNeXt algorithm: first, it explores the performance of various models on railways, studies the problems of semantic segmentation on railways and then analyzes the specific problems. On the basis of retaining the original excellent MSCAN encoder of SegNeXt, multiscale information fusion is used to further extract detailed features such as multihead attention and mask, solving the problem of inaccurate segmentation of current objects by the original SegNeXt algorithm. The improved algorithm is of great significance for the segmentation and recognition of railway signs.

The model constructed in this paper has advantages in the feature segmentation of distant small objects, but it still has the problem of segmentation fracture for the railway, which is not completely segmented. In addition, in the throat area, due to the complexity of the railway, the segmentation results are not accurate.

The identification and segmentation of railway signs based on the improved SegNeXt algorithm in this paper is of great significance for the understanding of existing railway scenes, which can greatly improve the classification and recognition ability of railway small object features and can greatly improve the degree of railway security.

This article introduces an enhanced version of the SegNeXt algorithm, which aims to improve the accuracy of semantic segmentation on railways. The study begins by investigating the performance of different models in railway scenarios and identifying the challenges associated with semantic segmentation on this particular domain. To address these challenges, the proposed approach builds upon the strong foundation of the original SegNeXt algorithm, leveraging techniques such as multi-scale information fusion, multi-head attention, and masking to extract finer details and enhance feature representation. By doing so, the improved algorithm effectively resolves the issue of inaccurate object segmentation encountered in the original SegNeXt algorithm. This advancement holds significant importance for the accurate recognition and segmentation of railway signage.

This study aims to investigate whether gender diversity in audit committees affects the purchase of nonaudit services in China. Results from family and nonfamily firms are compared and the critical mass participation of females are further examined.

The sample comprises 1,834 Chinese listed companies from 2012 to 2021, among which 910 are family firms. The Heckman (1979) two-stage model is used to mitigate the potential endogeneity issue in the selection of gender diversity. Propensity score matching is also used to further alleviate the endogeneity problem in relation to family firms.

Results show a significant and negative correlation between the gender diversity in audit committees and nonaudit service fees. This association is more apparent in nonfamily than in family firms. Findings are consistent and robust to endogeneity tests and sensitivity analyses. The analysis of critical mass and symbolic participation shows that three female directors can more significantly restrain nonaudit fees than one to two females on the board.

This study contributes to literature on resource dependence theory, which posits that audit committees help enterprises establish contact with auditors, improve the company legitimacy, assist in communication and provide relevant expertise. This study also relates to agency theory, which holds that differences in the severity of types I and II agency problems between family and nonfamily firms lead to differences in auditor selection and related costs.

Extending from previous research on the relation between the gender diversity in audit committees and nonaudit fees, the present study delves into this connection within the context of China, an emerging economy. As a result, this investigation offers novel insights and expands upon current knowledge. In addition, the correlation between the gender diversity of audit committees and nonaudit fees is explored for family and nonfamily firms.

This study aims to explore the relationship between folk religious place-making and the development of urban public spaces and summarize its influence on community network construction and daily behavior to discover the authentic practices and role of folk faith culture in social space.

Taking Macau's Shi Gandang Temple and its belief culture as an example, on-site research, historical evidence and interviews were used to elaborate and analyze the processes of place-making, social functions, management mechanisms and folk culture to establish a new perception of folk religious place-making in contemporary urban spaces.

The article argues that the culture of folk beliefs profoundly influences urban spaces and the social management system of Macau and has a positive significance in building the local community and geopolitical relations. In addition, it suggests that the participation of folk religious places in local practices is important as key nodes and emotional hubs of local networks, reconciling conflicts between communities of different backgrounds and driving urban spaces toward diversity while forming a positive interaction and friendly cooperation between regional development and self-contained management mechanisms, governance models and cultural orientations.

This study takes an architectural and anthropological perspective of the impact of faith on urban spaces and local governance, using the Shi Gandang Temple in Macau as an example, to complement related studies.

As a smart service, location-based advertising (LBA) integrates advanced technologies to deliver personalized messages based on a user’s real-time geographic location and needs. However, research has shown that privacy concerns threaten the diffusion of LBA. This research investigates how privacy-related factors (i.e. LBA type, privacy self-efficacy (PSE) and consumer generation) impact consumers’ value-in-use and their intention to use LBA.

This study developed and examined an LBA value-in-use framework that integrates the role of LBA type, consumers’ PSE and consumer generation into the technology acceptance model (TAM). Data were collected through two experiments in the field with a total of 374 consumers. The proposed relationships were tested using PROCESS modeling.

The results reveal that pull (vs push) LBA causes higher value-in-use in terms of perceived usefulness and perceived ease of use, leading to greater usage intention. Further, the differences in the mediated relationship between pull- and push-LBA are larger among consumers of low PSE (vs high PSE) and Generation Z (vs other generations). The findings suggest that the consumer value-in-use brought about by LBA diminishes when using push-LBA for low PSE and Generation Z consumers.

This research is the first to integrate the privacy-related interactions of LBA type and consumer characteristics into TAM to develop a TAM-based LBA value-in-use framework. This study contributes to the literature on service value-in-use, smart services and LBA by clarifying the boundary conditions that determine the effectiveness of LBA in enhancing consumers’ value-in-use.

This paper aims to examine the relationship between environmental, social and governance (ESG) performance and systemic risk sensitivity of Chinese listed companies. From the consumer loyalty and investor structure perspectives, the relationship between ESG performance and systemic risk sensitivity is analyzed.

Since Morgan Stanley Capital International (MSCI) ESG officially began to analyze and track China A-shares from 2018, 275 listed companies in the SynTao Green ESG testing list for 2015–2021 are selected as the initial model. To measure the systematic risk sensitivity, this study uses the beta coefficient, from capital asset pricing model (CPAM), employing statistics and data (STATA) software.

The study reveals that high ESG rating companies have high corresponding consumer loyalty and healthy trading structure of institutional investors, thereby the systemic risk sensitivity is lower. This paper reveals that companies with high ESG rating are significantly less sensitive to systemic risk than those with low ESG rating. At the same time, ESG has a weaker impact on the systemic risk of high-cap companies than low-cap companies.

The study helps the companies understand the influence of market value on the relationship between ESG performance and systemic risk sensitivity. Moreover, this paper explains explicitly why ESG performance insulates a firm’s stock from market downturns with the lens of consumer loyalty theory and investor structure theory.

The paper provides new insights on the company’s ESG performance that significantly affects the company’s systemic risk sensitivity.

This study aims to assess financial development and debt status impact on energy efficiency in Nigeria as a developing economy.

This study combined the autoregressive distributed lag (ARDL), fully modified ordinary least squares and canonical cointegration regression analytical methods to estimate the parameters for energy efficiency policy recommendations. Secondary data between 1990 and 2020 were used for the analysis.

The result confirms the long-run nexus between energy efficiency, financial development and total debt stock. Furthermore, the ARDL estimates for this study’s key variables show that financial development promotes energy efficiency in the short run but hinders long-run energy efficiency. Total debt stock limits energy efficiency in Nigeria in short- and long-run periods.

The limitation of this study is that the scope is limited to Nigeria as a developing economy. The need to support energy efficiency projects is a global call requiring cross-country analysis. Despite this study’s focus on Nigeria, it provides useful insights that can guide energy efficiency policy through the financial sector and debt management.

The financial sector must ensure the availability of long-term credit facilities to clean energy investors. The government must maintain a sustainable debt profile to pave the way for capital expenditure on clean energy projects that promote energy efficiency.

The environmental consequences of energy intensity are being felt globally, with the developing countries most vulnerable. The cheapest way to curb these consequences is to promote energy efficiency to reduce the disastrous effect. Driving energy efficiency requires investment in energy-efficient technology but the challenge for developing economies, i.e. Nigeria’s funding, remains challenging amid a blotted debt profile. This becomes crucial to investigate how financial sector development and debt management can accelerate energy-efficient investments in Nigeria.

Naming practices reflect culture, language and identity considerations. This study aims to explore Chinese American naming choices, revealing nuanced and complex linguistic, cultural and pragmatic considerations for teachers of literacy.

The authors interviewed Chinese parents who are now living with their school-aged children in the USA on the naming choices of their students. By using content analysis, this study found patterns and themes from the interview data.

The findings of this study suggest Chinese parents named their US school-aged children by taking into consideration of both Mandarin and English linguistic features, traditional and pop culture and the transnational identity of their children.

The findings of this study can help teachers and teacher educators better understand the naming traditions of Chinese American families and connect these traditions to literacy instruction in the classroom. This study proposes practical suggestions suitable for both monolingual and multilingual students to explore all children’s names and help build inclusive, culturally sustaining classrooms.

Online labour markets (OLMs) have recently become a widespread phenomenon of digital work. While the implications of OLMs on worker well-being are hotly debated, little empirical research examines the impact of such work on individuals. The highly competitive and fast-paced nature of OLMs compels workers to multitask and to perform intense technology-enabled work, which can potentially enhance technostress. This paper examines the antecedents and well-being consequences of technostress arising from work in OLMs.

The authors draw from person–environment fit theory and job characteristics theory and test a research model of the antecedents and consequences of worker technostress in OLMs. Data were gathered from 366 workers in a popular OLM through a large-scale online survey. Structural equation modelling was used to evaluate the research model.

The findings extend existing research by validating the relationships between specific OLM characteristics and strain. Contrary to previous literature, the results indicate a link between technology complexity and work overload in OLMs. Furthermore, in OLMs, feedback is positively associated with work overload and job insecurity, while strain directly influences workers' negative affective well-being and discontinuous intention.

This study contributes to technostress literature by developing and testing a research model relevant to a new form of work conducted through OLMs. The authors expand the current research on technostress by integrating job characteristics as new antecedents to technostress and demonstrating its impact on different types of subjective well-being and discontinuous intention. In addition, while examining the impact of technostressors on outcomes, the authors consider their impact at the individual level (disaggregated approach) to capture the subtlety involved in understanding technostressors' unique relationships with outcomes.