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This paper aims to provide strategies for individuals with limited work capacity (LWC) to build workplace friendships and foster inclusion, which can benefit their mental health.

The paper integrates key theories such as social exchange theory and the similarity-attraction paradigm to analyze the dynamics of relationships. Practical tips grounded in the existing literature are outlined.

Effective communication, building trust, showing mutual respect and discovering common interests can facilitate friendship development for employees with LWC. Supportive organizational policies and culture are also critical.

By building workplace bonds and inclusion, individuals with LWC may experience greater social support, more engagement and better mental well-being. This also helps to diminish stigma and marginalization.

This viewpoint provides practical guidance specifically designed for individuals with Limited Work Capacity (LWC) to overcome workplace obstacles and build social relationships. It addresses an existing gap in the interpersonal facets of disability inclusion.

Using the theoretical framework of social comparison theory (SCT), this study investigates the effects of employee envy on service sabotage behaviors in the hospitality industry. It further examines the complex dynamics of self-performance and job dissatisfaction in this context. Notably, this paper seeks to determine the potential moderating role of perceived employability in the interactions between service sabotage, employee envy, job dissatisfaction and self-performance.

Our research structure was divided into four distinct models. The findings of Model 1 highlight the significant impact of employee envy on service sabotage. The analysis in Model 2a shows that job dissatisfaction acts as a partial mediator in the employee envy and service sabotage linkage. On the other hand, Model 2b reveals self-performance as yet another partial mediator between envy-service sabotage relationships. In turn, Model 3 demonstrates that job dissatisfaction and self-performance play a serial mediation role in the envy-service sabotage relationship. In addition, our research shows that perceived employability effectively moderates the three proposed paths within these relationships.

Our research structure was divided into four distinct models. The findings of Model 1 highlight the significant impact of employee envy on service sabotage. The analysis in Model 2a shows that job dissatisfaction acts as a partial mediator in the employee envy and service sabotage linkage. On the other hand, Model 2b reveals self-performance as yet another partial mediator between envy-service sabotage relationships. In turn, Model 3 demonstrates that job dissatisfaction and self-performance play a serial mediation role in the envy-service sabotage relationship. In addition, our research shows that perceived employability effectively moderates the three proposed paths within these relationships.

Hotel managers must keep a close eye on their front-of-house staff to avoid any unintentional or direct interactions with customers. Equally important is the consistent and impartial treatment of all employees, which is an important consideration for managers to consider because it can help mitigate employee envy and job dissatisfaction.

This study seeks to enhance understanding of SCT by emphasizing perceived employability as a boundary influencing the relationships between these factors and desired outcomes in the hotel industry, such as job dissatisfaction, self-performance and service sabotage. This paper is an initial attempt to investigate the underlying mechanisms in the relationship between envy and service sabotage.

This study aims to explore the mechanism of abusive supervision differentiation on employee work-family conflict, and examine the chain mediating role of work-related rumination and organizational citizenship behavior/deviant workplace behavior, as well as the moderating role of work-family boundary segmentation preference.

The authors designed two studies: Study 1 was a scenario experiment with 120 Master of Business Administration students. To further explore this finding, the authors conducted a multiwave survey in Study 2 with 345 employees from various organizations.

The results of Study 1 showed that abusive supervision differentiation had a positive effect on work-related rumination, and work-related rumination mediated the relationship between differentiated abusive supervision and organizational citizenship behavior/deviant workplace behavior. The results of Study 2 not only confirmed the conclusions of Study 1 but also revealed that organizational citizenship behavior/deviant workplace behavior significantly affected work-family conflict. Abusive supervision differentiation had a positive effect on work-family conflict through work-related rumination and organizational citizenship behavior/deviant workplace behavior. In addition, work-family boundary segmentation preference negatively moderated the relationship between organizational citizenship behavior and work-family conflict.

First, to the best of the authors’ knowledge, this study is the first paper to test the spillover effect of abusive supervision differentiation on the family domain through a chain mediation model. It extends the research on abusive supervision differentiation from the work domain to the family domain. Second, previous research has highlighted role conflict or role insufficiency as significant factors contributing to work-family conflict. However, this study suggests that abusive supervision differentiation from workplace managers can also trigger work-family conflict, providing a new perspective in the study of precursors to work-family conflict.

The purpose of this study is to investigate the influence of green finance on human well-being in China in the context of urbanization and aging population. It aims to explore the contributions of green finance in such demographic scenarios.

This study innovates and optimizes the calculation of the carbon intensity of human well-being (CIWB) index and strengthens the integrity of the assessment model for green finance development. It uses the serial multiple mediator model and moderation effect analysis to address the impact of green finance on human well-being in China on the provincial level from 2009 to 2020.

Green finance has a significant, positive and direct impact on human well-being. Simultaneously, it influences human well-being indirectly through three transmission channels. Urbanization and an ageing population are significant individual mediators through which green finance contributes to human well-being improvement. Notably, these two mediators also work together to transfer the promotional impact of green finance to human well-being.

The government can perfect the regulations to strengthen the market ecosystem to accelerate the development of green finance. Reforms on the administrative division to expand the size of cities with the implementation of ageing friendly development strategy is also necessary. Attracting incoming foreign direct investment in sustainable projects and adjusting public projects and trade activities to fulfil the sustainable principles are also regarded as essential.

The findings challenge traditional views on the impact of aging populations, highlighting the beneficial role of green finance in improving well-being amidst demographic changes. This offers a new perspective on economic and environmental sustainability in aging societies.

A multi-dimensional well-being indicator, CIWB and the serial multiple mediator model are used and direct and indirect impacts of green finance on human well-being is exhibited. It offers novel insights on the transmission channels behind, identifies the mediating role of urbanization and ageing population and offers empirical evidences with strong academic and policy implications.

This study aims to investigate the affordances of service robots (SRs) in hotels and their effects on frontline employees (FLEs).

Purposive and referral samplings methods were used to conduct 28 semistructured interviews with hotel FLEs, and the transcribed manuscript was analyzed based on grounded theory.

The study identifies six dimensions of SR affordances: physical, sensory, task, safety, social and emotional affordances. The main effects of SR affordances on FLEs involve reducing work stress and mental fatigue and increasing positive emotions in the psychological aspects of FLEs. In terms of behavioral aspects, shifts in task priorities and enhancements in SR usage behaviors were observed. Accordingly, a mechanistic framework was revealed through which SR affordances influence FLEs via direct and indirect interactions between FLEs and SRs.

This paper expands robotics research from a supply-side perspective and is one of the few studies to investigate SR affordances in the field of hospitality research. Findings of this study provide practical guidelines for designing and implementing SRs to support hotel FLEs in their daily work.

本研究旨在调查酒店中服务机器人（SR）的可供性及其对一线员工（FLEs）的影响。

本研究采用目的性和推荐抽样方法, 对酒店一线员工进行了28次半结构化访谈, 并根据扎根理论对转录的手稿进行了分析。

本研究确定了服务机器人的六个可供性维度：物理、感官、任务、安全、社会和情感可供性。服务机器人可供性对一线员工的主要影响包括减少工作压力和心理疲劳, 以及在心理方面增加积极情绪。在行为方面, 观察到任务优先级的变化和服务机器人使用行为的增强。因此, 研究揭示了一种机制框架, 通过一线员工与服务机器人的直接和间接互动, 服务机器人可供性影响一线员工。

本文从供给侧视角扩展了机器人研究, 是少数几篇研究酒店业中服务机器人可供性的研究之一。本研究结果为设计和实施服务机器人以支持酒店一线员工的日常工作提供了实践指南。

This study explores the impact of ethical and authentic leadership on employees' workplace perceptions, focusing on organisational citizenship behaviour (OCB), trust in leader, commitment, employee voice and empowerment in independent hotels across two contrasting Global Leadership and Organizational Behaviour Effectiveness (GLOBE) clusters: Germanic and Middle-Eastern clusters. It examines how national culture influences these relationships in the hospitality industry.

Data were collected from 1,678 employees in independent hotels in the Germanic European cluster (Germany and the Netherlands) and the Middle-Eastern cluster (Qatar and Turkey) using selective and snowball sampling techniques. Hypotheses were tested using two-stage structural equation modelling.

Ethical leadership significantly affects employee voice in Germany and the Netherlands but not in Qatar and Turkey. Authentic leadership positively influences employee voice in Qatar, Turkey and Germany but does not significantly impact trust in leader in any of the four countries. The study underscores the role of cultural dimensions, particularly power distance, in shaping these relationships.

This research contributes to the literature by investigating the effects of ethical and authentic leadership on key organisational variables in culturally diverse contexts within the hospitality industry. The findings highlight the necessity of considering national culture in leadership practices and suggest practical implications for independent hotels to adapt their leadership approaches to enhance employee outcomes. Future research should explore cultural dimensions as moderators in organisational relationships.

With the development of intelligent technology, deep learning has made significant progress and has been widely used in various fields. Deep learning is data-driven, and its training process requires a large amount of data to improve model performance. However, labeled data is expensive and not readily available.

To address the above problem, researchers have integrated semi-supervised and deep learning, using a limited number of labeled data and many unlabeled data to train models. In this paper, Generative Adversarial Networks (GANs) are analyzed as an entry point. Firstly, we discuss the current research on GANs in image super-resolution applications, including supervised, unsupervised, and semi-supervised learning approaches. Secondly, based on semi-supervised learning, different optimization methods are introduced as an example of image classification. Eventually, experimental comparisons and analyses of existing semi-supervised optimization methods based on GANs will be performed.

Following the analysis of the selected studies, we summarize the problems that existed during the research process and propose future research directions.

This paper reviews and analyzes research on generative adversarial networks for image super-resolution and classification from various learning approaches. The comparative analysis of experimental results on current semi-supervised GAN optimizations is performed to provide a reference for further research.

This study aims to conduct a comprehensive review of scholarly literature on the educational impacts of the metaverse, systematically identifying emerging themes, challenges and implications for metaverse education.

The study uses systematic literature review techniques using the Scopus database to investigate empirical studies and systematic reviews specifically examining the convergence of the metaverse and education.

The study shows that the metaverse has a substantial influence on education, emphasising immersive learning, real social interactions and the transformation of traditional frameworks. This paper identifies nine themes, illuminating the growing relevance of metaverse tools in academic institutions, influencing learning methods, outcomes and positive student dispositions.

This study provides a foundation for further investigations into the metaverse’s potential to disseminate knowledge and enhance comprehension of metaverse technologies. It explores the metaverse’s potential in relation to progress, upcoming trends and cultural awareness while highlighting obstacles that must be addressed for effective metaverse teaching.

This research paper makes a substantial scholarly contribution by undertaking a systematic analysis of empirical studies and identifying emerging themes in the area of metaverse education. It offers substantial insights into the transformative potential of metaverse education and its implications for pedagogical and instructional approaches in the digitised era through the analysis of fundamental inquiries.

This article introduces SigBERT, a novel approach that fine-tunes bidirectional encoder representations from transformers (BERT) for the purpose of distinguishing between intact and impaired structures by analyzing vibration signals. Structural health monitoring (SHM) systems are crucial for identifying and locating damage in civil engineering structures. The proposed method aims to improve upon existing methods in terms of cost-effectiveness, accuracy and operational reliability.

SigBERT employs a fine-tuning process on the BERT model, leveraging its capabilities to effectively analyze time-series data from vibration signals to detect structural damage. This study compares SigBERT's performance with baseline models to demonstrate its superior accuracy and efficiency.

The experimental results, obtained through the Qatar University grandstand simulator, show that SigBERT outperforms existing models in terms of damage detection accuracy. The method is capable of handling environmental fluctuations and offers high reliability for non-destructive monitoring of structural health. The study mentions the quantifiable results of the study, such as achieving a 99% accuracy rate and an F-1 score of 0.99, to underline the effectiveness of the proposed model.

SigBERT presents a significant advancement in SHM by integrating deep learning with a robust transformer model. The method offers improved performance in both computational efficiency and diagnostic accuracy, making it suitable for real-world operational environments.

The study suggests that the high concentration of mining and metallurgical enterprises on the territory of the Russian Ural region determines the need to consider industrial waste, including nickel slag, as a possible raw material for the production of ceramic bricks. The article describes the properties of clays and nickel slag obtained at metallurgical enterprises in the Orenburg region and the features of their use as components in the composition of ceramic bricks.

To achieve this purpose, such tasks as determining the technological parameters of production, conducting the X-ray phase and microstructural analysis of the obtained samples were solved.

Compositions of ceramic mass using clay from the Khalilovsky deposit (Orenburg region) with the addition of nickel slag (20 and 40% by weight) have been developed, and their physical and mechanical properties (compressive strength, bending strength, water absorption and density) have been determined. With the help of modern research methods involving high-tech equipment, the microstructure is considered and the phase composition of the finished samples is determined. As a result of the conducted research, it was found that the composition of the selected clay and nickel slag in the obtained rational composition ensures the production of ceramic bricks of grades M175 and M200.

This is the first study on the use of nickel slag for the production of ceramic bricks. The results relate primarily to Russian feedstocks, but a methodology is presented that can be applied to other countries as well as to other silica-containing feedstocks.