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1 – 10 of 12Yourong Yao, Zixuan Wang and Chun Kwok Lei
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Practical implications
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.
Social implications
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.
Originality/value
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.
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Xiaoyu Wang, Mengxi Chen, Zhiyan Wang, Chun Hung Roberts Law and Mu Zhang
This study aims to investigate the affordances of service robots (SRs) in hotels and their effects on frontline employees (FLEs).
Abstract
Purpose
This study aims to investigate the affordances of service robots (SRs) in hotels and their effects on frontline employees (FLEs).
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
研究目的
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。
研究方法
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。
研究发现
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。
研究创新
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。
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Alireza Nazarian, Ehsan Zaeri, Pantea Foroudi, Amirreza Afrouzi and Peter Atkinson
This study explores the impact of ethical and authentic leadership on employees' workplace perceptions, focusing on organisational citizenship behaviour (OCB), trust in leader…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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Yongqing Ma, Yifeng Zheng, Wenjie Zhang, Baoya Wei, Ziqiong Lin, Weiqiang Liu and Zhehan Li
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
Following the analysis of the selected studies, we summarize the problems that existed during the research process and propose future research directions.
Originality/value
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.
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Alisha Waquar, Sujood, Saima Kareem, Nusrat Yasmeen and Sarah Hussain
This study aims to conduct a comprehensive review of scholarly literature on the educational impacts of the metaverse, systematically identifying emerging themes, challenges and…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Originality/value
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.
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Ahmad Honarjoo, Ehsan Darvishan, Hassan Rezazadeh and Amir Homayoon Kosarieh
This article introduces SigBERT, a novel approach that fine-tunes bidirectional encoder representations from transformers (BERT) for the purpose of distinguishing between intact…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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Yongsheng Zhao, Jiaqing Luo, Ying Li, Caixia Zhang and Honglie Ma
The combination of improved PSO (IPSO) algorithm and artificial neural network (ANN) model for intelligent monitoring of the bearing performance of the hydrostatic turntable.
Abstract
Purpose
The combination of improved PSO (IPSO) algorithm and artificial neural network (ANN) model for intelligent monitoring of the bearing performance of the hydrostatic turntable.
Design/methodology/approach
This paper proposes an artificial neural network model based on IPSO algorithm for intelligent monitoring of hydrostatic turntables.
Findings
The theoretical model proposed in this paper improves the accuracy of the working performance of the static pressure turntable and provides a new direction for intelligent monitoring of the static pressure turntable. Therefore, the theoretical research in this paper is novel.
Originality/value
Theoretical novelties: an ANN model based on the IPSO algorithm is designed to monitor the load-bearing performance of a static pressure turntable intelligently; this study show that the convergence accuracy and convergence speed of the IPSO-NN model have been improved by 52.55% and 10%, respectively, compared to traditional training models; and the proposed model could be used to solve the multidimensional nonlinear problem in the intelligent monitoring of hydrostatic turntables.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0081/
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Wei Qian, Carol Tilt and Ping Zhu
This paper aims to examine the role of local/provincial government in influencing corporate social and environmental reporting (CSER) in China, and more specifically, how the…
Abstract
Purpose
This paper aims to examine the role of local/provincial government in influencing corporate social and environmental reporting (CSER) in China, and more specifically, how the underlying economic and political factors associated with local government have influenced the quality of CSER.
Design/methodology/approach
The authors used 234 environmentally sensitive companies listed on the Shanghai and Shenzhen Stock Exchanges during 2013 and 2015 as the research sample to test the relationship between CSER and local government’s political connection and economic prioritisation and the potential mediating effect of local economic prioritisation.
Findings
The analysis provides evidence that local/provincial government’s political geographical connectedness with the central government has directly and positively influenced the level of CSER, while local prioritisation of economic development has a direct but negative effect on CSER in China. In addition, local/provincial prioritisation of economic development has mediated the relationship between local–central political geographical connectedness and CSER.
Practical implications
While local/provincial governments are heavily influenced by the coercive pressure from the central government, they also act in their own political and economic interests in overseeing CSER at the local level. This study raises the question about the effectiveness of the top-down approach to improving CSER in China and suggests that the central government may need to focus more on coordinating and harmonising different local/provincial governments’ interests to enable achieving a common sustainability goal.
Originality/value
The authors provide evidence revealing how the economic and political contexts of local government have played a significant role in shaping CSER in China. More specifically, this paper addresses a gap in the literature by highlighting the importance of local government oversight power for CSER development and how such oversight is determined by local prioritisation of economic development and political geographical connectedness of local and central governments.
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Jing Chen and Hongli Chen
The purpose of this research is to provide insights into the daily search strategies of users, which can inform the enhancement of search experiences across multiple applications…
Abstract
Purpose
The purpose of this research is to provide insights into the daily search strategies of users, which can inform the enhancement of search experiences across multiple applications. By understanding how users navigate and interact with different apps during their search processes, the study seeks to contribute to the design of more intuitive and user-friendly app systems.
Design/methodology/approach
This study employs a mixed-methods approach to analyze users' daily search strategies in a natural cross-app interactive environment. Data collection was conducted using the Critical Incident Technique and the Micro-Moment Time Line, involving 204 participants to capture their real-time search experiences. Open coding techniques were utilized to categorize sequential search tactics, while the PrefixSpan algorithm was applied to identify patterns in frequently applied search strategies.
Findings
The study findings unveil a comprehensive framework that includes a variety of intra-app search tactics and inter-app switching tactics. Five predominant search strategies were identified: Iterative querying, Selective results adoption, Share-related, Recommended browsing, and Organizational results strategies. These strategies reflect the nuanced ways in which users engage with apps to fulfill their information needs.
Originality/value
This research represents a pioneering effort in systematically identifying and categorizing daily search strategies within a natural cross-app interaction context. It offers original contributions to the field by combining intra-app and inter-app tactics, providing a holistic view of user behavior. The implications of these findings are significant for app developers and designers, as they can leverage this knowledge to improve app functionality and user manuals, ultimately enhancing the overall search experience for users.
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Rama Krishna Shinagam, Deepak Raj Kumar Vengalasetti and Tarun Maruvada
This study aims to identify the location of cracks in composite plates using a normalized mode shape curve algorithm. Crack in any structure is a destructive occurrence. Detecting…
Abstract
Purpose
This study aims to identify the location of cracks in composite plates using a normalized mode shape curve algorithm. Crack in any structure is a destructive occurrence. Detecting these cracks early is pivotal for ensuring safety and preventing potential accidents. To prevent failure of structures, it is crucial to detect these cracks effectively and take the necessary precautions. Hence, crack detection and localization techniques are used to avoid sudden failures of structures while in operation.
Design/methodology/approach
An experimental modal analysis is conducted on composite plates with and without cracks to determine the natural frequencies and mode shapes. For this purpose, an impact hammer, uniaxial accelerometer and four-channel vibration analyzer are used to find the natural frequencies and mode shapes. Numerical modal analysis is performed on no crack and cracked composite plates using ANSYS software, and these are validated by the experimental modal analysis results. The normalized mode shapes algorithm is trained using test data of the first three natural frequencies collected from numerical modal analysis on different cracked composite plates for localization of crack.
Findings
The natural frequencies derived from both experimental modal analysis and numerical modal analysis exhibit a variance of 9.6%. The estimation of the crack location is achieved with exceptional precision by intersecting the first three normalized mode shapes. The first three normalized mode shape curve intersections provide a solid indication of the crack’s location. As the difference in error between the actual and estimated crack locations is only 0.9%.
Originality/value
This study introduces the first application of experimental modal analysis in conjunction with the normalized mode shape curve algorithm for localizing cracks in composite plates. The normalization process of mode shapes, derived from experimental modal analysis, forms a fundamental component of the mode shape curve algorithm specifically designed for crack localization. Combining experimental modal analysis with a specific algorithm of normalizing mode shapes is used to identify and locate cracks within these composite plates.
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