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1 – 10 of 87Zhihong Tan, Ling Yuan, Junli Wang and Qunchao Wan
This study aims to investigate the negative interpersonal antecedents, emotional mediators and boundary conditions of knowledge sabotage behavior.
Abstract
Purpose
This study aims to investigate the negative interpersonal antecedents, emotional mediators and boundary conditions of knowledge sabotage behavior.
Design/methodology/approach
The authors collected data from 275 Chinese employees using convenience sampling and snowball sampling across three stages. Subsequently, the authors used both hierarchical regression and bootstrap methods to test the proposed hypotheses.
Findings
The results confirmed that workplace ostracism has positive effects on employee knowledge sabotage behavior both directly and via employee anger. In addition, the authors found that employee bottom-line mentality (BLM) moderates not only the direct effect of workplace ostracism on employee anger but also the indirect effect of employee anger in this context. Employee conscientiousness moderates only the direct effect of workplace ostracism on employee anger and does not moderate the indirect effect.
Originality/value
To the best of the authors’ knowledge, this study not only explores the influence of workplace ostracism on employee knowledge sabotage behavior for the first time but also elucidates the underlying emotional mechanisms (anger) and boundary conditions (employee BLM and conscientiousness) by which workplace ostracism influences employee knowledge sabotage behavior, thus deepening the understanding of how knowledge sabotage emerges in organizations.
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Aamir Suhail, Inam Ul Haq, Muhammad Umer Azeem and Eran Vigoda-Gadot
This study investigates how compulsory citizenship behaviors (CCB) affect employees’ energy and motivation to engage in other voluntary behaviors, such as service-oriented…
Abstract
Purpose
This study investigates how compulsory citizenship behaviors (CCB) affect employees’ energy and motivation to engage in other voluntary behaviors, such as service-oriented citizenship behavior and creativity. Specifically, we explore how employees’ perceptions of job overload mediate this relationship, based on their generational differences.
Design/methodology/approach
This study employed a time-lagged survey design to collect data from 265 frontline employees and their supervisors in Pakistani-based organizations. The data was collected in three rounds, with a three-week gap between each round.
Findings
The findings suggest that role overload, resulting from compulsory citizenship pressure, undermines millennial employees' service-oriented organizational citizenship behavior (OCB) and creativity. However, these negative effects are less salient among non-millennials.
Practical implications
The findings of this study provide valuable insights for managers, emphasizing the importance of exercising caution when imposing excessive citizenship pressures on employees against their will. In addition, organizations and human resource (HR) managers should consider devising policies for formal recognition of voluntary behaviors that contribute to organizational effectiveness.
Originality/value
This study contributes to existing CCB research by unraveling the previously unexplored mediating role of role overload and the contingency role of generational difference in explaining how and when coerced citizenship demands hinder employees’ propensity to engage in service-oriented OCB and creativity.
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Zhaozhao Tang, Wenyan Wu, Po Yang, Jingting Luo, Chen Fu, Jing-Cheng Han, Yang Zhou, Linlin Wang, Yingju Wu and Yuefei Huang
Surface acoustic wave (SAW) sensors have attracted great attention worldwide for a variety of applications in measuring physical, chemical and biological parameters. However…
Abstract
Purpose
Surface acoustic wave (SAW) sensors have attracted great attention worldwide for a variety of applications in measuring physical, chemical and biological parameters. However, stability has been one of the key issues which have limited their effective commercial applications. To fully understand this challenge of operation stability, this paper aims to systematically review mechanisms, stability issues and future challenges of SAW sensors for various applications.
Design/methodology/approach
This review paper starts with different types of SAWs, advantages and disadvantages of different types of SAW sensors and then the stability issues of SAW sensors. Subsequently, recent efforts made by researchers for improving working stability of SAW sensors are reviewed. Finally, it discusses the existing challenges and future prospects of SAW sensors in the rapidly growing Internet of Things-enabled application market.
Findings
A large number of scientific articles related to SAW technologies were found, and a number of opportunities for future researchers were identified. Over the past 20 years, SAW-related research has gained a growing interest of researchers. SAW sensors have attracted more and more researchers worldwide over the years, but the research topics of SAW sensor stability only own an extremely poor percentage in the total researc topics of SAWs or SAW sensors.
Originality/value
Although SAW sensors have been attracting researchers worldwide for decades, researchers mainly focused on the new materials and design strategies for SAW sensors to achieve good sensitivity and selectivity, and little work can be found on the stability issues of SAW sensors, which are so important for SAW sensor industries and one of the key factors to be mature products. Therefore, this paper systematically reviewed the SAW sensors from their fundamental mechanisms to stability issues and indicated their future challenges for various applications.
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Weiyi Cong, Shoujian Zhang, Huakang Liang and Qingting Xiang
Job stressors have a considerable influence on workplace safety behaviors. However, the findings from previous studies regarding the effect of different types of job stressors…
Abstract
Purpose
Job stressors have a considerable influence on workplace safety behaviors. However, the findings from previous studies regarding the effect of different types of job stressors have been contradictory. This is attributable to, among other factors, the effectiveness of job stressors varying with occupations and contexts. This study examines the effects of challenge and hindrance stressors on construction workers' informal safety communication at different levels of coworker relationships.
Design/methodology/approach
A three-dimensional framework of informal safety communication is adopted, including self-needed, citizenship and participatory safety communication. Stepwise regression analysis is then performed using questionnaire survey data collected from 293 construction workers in the Chinese construction industry.
Findings
The results demonstrate that both challenge and hindrance stressors are negatively associated with self-needed and citizenship safety communication, whereas their relationships with participatory safety communication are not significant. Meanwhile, the mitigation effects of the coworker relationship (represented by trustworthiness and accessibility) on the above negative impacts vary with the communication forms. Higher trustworthiness and accessibility enable workers faced with challenge stressors to actively manage these challenges and engage in self-needed safety communication. Similarly, trustworthiness promotes workers' involvement in self-needed and citizenship safety communication in the face of hindrance stressors, but accessibility is only effective in facilitating self-needed safety communication.
Originality/value
By introducing the job demands-resources theory and distinguishing informal safety communication into three categories, this study explains the negative effects of challenge and hindrance job stressors in complex and variable construction contexts and provides additional clues to the current inconsistent findings regarding this framework. The diverse roles of challenge and hindrance job stressors also present strong evidence for the need to differentiate between the types of informal safe communication.
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Miguel Calvo and Marta Beltrán
This paper aims to propose a new method to derive custom dynamic cyber risk metrics based on the well-known Goal, Question, Metric (GQM) approach. A framework that complements it…
Abstract
Purpose
This paper aims to propose a new method to derive custom dynamic cyber risk metrics based on the well-known Goal, Question, Metric (GQM) approach. A framework that complements it and makes it much easier to use has been proposed too. Both, the method and the framework, have been validated within two challenging application domains: continuous risk assessment within a smart farm and risk-based adaptive security to reconfigure a Web application firewall.
Design/methodology/approach
The authors have identified a problem and provided motivation. They have developed their theory and engineered a new method and a framework to complement it. They have demonstrated the proposed method and framework work, validating them in two real use cases.
Findings
The GQM method, often applied within the software quality field, is a good basis for proposing a method to define new tailored cyber risk metrics that meet the requirements of current application domains. A comprehensive framework that formalises possible goals and questions translated to potential measurements can greatly facilitate the use of this method.
Originality/value
The proposed method enables the application of the GQM approach to cyber risk measurement. The proposed framework allows new cyber risk metrics to be inferred by choosing between suggested goals and questions and measuring the relevant elements of probability and impact. The authors’ approach demonstrates to be generic and flexible enough to allow very different organisations with heterogeneous requirements to derive tailored metrics useful for their particular risk management processes.
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Hassam Waheed, Peter J.R. Macaulay, Hamdan Amer Ali Al-Jaifi, Kelly-Ann Allen and Long She
In response to growing concerns over the negative consequences of Internet addiction on adolescents’ mental health, coupled with conflicting results in this literature stream…
Abstract
Purpose
In response to growing concerns over the negative consequences of Internet addiction on adolescents’ mental health, coupled with conflicting results in this literature stream, this meta-analysis sought to (1) examine the association between Internet addiction and depressive symptoms in adolescents, (2) examine the moderating role of Internet freedom across countries, and (3) examine the mediating role of excessive daytime sleepiness.
Design/methodology/approach
In total, 52 studies were analyzed using robust variance estimation and meta-analytic structural equation modeling.
Findings
There was a significant and moderate association between Internet addiction and depressive symptoms. Furthermore, Internet freedom did not explain heterogeneity in this literature stream before and after controlling for study quality and the percentage of female participants. In support of the displacement hypothesis, this study found that Internet addiction contributes to depressive symptoms through excessive daytime sleepiness (proportion mediated = 17.48%). As the evidence suggests, excessive daytime sleepiness displaces a host of activities beneficial for maintaining mental health. The results were subjected to a battery of robustness checks and the conclusions remain unchanged.
Practical implications
The results underscore the negative consequences of Internet addiction in adolescents. Addressing this issue would involve interventions that promote sleep hygiene and greater offline engagement with peers to alleviate depressive symptoms.
Originality/value
This study utilizes robust meta-analytic techniques to provide the most comprehensive examination of the association between Internet addiction and depressive symptoms in adolescents. The implications intersect with the shared interests of social scientists, health practitioners, and policy makers.
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Ahmad Honarjoo and Ehsan Darvishan
This study aims to obtain methods to identify and find the place of damage, which is one of the topics that has always been discussed in structural engineering. The cost of…
Abstract
Purpose
This study aims to obtain methods to identify and find the place of damage, which is one of the topics that has always been discussed in structural engineering. The cost of repairing and rehabilitating massive bridges and buildings is very high, highlighting the need to monitor the structures continuously. One way to track the structure's health is to check the cracks in the concrete. Meanwhile, the current methods of concrete crack detection have complex and heavy calculations.
Design/methodology/approach
This paper presents a new lightweight architecture based on deep learning for crack classification in concrete structures. The proposed architecture was identified and classified in less time and with higher accuracy than other traditional and valid architectures in crack detection. This paper used a standard dataset to detect two-class and multi-class cracks.
Findings
Results show that two images were recognized with 99.53% accuracy based on the proposed method, and multi-class images were classified with 91% accuracy. The low execution time of the proposed architecture compared to other valid architectures in deep learning on the same hardware platform. The use of Adam's optimizer in this research had better performance than other optimizers.
Originality/value
This paper presents a framework based on a lightweight convolutional neural network for nondestructive monitoring of structural health to optimize the calculation costs and reduce execution time in processing.
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Lei Gan, Anbin Wang, Zheng Zhong and Hao Wu
Data-driven models are increasingly being used to predict the fatigue life of many engineering components exposed to multiaxial loading. However, owing to their high data…
Abstract
Purpose
Data-driven models are increasingly being used to predict the fatigue life of many engineering components exposed to multiaxial loading. However, owing to their high data requirements, they are cost-prohibitive and underperforming for application scenarios with limited data. Therefore, it is essential to develop an advanced model with good applicability to small-sample problems for multiaxial fatigue life assessment.
Design/methodology/approach
Drawing inspiration from the modeling strategy of empirical multiaxial fatigue models, a modular neural network-based model is proposed with assembly of three sub-networks in series: the first two sub-networks undergo pretraining using uniaxial fatigue data and are then connected to a third sub-network trained on a few multiaxial fatigue data. Moreover, general material properties and necessary loading parameters are used as inputs in place of explicit damage parameters, ensuring the universality of the proposed model.
Findings
Based on extensive experimental evaluations, it is demonstrated that the proposed model outperforms empirical models and conventional data-driven models in terms of prediction accuracy and data demand. It also holds good transferability across various multiaxial loading cases.
Originality/value
The proposed model explores a new avenue to incorporate uniaxial fatigue data into the data-driven modeling of multiaxial fatigue life, which can reduce the data requirement under the promise of maintaining good prediction accuracy.
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Gang Wang, Mian Wang, ZiHan Wang, GuangTao Xu, MingHao Zhao and Lingxiao Li
The purpose of this paper is to assess the hydrogen embrittlement sensitivity of carbon gradient heterostructure materials and to verify the reliability of the scratch method.
Abstract
Purpose
The purpose of this paper is to assess the hydrogen embrittlement sensitivity of carbon gradient heterostructure materials and to verify the reliability of the scratch method.
Design/methodology/approach
The surface-modified layer of 18CrNiMo7-6 alloy steel was delaminated to study its hydrogen embrittlement characteristics via hydrogen permeation, electrochemical hydrogen charging and scratch experiments.
Findings
The results showed that the diffusion coefficients of hydrogen in the surface and matrix layers are 3.28 × 10−7 and 16.67 × 10−7 cm2/s, respectively. The diffusible-hydrogen concentration of the material increases with increasing hydrogen-charging current density. For a given hydrogen-charging current density, the diffusible-hydrogen concentration gradually decreases with increasing depth in the surface-modified layer. Fracture toughness decreases with increasing diffusible-hydrogen concentration, so the susceptibility to hydrogen embrittlement decreases with increasing depth in the surface-modified layer.
Originality/value
The reliability of the scratch method in evaluating the fracture toughness of the surface-modified layer material is verified. An empirical formula is given for fracture toughness as a function of diffused-hydrogen concentration.
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Yun Liu, Xingyuan Wang and Heyu Qin
This paper aims to explore the matching effect of hospitality brand image (cool vs non-cool) and service agents (Artificial intelligence [AI] vs human staff) on brand attitude…
Abstract
Purpose
This paper aims to explore the matching effect of hospitality brand image (cool vs non-cool) and service agents (Artificial intelligence [AI] vs human staff) on brand attitude, with a focus on assessing the role of feeling right as a mediator and service failure as a moderator.
Design/methodology/approach
This paper tested the hypotheses through three experiments and a Supplementary Material experiment, which collectively involved 835 participants.
Findings
The results indicated that the adoption of AI by cool brands can foster the right feeling and enhance consumers’ positive brand attitudes. In contrast, employing human staff did not lead to improved brand attitudes toward non-cool brands. Furthermore, the study found that service failure moderated the matching effect between service agents and cool brand images on brand attitude. The matching effect was observed under successful service conditions, but it disappeared when service failure occurred.
Practical implications
The findings offer practical guidance for hospitality companies in choosing service agents based on brand image. Cool brands can swiftly transition to AI, reinforcing their modern, cutting-edge image. Traditional brands may delay AI adoption or integrate it strategically with human staff.
Originality/value
To the best of the authors’ knowledge, this paper represents one of the first studies to address the issue of selecting the optimal service agent based on hospitality brand image. More importantly, it introduces the concept of a cool hospitality brand image as a boundary condition in the framework of AI research, providing novel insights into consumers’ ambivalent responses to AI observed in previous studies.
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