Bei Ma, Rong Zhou and Xiaoliang Ma
Integrating balance theory and social identify theory, this paper proposes a multilevel model to explain how abusive supervision climate of team impacts the relationship among…
Abstract
Purpose
Integrating balance theory and social identify theory, this paper proposes a multilevel model to explain how abusive supervision climate of team impacts the relationship among team members as well as subordinates’ behavior towards their teammates, especially organizational citizenship behavior (OCB).
Design/methodology/approach
A survey was conducted to collect two-wave and multi-source data from 398 employees nested in 106 teams from Chinese high-technology companies. Hierarchical linear modeling was conducted to examine the theoretical model.
Findings
The results indicate that there is an inverted U-shape association between abusive supervision climate and subordinates’ OCB towards coworker; team member exchange (TMX) mediates their inverted U-shaped link. Furthermore, we confirm that coworker support plays a vitally moderating role upon the curvilinear link of abusive supervision climate (ASC)–TMX; specifically, when employees perceive low coworker support, negative relations between ASC and TMX will be stronger.
Originality/value
This study identifies team members’ advantageous and adverse relational response to shared threat of ASC and examines coworker support as a moderator of ASC, which provides valuable insights into when and why employees tend to cooperate with their teammates to jointly confront their leader’s abuse and highlights the importance of coworkers, thus enabling organizations to deeply understand the wider influences of ASC on interpersonal relationship between team members.
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Bin Zhou, Jin Ma, Hongyan Zhou, Xiaoliang Shi and Ahmed Mohamed Mahmoud Ibrahim
This paper aims to investigate the friction noise properties of M50 matrix curved microporous channel composites filled with solid lubricant Sn-Ag-Cu (MS).
Abstract
Purpose
This paper aims to investigate the friction noise properties of M50 matrix curved microporous channel composites filled with solid lubricant Sn-Ag-Cu (MS).
Design/methodology/approach
Pure M50 (MA) and MS are prepared by selective laser melting and vacuum-pressure infiltration technology. The tribological and friction noise properties of MA and MS are tested through dry sliding friction and then the influential mechanism of surface wear sate on friction noise is investigated by analyzing the variation law of noise signals and the worn surface characteristics of MS.
Findings
Experimental results show that the friction noise sound pressure level of MS is only 75.6 dB, and it mainly consists of low-frequency noise. The Sn-Ag-Cu improves the surface wear state, which reduces self-excited vibration of the interface caused by fluctuation of friction force, leading to the decrease of friction noise.
Originality/value
This investigation is meaningful to improve the tribological property and suppress the friction noise of M50 bearing steel.
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Hongru Ma, Xiaobin Deng, Xiaoliang Shi, Guanchen Lu, Hongyan Zhou, Yuan Chen and Zhenyu Yang
This paper aims to explore the damage mechanism of a lubricating film on the worn surface of solid self-lubricating composites under different loads.
Abstract
Purpose
This paper aims to explore the damage mechanism of a lubricating film on the worn surface of solid self-lubricating composites under different loads.
Design/methodology/approach
By comparing the actual stress with the strength, it is possible to determine the approximate wear state of the lubricating film. To prove the validity of the mathematical model that can predict the initiation of micro cracks or even the failure of the lubricating film, M50-5 Wt.% Ag self-lubricating composites (MA) was prepared. Tribological tests of the composites against Si3N4 ceramic balls were conducted at room temperature from 2 to 8 N. The electron probe microanalysis images of the lubricating film verify the wear state of the lubricating film.
Findings
The study found that the back edge of the contact area is the most vulnerable to destruction. The tensile stress and the equivalent shear stress have a positive correlation with load and friction coefficient. When the load is 4 N, an intact lubricating film covers the worn surface because the tensile stress and the equivalent shear stress are below the tensile strength and the shear strength, respectively; under other working conditions, the lubricating film is destroyed.
Originality/value
This paper has certain theoretical guidance for the study of tribological properties of solid self-lubricating composites. Moreover, this mathematical model is appropriate to be applied for the other composites.
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Jiayuan Yan, Xiaoliang Zhang and Yanming Wang
As a high-performance engineering plastic, polyimide (PI) is widely used in the aerospace, electronics and automotive industries. This paper aims to review the latest progress in…
Abstract
Purpose
As a high-performance engineering plastic, polyimide (PI) is widely used in the aerospace, electronics and automotive industries. This paper aims to review the latest progress in the tribological properties of PI-based composites, especially the effects of nanofiller selection, composite structure design and material modification on the tribological and mechanical properties of PI-matrix composites.
Design/methodology/approach
The preparation technology of PI and its composites is introduced and the effects of carbon nanotubes (CNTs), carbon fibers (CFs), graphene and its derivatives on the mechanical and tribological properties of PI-based composites are discussed. The effects of different nanofillers on tensile strength, tensile modulus, coefficient of friction and wear rate of PI-based composites are compared.
Findings
CNTs can serve as the strengthening and lubricating phase of PI, whereas CFs can significantly enhance the mechanical properties of the matrix. Two-dimensional graphene and its derivatives have a high modulus of elasticity and self-lubricating properties, making them ideal nanofillers to improve the lubrication performance of PI. In addition, copolymerization can improve the fracture toughness and impact resistance of PI, thereby enhancing its mechanical properties.
Originality/value
The mechanical and tribological properties of PI matrix composites vary depending on the nanofiller. Compared with nanofibers and nanoparticles, layered reinforcements can better improve the friction properties of PI composites. The synergistic effect of different composite fillers will become an important research system in the field of tribology in the future.
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Yuming Guan, Jingbo Mu, Hongwei Che, Xiaoliang Zhang and Zhixiao Zhang
The purpose of this study is to design carbon electrode materials for high performance electric double-layer capacitors (EDLCs) with pores that are large enough and have suitable…
Abstract
Purpose
The purpose of this study is to design carbon electrode materials for high performance electric double-layer capacitors (EDLCs) with pores that are large enough and have suitable pore size distribution for the electrolyte to access completely to improve EDLCs’ electrochemical performance.
Design/methodology/approach
This study develop an improved traditional KOH activation method, and a series of micro-meso hierarchical porous carbons have been successfully prepared from phenol formaldehyde resin by combining polyethylene glycol (PEG) and conventional KOH activation.
Findings
As evidenced by N2 adsorption/desorption tests, the obtained samples present Types IV and I-IV hybrid shape isotherms compared with KOH-activated resin (typical of Type I). The sample AC2-7-1, which the addition quantity of PEG is 25 per cent PF (weight ration) activated at 700? For 1 h is considered as the optimum preparation condition. It exhibits the highest specific capacitance value of 240 F/g in 30 wt% KOH aqueous electrolytes because of its higher specific surface area (2085 m2/g), greater pore volume (1.08 cm3/g) and the maximum mesoporosity (43 per cent). In addition, the capacity decay of this material is only 3.1 per cent after 1000 cycles.
Originality/value
The materials that are rich in micropores and mesopores show great potential in EDLC capacitors, particularly for applications where high power output and good high-frequency capacitive performances are required.
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Xiaohong Gao, Yizheng Wang, Tianlong Wang, Feibo Li, Yanming Wang and Xiaoliang Zhang
The anti-friction and anti-wear properties of WS2@GO composites on paraffin liquid were investigated with a four-ball tribometer.
Abstract
Purpose
The anti-friction and anti-wear properties of WS2@GO composites on paraffin liquid were investigated with a four-ball tribometer.
Design/methodology/approach
A series of graphene oxide (GO) nano hybrid composites decorated with tungsten disulfide (WS2) were prepared in-suit by hydrothermal strategy.
Findings
The results showed that compared to the virgin oil, friction coefficient and diameter of wear scare of lubricant oil containing W/G = 1:1 hybrid composite was reduced by 42.7% and 31.6%, respectively. At the microscopic, the excellent lubrication performance resulted from the tribo-chemical reaction on the sliding interface, which promotes the formation of tribo-film with a thickness of 8 nm. The carbonization compound, WO3 and Fe2O3 in the tribo-film results from the tribo-chemical reactions at the sliding interface, which can improve the stability and strength of tribo-film. Thereby the metal surface was further protected from friction and wear.
Originality/value
A series of WS2@GO composites were prepared in-suit by a hydrothermal strategy, and the tribo-film was analyzed by the transmission electron microscope and X-ray photoelectron spectrometer.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2024-0397
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Jianyao Jia, Shan Jiang, Liang Xiao and Fei Lu
The adoption of emerging information and communication technologies in construction project teams has engendered numerous virtual spaces, characterized by communication visibility…
Abstract
Purpose
The adoption of emerging information and communication technologies in construction project teams has engendered numerous virtual spaces, characterized by communication visibility and content persistence. As a result, the knowledge exchanged in these virtual spaces serves as a team’s digital resources. However, the extant literature mostly takes a process-based approach to examine the impact of knowledge sharing, thus failing to fully comprehend the process of converting digital resources into performance, resulting in a gap in the literature.
Design/methodology/approach
This study employs team resource-based theory to construct a theoretical model and develop hypotheses. Specifically, knowledge integration capability and team efficacy are hypothesized as two types of critical capabilities that mediate the links between knowledge sharing (quantity and quality) in virtual spaces and management performance. Data from 128 middle and senior construction project managers were collected to test the proposed theoretical model.
Findings
The results suggest that relationships between knowledge sharing (quantity and quality) and project management performance are both mediated by knowledge integration capability. Moreover, team efficacy could only partially translate knowledge sharing quantity into performance and couldn’t transform knowledge sharing quality into performance. Besides, knowledge integration is found to strengthen the link between knowledge sharing quantity and performance but weaken the relationship between knowledge sharing quality and performance.
Originality/value
This study explores how knowledge shared in virtual spaces could be leveraged for improving management performance in construction project teams. The findings in this study enhance the understanding of knowledge sharing in digital environments and afford important insights into transforming digital resources into performance within construction project teams.
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Jingjing Wang, Zhiqiang Li, Huanhuan Feng, Yuanjing Guo, Zhengbo Liang, Luyao Wang, Xing Wan and Yalin Wang
Recently, sharing economy is gradually accepted by people, and it has expanded from life to knowledge. It is important to encourage people to produce high quality content in…
Abstract
Recently, sharing economy is gradually accepted by people, and it has expanded from life to knowledge. It is important to encourage people to produce high quality content in knowledge sharing area, and knowledge payment is one of the most effective ways to achieve it. Therefore, the knowledge payment has been regarded as a huge business opportunity, and it is of great meaning to study the development trend and feasibility of knowledge payment. This chapter, through big data methods, analyzes the business model of Zhihu (a Chinese platform of knowledge sharing) after it introduced knowledge payment projects, such as Zhihu Live and Pay Consultation. According to data of Zhihu users’ Q&A, concerned fields and others, this chapter tries to outline its user profile to find out the target groups of different topics, the proper form of knowledge payment and the hot topics of Zhihu Live. Through the analysis of knowledge graph, this chapter finds that Zhihu Live is expected to be the mainstream knowledge payment form in the future, and the most potential topics are mainly focused on science, law, and business. Meanwhile, it establishes a pricing model for Zhihu Live, and provides suggestions for the development of knowledge payment.
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Xiaoliang Qian, Heqing Zhang, Cunxiang Yang, Yuanyuan Wu, Zhendong He, Qing-E Wu and Huanlong Zhang
This paper aims to improve the generalization capability of feature extraction scheme by introducing a micro-cracks detection method based on self-learning features. Micro-cracks…
Abstract
Purpose
This paper aims to improve the generalization capability of feature extraction scheme by introducing a micro-cracks detection method based on self-learning features. Micro-cracks detection of multicrystalline solar cell surface based on machine vision is fast, economical, intelligent and easier for on-line detection. However, the generalization capability of feature extraction scheme adopted by existed methods is limited, which has become an obstacle for further improving the detection accuracy.
Design/methodology/approach
A novel micro-cracks detection method based on self-learning features and low-rank matrix recovery is proposed in this paper. First, the input image is preprocessed to suppress the noises and remove the busbars and fingers. Second, a self-learning feature extraction scheme in which the feature extraction templates are changed along with the input image is introduced. Third, the low-rank matrix recovery is applied to the decomposition of self-learning feature matrix for obtaining the preliminary detection result. Fourth, the preliminary detection result is optimized by incorporating the superpixel segmentation. Finally, the optimized result is further fine-tuned by morphological postprocessing.
Findings
Comprehensive evaluations are implemented on a data set which includes 120 testing images and corresponding human-annotated ground truth. Specifically, subjective evaluations show that the shape of detected micro-cracks is similar to the ground truth, and objective evaluations demonstrate that the proposed method has a high detection accuracy.
Originality/value
First, a self-learning feature extraction method which has good generalization capability is proposed. Second, the low-rank matrix recovery is combined with superpixel segmentation for locating the defective regions.
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Xiaoliang Qian, Jing Li, Jianwei Zhang, Wenhao Zhang, Weichao Yue, Qing-E Wu, Huanlong Zhang, Yuanyuan Wu and Wei Wang
An effective machine vision-based method for micro-crack detection of solar cell can economically improve the qualified rate of solar cells. However, how to extract features which…
Abstract
Purpose
An effective machine vision-based method for micro-crack detection of solar cell can economically improve the qualified rate of solar cells. However, how to extract features which have strong generalization and data representation ability at the same time is still an open problem for machine vision-based methods.
Design/methodology/approach
A micro-crack detection method based on adaptive deep features and visual saliency is proposed in this paper. The proposed method can adaptively extract deep features from the input image without any supervised training. Furthermore, considering the fact that micro-cracks can obviously attract visual attention when people look at the solar cell’s surface, the visual saliency is also introduced for the micro-crack detection.
Findings
Comprehensive evaluations are implemented on two existing data sets, where subjective experimental results show that most of the micro-cracks can be detected, and the objective experimental results show that the method proposed in this study has better performance in detecting precision.
Originality/value
First, an adaptive deep features extraction scheme without any supervised training is proposed for micro-crack detection. Second, the visual saliency is introduced for micro-crack detection.