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One of the most important challenges confronting enterprise managers is that of controlling employees' social cyberloafing. The use of enterprise social media entails opportunities for cyberloafing. However, previous research on how enterprise social media use affects cyberloafing is rather limited. Using the job demands-resources (JD-R) model, this paper proposes a research model to investigate the relationship between enterprise social media usage and employees' social cyberloafing behavior.

Structural equation modeling was performed to test the research model and hypotheses. Surveys were conducted in an online platform in China, generating 510 employees' data for analysis.

First, both public social media and private social media used for work-related and social-related purposes have a positive effect on employees' job engagement. Further, job engagement has a negative effect on employees' social cyberloafing. Second, the use of public social media for work-related and social-related purposes has no effect on employees' emotional exhaustion. However, work-related private social media usage has a negative effect on employees' emotional exhaustion, and social-related private social media usage has a positive effect on employees' emotional exhaustion. Further, employees' emotional exhaustion has a positive effect on employees' social cyberloafing. Third, there are significant differences in the effects of enterprise social media on employees' social cyberloafing between male and female employees.

First, this paper contributes to the social cyberloafing literature by establishing a relationship between enterprise social media usage and social cyberloafing in relation to the dual influence mechanism. Second, it contributes to the JD-R model by clarifying how the use of enterprise social media with different motivations affects social cyberloafing through a mediation mechanism, namely, an enabling mechanism and a burden mechanism. Third, this paper also contributes to the social cyberloafing literature by revealing the boundary condition, namely gender, between enterprise social media use and employees' social cyberloafing.

The combination of mobile devices and innovative tools offers new possibilities for the development of a community of practice for design makers. Mobile learning has become an essential method that design makers should adopt. The main content of this study is to explore the characteristics of learning behaviors and learning needs of creative design makers' group in forming a community of practice in the era of mobile learning.

This study conducted questionnaire research on the potentially associated or directly associated population of design makers. The process of the study also combined observational and interview studies to compensate for the lack of questionnaire research.

Based on the support of mobile learning technology, design makers share and co-create to achieve individual development and evolution of learning organizations, and produce creative value. Design-maker communities of practice form common communities in the framework of informal organizations to support continuous individual learning. Convergent interests or concerns in making things, real-world contexts based on makerspaces and hands-on practice based on real projects are the basis for forming design-maker communities of practice. A variety of open-source hardware, software and platforms that can support mobile learning are important for the development of design-maker communities of practice. The design-maker community of practice needs group factors, activity development, physical and technical resources, spatial support and institutional norms to enhance learning behaviors and satisfy learning needs.

The discovery and construction of these associated factors can help creative design practitioners form a lasting and virtuous organizational development. This study facilitates the formation of a social network for learning and knowledge sharing among design-maker communities of practice. It enhances the innovation ability and enthusiasm of design makers according to the population characteristics and learning needs of design makers. This study also facilitates the generation of a positive adaptive maker culture and maker spirit within design maker organizations.

This study aims to investigate the role of aluminium (Al) in marine environment and the corrosion mechanism of galvalume coatings by conducting accelerated experiments and data analysis.

Samples were subjected to accelerated corrosion for 136 days via salt spray tests to simulate the natural conditions of marine environment and consequently accelerate the experiments. Subsequently, the samples were examined using various test methods, such as EDS, scanning electron microscopy (SEM), X-ray diffraction (XRD) and electrochemical impedance spectroscopy (EIS), and the obtained data were analysed.

Galvalume coatings comprised interdigitated zinc (Zn)-rich and dendritic Al-rich phases. Corrosion was observed to begin with a Zn-rich phase. The primary components of the corrosion product film were Al₂O₃ and Zn₅(OH)₈Cl₂·H₂O. It was confirmed that the role of Al was to form a dense protective film, thereby successfully blocking the entry of corrosive media and protecting the iron substrate.

This study provides a clearer understanding of the corrosion mechanism and kinetics of galvalume coatings in a simulated marine environment. In addition, the role of Al, which is rarely mentioned in the literature, was investigated.

This study aims to understand workplace conflict outcomes (WCO) literature and identify the research gaps by mapping its knowledge base and theoretical evolution.

This study combines bibliometric and qualitative analysis and encompasses 1,043 Scopus-indexed documents published between 1972 and 2022. The bibliometric analysis used VOSviewer, Excel and Tableau software for descriptive statistics, citation and co-citation analyses of publication patterns, authors, documents and journals. The qualitative analysis critiqued main theoretical perspectives and topical interests.

This study revealed a significant increase in literature after 2000, with authors representing 70 societies, primarily the USA, China, Australia, Canada and the Netherlands. Influential authors and their canonical articles were identified, including Jehn, De Dreu, Spector, Amason and Pelled. Highly cited articles focused on task, relationship, role and process conflict. Four main theoretical schools were categorized: conflict type paradigm, individual differences, conflict cooccurrence and conflict dynamics. Influential journals spanned psychology, management, negotiation and decision-making and business and marketing fields, including JAP, AMJ, ASQ, JM, JOB, AMR, IJCMA and OS.

This study provides implications for future bibliometric analyses, theoretical and empirical studies, practitioners and society based on its quantitative and qualitative findings.

To the best of the authors’ knowledge, this study represents the first bibliometric review of WCO literature, serving as a baseline for tracking the field’s evolution and theoretical advancements.

An efficient e-waste management system is developed, aided by deep learning techniques. Here, a smart bin system using Internet of things (IoT) sensors is generated. The sensors detect the level of waste in the dustbin. The data collected by the IoT sensor is stored in the blockchain. Here, an adaptive deep Markov random field (ADMRF) method is implemented to determine the weight of the wastes. The performance of the ADMRF is boosted by optimizing its parameters with the help of the improved corona virus herd immunity optimization algorithm (ICVHIOA). Here, the main objective of the developed ADMRF-based waste weight prediction is to minimize the root mean square error (RMSE) and mean absolute error (MAE) rate at the time of testing. If the weight of the bins is more than 80%, then an alert message will be sent to the waste collector directly. Optimal route selection is carried out using the developed ICVHIOA for efficient collection of wastes from the smart bin. Here, the main objectives of the optimal route selection are to reduce the distance and time to minimize the operational cost and the environmental impacts. The collected waste is then considered for recycling. The performance of the implemented IoT and blockchain-based smart dustbin is evaluated by comparing it with other existing smart dustbins for e-waste management.

The developed e-waste management system is used to collect the waste and to avoid certain diseases caused by the dumped waste. Disposal and recycling of the e-waste is necessary to decrease pollution and to manufacture new products from the waste.

The RMSE of the implemented framework was 33.65% better than convolutional neural network (CNN), 27.12% increased than recurrent neural network (RNN), 22.27% advanced than Resnet and 9.99% superior to long short-term memory (LSTM).

The proposed E-waste management system has given an enhanced performance rate in weight prediction and also in optimal route selection when compared with other conventional methods.

The purpose of this study is to examine how the interplay of stressor (e.g. fear of missing out, FoMO) and strains (e.g. perceived social overload, communication overload, information overload and system feature overload) in social networking sites (SNS) use can contribute to users’ SNS fatigue from a configurational view.

Data were collected among 363 SNS users in China via an online survey, and fuzzy-set qualitative comparative analysis (fsQCA) was applied in this study to scrutinize the different combinations of FoMO and overload that contribute to the same outcome of SNS fatigue.

Six combinations of casual conditions were identified to underlie SNS fatigue. The results showed that FoMO, perceived information overload and system feature overload are the core conditions that contribute to SNS fatigue when combined with other types of overloads.

The current work supplements the research findings on SNS fatigue by identifying the configurations contributing to SNS fatigue from the joint effects of stressor (FoMO) and strain (perceived social overload, communication overload, information overload and system feature overload) and by providing explanations for SNS fatigue from the configurational perspective.

This paper aims to use an ionic liquid (IL, [HMIM]PF₆) to improve the lubrication performance of liquid metal (LM) as a lithium grease additive and to expand the application range of LM.

In this paper, the different mass ratios of [HMIM]PF₆/LM mixtures were added into the lithium grease on a four-ball tribo-meter to investigate the effects of its tribological behavior. Scanning electron mircoscope/energy dispersive spectroscopy and X-ray photoelectron spectroscopy were used to reveal the anti-wear and friction-reducing mechanism of the additives.

When the load was used at 461 N, the average coefficient of friction (ACOF) and average wear scar diameter (AWSD) of steel ball Lubricated with grease with an optimal ratio of 2:3 ([HMIM]PF₆/LM) were reduced by 32.8% and 30.5%, respectively. Friction and wear mechanisms are ascribed to friction-induced additive components that can simultaneously form a composite lubrication film consisting of FePO₄, FeF₃, Ga₂O₃, In₂O₃ and SnO₂.

Compared with the pure lithium-based grease, when [HMIM]PF₆/LM was added with an optimal ratio of 2:3, the ACOF and AWSD were reduced by 12.4% from 0.097 to 0.085 and 23.8% from 552.117 µm to 420.590 µm under 392 N, respectively. When at 461 N, the ACOF and AWSD of steel ball were reduced by 32.8% from 0.122 to 0.082 and 30.5% from 715.714 µm to 497.472 µm, respectively. It was shown that the simultaneous addition of LM and [HMIM]PF₆ can form a composite lubrication film consisting of FePO₄, FeF₃, Ga₂O₃, In₂O₃ and SnO₂.

In this paper, [HMIM]P F₆ is added with LM simultaneously to improve the lubrication properties of lithium grease, and expand the application scope of LM.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2024-0017/

The purpose of this study is to explore a new assembly process planning and execution mode to realize rapid response, reduce the labor intensity of assembly workers and improve the assembly efficiency and quality.

Based on the related concepts of digital twin, this paper studies the product assembly planning in digital space, the process execution in physical space and the interaction between digital space and physical space. The assembly process planning is simulated and verified in the digital space to generate three-dimensional visual assembly process specification documents, the implementation of the assembly process specification documents in the physical space is monitored and feed back to revise the assembly process and improve the assembly quality.

Digital twin technology enhances the quality and efficiency of assembly process planning and execution system.

It provides a new perspective for assembly process planning and execution, the architecture, connections and data acquisition approaches of the digital twin-driven framework are proposed in this paper, which is of important theoretical values. What is more, a smart assembly workbench is developed, the specific image classification algorithms are presented in detail too, which is of some industrial application values.

The purpose of this study is to analyse the magnetic field effect on Fe₃O₄/H₂O Ferrofluid flowing in a sudden expansion tube, which has specific behaviour in terms of rheology, with convex dimple fins. Because the investigation of flow separation is a prominent application in performance, the effect of magnetic field and convex dimple on the thermo-hydraulic performance of sudden expansion tube are examined, in detail.

During the solution of the boundary conditions of the sudden expansion tube, finite volume method was used. Analyses have been conducted considering the single-phase solution, steady-state, incompressible fluid and no-slip condition of the wall under forced convection conditions. In the analyses, it has been assumed that the flow was developing thermally and has been fully developed hydrodynamically.

The present study focuses on exploring the influence of the magnetic field, nanofluid concentration and convex dimple fins on the thermo-hydraulic performance of sudden expansion tube. The results indicate that the strength of the magnetic field, nanofluid concentration and convex dimple fins have a positive effect on the convective heat transfer in the system.

The authors conducted numerical studies, determining through a literature search that no one had yet investigated enhancing heat transfer on a sudden expansion tube using combinations of magnetic fields, nanofluids and convex dimple fins. The results of the numerical analyses provide valuable information about the improvement of heat transfer and system performance in electronic device cooling and heat exchangers.

The paper focuses on the issue of manual rebar-binding tasks in the construction industry, which are marked by high labor intensity, high costs and inefficient operations. The rebar-binding robots that are currently available are not fully mature. Most of them can only bind one or two nodes in one position, which leads to significant time wastage in movement. Based on a new type of rebar-binding robot, this paper aims to propose a new movement and binding control that reduces manpower and enhances efficiency.

The robot is combined with photoelectric sensors, travel switches and other sensors. It is supposed to move accurately and run in a limited area on the rebar mesh through logical judgment, speed control and position control. Machine vision is used by the robot to locate the rebar nodes and then adjusts the binding-gun position to ensure that multiple rebar nodes are bound sequentially.

By moving on the rebar mesh with accuracy, the robot meets the positioning accuracy requirements of the binding module, with experimental testing accuracy within 5 mm. Furthermore, its ability to bind four rebar nodes in one place results in a high efficiency and a binding effect that meets building standards.

The innovative design of the robot can adapt itself to the rebar mesh, move accurately to the target position and bind four nodes at that position, which reduces the number of movements on the mesh. Repetitive and heavy rebar-binding tasks can be efficiently completed by the robot, which saves human resources, reduces worker labor intensity and reduces construction overhead. It provides a more feasible and practical solution for using robots to bind rebar nodes.