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This study aims to investigate the surface modification on 20CrMnTi gear steel individually treated by diamond-like carbon films and nitride coatings.

For this purpose, the mechanical properties of a-C:H, ta-C and AlCrSiN coatings are characterized by nano-indentation and scratch tests. The friction and wear behaviors of these three coatings are evaluated by ball-on-disc tribological experiments under dry contact conditions.

The results show that the a-C:H coating has the highest coating-substrate adhesion strength (495 mN) and the smoothest surface (Ra is about 0.045 µm) compared with the other two coatings. The AlCrSiN coating shows the highest mean coefficient of friction (COF), whereas the ta-C coating exhibits the lowest one (steady at about 0.16). The carbon-based coatings possess excellent self-lubricating properties compared with nitride ceramic ones, which effectively reduce the COF by about 64%. The major failure mode of carbon-based coatings in dry contact is slight abrasive wear. The damage of AlCrSiN coating is mainly adhesive wear and abrasive wear.

It is suggested that the carbon-based film can effectively improve the friction-reducing and wear resistance performance of the gear steel surface, which has a promising application prospect in the mechanical transmission field.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0129/

When establishing a mathematical model to simulate solid mechanics, considering realistic geometries, special tools are needed to translate measured data, possibly with noise, into idealized geometrical entities. As an engineering application, wheel-rail contact interactions are fundamental in the dynamic modeling of railway vehicles. Many approaches used to solve the contact problem require a continuous parametric description of the geometries involved. However, measured wheel and rail profiles are often available as sets of discrete points. A reconstruction method is needed to transform discrete data into a continuous geometry.

The authors present an approximation method based on optimization to solve the problem of fitting a set of points with an arc spline. It consists of an initial guess based on a curvature function estimated from the data, followed by a least-squares optimization to improve the approximation. The authors also present a segmentation scheme that allows the method to increment the number of segments of the spline, trying to keep it at a minimal value, to satisfy a given error tolerance.

The paper provides a better understanding of arc splines and how they can be deformed. Examples with parametric curves and slightly noisy data from realistic wheel and rail profiles show that the approach is successful.

The developed methods have theoretical value. Furthermore, they have practical value since the approximation approach is better suited to deal with the reconstruction of wheel/rail profiles than interpolation, which most methods use to some degree.

The aim of this paper is to present a comprehensive analysis of risk management in East Asia from 1998 to 2021 by using bibliometric methods and tools to explore research trends, hotspots, and directions for future research.

The data source for this paper is the Web of Science Core Collection, and 7,154 publications and related information have been derived. We use recognized bibliometric indicators to evaluate publications and visually analyze them through scientific mapping tools (VOS Viewer and CiteSpace).

The analysis results show that China is the most productive and influential country/region. East Asia countries have strong cooperation with each other and also have cooperation with other countries. The study shows that risk management has been involved in various fields such as credit, supply chain, health emergency and disaster especially in the background of COVID-19. We also found that machine learning, especially deep learning, has been playing an increasingly important role in risk management due to its excellent performance.

This paper focuses on studying risk management in East Asia, exploring its publication's fundamental information, citation and cooperation networks, hotspots, and research trends. It provides some reference value for scholars who are interested or further research in this field.

This study investigates the direct influence of ambidextrous leadership on employees’ innovation behaviour, the mediating role of innovative self-efficacy and harmonious work passion, and the moderating role of Zhong-Yong thinking.

The authors conducted a series of questionnaire surveys to collect data in three time periods and from multiple sources; 332 supervisor–subordinate matched samples were obtained. The hypothesised relationships were tested using structural equation modelling and ProClin.

Ambidextrous leadership is positively associated with employees’ innovation behaviour, while innovative self-efficacy and harmonious work passion play mediating roles. The analysis further confirms that innovative self-efficacy and harmonious work passion play a chained double-mediating role between ambidextrous leadership and employees’ innovation behaviour, while Zhong-Yong thinking plays moderating roles between ambidextrous leadership and innovative self-efficacy and between ambidextrous leadership and harmonious work passion.

This study demonstrates the influence of ambidextrous leadership on employees’ innovation behaviour, specifically the role of ambidextrous leadership, and extends the relationship’s theoretical foundation. It is also expected to provide inspiration and serve as a reference for local Chinese management.

This study aims to integrate conservation of resources theory discus the antecedents and consequences of cyberloafing as well as the boundary effect between cyberloafing and mental health.

The authors collected 431 valid questionnaires in four months. Each questionnaire was divided into two parts that had to be distributed. The interval between the first distribution and the second distribution was 15 days.

The research study revealed that employees’ Zhong-Yong thinking and cyberloafing promote mental health, and cyberloafing has a mediating effect. Mindfulness weakens the positive impact of cyberloafing on mental health.

The research study’s results break the stereotype that cyberloafing is not good for organizations. When managers allow employees to engage in cyberloafing at work, this is conducive to employees’ mental health, which can ensure the company’s sustainable development.

This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with similar oil reservoirs. The ultimate objective is to optimize oil extraction from this field by leveraging intelligent technology. Incorporating intelligent technology in oil fields can significantly simplify operations, especially in challenging-to-access areas and increase oil production, thereby generating higher income and profits for the field owner.

This study evaluates the level of maturity of present oil field technologies from the perspective of an intelligent oil field by using criteria for measuring the readiness of technologies. A questionnaire was designed and distributed to 18 competent oil industry professionals. Using weighted criteria, a mean estimate of oil field technical maturity was derived from the responses of respondents. Researchers evaluated the level of technological readiness for Brunei, Kuwait and Saudi Arabia’s oil fields using scientific studies.

None of the respondents believe that the intelligent oil field in Iran is highly developed and has a TRL 9 readiness level. The bulk of experts believed that intelligent technologies in the Iran oil industry have only reached TRL 2 and 1, or are merely in the transfer phase of fundamental and applied research. Clearly, Brunei, Kuwait and Saudi Arabia have the most developed oil fields in the world. In Iran, academics and executive and contracting firms in the field of intelligent oil fields are working to intelligently develop young oil fields.

This study explores the level of maturity of intelligent technology in one of Iran’s oil fields. It compares it to the level of maturity of intelligent technology in several other intelligent oil fields throughout the globe. Increasing intelligent oil fields TRL enables better reservoir management and causes more profit and oil recovery.

This study aims to model tourist activities in a network and explore the properties of the network. Such network enables the author to explain and quantify how tourist activities are connected in determining tourist consumption as well as the organization of destination supply.

The author developed a network formation mechanism to create edges between nodes based on the joint probability of a pair of activities undertaken by tourists at a destination. By adjusting network sparsity, the author created an ensemble of four topologically similar networks for empirical testing. The author used tourist activity data of Hong Kong inbound tourists to test the network model.

The author found a robust hub–periphery topological structure of the tourist activity network. In addition, the network is featured by high clustering, short diameter and positive correlations between four node centralities, namely, degree, closeness, betweenness and eigenvector centralities. The author also generated the k-cores of the networks to further unravel the structure of hub nodes. The author found that the k-cores are dominated by tourist activities related to shopping or sightseeing, suggesting the high complementarity of these activities.

This study provides a different lens through which tourist consumption can be understood from a macroscopic angle by examining network topology and from a microscopic angle by examining node centralities.

To the best of the author’s knowledge, this is the first study attempting to model tourist activity and consumption in a network and explore the properties of the network. Not only has this study provided a new real-world network for network research, but it has also suggested an innovative modeling approach for tourist behavior research.

The existing literature has examined the determinants of post-purchase behavioral intentions. However, less attention has been devoted to the factors that contribute to perceived usefulness of fast-food restaurants attributes. The current study considers the servicescapes and social servicescapes of restaurants as well as their relationship with customers' perceived usefulness, with the moderating role of customer experience. It also explores how perceived usefulness influences choice process satisfaction and subsequent behavioral responses, including revisit intention and negative word-of-mouth.

Data from 485 fast-food restaurant consumers in Pakistan were collected using purposive sampling. The data were analyzed using both structural equation modeling (SEM) through AMOS 24.0 and the PROCESS macro in IBM SPSS 27.0.

The research revealed that perceived usefulness in fast-food restaurant industry is positively influenced by servicescapes and social servicescapes. Similarly, choice process satisfaction is primarily caused by perceived usefulness and affects behavioral responses. It also found that choice process satisfaction is positively associated with revisit intentions and negative word-of-mouth. Customer experience significantly moderates the relationship between ambient condition, facility aesthetic, layout, perceived similarity and perceived usefulness. However, customer experience insignificant moderates the relationships of physical appearance and suitable behavior with perceived usefulness.

The findings provide insightful information for both academic and managerial fields, contributing to the literature on consumer psychology, consumer behavior, servicescapes and the stimulus-organism-response theory. The study also assists restauranteurs in the fast-food restaurant industry in overcoming the challenges posed by a highly competitive environment and developing strategies based on consumer perceptions.

This study, conducted in Pakistan, took a pioneer step in testing and confirming a novel perceived usefulness model that incorporates not only servicescapes but also social servicescapes in consumer behavior. It enhances the knowledge of consumer visit intentions by quantifying the significance of perceived usefulness developed by different servicescapes.

Smart-work has been attracting more attention since the COVID-19 outbreak hit the world in 2020. Smart-working practices do not always run smoothly despite the necessary infrastructure being in place. Taking the quality-value-loyalty chain and information system continuance model as the basis, this study aims to identify how “smart-work support service” leads to employees’ continuance intention toward smart-work. In this study, the smart-work support service refers to the infrastructure making smart-work possible and services needed to support smart-work.

Using data collected from a survey of 406 employees working in Korea, this study verifies the components of smart-work support service quality and dimensions of perceived value through partial least squares analysis and then tests the proposed conceptual model using structural equation modeling.

The results verified that the quality of smart-work support service consists of eight attributes while dividing the perceived value of smart-work into three dimensions and further revealed that the service quality influences the intention to continue smart-working by way of perceived value and satisfaction.

This study sought to explore the relationship among service quality, perceived value and satisfaction by clearly conceptualizing and measuring them in the context of smart-work, thereby ultimately understanding the impact they have on the intention to continue smart-work.