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Power transformers are vital components of an electrical network. A defective transformer can cause instability and blackouts in parts of the network. An accurate classification of different transformer faults results in a relatively accurate fault diagnosis and timely corrective actions. It is possible to increase productivity and reduce costs by using fault detection of power transformers through the analysis of gases dissolved in oil. The proposed technique is a suitable tool to help the utilities and engineers in charge of preventive maintenance by reducing the costs of different fault diagnosis tests for power transformers.

In this paper, the IEC 60599 standard along with clustering and classification methods are used to classify power transformer’s fault types. K-means and Fuzzy C-means clustering methods are used for clustering, and the support vector machine (SVM) method is used for classification of different types of faults in ‎power ‎transformers. The performance of K-means and SVM methods is improved by using the Grasshopper Optimization Algorithm (GOA). The efficiency of the proposed methods is evaluated using real field data of power transformers. The purpose of this study is to propose hybrid methods including K-means-GOA clustering and SVM-GOA classification for accurate fault diagnosis. These methods have been used for the first time in fault diagnosis determination of power transformers through gas analysis. The Silhouette criteria is used in this paper to compare the efficiency of different clustering methods.

Simulation results of the paper are based on the gas chromatography data related to 266 different real power transformers. They show the high accuracy and high-performance speed of intelligent clustering and classification methods compared to conventional ones. This analysis would be helpful in performing the required maintenance check and plan for repairs.

The applicability and efficiency of the proposed hybrid K-means-GOA and SVM-GOA models are verified for transformer fault detection using the experimental diverse data set including 266 set of real field test parameters of power transformers.

This study aims to examine the effects of dialect connectedness between the chairman and the chief executive officer (CEO) (DCCC) on the tunneling activities of controlling shareholders.

This study uses abnormal related-party transactions (ARPT) as a proxy for tunneling activities and traces dialects of chairmen and CEOs based on the respective birthplace information. Baseline results are examined using a fixed-effects model. The results remain robust when using the instrumental variable approach, propensity score matching (PSM) technique, changing the measurement of tunneling and Heckman two-step selection model.

The results show that DCCC reduces tunneling activities. This negative association is more pronounced for non-state-owned enterprises and firms whose chairmen and CEOs work in the respective hometowns. DCCC restrains tunneling activities through mechanisms by establishing an informal supervisory effect on CEOs because the CEOs fear reputational damage and strengthening cooperation between chairmen and CEOs. Further analyses suggest that this negative association is more significant when chairmen and CEOs are non-controlling shareholders, but the association is weakened during the coronavirus disease 2019 (COVID-19) crisis.

As dialect is a carrier of culture, this study's results imply that cultural proximity can replace formal mechanisms to enhance corporate governance.

The authors empirically examined the theoretically recognized industrial linkages between manufacturing and services from the trade perspective. In particular, they confirmed the trade effect of manufacturing on services, given that global value chain fragmentation pervades and splits manufacturing and services segments separately in developed and developing countries.

Based on observations of 47 countries with manufacturing and service trade data from 1990 to 2020 and with gravity model specification, the authors primarily used the Poisson pseudo-maximum likelihood (PPML) estimation with multiple levels of fixed effects. Considering that many zero values are included in the dependent variable and potential endogeneity, other methods such as Tobit regression, Heckman estimation and two-stage least squares estimation (2SLS) are used. Subsample estimation also supplemented the empirical research.

The results showed that manufacturing trade is a stepping-stone rather than an obstacle to service trade. This finding exhibited significant robustness under different model specifications, instrumental variable estimation and subsample checks. Moreover, in contrast to the north–north country ties, manufacturing trade between northern and southern countries has played a prominent stepping-stone role; meanwhile, manufacturing trade among core–peripheral countries has a considerably more significant impact than the outcomes of core–core and peripheral–peripheral countries.

The authors provided direct clarification and revealed that trade in manufacturing remains the demand basis for service trade. As trade in manufacturing and services are typical phenomena of transnational production linkages, the authors suggested exploring the underlying role of global value chain (GVC) fragmentation and the offset and even barrier effect of biased institutional arrangements on GVC fragmentation.

The operation of water environment treatment Public-Private Partnership projects (WETP-PPP) is crucial to the project effectiveness. However, there are often problems in projects that attach importance to construction and neglect operation management, which seriously affect the project operation effect. To ensure the good operation effect of the WETP-PPP, an evolutionary game model of the regulation strategy during the operation period of WETP-PPP is constructed.

An evolutionary game model of regulation is established which considers the government, the project company and the public in water environment treatment Public-Private Partnership projects (WETP-PPP). Five scenarios of equilibriums and the game's evolutionary stable strategies are analyzed, and the corresponding stability conditions are then obtained. Finally, through the simulation, the influence of different factors on the choice of the three-party strategy is analyzed.

First, the key factors that affect the evolution game are the regulation costs and performance rewards of the government, the project company's operation costs and penalties for opportunism and the public supervision costs and rewards. Second, in order to ensure the operation effect, the government needs the performance incentive from the superior government. Third, the public's supervision enthusiasm needs to be mobilized by the government. Last, the penalty strength of speculative operation should be strong enough to play a deterrent role.

The theoretical research in this paper has some limitations. Initially, due to the large number of participants in WETP-PPP, in addition to the government department, the project company and the public studied in this paper, it also involves the consulting industry and financial institutions. In the future, more participants can be added to form four-party interest relationships and conduct four-party evolutionary game research. Second, the operation environment of WETP-PPP is complex and changeable, and various influencing factors are intertwined, the number of parameters involved in this paper is limited, and further detailed research is needed in the future.

Based on the evolutionary game theory, this article discusses the evolution law of the tripartite game behavior of the government department, the project company and the public, which is helpful to clarify the strategy evolution path of the tripartite in the WETP-PPP, and the generation condition and evolution mechanism of the equilibrium strategy of the tripartite game. The key parameters affecting the tripartite strategy selection are analyzed through simulation, which can provide reference for the government department to formulate relevant measures. At the same time, it broadens the application field of evolutionary games and supplements the research on the management mechanism of WETP-PPP during the operation period.

Based on the evolutionary game theory, this paper introduces the supervision behavior of the public, which can provide a new perspective for researchers to conduct relevant research. Secondly, for the regulation during the operation of WETP-PPP, this paper can provide reference for the government department to establish a scientific public supervision system, improve the government supervision mechanism and other relevant measures, which can help promote the public supervision willingness, improve the regulation efficiency of the government and guide the project company to reduce speculation, so as to ensure the effect of water environment management.

This paper focuses on the regulation of WETP-PPP during the operation period to research interactions among the government, the project company and the public. Based on the analysis of the evolutionary game, some suggestions are put forward, such as perfecting the government regulation mechanism, optimizing the reward and punishment system for the project company and broadening the channels of public supervision. The research results of this paper can provide support for the government's regulation of WETP-PPP and ensure the project operation effect.

With the current developments within the sphere of Internet of Things (IoT) technology, many conventional articles are all being fitted with smart functionalities, ranging from chairs, beds, shoes and caps to underwear. Bags which are utility as well as fashion items have not been left out of this smart craze, albeit to a less popular degree. The purpose of this study is to fill the research gap on the subject of smart bags research and applications and to contribute to the general discourse on IoT.

This study adopts literature search and database review, concept mapping as well as synthesis methodologies. Relevant literature form databases such as Web of Science, Google Scholar and Bing Scholar were interrogated. Manual sifting was done to eliminate papers that do not fit the set inclusion criteria. Literature on smart bags was organized into structured frameworks using concept mapping methodology. Applying a synthesis methodology enabled an exploration of the different technological trends in smart bag research and their areas of application.

The study identified about 15 different smart bag applications and functionalities. Discussed in this study is a classification of bags based on a number of points such as way of carrying, size, utility and fabrication materials. Also discussed are the description of what constitute a smart bag, relevant technologies for smart bag design and engineering and subsequently the current trends in smart bag applications. This study also discovered that the air travel industry tend to have some difficulties with this smart bag technologies, specifically with their built-in batteries.

The results of this study will provide researchers and other stakeholders with key information about existing problems and opportunities in smart bag research and applications. This will go a long way to help in guiding future research as well as policymaking in smart bag design and application.

To the best of the authors’ knowledge, this is the first review on the subject of smart bags even though smart bag research and commercial product design continue to gain momentum in recent years.

Drawing upon affective events theory and regulatory focus theory, the current study examines the relationship between customer gratitude and customer-oriented organizational citizenship behavior (customer-oriented OCB), and the mediating role of positive affect and the moderating role of trait promotion focus.

Three-wave time-lagged data from 674 nurses nested within 125 department supervisors was collected. Multilevel modeling and Monte Carlo simulation were performed using Mplus 7.1 software to test all hypotheses.

Customer gratitude was positively associated with nurses’ customer-oriented OCB, and the relationship was mediated by positive affect. Nurse trait promotion focus strengthened the positive relationship between patient gratitude and positive affect, such that the relationship was stronger for those with a higher level of trait promotion focus.

This paper extends research on the effects of customer gratitude by extending our understanding of customer gratitude as a positive workplace event that can potentially promote employees’ positive behaviors toward customers, especially those with a stronger promotion focus.

This study is one of the first to examine the relationship between customer gratitude and employee customer-oriented OCB and uncover potential mechanisms to understand how this relationship unfolds and to whom this relationship is stronger. These findings can inform practices for service organizations.

This paper aims to focus on the research progress of intelligent self-healing anti-corrosion coatings in the aviation field in the past few years. The paper provides certain literature review supports and development direction suggestions for future research on intelligent self-healing coatings in aviation.

This mini-review uses a systematic literature review process to provide a comprehensive and up-to-date review of intelligent self-healing anti-corrosion coatings that have been researched and applied in the field of aviation in recent years. In total, 64 articles published in journals in this field in the last few years were analysed in this paper.

The authors conclude that the incorporation of multiple external stimulus-response mechanisms makes the coatings smarter in addition to their original self-healing corrosion protection function. In the future, further research is still needed in the research and development of new coating materials, the synergistic release of multiple self-healing mechanisms, coating preparation technology and corrosion monitoring technology.

To the best of the authors’ knowledge, this is one of the few systematic literature reviews on intelligent self-healing anti-corrosion coatings in aviation. The authors provide a comprehensive overview of the topical issues of such coatings and present their views and opinions by discussing the opportunities and challenges that self-healing coatings will face in future development.

This study aims to address the issue that existing methods for limb action recognition typically assume a fixed wearing orientation of inertial sensors, which is not the case in real-world human-robot interaction due to variations in how operators wear it, installation errors, and sensor movement during operation.

To address the resulting decrease in recognition accuracy, this paper introduced a data transformation algorithm that integrated the Euclidean norm with singular value decomposition. This algorithm effectively mitigates the impact of orientation errors on data collected by inertial sensors. To further enhance recognition accuracy, this paper proposed a method for extracting features that incorporate both time-domain and time-frequency domain features, markedly improving the algorithm’s robustness. This paper used five classifiers to conduct comparative experiments on action recognition. Finally, this paper built an experimental human-robot interaction platform.

The experimental results demonstrate that the proposed method achieved an average action recognition accuracy of 96.4%, conclusively proving its effectiveness. This approach allows for the recognition of data from sensors placed in any orientation, using only training samples conducted at an orientation.

This study addresses the challenge of reduced accuracy in limb action recognition caused by sensor misorientation. The human-robot interaction system developed in this paper was experimentally verified to effectively and efficiently guide the industrial robot to perform tasks based on the operator’s limb actions.

This systematic literature review investigates the phenomenon of board multiple directorships and its implications for corporate governance and organisational performance.

The study adopts a systematic approach, which involves identifying and analysing relevant research papers on board multiple directorships. This study synthesises the latest research findings to gain insights into the determinants and consequences of multiple directorships. The sample literature was collected from the Scopus database from year 2000 till 2023.

The review reveals several key findings. Firstly, multiple directorships have both positive and negative implications for corporate governance. They can bring value by providing directors access to valuable information and resources from different companies, enhancing board functions and improving firm performance. However, there is a concern that overworked directors may not effectively fulfil their fiduciary responsibilities on any board, compromising their monitoring abilities.

This study contributes to the existing body of knowledge by comprehensively reviewing multiple board directorships research and their impact on organisations. This study synthesises the latest research findings and offers valuable insights into the determinants and consequences of this practice. Also, this study highlights the need for effective corporate governance practices that balance multiple directorships’ benefits and potential drawbacks. The study also identifies research themes and suggests potential areas for future research, contributing to the advancement of understanding in board multiple directorships.

This study aims to investigate the “digitalization paradox” in manufacturing digital transformation, where significant investments in digital technology may not necessarily lead to increased returns. Specifically, it explores the intricate relationship between digital technology convergence, financial performance, productivity and technological innovation in listed Chinese manufacturing firms, drawing upon theories of digital innovation and knowledge networks.

Using a large panel data from 747 listed firms in China’s manufacturing sector and their 428,927 patents spanning from 2013 to 2022, this research first quantifies manufacturing firm-level digital technology convergence through patent network analysis. Furthermore, this study employs hierarchical regression analysis and the instrumental variable method to investigate the curvilinear relationship between digital technology convergence and financial performance. Furthermore, the moderating role of firms’ productivity and technological innovation is tested.

Three types of firm-level digital technology convergence (DTC) are delineated and quantified: local authority in digital convergence (DegreeDTC), convergence with heterogeneous digital knowledge (BetweenessDTC) and shortest-path convergence with digital technologies (ClosenessDTC, where a higher value signifies a more conservative and shorter path in adopting digital technologies). Network visualization shows that manufacturing firms' DTC has consistently increased over time. Contrary to traditional assumptions, our research reveals a U-shaped relationship between DTC (specifically, DegreeDTC and BetweenessDTC) and financial performance. This relationship is characterized by a negative correlation at lower levels and a positive one at higher levels. The joint effect of firms’ productivity and technological innovation significantly strengthens this relationship. These findings are robust across a series of robustness checks.

Our findings offer practical insights for both managers and policymakers. We recommend a balanced approach to digital innovation management within the technology convergence paradigm. Manufacturing firms can generate economic value by strategically choosing to either shrink or expand their digital technology application areas, thereby reducing uncertainties related to emerging convergent businesses. Additionally, the study underscores the synergistic strategy of combining innovation with productivity. Within the DTC business context, integrating productivity with technological innovation not only enhances cost flexibility but also improves problem-solution matching, ultimately amplifying synergistic benefits.

To the best of our knowledge, this is the first study to apply a digital technology co-occurrence network to unveil nuanced relationships in “DTC – finance performance” within the manufacturing sector. It challenges conventional thinking regarding the common positive effect of digital innovation and technological convergence. This study provides a comprehensive analysis of DTC, financial performance, productivity and technological innovation dynamics, as well as offers managerial implications for managers and policymakers.

• (1)

  We quantify manufacturing firm-level DTC through patent network analysis and find consistent increases over time.

• (2)

  A significant U-shaped relationship between DTC and financial performance, being negative at lower levels and positive at higher levels.

• (3)

  The joint effect of firms’ productivity and technological innovation reinforces this relationship by distributing costs and enhancing synergistic benefits.

• (4)

  We challenge existing literature by uncovering a complex relationship in “DTC – finance performance”, contrary to popular belief of a monotonic effect of digital innovation or technological convergence.

We quantify manufacturing firm-level DTC through patent network analysis and find consistent increases over time.

A significant U-shaped relationship between DTC and financial performance, being negative at lower levels and positive at higher levels.

The joint effect of firms’ productivity and technological innovation reinforces this relationship by distributing costs and enhancing synergistic benefits.

We challenge existing literature by uncovering a complex relationship in “DTC – finance performance”, contrary to popular belief of a monotonic effect of digital innovation or technological convergence.