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Harmonic drives are used widely in aviation, robotics and instrumentation due to their benefits including high transmission ratio, compact structure and zero backlash. One of the common faults of a harmonic drive is the axial movement of the input shaft. In such a case, its input shaft moves in the axial direction relative to the body of the harmonic drive. The purpose of this study is to propose two fault diagnosis methods based on the current signal of the driving servomotor for the axial movement failure in terms of input shafts of harmonic drives.

In the two proposed fault diagnosis methods, the wavelet threshold algorithm is firstly used for filtering noises of the motor current signal. Then, the feature of the denoised current signal is extracted by the empirical mode decomposition (EMD) method and the wavelet packet energy-entropy (WPEE) theory, respectively, obtaining two kinds of feature sets. After a deep learning model based on the deep belief network (DBN) is constructed and trained by using these feature sets, we finally identify the normal harmonic drives and the ones with the axial movement fault.

In contrast to the traditional back propagation (BP) neural network model and support vector machine (SVM) model, the fault diagnosis methods based on the combination of the EMD (as well as the WPEE) and the DBN model can obtain higher accuracy rates of fault diagnosis for axial movement of harmonic drives, which can be greater than or equal to 97% based on the data of the performed experiment.

The authors propose two fault diagnosis methods based on the current signal of the driving servomotor for the axial movement failure in terms of input shafts of harmonic drives, which are verified by the experiment. The presented study may be beneficial for the development of self-diagnosis and self-repair systems of different robots and precision machines using harmonic drives.

The aim of this study is to discern the role of digital finance in driving rural industrial integration and revitalization. Specifically, it intends to shed light on how the deep development of digital finance can contribute to the optimization and transformation of the rural industrial structure. The research further explores the particular effects of this financial transformation in the central and western regions of China.

This research studies the influence of digital finance on rural industrial integration across 30 Chinese provinces from 2011 to 2020. Utilizing the entropy weight method, a comprehensive evaluation index system is established to gauge the level of rural industrial integration. A two-way fixed effects model, intermediary effect model, and threshold effect model are employed to decipher the relationship between digital finance and rural industrial integration.

Findings reveal a positive relationship between digital finance and rural industrial integration. A single threshold feature was identified: beyond a traditional finance development level, the marginal effect of digital finance on rural industrial integration increases. These effects are more noticeable in central and western regions.

Empirical outcomes contribute to policy discourse on rural digital finance, assisting policymakers in crafting effective strategies. Understanding the threshold of traditional finance development provides a new perspective on the potential of digital finance to drive rural industrial integration.

In response to the challenges posed by the conventional manual flange docking method in the LNG (Liquefied Natural Gas) loading process, such as low positioning accuracy, constraints on production efficiency and safety hazards, this study analyzed the LNG five-axis loading arm’s main functions and structural characteristics.

An automated solution for the joints of the LNG loading arm was designed. The forward kinematic model of the LNG loading arm was established using the Denavit–Hartenberg (D-H) parameter method, and its workspace was analyzed. The Newton–Raphson iteration method was employed to solve the inverse kinematics of the LNG loading arm, facilitating trajectory planning. The relationship between the target position and the joint variables was established to verify the stability of the arm’s motion. Flange center identification was achieved using the Hough transform function. Based on the ROS platform, combined with Gazebo and Rviz, an experimental simulation of automatic docking of the LNG loading arm was conducted.

The docking errors in the XYZ directions were all less than 0.8 mm, meeting the required docking accuracy. Moreover, the motion performance of the loading arm during docking was smooth and free of abrupt changes, validating its capability to accomplish the automatic docking task.

The proposed trajectory planning and automatic docking scheme can be used for the rapid filling of LNG filling arms and LNG tankers to improve the efficiency of LNG transportation. In guiding the docking, the proposed automatic docking scheme is an accurate and efficient way to improve safety.

Maritime transportation plays an important role in facilitating both the global and regional merchandise trade, where accurate trend prediction is crucial in assisting decision-making in the industry. This paper aims to conduct a macro-level study to predict world vessel supply and demand.

The automatic autoregressive integrated moving average (ARIMA) is used for the univariate vessel supply and demand time-series forecasting based on the data records from 1980 to 2021.

For the future projection of the demand side, the predicted outcomes for total vessel demand and world dry cargo vessel demand until 2030 indicate upward trends. For the supply side, the predominant upward trends for world total vessel supply, oil tanker vessel supply, container vessel supply and other types of vessel supply are captured. The world bulk carrier vessel supply prediction results indicate an initial upward trend, followed by a slight decline, while the forecasted world general cargo vessel supply values remain relatively stable. By comparing the predicted percentage change rates, there is a gradual convergence between demand and supply change rates in the near future. We also find that the impact of the COVID-19 pandemic on the time-series prediction results is not statistically significant.

The results can provide policy implications in strategic planning and operation to various stakeholders in the shipping industry for vessel building, scrapping and deployment.

Climate change and global warming are two major ecological concerns. The construction industry has instituted measures such as green construction in response to these concerns. This study seeks to assess the views of architects on the uptake of innovative green construction (IGC) in Ghana.

This study applies the theory of planned behaviour (TPB) to investigate the factors influencing the decision to adopt IGC. A structured questionnaire was issued to architects who have been involved in the design and/or construction of green buildings in Ghana. The dataset was obtained from 61 architects and Partial Least Square was used to analyse the data.

The results show that two TPB factors; attitude and perceived behavioural control are significant determinants of architects’ intention to adopt IGC. Interestingly, behavioural intention did not have an influence on the actual behaviour of IGC adoption. However, perceived behavioural control had a significant impact on the actual adoption of IGC.

Contextually, the findings of the study will contribute to policy development and marketing of various green innovation within the Ghanaian construction milieu. Practically, the study will help encourage stakeholders to build the right capacity and competence towards the uptake of IGC.

The originality of the paper is based on the theoretical framework underpinning the study and the target respondents as the unit of analysis in assessing the full uptake of IGC in Ghana. The utility of the model evinces the role behavioural changes play in ecological development.

Conceptual and empirical research over the past 20 years has moved the social media (SM) literature beyond the embryotic stage to a well-developed academic discipline. As the lead article in the special issue in the Journal of Research in Interactive Marketing on Cutting-Edge Research in Social Media and Interactive Marketing, this review and agenda article has two key goals: (1) to review key SM and interactive marketing research over the past three years and (2) to identify the next wave of high priority challenges and research opportunities.

Given the “cutting-edge” research focus of the special issue, this review and research agenda paper focused on articles published in 25 key marketing journals between January 2021 and March 2024. Initially, the search request was for articles with “social media, social selling, social commerce” located in the article title, author-selected key words and journal-selected keywords. Later, we conducted searches based on terminology from articles presented in the final review. In total, over 1,000 articles were reviewed across the 25 journals, plus additional ones that were cited in those journals that were not on the initial list.

Our review uncovered eight key content areas: (1) data sources, methodology and scale development; (2) emergent SM technologies; (3) artificial intelligence; (4) virtual reality; (5) sales and sales management; (6) consumer welfare; (7) influencer marketing; and (8) social commerce. Table I provides a summer of key articles and research findings for each of the content areas.

As a literature review and research agenda article, this paper is one of the most extensive to date on SM marketing, and particularly with regard to emergent research over the past three years. Recommendations for future research are integrated through the paper and summarized in Figure 2.

Consumer welfare is one of the eight emergent content areas uncovered in the literature review. Specific focus is on SM privacy, misinformation, mental health and misbehavior.

This study aims to explore a potential conference experience design strategy, namely, festivalization. It investigates the potential festivalization effects on conference attendees in two formats of business conferences: virtual and in-person.

A series of two scenario-based experimental studies were conducted. A series of one-way analysis of covariance and PROCESS procedures (Model 6) were performed for data analysis.

The inclusion of festivalization elements significantly enhances positive responses of attendees, especially for in-person conferences. This effect is further explained by a serial mediation effect, where enhanced perceived values and conference engagement play key roles in improving attendees’ conference experience.

By incorporating festivalization elements, conference organizers can create a more engaging and satisfying event experience for attendees. This can lead to greater satisfaction, positive word-of-mouth and increased registrations.

This study represents a pioneering effort in revealing the underlining mechanisms that explain how festivalization affects attendee engagement and subsequent behaviors in business event management in both face-to-face and virtual settings.

Building on social exchange theory (SET), the main aim of this paper is to empirically study the impact of high-commitment work practices (HCWPs) systems on radical innovation. Additionally, the paper examines the mediating roles of employee innovative work behaviour (IWB) and knowledge sharing (KS) in the relationship between HCWPs and radical innovation.

Using a survey questionnaire, data were collected from employees working in pharmaceutical, manufacturing and technological industries in Jordan. A total of 408 employees participated in the study. Structural equation modelling (SEM) using AMOS v28 was employed to test the research hypotheses.

This research found that HCWPs in the form of a bundle of human resource management (HRM) practices are significant for employee IWB and KS. However, similar to previous studies, this paper failed to find a direct significant impact for HCWPs on radical innovation. Rather, the impact was mediated by employee IWB. Additionally, this paper found that HCWPs are significant for KS and that KS is significant for employee IWB.

Distinctively, this paper considered the mediating effect of employee IWB on radical innovation. Extant research treated IWB as a consequence of organisational arrangements such as HRM practices; this paper considered IWB as a foundation and source for other significant organisational outcomes, namely radical innovation. Additionally, the paper considered employees' perspectives in studying the relationship between HRM, KS, IWB and radical innovation.