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The purpose of this study is to explore how and when ethical leadership enhances bootlegging. To achieve this purpose, the authors proposed a moderated dual-path model in this study.

The model was tested on two related studies. Study 1 was based on three-wave, collected data from a sample of 511 employees of Chinese companies. Data used in Study 2 was collected by survey from employees and their direct leaders of multiple departments of companies in China.

In Study 1, the authors found that moral efficacy and moral identity mediate between ethical leadership and bootlegging. Findings from Study 2 provide convergent support of moral efficacy’s and moral identity’s impact on the mediation relationship between ethical leadership and bootlegging. Moreover, the results of Study 2 further reveal that the relationship between ethical leadership and moral efficacy (or moral identity) was more significant among leader–follower with different genders.

This study not only enriches the literature on ethical leadership and gender (dis)similarity, but also helps managers to better understand the function of bootlegging.

The purpose of this paper is to propose a knowledge extraction framework to extract knowledge, including entities and relationships between them, from unstructured texts in digital humanities (DH).

The proposed cooperative crowdsourcing framework (CCF) uses both human–computer cooperation and crowdsourcing to achieve high-quality and scalable knowledge extraction. CCF integrates active learning with a novel category-based crowdsourcing mechanism to facilitate domain experts labeling and verifying extracted knowledge.

The case study shows that CCF can effectively and efficiently extract knowledge from multi-sourced heterogeneous data in the field of Tang poetry. Specifically, CCF achieves higher accuracy of knowledge extraction than the state-of-the-art methods, the contribution of feedbacks to the training model can be maximized by the active learning mechanism and the proposed category-based crowdsourcing mechanism can scale up the effective human–computer collaboration by considering the specialization of workers in different categories of tasks.

This research proposes CCF to enable high-quality and scalable knowledge extraction in the field of Tang poetry. CCF can be generalized to other fields of DH by introducing domain knowledge and experts.

The extracted knowledge is machine-understandable and can support the research of Tang poetry and knowledge-driven intelligent applications in DH.

CCF is the first human-in-the-loop knowledge extraction framework that integrates active learning and crowdsourcing mechanisms; he human–computer cooperation method uses the feedback of domain experts through the active learning mechanism; the category-based crowdsourcing mechanism considers the matching of categories of DH data and especially of domain experts.

The purpose of this paper is to design a climbing robot connected by a connecting rod mechanism to achieve multi-functional tasks such as obstacles crossing and climbing of power transmission towers.

A connecting rod type gripper has been designed to achieve stable grasping of angle steel. Before grasping, use coordination between structures to achieve stable docking and grasping. By using the alternating movements of two claws and the middle climbing mechanism, the climbing and obstacle crossing of the angle steel were achieved.

Through a simple linkage mechanism, a climbing robot has been designed, greatly reducing the overall mass of the robot. It can also carry a load of 1 kg, and the climbing mechanism can perform stable climbing. The maximum step distance of the climbing robot is 543 mm, which can achieve the crossing of angle steel obstacles.

A transmission tower climbing mechanism was proposed by analyzing the working environment. Through the locking ability of the screw nut, stable clamping of the angle steel is achieved, and a pitch mechanism is designed to adjust the posture of the hand claw.

The rapid development and high penetration of digitalization have triggered profound changes in the energy sector. The purpose of this study is to integrate the government digital transformation into the analysis framework and discuss its impact on urban energy efficiency and its realization mechanism.

Using the “Information Benefit Pilot City” (IBC) policy as a quasi-natural experiment, and drawing on data from 285 prefecture-level cities in China from 2008 to 2019, this paper discusses how digital government affects urban energy efficiency by using difference-in-differences (DID).

The results show that digital governance significantly improves energy efficiency, and this conclusion remains reliable even after a series of robustness tests, endogeneity processing and sensitivity analysis. Heterogeneity results show that resource-based, eastern, high economic development level and high urbanization rate city digital government construction are more conducive to improving energy efficiency. The mediating effect shows that the influence mechanism of digital government on energy efficiency mainly includes reducing carbon emission, promoting green technology innovation and attracting talents.

(1) From the perspective of government digital transformation, this study supplements the way to improve energy efficiency and also expands the social dividend of government governance transformation. (2) Through quasi-experimental analysis of IBC policy, this paper solves the problem of difficulty in quantifying the government's digital transformation indicators. (3) The impact heterogeneity and realization mechanism are further discussed and the specific ways of digital government's impact on energy efficiency are revealed.

There are two opposite views about whether the Antitrust Law is conducive to the development of the economy. One view is that the Antitrust Law can restrain monopoly, maintain market competition and benefit economic growth. The other view is that the Antitrust Law inhibits innovation by monopolistic firms and fosters rent-seeking, which is bad for economic growth. To provide a possible perspective for clarifying the controversy, this paper aims to answer the following two questions: first, will the Antitrust Law inhibit corporate innovation? Second, does the antitrust enforcement agency discriminate against private enterprises?

Based on the samples of A-share listed companies from 2003 to 2013, the authors use the implementation of China’s Antitrust Law in 2008 as a policy shock, take the monopoly enterprises in each industry as the treatment group and competitive enterprises as the control group, using the difference-in-differences method to test the impact of the implementation of the Antitrust Law on corporate innovation activities.

The results show that compared with competitive enterprises, the patent output of monopolistic enterprises was significantly reduced after the implementation of the Antitrust Law, which indicates that the Antitrust Law does inhibit the innovation activities of monopolistic enterprises. Further research finds that the innovation suppression effect of the Antitrust Law is more prominent in state-owned enterprises, which means that the government does not have “selective law enforcement” against private enterprises in the process of law enforcement. Therefore, the results provide evidence for the idea that government intervention is neutral.

First, the paper enriches and expands the research on the factors affecting corporate innovation from the perspective of market structure. Second, it enriches and expands relevant research on the consequences of implementing the Antitrust Law from the perspective of corporate innovation. Third, it not only provides the relevant empirical evidence for clarifying the dispute about the Antitrust Law but also is helpful to clarify whether the Chinese Government has “selective law enforcement” against private enterprises.

Augmented reality (AR) and virtual reality (VR) are becoming increasingly interwoven into people's daily lives, with applications in fields such as science, engineering, medical, the arts, education, finance and business. While much study has been conducted in the field of VR and AR in a variety of areas, less attention has been paid to online education. The purpose of this research is to conduct a systematic review of studies on AR and VR, as well as its applications in many disciplines of education, with a special emphasis on online education.

The data were gathered from the SCOPUS database under the subject “Augmented and Virtual Reality Applications in Online Education.” The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) format has been used to summarize the available literature and research in academics throughout the world. First, systematic literature reviews and later bibliometric analysis were conducted for performance and science mapping analysis.

The research adds to the body of knowledge about the role of AR and VR in online education and its future prospects. AR and VR have demonstrated a substantial contribution to facilitating teaching in a variety of fields, including engineering, medicine, nursing and chemistry. Additionally, this research indicates that AR and VR can be utilized to teach various areas and specialties. Additionally, it can be used in other aspects of online education, such as admissions, industry visits, training, internationalization and specific courses for students with disabilities.

This research lays the framework for educational institutions, legislators and researchers to investigate additional applications of VR and AR. Though this research suggests some possible uses for AR and VR in the online education system, more applications can be integrated into the online education system to fully leverage the potential of AR and VR worldwide. AR and VR have the potential to be a very cost-effective method of delivering online education on a wide scale in the future.

The article explores the applicability of VR and AR in education using bibliometric analysis. This is one of the first studies to do an assessment of VR and AR, evaluating their strengths, drawbacks and current applications. Future application areas are also identified as a result of the investigation.