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This study aims to investigate the motivations for the adoption of Industry 4.0 technologies among manufacturing firms in developing economies. Specifically, the effects of relative advantage of the technologies, competitive pressure, and government support on the adoption are explored. Moreover, the mediating role of top management support between environmental factors (government support and competitive pressure) and the adoption of Industry 4.0 technologies is examined.

A research model is developed based on the technology-organization-environment (TOE) framework strengthened by institutional theory. Structural equation modeling (SEM) approach is employed to evaluate the model using data obtained from 215 manufacturing firms through a cross-industry survey. Additionally, a post-hoc analysis is conducted using cluster analysis and ANOVA.

The results show that competitive pressure and government support significantly promote top management support, which in turn contributes to the adoption of Industry 4.0 technologies. Relative advantage of the technologies is not significantly related to the adoption.

This study does not explore the relationship between technology type and the specific needs of manufacturing firms. Future researchers can conduct a more comprehensive analysis by examining how different technology types align with the unique needs of individual companies.

The findings of this study have implications for both policymakers and managers. Policymakers can leverage these insights to understand the underlying motivations behind manufacturing firms' adoption of Industry 4.0 technologies and develop promoting policies. In turn, managers should keep an eye on government policies and utilize government support to facilitate technology adoption.

This study uncovers the underlying motivations—government support and competitive pressure—for the adoption of Industry 4.0 technologies among manufacturing firms in developing economies. Meanwhile, it complements previous research by showing the mediating role of top management support between environmental factors (government support and competitive pressure) and the adoption of Industry 4.0 technologies.

A city is a spatial carrier of innovation activities. Improving the level of urban innovation can play a significant supporting role in building an innovative country. China began to implement the innovative city pilot policy in 2008 and continued to expand the policy into more areas for exploring the path of innovative urban development with Chinese characteristics and improving urban innovation.

Based on mechanism analysis, this paper used the panel data of 269 cities from 2003 to 2016 to empirically test the effect of the pilot policy on the level of urban innovation by using different methods, such as the difference-in-differences model.

The results show that the innovative city pilot policy significantly improves the level of urban innovation. However, according to the findings of the heterogeneity analysis, the effect of the pilot policy on improving the innovation level in direct-controlled municipalities, provincial capitals and sub-provincial cities is weaker than that in ordinary cities, and the effect of the pilot policy on improving the innovation level in cities with a higher quality of science and education resources is weaker than that in cities with lower quality of science and education resources.

Moreover, as the level of urban innovation increases, the effect of the pilot policy on improving the level of urban innovation is an asymmetric inverted V shape, which means the effect is first strengthened and then weakened. The research also finds that the locational heterogeneity of the pilot policy for improving the level of urban innovation is not notable. In addition, the innovative city pilot policy can strengthen the government's strategic guidance, promote the concentration of talent, incentivize corporate investment and optimize the innovation environment, having a positive impact on urban innovation. Moreover, the effect of concentration of talent and the effect of corporate investment incentive are the important reasons for the pilot policy to promote the improvement of the level of urban innovation.

Decision-making is one of the key technologies for self-driving cars. The high dependency of previously existing methods on human driving data or rules makes it difficult to model policies for different driving situations.

In this research, a probabilistic decision-making method based on the Markov decision process (MDP) is proposed to deduce the optimal maneuver automatically in a two-lane highway scenario without using any human data. The decision-making issues in a traffic environment are formulated as the MDP by defining basic elements including states, actions and basic models. Transition and reward models are defined by using a complete prediction model of the surrounding cars. An optimal policy was deduced using a dynamic programing method and evaluated under a two-dimensional simulation environment.

Results show that, at the given scenario, the self-driving car maintained safety and efficiency with the proposed policy.

This paper presents a framework used to derive a driving policy for self-driving cars without relying on any human driving data or rules modeled by hand.

The aim of the paper is to investigate the associations between hedge fund activism and corporate internal control weaknesses.

In this paper, the authors identify hedge fund activism events using 13D filings and news search. After matching with internal control related information from Audit Analytics, the authors utilize ordinary least square (OLS) and propensity score matching (PSM) to analyze the data.

The authors find that after hedge fund activism, target firms report additional internal control weaknesses, and these identified internal control weaknesses are remediated in subsequent years, leading to better financial-reporting quality.

The findings indicate that both managers and activists have incentives to develop a stronger internal control environment after targeting.

In order to systematically grasp the changes and matching characteristics of wheel and rail profiles of high speed railway (HSR) in China, 172 rail profile measurement points and 384 wheels of 6 high-speed electric motive unites (EMUs) were selected on 6 typical HSR lines, including Beijing–Shanghai, Wuhan–Guangzhou, Harbin–Dalian, Lanzhou–Xinjiang, Guiyang–Guangzhou and Dandong–Dalian for a two-year field test.

Based on the measured data, the characteristics of rail and wheel wear were analyzed by mathematical statistics method. The equivalent conicity of wheel and rail matching in a wheel reprofiling cycle was analyzed by using the measured rail profile.

Results showed that when the curve radius of HSR was larger than 2,495 m, the wear rate of straight line and curve rail was almost the same. For the line with annual traffic gross weight less than 11 Mt, the vertical wear of rail was less than 0.01 mm. The wear rate of the rail with the curve radius less than 800 m increased obviously. The wheel tread wear of EMUs on Harbin–Dalian line, Lanzhou–Xinjiang line and Dandong–Dalian line was relatively large, and the average wear rate of tread was about 0.05–0.06 mm·(10,000 km)⁻¹, while that of Beijing–Shanghai line, Wuhan–Guangzhou line and Guiyang–Guangzhou line was about 0.03–0.035 mm·(10,000 km)⁻¹. When the wear range was small, the equivalent conicity increased with the increase of wheel tread wear. When the wear range of wheel was wide, the wheel–rail contact points were evenly distributed, and the equivalent conicity did not increase obviously.

This research proposes the distribution range of the equivalent conicity in one reprofiling cycle of various EMU trains, which provides guidance for the condition-based wheel reprofiling.

China has proposed two-stage goals of carbon peaking by 2030 and carbon neutralization by 2060. The carbon emission reduction effect of the power industry, especially the thermal power industry, will directly affect the progress of the goal. This paper aims to reveal the spatial-temporal characteristics and influencing factors of carbon emission efficiency of the thermal power industry and proposes policy suggestions for realizing China’s carbon peak and carbon neutralization goals.

This paper evaluates and compares the carbon emission efficiency of the thermal power industry in 29 provinces and regions in China from 2014 to 2019 based on the three-stage slacks-based measure (SBM) of efficiency in data envelopment analysis (DEA) model of undesired output, excluding the influence of environmental factors and random errors.

Empirical results show that during the sample period, the carbon emission efficiency of China’s thermal power industry shows a fluctuating upward trend, and the carbon emission efficiency varies greatly among the provincial regions. The carbon emission efficiency of the interregional thermal power industry presents a pattern of “eastern > central > western,” which is consistent with the level of regional economic development. Environmental factors such as economic level and environmental regulation level are conducive to the improvement of carbon emission efficiency of the thermal power industry, but the proportion of thermal power generation and industrial structure is the opposite.

This paper adopts the three-stage SBM–DEA model of undesired output and takes CO₂ as the undesired output to reveal the spatial-temporal characteristics and influencing factors of carbon emission efficiency in China’s thermal power industry. The results provide a more comprehensive perspective for regional comparative evaluation and influencing factors of carbon emission efficiency in China’s thermal power industry.

This review aims to provide synoptic documentation on acclaimed anecdotal plant-based remedies used by Latin America and the Caribbean (LAC) communities to manage COVID-19. The theoretical approaches that form the basis for using the anecdotally claimed phytotherapies were reviewed against current scientific evidence.

In this paper plant-based remedies for managing COVID-19 were searched on social and print media to identify testimonies of people from different communities in LAC countries. Information was extracted, evaluated and reviewed against current scientific evidence based on a literature search from databases such as Journal Storage (JSTOR), Excerpta Medica Database (EMBASE), SpringerLink, Scopus, ScienceDirect, PubMed, Google Scholar and Medline to explore the scientific basis for anecdotal claims.

A total of 23 medicinal plants belonging to 15 families were identified as phytotherapies used in managing COVID-19 in LAC communities.

The plant-based remedies contained valuable phytochemicals scientifically reported for their anti-inflammatory, antiviral, antioxidant and anticancer effects. Anecdotal information helps researchers investigate disease patterns, management and new drug discoveries. The identified acclaimed plant-based remedies are potential candidates for pharmacological evaluations for possible drug discovery for future pandemics.

This paper aims to present a human-in-the-loop natural teaching paradigm based on scene-motion cross-modal perception, which facilitates the manipulation intelligence and robot teleoperation.

The proposed natural teaching paradigm is used to telemanipulate a life-size humanoid robot in response to a complicated working scenario. First, a vision sensor is used to project mission scenes onto virtual reality glasses for human-in-the-loop reactions. Second, motion capture system is established to retarget eye-body synergic movements to a skeletal model. Third, real-time data transfer is realized through publish-subscribe messaging mechanism in robot operating system. Next, joint angles are computed through a fast mapping algorithm and sent to a slave controller through a serial port. Finally, visualization terminals render it convenient to make comparisons between two motion systems.

Experimentation in various industrial mission scenes, such as approaching flanges, shows the numerous advantages brought by natural teaching, including being real-time, high accuracy, repeatability and dexterity.

The proposed paradigm realizes the natural cross-modal combination of perception information and enhances the working capacity and flexibility of industrial robots, paving a new way for effective robot teaching and autonomous learning.

This paper aims to analyze the bearing characteristics of the high speed train window glass under aerodynamic load effects.

In order to obtain the dynamic strain response of passenger compartment window glass during high-speed train crossing the tunnel, taking the passenger compartment window glass of the CRH3 high speed train on Wuhan–Guangzhou High Speed Railway as the research object, this study tests the strain dynamic response and maximum principal stress of the high speed train passing through the tunnel entrance and exit, the tunnel and tunnel groups as well as trains meeting in the tunnel at an average speed of 300 km·h-1.

The results show that while crossing the tunnel, the passenger compartment window glass of high speed train is subjected to the alternating action of positive and negative air pressures, which shows the typical mechanic characteristics of the alternating fatigue stress of positive-negative transient strain. The maximum principal stress of passenger compartment window glass for high speed train caused by tunnel aerodynamic effects does not exceed 5 MPa, and the maximum value occurs at the corresponding time of crossing the tunnel groups. The high speed train window glass bears medium and low strain rates under the action of tunnel aerodynamic effects, while the maximum strain rate occurs at the meeting moment when the window glass meets the train head approaching from the opposite side in the tunnel. The shear modulus of laminated glass PVB film that makes up high speed train window glass is sensitive to the temperature and action time. The dynamically equivalent thickness and stiffness of the laminated glass and the dynamic bearing capacity of the window glass decrease with the increase of the action time under tunnel aerodynamic pressure. Thus, the influence of the loading action time and fatigue under tunnel aerodynamic effects on the glass strength should be considered in the design for the bearing performance of high speed train window glass.

The research results provide data support for the analysis of mechanical characteristics, damage mechanism, strength design and structural optimization of high speed train glass.

In this study, the authors sought to investigate how the implicit social ties of both project owners and potential backers are associated with crowdfunding project success.

Drawing on social ties theory and factors that affect crowdfunding success, in this research, the authors developed a model to study how project owners' and potential backers' implicit social ties are associated with crowdfunding projects' degrees of success. The proposed model was empirically tested with crowdfunding data collected from Kickstarter and social media data collected from Twitter. The authors performed the test using an ordinary least squares (OLS) regression model with fixed effects.

The authors found that project owners' implicit social ties (specifically, their social media activities, degree centrality and betweenness centrality) are significantly and positively associated with crowdfunding projects' degrees of success. Meanwhile, potential project backers' implicit social ties (their social media activities and degree centrality) are negatively associated with crowdfunding projects' degrees of success. The authors also found that project size moderates the effects of project owners' social media activities on projects' degrees of success.

This work contributes to the literature on crowdfunding by investigating how the implicit social ties of both potential backers and project owners on social media are associated with crowdfunding project success. This study extends the previous research on social ties' roles in explaining crowdfunding project success by including implicit social ties, while the literature explored only explicit social ties.