Search results

Sharing and disseminating debunking information are critical to correcting rumours and controlling disease when dealing with public health crises. This study investigates the factors that influence social media users' debunking information sharing behaviour from the perspective of persuasion. The authors examined the effects of argument adequacy, emotional polarity, and debunker's identity on debunking information sharing behaviour and investigated the moderating effects of rumour content and target.

The model was tested using 150 COVID-19-related rumours and 2,349 original debunking posts on Sina Weibo.

First, debunking information that contains adequate arguments is more likely to be reposted only when the uncertainty of the rumour content is high. Second, using neutral sentiment as a reference, debunking information containing negative sentiment is shared more often regardless of whether the government is the rumour target, and information containing positive sentiment is more likely to be shared only when the rumour target is the government. Finally, debunking information published by government-type accounts is reposted more often and is enhanced when the rumour target is the government.

The study provides a systematic framework for analysing the behaviour of sharing debunking information among social media users. Specifically, it expands the understanding of the factors that influence debunking information sharing behaviour by examining the effects of persuasive cues on debunking information sharing behaviour and the heterogeneity of these effects across various rumour contexts.

In view of the unknown environmental parameters and uncertain interference during gripping by the manipulator, it is difficult to obtain an effective gripping force with the traditional impedance control method. To avoid this dilemma, the purpose of this study is to propose an adaptive control strategy based on an adaptive neural network and a PID search optimization algorithm for unknown environments.

The method is based on a variable impedance model, and a new impedance model is established using a radial basis function (RBF) neural network to estimate unknown parameters of the impedance model. The approximation errors of the adaptive neural network and the uncertain disturbance are effectively suppressed by designing the adaptive rate. In the meantime, auxiliary variables are constructed for Lyapunov stability analysis and adaptive controller design, and PSA is used to ensure the stability of the adaptive impedance control system. Based on the Lyapunov stability criterion, the adaptive im-pedance control system is proved to have progressive tracking convergence property.

Through comparative simulations and experiments, the superiority of the proposed adaptive control strategy in position and force tracking has been verified. For objects with low flexibility and light-weight (such as a coke, a banana and a nectarine), this control method demonstrates errors of less than 10%.

This paper uses RBF neural networks to estimate unknown parameters of the impedance model in real-time, enhancing system adaptability. Neural network weights are updated online to suppress errors and disturbances. Auxiliary variables are designed for Lyapunov stability analysis. The PSA algorithm is used to adjust controller parameters in real-time. Additionally, comparative simulations and experi-ments are designed to analyze and validate the performance of controller.

This study investigates whether, how and under what circumstances off-farm work induces farmland abandonment, which is of great importance for developing countries to cope with food security.

Exploiting large-scale panel data from the newly released Chinese Family Database, this study employs a two-way fixed effects model to empirically estimate the causal relationship between off-farm work and farmland abandonment.

In the context of large-scale labor migration in rural China, current off-farm work leads to an increase in the probability and area of farmland abandoned due to insufficient agricultural labor. However, off-farm work does not harm farm households in plain areas, or villages with land rental markets, abundant agricultural labor, and agricultural machinery, while it harms others. Moreover, farmers who work off-farm in the local area are less likely to abandon their farmland than those in other areas. Additionally, when the number of off-farm workers in a household exceeds two, the probability and area of farmland abandonment will miraculously decline, as the household will no longer live entirely on agriculture.

This study may fill the gap in clarifying the relationship between off-farm work and farmland abandonment, and identify scenarios where off-farm work may not cause farmland abandonment through multiple dimensions, providing insights into the governance of farmland abandonment during rural-urban transformation in developing countries.

In the last few years, environmental issues have become a matter of survival. In this sense, e-waste management is among the major problems since it may be a way of mitigating mineral depletion. In this context, the literature lacks e-waste supply chain studies that systematically map supply chain challenges and risks concerning material recovery.

Given this context, the authors' paper conducted a systematic literature review (SLR) to build a framework to identify the constructs of e-waste supply chain risk management.

The paper revealed the theoretical relationship between important variables to achieve e-waste supply chain risk management via a circular economy (CE) framework. These variables include reverse logistics (RL), closed-loop supply chains (CLSC), supply chain risk management, supply chain resilience and smart cities.

The literature contributions of this paper are as follows: (1) a complete list of the risks of the e-waste supply chains, (2) the techniques being used to identify, assess and mitigate e-waste supply chain risks and (3) the constructs that form the theoretical framework of e-waste supply chain risk management. In addition, the authors' results address important literature gaps identified by researchers and serve as a guide to implementation.

This study examines conditions under which taxes and subsidies designed to mitigate corporate environmental impact positively influence corporate pro-environmental behavior (CPEB) adoption, considering unique dynamics within different industries.

A systematic literature review was conducted on 171 articles. Articles were coded using an inductive grid for comprehensive examination.

Taxes generally positively influence CPEB adoption, but reduced positive or even negative effects can arise. Subsidies, while often facilitating the achievement of environmental goals, variously impact CPEB. Explanations for variations include the level of taxation or subsidy, economic agent affected, subsidy source, nature of subsidy, factors external to tax or subsidy characteristics and conflicting environmental objectives. We suggest research avenues for each aspect, to enhance literature on the influence of tax policies on promoting CPEB.

Beyond general tax-policy considerations, we provide policymakers with recommendations for tax policies designed to promote CPEB.

We examine the distinctive effects of taxes and subsidies on CPEB adoption within diverse industries ((re)manufacturing, agriculture, shipping, automobile, freight transport and power generation). We compare specific effects across industries, and advocate detailed exploration of recurrent elements identified, emphasizing their potential significance in designing taxes and subsidies that promote CPEB.

Ever since China’s implementation of the open-door policy in 1978, there has been a remarkable transformation in the nation’s economic landscape. Undesirably, amidst the rapid urban development, the importance of prioritising and nurturing rural development in China has not received unwavering attention. Nevertheless, the Chinese government has embarked on many ventures to bridge the disparities existing amidst urban and rural areas, revitalise the rural economy, and enhance overall productivity. This paper enunciates the role of the Chinese government in prospering rural areas by implementing policies that align with the Sustainable Developmental Goals (SDGs)- 1, 2 and 12.

This study employed a comprehensive methodology encompassing both primary and secondary research techniques to procure valuable insights and reviewed various Chinese government policies pertaining to rural revitalisation.

The study results demonstrate that throughout the policy implementation, China has contributed to the livelihoods of the rural communities and achieved SDG-1 (ending poverty) by 2030, ten years ahead of Agenda (2030). The country has also substantially improved its rural agricultural system by integrating modern science and technology and aiming to achieve SDG-2 (ensure food security) with the alignment of SDG-12 (sustainable production and consumption). The findings of this research indicate that despite some limitations in China’s rural revitalisation strategy, overall progress is seen in many aspects, particularly in achieving SDG-1, 2, and 12.

The Chinese government has made significant efforts to promote ecological, social, and economic development in rural areas through various national initiatives such as the “New Countryside” and “Rural Revitalisation” strategies. These initiatives have successfully alleviated poverty, increased food production, and ensured sustainable production and consumption. The discoveries presented within this article possess immense value, as they provide profound insights for policymakers, rural planners, and researchers who are fervently searching for viable solutions to tackle the intricate interplay between rural development and sustainability. Therefore, this study has the potential to greatly benefit policymakers from various nations, as they can adopt China’s rural revitalisation model as a means to successfully achieve SDGs 1, 2, and 12.

This study found that despite numerous initiatives to improve rural landscapes, China’s rural revitalisation approach still poses concerns as local governments are likely to focus on increasing income capacity rather than concentrating on establishing environmental governance.

This study explores the configurations of management control systems (MCSs) while taking into account entrepreneurial cognition styles (ECSs) in small and medium enterprises (SMEs). The objective is to understand the impact of ECS on deployment and identify the various modes of MCS configurations employed by SMEs. The authors draw on and synthesise two theoretical perspectives relating to cognition and management control packages to understand the associations between ECS and MCS employed by SMEs in managing their business. This study was conducted using a quantitative approach that utilises a questionnaire survey to collect cross-sectional data from 150 SMEs. The authors uncovered three cognitive styles: knowing (e.g. preciseness), planning (e.g. organising), and creativity (e.g. innovativeness). Furthermore, five configurations of MCS utilised by SMEs were identified: customer focus, performance monitoring, administrative focus, strategic focus, and development focus. By combining both analyses, the authors discovered three constellations of significant association between ECS and MCS characterised by Cluster 1’s cohesive integration approach, Cluster 2’s revealing strategic approach, and Cluster 3’s multifaceted exploration. The study is significant because it uncovers the complex relationship between ECS and MCS configurations, highlighting their interdependence within the institutional context. Using a cognitive view, the authors explore how the cognitive styles of entrepreneurs facilitated imprinting institutional context into MCS configurations. These insights enable us to envisage that ECS is not mutually exclusive but forms a continuum that provides more plausible explanations that relax the direct universal relationship between MCS configurations and contextual factors.

This study examines how local governments and enterprises can implement ecological restoration of abandoned mines based on ecology-oriented development (EOD), which will be more beneficial to local environmental protection and economic development under the central government’s policy of outcome incentives or process subsidies.

We construct a dynamic differential game model to simulate the interactions between local governments and enterprises during the ecological restoration of abandoned mines from an EOD perspective.

The findings suggest that under the central government’s outcome incentive policy, cooperation between local governments and enterprises is an optimal strategy. Under the process subsidy policy, while neither cooperative nor non-cooperative models significantly affect the investment levels of local governments and enterprises, a cooperative approach ensures optimal investments from both without solely relying on the process subsidy. Additionally, incorporating altruistic preferences can lead to Pareto improvements in economic and environmental results under central government outcome incentives.

This research offers a policy foundation for governments to encourage the EOD model in the ecological restoration of abandoned mines. It provides theoretical support for achieving environmental sustainability and high-quality economic development, and is particularly significant for resource-depleted cities seeking to transform their development strategies.

Through a dynamic differential game model involving government agencies and enterprises to simulate decision-making in the ecological restoration of abandoned mines, incorporating altruistic preferences into this restoration process, and identifying optimal strategies and policies for ecological restoration.

Rapid innovation and developments in personal electronic technology have encouraged users to change users' devices more frequently than ever, which has resulted in creating a massive increase in the amount of electronic waste. The study focuses on identifying the barriers to closed-loop supply chain (CLSC) in the electronic industry.

A framework for analyzing the relationships among CLSC adoption barriers is designed. The authors adopted the decision-making trial and evaluation laboratory (DEMATEL) technique to determine the critical barriers of electronic CLSC from the opinion of experts in the field.

The outcome from the analysis suggests that cost barriers, financial barrier, process barriers and supplier-side barriers are the main causal factors that prevent the adoption and implementation of e-waste CLSC. The causal relationship indicates that financial barrier is the most influential factor, while phycological barrier is the most flexible barrier to the adoption of e-waste CLSC.

This study is restricted to CLSC adoption barriers in the electronic industry by evaluating 36 sub-barriers grouped into 8 main dimensions related to different members of the supply chain.

Closed-loop adoption barriers have been proposed to understand the crucial barriers to implementation of CLSC in the electronic industry. The cause-and-effect relationship indicates the critical factors to be improved to increase adoption of e-waste CLSC, helping managers and regulatory bodies to mitigate the problem areas.

This study contributes to the literature on CLSC by adopting a multi-criteria decision-making (MCDM) technique which captures the critical barriers of e-waste CLSC adoption in Indian scenario.

This paper aims to investigate the following issues: the mechanisms through which different types of top management team’s social capital influence the innovation quality of high-tech firms, and the moderating effect of organizational knowledge utilization on the relationship between top management team’s social capital and innovation quality in high-tech firms.

This study categorizes top management team’s social capital into political, business and academic dimensions, investigating their impact on innovation quality in high-tech firms. Furthermore, a research model is developed with organizational knowledge utilization as the moderating variable. Data from Chinese high-tech firms between 2010 and 2019 are collected as samples for analysis.

The innovation quality of high-tech firms shows an inverted U-shaped trend as the top management team’s political capital and business capital increase. The top management team’s academic capital has a significantly positive correlation with the innovation quality of high-tech firms. Moreover, organizational knowledge utilization plays a significant moderating role in the relationship between the top management team’s social capital and innovation quality in high-tech firms.

This study explores the relationship among different dimensions of top management team’s social capital, innovation quality and organizational knowledge utilization. It holds significant theoretical value in enriching and refining the interactions between top management team’s social capital, knowledge management theory and innovation management theory. In addition, it offers important practical implications for firms to rationally approach top management team’s social capital, emphasize top management team configuration management and establish a comprehensive and efficient organizational knowledge utilization mechanism.