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This study aims to examine the relationship between environmental, social and governance (ESG) disclosure, firm risk and stock market returns within the Chinese energy sector. Using a variety of econometric techniques, the study seeks to uncover the impact of ESG disclosure on risk mitigation and its influence on stock market performance.

Benchmark regression models were used to explore the associations between ESG disclosure, firm risk and stock returns. To address potential endogeneity, a generalised method of moments estimator is used. Quantile regression was used for robustness analysis.

The study reveals a negative relationship between ESG disclosure and firm risk, indicating that companies with greater ESG disclosure tend to experience reduced risk exposure. In addition, a positive association is observed between ESG disclosure and stock market returns, suggesting that companies with more comprehensive ESG disclosure practices tend to perform better in the stock market.

This study implies that investors appreciate sustainable investment and incorporate ESG practices and disclosure in decision-making. Policymakers can promote transparent ESG reporting through regulatory frameworks, fostering sustainable practices in the energy sector.

Despite the mounting concerns over carbon dioxide emissions and the energy industry’s environmental footprint, this study pioneers a comprehensive analysis of ESG disclosure within this critical sector. Delving into the relationship of ESG practices, firm risk and market returns, this research uniquely examines both risk mitigation and return enhancement, shedding new light on sustainable strategies in the energy domain.

This paper examines the mediation role of green innovation in the relationship between corporate social responsibility and environmental performance of manufacturing firms in Ghana.

The paper chose African emerging markets and surveyed managers from manufacturing firms. With 301 questionnaires qualified for this study’s final analyses, the authors adopt the multiple regression with mediation models to estimates the nexus among study variables.

Results evidence that both corporate social responsibility and green innovation has a positive and significant impact on environmental performance. Interestingly, the authors find that corporate social responsibility significantly improves environmental performance through green innovation indicating that firms could essentially build their dynamic resource and innovation capabilities in sustainability leading to enhanced environmental performance.

This paper develops a dynamic resource-based view of firm environmental performance illustrating how firms use resources to build strategic capabilities for competitive advantage, which leads to improved environmental performance. The paper highlights the mediation role of green innovation on corporate social responsibility and environmental performance relationships.

This study's results provide significant insights to owners and managers of manufacturing companies to integrate corporate social responsibility and green innovation to ensure environmental performance and sustainability. Furthermore, policy makers should encourage green innovation when design sustainable development systems in the manufacturing industry.

The paper provides a valuable model showing how green innovation mediates corporate social responsibility to improve environmental performance and build competitive advantages considering both small, medium, and large manufacturing enterprises in emerging countries.

Innovation in fintech presents great opportunities and huge challenges for accounting practices around the world. This paper aims to examine the impact of Fintech on accounting practices including financial reporting, performance management, budgeting, auditing, risk and fraud management. Fintech is proxied by the adoption of AI and big data analysis in accounting practices.

We chose African countries as our focus countries and surveyed chartered and qualified accountants in both Ghana and Nigeria. With 201 questionnaires qualified for our final analyses, we adopted the structural equation modelling to analyse the impact of Fintech on accounting practices.

The empirical results show that the impact of AI and big data on accounting practices is positive and significant, indicating that fintech could potentially mitigate the agency problem in accounting practices and lead to better accounting practices. Interestingly, we find that, in general, the impact of AI is larger than that of big data.

Our results provide significant insights to regulators, policymakers and managers about the future development of adopting fintech in the regulation and governance framework at both macro and micro levels for accounting practice.

Banks and corporate customers have realized that bank-corporate relationship is important but little is known about why and how banks establish and exploit relationships. No comprehensive theory has explained relationship banking and in order to get a better understanding the purpose of this paper is to investigate why and how banks and companies communicate in order to create value.

This study adopts a qualitative methodology and a grounded theory approach was adopted. In total, 34 in-depth interviews were conducted with banks and 15 with corporate managers. Grounded theory models are developed based on interview data.

It was found that the nature of bank-corporate relationship is long term. The relationship is based on trust-based personal communications between banks and corporate customers. Macro conditions including the advances in technology, financial regulation and business globalization were considered when the case banks adopted relationship banking. Some intervening conditions including customer information and knowledge, customer needs and customer confidence also influence the development of relationship banking. The interviewees perceived that the case banks gained benefits including better customer retention economy, risk management efficiency and greater effectiveness in maintaining sustainable profitability. The corporate customers gained benefits including fund availability, product availability, service quality, help in-time and business platform.

This study derives concepts and categories from primary data and identifies relationships among these theoretical elements. This investigation provides a comprehensive picture of relationship banking and supplies some theoretical and practical implications. Moreover, a value creation and allocation theory of the bank is developed.

This paper aims to automatically plan sequence for complex assembly products and improve assembly efficiency.

An assembly sequence planning system for workpieces (ASPW) based on deep reinforcement learning is proposed in this paper. However, there exist enormous challenges for using DRL to this problem due to the sparse reward and the lack of training environment. In this paper, a novel ASPW-DQN algorithm is proposed and a training platform is built to overcome these challenges.

The system can get a good decision-making result and a generalized model suitable for other assembly problems. The experiments conducted in Gazebo show good results and great potential of this approach.

The proposed ASPW-DQN unites the curriculum learning and parameter transfer, which can avoid the explosive growth of assembly relations and improve system efficiency. It is combined with realistic physics simulation engine Gazebo to provide required training environment. Additionally with the effect of deep neural networks, the result can be easily applied to other similar tasks.

Hand, foot and mouth disease (HFMD) is a common infectious disease in infants and children. HFMD has caused millions of cases and a large epidemic worldwide. A number of studies have shown that the incidence of HFMD is closely related to various factors such as meteorological factors, environmental air pollution factors and socio-economic factors. However, there are few studies that systematically consider the impact of various factors on the incidence of HFMD. The paper aims to discuss these issues.

This study used grey correlation analysis and principal component analysis (PCA) method to systematically analyse the impact of meteorological factors, health resource factors, socio-economic factors and environmental air pollution factors on the incidence of HFMD in Shenzhen.

The incidence of HFMD in Shenzhen was affected by multiple factors. Grey correlation analysis found eight influencing factors which are as follows: volume of industrial waste gas emission; the days of air quality equal to or above grade; the volume of industrial nitrogen oxide emission; precipitation; the mean air temperature; the gross domestic product; the expenditure for medical and health care; and the gross domestic product per capita. PCA found that the gross domestic product, the volume of industrial soot emission, the relative humidity, and the days of air quality equal to or above grade have a higher load value.

This study is the one of the first studies that apply the grey correlation analysis to analyse the influencing factors of HFMD in the English literature, which to some extent fills up the blank in this field.

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.

Due to the non-linear nature of the hysteresis behavior, the accurate identification of the parameters of the Bouc–Wen hysteresis model is still a challenging problem. The purpose of this paper is to explore the potential of a heuristic improved whale optimization algorithm (IWOA) to accurately identify the model parameters, which has never been applied to the field of piezoelectric hysteresis identification.

Based on the analysis of the Bouc–Wen model structure and WOA optimization process, an approach that can fully exploit the potential of WOA is proposed. In this work, the position updating formula is improved by introducing non-linear weights, and the convergence factor formula is modified. And thus, the iteration speed, accuracy and stability of the classical WOA can be improved.

The experimental results show that the model output is in good agreement with the response of the real piezoelectric platform. Compared with the standard WOA and particle swarm optimization algorithms, the search performance of the proposed IWOA is better than those two competitors in terms of convergence speed and identification accuracy.

An IWOA is proposed according to the properties of the Bouc–Wen model and piezoelectric hysteresis. It has been approved that the algorithm has a good prospect in the identification of piezoelectric hysteresis systems. Furthermore, this method is easy to implement and is a good candidate algorithm to identify Bouc–Wen model parameters.

As an essential part of mainstream Western development economics, the trickle-down theory originates from the behavioral choices and iterations of thought on conflicts of interest in the evolution of remuneration structure in Western countries. The fundamental flaw of the logic of this theory is that it conceals the inherent implication of social systems and the essential characteristics of social structures.

This paper examines the relationships among economic growth, income distribution and poverty from the perspective of social relations of production – the nature of production relations determines the nature of distribution relations and further determines the essence of trickle-down development, and ownership is the core mechanism for realizing the trickle-down effect.

The stagnation or smoothness of the trickle-down effect in different economies is essentially subject to the logic of “development for whom”, which is determined by ownership relationship.

To be more specific, “development for capitalists” and “development for the people” indicate two distinctly different economic growth paths. The former starts with private ownership and follows a bottom-up negative trickle-down path that inevitably leads to polarization, while the latter starts with public ownership and follows a top-down positive trickle-down path that will lead to common prosperity in the end.

The purpose of this paper is to solve the azimuth sensitivity of a high-resolution range profile (HRRP), which is one of the biggest obstacles faced by a radar automatic target recognition (RATR) system.

Aimed at addressing the shortcomings of the equal angular-sector segmentation based on the scatterer model, an adaptive angular-sector segmentation is proposed on the basis of grey incidence analysis (GIA).

The main conclusions reached are as follows. First, the adaptive angular-sector segmentation in terms of GIA is suitable for RATR based on the HRRP; and, second, the adaptive angular-sector segmentation based on the type-B degree of grey incidence model is better than the Deng-Si degree of grey incidence model and the degree of grey slope incidence model.

The outcome obtained in this paper can be selected for the RATR application.

This paper has been built on the basis of previous research achievements, and a new RATR method of adaptive angular-sector segmentation is presented based on the GIA.