关键词：
substantive CSR motive attribution;symbolic CSR motive attribution;in-role green behavior;extra-role green behavior;green intrinsic motivation
摘要：
Employee green behavior plays an important role in the realization of corporate social responsibility (CSR) goals, and the employee motive attribution of CSR can affect employee green behavior. Therefore, it is important to understand how CSR motive attribution affects their green behavior. However, existing studies rarely establish a direct link between CSR motive attribution and green behavior. Based on the attribution theory, we establish a framework to explore the impact of CSR motive attributions on employees’ green behaviors. To examine our theoretical model and research hypotheses, we conducted an experimental study (Study 1) and a multi-wave survey study (Study 2). The combined results show that (substantive and symbolic) CSR motive attributions positively influence in-role green behavior; however, for extra-role green behavior, substantive CSR motive attribution positively influences it, while symbolic CSR motive attribution negatively influences it. Green intrinsic motivation positively moderates the relationship between CSR motive attributions and in-role green behavior and positively moderates the relationship between substantive CSR motive attribution and extra-role green behavior but negatively moderates the relationship between symbolic CSR motive attribution and extra-role green behavior. This research contributes to the literature related to micro-CSR and provides explanations for the favorable and unfavorable environmental results brought on by substantive and symbolic CSR, respectively.
作者机构：
[Zhaoyu Liu; Caidie Yi; Ziyi Zhu; Zengyang He; Yiye Wu; Chengjuan Yang] School of Management, Wuhan Polytechnic University, Wuhan, Hubei, China
会议名称：
2025 IEEE International Conference on Electronics, Energy Systems and Power Engineering (EESPE)
会议时间：
17 March 2025
会议地点：
Shenyang, China
会议论文集名称：
2025 IEEE International Conference on Electronics, Energy Systems and Power Engineering (EESPE)
关键词：
Fiscal prediction;Adaptive-Lasso regression;Grey neural network;Combined prediction model
摘要：
The widespread application of data mining technology and the rapid development of machine learning techniques provide a simple and efficient method for predicting local fiscal revenue. The current main model for fiscal revenue prediction involves using data mining techniques for reasonable selection and analysis of data, followed by training neural networks to construct prediction models. This paper proposes a fiscal revenue prediction model based on data mining and grey neural networks, selecting 12 influencing factors that affect fiscal revenue. The Adaptive-Lasso method is used for variable coefficient estimation, and least angle regression is employed to solve the problem, eliminating some variables with lesser impact. The remaining variables are then subjected to GM (1,1) grey prediction to obtain their predicted values, and the prediction accuracy is evaluated with a grading system. Finally, historical data is used to train a BP neural network, constructing a grey neural network combined prediction model, where the grey predicted values are substituted into the trained grey neural network to yield future fiscal revenue predictions. Experimental results indicate that due to the high fault tolerance and adaptability of neural networks, the predicted values fit well with the actual values, with the two curves nearly overlapping. The grey neural network prediction results constructed in this paper are highly reliable.
作者机构：
[Li, Jiwen] Wuhan Univ Sci & Technol, Chinese Natl Community Res Inst, Wuhan 430065, Peoples R China.;[Li, Jiwen] Wuhan Univ Sci & Technol, Sch Law & Econ, Wuhan 430065, Peoples R China.;[Gan, Chang; Gan, C] Wuhan Polytech Univ, Sch Management, Wuhan 430048, Peoples R China.
通讯机构：
[Gan, C ] W;Wuhan Polytech Univ, Sch Management, Wuhan 430048, Peoples R China.
关键词：
urban-rural income inequality;carbon emission performance;spatial Durbin model;spillover effect
摘要：
Income inequality and carbon emission are two critical challenges that need to be solved to achieve SDGs. Unfortunately, few studies have explored the effect of urban–rural income inequality (URII) on carbon emission performance (CEP) from a holistic view that integrates local and adjacent hierarchies. Utilizing provincial data spanning from 2005 to 2021 in China, this paper examines the mechanism and influence of URII on CEP by using the spatial Durbin model and a mediating effect model. The results indicate that URII and CEP display significant spatial agglomeration characteristics. URII can inhibit the CEP, which also exerts a negative spatial spillover effect on CEP. URII can not only directly affect CEP but also indirectly influence it by increasing energy consumption and widening the urban–rural consumption gap. The negative effect of URII on CEP demonstrates regional variability, with a particularly prominent effect observed in the eastern region.
期刊：
Energy Economics,2025年144:108307 ISSN：0140-9883
通讯作者：
Han, XY
作者机构：
[Jiang, Dongming] Guangzhou Coll Technol & Business, Coll Accounting, Guangzhou, Peoples R China.;[Jia, Fang] Wuhan Polytech Univ, Sch Management, Wuhan 430023, Peoples R China.;[Han, Xiaoyu] Wuhan Text Univ, Sch Accountancy, Wuhan 430020, Peoples R China.
通讯机构：
[Han, XY ] W;Wuhan Text Univ, Sch Accountancy, Wuhan 430020, Peoples R China.
关键词：
Return and volatility spillovers;Energy;Electricity;Cryptocurrency;QVAR
摘要：
Over the past decade, the cryptocurrency market has experienced significant growth. However, the dynamics of risk spillover between various types of cryptocurrencies and the electricity market, as well as energy markets, under different quantile conditions remain ambiguous. To address this gap, this paper utilizes the Quantile Vector Autoregression (QVAR) model to examine the returns and volatility spillovers among energy (fossil and clean energy), the electricity market, and cryptocurrencies (clean and dirty cryptocurrency) markets across varying quantile conditions. Additionally, this paper investigates the determinants of spillover effects among these markets. The findings reveal that moderate spillover effects exist among these markets under conditional mean and median quantiles, while such effects are intensified in extreme quantile conditions. Moreover, oil, clean cryptocurrency, wind energy, and geothermal energy typically act as recipients of spillover effects, whereas natural gas, dirty cryptocurrency, bioenergy, solar energy, and, fuel cells generally function as transmitters of spillover effects. The electricity market serves as a recipient under mean and median quantile conditions but acts as a transmitter under extreme conditions. Furthermore, EPU, CFGI, TERM, and COVID-19 significantly enhance spillover effects among these three markets. These insights offer valuable implications for investors and policymakers.
Over the past decade, the cryptocurrency market has experienced significant growth. However, the dynamics of risk spillover between various types of cryptocurrencies and the electricity market, as well as energy markets, under different quantile conditions remain ambiguous. To address this gap, this paper utilizes the Quantile Vector Autoregression (QVAR) model to examine the returns and volatility spillovers among energy (fossil and clean energy), the electricity market, and cryptocurrencies (clean and dirty cryptocurrency) markets across varying quantile conditions. Additionally, this paper investigates the determinants of spillover effects among these markets. The findings reveal that moderate spillover effects exist among these markets under conditional mean and median quantiles, while such effects are intensified in extreme quantile conditions. Moreover, oil, clean cryptocurrency, wind energy, and geothermal energy typically act as recipients of spillover effects, whereas natural gas, dirty cryptocurrency, bioenergy, solar energy, and, fuel cells generally function as transmitters of spillover effects. The electricity market serves as a recipient under mean and median quantile conditions but acts as a transmitter under extreme conditions. Furthermore, EPU, CFGI, TERM, and COVID-19 significantly enhance spillover effects among these three markets. These insights offer valuable implications for investors and policymakers.
期刊：
Journal of Environmental Management,2025年385:125664 ISSN：0301-4797
通讯作者：
Gan, Chang;Wang, Kai;Voda, Mihai
作者机构：
[Gan, Chang] School of Management, Wuhan Polytechnic University, Wuhan, China. Electronic address: gzrycxwl@whpu.edu.cn;[Wang, Kai] College of Tourism, Hunan Normal University, Changsha, China. Electronic address: kingviry@163.com;[Voda, Mihai] Faculty of Geography, Dimitrie Cantemir University, Targu Mures, Romania. Electronic address: mihaivoda@cantemir.ro
通讯机构：
[Wang, Kai] C;[Voda, Mihai] F;[Gan, Chang] S;School of Management, Wuhan Polytechnic University, Wuhan, China. Electronic address:;College of Tourism, Hunan Normal University, Changsha, China. Electronic address:
关键词：
Digital economy;Green finance;Low-carbon transition;Moderating effect;Tourism development
摘要：
In the context of global efforts to curb CO 2 emissions, identifying new drivers of low-carbon transition has become a pressing task for countries worldwide. However, whether tourism development acts as a catalyst for this transition remains unclear. To address this gap, our study adopted carbon emission efficiency as an indicator to better capture the dynamics of the low-carbon transition. Employing a dynamic SYS-GMM model, this study explored the potential inverted U-shaped relationship between tourism development and low-carbon transition. Moreover, recognizing the growing influence of the digital economy and green finance in fostering sustainable tourism, this study further examined their moderating effects. The results indicate that tourism development initially promotes low-carbon transition, whereas its effect diminishes beyond a certain threshold, following an inverted U-shaped pattern. While both digital economy and green finance amplify the positive impact of tourism development, the digital economy also exacerbates negative externalities. In contrast, green finance plays a mitigating role.
In the context of global efforts to curb CO 2 emissions, identifying new drivers of low-carbon transition has become a pressing task for countries worldwide. However, whether tourism development acts as a catalyst for this transition remains unclear. To address this gap, our study adopted carbon emission efficiency as an indicator to better capture the dynamics of the low-carbon transition. Employing a dynamic SYS-GMM model, this study explored the potential inverted U-shaped relationship between tourism development and low-carbon transition. Moreover, recognizing the growing influence of the digital economy and green finance in fostering sustainable tourism, this study further examined their moderating effects. The results indicate that tourism development initially promotes low-carbon transition, whereas its effect diminishes beyond a certain threshold, following an inverted U-shaped pattern. While both digital economy and green finance amplify the positive impact of tourism development, the digital economy also exacerbates negative externalities. In contrast, green finance plays a mitigating role.
期刊：
International Transactions in Operational Research,2025年 ISSN：0969-6016
通讯作者：
Yuan Jiang
作者机构：
College of Economics, Shenzhen University, Shenzhen, 518000 China;Corresponding author.;["Tan, Yong; Zhou, Ziwei] School of Management, Wuhan Polytechnic University, Wuhan, 430048 China;[Guan, Xu] School of Management, Huazhong University of Science and Technology, Wuhan, 430074 China;[Jiang, Yuan"] College of Economics, Shenzhen University, Shenzhen, 518000 China<&wdkj&>Corresponding author.
摘要：
This paper investigates the firms' equilibrium disclosure strategies in an agricultural supply chain, wherein the farmer sells agricultural products through an intermediary platform to the end market. Both the farmer and the platform privately observe the product quality information and independently determine whether to disclose this information to the consumers. We examine two disclosure formats, farmer disclosure format and platform disclosure format, depending on who is responsible for quality disclosure. Our analysis reveals that the commission rate exerts a nontrivial impact on the farmer's and platform's disclosure incentive and their profits. The farmer has the incentive to disclose the quality information only when the commission rate is low, while the platform chooses to disclose the quality information only when the commission rate is high. Additionally, under farmer (platform) disclosure format, the platform's (farmer's) profit exhibits nonmonotonic pattern with respect to the commission rate when the disclosure cost is low. Moreover, we show that both the farmer and the platform may opt to take the disclosure responsibility by itself, and in certain conditions, their preferences for two disclosure formats could be aligned, resulting in a “win-win” situation for both parties.
摘要：
Payment digitalization has reformed consumer preferences and significantly influenced economic forms. Using the 2017 and 2019 China Household Finance Survey data, this study examines the impact of payment digitalization on tourism consumer spending and explores the moderating effect of transportation infrastructure improvement. Findings reveal that payment digitalization can encourage tourism consumption expenditure. Furthermore, improvements in transportation infrastructure can boost the promotion effect of payment digitalization on tourism consumption expenditure.
Payment digitalization has reformed consumer preferences and significantly influenced economic forms. Using the 2017 and 2019 China Household Finance Survey data, this study examines the impact of payment digitalization on tourism consumer spending and explores the moderating effect of transportation infrastructure improvement. Findings reveal that payment digitalization can encourage tourism consumption expenditure. Furthermore, improvements in transportation infrastructure can boost the promotion effect of payment digitalization on tourism consumption expenditure.
作者机构：
[Gao, Shiya] Wuhan Polytech Univ, Sch Management, Wuhan, Peoples R China.;[Guan, Xin] Guangzhou Xinhua Univ, Dongguan, Peoples R China.;[Cao, Xiaojing] London Metropolitan Univ, Business Adm, London, England.;[Bai, Zhili] Univ New South Wales, Sch Elect Engn & Telecommun, Sydney, Australia.;[Wang, Caimeng] Guangzhou Univ, Sch Management, Guangzhou, Peoples R China.
通讯机构：
[Yu, HY ] G;Guangzhou Yi Wu Vocat Training Sch, Guangzhou, Peoples R China.
摘要：
This study aims to explore the integration of the Faster R-CNN (Region-based Convolutional Neural Network) algorithm from deep learning into the MobileNet v2 architecture, within the context of enterprises aiming for carbon neutrality in their development process. The experiment develops a marine oil condition monitoring and classification model based on the fusion of MobileNet v2 and Faster R-CNN algorithms. This model utilizes the MobileNet v2 network to extract rich feature information from input images and combines the Faster R-CNN algorithm to rapidly and accurately generate candidate regions for oil condition monitoring, followed by detailed feature fusion and classification of these regions. The performance of the model is evaluated through experimental assessments. The results demonstrate that the average loss value of the proposed model is approximately 0.45. Moreover, the recognition accuracy of the model for oil condition on the training and testing sets reaches 90.51% and 93.08%, respectively, while the accuracy of other algorithms remains below 90%. Thus, the model constructed in this study exhibits excellent performance in terms of loss value and recognition accuracy, providing reliable technical support for offshore oil monitoring and contributing to the promotion of sustainable utilization and conservation of marine resources.
作者：
Tao Cui;Chao Wang;Yu Wei;Xiongping Yue*;Kun Zhao;...
期刊：
Mathematics,2025年:- ISSN：2227-7390
通讯作者：
Xiongping Yue
作者机构：
[Tao Cui; Yu Wei; Kun Zhao; Chen Liang] School of Logistics, Beijing Wuzi University, Beijing 101149, China;School of Management, Wuhan Polytechnic University, Wuhan 430024, China;Author to whom correspondence should be addressed.;[Chao Wang] College of Economics and Management, Beijing University of Technology, Beijing 100124, China;[Xiongping Yue] School of Management, Wuhan Polytechnic University, Wuhan 430024, China<&wdkj&>Author to whom correspondence should be addressed.
通讯机构：
[Xiongping Yue] S;School of Management, Wuhan Polytechnic University, Wuhan 430024, China<&wdkj&>Author to whom correspondence should be addressed.
摘要：
The efficiency of emergency response operations is critically dependent on the strategic storage and allocation of emergency supplies. Proper management of these resources reduces economic impacts and ensures prompt availability in crises. This study addresses the challenges and existing practices in emergency reserve warehousing, with a specific focus on a Fangshan District case study. It introduces optimized storage strategies and principles for storage location assignment, taking into account both planar and three-dimensional storage configurations. The study employs two pallet types to establish basic assumptions and formulates two models: one for standard pallets in three-dimensional storage and another for special pallets in planar storage, including scenarios for their combined usage. Utilizing an advanced non-dominated genetic algorithm (NSGA-II) with an elite strategy, the study conducts simulations and analyses of these models under various scenarios. The findings indicate that the application of the second scenario significantly improves storage location optimization in emergency reserve warehouses.
摘要：
This study aims to provide new evidence linking director tenure to corporate misconduct by analyzing the sample of publicly listed companies in China from 2009 to 2022. The findings reveal a significant positive correlation between director tenure and corporate misconduct, which is negatively moderated by director network position. Further analysis shows that both independent and non-independent directors' tenure increases the likelihood of corporate misconduct, while the centrality of independent and non-independent director networks negatively moderates these corresponding effects. Moreover, external audit quality plays a mediating role in the relationship between director tenure and corporate misconduct. This study elucidates the boundary conditions and mechanisms of corporate misconduct, supporting the management friendliness hypothesis. It offers practical implications for regulators and policymakers to strengthen board governance and audit oversight, thereby contributing to the research on the prevention of corporate misconduct. The limitations of the study include its geographical focus on the Chinese market, suggesting that future research should explore cross-national differences. These findings provide valuable insights for preventing corporate misconduct and promoting corporate sustainability.
摘要：
This study demonstrates that extreme temperatures disproportionately affect women’s employment in China’s manufacturing sector. Using matched data from county-level weather records and industrial enterprise surveys, we find that a one-percentage-point increase in extreme temperature exposure reduces female employment share by 4.75% points. Mechanism analysis reveals that this relationship is primarily driven by firms’ hiring decisions based on both perceived and actual gender differences in weather-related productivity. Our findings contribute to the literature by providing novel evidence on how indoor working conditions in manufacturing can perpetuate gender-based labour market disparities.
摘要：
The digital economy has reshaped the geography of tourism but its effect on regional tourism disparities remains unexplored. Based on provincial panel data in China from 2011 to 2022, this study explores the effect of the digital economy on regional disparities in tourism development. The results show that the digital economy regional disparities have a positive impact on the tourism development regional disparities, maintaining a positive influence throughout the 12th and 13th Five-Year Plans, but the coefficient decreases in different years. When analyzed regionally, narrowing digital economy regional disparities is conducive to narrowing the tourism development regional disparities between the eastern and central regions. This study is informative for balancing the tourism distribution pattern and reducing regional economic inequalities in the digital era.
作者机构：
[Gan, Chang] Wuhan Polytech Univ, Sch Management, Wuhan, Peoples R China.;[Voda, Mihai] Dimitrie Cantemir Univ, Fac Geog, Targu Mures, Romania.;[Wang, Kai] Hunan Normal Univ, Coll Tourism, Changsha, Peoples R China.
通讯机构：
[Wang, K ] H;Hunan Normal Univ, Coll Tourism, Changsha, Peoples R China.
关键词：
economic growth;inclusive growth;moderating effect;tourism development;urban–rural income gap
摘要：
Abstract Social fairness and economic recovery stimulation constitute crucial challenges in countries all around the world, and tourism development has enormous potential for balancing efficiency and fairness. Based on the panel data at city level in Yangtze River Delta Region, China, this study uncovered the role that tourism development plays in economic growth and urban–rural income gap by adopting the dynamic SYS‐GMM model. In addition, the moderating effect model was employed to concentrate on the moderating role of urbanization on the relationship between tourism development and economic growth as well as urban–rural income gap. The main conclusions are as follows. First, tourism development does not only promote economic growth, but it also narrows the urban–rural income gap. Second, when it comes to the dynamic effect generated by tourism development, the economic growth‐promotion effect is stronger than the urban–rural income gap‐inhibiting effect. Third, urbanization can enhance the impact of tourism development on economic growth and the reduction of urban–rural income gap.
