作者机构：
[Gao, Hanxiao; Zhou, Ping; Zhou, P; Li, Hailing; Lan, Yong] Hunan Agr Univ, Business Sch, Changsha 410125, Peoples R China.;[Zhang, H; Zhang, Hua] Cent South Univ, Business Sch, Changsha 410083, Peoples R China.;[Zhang, Hua; Li, Hailing] Cent South Univ, Inst Met Resources Strategy, Changsha 410083, Peoples R China.
通讯机构：
[Zhou, P; Li, HL ] H;[Zhang, H ] C;Hunan Agr Univ, Business Sch, Changsha 410125, Peoples R China.;Cent South Univ, Business Sch, Changsha 410083, Peoples R China.
关键词：
Climate risk;Energy production and consumption;Quantile-based causality;Frequency-domain-based causality
摘要：
This study investigates the causal effects of three dimensions of climate risks—Climate Physical Risk (CPR), Climate Concern Index (CCI), and Climate Policy Uncertainty (CPU)—on global energy production and consumption across diverse market environments from January 2013 to October 2022. Employing the Causality-in-Quantile approach, it examines how climate risks impact energy markets' volatility. Additionally, Wavelet Analysis is employed to analyze the heterogeneous impacts of climate risks on energy production and consumption at different time scales. Key findings include: (1) Crude oil production is subject to climate risk under all market conditions, while renewable energy production is subject to climate risk only in stable markets. (2) CCI exerts broader and more significant impacts on energy production and consumption compared to CPR and CPU. (3) The frequency domain analysis reveals that climate risk affects crude oil production in the short term and coal production in the long term. This study enhances understanding of climate risk interactions with energy markets and provides empirical insights crucial for policy formulation and investment decisions in addressing climate change challenges, offering practical guidance for stakeholders.
This study investigates the causal effects of three dimensions of climate risks—Climate Physical Risk (CPR), Climate Concern Index (CCI), and Climate Policy Uncertainty (CPU)—on global energy production and consumption across diverse market environments from January 2013 to October 2022. Employing the Causality-in-Quantile approach, it examines how climate risks impact energy markets' volatility. Additionally, Wavelet Analysis is employed to analyze the heterogeneous impacts of climate risks on energy production and consumption at different time scales. Key findings include: (1) Crude oil production is subject to climate risk under all market conditions, while renewable energy production is subject to climate risk only in stable markets. (2) CCI exerts broader and more significant impacts on energy production and consumption compared to CPR and CPU. (3) The frequency domain analysis reveals that climate risk affects crude oil production in the short term and coal production in the long term. This study enhances understanding of climate risk interactions with energy markets and provides empirical insights crucial for policy formulation and investment decisions in addressing climate change challenges, offering practical guidance for stakeholders.
期刊：
Environment, Development and Sustainability,2025年27(4):9357-9377 ISSN：1387-585X
通讯作者：
Chen, JY
作者机构：
[Dong, Xuesong] Hunan Agr Univ, Sch Business, Changsha 410083, Peoples R China.;[Chen, Jinyu; Huang, Jianbai] Cent South Univ, Sch Business, Changsha 410083, Peoples R China.;[Chen, Jinyu; Dong, Xuesong; Huang, Jianbai] Cent South Univ, Inst Met Resources Strategy, Changsha 410083, Peoples R China.
通讯机构：
[Chen, JY ] C;Cent South Univ, Sch Business, Changsha 410083, Peoples R China.;Cent South Univ, Inst Met Resources Strategy, Changsha 410083, Peoples R China.
关键词：
Metal consumption;Input-output analysis;Structural path analysis;Structural decomposition analysis
摘要：
The dependence of economic development on the metal resource is one of the challenges for developing countries. Given the enormous pressure of resource shortage in China, exploring the flow of metals between sectors is critical to achieve the Sustainable Development Goals. Based on the Chinese environmentally extended input–output (CEEIO) database from 1997 to 2017, the structural decomposition analysis (SDA) and the structural path analysis (SPA) models were combined to analyze the main driving factors and key paths of metal consumption in China. The results show that from 1997 to 2017, China’s economic development and metal consumption presented states of weak decoupling and expansion coupling. Capital formation, consumption expansion, and export expansion were main drivers of metal consumption. Sectors such as metal smelting, construction, and other manufacturing products consumed a large amount of metal directly or provide intermediate products for other sectors. In the future, the upstream and downstream links of the industrial chain should be managed according to the key path, so as to optimize the structure of intermediate products and final demand and realize metal resources conservation from production to consumption.
摘要：
Examining the relationship between organic farming adoption (OFA) and subjective well-being (SW) is crucial for understanding farmers' adoption behavior regarding organic farming and the factors facilitating its dissemination. This paper utilizes a sample of 450 farmers from four counties in the Xiangxi Tujia and Miao Autonomous Prefecture of Hunan Province, China, to compare the SW of conventional and organic farmers. Based on the Millennium Ecosystem Assessment well-being framework, using the ordered probit model, we analyzed the mechanisms of OFA on the SW of organic farmers, including the subgroups of conversion farmers and certified farmers. The results indicated that organic farmers reported higher SW than conventional farmers. The positive effect of OFA on SW of organic farmers was not present in the conversion period but was statistically significant in the certification period. Farm profitability, health, environmental quality, and food safety were mediators of OFA on SW, although the mediating effects of health and food safety didn't apply to conversion farmers. Findings from this study provide information on how OFA affects SW, which can be useful for governments to develop supportive policies to attract conventional farmers and stabilize organic farmers to adopt organic farming.
关键词：
agricultural insurance;agricultural agglomeration;industrial integration;agricultural resilience;sustainable agricultural systems
摘要：
Agricultural insurance has achieved rapid development in China, but its role in enhancing agricultural resilience remains unclear. This article aims to fill this research gap by investigating the impact and mechanism of agricultural insurance on agricultural resilience from the perspectives of agricultural agglomeration and industrial integration. The empirical results demonstrate that agricultural insurance exerts a significant and positive influence on the resilience of agriculture, which remains valid even after accounting for endogenous factors through the application of two IV sets. Further mechanism analysis reveals that agricultural insurance primarily boosts agricultural resilience by encouraging horizontal agricultural agglomeration rather than vertical industrial integration. Nevertheless, the influence of agricultural insurance on agricultural resilience differs among regions. Specifically, its effect on agricultural resilience is markedly more pronounced in the eastern and central regions compared to the less-developed western regions. Moreover, its effect on the agricultural resilience in the main grain-producing areas is obviously stronger than that in the main grain-selling area and those with a balance between production and marketing.
摘要：
Integration with rural tourism is an important way to achieve the sustainable development of ecological farms. Existing literature on the integration of agriculture and tourism lacks discussion from the microscopic farm level, making it difficult to capture the complex mechanisms of the integration of ecological farms and rural tourism. This paper attempts to address this problem by exploring the driving factors of the integration of ecological farms and rural tourism. The research aim of this paper is to construct a theoretical framework for driving the integration of ecological farms and rural tourism. We first conducted research on farms in four ecological agriculture demonstration zones: Ziquejie in Loudi, Hunan Province; Heshi in Shilin, Yunnan Province; Rongjiang in Dali, Yunnan Province; and Youxiqiao Village in Hunan Province. We interviewed 64 stakeholders in ecotourism and used grounded theory methods to construct a model and propose hypotheses. On this basis, a measurement scale was designed, and data was collected from 1041 Chinese ecological farms (ecological farm operators) using a structured questionnaire. The partial least squares structural equation model (PLS-SEM) was used to model and analyze the data to test the constructed model. The study found that higher market demand, regional economic level, intrinsic development needs, intrinsic resource endowments, technical support, and resource integration can promote the integration of ecological farms and rural tourism. Market demand and intrinsic development needs constitute the generative force of agritourism integration, while resource integration and intrinsic resource endowments constitute the development force of agritourism integration, and technical support and the regional economic level constitute the supporting force of agritourism integration.
关键词：
livestock publicly listed company;green total factor productivity;dynamic QCA;configuration analysis
摘要：
Improving the green total factor productivity (GTFP) of publicly listed companies in the livestock sector is essential for achieving sustainable and high-quality development in China's agricultural industry. This study proposes an integrated analysis framework for the advancement of GTFP, focusing on internal resource allocation and external business environment configurations. Using panel data from 32 publicly listed companies in China's livestock sector covering the period 2016 to 2021, we apply the dynamic qualitative comparative analysis (QCA) and necessary condition analysis (NCA) methodologies to explore the configuration pathways for multiple factors that influence GTFP, aiming to identify the mechanisms that drive these pathways in publicly listed livestock companies. The findings reveal that individual antecedent conditions are not essential for achieving high green total factor productivity (GTFP) in firms. Rather, internal and external factors jointly facilitate GTFP enhancement, resulting in three distinct configurational pathways that share the equivalence of "diverse configuration pathways leading to the same objective". Over time, the consistency level of each configuration pathway fluctuates above 0.94, demonstrating their stability over the study period. In terms of individual companies, the explanatory power of each configuration remains uniform across enterprises, exhibiting no significant differences. This study expands the scope of GTFP-related research and advances the application of the dynamic QCA method. It also provides enlightenment for policymakers to refine sectoral regulations and for companies seeking strategies to improve GTFP.
摘要：
Using a novel Chinese gambler conviction database to proxy the local gambling preference, we examine the impact of gambling preference on the disclosure of key audit matters (KAMs). Our findings suggest that the number of KAMs is significantly greater for firms in cities with a strong gambling preference than for firms in cities with a weak gambling preference. Our results are consistent with the view that firms located in areas with a sin culture may improve the quality of their financial reports to overcome their stigmatized image. Additional analysis suggests that large audit firms, shorter audit terms, and closer audit-client distance strengthen the positive relationship between the gambling preference and the disclosure of KAMs. Namely, audit firms with a good reputation, strong independence, and information advantages play a more significant role in “destigmatization”. Finally, we show that auditors charge more audit fee and exert more audit effort towards clients located in areas with a strong gambling preference. This finding suggests that attempts by firms that are affected by a sin culture to achieve “destigmatization” by improving the quality of their financial reports are also costly.
作者机构：
Modern Post College, Hunan Post and Telecommunication College, Changsha 410015, China;College of Business, Hunan Agricultural University, Changsha 410128, China;Author to whom correspondence should be addressed.;[Jin Xu] College of Economics, Hunan Agricultural University, Changsha 410128, China;[Ming Mo] College of Business, Hunan Agricultural University, Changsha 410128, China<&wdkj&>Author to whom correspondence should be addressed.
通讯机构：
[Ming Mo] C;College of Business, Hunan Agricultural University, Changsha 410128, China<&wdkj&>Author to whom correspondence should be addressed.
关键词：
digital transformation;rural elderly services;smart senior care;evolutionary game;simulation analysis
摘要：
Amid accelerating population aging and the rapid evolution of digital technologies, the digital transformation of rural elderly care services has become a pivotal strategy for restructuring the rural elderly care system. This study identified the local government, rural elderly care service centers, and the elderly population as the principal stakeholders, and developed a tripartite evolutionary game-theory model to examine the dynamic strategic interactions among these actors under the influence of digital technologies. The model further investigated the evolutionary trajectories and equilibrium conditions of their behavioral strategies. Numerical simulations conducted via MATLAB were employed to validate and visualize the model outcomes. The findings revealed the following. (1) The evolutionary equilibrium of digital elderly care service development in rural areas is jointly determined by the strategic choices of the three parties, with its stability shaped by a complex interplay of cost structures, incentive mechanisms, and utility outcomes. (2) Cost factors exhibit heterogeneous effects across stakeholders. Specifically, excessive regulatory costs diminish the performance incentives of local governments, digital infrastructure and operational expenditures influence service centers’ capacity for precision-oriented service delivery, and the participation of the elderly is constrained by affordability thresholds. (3) Local government behavior demonstrates a pronounced sensitivity to incentives. In particular, rewards and social reputation conferred by higher-level governmental bodies exert a significantly stronger influence than punitive measures. (4) Government subsidies for digital transformation enhance cross-stakeholder synergy through dual transmission channels. Nonetheless, excessive subsidies may escalate fiscal risk, while moderately calibrated penalty mechanisms effectively curb moral hazard within service centers. This study advances theoretical understanding of multi-stakeholder coordination in the context of digitally enabled rural elderly care and provides actionable insights for policymakers aiming to formulate interest-aligned strategies and construct resilient, intelligent governance systems for elderly care.
期刊：
Technological Forecasting and Social Change,2025年217:124169 ISSN：0040-1625
通讯作者：
Yi, CQ
作者机构：
[Yang, Lulu; Yang, Yimin; Dong, Xuesong; Li, Hailing; Yi, Chaoqun] Hunan Agr Univ, Business Sch, Changsha 410128, Hunan, Peoples R China.;[Wang, Zilong] Chinese Acad Social Sci, Inst Ind Econ, Beijing 100006, Peoples R China.
通讯机构：
[Yi, CQ ] H;Hunan Agr Univ, Business Sch, Changsha 410128, Hunan, Peoples R China.
关键词：
Green supply chain;Artificial intelligence (AI);Technology adoption;Social welfare
摘要：
This paper investigates the retailer’s artificial intelligence (AI) adoption strategies in the green supply chain involving a manufacturer and a retailer. We demonstrate that the decision to introduce AI is influenced by the retailer’s estimation of the consumers’ green preference (CGP) without AI as well as the unit adoption cost of AI. Specifically, irrespective of whether the retailer underestimates or overestimates the CGP without AI, as the estimation bias increases, the retailer becomes more inclined to adopt AI; however, an increase in the unit adoption cost will discourage adoption. Furthermore, we find that if the retailer underestimates the CGP without AI, adopting AI may negatively impact the profits of both the manufacturer and the supply chain, as well as the greenness level, while simultaneously enhancing social welfare. Conversely, if the CGP is overestimated, adopting AI can improve the manufacturer’s profit and the supply chain’s profit but decrease the greenness level and potentially harm social welfare. We extend the model by considering the prediction accuracy of AI, demonstrating that as the prediction accuracy increases, the retailer who underestimates the CGP without AI becomes more inclined to adopt AI; however, this may not hold under certain conditions if the CGP is overestimated.
This paper investigates the retailer’s artificial intelligence (AI) adoption strategies in the green supply chain involving a manufacturer and a retailer. We demonstrate that the decision to introduce AI is influenced by the retailer’s estimation of the consumers’ green preference (CGP) without AI as well as the unit adoption cost of AI. Specifically, irrespective of whether the retailer underestimates or overestimates the CGP without AI, as the estimation bias increases, the retailer becomes more inclined to adopt AI; however, an increase in the unit adoption cost will discourage adoption. Furthermore, we find that if the retailer underestimates the CGP without AI, adopting AI may negatively impact the profits of both the manufacturer and the supply chain, as well as the greenness level, while simultaneously enhancing social welfare. Conversely, if the CGP is overestimated, adopting AI can improve the manufacturer’s profit and the supply chain’s profit but decrease the greenness level and potentially harm social welfare. We extend the model by considering the prediction accuracy of AI, demonstrating that as the prediction accuracy increases, the retailer who underestimates the CGP without AI becomes more inclined to adopt AI; however, this may not hold under certain conditions if the CGP is overestimated.
作者机构：
[Ming Mo; Lidanting Zeng] School of Business, Hunan Agricultural University, Changsha, 410128, China
通讯机构：
[Ming Mo] S;School of Business, Hunan Agricultural University ,Changsha 410128, China
关键词：
Innovation efficiency;Malmquist model;Seed companies;Two stage DEA model;fsQCA
摘要：
Seed industry plays a pivotal role in the advancement of national agricultural growth, with seed companies serving as the primary drivers of seed production. The existence of seed companies with the ability to integrate innovation and adapt to market demand plays a crucial role in a nation's capacity to ensure food security over time. This study utilizes micro-data from listed seed companies in China spanning the years 2019 to 2023 to conduct a comprehensive analysis of enterprise innovation efficiency. The research aims to identify strategies for enhancing innovation efficiency and ultimately fostering development within these seed companies. The findings indicate that: (1) The general level of innovation efficiency among listed seed companies in China exhibits significant potential for enhancement, with technology research and development stage demonstrating higher efficiency levels compared to stage of achievement transformation; (2) The enhancement of innovation efficiency in listed seed companies does not rely solely on any individual factor, but rather necessitates the combined influence of two or more antecedent variables; (3) Listed seed companies in China can enhance their innovation capability through five key approaches: employee-centric, talent and management-focused, talent and scale diversity-driven, talent and government collaboration, and talent and diversity enhancement strategies. The findings presented in this paper are expected to enhance the innovation efficiency of seed companies and offer both policy recommendations and practical guidance for fostering seed industry.
Seed industry plays a pivotal role in the advancement of national agricultural growth, with seed companies serving as the primary drivers of seed production. The existence of seed companies with the ability to integrate innovation and adapt to market demand plays a crucial role in a nation's capacity to ensure food security over time. This study utilizes micro-data from listed seed companies in China spanning the years 2019 to 2023 to conduct a comprehensive analysis of enterprise innovation efficiency. The research aims to identify strategies for enhancing innovation efficiency and ultimately fostering development within these seed companies. The findings indicate that: (1) The general level of innovation efficiency among listed seed companies in China exhibits significant potential for enhancement, with technology research and development stage demonstrating higher efficiency levels compared to stage of achievement transformation; (2) The enhancement of innovation efficiency in listed seed companies does not rely solely on any individual factor, but rather necessitates the combined influence of two or more antecedent variables; (3) Listed seed companies in China can enhance their innovation capability through five key approaches: employee-centric, talent and management-focused, talent and scale diversity-driven, talent and government collaboration, and talent and diversity enhancement strategies. The findings presented in this paper are expected to enhance the innovation efficiency of seed companies and offer both policy recommendations and practical guidance for fostering seed industry.
作者机构：
[Liu, Shun Jia] Hunan Agr Univ, Sch Business, Changsha, Peoples R China.;[Zhu, Xiaoqian; Li, Jianping] Univ Chinese Acad Sci, Sch Econ & Management, Beijing, Peoples R China.;[Zhu, Xiaoqian; Li, Jianping] UCAS, MOE Social Sci Lab Digital Econ Forecasts & Policy, Beijing, Peoples R China.;[Wu, Dengsheng] Chinese Acad Sci, Inst Sci & Dev, Beijing, Peoples R China.;[Xu, Xin Long] Hunan Normal Univ, Coll Tourism, Changsha, Peoples R China.
通讯机构：
[Xin Long Xu] C;College of Tourism, Hunan Normal University, Changsha, China<&wdkj&>Institute of Interdisciplinary Studies, Hunan Normal University, Changsha, China
摘要：
<jats:title>Abstract</jats:title><jats:p>Existing studies on the environmental Kuznets curve (EKC) neglect the inverse effect of pollution transfer from environmental regulation interactions on pollution reduction from a risk analysis perspective. Based on the regional differentiated attitudes on the environmental regulation reached in risk communication by the risk awareness biases of multiple interest groups, this article clarifies the causality between risk communication and risk transfer based on multistakeholder engagement processes; furthermore, the article incorporates the simultaneous action of the technological innovation effect and pollution risk transfer effect to construct a spatial environmental hyperbolic model with a bidirectional correlation between pollution emissions and economic growth in different regions. To verify our model, we select the pollution from agricultural watersheds in China as a sample to examine the two inverse effects. The results demonstrate that (1) agricultural watershed pollution and economic growth show an inverted U‐shaped relation and a U‐shaped relation in the local region and adjacent regions, respectively; (2) the pollution reduction assessment of the classical EKC model can be largely attributed to pollution risk transfer behavior; and (3) the turning point of the U‐shaped curve appears earlier than that of the inverted U‐shaped curve in the spatial hyperbola model. The findings suggest that stakeholders should consider the risk awareness bias caused by the imbalance of regional economic development and the scenarios that provide a “haven” for pollution risk transfer. Moreover, our study expands the theoretical connotation of the classical EKC hypothesis and is more suitable for pollution reduction scenarios in developing countries.</jats:p>
