关键词：
Entrepreneurial networks;Causation;Effectuation;Business model innovation;Environmental dynamism;Resource orchestration
摘要：
PurposeAlthough it is acknowledged that entrepreneurial networks play a crucial role in fostering business model innovation (BMI) for start-ups, it is unclear how and when these networks affect BMI. This research developed a moderated mediation model to explore the impact of entrepreneurial networks on BMI in start-ups and examined the dual mediating effects of causation and effectuation, as well as the moderation of environmental dynamism.Design/methodology/approachThe proposed framework was tested by hierarchical regression analyses and bootstrapping using samples of 248 start-ups in China.FindingsThe results showed that entrepreneurial networks significantly positively impacted start-up BMI. Causation and effectuation played dual mediating roles between entrepreneurial networks and BMI. Furthermore, the entrepreneurial networks-effectuation-BMI association was more substantial in highly dynamic environments, whereas the entrepreneurial networks-causation-BMI relationship was unaffected.Research limitations/implicationsThere are several theoretical contributions resulting from this research. The findings offer new insights for understanding the antecedents of start-up BMI from the network perspective. This research adds to the growing literature on resource orchestration (RO) by exploring the dual mediating influences of causation and effectuation in resource management. This investigation revealed the boundary condition between entrepreneurial networks and BMI by testing the moderating influence of environmental dynamism.Practical implicationsStart-ups must effectively use external resources embedded within networks to advance BMI. Start-up entrepreneurs should apply causation and effectuation to transform entrepreneurial network resources into BMI. Start-up entrepreneurs must dynamically manage resources in response to ever-changing environmental conditions. Resource acquisition and management of entrepreneurial networks can vary significantly in their influence on start-up BMI under different environmental contexts.Originality/valueUnlike previous BMI research focused on internal organizational factors, this study highlighted the critical importance of entrepreneurial networks as a prerequisite for achieving start-up BMI, contributing to the literature on open innovation and resource-based view. Examining the dual mediating roles of causation and effectuation illustrated the bridging role of strategic decision-making logic in connecting resources to value creation, contributing to the developing RO literature. The moderating influence of environmental dynamism was explored, clarifying how start-up BMI benefits from entrepreneurial networks in differing situations. A framework for reconciling contradictory findings concerning the association between entrepreneurial networks and innovation is provided.
摘要：
This paper shows that the panic index shadow line difference (ULD) can be an effective predictor of oil returns. We use a candlestick chart to plot the investor panic index (VIX) and subtract the lower shadow from the upper shadow to obtain ULD. The in-sample analysis shows that the ULD can significantly and negatively predict oil returns. The out-of-sample results show that the inclusion of ULD, an exogenous regression variable, in the model not only substantially improves the predictive accuracy of oil returns, but also yields good economic benefits when using its predicted values for portfolio investment. All bivariate regression models that include ULD as an exogenous regression variable obtain higher prediction accuracy than univariate regression models, both for in-sample and out-of-sample predictions. All the robustness tests done in this paper show that ULD is a powerful predictor that significantly improves the predictability of oil returns.
关键词：
Preventive maintenance;Two-dimensional warranty;Gamma usage process
摘要：
This study considers a manufacturer performing preventive maintenance (PM) on a product according to a one- or two-dimensional (2-D) policy. The one-dimensional PM policy is based on either time or usage, while in the two-dimensional case, PM is scheduled based on both scales. The product carries a 2-D warranty that offers protection for a certain amount of time and usage. Its cumulative usage is continuously monitored by the manufacturer and is assumed to follow a gamma process. In this context, we first propose a doubly stochastic Poisson process model for product failures where the stochastic intensity is influenced by the gamma usage process in an additive manner. We then explicitly derive the expected total costs of the two one-dimensional PM policies using the concepts of first hitting times and gamma bridges. For the 2-D PM policy, we express the associated cost in terms of the value function of a dynamic programming model. In the numerical experiments, we show how the variability of the usage process affects the costs of the three PM policies and find that the optimal 2-D policy degenerates into a one-dimensional policy.
摘要：
Abstract Reducing the burden of social security contributions for firms, unleashing their vitality, and enhancing their total factor productivity (TFP) are crucial measures in China's pursuit of sustainable and high‐value‐added growth. This article utilizes three reductions in the corporate pension insurance contribution ratio in China as a quasi‐natural experiment to construct a treatment intensity DID (Difference‐in‐Differences) model. By utilizing data from listed companies between 2013 and 2020, this study empirically examines the impact of reducing the pension insurance contribution ratio on firms’ TFP while identifying the underlying mechanisms. The findings of the study are as follows: First, the policy exhibits a significant positive effect on corporate TFP in China. Second, this policy's contribution primarily stems from stimulating firms to increase their employment of highly skilled labour, elevating wages for ordinary employees, and enhancing firm investment efficiency. Lastly, the analysis of heterogeneity demonstrates that the policy's positive effect is more pronounced among non‐state‐owned enterprises, small and medium‐sized enterprises, and labour‐intensive enterprises. This study provides empirical evidence for evaluating the contribution reduction policy and serves as a policy reference for endeavours to deepen the reform of the pension insurance system and enhance pension insurance fund budget management.
通讯机构：
[Han, F ] N;Nanjing Audit Univ, 86 Yushan West Rd,Jiangpu St, Nanjing, Peoples R China.
关键词：
Government environmental subsidies;Corporate green innovation;Government intervention;Externalities;Signal effect
摘要：
This paper explores the impact of government environmental protection subsidies on corporate green inno- vation using panel data of listed companies from 2007 to 2019. The results show that such subsidies can sig- nificantly promote corporate green innovation, and the results are robust. Financing constraints, research and development (R&D) willingness, and resource allocation efficiency are important variables for govern- ment environmental protection subsidies to promote corporate green innovation. Further analysis shows that compared with industrial policies at the provincial level, the key supportive industrial policies at the central level have a more obvious reinforcing effect on government environmental subsidies to promote enterprise green innovation. Furthermore, government environmental subsidies in the eastern, middle, and western regions benefit the promotion of enterprise green innovation, and the promotional effect is stronger in the middle and western regions. Compared with state-owned enterprises, government environmental subsidies have a more obvious promotional effect on promoting green innovation of non-state-owned enter- prises. This paper provides strong theoretical inspiration for better playing the positive incentive role of gov- ernment intervention with the help of government environmental protection subsidies. (c) 2023 Published by Elsevier Espana, S.L.U. on behalf of Journal of Innovation & Knowledge. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
作者：
Linda Opoku;Bismark Addai*;Adjei Gyamfi Gyimah;Felix Asante
期刊：
Rural Society,2024年:22 ISSN：1037-1656
通讯作者：
Bismark Addai
作者机构：
[Linda Opoku; Felix Asante] Department of Geography and Rural Development, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana;[Bismark Addai] School of Economics and Management, Changsha University of Science and Technology, Changsha, People’s Republic of China;[Adjei Gyamfi Gyimah] Consulting and Training Department, Career Spring Institute, Kumasi, Ghana
通讯机构：
[Bismark Addai] S;School of Economics and Management, Changsha University of Science and Technology, Changsha, People’s Republic of China
摘要：
Waste management is a global environmental problem. This article addresses research gaps in rural waste management in Ghana by establishing the willingness, and factors determining the willingness of rural residents to pay for waste management services (WMS). A Logit model was used to estimate the determinants of willingness to pay (WTP) for WMS, and a Tobit model was used to assess the determinants of the amount willing to pay for WMS. Factors that positively affect WTP for WMS are gender, marital status, education, monthly earnings, house ownership, mode of disposal, quantity of waste, and the distance to disposal. Age, household size, and adaptability have a negative effect. Gender, education, monthly earnings, house ownership, mode of disposal, the quantity of waste, and the frequency of disposal positively influence the amount respondents are prepared to pay, while age, household size, and adaptability to change negatively influence the amount to pay for improved WMS.
摘要：
The single -batch machine, commonly found in industrial manufacturing, can concurrently process a group of jobs in variable -speed batches, leading to fluctuating levels of both energy consumption and processing time. Identifying an optimal balance between total energy consumption and makespan presents a challenge due to the intricate nature of their relationship in real -world scenarios. This study introduces a mixed -integer programming model designed to determine optimal machine operating states for diverse workloads, meeting customer requirements while concurrently achieving energy savings for sustainability. An energy -aware batch scheduling deep Q -learning network (EBSDQN) framework has been created, encompassing sequencing policies, batching rules, and speed adjustment policies. This framework is explicitly crafted to tackle the NP -hard problem, a challenge that commonly perplexes commercial solvers like Gurobi when seeking optimal solutions within a 360 -second time frame for small-scale instances. The EBSDQN design is fortified with efficient action decoding policies, refined reward assessments, exploitative neighborhood rules, and a streamlined buffer training process. This approach not only conserves training time but also adapts dynamically in accordance with the principles of the Markov Decision Process (MDP) and deep neural network. The developed algorithm exhibits impressive robustness, reaching convergence after 600 episodes of training. In separate comparisons with a commercial solver, two single -objective algorithms, and two multi -objective algorithms, our algorithm consistently demonstrates superior overall performance across the same instances. In the worst -case analysis, further examination delves into the influences of job features. In summary, this study underscores the high sensitivity of both TEC and Cmax to job processing time distribution, suggesting the prioritization of TEC over Cmax in optimization for sustainable planning and operations. Furthermore, this research has the potential to accelerate the integration of artificial intelligence into the manufacturing sector.
作者机构：
[Li, Shuxian] School of Business, Sun Yat-Sen University, Guangzhou, Guangdong Province, China;[Liu, Xinheng] School of Economics and Management, Changsha University of Science & Technology, Changsha, Hunan Province, China
摘要：
We analyze whether and how internet searching impacts stock price informativeness. Using the 2010 Google withdrawal in China as a quasi-natural experiment, we establish a causal effect between internet searching and stock price informativeness using a difference-in-difference framework. We find that firms with higher Google search volume experience a 10% decrease in stock price informativeness after the Google withdrawal. The negative effect of the Google withdrawal on stock price informativeness is pronounced in firms with more retail investors, larger state-ownership, and poor analysts' earnings forecasts. Our results suggest that retail investors can benefit from internet searching to collect and process firm-specific information more efficiently.
作者机构：
[Yaozhong Wang; Zunguo Hu; Xuanai Huang] School of Economics and Management, Changsha University of Science & Technology, Changsha 417000, China;School of Finance and Economics, Guangdong Polytechnic Normal University, Guangzhou 510665, China;Author to whom correspondence should be addressed.;[Ying Chen] School of Finance and Economics, Guangdong Polytechnic Normal University, Guangzhou 510665, China<&wdkj&>Author to whom correspondence should be addressed.
通讯机构：
[Ying Chen] S;School of Finance and Economics, Guangdong Polytechnic Normal University, Guangzhou 510665, China<&wdkj&>Author to whom correspondence should be addressed.
关键词：
green innovation;enterprise performance;causal forest;machine learning
摘要：
As increasingly stringent environmental regulations are put into effect, Environmental, Social, and Governance (ESG) concepts are being seamlessly integrated into the core of corporate innovation strategies. Due to the quasi-public product perspective of green innovation, the performance of enterprises as a result of green innovation activities exhibits significant heterogeneity. This heterogeneity exists not only between corporate value and financial performance but also among individual enterprises. This paper is based on a sample of 1510 listed Chinese companies examined from 2013 to 2020 and uses machine learning algorithms and quasi-natural experiments to precisely estimate the causal relationship and mechanisms between green innovation and corporate performance. The findings elucidate several critical aspects of green innovation within the corporate sphere: Firstly, rather than attracting green incentives from financial markets, green innovation activities inadvertently stifle the enhancement of corporate value. Secondly, these activities markedly bolster corporate financial performance, primarily by diminishing operational costs, which in turn elevates the return on assets (ROA). Lastly, of all corporate characteristics examined, enterprise size and equity concentration stand out as key determinants influencing the variability in outcomes of green innovation performance. The above findings provide information on the significant implications of enhancing green technology innovation systems and green incentive mechanisms.
摘要：
Systemic risk is one of the main concerns for banks charged with maintaining overall financial stability. This paper adopts the minimum density method to construct an interbank lending network for European banks and examines how the network structure affects systemic risk. The result reveals that banks positioned at the core of the network exhibit higher levels of systemic risk. Moreover, we find that banks with higher network centrality can show larger systemic risk during times of distress. We demonstrate the robustness of our results by addressing potential endogeneity in the model, replacing network characteristics, and reconstructing the interbank network.
期刊：
International Journal of Finance & Economics,2024年29(1):943-960 ISSN：1076-9307
通讯作者：
Shuxian Li<&wdkj&>Xu Gong<&wdkj&>Shuxian Li Shuxian Li Shuxian Li<&wdkj&>Xu Gong Xu Gong Xu Gong
作者机构：
[Liu, Xinheng; Fan, Chen] Changsha Univ Sci & Technol, Sch Econ & Management, Changsha, Peoples R China.;[Li, Shuxian] Sun Yat Sen Univ, Business Sch, Guangzhou 510275, Peoples R China.;[Fu, Chengbo] Univ Northern British Columbia, Sch Business, Prince George, BC, Canada.;[Gong, Xu] Xiamen Univ, China Inst Studies Energy Policy, Sch Management, Xiamen 361005, Peoples R China.
通讯机构：
[Shuxian Li; Shuxian Li Shuxian Li Shuxian Li] B;[Xu Gong; Xu Gong Xu Gong Xu Gong] S;School of Management, China Institute for Studies in Energy Policy, Xiamen University, Xiamen, China<&wdkj&>Business School, Sun Yat-Sen University, Guangzhou, China
摘要：
Abstract Using the exogenous event of oil price sharp decline in 2014–2015, this paper employs the difference‐in‐difference method to establish a causal link between the oil price decline and the Chinese firms' labour investment. Data of listed companies in China from 2012 to 2016 are used to explore this relationship. We show that the employment for firms in industries with significant negative oil price risk exposure increases 16.4% after the oil price plummeted, that is, the oil price decline significantly promotes the firms' labour force. Additionally, the positive effect of oil price decline on the firms' labour force is more pronounced in firms with higher risk‐taking, financing constraints, and industry competition. Lastly, we also document that the effect of oil price decline is through sales growth channels to increase labour demand. However, firms tend to overinvest in labour after the oil price plummeted. Based on these findings we suggest that oil price fluctuation should be an important factor for the Chinese government and enterprises when they make an economic decision related to the labour force.
作者：
Yichao Meng;Seyed Amir Mansouri*;Ahmad Rezaee Jordehi;Marcos Tostado-Véliz
期刊：
Journal of Cleaner Production,2024年440:140902 ISSN：0959-6526
通讯作者：
Seyed Amir Mansouri
作者机构：
[Yichao Meng] School of Economics & Management, Changsha University of Science & Technology, Changsha, 410076, China;[Seyed Amir Mansouri] Institute for Research in Technology (IIT), ICAI School of Engineering, Comillas Pontifical University, 28015, Madrid, Spain;[Ahmad Rezaee Jordehi] Department of Electrical Engineering, Rasht Branch, Islamic Azad University, Rasht, Iran;[Marcos Tostado-Véliz] Department of Electrical Engineering, University of Jaén, 23700, Linares, Spain
通讯机构：
[Seyed Amir Mansouri] I;Institute for Research in Technology (IIT), ICAI School of Engineering, Comillas Pontifical University, 28015, Madrid, Spain
摘要：
Multi-energy communities (MEC) integrated with renewable resources are known as a cost-effective and highly efficient solution to meet the diverse energy needs of subscribers. The increasing integration of MECs with electricity and natural gas networks has made it necessary to design new frameworks to optimize their energy management and then facilitate their participation in competitive energy markets. Hence, this article presents a bi-level optimization strategy for the decentralized coordination of MECs in competitive electricity and gas markets, in which the system operator adopts a robust technique to deal with operational uncertainties. The daily planning of MECs is performed in the upper level, while in the lower level, the planning of electricity and natural gas networks takes place. An adaptive alternating direction method of multipliers (ADMM) algorithm has also been introduced to settle the electricity and natural gas markets in a decentralized space while considering the CO2 footprint tax. The proposed strategy is implemented on a system containing a modified 69-bus IEEE distribution electricity network (EN) and a 65-node natural gas network (NGN). The results obtained from the case studies show that the proposed adaptive ADMM algorithm reached the optimal point in 113 iterations less than the original version, reducing the solution time by 48.01 %. The results prove that the proposed strategy has been able to coordinate the decentralized MECs with the least data sharing in the competitive electricity and gas markets. Additionally, it effectively utilizes the capabilities of renewable-based assets, storage systems, and smart EV charging to reduce the CO2 footprint, alleviate congestion, and improve the voltage and gas pressure profiles, while leading to reduced market clearing prices.
期刊：
Engineering Applications of Artificial Intelligence,2024年127:107401 ISSN：0952-1976
通讯作者：
Zheng, LF
作者机构：
[Zheng, LF; Zheng, Lifan; Zhang, Zhuo; Onyebuchi, Chiamaka Henrietta; Lu, Peng] Cent South Univ, Dept Sociol, Changsha, Peoples R China.;[Lu, Peng] Cent South Univ, Dept Artificial Intelligence, Changsha, Peoples R China.;[Zheng, Lifan; Zhang, Zhuo; Onyebuchi, Chiamaka Henrietta; Lu, Peng] PKU WUHAN Inst Artificial Intelligence, Wuhan 430073, Peoples R China.;[Lu, Peng] Zhejiang Lab, Intelligent Social Governance Ctr, Hangzhou, Peoples R China.;[Zheng, Lifan; Lu, Peng] Changsha Univ Sci & Technol, Sch Econ & Management, Hunan, Peoples R China.
通讯机构：
[Zheng, LF ] C;Cent South Univ, Dept Sociol, Changsha, Peoples R China.
关键词：
Crowd dynamics;High-rise building fires;Social force model;Self-rescue behaviors
摘要：
It is always challenging to seek external rescue assistance in high-rise building fires. Therefore, it is critical for individuals to master survival skills. For crowd dynamics modeling, previous research focused on numerical simulations and building designs with little attention to the self-rescue mechanism. It is critical to understanding crowd evacuations and better response strategies. We modeled the Grenfell Tower (a high-rise building with a complicated structure) case in 2017. Based on the percolation and social force models, we build an agent-based model to simulate individual behaviors inside. We obtain the optimal solution and robust paralleled outcomes under all counterfactual situations based on precisely matching tangible case outcomes (fire duration, deaths, and injuries). For individuals, mastering self-rescue skills is better at reducing social losses (deaths & injuries). In terms of high-rise buildings design, the central alarm system is also useful to reduce them. Besides, the crowd evacuation guided by the social force model also reduces deaths & injuries. This work provides insight into better high-rise building design and practical response strategies for societies. The central alarm system and fire-proof materials should be used in high-rise buildings. The residents should have routine training in social force-based evacuations and survival (self-rescue) skills to better the evacuation process and outcome under natural disasters and social emergencies.
关键词：
Highway toll allocation problem;Axiomatic characterization;Shapley value
摘要：
An important operational aspect in the management of tolled highways is how the collected tolls should be allocated over the different highway segments, either operated by different operators or by different units of one operator. This paper analyzes this toll allocation problem both from an axiomatic and a game theoretic perspective. Based on different toll charging systems, specifically the distance-based toll system and the fixed toll system, we propose three allocation or sharing methods: the Segments Equal Sharing method, the Exits Equal Sharing method, and the Entrances Equal Sharing method. After direct and game theoretic characterizations of these methods, we apply them to several real-life highways.
摘要：
The authority has moved away from using GDP as the sole measure of local government performance, placing new emphasis on environmental governance, tax administration, and technological innovation. This shift has spurred competition among local governments, prompting the need to examine the relationship between government competitive behaviour and firms’ green innovation. The study uses panel data from 2007 to 2020 and presents a comprehensive research-based explanation of how local government competition affects firms’ green innovation activities under China’s fixed and floating environmental tax and fee systems, applying the causal forest algorithm. The results show that local government competition suppresses green innovation under the floating system, but stimulates it under the fixed system. Further analysis shows that the floating system’s relatively higher national environmental governance tax and the increased competition under the floating system increase firms’ operating costs, leading to a ‘crowding out effect’ on green innovation. Conversely, under the fixed system, increased competition among local governments reduces operating costs, promotes investment in green innovation, and creates a ‘leverage effect’.
摘要：
Industrialized nations have witnessed a decline in environmental quality over the years. The potential of digitalization in mitigating environmental pollution is of significant interest. Drawing on firm-level data from listed Chinese companies between 2010 and 2020, including pollutant and financial metrics, this study investigates the influence of digitalization on industrial environmental pollution. We found that digitalization substantially diminishes the intensity of industrial pollution emissions. These findings hold even after employing instrumental variable tests, substituting the dependent variable with carbon dioxide emissions, and conducting a quasi-natural experiment in intelligent manufacturing. Moreover, our exploration of the underlying mechanisms reveals that the decline in pollution emission intensity attributable to digitalization stems from both structural and technological factors; specifically, it enhances environmental investment and fosters green innovation. The benefits of digitalization in curbing emission intensity are pronounced for firms characterized by lower pollution levels, executive leadership with environmental work backgrounds, heightened capital intensity, and elevated media coverage.
摘要：
The construction and development of energy storage are crucial areas in the reform of China's power system. However, one of the key issues hindering energy storage investments is the ambiguity of revenue sources and the inaccurate estimation of returns. In order to facilitate investors' understanding of revenue sources and returns on investment of energy storage in the existing electricity market, this study has established multiple relevant revenue quantification models. The research methodology employed in this paper consists of three main components: Firstly, we established a revenue model and a cost model for energy storage participation in the electricity market. These models focus on arbitrage revenue, subsidy revenue, auxiliary services revenue, investment cost, operational and maintenance cost, and auxiliary service cost of energy storage. Subsequently, we utilized an enhanced Grey Wolf Optimizer algorithm to solve the optimization problem and maximize revenue, thus obtaining the optimal capacity and revenue scale of energy storage in the electricity market. Finally, we compared the whole-lifecycle ROI of different energy storage options in various scenarios. The evaluation results demonstrate that the difference between peak and off-peak loads impacts the investment demand and charging/discharging depth of energy storage. In addition, the discrepancy between peak and off-peak prices affects the arbitrage return of energy storage. These two factors can serve as criteria for energy storage investors to assess their return expectations. When solely considering economic returns and disregarding technical factors, pumped storage energy storage emerges as the most suitable mechanical energy storage option requiring investment. The main contribution of this study lies in the estimation of the lifecycle investment returns for various energy storage technologies in the Chinese electricity market, thus providing valuable insights for the investment and operational practices of market participants.
关键词：
Female executives;ESG performance;Ownership concentration;Media exposure;Sustainable enterprise development
摘要：
The relationship between the personal characteristics of senior management team members and the sustainable development of the enterprise has received much attention. This study used data on A-share listed companies in China from 2009 to 2022 to examine the effect of female executives on enterprise environmental, social, and governance (ESG) performance and tested the moderating role of ownership concentration and media exposure. Empirical testing was conducted on 20,188 annual observation samples using regression analysis. The empirical results demonstrate that female executives significantly improve corporate ESG performance, especially social responsibility performance. The study also revealed that ownership concentration plays an internal moderating role on the connection between female executives and corporate ESG performance, while media exposure plays an external moderating role. The conclusions remain the same after several robustness tests, including a lag test, substitution variable estimation, and propensity score matching. An economic consequence check and heterogeneity test were also conducted. This study's findings enrich the research on ESG influencing factors and offers empirical support for the value of female participation in corporate governance.
摘要：
Practicing ESG concept is a necessary way for sustainable development of enterprises and an important hand in realizing high-quality economic growth. This paper introduces the hypothesis of "distance attenuation effect" of geo-economics into the research field of corporate ESG performance, and systematically examines the impact of neighboring the Environmental Protection Agency (EPA) on corporate ESG performance by using the data of China's listed companies in the manufacturing industry from 2011 to 2021. It is found that being a neighbor to the EPA has a significant inhibitory effect on corporate ESG performance, which was reduced by 0.196% when the distance between the two was reduced by every 1km. And the inhibitory effect has a stepwise decreasing characteristic, i.e., it is the strongest at the level of county EPA, followed by municipal EPA, and the smallest at the level of provincial EPA. The mechanism analysis shows that the rent-seeking behavior caused by neighboring with EPA is an important reason for the decline of ESG performance, which verifies the "distance attenuation effect" of rent-seeking difficulty. Although neighboring the EPA improves firms' financial performance, it greatly harms firms' environmental, social and governance performance, which confirms the profit-seeking motive of firms' rent-seeking. In addition, the deterrent effect generated by third-party supervision and digital supervision can inhibit corporate rent-seeking to a certain extent, which helps weaken the negative impact of neighboring the EPA on corporate ESG performance.
