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This study reduces carbon emission in logistics distribution to realize the low-carbon site optimization for a cold chain logistics distribution center problem.

This study involves cooling, commodity damage and carbon emissions and establishes the site selection model of low-carbon cold chain logistics distribution center aiming at minimizing total cost, and grey wolf optimization algorithm is used to improve the artificial fish swarm algorithm to solve a cold chain logistics distribution center problem.

The optimization results and stability of the improved algorithm are significantly improved and compared with other intelligent algorithms. The result is confirmed to use the Beijing-Tianjin-Hebei region site selection. This study reduces composite cost of cold chain logistics and reduces damage to environment to provide a new idea for developing cold chain logistics.

This study contributes to propose an optimization model of low-carbon cold chain logistics site by considering various factors affecting cold chain products and converting carbon emissions into costs. Prior studies are lacking to take carbon emissions into account in the logistics process. The main trend of current economic development is low-carbon and the logistics distribution is an energy consumption and high carbon emissions.

Recently, electric vehicles have been widely used in the cold chain logistics sector to reduce the effects of excessive energy consumption and to support environmental friendliness. Considering the limited battery capacity of electric vehicles, it is vital to optimize battery charging during the distribution process.

This study establishes an electric vehicle routing model for cold chain logistics with charging stations, which will integrate multiple distribution centers to achieve sustainable logistics. The suggested optimization model aimed at minimizing the overall cost of cold chain logistics, which incorporates fixed, damage, refrigeration, penalty, queuing, energy and carbon emission costs. In addition, the proposed model takes into accounts factors such as time-varying speed, time-varying electricity price, energy consumption and queuing at the charging station. In the proposed model, a hybrid crow search algorithm (CSA), which combines opposition-based learning (OBL) and taboo search (TS), is developed for optimization purposes. To evaluate the model, algorithms and model experiments are conducted based on a real case in Chongqing, China.

The result of algorithm experiments illustrate that hybrid CSA is effective in terms of both solution quality and speed compared to genetic algorithm (GA) and particle swarm optimization (PSO). In addition, the model experiments highlight the benefits of joint distribution over individual distribution in reducing costs and carbon emissions.

The optimization model of cold chain logistics routes based on electric vehicles provides a reference for managers to develop distribution plans, which contributes to the development of sustainable logistics.

In prior studies, many scholars have conducted related research on the subject of cold chain logistics vehicle routing problems and electric vehicle routing problems separately, but few have merged the above two subjects. In response, this study innovatively designs an electric vehicle routing model for cold chain logistics with consideration of time-varying speeds, time-varying electricity prices, energy consumption and queues at charging stations to make it consistent with the real world.

This paper aims to explore the pathways of carbon transfer in 200 US corporations along with the motivations that drive such transfers. The particular focus is on each firm’s embeddedness in the global value chain (GVC) and the influence of environmental law, operational costs and corporate social responsibility (CSR). The insights gleaned bridge a gap in the literature surrounding GVCs and corporate carbon transfer.

The methodology comprised a two-step research approach. First, the authors used a two-sided fixed regression to analyse the relationship between each firm’s embeddedness in the GVC and its carbon transfers. The sample consisted of 217 US firms. Next, the authors examined the influence of environmental law, operational costs and CSR on carbon transfers using a quantitative comparison analysis. These results were interpreted through the theoretical frameworks of the GVC and legitimacy theory.

The empirical results indicate positive relationships between carbon transfers and GVC embeddedness in terms of both a firm’s position and its degree. From the quantitative comparison, the authors find that the pressure of environmental law and operational costs motivate these transfers through the value chain. Furthermore, CSR does not help to mitigate transfers.

The findings offer insights for policymakers, industry and academia to understand that, with globalised production and greater value creation, transferring carbon to different parts of the GVC – largely to developing countries – will only become more common. The underdeveloped nature of environmental technology in these countries means that global emissions will likely rise instead of fall, further exacerbating global warming. Transferring carbon is not conducive to a sustainable global economy. Hence, firms should be closely regulated and given economic incentives to reduce emissions, not simply shunt them off to the developing world.

Carbon transfer is a major obstacle to effectively reducing carbon emissions. The responsibilities of carbon transfer via GVCs are difficult to define despite firms being a major consideration in such transfers. Understanding how and why corporations engage in carbon transfers can facilitate global cooperation among communities. This knowledge could pave the way to establishing a global carbon transfer monitoring network aimed at preventing corporate carbon transfer and, instead, encouraging emissions reduction.

This study extends the literature by investigating carbon transfers and the GVC at the firm level. The authors used two-step research approach including panel data and quantitative comparison analysis to address this important question. The authors are the primary study to explore the motivation and pathways by which firms transfer carbon through the GVC.

Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.

This paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.

The results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.

Since the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.

This study investigated the visibility of carbon emissions allowances accounting in the financial reports of 32 clean development mechanism (CDM) projects in the UAE to uncover the obstacles to setting consistent standards for carbon emission accounting. As carbon emissions are monetized as credits, consistent accounting standards can aid decision-makers in the development of carbon emission mitigation strategies.

This study used a grounded theoretical framework for exploring the terms used in the policy documents of international accounting bodies regarding accounting standards and guidelines for carbon emission credits. Raw qualitative data were gathered, and an inductive approach was used by analyzing documents from various sources using the qualitative data text analysis software QDA Miner 6.

The findings showed that the financial statement reports of the corporations did not include disclosure of the carbon credit account. This omission was due to the lack of global standardization of carbon credit accounts and emission allowance recognition. This may hinder the production of a comprehensive report containing accurate and valuable financial information relevant to all stakeholders.

The study is among the first to use a grounded theoretical framework to investigate whether corporations are applying common standards and guidelines for carbon emissions accounting.

This paper aims to identify the interplay of standard Capesize optimal speeds for time charter equivalent (TCE) maximization in the Australia–China iron ore route and the optimal speeds as an operational tool for compliance with the International Maritime Organization (IMO) carbon intensity indicator (CII).

The TCE at different speeds have been calculated for four standard Capesize specifications: (1) standard Capesize with ecoelectronic engine; (2) standard Capesize with non-eco engine (3) standard Capesize vessel with an eco-electronic engine fitted with scrubber and (4) standard Capesize with non-eco engine and no scrubber fitted.

Calculations imply that in a highly inflationary bunker price context, the dollar per ton freight rates equilibrates at levels that may push optimal speeds below the speeds required for minimum CII compliance (C Rating) in the Australia–China trade. The highest deviation of optimal speeds from those required for minimum CII compliance is observed for non-eco standard Capesize vessels without scrubbers. Increased non-eco Capesize deployment would see optimal speeds structurally lower at levels that could offer CII ratings improvements.

While most of the studies have covered the use of speed as a tool to improve efficiency and emissions in the maritime sector, few have been identified in the literature to have examined the interplay between the commercial and operational performance in the dry bulk sector stemming from the freight market equilibrium. The originality of this paper lies in examining the above relation and the resulting optimal speed selection in the Capesize sector against mandatory environmental targets.

This study aims to investigate the relationship between business group affiliation and CO2 emissions in Chile, providing insights into the pollution externalities associated with business group structures and their implications for environmental performance.

A hand-matched sample of industrial facilities and subsidiaries of listed firms in Chile was utilized to analyze the CO2 emissions of business group-affiliated firms compared to stand-alone firms. Fixed-effect regression analysis and propensity score matching were employed to examine the differences in emissions levels.

The results suggest that firms affiliated with business groups have higher CO2 emissions in comparison to similar stand-alone firms. This suggests that business group structures may weaken the pressures for emission reduction and maintenance of public legitimacy among affiliated firms.

The findings of this study are subject to certain limitations, such as the use of a specific dataset from Chile and the inability to explore certain factors due to data constraints. For instance, we were unable to examine the separation between control and cash-flow rights as well as the influence of manager characteristics on pollution levels. Future research should address these limitations and expand the analysis to other emerging market countries to further investigate the impact of lax or ineffective environmental regulations on pollution outcomes.

The research findings have practical implications for investors and policymakers. Investors interested in environmentally sustainable investments should consider the higher pollution levels associated with business group-affiliated firms. Policymakers can use these findings to design more effective regulations and incentives to encourage emission reduction efforts within business group structures.

The study’s results emphasize the need for a comprehensive understanding of the environmental implications of business group affiliation. By recognizing the potential for higher emissions in business group structures, stakeholders can advocate for sustainable practices, encourage transparency and promote responsible environmental management within corporate entities.

This study contributes to the literature on corporate governance, climate risks and pollution externalities by providing an empirical evidence on the relationship between business group affiliation and CO2 emissions. It highlights the importance of considering the influence of corporate structures on environmental performance, particularly in the context of emerging market economies.

Este estudio tiene como objetivo investigar la relación entre la afiliación a grupos empresariales y las emisiones de CO2 en Chile, proporcionando información sobre las externalidades de contaminación asociadas con las estructuras de grupos empresariales y sus implicaciones para el desempeño ambiental de las empresas.

Se utilizó una muestra recolectada de manera manual de instalaciones industriales y subsidiarias de empresas listadas en Chile para analizar las emisiones de CO2 de empresas afiliadas a grupos empresariales en comparación con empresas independientes. Se emplearon análisis de regresión de efectos fijos y modelos de emparejamiento por puntaje de propensión para examinar las diferencias en los niveles de emisiones.

Los resultados sugieren que las empresas afiliadas a grupos empresariales tienen mayores emisiones de CO2 en comparación con empresas independientes similares. Esto sugiere que las estructuras de grupos empresariales pueden debilitar las presiones para la reducción de emisiones y el mantenimiento de la legitimidad pública entre las empresas afiliadas.

Este estudio contribuye a la literatura sobre gobierno corporativo, riesgos climáticos y externalidades de contaminación al proporcionar evidencia empírica sobre la relación entre la afiliación a grupos empresariales y las emisiones de CO2. Destaca la importancia de considerar la influencia de las estructuras corporativas en el rendimiento ambiental, especialmente en el contexto de las economías de mercados emergentes.

Los hallazgos de este estudio están sujetos a ciertas limitaciones, como el uso de un conjunto de datos específico de Chile y la incapacidad para explorar ciertos factores debido a restricciones de datos. Por ejemplo, no pudimos examinar la influencia de las características de los ejecutivos de las empresas en los niveles de contaminación. Investigaciones futuras deberían abordar estas limitaciones y ampliar el análisis a otros países de mercados emergentes para investigar más a fondo el impacto de regulaciones ambientales laxas o ineficaces en los resultados de contaminación.

Los hallazgos de la investigación tienen implicaciones prácticas para inversores y responsables políticos. Los inversores interesados en inversiones ambientalmente sostenibles deben tener en cuenta los niveles más altos de contaminación asociados con empresas afiliadas a grupos empresariales. Los responsables políticos pueden utilizar estos hallazgos para diseñar regulaciones más efectivas e incentivos para fomentar los esfuerzos de reducción de emisiones dentro de las estructuras de grupos empresariales.

Los resultados del estudio enfatizan la necesidad de comprender de manera integral las implicaciones ambientales de la afiliación a grupos empresariales. Al reconocer el potencial de mayores emisiones en las estructuras de grupos empresariales, los interesados pueden abogar por prácticas sostenibles, fomentar la transparencia y promover una gestión ambiental responsable dentro de las entidades corporativas.

This paper aims to empirically investigate the impact of the carbon intensity constraint policy (CICP) on green innovation.

This study takes the implementation of the CICP as a quasi-natural experiment and uses a quasi–difference-in-difference method to investigate the impact of the CICP on firm green innovation from a microeconomic perspective.

The CICP significantly limits the quality of firms’ green innovation. Among the range of green patents, the CICP distorts only patents related to CO₂ emissions. The inhibitory effect is more pronounced in non-state-owned enterprises and heavily polluting firms. R&D investment and green investor are identified as the main mechanism.

These findings provide evidence for the influence of the CICP on firm green innovation, which can guide policymakers in China and other emerging economies that prioritize carbon intensity constraint targets and the improvement of relevant auxiliary measures.

Governments and firms should have a comprehensive understanding of environmental policies and corporate behavior and need to mitigate the negative impact through a combination of measures.

This study contributes to the literature by providing additional empirical evidence regarding the two opposing sides of the ongoing debate on the positive or negative effects of CICP. It also provides new evidence on the policy effect of the CICP on firm green innovation, together with its mechanisms and heterogeneous influences.

This study aims to investigate the external effect of the economic growth target pressure of local governments on establishment-level SO₂ emissions.

Based on manually collected panel data of 74,058 China's industrial establishments and more than 330 thousand observations from CIED and ESR, the authors use a firm-fixed effect model, instrumental variables estimation and heterogeneity tests to identify the environmental externality of economic growth target pressure.

The establishments in cities that meet or slightly exceed the economic growth target experience greater negative externality measured by SO₂ emission intensity. This external effect is more pronounced in regions: with a strict and overweighted target setting; with stronger officials' promotion incentives; with a low degree of marketization; and in firms with great economic importance. The authors identify the underlying mechanisms of dependence on dirty industry and the relaxation of environmental enforcement. And the environmental protection constraints in 2007 mitigate the negative externality.

The paper sheds light on to what extent economic growth target pressure has a negative externality of pollution in China and how this pressure may conflict with environmental protection.

This paper complements prior research on the economic effects of economic growth targets, expands the knowledge on the determinants of establishment-level pollution emission from the perspective of target pressure and provides insight into the environmental externality that results from political factors.

This study examines the effect of female governors (gender effect) on environmental performance in terms of state-level carbon dioxide (CO2) emissions in United States.

The study used annual data from 1970 to 2020 to investigate the relationship between female political leadership and state-level CO2 emissions. Hypothesis was tested through ordinary least squares regression (OLS). The results of the study were also validated using propensity score matching and a difference-in-difference approach.

This study provides empirical insights into the relationship between female political leadership and state-level CO2 emissions. The findings indicate that female governors have a significant negative impact on state-level CO2 emissions per capita. These results suggest that female political leadership is associated with a reduction in CO2 emissions per capita at the state level. The results also show that states under the leadership of female governors experience lower levels of CO2 emissions than those with male governors, indicating female leadership’s potential to promote environmental sustainability.

The findings of this study have practical implications for policymakers, government officials, and other stakeholders involved in the formulation of strategies to promote environmental sustainability. This study highlights the significant role that female political leader play in mitigating CO2 emissions at the state level. It suggests that promoting female in political leadership positions can lead to more environmentally conscious policy decisions and actions, resulting in reduced CO2 emissions per capita. Policymakers should actively encourage women’s participation in leadership roles to utilize their potential contributions to advancing sustainability goals. Furthermore, organizations that focus on environmental issues should prioritize supporting and promoting female leaders who have demonstrated a commitment to environmental sustainability. Ultimately, this study highlights the need for female in political leadership as a potential strategy to address environmental challenges and advance a more sustainable future.

This study pioneers research on the links between female political leadership and state-level CO2 emissions. This study contributes to the literature by emphasizing the potential role of female political leaders in promoting environmental sustainability. Overall, this study enriches the social role and upper echelons theories literature through empirical evidence.