Search Results (296)

Efficient plastic waste end-of-life management is a serious worldwide environmental issue motivated by growing waste production and negative effects of wrongful disposal. This study presents a comparative overview of plastic waste management regimes within the European Union (EU), the United States of America (USA), and Romania, ranked with circular economy goals. By using the United States Environmental Protection Agency (US EPA) Waste Reduction Model (WARM), version 16, the study provides a quantified score to greenhouse gas (GHG) emissions within three large options of management: recycling, energy recovery through combustion, and landfilling. The model setup utilizes region-specific information on legislation, base technology, and recycling efficiency. The outcomes show that recycling always entails net GHG emissions reductions, i.e., −4.49 kg CO_2e/capita/year for EU plastic waste and −20 kg CO_2e/capita/year for USA plastic waste. Combustion and landfilling have positive net emissions from 1.76 to 14.24 kg CO_2e/capita/year. Economic indicators derived from the model also show significant variation: salaries for PET management amounted to USD 2.87 billion in the EU and USD 377 million in the USA, and tax collection was USD 506 million and USD 2.01 billion, respectively. The conclusions highlight the wider environmental and socioeconomic benefits of recycling and reinforce its status as a cornerstone of circular-economy sustainable plastic waste management and a strategic element of national development agendas, with special reference to Romania’s national agenda. Full article

The B Corp certification is a voluntary designation granted by B Lab. This nonprofit organization evaluates two main aspects of a company’s operations: the positive impact generated by its daily activities and how its business model reflects unique practices that yield positive outcomes for its stakeholders. Sistema B is at the forefront of the B movement in Latin America and the Caribbean, working to develop an ecosystem that enables B Corps to harness market forces to address social and environmental challenges. However, the B Corp movement in this region faces significant challenges, primarily due to a lack of government support, including tax benefits and legal recognition. This study aims to advance the existing literature on B Corps by examining sustainability-oriented hybrid organizations that strive to reconcile profit generation with social impact within the context of Mexico’s socioeconomic landscape. Additionally, it seeks to enhance the understanding of how ventures navigate trade-offs between financial and social objectives, and to identify factors that can help address these challenges. Twenty semi-structured interviews were conducted with Mexican B Corps to explore the entrepreneurial motivations related to social objectives, the B Corp movement, and the internal organizational dynamics of balancing social and economic logics. We discuss how tensions arise and are managed, as well as the issues regarding regulatory tensions in Mexico and the challenges that stem from organizational complexities. Future research directions are also outlined. Full article

With the acceleration of global climate warming and agricultural modernization, the energy and carbon emission issues of agricultural parks (APs) have drawn increasing attention. An AP equipped with biogas-based combined heat and power (CHP) generation and photovoltaic systems serves as a prosumer terminal in a distribution network (DN). This paper introduces carbon emission flow (CEF) theory into the coordinated dispatch of APs and DNs. First, a CEF model for APs is established. Then, based on this model, a carbon–energy coordinated dispatch is carried out under bidirectional CEF interaction between the park and DN. A bidirectional carbon tax mechanism is adopted to explore the low-carbon synergy potential between them. Finally, the Stackelberg game approach is employed to address the pricing of electricity purchase/sale and carbon taxes in a DN, and the particle swarm optimization algorithm is used for rapid generating solutions. The case study shows that the proposed CEF model can effectively determine CEF distribution in the park. Moreover, the proposed bidirectional carbon tax mechanism significantly enhances the low-carbon economic benefits of both the AP and the DN. Full article

This study investigates the dynamic relationship between environmental tax revenue and economic development in the European Union from 2013 to 2022. The findings reveal that these taxes significantly contribute to economic development in the long run, although short-run effects vary by tax type and country. The PMG model results indicate that energy tax revenues increase GDP per capita by 0.038, transport tax revenues by 0.041, and resource tax revenues by 0.018, all of which are statistically significant. Pollution tax revenues have an effect of 0.002 in the long run but are not statistically significant. In the short run, none of the tax variables show significant effects, although pollution tax revenues have a transitional impact of 0.196. The error correction term of −1.321 confirms a strong long-run adjustment, reinforcing the gradual economic benefits of environmental taxation. The results underscore the importance of resource and pollution taxes, which exhibit robust positive impacts, particularly in resource-rich and pollution-intensive economies. Energy and transport taxes also influence economic performance; however, their effectiveness depends on the structural and sectoral differences among countries. This study provides valuable insights for policymakers by highlighting the necessity of designing tailored environmental taxation policies that align with national conditions and long-term sustainability goals. Additionally, this study adopts a systems thinking perspective to capture the interconnectedness between environmental fiscal instruments and macroeconomic sustainability, offering a holistic interpretation of policy impacts. Full article

The primary objective of this study is to investigate the intricate relationship between different ownership structures, such as family, institutional, managerial, and foreign ownership, and tax avoidance practices. It also seeks to explore the moderating influence of female board members in shaping these relationships. This study utilizes balanced panel data from 72 industrial and service firms listed on the Amman Stock Exchange during the period of 2018 to 2023. The Generalized Method of Moments (GMM) was employed to estimate the results. The results indicate that family and foreign ownership positively influence tax avoidance practices, suggesting that families may engage in tax avoidance to benefit from rent extraction, while foreign investors may pressure managers to manipulate tax liabilities or shift profits across countries to minimize taxes. In contrast, the presence of female directors as well as institutional and managerial ownership is associated with a reduction in tax avoidance. Female directors play a moderating role in the relationship between ownership structure and tax avoidance. Their presence in interaction with institutional ownership reduces tax avoidance by focusing on tax compliance strategies. However, this effect changes in family and foreign-owned firms, where control over decision-making lies with the families or foreign shareholders, limiting the impact of female directors in promoting compliance and aligning their role with the tax avoidance strategies preferred by the controlling owners. Full article

Environmental sustainability is receiving growing global attention, making the development of low-carbon and green transportation increasingly important. Low-carbon policies offer significant advantages in incentivizing energy conservation and reducing emissions in the transportation sector; however, it is vital to consider the impacts of regional differences on the implementation effect of low-carbon policies. This paper explores multimodal transportation route optimization under a carbon tax policy. First, a bi-objective route optimization model is constructed, with the goal of minimizing total transportation cost and time, while accounting for uncertain demand, fixed departure schedules, and regional differences. Trapezoidal fuzzy numbers are used to represent uncertain demand, and a fuzzy adaptive non-dominated sorting genetic algorithm is designed to solve the bi-objective optimization model. The algorithm is then tested on differently sized networks and on real-world transportation networks in eastern and western China to validate its effectiveness and to assess the impacts of regional differences. The experimental results show the following. (1) When considering transportation tasks at different network scales, the proposed fuzzy adaptive non-dominated sorting genetic algorithm outperforms the NSGA-II algorithm, achieving minimum differences in percentages of cost and time of 9.25% and 7.72%, respectively. (2) For transportation tasks assessed using real-world networks in eastern and western China, an increase in the carbon tax rate significantly affects carbon emissions, costs, and time. The degree of carbon emission reduction varies depending on the development of the regional transportation network. In the more developed eastern region, carbon emissions are reduced by up to 44.17% as the carbon tax rate increases. In the less developed western region, the maximum reduction in carbon emissions is 14.37%. The carbon tax policy has a more limited impact in the western region compared to the eastern one. Therefore, formulating differentiated carbon tax policies based on local conditions is an effective way to maximize the economic and environmental benefits of multimodal transportation. Full article

This study evaluates the profitability and competitiveness of wheat and sunflower, strategic crops vital for food security, in Tekirdağ, Türkiye. Utilizing the Policy Analysis Matrix (PAM) and Stochastic Frontier Analysis (SFA), we analyze their profitability, competitiveness, and production efficiency under current agricultural policies. The findings reveal positive private profitability for wheat (354.86 USD/ha) and sunflower (240.82 USD/ha), with higher social profitability (431.78 USD/ha for wheat, 641.39 USD/ha for sunflower) indicating inherent efficiency. Policy analysis shows wheat benefits from a 7% price protection (NPCO 1.07), while sunflower is implicit taxed at 20% (NPCO 0.80). The SFA results indicate average technical efficiencies of 79.9% for wheat and 88.9% for sunflower, highlighting the potential for cost reduction through improved input use. In this study, the profitability rate at private prices was about 16% for both crops, while sunflower had a 35% rate at social prices. These findings highlight the need for holistic agricultural policies, including climate adaptation, efficient input use, and market competitiveness measures, to ensure the long-term sustainability of wheat and sunflower production in Tekirdağ and similar regions. Full article

This study examined the socioeconomic and veterinary cost factors influencing dog abandonment and adoption outcomes across 162 regions in the Republic of Korea from 2021 to 2023. Unlike prior research, this study distinguished between intentionally abandoned dogs and those lost and subsequently returned to their owners, normalizing abandonment data by population. Using publicly available regional data and spatial regression models, we found that the number of people receiving unemployment benefits was consistently and negatively associated with the number of dog abandonments per 100,000 residents, which was normalized by total population to avoid potential errors. Rabies vaccination costs were also negatively associated with abandonment. In contrast, comprehensive income tax amounts—a proxy for regional wealth—were positively correlated with the percentage of dog abandonments reported in 2021 and 2023. Spatial Lag Models accounted for over 50% of the variance in the number of dog abandonments, confirming spatial dependence and highlighting the importance of geographically targeted animal welfare interventions. However, spatial patterns in adoption were less consistent. These findings highlight the importance of incorporating economic and spatial considerations into the design of public policies and shelter strategies to mitigate dog abandonment and enhance adoption outcomes. Full article

This study assesses the energy, economic, and environmental implications of switching Tanzania’s road transport sector to natural gas, which is slowly transitioning. In energy, the main goal is to identify the energy demand for petroleum fuel (diesel and petrol) and natural gas during the transition, while in the economy, the government revenue in the form of taxes for shifted and unshifted vehicles, as well as the loss in government revenue from petroleum fuel revenue post-transition, is assessed. In the environment, carbon emission in terms of carbon dioxide equivalent (CO_2e), carbon tax revenues, and carbon credit revenues post-transition is estimated. The shift involved 10, 20, and 30% of the road vehicle population. The 10, 20, and 30% shift targeted about 142,247, 183,893, and 225,540 vehicles, which in turn dropped diesel and petrol demand by 7 and 3.68%, 7 and 3.8%, and 15 and 7.5%, respectively. In natural gas, the demand started at 0.0916 billion kg and grew exponentially by 200% and later by 300%. The transition has consequences in government revenue, which takes the form of taxes on petroleum products. The shift from 10 to 30% could lead to foregone taxes amounting to Tanzania shilling TZS 0.09, 0.31, and 0.54 trillion (US$ 33,358,680, US$ 11,490,212, and US$ 20,015,208), indicating a tax loss of about 3, 9, and 15%. Contrary, the government may benefit from these losses by lowering the amount of foreign currency necessary for oil importation. In environmental benefits, the 10, 20, and 30% shift could offset approximately 8,959,198.92119, 8,438,863.65528, and 7,918,528.38937 tCO_2e, equivalent to 5.4, 10.97, and 16.47% of the road emissions. The post-transition road emissions might result in a carbon tax revenue of about US$ 71,673,591.37, 67,510,909.24, and 63,348,227.11 per year. The post-transition carbon credit revenue of about US$ 20,813,410.64, 41,626,821.27, and 62,440,231.91 is expected annually. The findings are critical for policy design and promoting a transition in the road transport sector. Full article

The carbon tax is a crucial economic instrument for China; it aims to encourage the reduction of carbon emissions and provide additional revenue for the government in order to promote the transformation of society towards low-carbon and sustainable development. The suboptimal carbon tax refers to the carbon tax rate that achieves the best balance between emission reduction targets and economic benefits. Using China’s 2020 Non-competitive Input–Output Table, which encompasses 42 sectors, alongside carbon emission data sourced from the China Carbon Emission Accounts and Datasets (CEADs) covering 47 sectors, this study established a Carbon Tax-adjusted Input–Output Table of China’s Non-competitive Carbon Emissions 2020 (26 sectors) and constructed a multi-objective suboptimal carbon tax model based on an input–output price change model. Based on these, the suboptimal carbon tax rates under four different sets of constraints were simulated, including 49.2 CNY/ton (low inflation), 98.3 CNY/ton (low-to-medium inflation), 147.1 CNY/ton (medium-to-high inflation), and 195.5 CNY/ton (high inflation). We found that the suboptimal carbon tax should take into account its impact on prices, carbon reduction, and GDP, and higher carbon tax rates lead to more significant macroeconomic impacts and increased efforts in reducing emissions. Policy recommendations have also been put forward, such as launching a comprehensive research framework, establishing a synergistic and complementary mechanism between carbon taxation and carbon trading, designing a dynamic carbon tax, etc. Full article

The accelerated growth of older adults (the over-65s) in Italy fits within the context of the complex, hybrid nature of the pension system and the welfare benefits financed by tax revenues, which often overlap. As a result, older adults are experiencing growing inequalities in living and health conditions across the three Italian macro-areas (the North, Centre, and South and Islands), as well as between genders. This study aims to examine the sustained growth of older adults in Italy, with a particular emphasis on their most vulnerable segment—i.e., the over-85s. Drawing on mortality trends and the consequent increases in life expectancy at advanced ages, through indicators of mortality and life expectancy, the analysis explores how variations in the structure and distribution of pension benefits have produced significant territorial disparities. These disparities have, in turn, contributed to widening inequalities in household living conditions, especially regarding access to social assistance and long-term care services. Full article

Managing risk, matching resources efficiently, and ensuring fair allocation are fundamental challenges in both finance and decision-making processes. In many scenarios, participants contribute unequally to collective outcomes, raising the question of how to distribute costs, benefits, or opportunities in a justifiable and optimal manner. This paper applies the Shapley value—a solution concept from cooperative game theory—as a principled tool in the following two specific financial settings: first, in tax cooperation games; and second, in assignment markets. In tax cooperation games, we use the Shapley value to determine the equitable tax burden distribution among three firms, A, B, and C, which operate in two countries, Italy and Poland. Our model ensures that countries participating in coalitions face a lower degree of tax evasion compared to non-members, and that cooperating firms benefit from discounted tax liabilities. This structure incentivizes coalition formation and reveals the economic advantage of joint participation. In assignment markets, we use the Shapley value to find the optimal pairing in a four-buyers and four-sellers housing market. Our findings show that the Shapley value provides a rigorous framework for capturing the relative importance of participants in the coalition, leading to more balanced tax allocations and fairer market transactions. Our theoretical insights with computational techniques highlights the Shapley value’s effectiveness in addressing complex allocation challenges across financial management domains. Full article

The increasing human demand for natural resources is leading to critical resource depletion. This depletion is exacerbated by exceeding the Earth’s biological regeneration rate, threatening ecosystems’ ability to renew biomass. This ecological challenge hinders the potential for simultaneous economic, social, and environmental progress. This study investigates the complex relationships between the USA’s per capita income, energy efficiency innovations, environmental taxation, political stability, and its biocapacity. Using annual data from 1990 to 2024, the paper employs a comprehensive causality testing framework that accounts for the nonlinear nature of the data, as asymmetric effects are observed. This framework includes the Quantile Autoregressive Distributed Lags model (Q-ARDL), the Wald test for parameter consistency, and the Granger-causality in Quantiles test (GC-Q), enabling the estimation of unique parameter vectors for each quantile. A key finding reveals that the impact of per capita GDP on biocapacity is significantly larger than that of other regulatory mechanisms. This suggests that carbon pricing and energy efficiency technologies require widespread implementation to offset the environmental impact of economic growth. The quantile regression reveals complex short-run impacts on biocapacity with persistent positive effects from its lag, contrasting with the diminishing negative influence of GDP and positive influence of energy efficiency at higher quantiles, while long-run analysis shows a consistent negative impact of GDP and varying positive or nonlinear effects of other factors. Granger-causality tests indicate significant unidirectional positive effects from energy efficiency and political stability to biocapacity, a bidirectional relationship for environmental taxes in upper quantiles and GDP across all quantiles. The associated methodological and policy implications aim to assist policymakers in achieving a better balance between the benefits and costs of natural resource use in the USA, promoting sustainable development. Full article

The transportation sector has a significant impact on climate change, as it is responsible for 20% of the global greenhouse gas (GHG) emissions. This paper evaluates the role of electric vehicles (EVs) in achieving Europe’s ambitious target of carbon neutrality by 2050. The limitations of internal combustion engines (ICEs) along with the recent advancements, such as Euro 6 standards, are examined with a pseudo–lifecycle analysis (pseudo-LCA). While ICEs remain cost-effective initially, their higher long-term cost and environmental impact make them unsustainable. The benefits of EVs, including high energy efficiency, minimal maintenance, and reduced GHG emissions, are stated. However, challenges such as range limitations, charging infrastructure, and the environmental cost of battery production persist. Hybrid electric vehicles (HEVs) are highlighted as transitional technologies, offering improved thermal efficiency and reduced emissions, enhancing air quality in both urban and rural areas. The analysis extends to the use of alternative fuels, such as bioethanol, biodiesel, and hydrogen. These provide interim solutions but face scalability and sustainability issues. Policy interventions, including subsidies, tax incentives, and investments in renewable energy, are crucial factors for EV adoption. As EVs are pivotal to decarbonization, integrating renewable energy and addressing systemic challenges are essential for a sustainable transition. Full article

Previous studies have focused on the fact that government policies are the key factors in promoting the development of intelligent construction in construction enterprises. However, how to select different forms of policy support and quantify the intensity of policy support, as well as the impact on the behavioral strategies of construction enterprises and the government, still needs in-depth exploration. This paper constructs an evolutionary game model between construction companies and the government, using the system dynamics simulation software Vensim to analyze the model under three different government policy support scenarios. The study explores how varying levels of policy support and key factors influence the strategic choices of the game participants, providing valuable insights for promoting the development of intelligent construction. The key findings are as follows: (1) The willingness to adopt intelligent construction is heavily dependent on policy incentives. The incentive effect of the three single policies is much lower than that of the combined policies, and only high-intensity special fund support (more than 8 CNY/m²) significantly promotes widespread adoption. Among combinations of policies, tax incentives coupled with special funds prove most effective. (2) The government’s decision to actively promote intelligent construction hinges on a cost–benefit analysis. Under medium to high levels of special fund support, medium to low levels of service support are more beneficial for reaching a stable state of intelligent construction implementation. (3) Reducing the incremental costs of intelligent construction transformation is the primary key factor in promoting construction. The findings contribute to a deeper understanding of how both the government and construction companies can adjust their strategies in response to policy changes, ultimately leading to more effective policy implementation and strategic decision-making. Full article