Search Results (155)

Global retail e-commerce sales have surged, yet product fit uncertainty remains a significant challenge, leading to rising product return rates. To address consumer concerns about return shipping costs, major Chinese online retail platforms have introduced return shipping insurance (RSI). Retailers can choose between Retailer-RSI (RRSI), which is provided by the retailer, and Customer-RSI (CRSI), which is purchased by consumers. Despite these options, information asymmetry causes insurers to assess return rates with bias—referred to as managerial confidence bias. Consequently, platforms are increasingly partnering with insurers to enhance their RSI offerings. This study develops a game-theoretical model to examine the dynamics between a platform and an insurer, as well as the impact of managerial confidence bias on RSI strategies. Our analysis reveals that the platform–insurer relationship is crucial in determining the optimal RSI strategy. Under an independent insurer, RSI is viable only if the insurer underestimates product return rates (i.e., exhibits overconfidence bias); RRSI is preferred if the bias is sufficiently strong, whereas CRSI is chosen otherwise. In contrast, under a dependent insurer, CRSI is favored by the retailer only when its return handling costs are substantially high; otherwise, RRSI is preferred. Furthermore, RSI consistently increases consumer surplus by reducing return hassle costs while only mildly raising the product price. However, the independent insurer’s bias leads to its own profit loss, resulting in a “loss–win–win–win” scenario across stakeholders. In contrast, the dependent insurer, supported by platform subsidies, can yield a “win–win–win–win” outcome that aligns stakeholder interests and enhances long-term platform benefits. Full article

The transition to electric bus (EB) fleets is a critical step towards sustainable urban transportation, offering substantial reductions in greenhouse gas and pollutant emissions relative to diesel buses. However, transit authorities face multifaceted challenges in this transition, including limited driving ranges of EBs, the need for widespread charging infrastructure, and potential strain on the electric grid, alongside opportunities such as governmental subsidies and increased fare revenues. This paper proposes a comprehensive multi-period mixed-integer programming model seeking to optimize long-term EB fleet transition plans in urban contexts while jointly accounting for all inherent financial, technical, and operational factors impacting such a transition. The model is operationalized using real data acquired from Dubai’s Roads & Transport Authority (RTA), encompassing 71 bus routes and a 25-year planning horizon to meet a 100% electrification target by 2050. A scenario-based analysis evaluates the robustness of the transition plans under variations in key operational parameters. The results illustrate that optimized long-term planning yields substantial cost savings and emissions reductions, where the incorporation of environmental and social externalities and revenue shifts causes profit maximization to emerge as a more appropriate objective. In addition, it turns out that adequate dwell time is crucial for cost containment and full fleet electrification feasibility. While RTA targets 100% electrification by 2050, the base case is deliberately relaxed to 90% as certain routes, notably double-decker lines, are incompatible with currently available EB configurations. Nevertheless, full electrification is restored under the minimum dwell scenario. Also, a policy of purchasing only EBs accelerates full fleet electrification by roughly a decade with only a marginal increase in total cost, unlike imposing strict interim electrification targets. The optimized transition plans provide actionable insights for transit authorities balancing economic efficiency with sustainability goals. Full article

Under a dual-carbon background, promoting substantive green innovation in manufacturing enterprises has become a central topic in green transition research. This paper constructs an evolutionary game model involving manufacturing enterprises and consumers under market mechanisms and government intervention to analyze the evolutionary patterns and stability conditions of their strategic choices. Using case data and numerical simulations, it explores the role of government guidance in addressing market failures and fostering green innovation in manufacturing. The findings reveal the following: (1) Under market mechanisms, system evolution is influenced by multiple factors. If enterprises prioritize short-term gains by accelerating symbolic green innovation, consumer trust erodes, leading to a shift toward traditional consumption and ultimately driving the system toward market failure. (2) Under government intervention, incentive subsidies must reach a specific threshold to effectively guide manufacturers toward substantive green innovation. Such subsidies also lower the marginal cost of low-carbon consumption, enhancing consumer willingness to purchase green products. Furthermore, government regulation demonstrates positive promoting effects on the green behaviors of both manufacturers and consumers, with a more pronounced impact on the former. (3) The policy combination of incentive subsidies and government supervision significantly shapes evolutionary trajectories through a synergistic mechanism of “reward incentives and regulatory rigidity.” Policy mismatches may trap the system in market failure. Only when subsidy intensity sufficiently compensates for innovation costs and regulatory capacity exceeds enforcement efficiency thresholds can the system stably evolve toward a substantive green innovation, low-carbon consumption state, fostering a virtuous cycle of supply–demand synergy. Full article

CO₂ enhanced coalbed methane recovery (CO₂-ECBM) using huff-and-puff technology has attracted increasing attention as a promising approach to enhance the productivity of low-productivity coalbed methane (CBM) wells while simultaneously enabling CO₂ storage. However, the economic feasibility of this method and the optimal soaking time remains unclear. In this study, an economic evaluation model for CO₂ huff-and-puff CBM projects was developed based on the discounted cash flow method, incorporating key factors such as CBM price, government subsidies, carbon trading price, CH₄ separation cost, and CO₂ purchase and injection costs. Three representative scenarios were designed to evaluate the impacts of policy support and market conditions. The effects of CO₂ injection volume and soaking time on net cash flow (NCF), net present value (NPV), and dynamic payback period (DPP) were systematically investigated. The results indicate that CO₂ huff-and-puff is economically viable for enhancing CBM recovery. Increasing CO₂ injection volume markedly improves CH₄ production and project revenue, but also leads to higher initial investment and a longer payback period. The economic performance exhibits a non-monotonic dependence on soaking time, with an optimal range that maximizes NPV. Specifically, the optimal soaking time ranges from 30 to 60 days for injection volumes up to 2000 t, and from 60 to 90 days for higher injection volumes. External economic factors exert a strong influence on project performance: higher carbon trading prices and lower CO₂ purchase costs markedly improve profitability, while government subsidies effectively increase net returns and shorten the payback period. In the absence of subsidies, higher injection volumes are required to maintain economic viability. Overall, this study provides a comprehensive economic evaluation framework for CO₂ huff-and-puff CBM projects, identifies key operational and economic parameters for optimizing project performance, and offers theoretical support for field-scale applications. Nevertheless, the economic evaluation is based on deterministic numerical simulation results and simplified market assumptions. Long-term operational risks and geological heterogeneity are not explicitly considered, which may limit the applicability of the results under field conditions. Full article

As a core decarbonization technology, the scaling up of Near-Zero Energy Building (NZEB) technologies under the “dual carbon” goal necessitates collaboration among governments, technology suppliers, and construction enterprises. However, high research and development (R&D) costs coupled with low market acceptance impede widespread adoption. This study develops a tripartite evolutionary game model to analyze strategic interactions among stakeholders. Using MATLAB 2022B simulations, we simulate the strategy sets for the government (subsidize/no subsidy), suppliers (R&D/no R&D), and enterprises (procure/no purchase). The results identify two Evolutionary Stable Strategies (ESS): a market-driven ESS (0, 1, 1) emerges when the green premium (Pm) exceeds the incremental cost (Cb); while a policy-driven ESS (1, 1, 1) requires government subsidies (S) to offset R&D gaps, specifically when $S>Cr/\alpha -Pmz$. These findings provide a theoretical basis for understanding the synergistic mechanisms underlying NZEB adoption and highlight the dynamic interplay between policy incentives and market forces. Full article

Driven by the global agenda of low-carbon urban development, local governments in China have implemented targeted policies requiring new energy vehicle adoption in the ride-hailing industry. This study focuses on a key issue in the development of sustainable smart public transportation systems: the factors affecting the acceptance of electric vehicles (EVs) in ride-hailing services among full-time and part-time drivers. Using 432 valid samples of ride-hailing drivers from Zhangzhou, a third-tier city in China, we compared the basic personal attributes of full-time and part-time drivers. Ordered logit models were developed to explore differences in factors influencing their acceptance of electric ride hailing (ER). Findings reveal: (1) Drivers’ perceived significance of EVs in green transportation is positively associated with their acceptance of ER. (2) Endurance mileage and charging efficiency have no significant effect on acceptance among drivers in underdeveloped cities. (3) Full-time drivers exhibit relatively low concern for subsidy policies, whereas part-time drivers express a pressing need for vehicle purchase subsidies and operational subsidies. (4) Overall, part-time drivers demonstrate higher acceptance of ER than full-time drivers. Based on these findings, this paper offers policy recommendations for governments to enhance ER acceptance among both driver groups. It is important to note that the present study utilizes survey data collected from Zhangzhou. The research conclusions should be treated with caution when applied to other cities, and further studies can be conducted in different regions to verify the results. Full article

As the electrification of transportation systems accelerates, incentivizing electric vehicle (EV) participation in vehicle-to-grid (V2G) operations is becoming increasingly crucial. This paper introduces a dynamic EV charging and discharging strategy that incorporates integrated energy station (IES) congestion and electricity purchase and sale scenarios. The proposed strategy seeks to facilitate orderly EV charging and discharging within a real-time simulation framework that integrates the transportation network (TN), IES, and the external grid (EG). First, we develop a real-time collaborative simulation framework that combines microscopic traffic flow (MTL) and IES–grid energy interaction models to account for mutual feedback among these components. Second, we propose an EV IES selection strategy aimed at maximizing discharge revenue, which takes into account various factors, including driving distance, time costs, battery degradation, discharge benefits, and government subsidies. Finally, we design a dynamic discharge pricing model based on real-time vehicle arrival patterns at the IES and the status of electricity purchases and sales. Simulation results show that the EV IES selection strategy, optimized for discharge revenue, reduces average user waiting time by 5.36%, decreases network time loss by 3.86%, and increases EV discharge revenue by 6.79%. Furthermore, the introduction of dynamic pricing leads to additional reductions in waiting time and network time loss by 3.46% and 4.80%, respectively. The proposed mechanism and pricing strategy effectively mitigate traffic congestion, enhance user discharge revenue, and provide flexible scheduling options for IES operations. Full article

This study explores Nigeria’s bioenergy industry’s potential in reducing unemployment. It focuses on two objectives: first, to determine how the development of the bioenergy sector can reduce Nigeria’s unemployment rate, and second, to identify effective policy instruments to harness the potential of the bioenergy industry in Nigeria. Using a Forest and Agricultural Sector Optimization Model for Nigeria, this study modeled three scenarios with varying labor wage rates. The second scenario used an hourly wage of US$0.38/h for US$3.00 purchasing power parity (PPP), reflecting the International Labor Organization’s global minimum PPP. The first and third scenarios applied prices slightly below and well above the PPP at the rate of US$0.32/h for US$2.56 PPP and US$1.04/h for US$8.30 PPP, respectively. This was modeled against the baseline labor rate (Nigeria’s minimum wage of 45 USD/month, approximately US$0.28/h, equivalent to 70,000 NGN). Nigeria’s current energy and food security targets and policies are also implicitly implemented. The product-demand driver is the Nigerian population data projection, which aligns with the Shared Socioeconomic Pathways (SSPs) for Scenario 2. Results reveal that while increases in the labor wage rate improve labor welfare above the global poverty threshold, they also impact the bioenergy sector and the aggregated total economic welfare. Results highlight an optimal wage balance where employment growth in the bioenergy sector can be sustained without compromising production capacity or aggregated total welfare. Based on these insights, actionable policy implications from this study include implementing moderate wage growth, subsidies, and productivity investments to maximize bioenergy’s potential as a sustainable employment generator in Nigeria. Full article

This study explores changes in the transmission patterns between domestic and global grain prices under different grain price regulation policies. Price transmission is influenced by both policy interventions and external market dynamics. We conducted a segmented regression analysis to examine these relationships. The analysis focuses on how changes in international grain prices are transmitted to domestic prices before and after key policy adjustments. We interpret the results as shifts in price transmission coefficients across different policy regimes rather than as definitive causal impacts of specific policies. The study focuses on four major grains: wheat, rice, corn, and soybeans. We evaluated policy tools such as minimum purchase prices, temporary storage programs, target pricing mechanisms, and producer subsidies. Our findings show that the correlation between international and domestic grain prices became more strongly positive after specific policy changes. These changes include the introduction of the wheat minimum purchase price in 2006, the implementation of temporary storage for corn and soybeans in 2008, and the shift to producer subsidies for corn in 2016. These results indicate a shift towards more interconnected and resilient price transmission within the grain market system. In contrast, before the reduction in the rice minimum purchase price in 2018, international rice prices exhibited a slightly negative association with domestic prices. This negative association became more pronounced after the policy change. A similar shift occurred for soybeans, where the transmission pattern of global prices shifted from positive to negative following the adjustment of soybean price regulations in March 2017. These findings provide guidance for optimizing national grain pricing policies and strengthening the overall resilience and adaptability of food security systems, with an emphasis on their complex, interrelated nature. Full article

The role of poverty, specifically the urban poor, in shaping the urban landscape is often solely linked to slums and informal settlements in urban centers. However, contrary to this common perception, this study aims to elucidate how urban poor residents contribute to shaping urban sprawl in developing countries. After identifying patterns of urban sprawl and poverty in the Jakarta Metropolitan Area (JMA) in Indonesia, the study used the Structural Equation Model (SEM) method to analyze survey data from 195 respondents with a per capita income of less than USD 2.15 (IDR 34,000) daily in Tangerang Regency, a western suburb of the JMA. This study shows that urban sprawl and poverty concentration overlap. The urban poor contribute to urban sprawl by purchasing affordable land on the urban periphery, traveling there with their motorized vehicles, and taking advantage of government subsidies. However, rather than gaining more land, they face increased public service costs, a lack of basic facilities, and habitat destruction. Most respondents own their own homes, but almost half of the respondents (41.54%) state that these homes are less than 48 m² in size. It can be concluded that economically vulnerable populations can contribute to urban sprawl when confronted with ineffective planning institutions. Full article

Additive manufacturing (AM), or 3D printing, has a significant, largely beneficial influence on climate change by decreasing material waste and requiring less energy use. The application of AM in the construction and industrial sectors has the potential to reduce carbon emissions. This goal may be accomplished by using material and energy-saving measures, improving manufacturing processes, designing lightweight structures, and reducing transportation operations. While 3DP has the potential to help reduce environmental degradation, it is crucial to recognize the inherent setbacks associated with the technology. Certain AM processes have the potential to emit volatile organic compounds, which contribute to air pollution and hence need improved control. Industrial 3D printers can be excessively expensive, greatly increasing the initial expenditure required to begin a project. Despite these limitations, AM can reduce greenhouse gas emissions, generate better-built environments, and provide a means to reduce energy usage while supporting global carbon neutrality objectives. Governments should extend financial assistance in the form of subsidies to help reduce equipment purchase costs. Furthermore, AM’s capacity to foster a circular economy and minimize overall environmental effects is dependent on the improvement of material recycling and scalability. Full article

Determinants of consumers’ decisions in the electric vehicle market are dictated by many factors, starting from ecology to the profitability of owning an electric vehicle. Currently, the electric vehicle market in Poland grows every year. When addressing the issues related to the determinants of consumer decisions on the electric vehicle market, statistical data and an online questionnaire were used, in which 103 people, who were interested in electric vehicles, participated. The main purpose of this research was to determine what factors influence consumers’ attitude to the purchase of electric vehicles the most. The study focuses primarily on Battery Electric Vehicles (BEVs), as reflected in the survey design and respondents’ interpretations of electric vehicles. The study showed that over half of the respondents are considering the purchase of an electric vehicle, and to purchase this type of car they would be more encouraged by financial support, such as subsidies from the state and tax relief, as well as free parking spaces in cities. It was also established that consumers are discouraged from buying electric vehicles by the lack of adequate infrastructure in cities needed to freely own an electric vehicle, as well as too high prices of these cars and the long time it takes to charge the battery. Full article

This study aims to provide a comprehensive and realistic evaluation of consumer and external costs associated with commercially available passenger cars. The central research question is: How do Total Cost of Ownership (TCO) and external costs differ between conventional vehicles, Battery Electric Vehicles (BEVs), and Fuel Cell Electric Vehicles (FCEVs) across various vehicle segments? The methodological approach includes the selection of 55 commonly registered vehicle variants in Germany and the calculation of TCO and external costs over a 16-year vehicle lifetime. TCO components include purchase price, governmental subsidies, remaining value, fuel or energy expenses, maintenance, insurance and taxes. External costs incorporate emissions, land use and the societal costs from purchase bonuses. Apart from the large quantity of considered vehicles and the depth of investigation, this study’s main contribution is the consideration of tax revenue as a negative external cost. The results show that BEVs consistently exhibit the lowest TCO and external cost across all segments. For example, a BEV in the E segment has 26% lower TCO and 14,300 € lower external cost than an equivalent diesel vehicle. FCEVs show competitive results in both TCO and external costs, though limited by market availability. While higher in TCO, vehicles in higher segments generally lead to lower external cost due to higher tax revenue. The findings support the economic and ecological advantages of BEVs, which should therefore be primarily considered by consumers and policy-makers. Full article

The energy transition is an essential process for mitigating the effects of climate change in a global context where recent conflicts threaten energy security. Municipalities play an increasing role in achieving the decarbonization targets set at a national level, but they need effective tools to identify the most appropriate actions and policies for achieving quantitative targets. Among the tools available, energy models allow us to represent the evolution of the energy system under different boundary conditions or constraints and defining the least-cost pathways for sustainable development. The aim of this paper is to demonstrate the usefulness of a bottom-up modeling approach in the framework of the ETSAP TIMES model generator to represent and optimize the local-scale energy system of the city of Tito in Southern Italy, with a particular focus on the residential and tertiary sectors. The optimization of a Business-as-Usual reference scenario over a thirty-year time horizon (2020–2050) shows an initial situation based on the prevalent use of natural gas. The sensitivity analysis carried out by gradually increasing the cost of natural gas and providing subsidies for the purchase of heat pumps shows a 92% reduction in fossil fuel consumption and a 60% for CO₂ emissions as early as 2030. Full article

A strategic fulcrum for leading high-quality economic development and shaping the nation’s future. Core competitiveness lies in how governments can effectively stimulate consumer demand for green consumption and motivate enterprises to pursue green technology innovation through the development of precise and efficient innovative regulation models. In this paper, a tripartite evolutionary game model is constructed based on evolutionary game theory, encompassing the government, enterprises, and consumers. We analyze the strategic interactions and evolutionary path among these three entities under conditions of bounded rationality and information asymmetry. The research reveals the following: (1) the government can effectively guide enterprises towards genuine green innovation through enhanced rewards for substantive innovation and increased penalties for strategic innovation; (2) consumer purchasing decisions are significantly shaped by economic benefits, perceived social value, and government subsidies, with their market choices forming a critical external supervisory force; and (3) government regulatory strategies are dynamically adjusted in response to market integrity levels and social welfare, with a tendency to implement innovative regulation when “greenwashing” risk is elevated. In conclusion, simulation analysis is conducted using MATLAB 2018a, and governance recommendations are offered based on three dimensions: precise government regulation, enhanced corporate responsibility, and enhanced consumer capabilities. These recommendations offer both a theoretical basis and a practical path for establishing an integrated green innovation governance system based on incentive constraint empowerment. Full article