Search Results (316)

Against the growing global focus on green development, government subsidies are widely recognized as a crucial policy tool to promote firms’ green transformation. In competitive markets, green investment decisions are jointly shaped by supply chain power structures, and different research and development (R&D) leadership can yield distinct policy outcomes. This study develops a Bertrand competition model of a green supply chain with one manufacturer and two competing retailers, comparing two structures: manufacturer-led R&D (SM) and retailer-led R&D (SR). We examine how these policies affect pricing decisions, product greenness, and revenues. Under the retailer-led R&D, a green cost-sharing ratio is introduced to capture the interaction between internal coordination and government support. The results show that subsidy effects depend on consumer green awareness. When green awareness is low, subsidies mainly raise prices through cost pass-through. When green awareness is high, subsidies can lower prices by stimulating demand. In addition, the interaction between subsidy intensity and cost sharing leads to non-monotonic changes in retailers’ revenues. By comparing different market structures and parameter settings, we identify the conditions under which SM or SR dominates in terms of prices, product greenness, and revenues, providing guidance for more flexible green subsidy design. Full article

Blockchain technology can enhance traceability and trust in contract farming supply chains, yet high implementation costs deter adoption by supply chain participants. This study examines the synergistic mechanisms between blockchain adoption strategies and government subsidy policies. We develop a multi-stage Stackelberg game model involving an agricultural enterprise, an e-commerce platform, and a government, and comparatively analyze six decision-making scenarios across non-subsidy, unilateral subsidy, and full-chain subsidy settings. Three key findings emerge. First, blockchain investment has a cost–effect threshold below which consumer traceability preferences do not translate into profit gains. Second, well-designed subsidies overcome investment inertia and yield Pareto improvements in both profits and social welfare, with the full-chain subsidy model (Model BG) maximizing social welfare; however, subsidies exhibit distinct efficiency boundaries, and over-subsidization causes resource misallocation. Third, both supply chain parties tend to free-ride on the other’s investment, creating strategic conflicts that necessitate differentiated subsidy mechanisms tailored to specific dominance structures. These findings provide policy guidance for facilitating agricultural digital transformation and enhancing supply chain coordination. Full article

Policy instability and regulatory barriers remain key obstacles to the long-term viability of agriphotovoltaics (APV) deployment. The Penthéréaz case in Switzerland provides empirical evidence of how cooperative governance and collective self-consumption can restore project feasibility after subsidy withdrawal. Using a single-case study and process-tracing approach based on cooperative documentation and regulatory records, the analysis explains how Penthéréaz Énergie Photovoltaïque S.A. cooperative (PEP)., initially structured as a subsidy-dependent venture, transitioned into a resilient collective self-consumption network supported by a private micro-grid. Following the withdrawal of federal feed-in tariffs, the project faced major economic risk and responded through decentralized financial restructuring, including community-funded debt at a 2% interest rate. The installation comprises 1180 photovoltaic panels with an installed capacity of 283 kWp, producing approximately 290,000 kWh per year while providing water-tightness and light permeability for agricultural infrastructure. The findings further indicate that operational success contributed to Swiss regulatory adjustments, enabling private distribution networks to cross public roads and secure geographic continuity for local energy sharing. With a reported self-consumption rate of 40% across a diversified user base including agri-food and residential consumers, the case demonstrates the operational value of local load-matching. The findings propose six context-dependent lessons derived from a single case, emphasizing governance capacity, tariff risk management, regulatory adaptability, and demand-oriented system design. Full article

The development of the new energy vehicle (NEV) industry has become a key driver of the global low-carbon transition. Understanding the policy effect on NEV diffusion is essential to promote sustainable growth. In this study, we propose a new approach that combines a two-layer small-world network involving consumers and enterprises and evolutionary game theory to study the diffusion effect of industrial and trade policies on enterprises’ low-carbon production strategies and consumer preferences. Different from existing diffusion models, we integrate reinforcement learning (RL) into the decision-making process of enterprises and use SHapley Additive exPlanations (SHAP) to decode the micro-level decision logic of enterprises. In terms of the decision-making mechanism, the simulation results show that the Q-learning algorithm better fits the real market diffusion trend of NEVs compared with traditional algorithms; in terms of policy effects, industrial policies and trade policies exhibit a synergistic effect. SHAP analysis reveals that enterprises are more concerned about NEV market maturity than the impact of policy parameters on decision-making; Sobol sensitivity analysis indicates that consumer subsidies have a greater impact on the market diffusion of NEVs than trade policies. Full article

The widespread adoption of solar energy storage systems is transforming the global energy landscape, enabling more efficient use of renewable resources and enhancing energy resilience. The integration of residential batteries significantly enhances energy efficiency and sustainability by facilitating the storage of surplus renewable energy, providing reliable backup during power outages, and optimising energy consumption. This study explores the factors influencing end-user adoption of batteries, utilising the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) as a guiding framework to analyse adoption behaviours and determinants. This study employs a qualitative approach using semi-structured interviews with stakeholders divided into three categories: regulatory authorities, industry experts, and end-users. This study highlights key factors influencing battery adoption, such as energy independence, grid reliability, and environmental impact, while addressing challenges like regulatory inconsistencies and installer training. Study extends UTAUT2 to residential battery adoption, emphasising performance expectancy, facilitating conditions, and price value in decision-making and makes a methodological contribution by validating deeper qualitative insights into renewable technology adoption. The practical implications emphasise the need for designing targeted policies, such as subsidies and net metering, alongside developing user-centric systems that enhance affordability, usability, and consumer awareness to facilitate residential battery adoption. Full article

Urban and peri-urban agriculture (UPA) has emerged as a critical strategy to address multidimensional urban challenges, including food insecurity, environmental degradation, and social inequality. Despite its potential benefits, UPA occupies a marginal position in municipal governance frameworks. Understanding how public policies and social influence mechanisms shape consumer behavior and producer viability requires a systems-thinking approach capable of capturing complex socio-economic-ecological interactions. Therefore, we developed an agent-based model (ABM) following the ODD + D protocol to simulate urban agriculture market dynamics, incorporating producer and consumer agents within a spatially explicit grid environment representing the urban landscape. We implemented three policy interventions and conducted six complementary experiments. Education campaigns achieved the highest local market share, demonstrating strict Pareto dominance over all subsidy-based strategies. Production subsidies yielded equivalent outcomes but at a fiscal cost, reducing producer income inequality (Gini). Stress tests revealed moderate resilience to production shocks. The findings demonstrate the power of agent-based modeling to uncover policy dynamics in complex urban food systems, providing actionable evidence for sustainable urban governance. Full article

Driven by the “dual carbon” goal and the strategy for cultivating new productive forces, China’s economy is undergoing a crucial transformation from high-speed growth to high-quality development. As a typical high-energy consumption and high-emission sector, the green and low-carbon transformation of the building materials industry directly affects the optimization of the national energy structure and the realization of ecological goals. However, traditional building material enterprises generally face practical challenges such as low resource utilization efficiency, insufficient digitalization and greening integration of the industrial chain, and weak green innovation momentum. The transformation actions of a single entity are difficult to break through systemic bottlenecks, and it is urgently necessary to establish a dynamic evolution mechanism involving multiple entities in collaboration. This paper aims to explore the evolutionary rules and stability of digital green (DG) transformation strategies of building materials enterprises (BMEs) under multi-agent interactions involving government, universities, and consumers. Centering on BMEs, a four-party evolutionary game model among the government, enterprises, universities, and consumers is constructed, and the evolutionary processes of strategic behaviors are characterized through replicator dynamic equations. Using MATLAB R2022 (Version number: 9.13.0.2049777) bnumerical simulations, this study investigates how key parameters, such as government subsidies, penalty intensity, and consumers’ green preferences, affect the transformation pathways of enterprises. The results reveal that the DG transformation behavior of BMEs is significantly influenced by governmental policy incentives and universities’ knowledge innovation. Stronger subsidies and penalties enhance enterprises’ willingness to adopt proactive DG strategies, while consumers’ green preferences further accelerate transformation through market mechanisms. Among multiple strategic combinations, active DG transformation emerges as the main evolutionarily stable strategy. This study provides a systematic multi-agent collaborative analysis framework for the transformation of BME DG, revealing the mechanisms by which policies, knowledge, and market demands influence enterprise decisions. Thus, it offers theoretical and decision-making references for the green and low-carbon transformation of the building materials industry. 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

The rise of “Internet + Recycling” platforms is transforming the domestic waste management landscape, creating dual-channel reverse supply chains where new platforms interact with traditional recyclers. However, these platforms face critical strategic decisions regarding their service portfolios (convenient but costly door-to-door vs. economical fixed-point drop-off) and their relationship with incumbents (cooperation vs. competition). This study aims to determine the optimal pricing, service level, and relationship strategies for an “Internet + Recycling” center to maximize profitability under the influence of consumer channel preferences and government subsidies. We developed four Stackelberg game-theoretic models representing different scenarios of service modes (fixed-point only vs. fixed-point with door-to-door) and relationship structures (cooperation vs. competition). We derived equilibrium solutions for recycling prices, service levels, and profits. Our results reveal that while cooperation generally leads to higher systemic profits, the addition of a door-to-door service significantly alters the strategic landscape. We find that a higher consumer preference for the platform channel allows the center to lower prices while increasing profits, and that government subsidies are the most effective at enhancing service levels in cooperative models. Crucially, intense competition incentivizes recycling centers to reduce rather than increase their service levels to cut costs. This research provides a decision-making framework for recycling enterprises to select optimal service and competitive strategies. It also offers insights for policymakers on how to design subsidies to effectively promote high-convenience recycling services and foster a more efficient circular economy. Full article

This study develops a carbon emissions reduction strategy for solar-powered coffee machines in Taiwanese convenience stores, aiming to strike a balance between profitability and decarbonization. An integrated framework of the fuzzy nonlinear multi-objective programming (FNMOP) model, Sobol sensitivity analysis, and Monte Carlo simulation was applied to quantify uncertainties in electricity supply, consumer demand, and investment costs. Solar-powered machines reduce annual CO₂ emissions by 172–215 kg per store. Allocating 0.49–0.61% of coffee profits as subsidies shortens payback to [6.5, 9.375] years. Monte Carlo simulation confirms robustness with a 95% confidence interval of [5.8, 11.2] years, while urban stores achieve payback 18–25% faster. Sobol analysis identifies annual savings and net profit margins as key drivers. The framework demonstrates scalability and international applicability, providing empirical evidence for policymakers and retailers to accelerate the adoption of renewable energy in consumer-facing operations. Its methodological integration and consumer-side focus offer a replicable model for convenience store chains in high-density retail markets worldwide, with potential multiplier effects across sectors and supply chains. Full article

The current retired recycling system suffers from “systemic coordination failure”, primarily due to ambiguous responsibility boundaries hindering interenterprise collaboration, unequal profit distribution discouraging technological innovation investment, and low participation from both consumers and recycling enterprises undermining the efficiency of recycling channels. However, the simplified tripartite game models commonly adopted in existing research exhibit significant limitations in explaining and addressing the above practical challenges, as they fail to incorporate consumers and third-party recyclers as strategic decision-makers into the analytical framework. To address these issues, this study develops, for the first time, a five-party evolutionary game model involving governments, vehicle manufacturers, battery producers, third-party recyclers, and consumers within a reverse supply chain framework. We further employ system dynamics to simulate the dynamic evolution of stakeholder strategies. The results show that: (1) When tri-party synergistic benefits exceed 15, the system transitions from resource dissipation to circular regeneration. (2) Government subsidies reaching the threshold of 2 effectively promote low-carbon transformation across the industrial chain. (3) Bilateral synergistic benefits of 12 can stimulate green technological innovation and industrial upgrading. (4) Establishing a multi-stakeholder governance framework is key to enhancing resource circulation efficiency. This research provides quantitative evidence and policy implications for constructing an efficient and sustainable power battery recycling system. 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

European Union legislation, particularly Council Directive 2004/113/EC, mandates gender neutrality in credit scoring to prevent discrimination. However, this creates a regulatory paradox if gender is a statistically relevant predictor of default risk. This study investigates this “fairness-through-unawareness” approach by empirically testing for systematic mispricing. We employ a twofold econometric analysis on a dataset of consumer loans from a Lithuanian peer-to-peer platform. After data preparation for the regression, the sample consists of 9707 loans. First, logistic regression is used to model actual default risk, controlling for credit rating, age, loan amount, and education. Second, Ordinary Least Squares (OLS) regression is used to model the interest rate set by the platform. The Logit model finds that gender is a highly significant predictor of default (p < 0.001), with male borrowers associated with a higher probability of default. Conversely, the OLS model finds that gender is not a statistically significant factor in loan pricing (p = 0.263), confirming the platform’s compliance with EU law. The findings empirically demonstrate the regulatory paradox: the legally compliant, gender-blind pricing model fails to account for a significant risk differential. This leads to systematic risk mispricing and an implicit cross-subsidy from lower-risk female borrowers to higher-risk male counterparts, highlighting a critical tension between regulatory intent and outcome fairness. The analysis is limited to observed loan-level characteristics; it does not incorporate household composition or the internal structure of the platform’s proprietary scoring model. Full article

Blockchain technology is increasingly adopted in supply chains to record product carbon footprints and environmental attributes on tamper-resistant ledgers. By improving the transparency and verifiability of emission-related information for governments, firms and consumers, blockchain reshapes the incentive effects of environmental taxes and subsidies that target emission abatement. This paper presents a government-manufacturer-consumer tripartite game model to analyze the abatement effects of tax and subsidy policies and their differences under heterogeneous consumer demand in a blockchain-driven framework. The results indicate that: (1) Both subsidy and tax policies can facilitate environmental improvement. When consumers’ green preference exceeds a specific threshold $X^{*}/\left(1+\gamma \right)$, the greenness of the tax policy is superior to that of the subsidy policy, and vice versa. (2) Under blockchain technology, tax and subsidy instruments differentially affect the profits of conventional and green manufacturers, shifting profits from high-emission sectors to green sectors. (3) The improvement of consumers’ environmental awareness can gradually reduce the implementation of the policy, urge enterprises to reduce emissions, and improve their profits. Nevertheless, the privacy concerns associated with blockchain technology present a significant obstacle to the effective implementation of carbon emission reduction strategies. Full article

(1) Background: Public service platforms (PSPs) have become increasingly popular for delivering public services. Typically, their fixed pricing and subsidy strategies overlook the participation of various stakeholders, resulting in inefficient supply of public services. This study aims to use China’s eldercare services as an example to examine its dynamic pricing and subsidy strategies. (2) Methods: Game theory was utilized to develop a two-level Stackelberg game framework considering the decision-making sequences among stakeholders with competing objectives. On this basis, the two-level Stackelberg game was solved based on the maximization of social welfare, platform profit, and utility, pursued by the government, private sector, and service providers, respectively. (3) Results: The service supply duration is determined by the service price. Specifically, when the service price falls within an appropriate range, the optimal supply duration increases with the service price. The results further show that the optimal service price increases with the platform’s commission rate but declines with government subsidies. Furthermore, the optimal government subsidy increases with the platform’s commission rate in a balanced market. By contrast, in an unbalanced market, where demand is either below the minimum supply or above the maximum supply, the government will withdraw subsidies entirely once the commission rate exceeds a certain threshold, thereby curbing excessive commission charges. (4) Conclusions: This study contributes to the body of knowledge of platform development by examining PSPs’ dynamic pricing and government subsidy strategies. Practically, this two-level Stackelberg game framework for PSPs will help improve the efficiency of public services provision for consumers and maximize social welfare and platforms’ profit for the government and private sector, respectively. Full article