Search Results (110)

Against the backdrop of China’s “dual-carbon” goals, the complex interplay between fiscal decentralization and green taxation presents significant challenges for climate governance. This study examines the impact of green taxation on carbon emissions within the context of fiscal decentralization, with a particular focus on spatial spillover effects and multidimensional indicators of fiscal decentralization. Drawing on panel data from 30 Chinese provinces between 2007 and 2022, we apply spatial Durbin and moderating effect models to examine these relationships. Our findings reveal a counterintuitive positive association between green taxation and carbon emissions, indicating the presence of a “green paradox.” Furthermore, the three dimensions of fiscal decentralization—revenue decentralization, expenditure decentralization, and fiscal autonomy—demonstrate heterogeneous relationships with carbon emissions, including inverted U-shaped, U-shaped, and linear patterns, respectively. The interaction effects between green taxation and fiscal decentralization also exhibit notable spatial spillover effects and emission reduction potential. The contribution of this study lies in its integrated analysis of multidimensional fiscal decentralization, spatial econometric methods, and underlying mechanisms, thereby addressing underexplored dimensions of China’s environmental fiscal policy. These findings not only provide policy insights for China but also offer valuable references for other developing and transitional economies striving to align fiscal and environmental governance. Full article

As one of the main sources of global greenhouse gas emissions, the low-carbon transformation and emission reduction in the construction industry are inevitable requirements for addressing climate change. Under cap-and-trade regulations, Carbon emission rights have become a key production factor. However, the price of carbon emission rights is highly random. Taking the EU carbon market in 2024 as an example, the carbon price fluctuated by more than 35%, soaring from 65 euros per ton to 80 euros per ton and then falling back. Such sharp fluctuations not only increase the cost uncertainty of enterprises but also complicate the investment decisions for emission reduction. Therefore, enterprises can enhance the flexibility of carbon emission rights trading decisions through option strategies, helping them hedge against the risks of carbon price fluctuations, and at the same time improve market liquidity and risk management capabilities. Against this background, based on the carbon cap-and-trade policy, this paper introduces the two-way option strategy into the construction supply chain game model composed of general contractors and subcontractors, and studies to obtain the optimal carbon reduction volume, carbon option purchase volume, maximum expected profit of general contractors, subcontractors and profit distribution ratio. This study shows that two-way options play a crucial role in optimizing supply decision-making and emission reduction strategies. Under the decentralized model, emission reduction responsibilities are often shifted to subcontractors by the general contractor, resulting in a decline in overall mitigation effectiveness. Furthermore, appropriately lowering the carbon emission benchmark can strengthen enterprises’ incentives for emission reduction and significantly enhance the profitability of the supply chain. The study further suggests that general contractors should enhance their competitiveness by developing environmentally friendly technologies and improving their ability to reduce emissions on their own. Meanwhile, subcontractors need to actively participate in the collaborative efforts through revenue-sharing contracts. This study reveals the strategic value of two-way carbon options in construction supply chain carbon trading and provides theoretical support for the formulation of carbon market policies, contributing to the low-carbon transition of the construction supply chain. Full article

In the face of economic, social, and environmental pressures, the issue of sustainable development has garnered widespread attention in the Logistics Service Supply Chain (LSSC) with risk attitudes under Technical Output Uncertainty. In this regard, this paper first constructs an optimal emission reduction investment game model for an LSSC composed of Logistics Service Integrators (LSIs) and Logistics Service Providers (LSPs) against the backdrop of Technical Output Uncertainty. To this end, it quantifies the participants’ risk attitudes using a mean-variance model to analyze optimal emission reduction investment decisions for centralized and decentralized LSSC under different levels of risk tolerance. Subsequently, it designs a joint contract with altruistic preferences for sharing emission reduction costs in the LSSC. This contract analyzes the parameter constraints for achieving Pareto optimization within the supply chain. Finally, the study employs a case simulation to analyze the changes in expected revenues for centralized LSSC and joint contracts under different risk tolerance levels. The study reveals that (1) in a centralized LSSC, under risk-neutral attitudes, there exists a unique optimal emission reduction investment, which yields the highest expected return from emission reduction. However, under risk-averse attitudes, the expected return is always lower than the optimal expected return under risk neutrality. (2) In a decentralized LSSC, the emission reduction investment decisions of the Logistics Service Providers are similar to those in a centralized LSSC. (3) Under risk-neutral attitudes, the cost-sharing and altruistic preference-based joint contract can also coordinate the risk-averse LSSC under certain constraints, and by adjusting the cost-sharing and altruistic preference parameters, the expected returns can be reasonably allocated. Full article

This study examines how contract structures influence coordination and innovation incentives in dual-channel telecommunications supply chains. We consider a setting where a mobile network operator (MNO) supplies services both directly to consumers and indirectly through a mobile virtual network operator (MVNO), which competes in the retail market. Using a game-theoretic framework, we evaluate how different contracts—single wholesale pricing, revenue sharing, and quantity discounts—shape strategic decisions, particularly in the presence of investment spillovers between parties. A key coordination problem emerges from the externalized gains of innovation, where one party’s investment generates value for both participants. Our results show that single wholesale and revenue sharing contracts often lead to suboptimal investment and profit outcomes. In contrast, quantity discount contracts, especially when combined with appropriate transfer payments, improve coordination and enhance the total performance of the supply chain. We also find that innovation led by the MVNO, while generally less impactful, can still yield reciprocal benefits for the MNO, reinforcing the value of cooperative arrangements. These findings emphasize the importance of contract design in managing interdependence and improving efficiency in decentralized supply chains. This study offers theoretical and practical implications for telecommunications providers and policymakers aiming to promote innovation and mutually beneficial outcomes through well-aligned contractual mechanisms. Full article

In the context of global climate governance and the low-carbon energy transition, virtual power plant (VPP), a key technology for integrating distributed energy resources, is urgently needed to solve the problem of decentralization and lack of synergy in electricity, carbon, and green certificate trading. Existing studies mostly focus on single energy or carbon trading scenarios and lack a multi-market coupling mechanism supported by blockchain technology, resulting in low transaction transparency and a high risk of information tampering. For this reason, this paper proposes a synergistic optimization strategy for electricity/carbon/green certificate virtual power plants based on blockchain cross-chain transactions. First, Latin Hypercubic Sampling (LHS) is used to generate new energy output and load scenarios, and the K-means clustering method with improved particle swarm optimization are combined to cut down the scenarios and improve the prediction accuracy; second, a relay chain cross-chain trading framework integrating quota system is constructed to realize organic synergy and credible data interaction among electricity, carbon, and green certificate markets; lastly, the multi-energy optimization model of the virtual power plant is designed to integrate carbon capture, Finally, a virtual power plant multi-energy optimization model is designed, integrating carbon capture, power-to-gas (P2G) and other technologies to balance the economy and low-carbon goals. The simulation results show that compared with the traditional model, the proposed strategy reduces the carbon emission intensity by 13.3% (1.43 tons/million CNY), increases the rate of new energy consumption to 98.75%, and partially offsets the cost through the carbon trading revenue, which verifies the Pareto improvement of environmental and economic benefits. This study provides theoretical support for the synergistic optimization of multi-energy markets and helps to build a low-carbon power system with a high proportion of renewable energy. Full article

Decentralized blockchains have grown into massive and Internet-scale ecosystems, collectively securing hundreds of billions of dollars in value. The complex interplay of technology and economic incentives within blockchain systems creates a delicate balance that is susceptible to significant shifts even from minor changes. This paper underscores the importance of conducting thorough, data-driven studies to monitor and understand the impacts of significant shifts in blockchain systems, particularly focusing on Ethereum’s groundbreaking builder–proposer separation (PBS) as a pivotal innovation reshaping the ecosystem. PBS revolutionizes Ethereum’s block production, entrusting builders with block construction and proposers with validation via blockchain consensus, with significant impacts on Ethereum decentralization, fairness, and security. Our empirical study reveals key insights, including the following: (a) A substantial 261% increase in proposer revenue underscores the effectiveness of PBS in promoting widespread adoption, significantly enhancing block rewards and proposer incomes. (b) The small profits garnered by builders, comprising only a 3.5% share of block rewards, raise concerns that the security assumptions based on builder reputation may introduce new threats to the system. (c) PBS promotes a more equitable distribution of resources among network participants by reducing proposer centralization and preventing centralization trends among builders and relays, thereby significantly enhancing fairness and decentralization in the Ethereum ecosystem. This study provides a comprehensive analysis of the dynamics of Ethereum PBS adoption, exploring its effects on revenue redistribution among various participants and highlighting its implications for the Ethereum ecosystem’s decentralization. Full article

This study describes the step-by-step development of a simplified system which can be implemented in industrial facilities with the help of their own surplus of plastic waste, mainly packaging waste, to reach a level of energy autonomy or semi-autonomy. This waste is converted to about 57,500 L of synthetic pyrolysis oil, which can then be used to power industries, being fed into a Combined Heat and Power system. To achieve this goal, the design has hydrocarbon stability at elevated temperature and restricted oxygen exposure, so that they can be converted to new products. Pyrolysis is a key process which causes thermo-chemical changes—ignition and vaporization. The research outlines the complete process of creating a basic small-scale pyrolysis system which industrial facilities can use to generate energy from their plastic waste. The proposed unit processes 360 tons of plastic waste yearly to produce 160 tons of synthetic pyrolysis oil which enables the generation of 500 MWh of electricity and 60 MWh of heat. The total investment cost is estimated at EUR 41,000, with potential annual revenue of up to EUR 45,000 via net metering. The conceptual design proves both environmental and economic viability by providing a workable method for decentralized waste-to-energy solutions for Small and Medium-sized Enterprises. Full article

The convergence of blockchain and metaverse technologies is poised to redefine how Global Value Chains (GVCs) create, capture, and distribute value, yet scholarly insight into their joint impact remains scattered. Addressing this gap, the present study aims to clarify where, how, and under what conditions blockchain-enabled transparency and metaverse-enabled immersion enhance GVC performance. A systematic literature review (SLR), conducted according to PRISMA 2020 guidelines, screened 300 articles from ABI Global, Business Source Premier, and Web of Science records, yielding 65 peer-reviewed articles for in-depth analysis. The corpus was coded thematically and mapped against three theoretical lenses: transaction cost theory, resource-based view, and network/ecosystem perspectives. Key findings reveal the following: 1. digital twins anchored in immersive platforms reduce planning cycles by up to 30% and enable real-time, cross-border supply chain reconfiguration; 2. tokenized assets, micro-transactions, and decentralized finance (DeFi) are spawning new revenue models but simultaneously shift tax triggers and compliance burdens; 3. cross-chain protocols are critical for scalable trust, yet regulatory fragmentation—exemplified by divergent EU, U.S., and APAC rules—creates non-trivial coordination costs; and 4. traditional IB theories require extension to account for digital-capability orchestration, emerging cost centers (licensing, reserve backing, data audits), and metaverse-driven network effects. Based on these insights, this study recommends that managers adopt phased licensing and geo-aware tax engines, embed region-specific compliance flags in smart-contract metadata, and pilot digital-twin initiatives in sandbox-friendly jurisdictions. Policymakers are urged to accelerate work on interoperability and reporting standards to prevent systemic bottlenecks. Finally, researchers should pursue multi-case and longitudinal studies measuring the financial and ESG outcomes of integrated blockchain–metaverse deployments. By synthesizing disparate streams and articulating a forward agenda, this review provides a conceptual bridge for international business scholarship and a practical roadmap for firms navigating the next wave of digital GVC transformation. Full article

The Fourth Industrial Revolution has introduced “shared manufacturing” as a key concept that leverages digitalization, IoT, blockchain, and robotics to redefine the production and delivery of manufacturing services. This paper presents a novel approach to decentralized warehouse management integrating Large Language Models (LLMs) into the decision-making processes of autonomous agents, which serves as a proof of concept for shared manufacturing. A multi-layered system architecture consisting of physical, digital shadow, organizational, and protocol layers was developed to enable seamless interactions between parcel and warehouse agents. Shared Warehouse game simulations were conducted to evaluate the performance of LLM-driven agents in managing warehouse services, including direct and pooled offers, in a competitive environment. The simulation results show that the LLM-controlled agent clearly outperformed traditional random strategies in decentralized warehouse management. In particular, it achieved higher warehouse utilization rates, more efficient resource allocation, and improved profitability in various competitive scenarios. The LLM agent consistently ensured optimal warehouse allocation and strategically selected offers, reducing empty capacity and maximizing revenue. In addition, the integration of LLMs improves the robustness of decision-making under uncertainty by mitigating the impact of randomness in the environment and ensuring consistent, contextualized responses. This work represents a significant advance in the application of AI to decentralized systems. It provides insights into the complexity of shared manufacturing networks and paves the way for future research in distributed production systems. Full article

Achieving sustainable models is a crucial challenge today, where government actions play a fundamental role. Therefore, this study aims to analyze the impact of fiscal decentralization on CO₂ emissions in 40 economies between 2000 and 2020. To this end, an unbalanced panel was constructed, and the Method of Moments Quantile Regression (MMQR) was employed. As a robustness check, Driscoll and Kraay’s standard errors approach was used. The MMQR results indicate that fiscal decentralization has a positive and significant effect across all quantiles of CO₂ emissions. Additionally, it was found that revenue-side decentralization has a greater impact on the lower quantiles of CO₂ emissions, while expenditure-side decentralization has a stronger effect on the upper quantiles. The findings also reveal that renewable energy mitigates CO₂ emissions, whereas economic growth, resource rents, and information and communication technologies increase them, although the latter with lower statistical significance. These findings are expected to serve as a basis for public policy formulation aimed at improving environmental quality. Full article

This paper aims to test the hypothesis of the existence of significant tax competition between communes, which mainly concerns the share of value-added tax (VAT) proceeds, by exploring the system for allocating intergovernmental transfers in Morocco and analyzing the determinants of VAT transfers to local authorities. It contributes to fiscal federalism by assessing the design of the decentralized system and intergovernmental transfers. It aims to explore and understand the variables determining decentralization in Moroccan Municipalities over the period 2014–2018, based on institutional, budgetary, and political justifications, as well as their influence on local tax efficiency, highlighting the importance of intergovernmental transfers and their impacts on local government autonomy. We find that VAT revenue transfer antecedents include factors such as public expenditure, fiscal potential, tax effort, and political alignment. The results of this study can help better understand the relationship between VAT and economic variables and guide government tax policies in an emerging economy. This paper offers original perspectives on the importance of an informed vision for government decision-makers to develop effective tax policies considering stringent local budget constraints, the need for VAT revenue autonomy across levels of government, and the need for meeting the redistributive goals of the current VAT system. Full article

Since 2019, Togo has been strengthening financial decentralization through municipalization and the election of municipal councilors. Municipal financial autonomy is a key driver of local governance, allowing municipalities to mobilize their own resources, manage tax and non-tax revenues, and implement development projects. However, despite a legal framework governing local taxation, Togolese municipalities continue to face chronic financial constraints that limit their ability to finance public services and infrastructure. This study examines the mechanisms of financial decentralization in Togo and their contribution to municipal budgets. Using a quantitative approach that combines documentary analysis and interviews with 188 experts and practitioners in local finance, the study identifies the following four primary financing mechanisms: local, national, community-based and international. Among these, own revenues, including tax revenues, non-tax revenues, and revenues from the provision of services, together with government transfers through the Local Authorities Support Fund (FACT) are the main sources of local government finance. However, the results show that several legally defined fiscal instruments remain underutilized or outdated in many municipalities, significantly limiting their effectiveness in mobilizing resources. These results highlight the need to optimize fiscal decentralization strategies in order to strengthen the financial autonomy of municipalities and support sustainable territorial development. Full article

In the context of a high proportion of new energy grid connections, demand-side resources have become an inevitable choice for constructing new power systems due to their high flexibility and fast response speed. However, the response capability of demand-side resources is decentralized and fluctuating, which makes it difficult for them to effectively participate in power market trading. Therefore, this paper proposes a robust transaction decision model for demand-side resource aggregators considering multi-objective clustering aggregation optimization. First, a demand-side resource aggregation operation model is designed to aggregate dispersed demand-side resources into a coordinated aggregated response entity through an aggregator. Second, the demand-side resource aggregation evaluation indexes are established from three dimensions of response capacity, response reliability, and response flexibility, and the multi-objective aggregation optimization model of demand-side resources is constructed with the objective function of the larger potential market revenue and the smallest risk of deviation penalty. Finally, robust optimization theory is adopted to cope with the uncertainty of demand-side resource responsiveness, the robust transaction decision model of demand-side resource aggregator is constructed, and a community in Henan Province is selected for simulation analysis to verify the validity and applicability of the proposed model. The findings reveal that the proposed cluster aggregation optimization method reduces the bias penalty risk of the demand-side resource aggregators by about 33.12%, improves the comprehensive optimization objective by about 18.10%, and realizes the optimal aggregation of demand-side resources that takes into account both economy and risk. Moreover, the robust trading decision model can increase the expected net revenue by about 3.1% under the ‘worst’ scenario of fluctuating uncertainties, which enhances the resilience of demand-side resource aggregators to risks and effectively fosters the involvement of demand-side resources in the electricity market dynamics. Full article

Agrivoltaics, combining agricultural production with a photovoltaics system, leverage the dual benefits of panel shading and electricity to optimize traditional farming methods. Agrivoltaics offer many advantages, including agricultural and environmental benefits (e.g., increased crop productivity, water conservation, and enhanced biodiversity), energy benefits (e.g., increased energy production and efficiency), and social benefits (e.g., improved food and energy security, diversification of income, and rural development). Although agrivoltaic approaches have been around for about forty years, little is known about the long-term benefits, potential compatibility with current agricultural practices, market uncertainty and economic viability, and overall benefits. This research provides a review of the literature with a particular focus on individual income generation opportunities: (1) solar energy generation, (2) electricity sales, (3) agricultural production, (4) agricultural sales, and (5) agrivoltaics installations. Each focus area has an associated critical review of government-sponsored market transformation policies aimed to increase agrivoltaics adoption. The paper concludes with a call to action for establishing a collaborative agenda toward prioritizing agrivoltaics research and adoption. Future research is needed to find innovative designs and practices that maximize agricultural productivity within APV systems. Two promising areas for research and innovation include (1) real-time performance monitoring and (2) peer-to-peer networks. Implementing real-time performance monitoring systems can provide valuable data on energy production, microclimate conditions, and crop growth within APV setups. Additionally, peer-to-peer trading platforms can allow farmers to sell surplus energy generated by their APV systems directly to local consumers, bypassing traditional energy utilities. This decentralized model could provide farmers with an additional revenue stream, while promoting the use of renewable energy within local communities, further incentivizing the adaptation of APVs. Full article

Improving product quality is an effective way for a company to gain goodwill as well as to increase sales. In this paper, the focus is on a two-echelon supply chain consisting of a manufacturer and a retailer. Considering the delayed effect of quality improvement on product quality, the differential equations on the levels of quality and goodwill as the state variables are established to explore the impact of delay time on members’ strategy inputs, supply chain profits and performance under decentralized and centralized decision models. Additionally, in this paper, how different profit maximization scenarios affect supply chain revenue under decentralized models is examined. The equilibrium solutions are obtained by numerical simulation. The results show that both quality improvement efforts and marketing efforts are decreasing functions of delay time, and the delay effect affects the motivation of supply chain members’ strategic inputs. Importantly, supply chain profit under centralized decision is not always higher than that under decentralized decision when the manufacturer’s concern degree and delay time are taken into account. The Rubinstein bargaining model is then used to optimize the profit distribution between the manufacturer and the retailer under centralized decision. In this paper, it is also identified that the longer the delay time, the lower the levels of quality and goodwill. The dual effect of delay effect and concern degree will exacerbate the negative impact on the levels of quality and goodwill. Full article