Search Results (596)

Global policy narratives on livestock development increasingly emphasize environmental concerns, often overlooking the social dimensions of the sector. In the case of dairy, the world’s most valuable agricultural commodity, its role in social and economic development remains poorly quantified. Our study contributes to a more balanced vision of the UN SDGs thanks to the inclusion of a socio-economic dimension. Here we present a novel empirical approach to assess the socio-economic impacts of dairy development using a new global dataset and non-parametric modelling techniques (local polynomial regressions), with yield as a proxy for sectoral performance. We find that as dairy systems intensify, the number of farm households engaged in production declines, yet household incomes rise. On-farm labour productivity also increases, accompanied by a reduction in employment but higher wages. In dairy processing, employment initially grows, peaks, and then contracts, again with rising wages. The most substantial impact is observed among consumers: an increased milk supply leads to lower prices and improved affordability, expanding the access to dairy products. Additionally, dairy development is associated with greater agricultural value added, an expanding tax base, and the increased formalization of the economy. These findings suggest that dairy development, beyond its environmental footprint, plays a significant and largely positive role in social transformation, yet is having to adapt sustainably while tackling labour force relocation, and that dairy development’s social impacts mimic the general agricultural sector. These results might be of interest for the assessment of policies regarding dairy development. Full article

This article provides an overview of the current state-of-the-art in cyber risk and cyber risk management, focusing on the mathematical models that have been created to help with risk quantification and insurance pricing. We discuss the main ways that cyber risk is measured, starting with vulnerability functions that show how systems react to threats and going all the way up to more complex stochastic and dynamic models that show how cyber attacks change over time. Next, we examine cyber insurance, including the structure and main features of the cyber insurance market, as well as the growing role of cyber reinsurance in strategies for transferring risk. Finally, we review the mathematical models that have been proposed in the literature for setting the prices of cyber insurance premiums and structuring reinsurance contracts, analysing their advantages, limitations, and potential applications for more effective risk management. The aim of this article is to provide researchers and professionals with a clear picture of the main quantitative tools available and to point out areas that need further research by summarising these contributions. Full article

Energy Performance Contracts (EPC) are performance-based financing mechanisms designed to improve energy efficiency and support renewable energy adoption in the public sector. This study examines the economic efficiency of a 1710.72 kWp solar power plant (SPP), implemented under an EPC at Alanya Alaaddin Keykubat University, using a regression-based analysis. The model evaluates the effects of solar radiation, investment cost, and electricity sales price on unit production cost, and its predictions were compared with actual production data. Results show the system exceeded the EPC contract target by 16.2%, producing 2,423,472.28 kWh in its first year and preventing 1168.64 tons of CO₂ emissions. The developed multiple linear regression model achieved a predictive error margin of 14.7%, confirming its validity. This study highlights the technical, economic, and environmental benefits of EPC applications in Türkiye’s public institutions and offers a practical decision-support framework for policymakers. The novelty lies in integrating a regression model with operational data and providing a comparative assessment of planned, predicted, and actual outcomes. Full article

In the context of global e-commerce platform supply chains dominated by Alibaba and Amazon, power reconfiguration among tripartite stakeholders (platforms, manufacturers, and retailers) remains a critical yet underexplored issue in supply chain contract design. To analyze the strategic interactions between platforms, manufacturers, and retailers, as well as how platforms select the contract format within a tripartite supply chain, this study proposes a Stackelberg game-theoretic framework incorporating participation constraints to compare fixed-fee and revenue-sharing contracts. The results demonstrate that revenue-sharing contracts significantly enhance supply chain efficiency by aligning incentives across members, leading to improved pricing and sales outcomes. However, this coordination benefit comes with reduced platform dominance, as revenue-sharing inherently redistributes power toward upstream and downstream partners. The analysis reveals a nuanced contract selection framework: given the revenue sharing rate, as the additional value increases, the optimal contract shifts from the mode RR to the mode RF, and ultimately to the mode FF. Notably, manufacturers and retailers exhibit a consistent preference for revenue-sharing contracts due to their favorable profit alignment properties, regardless of the platform’s value proposition. These findings may contribute to platform operations theory by (1) proposing a dynamic participation framework for contract analysis, (2) exploring value-based thresholds for contract transitions, and (3) examining the power-balancing effects of alternative contract formats. This study offers actionable insights for platform operators seeking to balance control and cooperation in their supply chain relationships, while providing manufacturers and retailers with strategic guidance for contract negotiations in platform-mediated markets. These findings are especially relevant for large e-commerce platforms and their partners managing the complexities of contemporary digital supply chains. Full article

To address the issue of excessive pessimism caused by demand and supply uncertainties in the green hydrogen supply chain, this study develops a two-tier green hydrogen supply chain model comprising upstream hydrogen production stations and downstream hydrogen refueling stations. This research work investigates optimal ordering and production strategies under stochastic demand and supply conditions. Additionally, option contracts are introduced to share the risks associated with the stochastic output of green hydrogen. This study shows the following: (1) Under decentralized decision-making, the optimal ordering quantity when the hydrogen refueling station is excessively pessimistic is not necessarily lower than the optimal ordering quantity when it is in a rational state, and hydrogen production stations will only operate when the degree of excessive pessimism is relatively low. (2) The initial option ordering quantity is always larger than the minimum execution quantity under the option contract; higher first-order option prices and lower second-order option prices can help to increase the initial option ordering quantity. (3) The option contract is effective in circumventing the negative impact of excessive pessimism at hydrogen production stations on planned production quantities. This study addresses the gap in the existing research regarding excessively pessimistic behaviors and the application of option contracts within the green hydrogen supply chain, providing both theoretical insights and practical guidance for decision-making optimization. This advancement further promotes the sustainable development of the green hydrogen industry. 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

The distortion of energy prices has become an important obstacle to the high-quality development of China’s economy. Moreover, energy price distortions are not merely a domestic issue. They may trigger carbon leakage by diverting emissions-intensive production to countries with cheaper energy. Although the existing literature has extensively examined the effects of energy price distortions, two significant research gaps remain. First, most studies treat energy price distortions merely as an influencing factor, lacking a systematic analysis that places it at the core. Second, the spatial correlation characteristics of energy price distortions are often overlooked. This study measures the degree of energy price distortions across Chinese provinces from 2000 to 2022 and employs methods such as the Global Moran’s I, Local Moran’s I, and kernel density estimation to systematically analyze the spatial correlation, spatial distribution of coordination indices, and dynamic evolution patterns of these distortions. The results reveal that: (1) the overall degree of energy price distortions in China exhibited a trend of rising first and then declining, with significant regional disparities; (2) the regional gap followed an “expansion-contraction” trajectory; (3) there is notable spatial autocorrelation, with high-distortion areas concentrated in Northeast China, the middle reaches of the Yellow River, and Northwest China; and (4) the dynamic evolution suggests that distortion levels in high- and medium-value regions may continue to decline, while those in low-value regions may increase. This study fills a critical gap in the systematic spatial analysis of energy price distortions and provides new empirical evidence and policy insights for advancing market-oriented reforms in energy markets. Full article

This paper examines the strategic decisions of fashion brands to develop and sell non-fungible tokens (NFTs) within the metaverse. We construct two operational models based on whether NFTs are adopted: the traditional fashion model without NFT (Scenario T) and the digital fashion model with NFT (Scenario D). By comparing the equilibrium outcomes of fashion brands in Scenarios T and D, we derive valuable insights into the implementation of digital strategies in the fashion industry. Our analysis reveals three key findings. First and foremost, the proportion of fashion customers to conventional customers, as well as the digital value and cost of NFTs, are direct factors influencing the adoption of digital strategies by fashion brands. Secondly, opportunistic pricing by manufacturers is an indirect factor influencing fashion brands’ strategic choices, and a fixed production price contract can effectively avoid this case. Finally, we find that personalized pricing and a free NFT strategy are effective tools to boost fashion brands’ digital revenues. Full article

This paper studies a supply chain comprising a supplier, a third-party remanufacturer (TPR), and a retailer. The retailer sells both genuine and remanufactured products (i.e., Model O). Leveraging information advantages, the retailer may engage in brand deception by mislabeling remanufactured products as genuine to obtain extra profits (i.e., Model BD). AI-powered anti-counterfeiting technologies (AIT) (i.e., Model BA) and revenue-sharing contracts (i.e., Model C) are considered countermeasures. The findings reveal that (1) brand deception reduces (increases) sales of genuine (remanufactured) products, prompting the supplier (TPR) to lower (raise) wholesale prices. The asymmetric profit erosion effect highlights the gradual erosion of profits for the supplier, retailer, and TPR under brand deception. (2) The bi-interval adaptation effect indicates that AIT is particularly effective in industries with low adaptation resistance. When both the relabeling rate and industry adaptation resistance are low (high), Model BA (Model O) achieves a triple win. (3) Sequentially, when the industry adaptation resistance is low, AIT can significantly improve total profits, consumer surplus (CS), and social welfare (SW). Compared to Model BD, revenue-sharing offers slight advantages in CS but notable disadvantages in SW. Full article

Since the enforcement of Law 98/2016 on public procurement in Romania, the inclusion of price adjustment clauses in construction contracts has become a standard practice. This paper, which presents a comprehensive analysis of the financial implications of eight adjustment formulas applied to public construction projects executed over three durations (12, 24, and 36 months) between 2018 and 2024, is a significant contribution to the field. A comparative analysis using objective indices published by Romania’s National Institute of Statistics reveals the impact of inflation and cost variations on adjusted contract values. Three scenarios, each starting in different years (2018, 2020, and 2022), are explored to determine the sensitivity of the formulas to market fluctuations. Results show that by applying the eight adjustment formulas, only two formulas tend toward annual inflation. The indices used by the construction branch are not correlated with yearly inflation, and when no advance payments are granted, they offer a reliable basis for economic equilibrium in public contracting. The study guides the selection of appropriate adjustment models to manage financial risk in a volatile construction market, providing valuable insights for academics, researchers, and professionals in civil engineering and public procurement. Full article

Background: Economic logistics in fire and rescue services is a critical determinant of operational readiness, fiscal sustainability, and resilience to large-scale emergencies. Despite its strategic importance, logistics remains under-researched in Central and Eastern European contexts, where legacy governance structures and EU-funded modernization coexist with systemic inefficiencies. This study focuses on the Slovak Fire and Rescue Service (HaZZ) as a case to explore how economic logistics systems can be restructured for greater performance and value. Objective: The objective of this paper was to evaluate the structure, performance, and reform potential of the logistics system supporting HaZZ, with a focus on procurement efficiency, lifecycle costing, digital integration, and alignment with EU civil protection standards. Methods: A mixed-methods design was applied, comprising the following: (1) Institutional analysis of governance, budgeting, and legal mandates based on semi-structured expert interviews with HaZZ and the Ministry of Interior officers (n = 12); (2) comparative benchmarking with Germany, Austria, the Czech Republic, and the Netherlands; (3) financial analysis of national logistics expenditures (2019–2023) using Total Cost of Ownership (TCO) principles, completed with the visualization of cost trends and procurement price variance through original heat maps and time-series graphs. Results: The key findings are as follows: (1) HaZZ operates a formally centralized but practically fragmented logistics model across 51 district units, lacking national coordination mechanisms and digital infrastructure; (2) Maintenance costs have risen by 42% between 2019 and 2023 despite increasing capital investment due to insufficient lifecycle planning and asset heterogeneity; (3) Price variance for identical equipment categories across regions exceeds 30%, highlighting the inefficiencies in decentralized procurement; (4) Slovakia lacks a national Logistics Information System (LIS), unlike peer countries which have deployed integrated digital platforms (e.g., CELIS in the Czech Republic); (5) Benchmarking reveals high-impact practices in centralized procurement, lifecycle-based contracting, regional logistics hubs, and performance accountability—particularly in Austria and the Netherlands. Impacts: Four high-impact, feasible reforms were proposed: (1) Establishment of a centralized procurement framework; (2) national LIS deployment to unify inventory and asset tracking; (3) adoption of lifecycle-based and performance-based contracting models; (4) development of regional logistics hubs using underutilized infrastructure. This study is among the first to provide an integrated economic and institutional analysis of the Fire and Rescue Service logistics in a post-socialist EU member state. It offers a structured, transferable reform roadmap grounded in comparative evidence and adapted to Slovakia’s hybrid governance model. The research bridges gaps between modernization policy, procurement law, and digital public administration in the context of emergency services. Full article

As healthcare systems face mounting pressure to modernise payment infrastructure, fintech innovations have emerged as potential tools to improve affordability and efficiency. However, the adoption of these technologies in clinical settings remains limited. This study investigated the perceptions and resistance patterns of healthcare professionals toward Buy-Now-Pay-Later technology and blockchain in healthcare finance, using Innovation Resistance Theory as the guiding framework. Survey data collected from medical practitioners (N = 366) were analysed to identify knowledge gaps, perceived risks, and tradition-related barriers that influence adoption intent. The findings reveal that while interest in financial innovation exists, resistance is driven by institutional conservatism, regulatory uncertainty, and limited familiarity with decentralised finance systems. This research contributes to the literature by offering a theory-based explanation for why even high-potential financial tools face behavioural and structural resistance in healthcare environments. Full article

The energy sector underwent a significant transformation with increasing demand for efficiency, transparency, and sustainability. The traditional or conventional system often faces several challenges, such as inefficient energy trading, a lack of transparency in renewable energy generation verification, and complex regulatory guidelines that affect its widespread adoption. Thus, blockchain technology has emerged as a potential solution to overcome these challenges, as it is known for its transparent, secure, and decentralized nature. However, despite the promising application of blockchain, its integration into the energy supply chain (ESC) is underexplored. The purpose of this research is to analyze the potential applications of blockchain technology in ESC in order to enhance efficiency, transparency, and sustainability in energy systems. The aim is to investigate the integration of blockchain with emerging technologies (such as IoTs, smart contracts, and P2P energy trading) in order to optimize energy production, distribution, and consumption. Furthermore, by comparing different blockchain platforms (like Ethereum, Solana, Hedera, and Hyperledger Fabric), this study discusses the security and scalability challenges of using blockchain in energy systems. It also examines the practical use cases of blockchain for the tokenization of RECs, dynamic energy pricing, and P2P energy trading by providing the Energy Web Foundation and Power Ledger as real-world examples. The article concludes that blockchain technology has the potential to transform ESC by enabling decentralized energy trading, which subsequently enhances transparency in energy transactions and the verification of renewable energy generation. It also identifies smart contracts and tokenization of energy assets as key parameters for dynamic pricing models and efficient trading mechanisms. However, regulatory and scalability challenges remain significant obstacles to its widespread adoption. Finally, this study provides the basis for future advancement in the adoption of blockchain technology in ESC, which offers a valuable resource for industry professionals, regulating authorities, and researchers. Full article

The COVID-19 pandemic and the Russia–Ukraine war have struck the world’s energy markets. This study analyzed how the recent unstable fossil fuel markets impacted the Japanese electricity contracts, classified as extra-high-, high-, and low-voltage contracts. Multiple structural break tests were conducted to endogenously determine breaks affecting electricity prices during January 2019 to November 2022. By incorporating the effects of these breaks in the autoregressive distributed lag (ARDL) model, the study analyzed the effects of natural gas, coal, and crude oil prices on the types of electricity contract prices. The results of the analyses indicated a surge in electricity prices for low- and high-voltage contracts driven by an increase in natural gas. The results imply the importance of providing proper financial support to mitigate the effects of soaring electricity prices and implementing policies to diversify the electricity generation mix in Japan. Full article

When power system equipment fails due to disasters, resulting in the isolation of parts of the network, the loads within the isolated system cannot be guaranteed a continuous power supply. However, for critical loads—such as hospitals or data centers—continuous power supply is of utmost importance. While distributed energy resources (DERs) within the network can supply power to some loads, outages may lead to compensation and fairness issues regarding the unsupplied loads. In response, this study proposes a methodology to determine the appropriate power contract price for key customers by estimating the unsupplied power demand for critical loads in isolated networks and incorporating both outage compensation costs and voltage stability penalties. The microgrid under consideration comprises DERs—including electric vehicles (EVs), fuel cell electric vehicles (FCEVs), photovoltaic (PV) plants, and wind turbine (WT) plants—as well as controllable resources such as battery energy storage systems (BESS) and hydrogen energy storage systems (HESS). It serves both residential load clusters and critical loads associated with social infrastructure. The proposed methodology is structured in two stages. In normal operating conditions, optimal scheduling is simulated using second-order conic programming (SOCP). In the event of a fault, mixed-integer SOCP (MISOCP) is employed to determine the optimal load shedding strategy. A case study is conducted using the IEEE 123 bus test node system to simulate the outage compensation cost calculation and voltage penalty assessment processes. Based on this analysis, a contract price for key customers that considers both disaster-induced outages and voltage impacts is presented. Full article