Search Results (161)

This study applies the Contingent Valuation Method (CVM) to estimate the non-use value of Laojun Mountain National Park, a culturally and ecologically significant site within the Three Parallel Rivers World Heritage region of northwestern Yunnan, China. Based on 219 valid survey responses, the analysis identifies education, income, occupation, cultural identity, and recognition of legacy values as significant determinants of willingness to pay (WTP) for conservation. Interaction effect logistic regression shows that the influence of cultural identity on WTP is moderated by income level and ecological awareness. Valuation results indicate that the park’s annual non-use value ranges from 79.697 to 260.841 billion yuan, based on median and mean estimates. Motivational analysis highlights aesthetic appreciation, cultural meaning, and intergenerational ethics as key drivers of conservation support, while refusal to pay is primarily attributed to expectations of governmental responsibility, especially among low-income and less-educated respondents. These findings advance theoretical understanding of bio-cultural valuation, offer practical guidance for the design of Payment for Ecosystem Services (PES) schemes, and underscore the importance of integrating socio-cultural dimensions into sustainable conservation finance and policy strategies. Full article

Materialism is recognized as an important determinant of consumer behavior. However, studies exploring how materialism influences impulsive buying through the Diderot effect in digital contexts remain scarce. This study analyzes data from 416 adult consumers in Türkiye using Structural Equation Modeling (SEM). Four hypotheses were tested: (i) materialism increases the Diderot effect, (ii) the Diderot effect strengthens impulsive buying, (iii) materialism directly influences impulsive buying, and (iv) materialism indirectly affects impulsive buying through the Diderot effect. The findings support all four hypotheses. Materialism significantly increases both the Diderot effect and impulsive buying in online environments. The Diderot effect partially mediates this relationship and acts as an independent predictor of impulsive tendencies. The study also points out that digital stimuli such as recommendation systems, fast payment options, and social proof may reinforce this mechanism, highlighting the importance of understanding consumer behavior in digital settings. Overall, the results underline that materialistic desires, when combined with the completion motive of the Diderot effect, strongly shape impulsive tendencies. Beyond advancing theory, the study emphasizes that marketing strategies should go beyond promoting higher consumption and instead foster conscious and sustainable shopping practices. This approach not only supports consumer well-being, but also contributes to building ethical and sustainable markets. Full article

This paper proposes a coalition-based framework for the coordinated operation of multi-regional power systems subject to extreme uncertainty in demand surges, renewable variability, and resource mobilization delays. Methodologically, we integrate Bayesian learning with distributionally robust optimization (DRO), embedding dynamically updated scenario posteriors into a Wasserstein ambiguity set. This construction captures both stochastic variability from renewable and load realizations and epistemic uncertainty from incomplete knowledge of probability distributions. To align individual incentives with system-level efficiency, we design a risk-adjusted utility mechanism that combines VCG transfers, Shapley allocations, and nucleolus refinements. These mechanisms explicitly consider agent heterogeneity, risk aversion, and coalition stability, ensuring that cooperation remains both efficient and sustainable. The optimization model maximizes expected social welfare while incorporating constraints on transmission corridor capacities, mobilization logistics, demand–response rebound effects, and mobile energy storage operations. A hierarchical decomposition algorithm integrates the Bayesian-DRO dispatch layer with cooperative game-theoretic allocations to maintain tractability and robustness at large scale. A case study on a six-province interconnected system with 14–26 GW peak demand, 10.2 GW solar, 8.6 GW wind, 14 GW peaking units, and 6.8 GW mobile storage demonstrates the effectiveness of the approach. Results indicate that the proposed framework raises expected welfare by nearly 10% relative to a non-cooperative baseline, reduces the probability of unserved energy exceeding 1.5% from almost 2% to negligible levels, and narrows payment disparities across provinces to strengthen coalition stability. Demand response peaks at 250–300 MW with rebound averaging 25%, while mobile BESS units cycle frequently to enhance local reliability. Overall, the findings highlight a robust and incentive-compatible pathway for resilient inter-provincial operation, providing both methodological advances and policy-relevant insights for multi-regional energy governance. Full article

Background: Glioblastoma is an incurable form of brain cancer with a median overall survival of 1.5 years. Despite its progressive nature and high symptom burden, palliative care is not consistently integrated in routine glioblastoma care. Early integration of palliative care better addresses the needs of patients and caregivers, improves quality of life, and reduces inappropriate care in the end-of-life phase. This study aims to design an integrated care pathway to support the early integration of palliative care for patients with glioblastoma. Methods: We used a design thinking approach, engaging stakeholders from neuro-oncology, specialist palliative care, primary care, district nursing, healthcare administration, health insurance, health economics, and patient advocacy. The process consisted of thirteen informal interviews (with healthcare professionals, patients, and caregivers), six expert meetings, and two workshops. Results: First, we mapped existing routine glioblastoma care and identified perceived barriers to early palliative care integration, including variations in advance care planning (ACP) timing, clinicians’ hesitation, unclear referral criteria to specialist palliative care, suboptimal care coordination, and limited experience with glioblastoma in the primary care setting. Second, iterative prototyping led to the development of a care pathway with key components: initiation of ACP by the lead clinician within six weeks of diagnosis, integrated multidisciplinary team meetings for complex cases, ongoing coordination, clear referral triggers for specialist palliative care, and structured caregiver care. Conclusions: The co-designed pathway provides a feasible model for integrating early palliative care into routine care for patients with glioblastoma. Future steps include implementation and evaluation of the care pathway and development of a payment model. Full article

Technological advancements are reshaping New Mobility Services (NMS) by enhancing trip planning, booking, and payment processes, while also improving fleet management, infrastructure utilization, and data-driven decision-making. Despite these developments, challenges persist in integrating technologies into cohesive and interoperable mobility systems. This study draws insights from 163 stakeholders across the NMS ecosystem to examine both the opportunities and barriers associated with the effective integration of technology into NMS, particularly within urban and metropolitan contexts. Using statistical methods, these responses were analyzed across eight stakeholder groups to determine whether their views converge or diverge. Findings reveal a broad consensus on the technologies expected to have the greatest impact, as well as on the main challenges of integrating these technologies into NMS. Divergences arise in the perceived influence on specific mobility attributes, such as environmental sustainability, security, safety, equity, and social inclusion, and in the services considered most likely to benefit. Notably, investors express a more optimistic view across nearly all technologies, prioritizing shared vehicle services and anticipating the strongest impacts in environmental sustainability. The rest of the stakeholder groups emphasize the potential of technology to enhance modal integration and identify Mobility-as-a-Service (MaaS) as the NMS with the greatest expected benefits. These insights help identify strategic priorities and redirect efforts toward promoting investment in technologies with the highest potential to deliver transformative benefits across the NMS ecosystem. Full article

In today’s digital economy, electronic payments are essential to supporting financial transactions. However, the danger of fraud also rises with company complexity and volume. This study uses machine learning and advanced analytics to investigate fraud detection in electronic payments. Using business tools like accounts, account types, and balance sheets, we spot patterns and trends connected to illicit activities. To detect and identify fraud, our study uses pre-existing data, machine learning algorithms, and infrastructure. The author has assessed the performance of several models, such as logistic regression, random forests, and k-nearest neighbor models, using criteria like accuracy, precision, and recall. To determine the most important characteristics for fraud detection, the author also conducts a significance analysis and examines the model’s interpretability. According to the current study’s findings, financial institutions and payment systems will be able to identify fraud more efficiently and gain an improved knowledge of the traits of commercial fraud. Full article

Fraudulent online payment operations represent a persistent challenge in digital commerce, particularly in sectors like air travel, where credit and debit card payments dominate. This study presents a novel fraud detection framework tailored to airline ticket purchases, combining a synthetic dataset generator with a modular, customizable feature engineering process. These are two machine learning models—support vector machines (SVMs) and the light gradient boosting machine (LightGBM)—for real-time fraud detection. A synthetic dataset was generated, including a rich set of engineered features reflecting realistic user, transaction, and flight-related attributes. While both models were evaluated using classification-evaluation metrics, LightGBM outperformed SVMs in terms of overall performance with an accuracy of 94.2% and a recall of 71.3% for fraudulent cases. The main contribution of this study is the design of a reusable, customizable feature engineering framework for fraud detection in the airline sector, along with the development of a lightweight, adaptable fraud detection system for merchants, especially small and medium-sized enterprises. These findings support the use of advanced machine learning methods to enhance security in digital airline transactions. Full article

Advanced Persistent Threats (APT) are stealthy multi-step attacks, often executed over an extensive time period and tailored for a specific attack target. APTs represent a “low and slow” type of cyberattack, meaning that they most often remain undetected until the consequence of the attack becomes evident. Energy infrastructure, including power grids, oil and gas infrastructure, offshore wind installations, etc., form the basis of a modern digital nation. In addition to loss of power, financial systems, banking systems, digital national services, etc., become non-operational without electricity. Loss of power from an APT cyberattack could result in loss of life and the possibility of creating digital chaos. Digital payments becomes unavailable, digital identification is affected, and even POS terminals need to run on emergency power, which is limited in time, resulting in challenges in paying for food and beverages. Examples of Advanced Persistent Threats (APTs) targeting energy infrastructures include Triton, which in 2017 aimed to manipulate the safety systems of a petrochemical plant in Saudi Arabia, potentially leading to catastrophic physical consequences. Another significant incident is the Industroyer2 malware attack in 2022, which targeted a Ukrainian energy provider in an attempt to disrupt operations. The paper combines APT knowledge with energy infrastructure domain expertise, focusing on technical aspects while at the same time providing perspectives on societal consequences that could result from APTs. Full article

Research on ecosystem carbon sequestration services and ecological compensation is crucial for advancing carbon neutrality. As a public good, ecosystem carbon sequestration services inherently lead to externalities. Therefore, it is essential to consider externalities in the flow of sequestration services. However, few studies have examined intra- and inter-regional ecosystem carbon sequestration flows, making regional ecosystem carbon sequestration flows less comprehensive. Against this background, the research objectives of this paper are as follows. The flow of carbon sequestration services between Henan Province and out-of-province regions is studied. In addition, this study clarifies the beneficiary and supply areas of carbon sink services in Henan Province and the neighboring regions at the prefecture-level city scale to obtain a more systematic, comprehensive, and actual flow of carbon sequestration services for scientific and effective eco-compensation and to promote regional synergistic emission reductions. The research methodologies used in this paper are as follows. First, this study adopts a meta-coupling framework, designating Henan Province as the focal system, the Central Urban Agglomeration as the adjacent system, and eight surrounding provinces as remote systems. Regional carbon sequestration was assessed using net primary productivity (NEP), while carbon emissions were evaluated based on per capita carbon emissions and population density. A carbon balance analysis integrated carbon sequestration and emissions. Hotspot analysis identified areas of carbon sequestration service supply and associated benefits. Ecological radiation force formulas were used to quantify service flows, and compensation values were estimated considering the government’s payment capacity and willingness. A three-dimensional evaluation system—incorporating technology, talent, and fiscal capacity—was developed to propose a diversified ecological compensation scheme by comparing supply and beneficiary areas. By modeling the ecosystem carbon sequestration service flow, the main results of this paper are as follows: (1) Within Henan Province, Luoyang and Nanyang provided 521,300 tons and 515,600 tons of carbon sinks to eight cities (e.g., Jiaozuo, Zhengzhou, and Kaifeng), warranting an ecological compensation of CNY 262.817 million and CNY 263.259 million, respectively. (2) Henan exported 3.0739 million tons of carbon sinks to external provinces, corresponding to a compensation value of CNY 1756.079 million. Conversely, regions such as Changzhi, Xiangyang, and Jinzhong contributed 657,200 tons of carbon sinks to Henan, requiring a compensation of CNY 189.921 million. (3) Henan thus achieved a net ecological compensation of CNY 1566.158 million through carbon sink flows. (4) In addition to monetary compensation, beneficiary areas may also contribute through technology transfer, financial investment, and talent support. The findings support the following conclusions: (1) it is necessary to consider the externalities of ecosystem services, and (2) the meta-coupling framework enables a comprehensive assessment of carbon sequestration service flows, providing actionable insights for improving ecosystem governance in Henan Province and comparable regions. Full article

In the digital era, face recognition technology has emerged as a promising solution for enhancing payment system security and convenience. This systematic literature review examines face recognition advancements in payment security following the PRISMA framework. From 219 initially identified articles, we selected 10 studies meeting our technical criteria. The findings reveal significant progress in deep learning approaches, multimodal feature integration, and transformer-based architectures. Current trends emphasize multimodal systems combining RGB with IR and depth data for sophisticated attack detection. Critical challenges remain in cross-dataset generalization, evaluation standardization, computational efficiency, and combating advanced threats including deepfakes. This review identifies technical limitations and provides direction for developing robust facial recognition technologies for widespread payment adoption. Full article

This study investigates the convergence of blockchain, artificial intelligence (AI), near-field communication (NFC), and mobile technologies in electronic payment (e-payment) systems, proposing an innovative integrative framework to deconstruct the systemic innovations and transformative impacts driven by such technological synergy. Unlike prior research, which often focuses on single-technology adoption, this study uniquely adopts a cross-technology convergence perspective. To our knowledge, this is the first study to empirically map the multi-technology convergence landscape in e-payment using scientometric techniques. By employing bibliometric and thematic network analysis methods, the research maps the intellectual evolution and key research themes of technology convergence in e-payment systems. Findings reveal that while the integration of these technologies holds significant promise, improving transparency, scalability, and responsiveness, it also presents challenges, including interoperability barriers, privacy concerns, and regulatory complexity. Furthermore, this study highlights the potential for convergent technologies to unintentionally deepen the digital divide if not inclusively designed. The novelty of this study is threefold: (1) theoretical contribution—this study expands existing frameworks of technology adoption and digital governance by introducing an integrated perspective on cross-technology adoption and regulatory responsiveness; (2) practical relevance—it offers actionable, stakeholder-specific recommendations for policymakers, financial institutions, developers, and end-users; (3) methodological innovation—it leverages scientometric and topic modeling techniques to capture the macro-level trajectory of technology convergence, complementing traditional qualitative insights. In conclusion, this study advances the theoretical foundations of digital finance and provides forward-looking policy and managerial implications, paving the way for a more secure, inclusive, and innovation-driven digital payment ecosystem. Full article

The maritime sector is under pressure to increase ship energy efficiency and reduce greenhouse gas (GHG) emissions as a part of global decarbonization goals. Various innovative technologies are being adopted in recent years, raising concerns not only about technological feasibility but also about the economic viability of such technologies in the context of sustainable maritime practices. This study evaluates the operational performance, potential to increase energy efficiency, and economic feasibility of wind-assisted propulsion technologies such as rotor sails across different vessel types and operational profiles. As a contribution to cleaner and more efficient shipping, energy savings produced by rotor thrust were analyzed in relation to vessel dimensions and rotor configuration. The results derived from publicly available industry data including shipowner reports, manufacturer case studies, and classification society publications on 25 confirmed rotor sail installations between 2010 and 2025 indicate that savings typically range between 4% and 15%, with isolated cases reporting up to 25%. A simulation model was developed to assess payback time based on varying fuel consumption, investment cost, CO₂ pricing, and operational parameters. Monte Carlo analysis confirmed that under typical assumptions rotor sail investments can reach payback in three to six years (as the ship is also liable for CO₂ payments). These findings offer practical guidance for shipowners and operators evaluating wind-assisted propulsion under current and emerging environmental regulations and contribute to advancing sustainability in maritime transport. The research contributes to bridging the gap between simulation-based and real-world performance evaluations of rotor sail technologies. Full article

Engineering contract management is a critical component of project management systems, serving as a key mechanism for ensuring successful project implementation. This study systematically analyzes 349 s-instance judicial cases related to construction engineering contract disputes in the Yangtze River Delta Economic Zone from 2017 to 2021, based on data obtained from the China Judgments Online database. The research identifies contractual risk characteristics across dimensions such as regional distribution, dispute terminology, legal citation patterns, and appellate role transitions. The key findings include the following: (1) Primary risks involve payment disputes, quality assurance failures, contractual validity issues, and schedule compliance challenges. (2) Litigation patterns reveal complex interdependencies between contracting parties and stakeholders, posing significant risk management challenges. (3) High second-instance modification rates stem from procedural irregularities, new evidence, improper legal application, and factual errors in initial trials. The study proposes stratified risk mitigation strategies, including governmental regulatory improvements and enterprise-level management optimizations. These findings offer valuable insights into advancing risk governance in construction contract administration, particularly through an enhanced understanding of dispute complexity and systemic vulnerabilities. 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

Under the global climate governance framework, advancing China’s “Dual Carbon” goals within the context of sustainable development requires detailed, micro-level research. While existing studies predominantly focus on national or provincial macro scales, there remains a critical gap in county-level analyses that account for regional heterogeneity—particularly in geographically and economically transitional provinces like Shaanxi. This study focuses on 107 counties in Shaanxi Province, using land-use data from 2000 to 2022 to construct carbon emission and carbon compensation accounting models. We measure horizontal carbon compensation standards, examine spatiotemporal patterns of carbon emissions, delineate compensation zones, and propose regional low-carbon development strategies to inform sustainable development planning. The results show the following: (1) They reveal a steady increase in CO₂ emissions over the period (from 940 million tons in 2000 to 2.089 billion tons in 2022), highlighting an ongoing challenge for sustainability, with a spatial pattern of “high in the north, low in the south, and outward expansion from the center.” (2) In 2022, carbon payments across the province totaled CNY 1.068 billion, while compensation reached CNY 670 million, with significant spatial heterogeneity: 87 counties identified as payers (66 heavy) and 20 as receivers (17 heavy). (3) By integrating the Economic Contribution Coefficient, Ecological Support Coefficient, and Carbon Offset Rate with Major Function-oriented Zoning, we classify the counties into 12 carbon compensation subregions and recommend gradient-based development strategies. This refined zoning framework provides a clear operational framework for formulating differentiated low-carbon land-use optimization strategies and regional carbon compensation policies tailored to the characteristics of different functional zones. The research findings offer differentiated compensation standards and low-carbon land-use planning guidelines to support Shaanxi Province’s transition towards sustainable development, serving as a reference for carbon governance and sustainable development practices in China’s provinces with transitional geographical features and promoting the realization of China’s “Dual Carbon” targets as integral components of national sustainable development. Full article