Search Results (70)

South Korea’s official development assistance to the energy sector has increased steadily over the past decade, reaching USD 232.20 million in 2024. Yet public willingness to pay for renewable energy official development assistance remains largely unknown. This study uses a discrete choice experiment with 1000 nationally representative South Korean respondents and a mixed logit model to estimate marginal willingness to pay for key project attributes, including electrification, greenhouse gas reduction, firm expansion, expert training, and reputation enhancement. The results show that greenhouse gas reduction and expert training receive the highest willingness to pay, followed by firm expansion. Electrification and reputation enhancement receive relatively low support. The findings also reveal substantial preference heterogeneity, with younger and nationally oriented respondents placing greater value on economic returns. These results provide new donor country evidence on public preferences for renewable energy official development assistance and offer policy implications for designing a more climate-focused and socially supported green aid portfolio. Full article

Despite decades of methodological sophistication, research on sustainable food behavior remains critically limited in predicting actual purchases. This study aims to examine how methodological fragmentation across psychometric, econometric, and behavioral approaches affects the predictive validity of sustainable food choice and purchasing behavior. This integrative systematic review of 62 empirical studies across psychometric validation, discrete choice experiments (DCEs), trust and cognitive biases, and objective behavioral measurement diagnoses the structural disarticulation between these traditions as the primary cause of limited predictive validity. Findings reveal a pronounced inversion of the evidence hierarchy: while self-report studies report moderate attitude–behavior correlations (β ≈ 0.40–0.50, self-report), the only long-term study using objective scanner data demonstrates that this relationship collapses to a virtually null effect (β = 0.022), representing a 95.6% decay in predictive capacity. Psychometric instruments demonstrate strong structural validity but lack ecological validation against actual purchases. DCEs have evolved econometrically (from MNL to GMNL models), yet remain isolated from psychological theory and real-world validation. Critically, no reviewed study integrated validated scales, a DCE, and objective behavioral data within a single design. Key moderators—skepticism, halo effects, and affective heuristics—are systematically underoperationalized. To overcome this impasse, we propose Hybrid Choice Models (HCM) as the central tool to formally articulate latent attitudes, stated preferences, and observed behavior, enabling cumulative evidence to inform policy and market strategies with greater predictive accuracy. These findings indicate that predictive advances depend on integrating measurement paradigms to achieve ecologically valid and policy-relevant models of sustainable consumer behavior. Full article

Parallel discrete-event simulation (PDES) of register-transfer-level (RTL) designs on multi-socket NUMA platforms demand dynamic load balancing to mitigate barrier-induced tail latency. However, the ultra-fine event granularity of RTL simulation makes migration cost non-negligible, and the non-uniform memory hierarchy of NUMA turns migration cost into a topology-dependent variable rather than a constant. Existing approaches either ignore this topology dependence or rely on heuristic thresholds that lack theoretical justification. This paper formulates NUMA-aware dynamic load balancing as a constrained optimization problem in which the migration cost is an explicit function of the socket locality between the source and destination cores. We introduce a unified net benefit function $G(m,i\to j,f)$ that jointly captures the tail-latency reduction, migration overhead, and cache warm-up penalty for migrating module m from core i to core j at frequency f. We prove that G is jointly concave in migration scale and frequency, yielding two analytical results: (i) a closed-form admission inequality that prescribes when migration is strictly beneficial, and (ii) a conservative fixed-frequency design rule that guides the choice of a global epoch length for the proposed epoch-based controller. We further show that when the initial static partition satisfies a bounded-quality condition, the total migration volume is provably bounded, formalizing the intuition that restraint is optimal, not merely conservative. We implement the proposed topology-aware admission control (TAC) framework in TACVS (Topology-Aware Admission Control Verilog Simulator), our event-driven parallel RTL simulation prototype. Experiments on four open-source RTL designs running on a 2-socket NUMA platform show that TAC reduces the tail-latency ratio by 18.0% on average (up to 28.5%) and improves normalized throughput by 27.1% on average (up to 34.1%) relative to topology-oblivious baselines. An ablation study further shows that admission control and cooldown are critical for performance, with throughput dropping by 15.9% and 22.8% on average (up to 22.4% and 32.5%) when each is removed, respectively. Full article

Methane emissions from dairy production constitute a significant share of agricultural greenhouse gas emissions in Poland and represent a key challenge under EU climate policy and the Common Agricultural Policy (CAP). This study evaluates dairy farmers’ acceptance of alternative methane mitigation measures (MMMs) and examines the cost-efficient design of agri-environmental contracts from a public-budget perspective. A Discrete Choice Experiment (DCE) conducted among 302 dairy farmers was used to estimate participation probabilities for different mitigation measures and contract attributes, including result-based (RB) and input-based (IB) payment schemes. These preference-based probabilities were subsequently embedded into a cost-minimisation optimisation framework that identifies the least-cost portfolios of MMMs capable of achieving increasing methane-reduction targets while remaining behaviourally feasible. The DCE results show significantly higher acceptance of RB contracts compared with IB schemes, strong resistance to vaccination-based measures, and relatively favourable preferences for biofiltration. Payment levels and environmental attitudes significantly influence participation decisions. When behavioural constraints are incorporated into the optimisation model, RB contracts allow for higher achievable methane reductions under the adopted assumptions, primarily due to higher participation rates of farmers in result-based contracts. The model indicates that, beyond moderate mitigation targets, IB schemes face participation limits that constrain scalability. Biofiltration consistently forms the backbone of cost-efficient portfolios, while less accepted measures enter optimal solutions only when ambition levels exceed the feasible potential of high-acceptance options, revealing a potential ambition–acceptance gap. Methodologically, the study integrates stated-preference data into a policy optimisation model, demonstrating how farmers’ quantified perceptions can be treated as structural inputs to environmental policy design rather than assuming full adoption of technically efficient measures. Conceptually, the framework links farmer participation, environmental effectiveness, and budget efficiency within a unified decision-support structure. The proposed framework contributes to sustainability-oriented policy design by linking environmental effectiveness, behavioural feasibility, and public-budget efficiency in methane mitigation strategies for the dairy sector. Although the results are scenario-based and conditional on assumed mitigation and cost parameters, they underline the importance of aligning environmental ambition with empirically grounded participation patterns when designing methane mitigation policies for the dairy sector. Full article

Flood hazard mitigation programs increasingly rely on property buyouts and home elevation, yet participation remains sensitive to program design details that affect household constraints. This study estimates homeowner preferences for buyout and elevation program attributes using a stated-preference discrete-choice experiment administered to N = 1560 homeowners, in which each respondent completed up to 4 choice tasks with 3 alternatives (Buyout, Elevation, and Neither). Choices are modeled in a random-utility framework with a multinomial logit as the primary specification and a mixed logit as a robustness specification. Observed choices favor Buyout (51.2%) over Elevation (29.6%) and the status quo (19.2%). In the estimated utility model, higher buyout offers increase acceptance, longer payment delays significantly reduce acceptance, and longer time to vacate increases acceptance; the acquisition option feature also raises buyout utility. These timing effects imply economically meaningful offer-equivalent tradeoffs: at representative baselines, an additional month of payment delay requires approximately a 6.45 percentage-point increase in offer (as a share of home value) to maintain acceptance, while households would trade about 8.02 percentage points of offer to obtain one additional month to vacate. Heterogeneity results indicate lower baseline participation among low-income respondents and attenuated marginal benefits of longer vacate time among respondents reporting damage. Respondent-level cross-validation shows stable predictive performance and similar accuracy across MNL and mixed logit models. The results highlight that accelerating payments and offering flexible time to vacate can increase program uptake, and that complementary supports may be needed to reduce participation barriers for economically vulnerable households. Full article

Algorithmic transparency is widely considered essential for fostering trust in AI-based financial e-commerce services. However, empirical evidence remains limited on whether transparency benefits all consumers uniformly and how it is evaluated relative to other service attributes in realistic decision contexts. This study examines how consumers trade off transparency, personalization, and user control in robo-advisor (RA) services across different consumer segments. Through a discrete choice experiment and latent class logit modeling, two distinct segments are identified: selective high-expertise investors, who prioritize personalization and user control over transparency, and receptive general consumers, who respond strongly to enhanced explainability. These findings indicate that algorithmic transparency does not serve as a universal design solution but operates conditionally based on consumer expertise and attribute interactions. Simulation results further show that while a regulation-compliant, uniform service design may facilitate market entry, it constraints long-term expansion in heterogeneous markets. In contrast, a segment-based service portfolio calibrated to the distinct preferences of each group significantly increases overall adoption under the same regulatory constraints. These results suggest that sustainable AI diffusion in financial e-commerce requires a nuanced approach that balances disclosure with functional autonomy to address the diverse needs of both sophisticated and novice users. Full article

Forest ecosystems are increasingly degraded by natural disasters and human activities, intensifying the need for large-scale restoration. Because restoration outcomes are long-term, uncertain, and largely non-market, understanding how environmental attitudes relate to public preferences and willingness to pay (WTP) is important for socially acceptable and financially feasible policy design. Using a discrete choice experiment in Korea, this study applies a hybrid choice framework that incorporates latent attitudinal variables into a mixed logit structure, allowing attitudes to interact with preference heterogeneity across restoration attributes. Results show significant heterogeneity in choices and WTP. The model identifies two segments with distinct trade-off patterns: one is more sensitive to risk and payment burden, while the other places relatively greater value on restoration and access-related improvements. Although attitudinal indicators are statistically relevant, segment differentiation is more strongly associated with risk sensitivity and cost aversion than with attitudes alone. Compared with conventional choice models, the latent-attitude specification improves behavioural interpretability and model fit, and yields policy-relevant WTP estimates. Overall, the findings indicate that attitudinal information is complementary to economic and risk-related factors, supporting more targeted and publicly aligned forest-restoration policies. Full article

Objectives: This systematic review aimed to synthesize evidence from discrete choice experiments to explore the preferences of patients, physicians, and caregivers regarding lung cancer treatment. Methods: A systematic literature search was conducted utilizing the PubMed, Web of Science, Embase, and Scopus databases, encompassing publications up to 12 July 2024. We included published discrete choice experiment (DCE) studies that assessed preferences for lung cancer treatment among patients, physicians, or caregivers, with no restrictions on country, language, publication date, or disease stage. Two researchers independently conducted the literature screening and data extraction. The included studies were assessed for quality using the PREFS checklist. Results: Among the 1086 studies identified, 18 studies met the eligibility criteria. A total of 115 attributes were extracted and categorized into three main categories: outcome, process, and cost, with subcategories under each. Regarding the relative importance of attributes, heterogeneity was observed among stakeholders. The PREFS scores of the 18 included studies, with an average score of 3.8, reflect the high overall quality of these studies. Conclusions: This review revealed both commonalities and differences in lung cancer treatment preferences among patients, physicians, and caregivers. However, existing studies have certain limitations in the coverage of study populations, the scope of attributes, and the research design of the experiments. Full article

Agri-environmental subsidies had been implemented to promote sustainable agriculture in regions such as the EU and the U.S. prior to the year 2000. Contract-Based Agri-Environmental Schemes (AESs) are designed to promote green, sustainable agriculture by employing environmentally friendly farming practices (EFFPs) to reduce pollution and meet other environmental goals. A central challenge, however, is the limited inclusion of small farmers, who are key to agricultural sustainability and form the backbone of production, particularly in developing countries. This study aims to investigate the preferences and participation of small farmers in AESs to enable effective policy design. Using discrete choice experiments (DCEs) and a latent class model (LCM) on survey data collected in 2017 from three key rice-producing counties in China—Fangzheng (Heilongjiang), Qingtongxia (Ningxia), and Yixing (Jiangsu)—allowed us to identify two distinct preference classes: “experienced adopters” and “potential adopters”. The results confirmed (1) a high participation rate of small farmers in AESs. Compensation can further motivate them to sign a contract. (2) There is significant heterogeneity among small farmers’ preferences on various EFFPs, so flexible and modulated schemes are needed; (3) those with experience in EFFPs are more likely to participate in AESs; and (4) the modular AES contract with progressive subsidy ties makes payments directly based on EFFP adoption, addressing the shortcomings of China’s current area-based subsidy system. The results of this paper can help policymakers fine-tune farming policies that effectively engage smallholders, thereby alleviating tensions over production–pollution cycles and fostering a more targeted and sustainable agricultural policy system. Full article

Sustainable packaging has become a major area of academic and practical interest, reflecting growing environmental awareness, regulatory pressure, and changing consumer expectations. This study aims to synthesize existing knowledge on consumers’ behavior toward sustainable packaging and their willingness to pay (WTP) for environmentally friendly solutions. Following PRISMA guidelines, a systematic literature review was conducted, encompassing 78 peer-reviewed publications from 2019 to 2025. Bibliometric mapping using VOSviewer (version 1.6.20) identified three main research streams: consumer attitudes and determinants of behavior, willingness to pay for sustainable packaging, and perception of packaging materials and systems. The reviewed studies, conducted across Europe, Asia, Australia, and North America, employed diverse methods, including surveys, discrete choice experiments, structural equation modeling, and mixed designs. Results indicate that consumer behavior is shaped by environmental awareness, self-identity, perceived usefulness, and trust in labeling, while packaging material and functionality remain decisive for acceptance. Most studies show that consumers are willing to pay a premium of about 10–20% for sustainable packaging, though price sensitivity and hygiene concerns limit actual adoption. The findings highlight the conditional nature of consumer acceptance and emphasize the need for transparent communication, credible certification, and functional design. This study provides guidance for policymakers and businesses seeking to promote sustainable packaging solutions. Full article

This study addresses the ecological impact of the internet’s energy consumption by examining the topic of sustainable web design from a consumer-centric perspective. Sustainable web design, encompassing data volume reduction, website element optimization and compression, and ecological hosting, offers the potential to mitigate ecological footprints while simultaneously improving the technical performance and user experience. A mixed-methods research approach was implemented, combining preliminary expert interviews to establish five foundational attributes used in the second part of the study, a discrete choice experiment. Robustness checks of the results employed a mixed logit estimation and tertiary covariates controlling for different sustainability personality types. Rapid loading times turned out to be particularly decisive in generating a positive brand image and enhancing purchase intentions. In addition, communication measures of sustainable web design practices in the form of sustainability seals, the disclosure of green hosting and the provision of transparent information about sustainability efforts also have a positive impact, enhancing the brand perception, quality assessment and users’ purchase decision. The findings, however, reveal no indication whether inherently visible aspects of websites as compared to implemented communication tools, like seals, labels, or information pages, are more effective measures in general. Full article

Traditional pedestrian evacuation models struggle to balance global exit guidance with local, individual decision making under hazards. We address this by decomposing long-term objectives into Particle Swarm Optimization (PSO)-based micro-goals and proposing a hybrid Cellular Automaton (CA) and PSO model. The hybrid design reduces the decoupling between spatial discretization and individual choices and more tightly couples hazard and density fields with movement decisions. Two contributions are central. First, we develop an autonomous following pathfinding mechanism (AFPM) that linearly blends the direction toward a PSO micro-goal with a herd following direction and adds a small reward for directional consistency. This mitigates path chaos from purely autonomous moves and congestion aggregation from purely herding moves. Second, we build a multi-dimensional interpretability and robustness framework that combines the empirical Cumulative Distribution Function (CDF) and a kernel-smoothed Probability Density Function (PDF) of key evacuation times (T_clear, T_95%_alive) together with vulnerability curves, to analyze the data and assess robustness. It combines Shapley Sobol analysis to quantify parameter effects on clearance time T_clear and the 95% survival evacuation time T_95%_alive, with CDF/PDF summaries and vulnerability curves to assess anti-interference performance. Experiments use a simulated underground shopping mall. In a 60 pedestrian case, a geometry-only baseline yields T_clear $\approx 33 \mathrm{s}$; hazard- and density-aware strategies produce slightly longer T_clear but reduce peak bottleneck congestion by 20–30%. When one exit is closed, the exceedance probability at $\tau =70 \mathrm{s}$ drops from 0.44 to 0.36, reducing long tail risk. Compared with geometry-based Dijkstra, the proposed model slightly increases clearance time while lowering peak congestion by 20–30%, achieving a balance between efficiency and safety. The model and evaluation protocol provide technical support for evacuation policy, facility layout, and emergency system design in large complex buildings. Full article

Background: Dysphagia is prevalent among nursing-home residents and contributes to complications such as aspiration pneumonia, malnutrition, and diminished quality of life. Nurses’ knowledge and attitudes strongly influence care quality, yet few validated tools exist to assess these domains in long-term care. Objective: This study aimed to develop and validate the Evaluating Attitudes, Training and Skills in Dysphagia Care (EATS) Questionnaire for nursing home nurses in Singapore. Methods: A cross-sectional study involving 111 nurses from three nursing homes was conducted. The EATS questionnaire was adapted from a hospice-based tool, refined through experts’ and users’ feedback, and subjected to psychometric testing. Analyses included item difficulty and discrimination for the knowledge component, exploratory factor analysis for the attitude component, and internal-consistency reliability. Construct validity was examined by comparing knowledge and attitude scores across nursing seniority and experience. Results: The final questionnaire comprised 22 knowledge and 18 attitude items that loaded onto three factors—Barriers to Dysphagia Care, Patients’ Preferences and Nurses’ Confidence, and Personal Choice. The attitude scale showed moderate internal consistency, and the knowledge items demonstrated acceptable performance for discrete factual content. Senior nurses scored higher in knowledge, confirming construct validity. The tool revealed persistent misconceptions and gaps in recognising subtle clinical signs of dysphagia. Conclusions: The EATS Questionnaire is a valid and pragmatic instrument for assessing dysphagia-related knowledge and attitudes among nursing home nurses. It provides actionable insights for designing targeted education and improving resident safety in long-term care settings. Full article

Father engagement in parenting programs is vital for positive child development and family wellbeing, yet fathers remain underrepresented in parenting programs. This study examines factors influencing fathers’ participation using two discrete choice experiments. Experiment 1 identified key attributes affecting engagement, including program content, cost, and delivery modality. Experiment 2 refined these insights, showing a preference for cost-free, face-to-face programs with practical activities. Findings highlight the importance of addressing financial barriers; offering flexible, relevant content; and designing father-friendly programs to improve accessibility and inclusivity. By prioritising fathers’ needs and preferences, parenting programs can better support child and family outcomes, fostering greater engagement and promoting equality across diverse family systems. Full article

The restoration of forest ecosystems damaged by wildfires and pest outbreaks has become increasingly urgent. However, the public-good nature of forests, the involvement of diverse stakeholders, and the spatial variability of degradation present significant challenges to effective policy design. In particular, previous studies have largely examined these threats in isolation, and few have provided integrated economic analyses of their combined impacts. This gap underscores the need to better understand heterogeneous public preferences and their implications for restoration policy. To address this, we conducted a discrete choice experiment (DCE) with 1021 Korean citizens and applied a two-stage analytical framework combining principal component analysis (PCA) and latent class choice modeling (LCM). Five distinct preference segments were identified, each exhibiting substantial variation in willingness to pay (WTP) for restoration attributes. Policy simulations further revealed that public acceptance declines sharply at higher cost levels, highlighting the importance of setting realistic financial thresholds for broad support. While visual materials, consequentiality checks, and cheap talk scripts were employed to mitigate hypothetical bias, the limitations of external validity and potential sampling biases should be acknowledged. Our findings provide empirical evidence for tailoring restoration policies to different stakeholder groups, while also stressing the financial and institutional constraints of implementation. In particular, the results suggest that cost thresholds, citizen engagement, and awareness-raising strategies must be carefully balanced to ensure both effectiveness and public acceptance. Taken together, these insights contribute to evidence-based forest policymaking that is both economically efficient and socially acceptable, while recognizing the context-specific limitations of the Korean case and the need for comparative studies across countries. Full article