Search Results (58)

The rapid expansion of the global gaming industry has intensified concern about Gaming Disorder (GD), creating a need for strategies that protect player well-being while remaining feasible for industry implementation. Using a PRISMA 2020-guided systematic review method, the study synthesised evidence from 40 peer-reviewed studies published between 2015 and 2025 on responsible gaming interventions implemented by game developers, platform operators, and digital storefronts. The review identified four main strategy clusters: structural design features, behavioural tools, monetisation controls, and regulatory measures. Across the literature, some interventions, including break reminders, spending controls, adaptive warnings, and design modifications that interrupt continuous play, showed potential to reduce excessive gaming and support self-regulation. However, effectiveness was often constrained by fragmented implementation, inconsistent evaluation, jurisdictional differences, and limited evidence from low- and middle-income settings. Digital storefronts were notably underexamined despite their growing influence on access and monetisation. The findings suggest that isolated technical or behavioural measures are unlikely to be sufficient on their own. In response, this review proposes the Integrated Responsible Gaming Strategy Framework (IRGSF), which brings together ethical design, behavioural support, socio-technical coordination, and stakeholder governance to guide more coherent and sustainable approaches to GD prevention. Full article

This study explores the challenges and opportunities for embedding the Natural Capital Approach (NCA) in policy processes, especially in the framing of the Environmental Improvement Plan (EIP), which is England’s strategic framework for improving the natural environment, including cleaner air and water, healthy soil, thriving wildlife and climate-adapted landscapes. Semi-structured interviews were undertaken with policymakers working in Defra (Department of Environment, Food and Rural Affairs) and its Arm’s Length Bodies (ALBs) organisations to investigate their views on the barriers and enablers to the adoption of the NCA. It has been widely recognised that the NCA provides unifying concepts that are able to connect economists and ecologists, and it can help to embed nature across government departments and supports to make the business case for nature improvement. On the other hand, there are perceived challenges in mainstreaming the NCA in environmental policy processes. There is some lack of agreement on the usefulness of the approach, problems with the oversuse of monetary valuation in policy appraisal, isolation of work, policy processes and government departments and difficulties in the communication of the benefits of the NCA. Recommendations to overcome the barriers include cross-departmental work placements of natural capital scientists, establishing cross-agency natural capital working goups to work on the use of the NCA to frame environment improvement policies, and prioritising the adoption of deliberative approaches to better understand local values on nature that are difficult or even impossible to monetise. Full article

Developing countries in which infrastructure development is heavily dependent on overseas development aid face significant sustainability challenges, including financing gaps and inadequate maintenance. Increasing private-sector investment is crucial for addressing these challenges. This paper proposes an innovative framework linking environmental, social, and governance (ESG) principles with a revised joint credit mechanism (JCM) to attract private investment in infrastructure development, particularly in Pacific Island countries facing the climate crisis. Under the revised JCM, by allocating generated carbon credits to participating Japanese companies, rather than the Japanese government, corporations can monetise credits through market transactions, creating compelling economic incentives for private-sector engagement. In ESG-advanced markets, credits serve as strategic instruments for corporate value enhancement beyond revenue generation, while corporations require continuous credit acquisition to sustain investor confidence. Our revised framework provides a sustainable solution to both financing gaps and infrastructure maintenance challenges. Our analysis demonstrates that integrating market dynamics and corporate incentives into bilateral climate mechanisms holds substantial potential for mobilising private capital for sustainable climate infrastructure finance. This approach represents a promising departure from traditional donor-dependent models, effectively aligning corporate interests with sustainable development objectives while advancing national emission reduction commitments. Full article

Background/Objectives: Breast cancer affects working-age women not only through treatment and survival but also through health-related quality of life (HRQoL), work capacity and informal caregiving needs. Evidence from Central and Eastern Europe remains limited. This study estimated the indirect societal burden of breast cancer among working-age women in Croatia and reported economic indirect costs separately from monetised HRQoL/welfare loss. Methods: A multicentre cross-sectional study conducted in 2024 included women aged 18–65 years receiving outpatient oncology care at two tertiary centres in Croatia. HRQoL was assessed with the EuroQol five-dimension five-level instrument (EQ-5D-5L) and compared with Croatian general-population norms. Utility decrements were annualised and monetised using a national willingness-to-pay threshold of €17,000 per quality-adjusted life year (QALY). Work productivity impairment was measured using the Work Productivity and Activity Impairment: General Health (WPAI:GH) questionnaire and valued, together with informal care, using the human-capital approach. Deterministic sensitivity analyses and approximate 95% confidence intervals were used to show how the estimates changed under key assumptions. Results: A total of 271 women participated (mean age 51.3 years among age-eligible records). Mean EQ-5D-5L utility was 0.76 versus 0.91 in the general population, corresponding to an annual QALY loss of 0.15 and a monetised HRQoL/welfare loss of €2550 per patient-year (95% CI €2083–€3017). Among employed participants, mean overall work productivity loss was 43.9% (842.9 h/year), equivalent to €7333 annually (95% CI €6311–€8355). Informal caregiving was reported by 54.7% of participants, with mean annual costs of €1566 (95% CI €1269–€1863). Economic indirect costs were €8899 per patient-year (95% CI €7835–€9963). In an extended welfare-inclusive scenario, the estimated burden was €11,449 per patient-year (95% CI €10,287–€12,611), corresponding to an illustrative national estimate of €86 million (95% CI €77–€95 million; 0.11% of gross domestic product). Conclusions: Breast cancer in working-age women imposes a substantial societal burden in Croatia, driven by reduced HRQoL, productivity losses and informal caregiving needs. These findings support taking societal burden into account in public health planning, survivorship care and health policy decision-making. Full article

The rapid global expansion of photovoltaic capacity, now exceeding 1 TW, has transformed solar power forecasting from an engineering problem into a financially critical investment decision. Yet virtually all published forecasting studies optimise statistical accuracy metrics without translating improvements into monetised operational value. This paper introduces a unified cost–benefit framework that maps forecast errors across three operationally distinct time horizons onto imbalance costs, arbitrage revenues, and AI deployment costs. The economic conclusions are grounded in Romanian Balancing Market conditions (mean up-regulation price λ⁺ ≈ 85 €/MWh, mean down-regulation price λ⁻ ≈ 42 €/MWh; 15 min settlement interval), a five-year dataset (2018–2022) from a 10 MW utility-scale PV installation in Romania, and an annual AI system cost of 36,000 €/MW decomposed into data infrastructure, cloud GPU compute, and model-monitoring personnel. A Temporal Fusion Transformer ensemble, benchmarked against CNN-LSTM, Informer, and smart-persistence baselines, achieves a 0.38 Skill Score at the day-ahead horizon and a 0.28 Value Score, translating to a net economic benefit of €142,000 per installed MW per annum after full AI system cost deduction. While the framework is designed to be reusable across markets, all reported economic values are specific to the stated Romanian market parameters and should be recalibrated for other regulatory jurisdictions. Full article

The relationship between forest ecosystem services and human health has emerged as a key topic in forest economics and health policy research. This study develops a spatial modelling framework to quantify the health benefits of forest ecosystem services and proposes policy mechanisms to incorporate these benefits into governmental health strategies. Using county-level panel data from 66 administrative units in Zhejiang Province, China, covering the period 2013–2023, we analyse the relationship between forest-mediated air purification services and two population health outcomes: the incidence of respiratory diseases and cardiovascular disease mortality. We employ a Spatial Durbin Model (SDM) to estimate both direct and spatial spillover effects across county boundaries. The findings indicate that forest ecosystem services exert significant negative effects on adverse health outcomes, with spillover effects extending beyond administrative boundaries. The monetised health benefit of forests is estimated at approximately RMB 1108.6 per hectare per year, substantially exceeding current ecological compensation standards and suggesting systematic undervaluation of forest health services. Heterogeneity analysis reveals that health benefits are greater in urbanised regions and among vulnerable population groups, including the elderly. These findings provide an empirical basis for reforming health-oriented ecological compensation mechanisms and offer implications for sustainable land use governance aligned with SDG 3 (Good Health and Well-being) and SDG 15 (Life on Land). Full article

Autonomous mobility is reshaping how travel time is perceived, experienced, and monetised. Most existing studies have examined the value of time (VOT), willingness to pay (WTP), comfort and safety perception, digital services, and user perception as isolated phenomena, with limited efforts to integrate these dimensions into unified analytical frameworks. This study aims to address the fragmented nature of existing research by developing an integrated understanding of user behaviour in autonomous mobility, linking VOT, WTP, psychological constructs, and service-related factors within a unified analytical perspective. A systematic review methodology following PRISMA 2020 guidelines was applied. A total of 81 peer-reviewed studies published between 2015 and 2026 were included and analysed, focusing on Private Autonomous Vehicles (PAVs) and Shared Autonomous Vehicles (SAVs). The results reveal three main trends. First, autonomous travel introduces greater flexibility in time use and enables productive or leisure activities during travel. Second, behavioural aspects of VOT and WTP are strongly influenced by psychological constructs such as trust, safety, and risk perception. Third, notable differences emerge between PAV and SAV contexts, particularly in terms of comfort, control, and safety perception. The literature predominantly employs stated preference surveys, discrete choice models, and hybrid models incorporating psychological factors. However, fragmentation persists in modelling behavioural aspects of time perception and shared mobility services. This study provides a structured synthesis of existing evidence and highlights key research gaps by integrating economic, psychological, and service-related dimensions. The findings emphasise the importance of context-specific and psychologically informed modelling approaches to better understand user acceptance and behavioural adaptation in autonomous mobility systems. Full article

The day-ahead scheduling of multi-stack Power-to-X (PtX) plants must simultaneously cope with stack degradation under variable loading and with compound uncertainty in renewable generation and electricity prices. Existing scheduling frameworks address these two challenges in isolation, since degradation-aware models remain deterministic and stochastic models treat the electrolyser as a constant-efficiency device. This work develops a degradation-aware two-stage stochastic mixed-integer linear programming (MILP) framework that closes this gap. First-stage binaries fix the commitment and startup decisions of every stack, while second-stage scenario-indexed variables capture the dispatch, the hydrogen output, the shortfall, and the load-dependent and start–stop cycling degradation cost monetised at the stack level through a piecewise linear epigraph. Joint wind price uncertainty is represented by a Gaussian copula fitted on empirical CDF marginals and reduced to twenty representative scenarios via k-medoids clustering. The framework is fully implemented in MATLAB R2024a with the Optimization Toolbox, using the built-in intlinprog and linprog solvers. On a 100 MW reference plant with ten heterogeneous PEM stacks, out-of-sample evaluation against four formal benchmarks demonstrates the lowest LCOH at EUR 24/kg, the highest demand reliability at 85.0%, the highest hydrogen delivery at 7.68 t/day, and up to 50% total cost reduction over deterministic baselines, with end-to-end runtime under two minutes on standard workstation hardware. Full article

Digital commerce ecosystems increasingly depend on the alignment between social media advertising formats and digital payment systems, yet existing research has examined these mechanisms in isolation, overlooking their combined influence on consumer behaviour, conversion, and long-term value creation. This study addresses that gap by developing an integrative conceptual framework that examines how advertising formats and payment infrastructures jointly shape sustainable digital monetisation within an Environmental, Social, and Governance (ESG) framework. Methodologically, the study adopts a structured narrative literature review of interdisciplinary peer-reviewed studies and selected high-quality institutional reports, drawn from Scopus, Web of Science Core Collection, and Google Scholar, covering publications from 2015 to April 2026. A four-stage PRISMA-adapted selection protocol was applied to ensure transparency, replicability, and analytical rigour across the review process. The findings demonstrate that advertising formats including native advertising, influencer marketing, user-generated content, short-form video, live streaming, and augmented reality drive consumer attention and purchase intention, while payment systems encompassing digital wallets, BNPL services, and in-platform checkout shape transactional trust and friction. Conversion and customer lifetime value emerge as joint outcomes of this interaction, mediated by consumer trust and transaction friction. The study further identifies key sustainability tensions related to digital carbon footprints from data-intensive formats, financial vulnerability associated with frictionless credit tools, and governance concerns surrounding transparency, privacy, and platform power concentration. The study contributes an integrative conceptual model linking advertising formats, payment systems, consumer behaviour, and ESG dimensions within a unified framework, supported by six theoretically grounded hypotheses (H1–H6) to guide future empirical research in sustainable digital commerce. Full article

This article analyses how Spanish newspapers and news agencies are embracing audio journalism and to what extent podcasts are establishing themselves as a tool for narrative, strategic, and commercial innovation. Based on the original production of 138 titles released by 15 news organizations, a mixed design (documentary collection, systematic listening and a 25-variable matrix on production, content, and distribution) is applied to describe formats, genres, themes and launch models, as well as the weight of co-productions and audio–video hybridisation. The results show, on the one hand, a clear expansion of informative podcasts, in the form of dailies, narrative series and conversational spaces, as well as a dominant focus on current affairs content; and, on the other hand, an asymmetrical development between groups, with Vocento’s audio division standing out in contrast to publications that barely exploit the expressive resources of the audio medium. It is concluded that podcasts are establishing themselves as vectors of transformation for the daily press by reinforcing editorial identity, diversifying offerings, and opening avenues for monetisation, but there is uneven experimentation with the potential of podcasts to deeply renew the ways of narrating and relating to audiences. Full article

The integration of generative artificial intelligence (GAI) into digital learning environments is a profound socio-technical transformation. While GAI promises enhanced accessibility and efficiency, it simultaneously obscures the human creativity and intellectual labour that underpins digital knowledge production. This opacity limits creators’ visibility into how their work is used, evaluated, and monetised. This review application work investigates how several leading large language models, including ChatGPT (GPT-4o), Gemini (1.5 Flash), and DeepSeek (V3), interact with a creative platform hosting over 300 original essays, poems, and artworks from various human creatives. Our review reveals that despite clear evidence of models engaging with original materials, standard platform analytics of the average creative record no attribution, referrals, or traceable interaction from their end, rendering creators’ labour invisible. This compels critical examination of knowledge provenance and power within AI-mediated education. To address this, we propose a socio-technical framework, Chujoyi-TraceNet, not as a technical fix, but a mechanism to re-centre ethics, justice, and recognition in digital governance. By integrating real-time tracking, blockchain-enabled licensing, and metadata watermarking, Chujoyi-TraceNet operationalises the principles of equitable attribution. This study argues for a re-imagining of digital ecosystems in education, one that links the technical act of attribution to broader debates on digital labour, platform ethics, and the pursuit of social justice, thereby contributing to more democratic and accountable learning media in the era of Industry 4.0 and 5.0. Full article

Autonomous battery electric vehicles (BEVs) have the potential to reshape urban mobility systems, yet their sustainability impacts remain underexplored in Gulf-region cities where traffic dynamics, land-use structures, and environmental conditions differ substantially from Western contexts. This study introduces a Saudi-specific assessment framework that integrates monetised externalities with empirically calibrated traffic dynamics to evaluate how automation influences safety, congestion, land use, emissions, and noise. To the best of our knowledge, this is the first Riyadh-calibrated monetised external-cost evaluation of autonomous BEVs that couples externality valuation with simulation-validated time-varying traffic dynamics (SAR per vkm and SAR per pkm), enabling realistic peak-period sustainability assessment. The framework’s key contribution is linking external-cost modelling with spatiotemporal traffic behaviour derived from Riyadh’s 2023 mobility patterns, providing a more realistic basis for sustainability evaluation. Using national datasets from transport, energy, and statistical authorities, the model estimates substantial reductions in external costs when transitioning from human-driven to autonomous BEVs, driven primarily by lower crash exposure and smoother traffic flow. To validate these findings under real operating conditions, a dynamic analysis incorporating hourly and seasonal traffic variability was developed, revealing that automation delivers its strongest improvements during peak-demand periods where congestion externalities are highest. The integrated results demonstrate the relevance of autonomous BEVs for dense rapidly growing Saudi cities and provide actionable insights for future mobility planning. The study highlights the policy importance of coordinated transport, land-use, and energy strategies to ensure that automation contributes meaningfully to national sustainability goals under Vision 2030. Full article

Plastic waste gasification offers a dual-benefit pathway for hydrogen production and waste management in emerging economies. However, existing hydrogen infrastructure planning focuses predominantly on blue and green pathways, with limited integration of waste-derived hydrogen or spatially distributed waste availability constraints. This study determines optimal waste-to-hydrogen infrastructure deployment in Oman through 2040 using mixed-integer linear programming with verified techno-economic parameters. Results indicate that plastic waste can produce 21,997 tonnes H₂ annually at a levelised cost of $2.88/kg, competitive with blue hydrogen ($1.80–2.50/kg) and significantly cheaper than current green hydrogen ($4–6/kg). The optimal network comprises four facilities at Muscat (500 TPD), Sohar (128 TPD), Salalah (192 TPD), and Nizwa (67 TPD), processing 275,000 tonnes of plastic waste whilst avoiding 137,000 tonnes of CO₂-eq through landfill diversion. However, feedstock availability constrains production to 24% of base case demand (90,000 tonnes), positioning waste-to-H₂ as a complementary pathway requiring integration with steam methane reforming for industrial hubs and electrolysis for the transport sector. Sensitivity analysis reveals hydrogen yield (±29% cost impact) and CAPEX (±20%) as critical parameters, with cost reduction pathways targeting $2.00–2.30/kg by 2035 through technology learning and co-benefit monetisation. Policy recommendations include extended producer responsibility schemes, government fleet procurement mandates, and regional waste trade agreements across the GCC. Waste-to-hydrogen demonstrates techno-economic viability as a guaranteed baseload contributor within diversified hydrogen strategies for Gulf economies. Full article

Living Wall Systems (LWS) are vertical vegetated building façade systems that offer environmental and social benefits; however, their adoption in South Africa, particularly within the Western Cape (WC), remains limited due to high capital and maintenance costs and the absence of regionally adapted design and cost models. This study investigates the viability and design development of LWS in the WC from a Quantity Surveying (QS) perspective, with the aim of developing a context-specific system utilising indigenous plant species and assessing its economic feasibility over the building life cycle. This study employed a mixed method research approach comprising a literature review, semi-structured interviews with industry professionals, thematic analysis, cost modelling, and the preparation of a detailed Bill of Quantities (BOQ). Life cycle costing (LCC) techniques were applied to evaluate long-term cost implications. The study resulted in the development of a criteria-led, context-adapted LWS model, termed Viridis 5045, which satisfies environmental, technical, and contextual requirements for the WC. The BOQ and LCC analyses provide projected capital and operational cost benchmarks for the proposed system. This study demonstrates that the Viridis 5045 model is technically feasible and contextually appropriate for application within the WC, supporting its consideration in sustainable construction practice when evaluated beyond conventional life cycle financial indicators. Future research should focus on the monetisation of long-term benefits, greywater integration, and Whole Life Costing. Full article

In evolutionary computation, distinct clusters that address different subproblems evolve independently of each other, which makes it difficult to exchange genetic information between them. However, a vaguely defined task within one system may be expressed more clearly within another. Effective interaction methods enable subsystems to collaborate more effectively in solving global tasks. By analysing how ambiguous intentions regarding electricity consumption influence actual behaviour in real-world scenarios, we discovered that transaction and negotiation patterns within electricity markets can effectively support this process. By introducing time and third parties, the study presents a semiautomatic, interpretable reasoning community logic system that enables machines to express transaction negotiation patterns. Through formalised operations, it facilitates the conversion of intentions, uncovering hidden relationships within global structures through this liberated form of expression. This paper examines its impact on computational and search paradigms through case studies, enabling collaborative approaches and granularity control via dynamic anchor points, and explores automated peer-to-peer transactions and electricity monetisation within highly abstracted power trading processes. Full article