Tourism villages surrounding Mount Merapi have demonstrated remarkable resilience, recovering from various disruptions and periods of inactivity. However, these communities continue to face significant sustainability challenges that threaten their long-term viability. These challenges stem from both external factors—particularly their location in a disaster-prone volcanic region—and internal factors related to local community capacity and tourism management capabilities. Building and maintaining resilience in these tourism villages is therefore crucial for ensuring sustainable tourism development in the region. This research develops probabilistic scenarios to assess tourism village resilience in the Mount Merapi area of Yogyakarta Special Region, Indonesia, employing a participatory Bayesian Network approach. The study classified administrative villages into two infrastructure-based clusters and selected ten representative tourism villages across both clusters. While the same Directed Acyclic Graph (DAG) framework was applied to both clusters, probability assessments were conducted independently through cluster-specific focus group discussions (FGDs). Key findings reveal that Cluster B demonstrates a higher baseline probability of achieving “Stable” resilience compared to Cluster A. Through strength analysis, government involvement and internal policy frameworks emerged as critical factors with significant interconnections to other variables. Sensitivity analysis identified economic activities, agrotourism development, and cultural preservation as particularly influential variables in both clusters, though their probability conditions differ between clusters. Forward propagation analysis demonstrated how specific states of sensitive variables affect the likelihood of achieving “Stable” resilience in both clusters. Conversely, backward propagation analysis identified the probability conditions associated with the desired “Stable” resilience state. The study concludes that enhancing tourism village resilience requires an integrated approach that simultaneously addresses economic activities, agrotourism development, cultural preservation, social capital, internal policy frameworks, government roles, and natural disaster response. This holistic strategy is essential for these communities to successfully navigate future sustainability challenges and maintain their resilience in an inherently volatile environment.
Traffic-related air pollution constitutes one of the primary threats to public health and environmental sustainability in urban centers worldwide. Historic centers face particular challenges because their narrow streets, irregular urban configuration, and high vehicle concentration during peak hours hinder the implementation of conventional environmental monitoring systems. This research assessed the pollutant emissions generated by vehicular traffic in the historic center of Ayacucho, Peru, an Andean city located at 2,761 meters above sea level with approximately 29,476 inhabitants in the study area. A mesoscopic simulation model was developed in PTV Vissim using the Mahut and Wiedemann car-following algorithm. Data were collected with unmanned aerial vehicles at 14 access intersections and complemented with traffic signal cycle measurements and speed recordings under free-flow and congested conditions. Emissions of carbon monoxide (CO), nitrogen oxides (NOx), volatile organic compounds (VOC), and fuel consumption were quantified across an area of 0.48 km². Model calibration achieved Geoffrey E. Havers (GEH) values below 5 at 81% of the calibration points, and every point fell below a GEH of 10. The Wilcoxon signed-rank test showed significant differences between emissions under free-flow and congested conditions. A heat map identified Jr. 2 de Mayo, Jr. Pizarro, and Jr. Libertad as the segments with the highest emission rates. The findings provide scientific evidence for authorities and urban planners to implement targeted mitigation strategies, and the approach is replicable in historic centers of intermediate Latin American cities with comparable topographic and urban characteristics.
Fast-fashion supply chains are under pressure to deliver greater traceability, provenance, accountability, and measurable sustainability outcomes, yet the evidence base for blockchain-enabled transparency remains uneven. This scoping review mapped primary research on blockchain applications for supply-chain transparency in fast fashion and directly transferable textile-apparel contexts. In this review, fast fashion is defined by compressed product cycles, high stock-keeping-unit turnover, frequent sourcing changes, intense buyer-driven price pressure, and extensive subcontracting. The search concept from the retained review record was translated into six standard bibliographic databases, and the numerically verified screening set comprised 122 de-duplicated records. After title/abstract screening and full-text assessment, 31 primary studies published between 2020 and 2025 were included. Data were charted on study design, setting, blockchain architecture, transparency function, implementation stage, reported outcome, barrier, enabler, and sustainability implication. The synthesis distinguishes findings specific to fast-fashion or apparel supply chains from transferable evidence derived from adjacent textile-fiber settings. Blockchain most consistently enabled tamper-resistant provenance records, audit-ready documentation, product authentication, and more granular environmental accounting when combined with the Internet of Things (IoT), radio frequency identification (RFID), and quick response (QR) identifiers, enterprise systems, or digital product passports. However, direct evidence of social-sustainability effects, such as improved labor rights, wages, working conditions, or grievance resolution, remained limited. The review therefore supports a qualified conclusion: blockchain is a conditional transparency infrastructure rather than an isolated technological solution, and its value depends on credible source-data capture, supplier incentives, governance arrangements, and policy standards that connect material traceability with environmental, economic, and social accountability.
This study evaluates the contribution of the food and beverage industry and food and beverage exports toward sustainable agricultural development in Algeria. Considering the pressure for food security, resource scarcity, and the imperative for diversification away from hydrocarbons, the paper poses whether agro-industrial activities enhance the agricultural value added and addresses the food system resilience and sustainable development of the environment. The study analyzes the annual data of the National Office of Statistics of Algeria and uses the Autoregressive Distributed Lag (ARDL), bounds testing approach to analyze the short and long run relationships of agricultural value added, gross production of the food industries, and food and beverage exports. The findings affirm that there is a long-run equilibrium relationship among the stated variables. It is shown that in the long-run, a 1% increase in gross production of the food industries is associated with a 0.491% increase in agricultural value added, and a 1% increase in food and beverage exports would yield a 0.107% increase in agricultural value added. The error-correction coefficient showed that around 82% of short-run deviations from the long-run equilibrium are corrected within a year. This shows that the food-processing and export capacity may be associated with stronger the agricultural development of Algeria, sustainably framing agro-industrial growth, the reduction of post-harvest losses, and the environmentally sustainable food production policy.
Low-carbon transformation of supply chains is important for climate-change mitigation, yet the mechanisms through which artificial intelligence (AI) contributes to low-carbon performance remain unclear. This study examines the associations between predictive, decision-making, and automated AI applications and low-carbon performance, considering the mediating role of green dynamic capability and the moderating role of low-carbon policies. Structural equation modeling (SEM) was applied to survey data collected from 398 managers and experts in Chinese enterprises using established measures of AI functions, green dynamic capability, low-carbon policies, and low-carbon performance. The results show that green dynamic capability fully mediates the associations of predictive and decision-making AI with low-carbon performance. For automated AI, the indirect effect through green dynamic capability is significant, while the direct effect is at the borderline of statistical significance, suggesting a possible partial mediation pattern that should be interpreted cautiously. Low-carbon policies positively moderate the relationships between all three AI functions and low-carbon performance. These findings suggest that AI is associated with supply chain decarbonization partly through firms’ green dynamic capabilities, while supportive policy conditions strengthen these relationships. The study therefore highlights the importance of integrating AI applications with organizational capabilities and supportive policy environments. Low-carbon performance in this study is perceived performance, reflecting respondents’ subjective assessments rather than independently verified absolute emission figures.
Indonesia occupies a strategically important position in the global energy transition because it is both a major producer of transition minerals and a country pursuing domestic decarbonization. This article develops an integrated sustainability framework to examine how Indonesia’s mining sector can contribute to a just and sustainable energy transition without reproducing carbon-intensive, socially uneven, and weakly governed development pathways. The study adopts a mixed-method design that combines a targeted literature review, policy analysis, and triangulation of secondary data from official and authoritative sources on mineral production, electricity generation, national energy planning, and climate commitments. The results identify four interdependent sustainability tensions that shape the sector’s transition role: value-added industrialization versus decarbonization, investment acceleration versus governance quality, export competitiveness versus ecological integrity, and national strategic gains versus local distributive justice. In response, the article proposes an integrated framework structured around four pillars: environmental integrity, social justice and inclusion, economic transformation, and adaptive governance. The framework is translated into five policy pathways: decarbonizing mine and smelter power supply, strengthening environmental, social, and governance (ESG)-linked permitting and monitoring, expanding local value capture and community safeguards, aligning mineral strategy with electricity and climate planning, and institutionalizing transition metrics for accountability. The article concludes that Indonesia’s mining sector should not be evaluated solely through output growth or downstream investment, but through its capacity to deliver low-carbon industrial value, equitable development, and credible environmental stewardship. The framework contributes a policy-relevant tool for governments, firms, and researchers seeking to govern critical-mineral expansion in ways that support long-term sustainability and a just transition.
This study reflects upon the transformability of the chosen principles of Energiewende (Germany’s energy transition) and policy instruments met in the Iraqi energy and urban scenario. The study does not take it for granted that the German model is directly applicable to other countries. Instead, using secondary sources such as policy documents, institutional reports, and academic literature, this study is comparative and context-sensitive. The analysis focuses on six dimensions: technical and network readiness, financial and investment capacity, institutional and regulatory quality, community acceptance and participation, equity in energy access, and renewable energy potential and energy efficiency. Finally, the Multi-Level Perspective is used to analyze and explain how emerging niche innovations, the prevailing socio-technical regime, and the landscape pressures are connected. Results show how elements of the Energiewende can be adapted and are divided into three types: elements which need little adaptation, elements which need significant adaptation, and elements which require more advanced institutional, technical, financial and/or market conditions. Energy efficiency and distributed solar energy, along with smart metering, reduction of transmission and distribution losses, institutional capacity building, and pilot energy storage and microgrids are the most viable components for the Iraqi environment. In contrast, electricity-market liberalization, sophisticated trading mechanisms, large-scale community ownership, and ambitious decarbonization objectives call for a certain amount of contextual provision and deeper readiness of the system. Based on these results, the study proposes three stages of an adaptive pathway: System Stabilization and Enabling Foundations, Expansion and Institutional Embedding, System Integration and Structural Transformation. Movement between stages is determined by observable improvements in readiness and not by pre-determined levels or timescales. The results also showcase how the framework can be implemented at the city, neighborhood, building and infrastructure level linked by smart urban planning, which offers a spatial and institutional context to operationalize the framework. The key enabling measures are: rooftop solar systems, microgrids, energy-efficient urban development, smart metering, demand management based on data analysis, local governance, and spatial-equity safeguards. The study presents an integrated analytical framework that integrates Energiewende principles, readiness assessment, Multi-Level Perspective, and smart urban planning for situations where the performance of the grid is weak, institutions and financial resources are limited, and access to energy service is unequal. Empirical validation of this framework will be needed by engaging the various stakeholders, spatial analysis, techno-economic analysis, pilot activities, and long-term monitoring.
Small-scale fisheries are vital for coastal livelihoods and food security but face persistent sustainability challenges driven by environmental degradation, climate variability, and structural economic vulnerability. Although sustainability assessments of small-scale fisheries are well established, financial aspects—particularly green finance—are often treated as secondary or mediating factors and remain weakly operationalized within integrated analytical frameworks. This study assesses the sustainability status of small-scale fisheries and identifies key leverage attributes by explicitly embedding green finance-related attributes as cross-cutting drivers within a multidimensional sustainability assessment. Using Multidimensional Scaling (MDS) implemented through the Rapid Appraisal for Fisheries (RAPFISH) framework, sustainability was evaluated across six interrelated dimensions: economic, social, institutional, regulatory, environmental, and cultural. The analysis was applied to coastal small-scale fisheries systems in East Java Province, Indonesia, using ordinal scores derived from expert judgment and stakeholder input. Results show that the cultural dimension exhibits strong sustainability and the social dimension remains moderately stable, while economic and environmental dimensions remain highly vulnerable. Leverage analysis indicates that green finance-related attributes—particularly access to finance, financial intermediation capacity, and policy integration—emerged as high-leverage attributes the overall sustainability configuration despite their limited current implementation. These findings indicate that finance functions as a high-leverage, cross-cutting structural driver in small-scale fisheries sustainability rather than a peripheral factor, offering evidence-based insights for policy alignment, institutional coordination, and targeted financial interventions to strengthen the sustainability of small-scale fisheries.
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