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.
This study examines the association between board structure and characteristics and the quality of sustainability reporting, using an integrated reporting-based proxy. Thirty-seven companies listed on the Johannesburg Stock Exchange (JSE) in South Africa were selected. Panel data were collected on board size, women on the board, ethnic diversity, the number of financial experts on the board, the average age of board members and their independence. Three control variables were included, namely profitability, firm age and firm size. Sustainability reporting quality (SRQ) was operationalised using the Ernst and Young (EY) Excellence in Integrated Reporting Awards, a categorical rating with four levels: Progress to be made, Average, Good, and Excellent. A multinomial logit model with firm level clustered standard errors was applied to assess the relationship between board structure and SRQ. Under the sample conditions, the results indicate a statistically significant positive association between ethnic diversity and the highest SRQ category. Board size and average board age showed negative and positive associations respectively, but neither was statistically significant after clustering. Board independence, financial expertise and gender diversity were not statistically associated with SRQ. The findings offer insights for policymakers on board composition, with ethnic diversity emerging as the characteristic most strongly associated with high-quality sustainability disclosure under the sample conditions examined.
Vietnam’s post-pandemic tourism recovery raises the question of how renewed visitor growth relates to economic value, climate vulnerability, and mobility-related carbon performance. This study assesses Vietnam’s tourism recovery under climate change and the Net Zero transition using secondary data for 2019–2023. It applies descriptive analysis, recovery indices, system-level emission-to-activity ratios, passenger-aviation Tapio decoupling analysis, and a national-transport system-level proxy elasticity for 2022–2023. National transport and passenger-aviation emissions are treated as system-level proxies for mobility-related carbon pressure and do not constitute a tourism emissions inventory. The results indicate a scale–value–carbon mismatch. In 2023, total tourist volume reached 117.3% of its 2019 level, whereas nominal tourism revenue and average nominal revenue per reported tourist visit reached 89.8% and 76.5%, respectively. Contextual climate evidence indicates vulnerability channels affecting destinations, infrastructure, transport connectivity, business operations, and service continuity. National transport and passenger-aviation emissions reached 104.1% and 93.8% of their 2019 levels. During 2022–2023, national transport emissions grew more slowly than measured passenger activity, while passenger aviation exhibited weak decoupling. Absolute emissions nevertheless increased in both systems. The results indicate short-run relative improvement in emissions performance rather than structural decarbonisation. Three policy priorities emerge: strengthening tourism carbon accounting, integrating climate adaptation into destination and transport planning, and coordinating measures to reduce mobility-related emissions. The diagnostic framework may also be relevant to tourism transitions in emerging economies facing similar climate, mobility, and data constraints.