Search Results (218)

This study examines the role of human capital, technological investment, and institutional quality in promoting economic complexity in South Africa, with implications for sustainable development and the strategic role of Small and Medium Enterprises. Motivated by the growing importance of productive sophistication for long-term development in emerging economies (notably SDG 8 and SDG 9), the study examines both long-run and short-run dynamics using the Autoregressive Distributed Lag approach, with robustness checks via Fully Modified Least Squares, Dynamic Least Squares, and Canonical Cointegration Regression. Structural Vector Autoregression is employed to assess the persistence of shocks, while the Toda–Yamamoto causality test evaluates causality. The results reveal that institutional quality significantly enhances economic complexity in the long run, while technological investment exhibits a negative long-run impact, potentially indicating absorptive capacity constraints within industries. Though human capital and income per capita do not influence complexity in the long run, they have short-term effects, with income per capita having the most immediate influence. Variance decomposition shows that shocks to technological investment are essential for economic complexity, and are the most persistent, followed by human capital and institutional quality. These findings show the need for institutional reforms that lower entry barriers for SMEs in industries, targeted innovation policies that support upgrading, and human capital strategies aligned with driven industrial transformation. The study offers insights for policymakers striving to influence structural drivers to advance sustainable industrial development and achieve the SDGs. Full article

The escalating climate crisis and global disruptions have prompted a critical re-evaluation of operations management within manufacturing and supply systems. This conceptual article addresses the theoretical and strategic gap in aligning resilience and sustainability by proposing an Integrated Sustainable Operational Strategy (ISOS) framework. Drawing on systems theory, circular economy principles, and sustainability science, the framework synthesizes multiple operational domains—circularity, localization, digital adaptation, and workforce flexibility—across macro (policy), meso (organizational), and micro (process) levels. This study constructs a conceptual model that explains the interdependencies and trade-offs among strategic operational responses in the Anthropocene era. Supported by multi-level logic and a synthesis of domain constructs, the model provides a foundation for empirical investigation and strategic planning. Key propositions for future research are developed, focusing on causal relationships and boundary conditions. The novelty of ISOS lies in its simultaneous integration of three strategic pillars—circularity, localization, and digital resilience—within a unified, multi-scalar architecture that bridges fragmented operational theories. The article advances theory by redefining operational excellence through regenerative logic and adaptive capacity, responding directly to SDG 9 (industry innovation), SDG 12 (responsible consumption and production), and SDG 13 (climate action). This integrative framework offers both theoretical insight and practical guidance for transforming operations into catalysts of sustainable transition. Full article

This paper presents an Industrial–Ecological Symbiosis Framework that enables industrial operations to achieve quantifiable ecological gains without compromising operational efficiency. The model integrates Mixed-Integer Linear Programming (MILP) with AI-optimised forecasting to allow real-time adjustments to production and resource use. It was tested across the apparel manufacturing, metalworking, and mining sectors using publicly available benchmark datasets. The framework delivered consistent improvements: fabric waste was reduced by 10.8%, energy efficiency increased by 15%, and carbon emissions decreased by 14%. These gains were statistically validated and quantified using ecological equivalence metrics, including forest carbon sequestration rates and wetland restoration values. Outputs align with national carbon accounting systems, SDG reporting, and policy frameworks—specifically contributing to SDGs 6, 9, and 11–13. By linking industrial decisions directly to verified environmental outcomes, this study demonstrates how adaptive optimisation can support climate goals while maintaining productivity. The framework offers a reproducible, cross-sectoral solution for sustainable industrial development. Full article

In response to growing environmental pressures and material constraints, circular economy principles are gaining traction across manufacturing sectors. However, most existing frameworks emphasize design and supply chain considerations, with limited focus on how circularity can be operationalized within internal manufacturing systems. This paper proposes a conceptual model that embeds circular operations at the core of production strategy. Grounded in circular economy theory, operations management, and socio-technical systems thinking, the model identifies four key operational pillars: circular input management, looping process and waste valorization, product-life extension, and reverse logistics. These are supported by enabling factors—digital infrastructure, organizational culture, and leadership—and mediated by operational flexibility, which facilitates adaptive, closed-loop performance. The model aims to align internal processes with long-term sustainability outcomes, specifically resource efficiency and operational resilience. Practical implications are outlined for resource-intensive industries such as automotive, electronics, and FMCG, along with a readiness assessment framework for guiding implementation. This study offers a pathway for future empirical research and policy development by integrating circular logic into the structural and behavioral dimensions of operations. The model contributes to advancing the Sustainable Development Goals (SDGs), particularly SDG 9 and SDG 12, by positioning circularity as a regenerative operational strategy rather than a peripheral initiative. Full article

This study addresses the problem of agricultural waste utilization and nutrition for older adults by developing a food product based on a circular design approach. Pineapple core was used to produce a clean-label dietary powder without chemical or enzymatic treatment, relying on repeated rinsing and hot-air drying. The development process followed a structured analysis of physical, chemical, and sensory properties. The powder contained 83.46 g/100 g dietary fiber, 0° Brix sugar, pH 4.72, low water activity (aw < 0.45), and no detectable heavy metals or microbial contamination. Sensory evaluation by expert panelists confirmed that the product was acceptable in appearance, aroma, and texture, particularly for older adults. These results demonstrate the feasibility and safety of valorizing agri-waste into functional ingredients. The process was guided by the Transformative Circular Product Blueprint, which integrates clean-label processing, IoT-enabled solar drying, and decentralized production. This model supports traceability, low energy use, and adaptation at the community scale. This study contributes to sustainable food innovation and aligns with Sustainable Development Goals (SDGs) 3 (Good Health and Well-being), 9 (Industry, Innovation and Infrastructure), and 12 (Responsible Consumption and Production). Full article

This study addresses a critical gap in understanding how mobile banking applications contribute to sustainable development by introducing a novel text mining framework to analyze sustainability dimensions through user-generated content. We analyzed 120,000 reviews from six major Turkish mobile banking applications using an ownership-sensitive analytical approach that integrates structural topic modeling with four sustainability dimensions (environmental, social, governance, and economic). Our analysis reveals significant institutional differences in sustainability approaches: government-owned banks demonstrate substantially stronger overall sustainability orientation (23.43% vs. 11.83% coverage) with pronounced emphasis on social sustainability (+181.7% growth) and economic development (+104.2% growth), while private banks prioritize innovation-focused sustainability. The temporal analysis (2022–2025) shows accelerating sustainability emphasis across all institutions, with distinct evolution patterns by ownership type. Institution-specific sustainability profiles emerge clearly, with each government bank demonstrating distinctive focus areas aligned with historical missions: cultural heritage preservation, agricultural sector support, and small business development. Mapping to Sustainable Development Goals reveals that government banks prioritize development-focused goals (SDGs 1, 8, and 10), while private banks emphasize innovation-focused goals (SDGs 9 and 17). This research makes three key contributions: demonstrating user-generated content as an effective lens for authentic sustainability assessment, establishing ownership-sensitive evaluation frameworks for digital banking sustainability, and providing empirical evidence for contextualized rather than universal sustainability strategies. The findings offer strategic implications for financial institutions, policymakers, and app developers seeking to enhance sustainable digital banking transformation. Full article

Cities are the growth engines responsible for shaping the global economy, major contributors to climate change, and are significantly affected by it. However, the United Nations adopted the Sustainable Development Goals (SDGs) to make these cities and human settlements inclusive, safe, resilient, and sustainable. Yet, the rapid and unplanned urban expansion exacerbates various environmental challenges and reduces green cover in urban areas. To address these issues and meet the SDGs, stakeholders need to emphasise and optimise urban spaces. This study investigates the borough-level analysis of green spaces and human exposure to green spaces across London using satellite-derived datasets on vegetation and socio-economic factors to examine the variations in urban vegetation cover and urban population exposure to vegetation cover between 2017 and 2024. This study highlights the spatial disparity in green space coverage and exposure to green space between the inner and outer boroughs of London. The methodology used here suggests an average loss of approximately 11 and 9 percent in green space coverage and green space exposure to population, respectively, between 2017 and 2024 across London boroughs. Full article

The global pursuit of sustainable development has intensified the need to integrate Circular Economy (CE), Sustainable Development Goals (SDGs), and Industry 4.0 (I4.0) as mutually reinforcing frameworks. This study explores the scientific evolution and interconnections among these pillars through a dual approach: (i) a scientometric analysis using CiteSpace, VOSviewer, and Bibliometrix in RStudio (2024.12.1+563), and (ii) a targeted mini-review of high-impact literature. A dataset of 478 Scopus-indexed articles (2016–2024) was analyzed, revealing CE and I4.0 as key technological and strategic enablers of the SDGs—particularly SDG 12 (Responsible Consumption and Production), SDG 9 (Industry, Innovation and Infrastructure), and SDG 13 (Climate Action). Moreover, the results underscore an increasing role of enabling digital technologies—such as IoT, blockchain, and big data—in shaping sustainable production systems. An important insight from this work is the growing relevance of policy frameworks as catalysts for implementing CE and I4.0 strategies, especially within national and international sustainability agendas. However, the low citation frequency of “policy” as a keyword indicates a gap in the literature that merits further exploration. Future research is encouraged to conduct in-depth bibliometric studies focused on sustainability-related policies, including regulations that operationalize CE and I4.0 to support SDG achievement. This study contributes a comprehensive overview of emerging research trends, identifies strategic knowledge gaps, and highlights the need for cohesive governance mechanisms to accelerate the digital–ecological transition. Full article

This study investigates medical students’ intentions to adopt AI-powered Natural Language Processing (NLP) tools (e.g., ChatGPT, Copilot) within educational contexts aligned with the perceived requirements of digital sustainability. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT), data were collected from 301 medical students in Saudi Arabia and analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The results indicate that Performance Expectancy (PE) (β = 0.65), Effort Expectancy (EE) (β = 0.58), and Social Influence (SI) (β = 0.53) collectively and significantly predict Behavioral Intention (BI), explicating 62% of the variance in BI (R² = 0.62). AI awareness did not significantly influence students’ responses or the relationships among constructs, possibly because practical familiarity and widespread exposure to AI-NLP tools exert a stronger influence than general awareness. Moreover, BI exhibited a strong positive effect on perceptions of digital sustainability (PDS) (β = 0.72, R² = 0.51), highlighting a meaningful link between AI adoption and sustainable digital practices. Consequently, these findings indicate the strategic role of AI-driven NLP tools as both educational innovations and key enablers of digital sustainability, aligning with global frameworks such as the Sustainable Development Goals (SDGs) 4 and 9. The study also concerns AI’s transformative potential in medical education and recommends further research, particularly longitudinal studies, to better understand the evolving impact of AI awareness on students’ adoption behaviours. Full article

The Belt and Road Initiative (BRI) prioritizes infrastructure investment to enhance regional connectivity and foster sustainable economic development. Therefore, this empirical study aims to examine the impact of the BRI, specifically through Chinese foreign direct investment (CFDI) on sustainable growth in Bangladesh. The study employs the Mann–Kendall trend analysis and the generalized method of moments (GMM). For the Mann–Kendall trend analysis, sectoral FDI and output data from four major industrial sectors, obtained from Bangladesh Bank and CEIC for the period 1996–2020, are used to analyze trends in industrial development. Additionally, to assess the BRI’s role in sustainable development, this study compares green gross domestic product (GGDP) and gross domestic product (GDP) using a GMM analysis of CFDI inflows across 16 industrial sectors from 2013 to 2022, sourced from various databases. Findings reveal that CFDI significantly contributes to domestic industrial growth, particularly in the manufacturing and construction sectors. Although Bangladesh joined the BRI in 2016, a notable surge in CFDI appears from 2011–2012, partially driven by Bangladesh’s economic liberalization policies, and reflects early strategic investment consistent with China’s expanding economic diplomacy, which was later formalized under the BRI framework. The two-step system GMM results demonstrate that CFDI has a stronger impact on GGDP (0.0350) than on GDP (0.0146), with GGDP showing faster convergence (0.6027 vs. 0.1800), highlighting more robust and rapid sustainable growth outcomes. This underscores the significant Chinese investment in green sectors in Bangladesh. The study also demonstrates that the BRI supports the achievement of Sustainable Development Goals (SDGs) 7 (green energy) and 9 (sustainable infrastructure). These insights offer valuable direction for future research and policy, suggesting that Bangladesh should prioritize attracting green-oriented CFDI in sectors like energy, manufacturing, and construction, while also strengthen. Full article

Mining involves daily descents underground and enduring dangerous and difficult conditions. Hence, it is very important to use solutions that will reduce the risk in miners’ work and ensure the greater safety and comfort of work in accordance with the goals of sustainable development. One way is training using virtual reality. Virtual reality provides greater safety (safe training conditions, the possibility of making a mistake without health consequences, practicing emergency scenarios, etc.) and aligns with the Sustainable Development Goals—particularly SDG 3 (health), SDG 8 (decent work), SDG 9 (innovation), and SDG 12 (sustainable production). However, it is also a technology that has its weaknesses (occurrence of contraindications, side effects, etc.). Therefore, the use of VR-based training should be examined in terms of the well-being and health of training employees. Due to this, this article examines the occurrence of psychophysical complaints during VR training; the tolerance and adequacy of the duration of a 50 min training session in VR was assessed; and the average time needed to adapt to the virtual environment was determined. The VR training was developed as a result of a research project conducted by JSW Nowe Projekty S.A. (ul. Ignacego Paderewskiego 41, 40-282 Katowice, Poland), Główny Instytut Górnictwa—Państwowy Instytut Badawczy (plac Gwarków 1, 40-160 Katowice, Poland), JSW Szkolenie i Górnictwo Sp. z o.o. at Jastrzębska Spółka Węglowa Capital Group (ul. Górnicza 1, 44-335 Jastrzębie-Zdrój, Poland) on the development and implementation of innovative training using VR for miners. The solution was developed in the context of mining’s striving for sustainable development in the area of improving working conditions and human safety. The first method used in the study is a survey completed by participants of training courses using virtual reality. The second method is the analysis of trainer observation sheets, which contain observations from training courses. The results revealed that for over 70% of respondents, the need to carry out activities in VR was not associated with fatigue. No average score for psychophysical symptoms assessed by respondents on a scale of 1 to 6 (including disorientation, blurred vision, dizziness, confusion, etc.) exceeded 1.4. The vast majority (85.5%) did not take off the goggles before the end of the training—the training lasted 50 min. This research contributes to the discussion on sustainable industrial transformation by demonstrating that VR training not only improves worker safety and preparedness but also supports development goals through human-centered innovation in the mining sector. Full article

The current study examines the determinants influencing preparatory year (PY) students’ intentions to adopt AI-powered natural language processing (NLP) models, such as Copilot, ChatGPT, and Gemini, and how these intentions shape their conceptions of digital sustainability. Additionally, the extended unified theory of acceptance and use of technology (UTAUT) was integrated with a diversity of educational constructs, including content availability (CA), learning engagement (LE), learning motivation (LM), learner involvement (LI), and AI satisfaction (AS). Furthermore, responses of 274 PY students from Saudi Universities were analysed using partial least squares structural equation modelling (PLS-SEM) to evaluate both the measurement and structural models. Likewise, the findings indicated CA (β = 0.25), LE (β = 0.22), LM (β = 0.20), and LI (β = 0.18) significantly predicted user intention (UI), explaining 52.2% of its variance (R² = 0.522). In turn, UI significantly predicted students’ digital sustainability conceptions (DSC) (β = 0.35, R² = 0.451). However, AI satisfaction (AS) did not exhibit a moderating effect, suggesting uniformly high satisfaction levels among students. Hence, the study concluded that AI-powered NLP models are being adopted as learning assistant technologies and are also essential catalysts in promoting sustainable digital conceptions. Similarly, this study contributes both theoretically and practically by conceptualising digital sustainability as a learner-driven construct and linking educational technology adoption to its advancement. This aligns with global frameworks such as Sustainable Development Goals (SDGs) 4 and 9. The study highlights AI’s transformative potential in higher education by examining how user intention (UI) influences digital sustainability conceptions (DSC) among preparatory year students in Saudi Arabia. Given the demographic focus of the study, further research is recommended, particularly longitudinal studies, to track changes over time across diverse genders, academic specialisations, and cultural contexts. Full article

Ensuring the resilient navigation of unmanned aerial vehicles (UAVs) under conditions of limited or unstable sensor information is one of the key challenges of modern autonomous mobility within smart infrastructure and sustainable development. This article proposes an intelligent autonomous UAV control method based on the integration of geometric trajectory modeling, neural network-based sensor data filtering, and reinforcement learning. The geometric model, constructed using path coordinates, allows the trajectory tracking problem to be formalized as an affine control system, which ensures motion stability even in cases of partial data loss. To process noisy or fragmented GPS and IMU signals, an LSTM-based recurrent neural network filter is implemented. This significantly reduces positioning errors and maintains trajectory stability under environmental disturbances. In addition, the navigation system includes a reinforcement learning module that performs real-time obstacle prediction, path correction, and speed adaptation. The method has been tested in a simulated environment with limited sensor availability, variable velocity profiles, and dynamic obstacles. The results confirm the functionality and effectiveness of the proposed navigation system under sensor-deficient conditions. The approach is applicable to environmental monitoring, autonomous delivery, precision agriculture, and emergency response missions within smart regions. Its implementation contributes to achieving the Sustainable Development Goals (SDG 9, SDG 11, and SDG 13) by enhancing autonomy, energy efficiency, and the safety of flight operations. Full article

This study analyzes the integration of Sustainable Development Goals (SDGs) 9 (Industry, Innovation, and Infrastructure) and 15 (Life on Land) into the tourism development strategies of Lago Agrio Canton, Sucumbíos Province, Ecuador. The main objective is to assess how tourism can serve as a driver for sustainable infrastructure development, environmental conservation, and inclusive local growth, in alignment with the 2030 Agenda. A qualitative methodology was adopted, involving documentary analysis with exploratory and descriptive scopes. The sources included national development plans, regional policy frameworks, institutional reports, and the relevant academic literature. This study employed territorial indicators related to infrastructure quality, ecosystem protection, and stakeholder participation to evaluate SDG alignment. The results highlight that sustainable tourism practices—particularly those incorporating corporate social responsibility and environmental stewardship—can stimulate innovation and enhance resilience in underdeveloped territories. Wetlands and forested areas emerge as key natural assets with strong potential for ecological tourism and sustainable investment. The findings suggest that collaborative actions between the public and private sectors, guided by SDGs 9 and 15, can generate long-term benefits, including biodiversity preservation, improved service infrastructure, and economic inclusion for local communities. Overall, the research underscores the potential of sustainable tourism as a practical mechanism for localizing the SDGs in fragile yet high-value ecological regions. Full article

The relationship between firm size and the financial performance of advertising and marketing companies remains understudied in the academic literature, including in the regional context. Using a panel data methodology, this study analyzes the impact of three proxies for firm size (total assets, number of employees, and sales) on the financial performance (return on assets and profit margin) of the 500 most profitable advertising and marketing companies from 16 Western European countries over the period 2019–2023. Weighted least squares regression analysis revealed statistically significant negative effects of all three proxies for firm size on financial performance, with the strongest negative effects on total assets on return on assets and sales on profit margin, which is similar to return on sales. Empirical data confirm the inverse relationship between total assets and their profitability; this indicates the advantages of resource-optimized business models with high management flexibility and effective use of intellectual capital compared to material-intensive structures. The inverse relationship between the number of employees and financial performance is due to higher operating personnel costs and the difficulty of effectively managing human resources as the number of employees increases. Increased sales negatively affect profit margins, demonstrating a decrease in the efficiency of converting revenue into profits as operations expand. These findings are important for developing effective financial management strategies and making investment decisions in the industry under study. The research contributes to SDGs 8, 9, and 12 by demonstrating how resource-optimized structures with higher management flexibility and effective use of intellectual capital can outperform material-intensive structures in the advertising and marketing industry. Full article