Search Results (253)

Organic vanilla production in Mexico holds significant promise but faces substantial challenges that impact its sustainability and market competitiveness. As the native region of Vanilla planifolia, Mexico is endowed with rich biodiversity and a deep cultural heritage surrounding vanilla cultivation. Organic production systems in the country predominantly rely on traditional agroforestry practices, manual pollination, and artisanal curing methods, all of which enhance the quality and distinctiveness of Mexican vanilla. However, production is hindered by critical factors, including low genetic diversity and susceptibility to phytopathogenic diseases, particularly stem and root rot caused by Fusarium oxysporum. In recent years, the application of in vitro micropropagation techniques has shown great potential for obtaining pathogen-free plants and conserving germplasm, offering a sustainable alternative to strengthen organic systems and reduce pressure on wild populations. The labor-intensive processes, yield variability, and the complexity of adhering to organic certification standards are additional challenges to overcome. Shifts in consumer preferences toward natural and sustainably produced goods have increased demand for organic vanilla, offering Mexican producers an opportunity to gain a more prominent position in the global market. Advancing research into disease management, fostering genetic conservation, and integrating scientific advances with traditional know-how are vital strategies for overcoming current limitations. In this context, organic vanilla production represents not only an economic opportunity but also a means to conserve biodiversity, support rural communities, and maintain the legacy of one of Mexico’s most emblematic agricultural products. This review was conducted using a qualitative, narrative analysis of recent scientific literature, technical reports, and case studies related to organic vanilla production in Mexico. Full article

Loquat fruit is valued for its pleasant taste and favorable ripening period. However, its delicate texture and high perishability make it highly vulnerable to damage during packaging, so the fruit is usually packed by hand. Developing a fruit-sizing machine could increase commercial market opportunities. Automated mass detection reduces manual sorting errors and labor requirements. Overall, it enhances grading accuracy, speed, and uniformity in loquat processing. It also helps distinguish between ripe, underripe, and overripe fruits through subtle mass differences. Mass modeling has proven to be an effective baseline approach for the development and optimization of grading machines, and its efficiency has been demonstrated across different fruit types. Here, we present a comparative analysis of various models for mass modeling of six international and Italian loquat varieties (“Algerie,” “Peluche,” “Golden Nugget,” “Virticchiara,” “Nespolone di Trabia,” and “Claudia”) cultivated in southern Italy. On fifty fruits per variety, singular mass and spatial diameters [longitudinal (DL), maximum transverse (DT1), and minimum transverse (DT2) were measured. Linear and non-linear regression analyses, including quadratic, polynomial, and cubic models, were applied to both the complete dataset and individual varieties. A set of predictors was used, including DL (length), DT1 (width), and DT2 (thickness), ellipsoid and oblate spheroid volume. Model performance was evaluated based on higher R² values, and lower RMSE and MBE values. The best general model was obtained using an ellipsoidal volume (R² = 0.97, RMSE = 2.76). Both linear and cubic models demonstrated high suitability across all varieties, with ellipsoidal volume emerging as the most effective predictor. Conversely, (DL) based models were the least suitable, yielding the lowest (R² = 0.41) values in “Virticchiara.” The developed general and specific-variety models and equations provide a solid foundation for establishing high-performance systems for mass and size estimation, which can be effectively integrated into a fruit sizer machine. Full article

Purpose of the article: The study aims to explore how demographic characteristics—including gender, age, education, employment type, household composition, and place of residence—affect perceived financial security among Hungarian adults. It seeks to identify which population segments feel most or least financially secure and to assess the relationship between socio-demographic factors and subjective financial well-being. Methods: The analysis is based on the OECD Financial Culture Survey conducted in Hungary on a representative sample of 1000 adults. Perceived financial security was measured using four questionnaire items related to financial satisfaction, concerns about expenses, and income sufficiency. Independent t-tests, one-way ANOVA, and Welch’s ANOVA were applied to test group differences. Findings & value added: Results indicate no significant gender differences in perceived financial security, while education and employment status show strong effects: higher educational attainment and self-employment or retirement are associated with greater financial security, whereas lack of formal education and disability predict lower security perceptions. Urban residents, particularly in large cities, report significantly higher perceived security than those in smaller towns. The study contributes to the literature by integrating OECD-level data with demographic analysis, highlighting the role of education and labor market position in shaping subjective financial well-being in Hungary. Full article

This paper examines how air pollution affects the distribution of labor income within firms. We build a within-firm incentive model and show that air pollution, treated as an exogenous shock, reduces production efficiency and increases operating uncertainty. In response, firms compress both employee and executive compensation. Because executive pay carries a larger weight on performance- and equity-based components and is therefore more sensitive to profit volatility, it declines by more, mechanically narrowing within-firm pay dispersion. At the same time, rank-and-file wages display downward rigidity. The result is a “synchronized decline with sharper cuts at the top,” a form of spurious equality. Using 2014–2022 data on non-financial A-share listed firms in China, we find that a 1% increase in air pollution is associated with a 0.37% average decline in labor income. Effects are stronger in labor-intensive firms and in firms with weaker unions. Two-stage least squares estimates indicate real consequences: talent outflows and reduced innovation. By linking air quality to wage setting, human capital, and innovation, our results reveal a sustainability channel through which pollution undermines decent work and inclusive growth—issues of global relevance for urban economies. The mechanisms we document are likely to generalize beyond China and inform integrated policies that combine environmental regulation with labor-market and innovation policy to support a just and sustainable transition. Full article

The rapid advancement of emerging technologies is reshaping industries, widening skills gaps, and increasing the demand for technology talent. Limited university–industry collaboration further constrains the alignment between educational outcomes and labor market needs. This study proposes an Integrated Competency-Based Framework for Employability and the Sustainability of Higher Education, focusing on institutional and knowledge sustainability. The Framework integrates a Competency Map that establishes a university–industry shared language and a Digital Platform that facilitates actor interactions, strengthening the characterization, visibility, and connection of student talent and industry opportunities through digital portfolios. The research followed a two-phase approach: design and pilot implementation. During the pilot, the core components of the Framework were developed, and its initial feasibility and potential relevance were assessed through a survey, a workshop, and semi-structured interviews with students, professors, and industry stakeholders. The findings suggest that the Framework may enhance student employability, access to industry opportunities and talent identification, and strengthen institutional processes that support teaching, curriculum development, academic quality enhancement, and accreditation, thus highlighting the potential contribution of the Framework to institutional, knowledge, and socio-economic sustainability. The study makes theoretical, empirical, and practical contributions by advancing competency-based education for employability and the sustainability of higher education. Full article

Shellfish aquaculture is considered a major pillar of the seafood industry for its high market value, which increases the value for global food security and sustainability, often constrained in terms of conventional, labor-intensive practices. This review outlines the importance of automation and its advances in the shellfish value chain, starting from the hatchery operations to harvesting, processing, traceability, and logistics. Emerging technologies such as imaging, computer vision, artificial intelligence, robotics, IoT, blockchain, and RFID provide a major impact in transforming the shellfish sector by improving the efficiency, reducing the labor costs and environmental impacts, enhancing the food safety, and providing transparency throughout the supply chain. The studies involving the bivalves and crustaceans on their automated feeding, harvesting, grading, depuration, non-destructive quality assessments, and smart monitoring in transportation are highlighted in this review to address concerns involved with conventional practices. The review puts forth the need for integrating automated technologies into farm management and post-harvest operations to scale shellfish aquaculture sustainably, meeting the rising global demand while aligning with the Sustainability Development Goals (SDGs). Full article

This article examines intergenerational social mobility as a driver of sustainable development on the case of Lithuania, a country in Eastern Europe. Using data from the European Social Survey (2020), the analysis explores how parental education and occupation shape individual educational and occupational outcomes. Descriptive, correlational, and regression analyses reveal that while structural mobility has been facilitated by Lithuania’s transition from Soviet rule to a market economy and subsequent European integration, family background remains a decisive factor. The study also highlights the key factors that promote or constrain social mobility in contemporary Lithuania. The interaction between mothers’ and fathers’ education fosters the attainment of higher levels of education, whereas mothers’ occupational status and respondents’ gender (male) appear to limit it. Similarly, the achievement of a higher occupational level is positively influenced by the interaction between parental education and the respondent’s own highest educational attainment, while negatively influenced by gender. These findings demonstrate that education not only determines social mobility but also supports the broader objectives of sustainable development by reducing inequality, fostering human capital, and advancing gender equality. The results underscore the importance of inclusive social policies that ensure equitable access to quality education and align educational opportunities with labor market demands, thereby reinforcing social mobility as a foundation for long-term social resilience and sustainability. Full article

Advancing toward sustainable higher education requires simultaneously addressing United Nations Sustainability Goals 4 (quality education) and 5 (gender equality). This mixed-methods case study analyzes how cultural stereotypes and gender expectations influence career choices in the field of computer science, which is highly masculinized in Chile. As a contextual and comparative contrast, the feminization of disciplines such as nursing is considered, illustrating the gender polarization across areas of knowledge. This comparison is not random, since in Chile the health sector stands at the opposite end of the spectrum from technology, as demonstrated by the study’s figures. As a theoretical basis, a simple systematic review of the literature published between 2013 and 2024 (in English and Spanish) was carried out, drawing on Scopus, Web of Science, SciELO, and ERIC databases, following some steps of the PRISMA protocol. Thematic analysis allowed mapping research by region, discipline, and type of intervention. The results confirm the persistence of stereotyped beliefs about skills and professional roles, even in contexts with formal equity policies. Strategies that foster empathy, belonging, and intercultural communication, implemented through mentoring, outreach activities, or curriculum redesign, emerge as key catalysts for more inclusive environments. The study presents a practical case applied to first-year computer engineering students at the Universidad de La Frontera (Chile), in which gendered perceptions embedded in vocational choice processes were identified. By situating this study in Chile’s context, we identify how local structures—school sector, regional labor markets, and gender norms—shape women’s participation in computing. Based on this experience, practical recommendations are proposed for integrating a gender perspective into technology education, including pedagogical strategies, gender-sensitive vocational guidance, and the visibility of role models. Full article

This study addresses the critical challenge of designing retirement savings systems that effectively balance liquidity needs and long-term accumulation in contexts characterized by high unemployment and labor market instability, with a focus on South Africa. Traditional pension schemes often assume uninterrupted careers and stable incomes, assumptions frequently violated in low- and middle-income countries, leading to inadequate retirement security and consumption volatility during working life. Motivated by this gap, we develop a stochastic two-pot retirement savings model that explicitly integrates labor market uncertainty using a Markov chain-based Monte Carlo simulation. The model allocates annual contributions between an accessible savings pot and a locked retirement pot, with individuals optimizing consumption and withdrawal decisions to maximize expected lifetime utility under Constant Relative Risk Aversion (CRRA) preferences. Our findings, derived from calibration to South African labor data, reveal that high unemployment and career uncertainty significantly increase the welfare-maximizing preference for liquidity. This result challenges conventional policies prescribing fixed contribution allocations, such as the one-third/two-thirds split in the new two-pot system, and underscores the importance of flexible retirement savings designs. We conclude that tailoring pension design to labor market realities can enhance both retirement security and welfare in volatile economies. Full article

As the importance of energy efficiency and smart readiness in the building sector has been on the rise, the financial evaluation of smart-ready technologies (SRTs) remains a gap in this field. This study introduces a methodology that comparatively evaluates the cost–benefit relationship between 11 different SRTs across three European countries—Cyprus, Italy and The Netherlands. Key performance indicators (KPIs) for energy-focused aspects such as Country-Specific Energy Savings Potential (CSESP) and Seasonal Smart Efficiency Coefficient (SSEC) and financial aspects such as Smart Readiness Cost Index (SRCI), Labor Cost Impact Factor (LCIF), Return on Smart Investment (RoSI), and Smart Investment Break-Even Period (SIBEP) were used to quantify the performance of the SRTs. The results indicate that regional labor rates, energy pricing, and climatic conditions—as well as relative technology cost–benefit tradeoffs—play a significant role in the economic viability of smart-ready devices. Having low labor costs and energy pricing, Cyprus exhibited the most cost-effective outcomes among the three countries. Italy showed strong returns although the initial investments were higher. The Netherlands was observed to benefit the most from heating-oriented technologies. The study comes to the conclusion that regionally specific methods are necessary for the adoption of SRTs and that techno-economic performance cannot be assessed separately from local market dynamics. The proposed framework supports stakeholders and policymakers in smart building investment and planning by offering a scalable method for device-level benchmarking. These indicators are developed specifically for this study and are not part of the official EU SRI (Smart Readiness Indicator) methodology. Their inclusion supports device-level evaluation and complements ongoing efforts toward SRI standardization. This research directly addresses Sustainable Development Goal (SDG) 7 on Affordable and Clean Energy, as well as SDG 11 on Sustainable Development, by evaluating how smart-ready technologies can contribute to energy efficiency and decarbonization in buildings. Based on the results, further research is needed to expand the indicator framework to additional technologies, include building typology effects, and integrate dynamic factors such as CO₂ pricing and real-time tariffs. Full article

Exploring the dynamic mechanisms of household poverty alleviation is crucial for achieving sustainable poverty reduction and preventing relapse into poverty. However, existing research is often constrained by a static perspective, failing to integrate poverty states with transition processes, and lacking the methodological tools to decipher the nonlinear heterogeneity and spatial dependence inherent in household pathways. This study addresses three critical questions: How can we conceptualize and quantify the dynamic trajectories of household poverty alleviation? What are the key mechanisms that drive households from poverty to stable sustainability? And how do these pathways vary across different spatial contexts? Our analysis, based on an explainable machine learning framework applied to longitudinal data from 107,637 households, yields several key findings. First, household pathways are strongly predicted by their initial typology. Those with heavy burdens and limited labor capacity ($S_{I-4}$) predominantly remained in unstable states (62.5%), while households with human capital advantages ($S_{I-3}$, $S_{I-6}$) achieved stable poverty alleviation directly at rates of 84.9% and 100%, respectively. Second, the transition from instability to stability follows discernible bridging mechanisms, where pathways reliant on skill upgrading prove more decisive for long-term stability than those dependent solely on short-term subsidies. Third, pathways are intrinsically shaped by spatial context, creating a geography of opportunity and risk—from policy compensation in mountainous areas, to resource-institutional synergy in agricultural plains, and labor-market stabilization in mining and peri-urban regions. In conclusion, sustainable poverty alleviation hinges on interventions precisely aligned with both initial household profiles and regional contexts. The central policy implication is to move beyond one-size-fits-all approaches by balancing protective safety nets with capacity-building investments, thereby creating equitable development pathways across diverse geographies. Full article

In pursuit of sustainable development goal 5 (SDG5), this study underscores gender equity and women’s empowerment as pivotal themes in sustainable development. It examines the drivers of women’s empowerment, including education, economics, finance, and legal rights, using data from $n=223$ individuals, primarily women (68.4%) aged 20–30 (69.6%). The research methodology integrates descriptive statistical measures, machine learning (ML) algorithms, and graphical representations to systematically explore the fundamental research inquiries that align with SDG5, which focuses on achieving gender equity. The results indicate that higher educational levels, captured through ordinal encoding and correlation analyzes, are strongly linked to increased labor market participation and entrepreneurial activity. The random forest (RF) and support vector machine (SVM) classifiers achieved overall accuracies of 89% and 93% for the categorization of experience, respectively. Although 91% of women have bank accounts, only 47% reported financial independence due to gendered barriers. Logistic regression correctly identified financially independent women with a 93% recall, but the classification of non-independent participants was less robust, with a 44% recall. Access to legal services, modeled using a neural network, was a potent predictor of empowerment (F1-score 0.83 for full access cases), yet significant obstacles persist for those uncertain about or lacking legal access. These findings underscore that, while formal institutional access is relatively widespread among educated women literate in the digital world, perceived and practical barriers in the financial and legal realms continue to hinder empowerment. The results quantify these effects and highlight opportunities for tailored, data-driven policy interventions targeting persistent gaps. Full article

This study investigates the role of career calling in shaping Chinese graduates’ professional match, with a focus on the mediating role of career loyalty and the moderating effect of industry income. Drawing on Conservation of Resources (COR) theory and person–environment (P–E) fit theory, we developed a three-wave, multi-source design with 2025 graduates across diverse industries. The results reveal that career calling significantly enhances professional match, and this relationship is fully mediated by career loyalty. Moreover, industry income strengthens the positive effect of calling, suggesting that external rewards amplify internal motivation in achieving sustainable career outcomes. Theoretically, the study extends calling research into the graduate labor market and integrates contextual economic factors into the COR and P–E fit frameworks. Practically, the findings highlight the importance of cultivating career calling through higher education, organizational practices, and policy initiatives to improve workforce alignment and long-term career sustainability. Full article

Traffic accidents remain a major global burden, causing mortality, disability, and socio-economic losses that hinder sustainable development. Beyond human suffering, crashes place long-term pressures on health systems, labor markets, and national economies, disproportionately impacting low- and middle-income countries. Estimating the true societal costs of accidents is therefore essential for designing effective, equitable, and sustainable road safety policies. This study applies the Willingness-to-Pay (WTP) method to evaluate the external costs of traffic-related deaths and injuries in Türkiye between 2008 and 2018. By incorporating material and immaterial losses, the WTP framework captures a broader spectrum of impacts than traditional approaches, offering valuable insights into the scale of welfare losses and the value of risk reduction. The findings reveal that external costs rose substantially over the decade, from 1.63% to 2.72% of national Gross Domestic Product (GDP), underscoring that economic losses from road crashes are growing faster than the economy. These results highlight the need for systematic interventions that integrate road safety into national sustainability agendas, including safer infrastructure, behavioral programs, advanced vehicle technologies, and efficient emergency response systems. The evidence presented strengthens the case for prioritizing traffic safety as a fundamental component of sustainable transport and public health strategies. Full article

Higher technical education plays a strategic role in equipping the workforce to navigate rapid technological advancements and evolving labor market demands. Within the Rome Technopole framework, Spoke 4 targets ITS Academies, promoting the development of flexible, modular programs that integrate advanced technical skills with ethical, legal, and societal perspectives. This study reports on a pilot training initiative on Artificial Intelligence (AI) co-designed by the Istituto Superiore di Sanità (ISS), aimed at exploring the ethical, practical, and educational relevance of AI in higher technical education. The module was developed and tested through a multi-stakeholder collaboration involving educators, institutional actors, and learners. A four-phase approach was adopted: (1) initial stakeholder consultation to identify needs and content directions, (2) collaborative design of the training module, (3) online delivery and engagement using a CAWI-based focus group, and (4) mixed-method evaluation, combining quantitative assessments and open-ended qualitative feedback. This design facilitated asynchronous participation and encouraged critical reflection on the real-world implications of AI. Through the four-phase approach, the pilot module was developed, delivered, and assessed with 37 participants. Quantitative analysis revealed high ratings for clarity, relevance, and perceived utility in terms of employability. Qualitative feedback highlighted the interdisciplinary design, the integration of ethical reasoning, and the module’s broad applicability across sectors—particularly Healthcare and Industry. Participants suggested including more real-world case studies and collaborative learning activities to enhance engagement. The findings support the feasibility and added value of embedding ethically informed, interdisciplinary AI education in professional technical training pathways. Developed within the Rome Technopole ecosystem, the pilot module offers a promising approach to fostering critical digital literacy and preparing learners for responsible engagement with emerging technologies. Full article