Abstract: Against the backdrop of rural revitalization, traditional villages in Guizhou's ethnic minority regions face the dual challenges of preservation and development. Existing research predominantly focuses on macro-scale morphological descriptions, lacking an operable spatial classification method that can directly guide planning and management. To address this gap, this paper takes Fengxi Village in Dejiang County as a case study, integrates Conzenian urban morphology theory with the concept of "management units", and proposes a spatial unit classification method for traditional villages based on the overlay analysis of "morphological regions + property parcels". First, the Conzenian plan analysis method is employed to systematically deconstruct Fengxi Village's land use, road system, plot combinations, and building types, thereby delineating its morphological regions. Subsequently, three evaluation factors—building value, quality, and appearance—are innovatively introduced. Through quantitative evaluation, all 702 buildings in the village are classified into five categories: preservation units, restoration and improvement units, comprehensive renovation units, demolition and renewal units, and new development units, with the quantities and proportions of each unit type statistically analyzed. Building on this foundation, differentiated control guidelines and development strategies are proposed for each unit category. The research indicates that this method achieves a transformation from "morphological description" to "implementable control", breaking down the vague goal of "holistic preservation" into concrete "unit-based guidance" actions, and provides a replicable technical pathway for the refined planning and management of traditional villages. The innovation of this paper lies in constructing a complete technical framework of "morphological analysis - factor evaluation - unit control", addressing the deficiency of existing research at the micro-operational level.

Abstract: Smart manufacturing depends on operational data that remain continuous, interpretable, and reusable in practice. In constrained small and medium-sized enterprise (SME) factories, however, the main bottleneck often lies not in later-stage analytics or AI applications, but in securing an operationally viable data foundation under real deployment conditions. A lifecycle-based analysis of smart manufacturing data pipelines, together with recurrent SME deployment constraints identified in prior studies, led this study to derive six recurring operational risks. On that basis, the study proposes an Operational Data Foundation Framework structured around core requirements of continuity, governance, diagnosability, operability, reprocessability, and evolvability. These requirements are further articulated through design principles and assessable operational invariants. The framework was instantiated in a real SME factory, where heterogeneous field sources were integrated into a coherent operational data foundation for smart manufacturing through constrained communication paths, durable edge-side capture, cloud-side stream processing, controlled data normalization, and monitoring and alerting functions. Requirement-based evidence from the field implementation showed that the system preserved stable semantics across the pipeline, made failures traceable to specific lifecycle segments, preserved historical records for later reprocessing, and remained manageable under constrained deployment conditions. A representative field case further demonstrated the framework's practical value: severe communication instability was diagnosed through lifecycle-segment discrepancy analysis and improved from approximately 33% to 95% packet reception after targeted intervention. The study contributes a field-grounded and assessable design logic for making smart manufacturing practically achievable in constrained SME factories.

Abstract: Land degradation, characterized by declining soil fertility and erosion, is a major constraint to maize productivity in Malawi, where more than half of the arable land is degraded. Although knowledge of soil fertility is critical for efficient input allocation, most smallholder farmers rely on subjective assessments of soil quality, potentially leading to imprecise decisions. This study examines how farmers’ perceptions of soil fertility and erosion influence input allocation and maize productivity among smallholder farmers in Malawi. Using plot level data from the Malawi Integrated Household Survey, we apply a Conditional Mixed Process estimator and Stochastic Frontier Analysis to assess input use behaviour and technical efficiency. Results indicate that farmers allocate more labour and inorganic fertilizer to plots perceived as fertile, and adoption of improved maize varieties is lower on plots perceived as poor. In contrast, organic manure is more frequently applied on degraded plots. Mean technical efficiency is estimated at 0.62, indicating substantial inefficiency relative to the production frontier. Technical efficiency declines monotonically with worsening soil conditions, falling from 0.76 on good plots to 0.52 on poor plots and 0.47 on highly eroded plots. These findings highlight sustainability risks and underline the need for improved soil diagnostics and targeted extension services.

Abstract: The fishing processing industry in Chimbote, Peru, reflects structural vulnerabilities common in extractive sectors of the Global South, including labour informality, weak occupational safety, and limited Internal Corporate Social Responsibility (ICSR). These conditions hinder progress toward Sustainable Development Goal 8 (SDG 8). While prior studies link ICSR to positive employee outcomes, the mechanisms through which its effects translate across organisational levels remain theoretically underdeveloped, par-ticularly in high-informality contexts. A quantitative, explanatory, cross-sectional design was employed using data from 384 workers in fishing processing firms. Data were col-lected through a 26-item Likert-scale instrument. Partial Least Squares Structural Equation Modelling (PLS-SEM) was applied to test a sequential mediation model, where ICSR in-fluences organisational-level labour management through individual and group-level processes. Reliability and validity were confirmed using Cronbach’s alpha, Composite Reliability, AVE, Fornell–Larcker, and HTMT. Structural relationships were assessed via bootstrapping (5,000 subsamples), and predictive relevance was evaluated using Q² and PLS Predict. The measurement model showed adequate reliability and validity. The direct effect of ICSR on organisational-level labour management was non-significant (β = 0.029, p = 0.567). However, all mediated paths were significant: ICSR → Individual (β = 0.608), Individual → Group (β = 0.526), and Group → Organisational (β = 0.396), all p < 0.001. Sequential mediation was confirmed (β_indirect = 0.127; 95% CI [0.090, 0.164]). Model fit (SRMR = 0.045) and predictive relevance (Q² = 0.150–0.361) were satisfactory. ICSR does not directly influence organisational outcomes; instead, its impact operates through a bottom-up multilevel mechanism, reinforcing individual, group, and organ-isational dynamics. These findings contribute to sustainable labour governance and multilevel organisational theory.

Abstract: Elderly people have the right to essential welfare and support services that encompass access to healthcare services. This article explores the day-to-day psycho-social en-counters of elderly women in accessing health services in rural Zimbabwe. The re-search utilised the qualitative research approach in which four key informants were purposively selected for interviews and the snowballing sampling technique used to reach out to eight elderly women who participated in the study. The study was guided by the Human Rights-Based Perspective which informs our thoughts on vulnerabilities of elderly women’s in rural Zimbabwe. The study established that the difficulties of el-derly women are tied to the deteriorating health status due to ageing connected to de-clining family support. As a consequence, the elderly women find themselves in some form of social isolation which generates a state of peril for the rural elderly women. The study established that such isolation results in acute vulnerability, intensified marginalisation and diminished access to essential healthcare services. The study recommends that the duty-bearers, that is, the state and stakeholders, should take up their responsibilities and design tailor-made health services that cater for the daily needs of elderly people in rural communities.

Abstract: This study defines grain production resilience as the stability of grain output under climate-related disturbances, measured by the negative value of the three-year rolling coefficient of variation of grain output. It incorporates agricultural insurance and farmland infrastructure into a unified analytical framework and treats climate shocks as state variables to examine their effects on grain production resilience and their interaction. Using panel data for 31 provinces in China from 2008 to 2024, this study constructs temperature and precipitation shock indices based on ERA5 data and estimates a panel smooth transition regression model. The results show that climate shocks significantly weaken grain production resilience, and their effects are nonlinear and state dependent. Farmland infrastructure has a relatively stable positive effect, whereas agricultural insurance plays a weaker role. Under temperature shocks, the two policy tools tend to exhibit a substitutive relationship. Under precipitation shocks, however, their relationship varies across shock regimes and becomes more complementary only under higher-shock conditions. These findings suggest that grain production support policies should be adjusted according to the type and intensity of climate shocks.

Abstract: Climate change is a global pressing concern that has affected all sectors, including the operations for Small and Medium Entreprises (SMEs) in developing countries, including Malawi. This has negatively affected the economies of scale, and exacerbated the SMEs’ growth. Nonetheless, renewable efficient energy (REE) systems, including solar and biogas, could help in building resilience to sustain their performance. In line with this, the study examined the factors that enhance the adoption of the renewable efficient energies, and constructed their resilience indices. Our study was grounded in the Diffusion of Innovation Theory and the Sustainable Livelihoods Framework. These theories guided the selection of variables to estimate a Multinomial Endogenous Switching Regression (MESR) econometric model, alongside estimating the absorptive, adaptive and transformative individual indices for 699 SMEs, using the 2019 Malawi Household Integrated Survey. The results from the MESR suggests that factors, such as access to credit, being male, access to education, access to capital sources, large profit share, bridging social capital and location among others, have a positive effect in influencing the adoption of renewable efficient systems. We simulated the adoption results, and found that SMEs who adopts REE increase their resilience by 87,3% and through the subsidy policy effect vulnerable SMEs who later adopts REE would shift their resilience by 0.169. Furthermore, the study found that transformative capacity plays the most important role in building long-term resilience for the SMEs. The study calls for polices, including establishing urban centers where SMEs can access information regarding REE and improving access to formal safety nets and capital sources beyond loan provisions.

Abstract: Technology adoption theories developed in institutionally mature contexts assume stable hierarchies among determinants, with perceived usefulness typically dominating. This paper qualifies this assumption by proposing that adoption hierarchies are institutionally contingent. Drawing on institutional voids theory and digital finance research, the paper develops a framework identifying three adoption regimes that function as ideal types which may overlap within contexts: (a) institutional trust dominant, where strong market supporting institutions enable usefulness-centered adoption; (b) vendor trust compensatory, where institutional voids elevate vendor-specific trust to primary importance; and (c) infrastructure-constrained, where basic access functions as a direct behavioral determinant. The framework extends technology acceptance theory by specifying when hierarchies change, theorizing trust as a compensatory mechanism, infrastructure as a hard constraint based on physical feasibility rather than perceptions, and a digital leveling effect explaining selective cultural influence. We derive propositions and outline a research agenda for cross-country and longitudinal validation, with implications for technology acceptance theory and digital financial inclusion practice.

Abstract: The rapid proliferation of healthcare data from electronic health records (EHRs), medical imaging systems, laboratory devices, and IoT-enabled patient monitoring devices has created unprecedented challenges for healthcare data management. Traditional Extract, Transform, Load (ETL) tools have long been employed to collect, integrate, and load data into centralized repositories such as data warehouses and data lakes. However, conventional ETL processes are often limited by rigid rule-based transformations, inefficiencies in handling unstructured or semi-structured data, and lack of automation in data quality assurance. This study investigates the integration of Artificial Intelligence (AI) techniques into ETL pipelines to enhance healthcare data management. AI methods—including machine learning, deep learning, and natural language processing (NLP) are incorporated to automate anomaly detection, optimize transformation rules, and extract insights from unstructured clinical text. A conceptual framework is proposed for an AI-augmented ETL system that ingests heterogeneous healthcare data, applies intelligent transformations, and loads high-quality, enriched datasets into a secure data warehouse. The system architecture enables real-time and batch processing, anomaly detection, and adaptive learning to improve ETL efficiency over time. Evaluation metrics include data quality improvement, processing speed, anomaly detection accuracy, and scalability. The findings demonstrate that AI-enhanced ETL significantly reduces data errors, accelerates processing, and provides enriched datasets suitable for downstream analytics, predictive modeling, and decision-making in healthcare operations. By integrating AI into ETL workflows, healthcare organizations can achieve more reliable, timely, and actionable data management, supporting clinical decision-making, operational efficiency, and regulatory compliance. This study contributes to the literature on intelligent data engineering in healthcare, presenting a scalable framework for future research and practical implementation in complex healthcare IT ecosystems.

Abstract: Mental disorders are among the leading causes of disability worldwide and impose substantial economic costs on individuals, healthcare systems, and national economies. While the clinical rationale for early identification of mental disorders is well established, the economic implications of systematic early screening and detection remain underemphasized in policy discourse. This paper examines the economic advantages of early screening and early detection of common and severe mental disorders, integrating findings from epidemiology, cost-of-illness studies, cost-effectiveness analyses, and health systems research. Evidence consistently demonstrates that delayed diagnosis is associated with increased healthcare utilization, reduced labor force participation, lower lifetime earnings, and higher social welfare expenditures. Conversely, early detection—particularly when integrated into primary care and early intervention services—has been shown to improve functional outcomes and, in many contexts, to be cost-effective or cost-saving from a societal perspective. The analysis supports the conclusion that early mental health screening constitutes not only a clinical priority but also a fiscally responsible strategy for health system sustainability and economic productivity.

Abstract: This paper investigates knowledge in the field of digitalization risk management through bibliometric analysis, in order to provide a critical overview of scientific knowledge and highlight future research directions. The main goal involved bibliometric analysis of publications from 2009-2025 using VosViewer and Biblioshiny - Bibliometrix. The research was conducted following a specific methodology and protocol for the design, planning and data collection for the review process; carrying out the review and bibliometric analysis; and evaluating and presenting research findings. The inclusion of studies in the analysis was carried out in accordance with PRISMA 2020 flow diagram template for systematic reviews. The most important results of the research seem to indicate that the analyzed period was marked by an upward trend in scientific interest, with an increase of publications after 2018-2019 and as a result of the Covid-19. The most productive countries are Germany, Italy, Russia, Ukraine and China. The most prolific institutions are Seoul National University and State University of Trade and Economics. Citations tend to follow the annual publication rate. According to thematic map, risk management is one of the motor themes and, as an element of originality, future research trends in this area include themes such as transformation, systems, resilience and digital risks.

Abstract: Background: Negative public attitudes promote undesirable stereotypes and stigma in stutterers. Method: To mitigate negative attitudes, 16 international samples of 403 total respondents took the Public Opinion Survey of Human Attributes–Stuttering (POSHA–S) before and after interventions and were compared to seven combined control groups with 249 respondents. Investigators sought (a) to replicate an extreme case of regression to the mean, the “crossover” effect reported earlier in larger combined samples where negative changers with high pre-scores ended with low post-scores and positive changers with low pre-scores finished with the high post-scores and (b) to identify POSHA–S items related to attitudes overall change and among negative, minimal, and positive changers. Results: As in previous studies, stuttering attitudes improved in the intervention group but not the control group. Intervention and control respondents demonstrated “crossover” but less than the earlier samples due to lower pre-post correlations. Item contributions to pre-post change and differences among the three changer groups were inconsistent; however, high agreement items by respondents were less likely to vary than items with less unanimous agreement. Conclusion: The “crossover” effect was replicated, and future research should explore its presence in other measures or conditions.

Abstract: Psychological constructs such as anxiety, depression, fatalism, divine control, luck, helplessness, and internality are pressing subjects in the United States (US). Although several studies have explored how specific covariates influence these constructs, like depression and anxiety, less is known about how predictors interact to predict the different subscales of fatalism, namely, fatalism, luck, divine control, helplessness, and internality. This study addresses the gap by using Conditional Inference Trees (CIT) to explore how interactions among predictors influence these constructs. Using a nationally representative survey of 2,000 respondents, CIT was employed to investigate how covariates, including Adverse Childhood Experiences (ACE), age, gender, race, education, and urbanicity, interact to predict each construct. Our analyses revealed that for the scales of fatalism, education, age, and race were key predictors, but their effects varied across the subscales of fatalism- fatalism, divine control, luck, helplessness, and internality. For instance, higher levels of education and younger age were associated with higher levels of fatalism and internality. ACE interacted with race to provide different levels of helplessness and divine control. In addition, by leveraging CIT, we were able to identify subtle interactions between covariates in predicting psychological constructs, primarily those related to the multi-fatalism scale.

Abstract:

Background: There is a proliferation of terms that are used to define and describe qualitative methods of review synthesis. These terms can make understanding which approach to use difficult and the ability to generate operational clarity challenging. This is particularly important for life-span mental health research and further research is required that exams and maps the terms and approaches to synthesis. Objective: This scoping review aims to map the landscape of qualitative synthesis methods, evaluate the ability to operationalise named methods, explore their philosophical foundations and methodological associations and consider the application within a specifically identified area of life-span mental health research. Methods: Following PRISMA-ScR guidelines a scoping review was undertaken. A comprehensive search was conducted across multiple databases and grey literature sources. Articles were included that examined a methodological approach to qualitative synthesis. Data extraction and charting focused on synthesis type, frameworks, philosophical alignment, and operational guidance. Results: Fifty-four articles were identified and within these 14 qualitative methodologies were identified and 5 types of aggregative methods and 10 types of interpretive methods of synthesis. Meta-ethnography, meta-synthesis, framework synthesis were the most frequently cited methodologies. A subset of these methodologies and methods were found to be the more operationalizable and these are discussed. Conclusion: The review highlights significant terminological and methodological fragmentation in qualitative synthesis. It underscores the need for clearer guidance, standardised terminology, and stronger links between synthesis methodologies, methods and philosophical traditions. A decision tree is proposed to support researchers in selecting appropriate synthesis methodologies.

Abstract: Competence-oriented Education for Sustainable Development requires evidence that immersive and gamified learning experiences elicit sustainability-relevant change beyond short pre-post windows. This study examines the Art Nouveau Path, a location-based mobile augmented reality heritage game implemented in Aveiro, Portugal, using a four-wave repeated cross-sectional design with anonymous student samples: baseline (S1-PRE, N = 221), immediate post-activity (S2-POST, N = 439, validated n = 438), follow-up (S3-FU, N = 434), and distant follow-up (S4-DFU, N = 69, validated n = 67). Analyses were anchored in an invariant 25-item GreenComp-based questionnaire (GCQuest) block targeting Embodying Sustainability Values (ESV; 1 to 6 scale) and combined distribution-aware descriptives, nonparametric omnibus and pairwise tests with Holm correction, and planned robustness checks including equal-n downsampling and alternative scoring. Results displayed a pronounced post-activity peak (S2-POST), partial attenuation at follow-up (S3-FU), and convergence toward baseline at distant follow-up (S4-DFU), accompanied by loss of the high-agreement tail. Item-level contrasts indicated that later-wave declines concentrated in effortful self-regulation and critical appraisal items, whereas values endorsement items were more stable. These findings indicate that field-deployable mobile AR heritage paths may generate strong proximal competence-aligned signals, but durable enactment-oriented change is likely to require structured reinforcement and integration into broader curricular sequences.

Abstract: This study explores the relationship between environmental, social, and governance (ESG) disclosure and the financial performance and risk profile of fully Islamic banks, with a focus on the moderating roles of board independence, gender diversity, and institutional ownership. Drawing on cross-sectional data from 30 publicly listed, independently managed Islamic banks in Asia for the years 2018 and 2023, the analysis examines the effects of ESG disclosure on return on assets (ROA), return on equity (ROE), Tobin’s Q, and the capital adequacy ratio (CAR). The findings reveal that ESG disclosure positively influenced ROA in 2018; however, this effect did not persist in 2023. No significant associations are observed between ESG disclosure and ROE, Tobin’s Q, or CAR in either year. Board independence is found to amplify the positive effect of ESG disclosure on ROA in 2018 and on CAR in 2023, while gender diversity enhances the risk-mitigating effect of ESG disclosure only in the later period. Institutional ownership, by contrast, does not exhibit a consistent moderating effect. These results underscore the pivotal role of board composition in unlocking the benefits of ESG disclosure in Islamic banking, while also indicating limited responsiveness from market valuation metrics. The study contributes to the ESG literature by highlighting the time-sensitive influence of governance mechanisms and provides actionable insights for enhancing ESG outcomes through board-level reforms.

Abstract: With the Sustainable Development Goals (SDGs) as a reference, this study systematically examines the evolution, characteristics, achievements, and challenges of China-Africa agricultural cooperation. The study elaborates on how China-Africa agricultural cooperation has transitioned from a politically-driven aid model to a comprehensive framework integrating aid, investment, trade, and technology transfer under the guidance of the Forum on China-Africa Cooperation (FOCAC). Despite remarkable achievements between China and Africa in food security, infrastructure construction, and technology transfer, the analysis identifies persistent dilemmas. These include limited impact on comprehensive regional development, scrutiny over trade imbalances and potential resource exploitation, and ineffective utilization of Africa's diverse agricultural resources. To address these issues, the paper proposes future pathways such as maximizing the potential of Agricultural Technology Demonstration Centers (ATDCs), supporting the development of the entire agricultural value chain, and effectively leveraging digital technology. This study argues that it is necessary to adopt a more comprehensive, integrated, and sustainable approach to improve the China-Africa agricultural cooperation model and promote Africa's achievement of S SDGs.

Abstract: Agricultural Commercialization Clusters (ACC) play a vital role in Ethiopia's agricultural and rural development initiatives, aimed at promoting sustainable livelihoods. This study examines the impacts of ACC practices on the livelihood diversification of rural households in South Ethiopia. Data was collected from 355 households, comprising 177 participants in Agricultural Commercialization Clusters (ACC) and 178 non-participants, using household surveys and qualitative insights from interviews and focus group discussions. Descriptive statistics and econometric modeling, including the Endogenous Switching Regression (ESR) approach, were used to assess the effects of Agricultural Commercialization Clusters (ACC) on livelihood diversification in South Ethiopia. The probit model identified critical determinants of agricultural commercialization cluster, such as education level, total land size, access to irrigation, and proximity to roads and markets. The ESR full information maximum likelihood (FIML) results showed that livelihood diversification was positively influenced by farmland size, access to agricultural extension services, and credit availability. For non-ACC participant households, engaging in ACC practices resulted in an 18.9% increase in livelihood diversification. The results suggest that ACC practices significantly enhance livelihood diversification in the region. In South Ethiopia, achievements of agricultural commercialization clusters significantly contribute to combating unemployment and are directly linked to the Sustainable Development Goals (SDGs), specifically SDG 1, 2, and 3. The study recommends that policymakers and development practitioners enhance access to extension services, credit, markets, roads, and irrigation infrastructure to strengthen livelihood diversification through ACC in South Ethiopia.

Abstract:

Digital transformation in public institutions is increasingly understood as a socio-technical and organizational process rather than a purely technological upgrade. This study presents the design of an ICT-based digital transformation roadmap aimed at improving administrative efficiency and citizen service delivery in a municipal public utility in Ecuador. A mixed-methods diagnostic approach was adopted, combining qualitative evidence from direct observation and a semi-structured interview with the head of the IT department, and quantitative data from a structured online survey administered to citizens. Baseline Key Performance Indicators (KPIs) were established using institutional records, service logs, and workflow analysis conducted over a three-month diagnostic window. Post-implementation KPI values are explicitly treated as {ex ante} projections, derived from process redesign analysis, benchmarking with comparable public utilities, and scenario-based assumptions, rather than empirically observed outcomes. The empirical results demonstrate high citizen readiness and acceptance of proposed digital services, including remote service portals, electronic invoicing, and automated support channels. The projected operational improvements—such as reductions in response and administrative processing times and increased digital transaction rates—are therefore presented as expected performance scenarios. A risk and alternative scenario analysis further examines how organizational constraints, resource availability, governance capacity, and change-management factors may moderate these outcomes. The study contributes a transparent and replicable framework for diagnosing digital readiness and planning ICT-driven transformation initiatives in resource-constrained public utilities, while emphasizing the need for future longitudinal validation using post-implementation data.

Abstract: The aim of this study was to analyze the effect of acute caffeine intake on maximal aerobic speed (MAS) assessed using the 30–15 Intermittent Fitness Test (IFT) in university soccer players. An experimental, randomized, double-blind, crossover design was employed, involving 26 male university team players (n=26). Each participant completed the test under two conditions: caffeine supplementation (220 mg) and placebo, separated by a 72-hour washout period. The final running speed achieved (VIFT) was used as an estimator of MAS. Statistical analysis included descriptive statistics, normality testing, and paired Student’s t-test, with a significance level set at p &lt; 0.05. The results revealed a significant improvement in VIFT under the caffeine condition (19.94 ± 1.67 km/h) compared with placebo (18.72 ± 1.50 km/h), with a mean difference of 1.22 km/h (6.5%) and a large effect size (dz = 1.24; p &lt; 0.001). It is concluded that acute caffeine intake produces a significant ergogenic effect on intermittent aerobic performance in university soccer players, representing a potentially useful strategy to optimize performance in competitive contexts.