Search Results (5,972)

The increasing reliance on digital infrastructures has positioned electronic records management systems (ERMS) as critical mechanisms for supporting organisational governance, accountability, transparency, and effective service delivery. This study presents a structured qualitative literature review examining ERMS implementation across developed and developing institutional contexts to identify key determinants, recurring implementation challenges, and contextual variations in adoption patterns. Drawing on studies published between 2012 and 2026, the review adopts a socio-technical analytical framework that categorises implementation determinants into environmental, technological, and organisational dimensions, specifically: governance and policy alignment; technological infrastructure readiness; interoperability and system integration; and human re-source capacity and organisational culture. The findings indicate that successful ERMS implementation depends on the alignment and interaction of governance frameworks, technological capabilities, and organisational readiness. The analysis further demonstrates that these determinants are highly interdependent and vary according to levels of institutional and digital maturity. In developing contexts, implementation is primarily constrained by inadequate infrastructure, financial limitations, weak policy enforcement, and shortages of skilled personnel. In contrast, digitally mature environments increasingly focus on interoperability, metadata standardisation, usability optimisation, and long-term digital preservation. This study contributes to the literature by synthesising fragmented empirical findings into an integrated socio-technical framework, thereby advancing a more structured understanding of ERMS implementation across diverse governance environments. The review also identifies major methodological limitations within the existing literature, including limited empirical validation, weak longitudinal analysis, language bias, and the predominance of single-institution case study designs. The findings provide practical implications for policymakers, information managers, and institutions seeking to strengthen electronic records management and information governance practices. Future research should prioritise longitudinal, comparative, and cross-national studies to further advance theoretical and empirical understanding of ERMS implementation. Full article

This study provides a systematic examination of global research trends and developments in the field of family and marriage over a twenty-five-year period (2000–2025). Employing a hybrid review design, the research integrates bibliometric analysis with PRISMA guidelines to ensure methodological rigor and transparency. Data were retrieved from the Web of Science, where an initial pool of 97,171 records was refined to 2974 eligible publications through a structured screening and inclusion process. The reduction to 2974 publications was the result of structure bibliometrics using CiteSpace, which employs algorithmic thresholds to identify the most structurally significant publications within a large corpus. Utilizing CiteSpace (version 6.4.R1), this analysis maps the intellectual structure and evolution of the field. By synthesizing co-citation, co-authorship, institutional, and keyword co-occurrence data, this study identifies critical collaboration networks, influential contributors, and dominant thematic domains. The findings reveal prominent research clusters, including premarital cohabitation, partner effects, family structure transitions, marital discord, systemic family functioning, and marriage education. Key contributors identified include influential scholars such as Catherine Walker O’Neal, Birditt, Kira S, Higginbotham Brian J, Beach Steven R. H., and Matthew D. Johnson. Leading institutions are the University System of Ohio, the University of California System, the Pennsylvania Commonwealth System of Higher Education (PCSHE), Pennsylvania State University, and Pennsylvania State University–University Park. At the country level, the United States, Canada, England, Australia, the Netherlands, and Belgium emerge as the most significant contributors. The findings offer a comprehensive synthesis of authorship trends, institutional influence, and shifting research trajectories within the field of family and marriage studies. Full article

The article examines how India and Pakistan have interpreted the Indus Water Treaty (IWT) in the broader context of their preference, needs, and constraints. Rather than treating the IWT as a static legal instrument or as a case of institutional resilience, the analysis conceptualizes the Treaty as a performance-based regime, where treaty stability emerges from how states perform their obligations over time rather than from institutional design alone. Adopting a qualitative process-tracing approach grounded in treaty interpretation as operationalized through state practice, this article advances three interrelated arguments: first, the durability of the IWT cannot be explained solely by institutional design, but must be understood as a “performance-based equilibrium” sustained through state practice. Second, this stability historically relied on a pattern of “compliance asymmetry,” in which India, as the upper riparian, exercised restraint well beyond minimal entitlement while Pakistan consolidated downstream dependence through infrastructural development. Third, the growing juridification of dispute resolution since the 2000s, driven by escalating infrastructural friction, has altered the political meaning of compliance, narrowed interpretive flexibility, and reshaped reciprocal expectations. The article contributes to the scholarship of international legal theory and hydro-politics, particularly by reconceptualizing treaty resilience as a function of material and political performance, rather than the formal text alone. Full article

The exponential growth of machine learning (ML) applications in smart grid (SG) research over the past decade has generated a vast and fragmented body of literature that lacks systematic synthesis. This study addresses that gap by presenting a comprehensive bibliometric and science mapping analysis of the ML–smart grid (MLSG) research landscape to date, drawing on 4156 peer-reviewed publications indexed in the Elsevier Scopus database from 2009 to 2025. The principal contributions of this study are fourfold. First, it provides a rigorous quantitative mapping of MLSG publication growth from one document in 2009 to 1163 publications in 2025, representing a growth rate of 116,200%, thereby establishing a definitive baseline for tracking future scholarly development in the field. Second, it identifies the key actors driving MLSG research, including the most prolific authors (Nadeem Javaid, Alsabaan M.), leading institutions (King Saud University, Tennessee Technological University), and dominant nations (India, China, United States), which offers researchers and funding bodies actionable intelligence on collaboration opportunities and research leadership. Third, through keyword co-occurrence and cluster analysis, the study maps the three dominant thematic hotspots structuring current MLSG research—Smart Grid Security, Power Load Forecasting, and Advanced Energy Management—providing a structured intellectual framework that can guide future research prioritization. Fourth, the study delivers a critical thematic literature review of these three hotspots, synthesizing the most impactful ML methodologies and applications reported across 4156 publications, including deep learning-based intrusion detection, ensemble forecasting models, and reinforcement learning-driven energy management. Collectively, these contributions offer a robust evidence base for researchers, policymakers, and industry practitioners seeking to navigate, benchmark, and advance the field of ML-enabled smart grid systems. Full article

Road construction contributes to embodied carbon in infrastructure, with asphalt-bound layers often dominating construction-stage greenhouse gas emissions in flexible pavements. Reclaimed asphalt pavement (RAP) and high-modulus asphalt concrete can reduce virgin material demand and improve structural efficiency, but their sustainability benefit depends on maintaining equivalent pavement performance. This study develops a climate-informed, mechanistic, environmental, and economic Pareto optimization framework for RAP-modified high-performance asphalt concrete (RAP-HPAC) pavement sections in Alberta. The framework couples fitted dynamic modulus master curves, monthly pavement temperature inputs, ALVA layered elastic analysis, Asphalt Institute fatigue and rutting criteria, A1–A5 global warming potential (GWP), and Alberta 2026 installed unit-price cost data. The RAP-HPAC mixture contains 50% RAP and was designed through a balanced mix design to target approximately 80% effective RAP binder activation. Three traffic classes were evaluated: 731, 1300, and 5426 ESAL/day/direction, each with 2% annual compound growth over a 20-year design period. Relative to independently optimized conventional HMA controls, Pareto-selected RAP-HPAC sections reduced P50 construction-stage GWP by approximately 19–30% and first cost by approximately 6–11% at a conservative 0.90× RAP-HPAC cost multiplier. The results show that RAP-HPAC is most beneficial when used as a structural-bound base that replaces conventional asphalt-bound capacity while preserving sufficient granular support. The framework provides a reproducible design-stage approach for comparing recycled high-modulus asphalt mixtures using performance, carbon, and cost criteria simultaneously. Full article

Hidden hunger and grassland degradation represent interconnected governance challenges in northern China’s pastoral areas. Nutrition-sensitive agriculture (NSA) has been conceptualised largely around crop-based systems, with limited attention to grassland grazing systems, where nutritional value is shaped by ecology, feeding practices, seasonality, local knowledge, and market institutions. Drawing on five rounds of fieldwork (2019–2025) across meadow, typical, and desert steppes in Inner Mongolia, this study employs a multi-case comparative design involving 92 semi-structured interviews, 58 policy documents, and long-term observations. Using reflexive thematic analysis, we develop an ecology–nutrition synergy framework to explain local practices and institutional constraints in nutrition-sensitive livestock farming. Three pathways are identified: grass–livestock nutritional balancing, scientific valorisation of native forage, and market experimentation linking ecological origin to nutritional quality. These pathways operate through three mechanisms: ecological mediation of nutritional quality, endogenous quality fluctuation as an inherent feature, and scientific codification of traditional pastoral knowledge. Four structural dilemmas constrain scaling: incompatibility between natural quality fluctuation and industrial standardisation; absence of institutional trust in nutritional premiums; short-term trade-offs between stocking control and nutritional enhancement; and fragmented cross-sectoral governance. The study extends NSA to grassland systems and offers a framework for integrating ecological protection, livestock quality, and nutrition-oriented governance in arid and semi-arid rangelands. Three theoretical contributions are advanced: (i) extending NSA’s conceptual boundary from cropping systems to natural grassland pastoral systems; (ii) embedding a nutrition-output dimension within Ostrom’s SES framework, thereby creating a triple-nested ecology–nutrition synergy framework; and (iii) specifying three grazing-system-specific mechanisms that distinguish grassland livestock systems from both crop-based and confined animal production systems. Full article

The open sharing of data as a factor of production is an important institutional mechanism for promoting sustainable innovation in the digital economy. Using Chinese A-share listed firms as the research sample and exploiting the staggered rollout of government open data (GOD) platforms across prefecture-level cities as a quasi-natural experiment, this paper constructs a staggered difference-in-differences (DID) model to examine the effect of GOD on green collaborative innovation (GCI) and its underlying mechanisms. The results show that GOD significantly promotes GCI, indicating that open government data can help firms strengthen collaboration in green innovation and contribute to more sustainable development. Mechanism analysis shows that GOD promotes GCI through four channels: increasing government subsidies, reducing information asymmetry, raising public environmental awareness, and advancing corporate digital transformation. Heterogeneity analysis reveals that the innovation-promoting effect of GOD is more pronounced in large cities, non-resource-based cities, and southern cities, and is more salient among state-owned enterprises, capital-intensive firms, and mature firms. This paper provides empirical evidence on the microeconomic effects of market-oriented data allocation and highlights the role of GOD in supporting GCI, corporate sustainable transformation, and the sustainable development of the digital economy. Full article

The purpose of this study is to explore how Zimbabwean firms use Environmental Management Accounting (EMA) and climate risk disclosure amid climate policy uncertainty and how managers perceive these practices as relevant to organisational resilience and long-term sustainability within a volatile institutional and macroeconomic context. The study was couched in the interpretivist research philosophy and adopted the inductive research approach. A case study research design, which aligns with a qualitative research design, was chosen for the study. The study employed in-depth interviews with management accountants, finance executives, and industry leaders across firms in Harare. The study adopted the cross-sectional time horizon and analysed data using thematic analysis to develop insights into the role of EMA and climate risk disclosure in times of policy uncertainty. The findings suggest that participants perceived climate policy uncertainty as influencing organisational efforts to reconfigure management accounting practices through greater environmental performance monitoring, adaptive budgeting, and scenario-based planning. The findings of this study suggest that organisational actors interpreted climate policy uncertainty as a condition requiring greater flexibility in budgeting, environmental monitoring, and strategic planning. Participants in this study associated EMA with improved environmental cost visibility and more adaptive approaches to investment appraisal and risk management under uncertain policy conditions. Similarly, participants perceived climate risk disclosure as increasingly crucial for strengthening organisational legitimacy, stakeholder confidence, and institutional credibility. While respondents linked sustainability-oriented accounting adaptation to broader organisational resilience and long-term sustainable growth aspirations, these relationships were understood through managerial perceptions and organisational experiences rather than as directly measurable macroeconomic outcomes. The study contributes to the sustainability accounting literature by providing qualitative, context-sensitive insights into how managers in an emerging economy interpret climate policy uncertainty and adapt EMA and climate risk disclosure practices within volatile institutional conditions. The study further contributes by integrating sensemaking theory and institutional theory to explain how organisational interpretations of uncertainty shape sustainability-oriented accounting adaptation and perceptions of organisational resilience. It is therefore recommended that the regulatory institutional pillar be strengthened to reduce uncertainty and enhance the EMA’s strategic adaptation. Full article

Background: Traditional villages are important carriers of China’s agrarian civilization, and rural tourism has increasingly been promoted as a strategy for local economic revitalization. In this context, governments have introduced external developers and encouraged village–enterprise integration as a community-based governance arrangement, raising questions about its implications for community empowerment. Methods: Guided by sustainable development and empowerment theory, this study adopts a qualitative case study approach to examine the impacts of rural tourism on traditional village communities and the constraints shaping these outcomes. Results: Drawing on empirical evidence from Yunqiu Mountain Village, the findings indicate that rural tourism generates a simultaneous process of empowerment and disempowerment across economic, social, psychological, and political dimensions, with political empowerment remaining particularly weak. Conclusions: The analysis further reveals that the rural collective land system, marked by diluted property rights, together with limited and ineffective community participation mechanisms, constitutes key institutional constraints on community empowerment. By highlighting the dynamic process of “empowerment–disempowerment” under China’s specific institutional arrangements, this study contributes to tourism impact research and provides empirical insights into the contextual applicability of empowerment theory in traditional village tourism development. Full article

Cape Coast is a prominent tourism destination in Ghana, distinguished by its historical landmarks, coastal ecosystems, and cultural heritage. Yet the city faces mounting threats from environmental hazards such as coastal erosion, flooding, extreme heat, and lagoon degradation, which directly compromise the sustainability of its tourism sector. Guided by the Sustainable Tourism Development Theory (STDT) and the Tourism Resilience and Adaptation Theory (TRAT), this study investigates the impacts of these hazards on tourism development, the effectiveness of current disaster risk reduction (DRR) strategies, and the roles of key stakeholders in building sectoral resilience. Using a qualitative research design, data were collected through in-depth interviews with eighteen stakeholders comprising four policymakers, six community leaders, five tourism business operators, and three representatives from non-governmental organisations, alongside documentary analysis of four institutional reports. The study contributes to the literature by demonstrating that fragmented, reactive DRR strategies and weak stakeholder coordination undermine Cape Coast’s tourism resilience, and by showing how urban natural assets, a dimension largely neglected in existing tourism–DRR scholarship, are central to both hazard exposure and adaptive capacity. The findings call for integrated, ecosystem-based DRR frameworks that align governance mechanisms with sustainable tourism imperatives. Full article

Small and medium-sized enterprises (SMEs) are particularly vulnerable when crisis support systems are delayed, unreliable, or difficult to access. This study examines how South African SMEs maintained strategic continuity during COVID-19 by developing the concept of relational substitution, defined as a process in which owner-managers compensate for weak formal support by internalizing continuity work within the employment relationship. The study is based on a secondary qualitative analysis of 16 semi-structured interviews with SME owners in the Western Cape, South Africa, complemented by a targeted evidence review to inform boundary-condition assessment. The findings show that owner-managers assembled relational continuity bundles that combined labor flexibility, retention intent, transparent communication, and visible well-being support. Owners presented these bundles as efforts to sustain cooperation, trust, and operational functioning when enacted through fairness logics such as voice, transparency, equal sacrifice, and relational care. The study contributes to SME resilience and management and organization studies by distinguishing relational substitution from sustainable human resource management, organizational justice, relational leadership, and institutional fragility, and by specifying the firm-level and institutional conditions under which this mechanism is more likely to support strategic continuity. Full article

To clarify the internal mechanism through which the scale of higher education influences regional economic development, this work constructed an operational framework of education, talents, science and technology, and industry. Based on the 2023 data of 31 provincial administrative regions in China, covering 178 national high-tech industrial development zones, an empirical analysis was conducted using descriptive statistics and the Bootstrap mediating-effect test. The findings indicate that the expansion of higher education scale can enhance the level of talent supply, promote the agglomeration of scientific and technological innovation resources, drive the development of industrial scale, and thereby significantly boost economic growth. Among these pathways, the scale of the undergraduate and postgraduate student population exerts a complete mediating effect, while research and development investment and the number of enterprises in high-tech zones demonstrate a partial mediating effect. Notably, a striking contrast emerges between regular undergraduate institutions and double-first-class universities. The former exhibit significant positive mediating effects, whereas the latter’s economic driving effect remains largely unrealized. Furthermore, the uneven distribution of high-quality educational resources, particularly the spatial polarization of double-first-class universities, coupled with a mismatch between talent cultivation and industrial demands, and the “spatial isolation” of achievements, all restricted the radiating effect of higher education on regional economies. Therefore, it is necessary to implement a regionally differentiated layout of higher education, optimize the allocation mechanism of scientific and technological innovation resources, strengthen industry–university–research collaboration, and give full play to the effect of industrial agglomeration. Full article

Spanish journalists do not suffer from work-related anxiety because they lack resilience; they suffer from it because they work in environments structurally designed to produce it. Based on this premise, this study develops the first empirically grounded multilevel governance model to reduce work-related anxiety among journalists, drawing on 23 in-depth interviews with Spanish professionals who have experienced it through either a diagnosis or self-report, analyzed using reflective thematic analysis. The findings are organized into three interconnected levels—micro, meso, and macro—and identify, respectively, pre-existing protective factors, reactive coping strategies, and advice and recommendations aimed at structural change. Anchored in Job Anxiety Theory and evidence from equivalent complex interventions, the model demonstrates that individual resources only produce sustainable effects when the organizational and sectoral levels actively support them. The asymmetry between the density of the micro level and the precariousness of the meso and macro levels constitutes the study’s central finding. Our model redefines anxiety in journalism as an institutional design challenge and offers a scalable, modular, and contextualized architecture for the Spanish media ecosystem. Full article

Farmers’ investment decisions can shape their capacity to implement practices consistent with sustainable development objectives. The article identifies the declarative structure of investment decisions on Polish dairy farms based on a survey and diverse theoretical frameworks (resource-based view, institutional approach, real options theory, behavioural theory, and the theory of planned behaviour). The purpose is to identify the determinants of the extent and structure of declared agricultural investments. The authors determined the relationships between declared investments and groups of variables and identified investment axes and interdependencies. Investment decision predictions are founded on logistic regression, an SEM model for relationship structuring, and residual correlation analysis for mapping relationships and evaluating the correlation demasking effect, according to which raw correlations between investment axes may hide underlying residual associations between them. We found that declared farmland investments were associated with milk production volume and appeared to be linked to long-term farm development objectives. The respondents became less keen on investing in livestock production as they aged, whereas older farmers showed a greater propensity to undertake energy-related investments. These results suggest that farmers’ declared investment intentions may be consistent with conditions conducive to achieving sustainable development objectives through their potential association with farm viability, resource-use efficiency, and rural economic development. Our findings may have potential policy relevance by informing the design of public measures aimed at strengthening farms’ adaptive capacity in the context of sustainability transitions. Full article

Background/Objectives: Artificial Intelligence (AI) integration in healthcare promises improved diagnostic accuracy, patient safety, and operational efficiency. However, AI acceptance among healthcare workers remains limited due to knowledge gaps, risk concerns, and governance challenges, particularly in developing countries like Saudi Arabia, where rapid healthcare modernization faces unique infrastructure, organizational, and cultural challenges. This research investigates the factors influencing AI acceptance among medical practitioners, nurses, administrators, and students in Saudi Arabian hospitals to identify key determinants and barriers to adoption. Methods: This cross-sectional study employed an extended Unified Theory of Acceptance and Use of Technology (UTAUT) framework integrated with ethical considerations from the Model for Ethical Assessment and Analysis of AI in Medicine (MEAAM). A structured bilingual questionnaire was administered to 119 healthcare professionals and students across Saudi Arabia, measuring constructs including Awareness and Knowledge, Performance Expectancy, Effort Expectancy, Facilitating Conditions, Social Influence, Trust, Perceived Risk, Ethical Governance, and Price Value. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed for quantitative analysis, supplemented by thematic analysis of open-ended qualitative responses. Results: The PLS-SEM analysis explained 59.8% of variance in behavioral intention to adopt AI (R² = 0.598). Awareness and Knowledge emerged as the strongest predictor (β = +0.505, p < 0.001), followed by Performance Expectancy (β = +0.229, p < 0.05) and Social Influence (β = +0.123). Perceived Risk functioned as the primary barrier (β = −0.185, p < 0.05). Qualitative findings identified infrastructure gaps, regulatory ambiguities, and training deficiencies as major implementation barriers, while emphasizing opportunities in diagnostic accuracy and remote monitoring. Conclusions: AI acceptance in Saudi healthcare is primarily driven by knowledge, with perceived usefulness and peer support as secondary facilitators, while safety and accountability concerns remain substantial obstacles. Successful AI integration requires coordinated efforts in education, transparent governance frameworks, and institutional support. This study contributes theoretically by validating extended UTAUT in a non-Western healthcare context and practically by providing evidence-based strategies for sustainable AI adoption that enhance healthcare quality while respecting professional roles and ethical principles. Full article