Search Results (47)

Artificial intelligence (AI) is reshaping the hospitality industry at an unprecedented pace. However, existing hospitality research has overwhelmingly concentrated on customer-facing applications, including service robots, chatbots, personalization, and revenue management, while largely overlooking the internal operational systems that sustain hotel performance. As a result, the concept of AI maturity within back-of-house hotel operations remains theoretically undefined, fragmented across functional domains, and lacks an integrated framework for assessment. This study addresses this critical gap by asking a fundamental research question: What does AI maturity actually mean for hotel back-of-house operations? Drawing upon a systematic literature review following the PRISMA protocol, this study synthesizes evidence from 18 studies spanning the interdisciplinary fields of hospitality management, operations management, information systems, and artificial intelligence to examine how AI is transforming core internal hotel functions. The review identifies current applications, implementation patterns, organizational enablers, barriers to adoption, and emerging trends across human resource management, procurement, finance and accounting, inventory management, housekeeping planning, maintenance, energy management, and managerial decision support. Building on these findings, the study develops the Artificial Intelligence Maturity in Back-of-House Operations (AIM-BoH) Framework, a domain-specific conceptual framework designed to conceptualize AI maturity across hotel back-of-house functions. The framework conceptualizes AI maturity as a multidimensional organizational capability encompassing technological adoption, process automation, decision intelligence, data readiness, human–AI collaboration, governance and ethical preparedness, and measurable operational outcomes. By moving beyond technology-centric perspectives, the framework provides a comprehensive model for understanding how AI creates organizational value through the integration of internal hotel processes. The proposed framework advances hospitality literature by establishing a common theoretical foundation for understanding AI maturity in internal hotel operations while offering hotel executives a structured conceptual lens for considering organizational capability development in the planning of digital transformation initiatives. The article concludes by proposing a research agenda for the empirical validation, refinement, and cross-cultural application of the AIM-BoH Framework, positioning it as a reference model for future hospitality AI research and practice. Full article

Background: Logistics and supply chain resilience research typically assumes access to formal infrastructure, including contracted fleets, warehouses, inventory systems, and institutionalized contingency mechanisms. Yet many micro and small enterprises (MSEs) in emerging economies operate without these resources, leaving their logistics practices underexplored. This study examines how informal MSEs sustain operational continuity and recover from disruptions through tacit relational support. Methods: Fuzzy-set Qualitative Comparative Analysis (fsQCA) was applied to 400 informal MSEs in Ecuador’s manufacturing, services, and commerce sectors. Tacit network structure was measured using four function-specific name generators covering transport, storage, contingency management, and informal financing. Operational resilience was assessed through order fulfillment rate and recovery time after disruption. Results: No relational-support domain was individually necessary for resilience. Six sufficient configurations were identified, with consistency values from 0.817 to 0.978 and solution coverage of 0.433. One configuration combined contingency-management and informal-financing ties despite low membership in transport and storage networks, indicating a compensatory relational pathway. Conclusions: Tacit personal networks are better understood as context-dependent relational logistics support systems than as substitutes for formal infrastructure. The findings offer bounded, exploratory configurational evidence on selected pathways associated with operational resilience in informal MSEs. Full article

Background/Objectives: Contemporary healthcare systems face compound challenges (including technological acceleration, demographic aging, rising chronic disease burden, and growing patient expectations) that demand models that are simultaneously efficient, high-quality, and person-centered. Despite a substantial body of research addressing organizational design, human capital management, and clinical competencies, these dimensions have largely been theorized in isolation. This study aims to construct and justify an integrated theoretical framework explaining how organizational models, human capital, and transversal competencies may jointly shape care quality, patient safety, and institutional sustainability in healthcare organizations. Methods: A narrative literature review was conducted, integrating contributions from business economics, healthcare management, organizational psychology, and nursing sciences. This design was selected for its suitability in synthesizing heterogeneous, multidisciplinary knowledge into a coherent conceptual framework, a purpose for which systematic meta-analytic approaches are not appropriate. Sources encompassed 79 references: peer-reviewed journals (PubMed, JSTOR, Google Scholar), institutional reports (WHO, OECD, European Commission, Joint Commission), normative standards (ISO 30414:2018), and Italian regulatory frameworks, spanning foundational twentieth-century contributions through the most recent literature (2025). Results: Four principal findings emerged: (1) healthcare organizations are evolving from rigid hierarchical structures toward flexible, value-based configurations, with the Value-Based Healthcare (VBHC) paradigm redirecting institutional attention from service volume to patient-meaningful outcomes per unit of cost; (2) transversal competencies (communication, empathy, emotional intelligence, teamwork, and transformational leadership) are closely associated with care quality and patient safety, with 70–80% of sentinel events associated with communication failures; (3) human capital, encompassing technical expertise and relational capacity, constitutes the primary lever of competitive advantage in healthcare institutions; and (4) the trajectory from pyramidal toward participatory and self-managed models is supported by international evidence, including the Buurtzorg experience in the Netherlands. Conclusions: The integrated three-pillar framework (combining resource-based theory and dynamic capabilities, Value-Based Healthcare, and evolutionary organizational theory) provides a theoretically grounded basis for understanding how organizational structure, human capital, and transversal competencies are jointly associated with clinical performance. Healthcare institutions should systematically integrate soft-skills training into professional education and invest in participatory organizational structures. Health policy should revise financing mechanisms to incentivize patient-meaningful outcomes over service volumes and support the broader transition toward Value-Based Healthcare models. The Italian SSN is discussed as an illustrative national context rather than as the primary empirical focus of the review. Full article

This paper examines the relation between transversal skills, economic education, and financial literacy in modern education. A systematic literature review was conducted in accordance with the PRISMA 2022 methodology, resulting in the selection and analysis of 49 peer-reviewed articles from Scopus and Web of Science. The paper explores theoretical considerations, pedagogical strategies, and the possibility of integrating these fields into educational practice. It identifies three specific points of research interest: firstly, to identify trends in the integration of transversal competencies into economic education; secondly, to assess how transversal skills impact the development of financial literacy; and thirdly, to create recommendations for educational programs and teaching methods. The results highlight that transversal skills—particularly critical thinking, collaboration, being digitally literate, and problem-solving—play an indispensable role in both learning economics and building financial literacy. While students of economic education gain insight into issues such as resource management, market mechanisms, and labor economics, financial literacy provides them with knowledge on personal finance issues, sustainability, and informed decision-making. An original aspect of the research is the attempt to merge transversal skills with economic education and financial literacy within a single framework. The results also indicate future directions of educational reform and point to ways to enhance students’ financial well-being and entrepreneurial capacity. Full article

Global health faces unprecedented challenges driven by communicable diseases, which are increasingly amplified by persistent health inequities, the impact of climate change, and the speed of emerging crises. Prevention is not merely a component but the foundational strategy for an effective, sustainable, and fiscally responsible public health response. This paper delves into the pivotal role of core prevention levers: robust vaccination programs, stringent hygiene standards, advanced epidemiological surveillance, and targeted health education. We detail how contemporary technological advancements, including Artificial Intelligence (AI), big data analytics, and genomics, are fundamentally reshaping infectious disease management, enabling superior predictive capabilities, faster early warning systems, and personalized prevention models. Furthermore, we thoroughly examine the imperative of integrating the One Health approach, which formally recognizes the close, interdependent links between human, animal, and environmental health as critical for combating complex threats like zoonoses and Antimicrobial Resistance (AMR). Despite significant scientific progress, persistent socio-economic disparities, the pervasive influence of health-related misinformation (infodemics), and structural weaknesses in global preparedness underscore the urgent need for decisive international cooperation and equitable financing models. We conclude that only through integrated, multidisciplinary, and resource-equitable strategies can the global community ensure effective prevention, mitigate severe socio-economic disruption, and successfully build resilient healthcare systems capable of withstanding future global health threats. Full article

Urban stormwater management presents significant challenges for municipalities seeking to balance environmental resilience with financial considerations and social equity. This study investigates the factors shaping residents’ willingness to pay (WTP) for a proposed stormwater management fee in Norwalk, Connecticut, within the context of local sustainability plans. A survey of 457 residents assessed demographics, personal beliefs, perceptions of benefits, risks, and WTP. Since participation was voluntary and open, an exact response rate could not be calculated, and the resulting respondent profile differed from city benchmarks. The results were analyzed using descriptive and inferential statistics alongside a Random Forest machine learning model assessing two payment scenarios, achieving classification accuracies above the majority-class baseline (approximately 60–68%). Across both scenarios, expectations of tangible and locally visible outcomes, including infrastructure upgrades and climate resilience improvements, were the strongest determinants of WTP. When respondents evaluated a specific fee amount rather than a general modest fee, concerns about affordability and program effectiveness became more influential and revealed the conditional nature of financial support. The findings illustrate the value of machine learning for analyzing public attitudes toward environmental finance and highlight how policy framing, transparency, and communication shape acceptance of sustainability measures. These insights provide a data-driven foundation for future research on public engagement and equity in local environmental policy and stormwater plan development. Full article

The digitalization of finance has accelerated the diffusion of FinTech and raised new questions about how AI, data security and blockchain shape consumer behaviour. This article examines current FinTech users, focusing on mobile banking, security perceptions, AI-enabled personalisation and trust in blockchain. A structured online survey of 191 adult users was analysed with descriptive statistics, chi-square tests and three multiple linear regression models. Results show that adoption is overwhelmingly mobile centric: 84.8% primarily use mobile banking applications, accessed almost exclusively via smartphones (96.9%). Data security is the dominant decision criterion, rated “very important” by 83.3% of respondents. While 70.1% believe AI can substantially improve the FinTech experience, trust depends on transparent explanations of how algorithms operate and on guarantees of personal data protection. Regression models indicate that usage intensity is higher among younger, higher-income users and those who perceive simplified interfaces as encouraging, whereas positive views of AI are broadly shared and not segment-specific. Trust in blockchain is linked to a pro-technology mindset rather than to socio-demographic or urban–rural differences. The findings highlight “secure convenience” and explainable AI as central conditions for sustainable FinTech engagement. Full article

Tuberculosis (TB) remains a public health threat in low- and middle-income countries (LMICs) of the World Health Organization (WHO) Eastern Mediterranean Region (EMR), driven by a combination of social determinants including undernutrition, fragile health systems, conflict-related disruptions, human mobility and displacement, sub-optimal programmatic implementation, and insufficient domestic investment. These programmatic and governance constraints operate within a broader geopolitical context marked by conflict, sanctions, protracted crises, and large-scale displacement, which further limit countries’ ability to deliver uninterrupted TB services. In 2023, the region’s TB incidence was estimated at 116 per 100,000 population, with Pakistan alone accounting for about 73% of the regional burden. Despite a multitude of efforts, progress in reducing the TB burden in the EMR remains slow, with high case detection and treatment coverage gaps, low uptake of TB preventive treatment (TPT), underutilization of WHO-recommended rapid diagnostics, and only 25% of drug-resistant TB (DR-TB) cases initiated on treatment. Vulnerable populations, including internally displaced persons, migrants, refugees, prisoners, and returnees, continue to face major access barriers, and cross-border TB collaboration remains limited. This commentary reasons that the slow pace of TB burden reduction in the region is not only a biomedical or resource issue but also a reflection of structural and governance shortcomings. It proposes a ten-point strategic vision focused on building a sustainable ecosystem, enhancing primary healthcare systems, adopting people-centered and rights-based approaches, leveraging artificial intelligence, and gradually reducing dependency on external donors where feasible. However, in highly fragile settings such as Yemen or Somalia, domestic financing remains limited, and sustained external support will continue to be indispensable. The commentary calls for stronger national leadership, inclusive stakeholder engagement, and increased domestic financing to deliver integrated and resilient TB services. Ending TB in the EMR is within reach, but it requires boldly committed, coordinated, and country-led action. Full article

The analysis carried out in this work shows that sustainable investment decisions aimed at SDG 7 are mainly driven by objective financial attributes, especially the level of risk and the type of providing institution. The empirical analysis is based on 873 valid responses, balanced by gender and income levels, which enables us to capture heterogeneity in sustainable investment preferences. This study contributes to the literature by jointly examining personality traits and gender as explanatory factors of willingness to pay for investments aligned with SDG 7. In the general model, strong risk aversion—particularly to high risk—and a positive valuation of cooperatives stand out over factors such as explicit reference to SDG 7 or personality traits, which are not significant. Gender segmentation reveals substantial differences: women display a much higher risk aversion and a greater willingness to pay for investing in cooperatives and, to a lesser extent, in sustainable institutions; in this group, extraversion is negatively associated with the choice of SDG 7 funds. For men, risk remains key but with lower penalization, and provider type carries more moderate weight; no relevant link with personality traits is detected. Thus, the gender effect hypothesis is fully confirmed, while the personality hypothesis is partially supported. These results suggest that the design of sustainable financial products should be a WTP adapted to differentiate demographic and behavioral profiles in order to mobilize private capital toward the energy transition. Full article

This study explores the application of spiking neural networks (SNNs) for click-through rate (CTR) prediction in personalized online advertising systems, introducing a novel hybrid model, the Temporal Rate Spike with Attention Neural Network (TRA–SNN). By leveraging the biological plausibility and energy efficiency of SNNs, combined with attention-based mechanisms, the TRA–SNN model captures temporal dynamics and rate-based patterns to achieve performance comparable to state-of-the-art Artificial Neural Network (ANN)-based models, such as Deep & Cross Network v2 (DCN-V2) and FinalMLP. The models were trained and evaluated on the Avazu and Digix datasets, using standard metrics like AUC-ROC and accuracy. Through rigorous hyperparameter tuning and standardized preprocessing, this study ensures fair comparisons across models, highlighting SNNs’ potential for scalable, sustainable deployment in resource-constrained environments like mobile devices and large-scale ad platforms. This work is the first to apply SNNs to CTR prediction, setting a new benchmark for energy-efficient predictive modeling and opening avenues for future research in hybrid SNN–ANN architectures across domains like finance, healthcare, and autonomous systems. Full article

Employees’ green voice behavior (GVB), as a specific category of extra-role green behavior, plays a vital role in promoting a firm’s sustainable development. However, its underlying mechanism has not been sufficiently explored. Drawing on social learning theory (SLT), this study proposes a research model that examines the indirect influence of environmentally-specific transformational leadership (ESTFL) on GVB via psychological empowerment (PE) and ecological reflexivity (ER) as well as the moderating role of person-supervisor value congruence (PSVC). To achieve the research goals, we conducted a two-wave online survey via the convenience sampling method to collect data from 530 employees and 106 direct supervisors working in the manufacturing, hospitality and service, energy production, construction, transportation, information and communication, and finance industries in China. Regression analyses and CFA based on SPSS and Mplus were employed to test and validate the research model. Our findings show that PE and ER both partially mediated the positive association between ESTFL and GVB. Moreover, PSVC moderated the mediating effects of ESTFL on GVB via PE and ER. This study advances empirical research regarding how leadership impacts GVB by revealing dual cognitive mechanisms and identifying its boundary condition. It also offers managerial implications for leaders and enterprises in China to promote employees’ GVB and improve sustainable management. Full article

Waqf investment funds represent an innovative approach to sustainable finance, integrating Islamic investment principles with contemporary social and economic goals. The research explores how Waqf investment funds affect socio-economic factors in Saudi Arabia through their influence on personal income, healthcare systems, and education while analyzing financial sustainability. The study assessed primary socio-economic indicators through beneficiary survey data, expert interviews, and secondary sources. The study used chi-square tests, exploratory factor analysis (EFA), and regression analysis to evaluate the long-term impact of the funds on social welfare and economic stability. The results highlight several significant achievements, the most important of which is that personal income benefited most from enhanced purchasing power. At the same time, healthcare outcomes improved significantly due to support for chronic disease treatments. Support for student housing and living services positively impacted the education sector by providing learning stability and access to educational opportunities. Financial sustainability reached its peak through improved financial security measures. The full potential of Waqf investment funds remains restricted because they face continuous issues with investment diversification, governance effectiveness, and entrepreneurial support. The results show that Waqf investment funds work as a welfare tool while also serving as a strategic tool for sustainable development in line with Saudi Vision 2030 and the United Nations Sustainable Development Goals. Full article

Agroforestry systems (AFSs) exhibit varied composition and dynamics as intrinsic characteristics of their specificities. In this context, a review of the adoption, composition, and dynamics of AFSs in the Amazon biome was conducted to identify the origin, institutions, and researchers of published studies with results on this scientific topic, focused on trends and characteristics of AFSs diversity in the Amazon. The methodology adopted was a scoping review, based on searches in the Scopus and Web of Science databases, using specific keywords to ensure that the articles addressed topics related to the adoption, composition, and dynamics of AFSs in the Amazon. Following the selection of subtopics, 66 articles were selected and analyzed. The analysis revealed that research on AFSs in the Amazon highlights interactions among traditional knowledge, innovations, and sustainability. The analysis of research published between 1996 and 2023 indicated growth in studies with an interdisciplinary focus, primarily from Brazil. However, internationalization, collaborative networks, and funding factors contribute to the prominence of foreign institutions. Research studies often address topics such as species diversity, agrobiodiversity, and tree growth in agroforestry intercrops. In this context, homegarden agroforestry (HAF) emerges as one of the main subjects of study, encompassing multifunctional environments, richness diversity, and ongoing experimentation with plant species. The choice of species for AFSs is influenced by factors such as labor, personal preferences, and market demands, although loggers and commercial forestry systems tend to have lower diversity, contrasting with HAF. AFSs implementation methods vary according to financing, management, and the farmer’s education and gender. Environmental conservation, food security, ecosystem services, and production flexibility are highlighted as benefits of AFSs, while challenges include technical and economic limitations. This research highlights the strengthening and consolidation of AFSs by addressing scientific gaps and demonstrating the need for studies on the adoption, consolidation, and management of these systems, as well as the relationship between diversity and yield. Future research should be concentrated on deepening studies on the relationship between diversity and yield in AFSs, as well as on management strategies that support the consolidation of these systems in the Amazon biome, integrating innovation, public policy support, and traditional knowledge of farmers. Full article

In the process of government management, officials may engage in rent-creation and rent-seeking within finance and debt management for personal gain, leading to corruption and jeopardizing government debt sustainability. Can anti-corruption effectively ameliorate this predicament? Based on the growing severity of global debt sustainability, 30 provincial-level administrative regions in China are used as research samples to explore the influence of China’s anti-corruption campaign targeting officials on local government debt sustainability and the moderating role of fiscal transparency. The results indicate that enhancing anti-corruption efforts will improve the sustainability of local government debt, while fiscal transparency will magnify this positive impact. Furthermore, regional heterogeneity analysis demonstrates that, in developed regions, the impact of anti-corruption on debt sustainability and the moderating impact of fiscal transparency have been bolstered by effective policy implementation. Our research findings not only unveil the influence of anti-corruption on local government debt sustainability and the crucial role of fiscal transparency, but also offer fresh insights to enable local government authorities to manage debt sustainably. Full article

Demographic aging results in a growing number of older people in need of care in many regions all over the world. Germany has witnessed steady population aging for decades, prompting policymakers and other stakeholders to discuss how to fulfill the rapidly growing demand for care workers and finance the rising costs of long-term care. Informed decisions on this matter to ensure the sustainability of the statutory long-term care insurance system require reliable knowledge of the associated future costs. These need to be simulated based on well-designed forecast models that holistically include the complexity of the forecast problem, namely the demographic transition, epidemiological trends, concrete demand for and supply of specific care services, and the respective costs. Care risks heavily depend on demographics, both in absolute terms and according to severity. The number of persons in need of care, disaggregated by severity of disability, in turn, is the main driver of the remuneration that is paid by long-term care insurance. Therefore, detailed forecasts of the population and care rates are important ingredients for forecasts of long-term care insurance expenditures. We present a novel approach based on a stochastic demographic cohort-component approach that includes trends in age- and sex-specific care rates and the demand for specific care services, given changing preferences over the life course. The model is executed for Germany until the year 2050 as a case study. Full article