Search Results (946)

Research on commuting patterns has mainly focused on urban and metropolitan areas, and such studies are not typically applied to rural and small-town regions, where workers often face longer commutes due to limited job opportunities and inadequate public transportation. By using the Census Transportation Planning Package (CTPP) data, this research fills that gap by analyzing commuting behavior by ethnic group and industry in south-central Minnesota, which is a predominantly rural area of 13 counties in the United States. The results show that both white and minority groups in District 7 experienced an increase in excess commuting from 2006 to 2016, with the minority group in Nobles County showing a significantly higher rise. Analysis by industry reveals that excess commuting in the leisure and hospitality sector (including arts, entertainment, and food services) in Nobles County increased five-fold during this time, indicating a severe spatial mismatch between jobs and affordable housing. In contrast, manufacturing experienced a decline of 50%, possibly indicating better commuting efficiency or a loss of manufacturing jobs. These findings can help city and transportation planners conduct an in-depth analysis of rural-to-urban commuting patterns and develop potential solutions to improve rural transportation infrastructure and accessibility, such as promoting telecommuting and hybrid work options, expanding shuttle routes, and adding more on-demand transit services in rural areas. Full article

Biotechnological research increasingly focuses on developing new drugs to counter the rise of antibiotic-resistant strains in hospitals. This study aimed to create bacterial lysates from antibiotic-resistant pathogens isolated from patients and medical instruments across hospital departments. Identification was performed based on morphological, cultural, and biochemical characteristics, as well as 16S rRNA gene sequencing using the BLAST algorithm. Strain viability was assessed using the Miles and Misra method, while sensitivity to eight antibacterial drug groups and biosafety between cultures were evaluated using agar diffusion. From 15 clinical sources, 25 pure isolates were obtained, and their phenotypic and genotypic properties were studied. Carbohydrate fermentation testing confirmed that the isolates belonged to the genera Escherichia, Citrobacter, Klebsiella, Acinetobacter, Pseudomonas, Staphylococcus, Haemophilus, and Streptococcus. The cultures exhibited good viability (10⁹–10¹⁰ CFU/mL) and compatibility with each other. Based on prevalence and clinical significance, three predominant hospital pathogens (Klebsiella pneumoniae 12 BL, Pseudomonas aeruginosa 3 BL, and Acinetobacter baumannii 24 BL) were selected to develop a bacterial lysate consortium. Lysates were prepared with physical disruption using a French press homogenizer. The resulting product holds industrial value and may stimulate the immune system to combat respiratory pathogens prevalent in Kazakhstan’s healthcare settings. Full article

This study evaluates the risk-adjusted performance of Hospitality REITs using multi-factor asset pricing models and downside risk measures with the aim of assessing their diversification potential and crisis sensitivity. Unlike prior studies that examine REITs in aggregate, this study isolates Hospitality REITs to explore their unique cyclical and macroeconomic sensitivities. This study looks at the risk-adjusted performance of Hospitality Real Estate Investment Trusts (REITs) in relation to more general REIT indexes and the S&P 500 Index. The study reveals that monthly returns of Hospitality REITs increasingly move in tandem with the stock markets during financial crises, which reduces their historical function as portfolio diversifiers. Investing in Hospitality REITs exposes one to the hospitality sector; however, these investments carry notable risks and provide little protection, particularly during economic upheavals. Furthermore, the study reveals that Hospitality REITs underperform on a risk-adjusted basis relative to benchmark indexes. The monthly returns of REITs show significant volatility during the post-COVID-19 era, which causes return-to-risk ratios to be below those of benchmark indexes. Estimates from multi-factor models indicate negative alpha values across conditional models, indicating that macroeconomic variables cause unremunerated risks. This industry shows great sensitivity to market beta and size and value determinants. Hospitality REITs’ susceptibility comes from their showing the most possibility for exceptional losses across asset classes under Value at Risk (VaR) and Conditional Value at Risk (CvaR) downside risk assessments. The findings have implications for investors and portfolio managers, suggesting that Hospitality REITs may not offer consistent diversification benefits during downturns but can serve a tactical role in procyclical investment strategies. Full article

Background/Objectives: In many parts of the world, pharmacists hold the primary responsibility for providing safe and effective pharmacotherapy. A key aspect is the availability of appropriate medicines for each individual patient. When industrially manufactured medicines are unsuitable or unavailable, pharmacists can prepare tailor-made medicines. While this principle applies globally, practices vary between countries. In the Netherlands, the preparation of medicines in pharmacies is well-established and integrated into routine healthcare. This narrative review explores the role and significance of extemporaneous compounding, pharmacy preparations and related product care in the Netherlands. Methods: Pharmacists involved in pharmacy preparations across various professional sectors, including community and hospital pharmacies, central compounding facilities, academia, and the professional pharmacists’ organisation, provided detailed and expert insights based on the literature and policy documents while also sharing their critical perspectives. Results: We present arguments supporting the need for pharmacy preparations and examine their position and role in community and hospital pharmacies in the Netherlands. Additional topics are discussed, including the regulatory and legal framework, outsourcing, quality assurance, standardisation, education, and international context. Specific pharmacy preparation topics, often with a research component and a strong focus on product care, are highlighted, including paediatric dosage forms, swallowing difficulties and feeding tubes, hospital-at-home care, reconstitution of oncolytic drugs and biologicals, total parenteral nutrition (TPN), advanced therapy medicinal products (ATMPs), radiopharmaceuticals and optical tracers, clinical trial medication, robotisation in reconstitution, and patient-centric solid oral dosage forms. Conclusions: The widespread acceptance of pharmacy preparations in the Netherlands is the result of a unique combination of strict adherence to tailored regulations that ensure quality and safety, and patient-oriented flexibility in design, formulation, and production. This approach is further reinforced by the standardisation of a broad range of formulations and procedures across primary, secondary and tertiary care, as well as by continuous research-driven innovation to develop new medicines, formulations, and production methods. Full article

This study builds on Davis’ TAM by integrating environmental and psychological variables relevant to AI medical diagnostics. This study developed a mathematical theoretical model called the “AI medical diagnosis-acceptance evaluation model” (AMD-AEM) to better understand acceptance behavior intention. Using mathematical modeling, we established reflective measurement model indicators and structural equation relationships, where linear structural equations illustrate the interactions among latent variables. In 2025, we collected empirical data from 2380 patients and medical staff who have experience with AI diagnostic systems in teaching hospitals in central Taiwan. Smart PLS 3 was employed to validate the AMD-AEM model. The results reveal that perceived usefulness (PU) and information quality (IQ) are the primary predictors of acceptance behavior intention (ABI). Additionally, perceived ease of use (PE) indirectly influences ABI through PU and attitude toward use (ATU). AI emotional perception (AEP) notably shows a significant positive relationship with ATU, highlighting that warm and positive human–AI interactions are crucial for user acceptance. IQ was identified as a mediating variable, with variance accounted for (VAF) coefficient analysis confirming its complete mediation effect on the path from ATU to ABI. This indicates that information quality enhances user attitudes and directly increases acceptance behavior intention. The AMD-AEM model demonstrates an excellent fit, providing valuable insights for academia and the healthcare industry. Full article

In recent years, the number of fake news stories has significantly increased in the world of media, especially with the widespread use of social media. It has impacted several industries, including tourism. From a tourism point of view, the spread of fake news can contribute to the reduction of the popularity of a destination. It may influence travel decisions by discouraging tourists from visiting certain places and thus damage the reputation of the destination, contributing to economic loss. After a literature review on the communication aspect of fake news and a general introduction of fake news in the tourism and hospitality industry, we conducted a systematic literature review (SLR), a research methodology to collect, identify, and analyse available research studies through a systematic procedure. The current SLR is based on the Scopus, Web of Science, and Google Scholar databases of existing literature on the topic of fake news in the tourism and hospitality industry. The study identifies, lists, and examines existing papers and conference proceedings from a vast array of disciplines, in order to give a well-rounded view on the issue of fake news in the tourism and hospitality industry. After selecting a total of 54 previous studies from more than 20 thousand results for the keywords ‘fake news’ and ‘tourism,’ we have analysed 39 papers in total. The SLR aimed to highlight existing gaps in the literature and areas that may require further exploration in future primary research. We have found that there is relatively limited academic literature available on the subject of fake news affecting tourism destinations, compared to studies focused on hospitality services. Full article

The adoption of artificial intelligence (AI) in marketing and social media is gaining scholarly interest. While AI technologies offer significant potential for enhancing customer engagement (CE), their effectiveness depends on an industry’s level of digital and AI readiness. This is especially relevant for people-centric sectors such as tourism and hospitality, where digital maturity remains relatively low. This study aims to understand how AI supports CE and social media marketing (SMM), and to identify the key antecedents and consequences of its use. Using the PRISMA approach, we conduct a systematic review of 55 peer-reviewed empirical studies on AI-based CE and SMM. Our analysis identifies the main contributing theories and AI technologies in the field, and uncovers four central themes: (1) AI in customer service and user experience design, (2) AI-based customer relationships with brands, (3) AI-driven development of customer trust, and (4) cultural differences and varying levels of AI readiness. We also develop a conceptual framework that outlines the determinants and outcomes of AI-based CE, including relevant moderators and mediators. The study concludes with directions for future research and provides theoretical and managerial implications, particularly for the tourism and hospitality industries. Full article

Ozonation and ozone-based advanced oxidation processes, including ozone/hydrogen peroxide and ozone/ultraviolet irradiation, have been extensively studied for their efficacy in treating wastewater across various industries. While sectors such as pulp and paper, textile, food and beverage, microelectronics, and municipal wastewater have successfully implemented ozone at full scale, others have yet to fully embrace these technologies’ effectiveness. This review article examines recent publications from the past two decades, exploring novel applications of ozone-based technologies in treating wastewater from diverse sectors, including food and beverage, agriculture, aquaculture, textile, pulp and paper, oil and gas, medical and pharmaceutical manufacturing, pesticides, cosmetics, cigarettes, latex, cork manufacturing, semiconductors, and electroplating industries. The review underscores ozone’s broad applicability in degrading recalcitrant synthetic and natural organics, thereby reducing toxicity and enhancing biodegradability in industrial effluents. Additionally, ozone-based treatments prove highly effective in disinfecting pathogenic microorganisms present in these effluents. Continued research and application of these ozonation and ozone-based advanced oxidation processes hold promise for addressing environmental challenges and advancing sustainable wastewater management practices globally. Full article

A novel framework is proposed to support the prediction of the plastic waste (PW) collection demand, route optimization, and overall management of PW from individual facilities. Based on electronic manifests from a local recycling company in Fukuoka, Japan, we developed a two-step artificial intelligence (AI)-based approach for predicting the demand for industrial PW (IPW) collection from a hospital. The daily hospital visitor numbers were introduced as a new independent variable in the IPW collection demand prediction. The stability (robustness) of each model was measured by its variance through experiments for two variable groups in four validation months. We found that introducing the visitor variables into IPW collection demand predictions was effective. A high monthly mean accuracy (85.06%) was achieved in predicting the daily IPW collection demand, which exceeded the accuracy of predictions using models without visitor records (84.44%). The stability of the Fine tree model with the highest prediction accuracy for March 2020 was 0.0466 $\mp$ 0.0174. Based on the findings of this study, we propose several strategies for waste management: enhancing prediction models, controlling visitor flows, and analyzing working patterns. This study successfully links AI techniques with a human mobility monitoring system (location data) for waste management using MATLAB. Full article

The implementation of Digital Twins (DTs) in hospitality facilities represents a significant opportunity to optimize front-end services, enhancing guest experience and operational efficiency. This paper proposes an ontology-driven approach for DTs in hotel reception areas, focusing on integrating IoT devices, real-time data processing, and service optimization. By modeling interactions between guests, receptionists, and hotel management systems, DTs enhance resource allocation, predictive maintenance, and customer satisfaction. Simulations and historical data analysis enable forecasting demand fluctuations and optimizing check-in/check-out processes. This research provides a structured framework for DT applications in hospitality, validated through scenario-based simulations, showing significant improvements in check-in time and guest satisfaction. Validation was conducted through scenario-based simulations reflecting real-world operational challenges, such as guest surges, room assignment, and staff workload balancing. Metrics including check-in time, guest satisfaction index, task completion rates, and prediction accuracy were used to evaluate performance. Simulations were grounded in historical hotel data and modeled typical peak-period dynamics to ensure realism. Results demonstrated a 25–35% reduction in check-in time, a 20% improvement in staff efficiency, and significant enhancements in guest satisfaction, underscoring the practical value of the proposed framework in real hospitality settings. Full article

The increasing complexity of the hotel industry necessitates the implementation of sophisticated cost systems capable of delivering accurate and relevant cost information to support managerial decision-making. Investigating the determinants of cost system design is crucial, given that no single accounting system is universally applicable across all business contexts. This study addresses a critical gap by examining the key drivers of cost system sophistication through the theoretical frameworks of contingency and upper echelons theories, focusing specifically on the Greek hotel sector. Employing multiple regression analysis, the findings reveal that firm size, cost structure, the importance of cost information in decision-making, and the integration of information technology significantly influence the complexity of cost systems. Conversely, factors such as competition, service diversity, business strategy, organizational life cycle, and executive characteristics showed no statistically significant impact. These findings contribute to management accounting and hospitality literature by integrating theoretical perspectives and identifying key determinants of cost system sophistication. Moreover, the study offers practical insights for designing cost systems that meet the specific needs of the hotel industry. Full article

As industrial automation evolves towards human-centric, adaptable solutions, collaborative robots must overcome challenges in unstructured, dynamic environments. This paper extends our previous work on developing a digital shadow for industrial robots by introducing a comprehensive framework that bridges the gap between physical systems and their virtual counterparts. The proposed framework advances toward a fully functional digital twin by integrating real-time perception and intuitive human–robot interaction capabilities. The framework is applied to a hospital test lab scenario, where a YuMi robot automates the sorting of microscope slides. The system incorporates a RealSense D435i depth camera for environment perception, Isaac Sim for virtual environment synchronization, and a locally hosted large language model (Mistral 7B) for interpreting user voice commands. These components work together to achieve bi-directional synchronization between the physical and digital environments. The framework was evaluated through 20 test runs under varying conditions. A validation study measured the performance of the perception module, simulation, and language interface, with a 60% overall success rate. Additionally, synchronization accuracy between the simulated and physical robot joint movements reached 98.11%, demonstrating strong alignment between the digital and physical systems. By combining local LLM processing, real-time vision, and robot simulation, the approach enables untrained users to interact with collaborative robots in dynamic settings. The results highlight its potential for improving flexibility and usability in industrial automation. Full article

Chemical products, including cleaning agents, disinfectants, stain removers, and cosmetics, release harmful chemicals that pose a risk to human health and the environment, necessitating alternative sources. The objective of this research was to identify the most effective phytoextract from food production waste for use in sustainable aerosol hygiene technology as an electrostatic bio-disinfectant. The investigation was performed through wipe tests and airborne microbial collection techniques. The upgraded coffee silverskin phytoextract demonstrated superior disinfection potential for various surfaces and airborne microbes compared to the hot trub phytoextract, with an industrial disinfectant serving as the control. Log reduction analyses revealed a more significant killing efficacy (p ≤ 0.05, using the ANOVA test) against Gram-positive organisms (Bacillus subtilis and Listeria monocytogenes) than against Gram-negative organisms (Escherichia coli and Vibrio parahaemolyticus), with the log reductions ranging from 3.08 to 5.56 and 3.72 to 5.81, respectively. Chemical characterization by LC-ESI-QTOF-MS, ¹H NMR, and FTIR showed that CGAs and chalcones are the most bioactive compounds in CSS and HT, respectively. The innovation in this work involves an integrated approach that combines waste-derived phytoextracts, advanced chemical profiling, and scalable aerosol disinfection. Furthermore, this research offers a greener, cost-effective, and industrially relevant alternative to synthetic chemical disinfectants. The interdisciplinary approach contributes to the development of bio-based disinfectants for use in the food industry, hospitals, and public health settings. This investigation supports a paradigm shift toward sustainable disinfection practices, thereby improving food and environmental safety. Full article

This study addresses a gap in hospitality research by investigating how employees’ perceptions of green intellectual capital (GIC) influence their satisfaction with both career and life. Although sustainability has become increasingly relevant in organizational strategies, limited research has examined how such job resources affect employees’ attitudes. Guided by the Job Demands–Resources (JD-R) framework, the study proposes a model in which organizational embeddedness (OE) mediates the relationship between green intellectual capital (GIC) and satisfaction outcomes, while thriving at work (TAW) moderates this pathway. The analysis is based on data collected from 371 employees working in four- and five-star hotels in Turkey. Structural equation modeling was used to test the hypotheses. The findings show that positive perceptions of green intellectual capital (GIC) are associated with stronger embeddedness, which, in turn, enhances career and life satisfaction. Moreover, this indirect effect is more pronounced among employees who report higher levels of thriving. The results emphasize how sustainability-oriented practices can serve as meaningful resources that improve employee outcomes in the hospitality industry. 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