Empirical Data Research Articles

Revolutionizing getaways: automation and artificial intelligence’s transformative journey in tourism and hospitality

PurposeThis theme issue aims to explore the depth and breadth of automation and artificial intelligence’s (AI’s) impact on the hospitality and tourism industry.Design/methodology/approachThe thematic examination of the articles presented in this theme issue highlights the central results concerning the strategic inquiry, especially regarding their addition to knowledge, which is vital for fostering idea creation and theoretical research beneficial to various stakeholders in the tourism and hospitality sector. Given the swift evolution of these technologies, grasping their utilization, advantages and obstacles is essential for industry experts, decision-makers and scholars.FindingsThis theme issue encapsulates the transformative impact of automation and AI in the tourism and hospitality industry, highlighting the juxtaposition of enhanced operational efficiency against employment security concerns. It emphasizes the need for ethical governance to address AI’s ethical dilemmas and security vulnerabilities. The exploration of consumer attitudes towards AI, particularly in service robots and facial emotion recognition technologies, is deemed crucial for leveraging AI’s full potential in service delivery. Furthermore, AI’s entry into gastronomy prompts a reevaluation of traditional culinary practices, advocating for a balance between technological innovation and the preservation of cultural heritage.Originality/valueThis theme issue stands out for its focused exploration of the transformative effects of automation and AI within the hospitality and tourism industry. Unlike broader discussions on technology in business, it delves into specific AI-driven innovations, operational changes and the resultant shifts in consumer behavior and industry standards. By curating a collection of empirical research, theoretical analyses and content analyses, this issue is providing important insights into how automation and AI are reshaping service delivery, management practices and strategic decision-making in an industry characterized by its intense customer focus and reliance on human-to-human interaction.

Effect of an in-hospital medication self-management intervention (SelfMED) on medication adherence in polypharmacy patients postdischarge: protocol of a pre–post intervention study

IntroductionHealthcare providers usually manage medication for patients during hospitalisation, although patients are expected to self-manage their medication after discharge. A lack of self-management competencies is found to be associated with...

비대면 온라인 수업에서의 학습 참여도와 학생 만족도의 관계에 관한 실증적 연구

Objectives The purpose of this study is to empirically analyze the relationship between learning engagement and student satisfaction in a contactless online class environment. Methods The study employed regression analysis and text-based network analysis as research methods. Regression analysis was used to quantitatively measure the direct impact of learning engagement factors on stu-dent satisfaction. Text-based network analysis was used to explore the indirect effects on satisfaction by identify-ing information flow and centrality within the learning community. Results The analysis revealed a positive correlation between course completion rates and the frequency of the keyword ‘hard work’ in lecture comments, as well as the number of completed quiz submissions. However, the number of lectures and viewing time did not have a significant impact. The network analysis indicated that key-words such as ‘fun,’ ‘informative,’ ‘quiz,’ and ‘completion’ were central, suggesting that learner interaction is a crucial factor in satisfaction. Conclusions In conclusion, this study suggests that promoting interaction among learners and encouraging their active participation in course design can improve the efficiency and satisfaction of virtual classes. The empirical data provided here is expected to contribute to the improvement of educational technology.

The role of managerial competencies in managing resources for sustainable development strategy in SMEs

Purpose Grounded in upper echelon (UE) theory, this study aims to examine the role of managerial competencies (business experience, financial literacy and digital literacy) in sustainable development strategy, with resource management as a mediator. Design/methodology/approach The empirical data collection is conducted through a survey completed by 297 top management teams of small and medium-sized enterprises (SMEs) operating in Pakistan. Structural equation modelling in Smart PLS is used to substantiate the hypotheses. Findings The findings reveal that financially and digitally literate managers significantly contribute to the sustainable development strategies of SMEs. However, experienced managers do not focus significantly on sustainable development strategies. Resource management partially mediates the nexus between financial literacy and sustainable development strategy, as well as between digital literacy and sustainable development strategy. In contrast, resource management does not mediate the nexus between business experience and sustainable development strategy. Research limitations/implications This study recommends that SMEs should prioritize managers with digital and financial literacy over those with experience. SMEs led by a management team with digital and financial literacy are more effective in resource management for sustainable development practices, whereas experienced managers may not significantly prioritize managing resources for sustainability. Originality/value While research based on the UE theory significantly contributes to the body of knowledge on sustainable development, the role of managerial competencies, particularly business experience, financial literacy and digital literacy, in sustainable development strategy via resource management is neglected. This research fills this gap in the context of UE theory and thereby enriches the literature.

Estimating software reliability using size-biased modelling

Software testing is an important step in software development where inputs are administered repeatedly to detect bugs present in the software. In this paper, we have considered the estimation of total number of bugs and software reliability as a size-biased sampling problem by introducing the concept of eventual bug size as a latent variable. We have developed a Bayesian generalised linear mixed model (GLMM) using software testing detection data to estimate software reliability and stopping phase. The model uses size-biased approach where the probability of detecting a bug is an increasing function of eventual size of the bug which is as an index for the potential number of inputs that may eventually pass through the bug. We have tested the sensitivity of the reliability estimates by varying the number of inputs and detection probability via a simulation study and have found that the key parameters could be accurately estimated. Further, we have applied our model to two empirical data sets – one from a commercial software and the other from ISRO launch mission software testing data set. The hierarchical modelling approach provides a unified modelling framework that may find applications in other fields (e.g. hydrocarbon explorations) apart from software management.

Boundary effects cause false signals of range expansions in population genomic data.

Studying range expansions (REs) is central for understanding genetic variation through space and time as well as for identifying refugia and biological invasions. Range expansions are characterized by serial founder events causing clines of decreasing diversity away from the center of origin and asymmetries in the two-dimensional allele frequency spectra. These asymmetries, summarized by the directionality index (ψ), are sensitive to REs and persist for longer than clines in genetic diversity. In continuous and finite meta-populations, genetic drift tends to be stronger at the edges of the species distribution in equilibrium populations and populations undergoing REs alike. Such boundary effects (BEs) are expected to affect geographic patterns in genetic diversity and ψ. Here we demonstrate that BEs cause high false positive rates in equilibrium meta-populations when testing for REs. In the simulations, the absolute value of ψ (|ψ|) in equilibrium data sets was proportional to the fixation index (FST). By fitting signatures of REs as a function of ɛ=|ψ|/FST and geographic clines in ψ, strong evidence for REs could be detected in data from a recent rapid invasion of the cane toad, Rhinella marina, in Australia, but not in 28 previously published empirical data sets from Australian scincid lizards that were significant for the standard RE tests. Thus, while clinal variation in ψ is still the most sensitive statistic to REs, to detect true signatures of REs in natural populations, its magnitude needs to be considered in relation to the overall levels of genetic structuring in the data.

A century of statistical Ecology.

As data and computing power have surged in recent decades, statistical modeling has become an important tool for understanding ecological patterns and processes. Statistical modeling in ecology faces two major challenges. First, ecological data may not conform to traditional methods, and second, professional ecologists often do not receive extensive statistical training. In response to these challenges, the journal Ecology has published many innovative statistical ecology papers that introduced novel modeling methods and provided accessible guides to statistical best practices. In this paper, we reflect on Ecology's history and its role in the emergence of the subdiscipline of statistical ecology, which we define as the study of ecological systems using mathematical equations, probability, and empirical data. We showcase 36 influential statistical ecology papers that have been published in Ecology over the last century and, in so doing, comment on the evolution of the field. As data and computing power continue to increase, we anticipate continued growth in statistical ecology to tackle complex analyses and an expanding role for Ecology to publish innovative and influential papers, advancing the discipline and guiding practicing ecologists.

A Study on The Cost And Profit Efficiency of Islamic and Conventional Bank Islamic Windows in Oman: A Proposed Framework

Objective: This study aims to analyze the efficiency of Islamic and conventional banks and their respective Islamic windows in Oman in terms of costs and profits. Theoretical Framework: The research employs a framework that examines cost and profit efficiency within the banking sector, contrasting the performance of full-fledged Islamic banks and Islamic windows of conventional banks. This framework also investigates the impact of bank-specific variables on efficiency levels. Method: Using empirical data from the Omani banking sector, the study quantifies efficiency by analyzing bank-specific variables such as capitalization, profitability, operational costs, and loan activity. The comparison includes both Islamic banks and the Islamic windows of conventional banks as of the end of the third quarter of 2022. Results and Discussion: The findings reveal that, overall, banks in Oman are more efficient at generating profits than controlling costs. Conventional banks, on average, demonstrate higher efficiency in both cost and profit metrics compared to Islamic banks. There exists a positive correlation between both types of efficiencies and factors like bank capitalization and profitability, while a negative correlation is evident with operational costs. Furthermore, increased loan activity is associated with higher profit efficiency but adversely affects cost efficiency. Research Implications: These results underscore significant efficiency disparities between Islamic and conventional banking sectors. They highlight the need for Islamic banks to enhance their cost management strategies without compromising profit generation, leveraging the benefits derived from their association with parent conventional banks. Originality/Value: The study contributes to the literature by providing a comparative analysis of cost and profit efficiencies in Islamic and conventional banks, with a particular focus on the unique market dynamics of Oman. This research is valuable for stakeholders in the Islamic banking industry, offering insights into leveraging existing infrastructures and enhancing operational efficiencies.

Digital Flow in a Pool Induced by a Vertical Jet

Turbulent water jets remain a critical study area, particularly the relation of the water flow with air entrainment and its role in energy dissipation at different hydraulic structures. Plunge pools, formed by the impact of jets on water cushions, play a pivotal role in energy dissipation. Understanding the complex flow dynamics within these pools is essential for designing efficient hydraulic structures. In this research, we present a comprehensive investigation of different numerical simulations, defining two-phase (air-water) in different ways, and them compare with experimental measurements. The primary objective is to analyze the pressure distribution at the bottom of a plunge pool induced by a vertical jet and understand the importance of accurately defining air-water flow in the dynamics of the jet into the pool. Our study bridges the gap between empirical data and computational modeling, shedding light on the intricate behavior of such flows with different method-based solvers: VOF, sub-grid, and multi-phase Euler. Various computational domains, mesh configurations, and analyses spanning different time periods, frequencies, and scales were considered.

The Knowledge Acquisition Process in Interorganizational Projects: A Multiple-Case Study of Infrastructural Projects in Pakistan

Knowledge acquisition is pivotal for delivering successful interorganizational projects where multiple organizations are involved. The phenomenon, however, has been the subject of very few comprehensive empirical studies. Hence, this article sets out to understand how knowledge is acquired, particularly in the context of interorganizational projects. It explores the knowledge acquisition process at different levels, including the individual, team, organizational, and interorganizational levels. For this purpose, metro train and metro bus projects in Pakistan were examined. A multicase study approach is employed in this article; semistructured interviews and archival documents are included in the empirical data. Within and across case analysis is used for analyzing the data. The findings present the knowledge acquisition process, including types of knowledge (i.e., explicit and tacit knowledge) and multiple levels such as individuals, teams, organizations, and the interorganizational level. By examining knowledge acquisition in interorganizational projects, this article contributes to the literature on knowledge-based theory.

Nurse perceptions of practice environment, quality of care and patient safety across four hospital levels within the public health sector of South Africa

Improving the practice environment, quality of care and patient safety are global health priorities. In South Africa, quality of care and patient safety are among the top goals of the National Department of Health; nevertheless, empirical data regarding the condition of the nursing practice environment, quality of care and patient safety in public hospitals is lacking.AimThis study examined nurses’ perceptions of the practice environment, quality of care and patient safety across four hospital levels (central, tertiary, provincial and district) within the public health sector of South Africa.MethodsThis was a cross-sectional survey design. We used multi-phase sampling to recruit all categories of nursing staff from central (n = 408), tertiary (n = 254), provincial (n = 401) and district (n = 244 [large n = 81; medium n = 83 and small n = 80]) public hospitals in all nine provinces of South Africa. After ethical approval, a self-reported questionnaire with subscales on the practice environment, quality of care and patient safety was administered. Data was collected from April 2021 to June 2022, with a response rate of 43.1%. ANOVA type Hierarchical Linear Modelling (HLM) was used to present the differences in nurses’ perceptions across four hospital levels.ResultsNurses rated the overall practice environment as poor (M = 2.46; SD = 0.65), especially with regard to the subscales of nurse participation in hospital affairs (M = 2.22; SD = 0.76), staffing and resource adequacy (M = 2.23; SD = 0.80), and nurse leadership, management, and support of nurses (M = 2.39; SD = 0.81). One-fifth (19.59%; n = 248) of nurses rated the overall grade of patient safety in their units as poor or failing, and more than one third (38.45%; n = 486) reported that the quality of care delivered to patient was fair or poor. Statistical and practical significant results indicated that central hospitals most often presented more positive perceptions of the practice environment, quality of care and patient safety, while small district hospitals often presented the most negative. The practice environment was most highly correlated with quality of care and patient safety outcomes.ConclusionThere is a need to strengthen compliance with existing policies that enhance quality of care and patient safety. This includes the need to create positive practice environments in all public hospitals, but with an increased focus on smaller hospital settings.

Predictive mapping of organic carbon stocks in surficial sediments of the Canadian continental margin

Abstract. Quantification and mapping of surficial seabed sediment organic carbon have wide-scale relevance for marine ecology, geology and environmental resource management, with carbon densities and accumulation rates being a major indicator of geological history, ecological function and ecosystem service provisioning, including the potential to contribute to nature-based climate change mitigation. While global analyses can appear to provide a definitive understanding of the spatial distribution of sediment carbon, regional maps may be constructed at finer resolutions and can utilise targeted data syntheses and refined spatial data products and therefore have the potential to improve these estimates. Here, we report a national systematic review of data on organic carbon content in seabed sediments across Canada and combine this with a synthesis and unification of the best available data on sediment composition, seafloor morphology, hydrology, chemistry and geographic settings within a machine learning mapping framework. Predictive quantitative maps of mud content, dry bulk density, organic carbon content and organic carbon density were produced along with cell-specific estimates of their uncertainty at 200 m resolution across 4 489 235 km2 of the Canadian continental margin (92.6 % of the seafloor area above 2500 m) (https://doi.org/10.5683/SP3/ICHVVA, Epstein et al., 2024). Fine-scale variation in carbon stocks was identified across the Canadian continental margin, particularly in the Pacific Ocean and Atlantic Ocean regions. Overall, we estimate the standing stock of organic carbon in the top 30 cm of surficial seabed sediments across the Canadian shelf and slope to be 10.9 Gt (7.0–16.0 Gt). Increased empirical sediment data collection and higher precision in spatial environmental data layers could significantly reduce uncertainty and increase accuracy in these products over time.

Bioethanol sacrifice zones and environmental/ epistemic injustice. A case study in Argentina.

This paper presents a case of environmental conflict caused by a corn-based bioethanol plant in Argentina- one of the world's most important agro-industrial economies. The aim is to illustrate how epistemic inequality is a transversal aspect of environmental injustice. Many of the environmental impacts of this production have been denounced by the affected peoples living next to the plant, which functions in a densely populated area. Their knowledges about health, air pollution and the risk of explosions have been systematically excluded from legal proceedings and policy-making in the case. Additionally, they have demanded the intervention of public universities and research centers in the case, but instead the scientific sector has offered its capacities to advance the agro-industrial complex rather than research the damages and risks made to environmental and human health. Thus, these peoples seem to be confined to a "sacrifice zone" where the protection of the rights to health and a clean environment are systematically violated, along with the denial of their status of legitimate knowers. This paper describes situations in which the knowledge of those affected is disregarded and/or excluded in the process of evidence-making. It also makes visible the co-responsibility of the scientific community in this case regarding the inequality between "production" and "impact" science related to the environmental sustainability of bioethanol. The empirical data of the case is presented within an Environmental/Epistemic Justice and STS framework. In order to overcome the devastating effects of agro-industrial sacrifice zones, this work contributes to the reflection on the interconnectedness of environmental sciences, affected people’s knowledge, and politics.

Happiness and Emigration as A Challenge to Albanian University Youth: A National Level Case

Aim: The research article aims to analyse happiness as the primary indicator of the current emigration potential of university youth. The challenges of decision-making of Albanian university youth to emigrate tease out the social, political and economic factors as indicators to decrease the level of happiness in terms of personal (being happy with life in general, with life, with family life in the last four years) and in social perspective such as being happy with economic status and house/shelter, the level of satisfaction with current life (standards of living), and the level of trust (in political and governmental institutions; in people, friends and media), as the pushing factors to potential emigration of youth. Methods: To guarantee a national-level measurement of the university youth emigration potential, due to the mentioned indicators, the empirical data gained from the quantitative online survey research on the measurement of opinions of (N=1010) Albanian university youth, at the national level of (N=7) (all) public universities in Albania, in (N=13) departments on social sciences profile, analysed by the Statistical program IMB SPSS 26, in different statistical approach analysis, such as descriptive, frequency, cross-tabs and Kurtosis. Results: Many measurement indicators show that personal and social levels of happiness reflect on a ‘low level of subjective well-being, unsatisfaction subjective well-being and dissatisfaction with life and living conditions that decrease the level of trust and security for life, and proxy dimensions of emigration decision (intention and concrete plan to migrate) of university youth. Conclusion: The low satisfaction (with life and living conditions), and low trust in the state bodies and political institutions, due to the current, social, political and economic conditions, formed an elation among the variables, on the conclusion that happiness is the main push factor and a challenge for potential emigration of university youth as high skilled worker, in the next years.

Industry sector’s influence on the narratives in environmental disclosures in the opinion of reports preparers. Evidence from Poland

The narrative phenomenon in accounting concerns, i.e., the disclosure of environmental information and the impression management of stakeholders. The study examines and assesses the dependence between the company’s industry of activity and the narration perception adopted by the preparers of environmental reports, in particular, the impression management techniques used. To achieve the purpose of the article, an in-depth survey was conducted covering a non-random sample of the employees of Polish enterprises involved in the preparation and reporting of environmental information. Contingency tables and association measures for categorical variables were used in the statistical analysis of the survey data. The analysis results of the collected empirical data confirmed that the company’s industry of activity impacts the way report preparers evaluate the scope and apply narrative strategies, especially impression management techniques. The research expands knowledge on the perception of the importance of environmental disclosures and the issue of environmental narrative practices from an enterprise perspective. The results of the analysis indicated a level of pro-environmental awareness and confirmed the knowledge of narrative strategies and techniques. This study contributes to the discussion on the effects of environmental narrative in accounting, offering yet another element of the current practice diagnosis in this area in Poland.

Analysis of the Role of Human Capital on Economic Growth in the Beijing-Tianjin-Hebei

Abstract This paper uses some human capital related data in the Beijing-Tianjin-Hebei region as empirical data to study the impact of human capital on the economic growth of the Beijing-Tianjin-Hebei region; based on the selected data, the principal component analysis method is used to analyze health human capital, education human capital, and comprehensive human capital. Measure and compare the human capital differences of the three places in Beijing, Tianjin and Hebei. Finally, based on the economic growth model, the three places are regression analysis, and the results of different types of human capital on the three places are obtained. The analysis results show that different types of human capital measurement values in the Beijing-Tianjin-Hebei region are indeed different. In general, the human capital in the Beijing-Tianjin-Hebei region contributes more to economic growth than physical capital, and the contribution of health human capital is better than that of education human capital. Keywords: Human capital, Economic growth, Regression analysis, Principal component analysis, Health; Education.

Triggering Violence? The Impact of Firearms on the Nature and Lethality of Violent Encounters: A European Perspective

Firearms are used in around 25% of homicides in Europe. More so than other weapons commonly used in violent encounters, firearms have the ability to inflict lethal injuries. Yet, theoretical approaches to understanding the impact of firearms on the prevalence, lethality, and nature of violent encounters are scarce and have been developed almost exclusively within and for the context of the United States, where the levels of firearm violence and firearm availability are much higher than in Europe, limiting their applicability to the European context. To address this issue, European empirical data are reviewed in this paper to critically assess the few existing theoretical approaches focusing on the use of firearms in lethal and non-lethal violence. Based on the obtained findings, future directions for empirical research, as well as suggestions for new conceptualizations of firearm violence in Europe are presented.

Application of Bayesian networks based on Sequential Monte Carlo simulation and physical model in fault diagnosis of horizontal three-phase separator system

In offshore production platforms, horizontal three-phase separator is common process equipment. Its main function is to complete the dehydration and degassing of crude oil. Separator system is more complex, and its failure may cause significant economic losses and disastrous consequences. Therefore, it is critical to accurately and quickly identify where and why faults occur in the separator system. In this study, separator fault diagnosis model based on Bayesian networks is developed. Moreover, Sequential Monte Carlo simulation and physical model are introduced to overcome field problems such as missing separator failure data and the inability of experts to provide accurate empirical knowledge. Using this model, 13 faults in a separator in an offshore crude oil processing system are successfully diagnosed. Meanwhile, the proposed model is compared with deep neural network, convolutional neural network, and deep residual network, with accuracy rates of 100%, 91.34%, 87.99%, and 94.62%, respectively. Then, the diagnostic accuracy of each model for different faults is also compared in this paper under various signal-to-noise ratios. The results show that the method proposed in this paper has better noise immunity compared to the other three models. Therefore, the accuracy and robustness of the proposed model is further demonstrated. Finally, to analyze the fault-tolerance of the proposed model, 2–3 error evidence is randomly entered. The results show that the proposed model has better fault tolerance compared to data-driven Bayesian networks.

Research on the impact and mechanisms of lean management on the green development of traditional small and micro manufacturing enterprises

AbstractTo achieve the “dual carbon” goals, manufacturing businesses must pursue green development. Compared to larger enterprises, the path towards green development is fraught with difficulties for the numerous traditional small and micro manufacturing enterprises. Lean thinking offers new solutions to the pain points and challenges of green development for these enterprises. However, existing research primarily focuses on large enterprises, with limited studies on traditional small and micro manufacturing enterprises; moreover, the conclusions on lean green development remain contentious and fail to effectively guide these enterprises through their green development bottlenecks. Therefore, this paper constructs a lean green development mechanism model for traditional small and micro manufacturing enterprises based on the grounded theory research method and the “resource‐behavior‐performance” model. It validates the model with empirical data from 333 traditional small manufacturing enterprises in China. The results show that in the actual development process of traditional small and micro enterprises, implementing lean organization and lean production significantly improves environmental performance, but the impact on economic performance is complex. Additionally, the influence of lean strategies on green development performance is not significant, not fully realizing their potential guiding role. Further in‐depth analysis of traditional small and micro manufacturing enterprises with a mature level of lean management reveals that as the level of lean management improves, the guiding effect of lean strategies begins to emerge; both lean organization and production have a significantly positive impact on economic performance. The findings are theoretically and practically significant for overcoming the green development challenges faced by traditional small and micro manufacturing enterprises, help to broaden the research scope of lean green development, and provide decision‐making and theoretical support for promoting the seamless implementation of lean green development in the traditional manufacturing sector.

WAR AS A FACTOR OF TRANSFORMATION IN PUBLIC CONSCIOUSNESS OF UKRAINIANS

The purpose of the study was to identify transformations in the public consciousness of Ukrainians caused by Russian aggression, primarily its impact on their awareness of their own identity, the components of which are historical memory, self-definition in relation to one's own country and people, relations with other peoples and countries, basic values, on which social life is based. Methodology. An idea about the nature and depth of these transformations can be based on the analysis of empirical data, including the content of mass media and social networks. However, the most relevant in this sense are the data of sociological studies, which allow us to see the mentioned processes in dynamics, and therefore to draw conclusions about the presence of certain trends and formulate certain forecasts based on them. The article analyzes the results of sociological research conducted in August - September 2022 by the Democratic Initiatives Foundation, the sociological service of the Razumkov Center, and the Kyiv International Institute of Sociology. Results. They witnessed significant changes in the attitude of Ukrainians, in particular, to the historical past, iconic historical figures and recently influential non-state institutions. On a number of issues, traditional differences in assessments between residents of central and western Ukraine, on the one hand, and eastern and southern Ukraine, on the other, are observed. At the same time, the factors contributing to the unification of Ukrainian citizens around common values, such as state independence, Ukrainian citizenship, and the native country as a place where a person sees his future, have been identified. A certain consensus was also found regarding who is responsible for the war waged against Ukraine, and the nature of future relations with Russia and the Russian people.