University of Macedonia

Background: Burnout is a psychological syndrome characterized by emotional exhaustion, feelings of cynicism and reduced personal accomplishment. In the past years there has been disagreement on whether burnout and depression are the same or different constructs, as they appear to share some common features (e.g. loss of interest and impaired concentration). However, the results so far are inconclusive and researchers disagree with regard to the degree to which we should expect such overlap. The aim of this systematic review and meta-analysis is to examine the relationship between burnout and depression. Additionally, given that burnout is the result of chronic stress and that working environments can often trigger anxious reactions, we also investigated the relationship between burnout and anxiety. Method: We searched the online databases SCOPUS, Web of Science, MEDLINE (PubMed) and Google Scholar for studies examining the relationship between burnout and depression and burnout and anxiety, which were published between January 2007 and August 2018. Inclusion criteria were used for all studies and included all types of studies (cross-sectional and longitudinal), published and unpublished research articles, full-text articles, articles written in the English language, studies that present the effects sizes of their findings and that used reliable research tools. Results: Our results showed a significant association between burnout and depression (r = 0.520, SE = 0.012, 95% CI = 0.492, 0.547) and burnout and anxiety (r = 0.460, SE = 0.014, 95% CI = 0.421, 0.497). However, moderation analysis for both burnout - depression and burnout - anxiety relationships revealed that the studies in which the MBI test was used and were rated as having poorer quality showed lower effect sizes. Conclusions: Our research aims to clarify the relationship between burnout - depression and burnout - anxiety relationships. Our findings revealed no conclusive overlap between burnout and depression and burnout and anxiety, indicating that they are different and robust constructs. Future studies should focus on utilizing more longitudinal designs in order to assess the causal relationships between these variables.

Technological innovation has become an integral aspect of our daily life, such as wearable and information technology, virtual reality and the Internet of Things which have contributed to transforming healthcare business and operations. Patients will now have a broader range and more mindful healthcare choices and experience a new era of healthcare with a patient-centric culture. Digital transformation determines personal and institutional health care. This paper aims to analyse the changes taking place in the field of healthcare due to digital transformation. For this purpose, a systematic bibliographic review is performed, utilising Scopus, Science Direct and PubMed databases from 2008 to 2021. Our methodology is based on the approach by Wester and Watson, which classify the related articles based on a concept-centric method and an ad hoc classification system which identify the categories used to describe areas of literature. The search was made during August 2022 and identified 5847 papers, of which 321 fulfilled the inclusion criteria for further process. Finally, by removing and adding additional studies, we ended with 287 articles grouped into five themes: information technology in health, the educational impact of e-health, the acceptance of e-health, telemedicine and security issues.

This paper empirically examines the impact of tourism on the long-run economic growth of Greece by using causality analysis of real gross domestic product, real effective exchange rate and international tourism earnings. A Multivariate Auto Regressive (VAR) model is applied for the period 1960:I-2000:IV. The results of co-integration analysis suggest that there is one co-integrated vector among real gross domestic product, real effective exchange rate and international tourism earnings. Granger causality tests based on Error Correction Models (ECMs), have indicated that there is a ‘strong Granger causal’ relationship between international tourism earnings and economic growth, a ‘strong causal’ relationship between real exchange rate and economic growth, and simply ‘causal’ relationships between economic growth and international tourism earnings and between real exchange rate and international tourism earnings.

A genetic perspective of human history in Europe was derived from 22 binary markers of the nonrecombining Y chromosome (NRY). Ten lineages account for >95% of the 1007 European Y chromosomes studied. Geographic distribution and age estimates of alleles are compatible with two Paleolithic and one Neolithic migratory episode that have contributed to the modern European gene pool. A significant correlation between the NRY haplotype data and principal components based on 95 protein markers was observed, indicating the effectiveness of NRY binary polymorphisms in the characterization of human population composition and history.

Out-of-pocket (OOP) payments are the principal means of financing health care throughout much of Asia. We estimate the magnitude and distribution of OOP payments for health care in fourteen countries and territories accounting for 81% of the Asian population. We focus on payments that are catastrophic, in the sense of severely disrupting household living standards, and approximate such payments by those absorbing a large fraction of household resources. Bangladesh, China, India, Nepal and Vietnam rely most heavily on OOP financing and have the highest incidence of catastrophic payments. Sri Lanka, Thailand and Malaysia stand out as low to middle income countries that have constrained both the OOP share of health financing and the catastrophic impact of direct payments. In most low/middle-income countries, the better-off are more likely to spend a large fraction of total household resources on health care. This may reflect the inability of the poorest of the poor to divert resources from other basic needs and possibly the protection of the poor from user charges offered in some countries. But in China, Kyrgyz and Vietnam, where there are no exemptions of the poor from charges, they are as, or even more, likely to incur catastrophic payments.

Effective health care interventions are underutilized in the developing world, and income-related disparities in use are large. The evidence concerning this access problem is summarized and its demand side causes are identified. Broad strategies that have been proposed to tackle the access problem through changes in economic incentives are considered. It is argued that there is a need to go beyond the identification of broad strategies to the design and evaluation of specific policy measures. Only through experimentation and evaluation will we learn what works in raising health care utilization, particularly among the poor in the developing world.

The audio watermarking method proposed in this paper offers copyright protection to an audio signal by time domain processing. The strength of audio signal modifications is limited by the necessity to produce an output signal that is perceptually similar to the original one. The watermarking method presented here does not require the use of the original signal for watermark detection. The watermark signal is generated using a key, i.e., a single number known only to the copyright owner. Watermark embedding depends on the audio signal amplitude and frequency in a way that minimizes the audibility of the watermark signal. The embedded watermark is robust to common audio signal manipulations like MPEG audio coding, cropping, time shifting, filtering, resampling, and requantization.

Concentration indices are frequently used to measure inequality in one variable over the distribution of another. Most commonly, they are applied to the measurement of socioeconomic-related inequality in health. We introduce the user-written command conindex, which provides point estimates and standard errors of a range of concentration indices. The command also graphs concentration curves (and Lorenz curves) and performs statistical inference for the comparison of inequality between groups. We offer an accessible introduction to the various concentration indices that have been proposed to suit different measurement scales and ethical responses to inequality. We also demonstrate the command's capabilities and syntax by analyzing wealth-related inequality in health and health care in Cambodia.

Purpose The purpose of this paper is to analyse the concept of supply chain collaboration and to provide an overall framework that can be used as a conceptual landmark for further empirical research. In addition, the concept is explored in the context of agri‐food industry and particularities are identified. Finally, the paper submits empirical evidence from an exploratory case study in the agri‐food industry, at the grower‐processor interface, and information regarding the way the concept is actually applied in small medium‐sized enterprises (SMEs) is presented. Design/methodology/approach The paper employed case study research by conducting in‐depth interviews in the two companies. Findings Supply chain collaboration concept is of significant importance for the agri‐food industry however, some constraints arise due to the nature of industry's products, and the specific structure of the sector. Subsequently, collaboration in the supply chain is often limited to operational issues and to logistics‐related activities. Research limitations/implications Research is limited to a single case study and further qualitative testing of the conceptual model is needed in order to adjust the model before large scale testing. Practical implications Case study findings may be transferable to other similar dual relationships at the grower‐processor interface. Weaker parts in asymmetric relationships have opportunities to improve their position, altering the dependence balance, by achieving product/process excellence. Originality/value The paper provides evidence regarding the applicability of the supply chain collaboration concept in the agri‐food industry. It takes into consideration not relationships between big multinational companies, but SMEs.

In this paper we investigate the relationship of corporate profitability and working capital management. We used a sample of 131 companies listed in the Athens Stock Exchange (ASE) for the period of 2001-2004. The purpose of this paper is to establish a relationship that is statistically significant between profitability, the cash conversion cycle and its components for listed firms in the ASE. The results of our research showed that there is statistical significance between profitability, measured through gross operating profit, and the cash conversion cycle. Moreover managers can create profits for their companies by handling correctly the cash conversion cycle and keeping each different component (accounts receivables, accounts payables, inventory) to an optimum level.

The identification of design patterns as part of the reengineering process can convey important information to the designer. However, existing pattern detection methodologies generally have problems in dealing with one or more of the following issues: identification of modified pattern versions, search space explosion for large systems and extensibility to novel patterns. In this paper, a design pattern detection methodology is proposed that is based on similarity scoring between graph vertices. Due to the nature of the underlying graph algorithm, this approach has the ability to also recognize patterns that are modified from their standard representation. Moreover, the approach exploits the fact that patterns reside in one or more inheritance hierarchies, reducing the size of the graphs to which the algorithm is applied. Finally, the algorithm does not rely on any pattern-specific heuristic, facilitating the extension to novel design structures. Evaluation on three open-source projects demonstrated the accuracy and the efficiency of the proposed method

Abstract This paper presents experimental results on the major benchmarking functions used for performance evaluation of Genetic Algorithms (GAs). Parameters considered include the effect of population size, crossover probability, mutation rate and pseudorandom generator. The general computational behavior of two basic GAs models, the Generational Replacement Model (GRM) and the Steady State Replacement Model (SSRM) is evaluated. Keywords: Genetic algorithmsBenchmarking functionsPopulation sizeMutation ratePseudo-random number generationC.R. Categories:: I.2.8F.2.2 * jason@uom.gr * jason@uom.gr Notes * jason@uom.gr

For organizations, the development of new business models and competitive advantages through the integration of artificial intelligence (AI) in business and IT strategies holds considerable promise. The majority of businesses are finding it difficult to take advantage of the opportunities for value creation while other pioneers are successfully utilizing AI. On the basis of the research methodology of Webster and Watson (2020), 139 peer-reviewed articles were discussed. According to the literature, the performance advantages, success criteria, and difficulties of adopting AI have been emphasized in prior research. The results of this review revealed the open issues and topics that call for further research/examination in order to develop AI capabilities and integrate them into business/IT strategies in order to enhance various business value streams. Organizations will only succeed in the digital transformation alignment of the present era by precisely adopting and implementing these new, cutting-edge technologies. Despite the revolutionary potential advantages that AI capabilities may promote, the resource orchestration, along with governance in this dynamic environment, is still complex enough and in the early stages of research regarding the strategic implementation of AI in organizations, which is the issue this review aims to address and, as a result, assist present and future organizations effectively enhance various business value outcomes.

In the absence of formal health insurance, we argue that the strategies households adopt to finance health care have important implications for the measurement and interpretation of how health payments impact on consumption and poverty. Given data on source of finance, we propose to (a) approximate the relative impact of health payments on current consumption with a coping-adjusted health expenditure ratio, (b) uncover poverty that is hidden because total household expenditure is inflated by financial coping strategies and (c) identify poverty that is transient because necessary consumption is temporarily sacrificed to pay for health care. Measures that ignore coping strategies not only overstate the risk to current consumption and exaggerate the scale of catastrophic payments but also overlook the long-run burden of health payments. Nationally representative data from India reveal that coping strategies finance as much as three-quarters of the cost of inpatient care. Payments for inpatient care exceed 10% of total household expenditure for around 30% of hospitalized households but less than 4% sacrifice more than 10% of current consumption to accommodate this spending. Ignoring health payments leads to underestimate poverty by 7-8% points among hospitalized households; 80% of this adjustment is hidden poverty due to coping.

Placement of attributes/methods within classes in an object-oriented system is usually guided by conceptual criteria and aided by appropriate metrics. Moving state and behavior between classes can help reduce coupling and increase cohesion, but it is nontrivial to identify where such refactorings should be applied. In this paper, we propose a methodology for the identification of Move Method refactoring opportunities that constitute a way for solving many common feature envy bad smells. An algorithm that employs the notion of distance between system entities (attributes/methods) and classes extracts a list of behavior-preserving refactorings based on the examination of a set of preconditions. In practice, a software system may exhibit such problems in many different places. Therefore, our approach measures the effect of all refactoring suggestions based on a novel entity placement metric that quantifies how well entities have been placed in system classes. The proposed methodology can be regarded as a semi-automatic approach since the designer will eventually decide whether a suggested refactoring should be applied or not based on conceptual or other design quality criteria. The evaluation of the proposed approach has been performed considering qualitative, metric, conceptual, and efficiency aspects of the suggested refactorings in a number of open-source projects.

Purpose – The present study attempts to contribute to the knowledge of how customer satisfaction, loyalty and commitment are defined and relate to each other in the Greek context.

In the past decade, current literature and businesses have drawn attention to Artificial Intelligence (AI) tools and in particular to the advances in machine learning techniques. Nevertheless, while the AI technology offers great potential to solve difficulties, challenges remain implicated in practical implementation and lack of expertise in the strategic usage of AI to create business value. This paper aims to implement a systematic literature review analyzing convergence of the AI and corporate strategy and develop a theoretical model incorporating issues based on the existing research in this field. Eighty-one peer-reviewed articles were discussed on the basis of research methodology from Webster and Watson (2002). In addition to gaps in future research, a theoretical model is developed, discussing the four sources of value creation: AI and Machine Learning in organizations; alignment of AI tools and Information Technology (IT) with organizational strategy; AI, knowledge management and decision-making process; and AI, service innovation and value. These outcomes lead to both theoretical and managerial viewpoints, with extensive possibilities to generate new methods and types of management practices.

This study scrutinizes the existing literature regarding the use of augmented reality and gamification in education to establish its theoretical basis. A systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was conducted. To provide complete and valid information, all types of related studies for all educational stages and subjects throughout the years were investigated. In total, 670 articles from 5 databases (Scopus, Web of Science, Google Scholar, IEEE, and ERIC) were examined. Based on the results, using augmented reality and gamification in education can yield several benefits for students, assist educators, improve the educational process, and facilitate the transition toward technology-enhanced learning when used in a student-centered manner, following proper educational approaches and strategies and taking students’ knowledge, interests, unique characteristics, and personality traits into consideration. Students demonstrated positive behavioral, attitudinal, and psychological changes and increased engagement, motivation, active participation, knowledge acquisition, focus, curiosity, interest, enjoyment, academic performance, and learning outcomes. Teachers also assessed them positively. Virtual rewards were crucial for improving learning motivation. The need to develop appropriate validation tools, design techniques, and theories was apparent. Finally, their potential to create collaborative and personalized learning experiences and to promote and enhance students’ cognitive and social–emotional development was evident.

Heterogeneity in reporting of health by socio-economic and demographic characteristics potentially biases the measurement of health disparities. We use anchoring vignettes to identify socio-demographic differences in the reporting of health in Indonesia, India and China. Homogeneous reporting by socio-demographic group is rejected and correcting for reporting heterogeneity tends to reduce slightly estimated disparities in health by education (not China) and to increase those by income. But the method does not reveal substantial reporting bias in measures of health disparities.

Men and women seem to process emotions and react to them differently. Yet, few neurophysiological studies have systematically investigated gender differences in emotional processing. Here, we studied gender differences using Event Related Potentials (ERPs) and Skin Conductance Responses (SCR) recorded from participants who passively viewed emotional pictures selected from the International Affective Picture System (IAPS). The arousal and valence dimension of the stimuli were manipulated orthogonally. The peak amplitude and peak latency of ERP components and SCR were analyzed separately, and the scalp topographies of significant ERP differences were documented. Females responded with enhanced negative components (N100 and N200), in comparison to males, especially to the unpleasant visual stimuli, whereas both genders responded faster to high arousing or unpleasant stimuli. Scalp topographies revealed more pronounced gender differences on central and left hemisphere areas. Our results suggest a difference in the way emotional stimuli are processed by genders: unpleasant and high arousing stimuli evoke greater ERP amplitudes in women relatively to men. It also seems that unpleasant or high arousing stimuli are temporally prioritized during visual processing by both genders.