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The migration of physicians is a global interest, causing imbalances between developed and developing countries. Romania is one of Europe's major providers of physicians, not because there is a surplus, but because physicians are drawn to places with better living and working conditions. Medicine in Romania is increasingly highly advanced, and Romanian physicians are well appreciated all over the world. Despite being one of the countries with the most medical graduates in the world, Romania is suffering a doctor exodus. After joining the EU, the problem of physician migration became widespread, resulting in a deficient and inefficient healthcare system. Therefore, the purpose of this study is to estimate the losses registered by Romania because of physicians' decision to migrate.

These losses were calculated in two ways: utilizing the statistical life value and the amount of money invested in training a medical graduate.

According to the findings, the losses in 2018 were 104.16 million euros, approximately 0.12% of GDP.

The originality of this paper consists in data, being provided by the College of Physicians from Romania and the method used, this study being the only one that estimates the cost of Romanian physicians' migration. The paper adds to existing knowledge an empirical results regarding quantifying the value reflecting the departure of physicians, using value of statistical life and the amount of money invested in preparing a medical graduate.

Companies avoid taxes in a variety of ways and use different methods to do that, one of the most common being earnings management. The purpose of this paper is to investigate whether companies manipulate their financial data in order to reduce taxes paid.

We considered a sample of 63 listed Romanian companies for the period 2016–2021. The Beneish model was used for estimating earnings management, and the effective tax rate was used to measure tax avoidance. The analysis was carried out using regression analysis in Stata13 software.

The findings of the research indicate a negative and statistically significant association between effective tax rate and earnings management, implying that one of the main reasons why companies manipulate their earnings to reduce tax burden and avoid taxes. Moreover, our results show that return on assets (ROA) has a statistically significant negative influence on the effective tax rate. Furthermore, our analysis reveals that firm size, growth, and Big4 audit have no effect on effective tax rate.

Because it analyzes concrete cases using financial data and provides some recommendations for addressing the issue of tax avoidance, this work is useful in advancing both quantitative and qualitative research on this topic. This research is relevant for businesses, governments, regulators, audit professionals and investors.

The study, by analyzing concrete cases using reported financial data, contributes in filling the gap within the literature that results from a lack of scientific research on the relationship between tax avoidance and earnings management, and then it clarifies the nature of the causal connection between them. Moreover, it considers a combination of firm related variables including performance, size and also audit quality.

This paper investigates the interrelationships of destination social responsibility (DSR), emotional attachment, self-congruity, experiential satisfaction and environmentally responsible behavior (ERB).

Using a sample of 294 visitors to the Guangzhou Zoo in China, this study tested the aforementioned relationships via structural equation modeling.

Emotional attachment mediates the effect of DSR on experiential satisfaction, while emotional attachment and experiential satisfaction mediate the effect of DSR on ERB sequentially. Moreover, self-congruity moderates the relationship between DSR and emotional attachment.

The management of zoos should use DSR communication strategies more proactively to make visitors become well-aware of their economic, philanthropic, environmental and social activities in the host community. This will result in many positive consequences, including visitors’ ERBs.

The study adds to the DSR literature by introducing multiple mediation mechanisms and paths that lead to visitors’ ERBs.

我们的论文调查了目的地社会责任 (DSR) 情感依恋、自我一致性、体验满意度和对环境负责的行为 (ERB) 之间的相互关系。

我们的研究以中国广州动物园的 294 名游客为样本, 通过结构方程模型测试了上述关系。

情感依恋介导 DSR 对体验满意度的影响, 而情感依恋和体验满意度依次介导 DSR 对 ERB 的影响。 此外, 自我一致性调节 DSR 与情感依恋之间的关系。

动物园的管理层应该更积极地使用 DSR 沟通策略, 让游客充分了解他们在东道社区的经济、慈善、环境和社会活动。 这将带来许多积极的后果, 包括访客的 ERB。

该研究通过引入多种调解机制和导致访客 ERB 的路径增加了 DSR 文献。

nuestro artículo investiga las interrelaciones de la responsabilidad social del destino (DSR), el apego emocional, la autocongruencia, la satisfacción experiencial y el comportamiento ambientalmente responsable (ERB).

utilizando una muestra de 294 visitantes del zoológico de Guangzhou en China, nuestro estudio probó las relaciones antes mencionadas a través del modelo de ecuaciones estructurales.

el apego emocional media el efecto de DSR en la satisfacción experiencial, mientras que el apego emocional y la satisfacción experiencial median el efecto de DSR en ERB secuencialmente. Además, la autocongruencia modera la relación entre DSR y apego emocional.

la administración de los zoológicos debe utilizar estrategias de comunicación de DSR de manera más proactiva para que los visitantes estén bien informados sobre sus actividades económicas, filantrópicas, ambientales y sociales en la comunidad anfitriona. Esto tendrá muchas consecuencias positivas, incluidos los ERB de los visitantes.

el estudio se suma a la literatura de DSR al presentar múltiples mecanismos de mediación y caminos que conducen a los ERB de los visitantes.

The purpose of this paper is to investigate how different manufacturing technologies are bundled together and how these bundles influence operations performance and, indirectly, business performance. With the emergence of Industry 4.0 (I4.0) technologies, manufacturing companies can use a wide variety of advanced manufacturing technologies (AMT) to build an efficient and effective production system. Nevertheless, the literature offers little guidance on how these technologies, including novel I4.0 technologies, should be combined in practice and how these combinations might have a different impact on performance.

Using a survey study of 165 manufacturing plants from 11 different countries, we use factor analysis to empirically derive three distinct manufacturing technology bundles and structural equation modeling to quantify their relationship with operations and business performance.

Our findings support an evolutionary rather than a revolutionary perspective. I4.0 technologies build on traditional manufacturing technologies and do not constitute a separate direction that would point towards a fundamental digital transformation of companies within our sample. Performance effects are rather weak: out of the three technology bundles identified, only “automation and robotization” have a positive influence on cost efficiency, while “base technologies” and “data-enabled technologies” do not offer a competitive advantage, neither in terms of cost nor in terms of differentiation. Furthermore, while the business performance impact is positive, it is quite weak, suggesting that financial returns on technology investments might require longer time periods.

Relying on a complementarity approach, our research offers a novel perspective on technology implementation in the I4.0 era by investigating novel and traditional manufacturing technologies together.

Online food delivery applications (OFDAs) provide an expedient platform, and consumers’ access to food has been drastically altered, especially during and after the COVID-19 pandemic. This study aimed to completely explore the attributes that influence consumers' purchase intention and how an app's aesthetics can evoke feelings that predict continuous usage intentions for OFDAs. The food industry, especially restaurants, heavily relies on mobile technology to facilitate critical online food delivery during the pandemic crisis.

The data for this study are gathered from 477 food consumers located in the federal capital territory (FCT) of Islamabad, Pakistan, through convenient sampling by developing a self-administrated online survey. SmartPLS is used for structural equation modeling to test the proposed research model and perform bootstrapping and algorithmic analysis.

Our findings revealed that perceived value positively predicted consumers’ purchase intentions. Moreover, perceived value mediates the association of information quality, familiarity, time-saving, usability and reputation with purchase intentions and fear of COVID-19 moderates the relationship between perceived value and purchase intention.

This research work has significant implications for researchers, web developers, app designers, delivery services, restaurants and other enterprises as it demonstrates the importance of aesthetically pleasing OFDAs in eliciting positive emotions and bolstering consumers’ intentions to continue using the app for efficient food delivery services.

This study expanded the application of the technology acceptance model (TAM) and attention, interest, desire and action (AIDA) by examining consumers’ purchase intentions in the context of OFDAs. Further, the successful utilization of TAM enhanced the understanding of consumer perceptions and behavioral intentions about the usage of OFDAs.

This paper aims to study a neural network-based fault-tolerant controller to improve the tracking control performance of an unmanned autonomous helicopter with system uncertainty, external disturbances and sensor faults, using the prescribed performance method.

To ensure that the tracking error satisfies the prescribed performance, the authors adopt an error transformation function method. A control scheme based on the neural network and high-order disturbance observer is designed to guarantee the boundedness of the closed-loop system. A simulation is performed to prove the validity of the control scheme.

The developed adaptive fault-tolerant control method makes the system with sensor fault realize tracking control. The error transformation function method can effectively handle the prescribed performance requirements. Sensor fault can be regarded as a type of system uncertainty. The uncertainty can be approximated accurately using neural networks. A high-order disturbance observer can effectively suppress compound disturbances.

The tracking performance requirements of unmanned autonomous helicopter system are considered in the design of sensor fault-tolerant control. The inequality constraint that the output tracking error must satisfy is transformed into an unconstrained problem by introducing an error transformation function. The fault state of the velocity sensor is considered as the system uncertainty, and a neural network is used to approach the total uncertainty. Neural network estimation errors and external disturbances are treated as compound disturbances, and a high-order disturbance observer is constructed to compensate for them.

The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.

This study aims to conduct a bibliometric analysis of sustainable tourism research published in Scopus-indexed journals covering the period from 1997 to 2021. Articles published during these 25 years were subjected to science mapping and performance analysis to propose potential areas for future research.

A bibliometric analysis using performance analysis and science mapping was conducted on 1,754 research papers retrieved from the Scopus database using the keyword “sustainable tourism.” Biblioshiny and VOSviewer are commonly used bibliometric tools. Science mapping techniques use coauthorship, keyword co-occurrence and co-citation analyses.

This study revealed the sustainable tourism publications’ spatial and temporal patterns, indicating a yearly growth rate of 19.9% during a 25-year period. The study identified Stefan Gossling as the most influential author, the “Journal of Sustainable Tourism” as the leading journal and Australia as the most productive country in sustainable tourism literature. The study used co-citation analysis to identify five thematic clusters, namely, reconceptualization and criticism, the role of residents, eco-labeling and the role of stakeholders, community-based tourism and the shift toward establishing sustainability indicators and effective governance and policymaking. The coauthorship analysis identifies the most influential author in collaborative efforts, and the most common pattern of collaboration is between researchers from different institutions in the same country, such as China and the Philippines, followed by collaborations between authors from other countries. The keyword co-occurrence analysis uncovered keywords that aligned with theme clusters generated from the co-citation analysis.

This study comprehensively uncovers five thematic clusters that have never been extracted so far in the literature. Also, it attempts to fill the gaps related to sustainable tourism by suggesting directions for future research.

Our study aims to explore the interplay between dysfunctional cognitive schemas and rationality for decision comprehensiveness in organizational strategic decisions.

We used a cross-sectional design in which we evaluated individual decision rationality using an objective decision competence test and dysfunctional cognitive schemas in a sample of 270 managers (145 women with an average age of 41 years old). In addition, we asked managers to rate the decision comprehensiveness of their organization’s strategic decision processes.

Our findings support the detrimental impact of dysfunctional cognition in strategic decision-making in such a way that the association between individual managerial rationality and the comprehensiveness of organizational strategic decisions was positive only when managers reported low dysfunctional cognition, while when managers reported high levels of dysfunctional cognitive schemas, the association between rationality and comprehensiveness was negative.

Our study provides initial empirical evidence for the interplay between dysfunctional cognition and managerial rationality in strategic decision processes, and it opens venues for future research to explore the detrimental role of dysfunctional cognitive schemas in strategy processes.