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This study investigates if the causal relationships between the exchange rates and selected inbound markets’ tourism demand are temporary or permanent, and compares market reactions in Türkiye.

Tourism demand is examined with a regional approach, focusing on the geographical markets, namely Europe, Commonwealth of Independent States (CIS) members and Asian countries, as the top inbound tourism markets, in addition to the total number of inbound tourists to Türkiye. Granger, frequency-domain causality, asymmetric Toda–Yamamoto, and asymmetric frequency-domain causality tests were employed to investigate and compare markets on exchange rate–tourism demand relationship for 2008M01-2020M02.

The results indicate that exchange rates affect European tourism demand both in the short and long run. The meaning of this Frequency Domain Causality (FDC) analysis finding shows that the exchange rate has both permanent and temporary effects on European tourists. The relationships are statistically insignificant for CIS members and Asian countries. The exchange rates also permanently affect total inbound tourism demand, but the independent variable has no short-run (temporary) effects on total demand. Asymmetric causality tests confirmed a permanent causality relationship from the positive and negative components of exchange rates to the positive and negative components of European and total tourism demand.

The Granger causality test provides information on the presence of a causal relation, while the FDC test, an extended version of Granger causality, enlightens the short- (temporary) and long-run (permanent) relationships and allows for analyzing the duration of the impact. In addition, asymmetric causality relationships are also investigated in the study. Besides, this study is the first in the literature to examine the relationship between tourism demand and the exchange rate regionally (continentally) for Türkiye.

This study aims to determine the impact of forensic accounting, probability of detections, tax penalties, government spending, tax justice and tax ethics on value-added tax (VAT) evasion.

The study uses partial least squares-structural equation modeling to examine the connection between tax sanction, probability of detection, tax ethics, tax justice, forensic accounting and government spending on VAT evasion based on 248 responses collected from the retail industry in Jordan.

The findings also demonstrate that there is a negative correlation between tax sanctions, probability of detection, tax ethics, tax justice, forensic accounting, government spending and VAT evasion efficiency.

The results, considering forensic accounting and government expenditure considerations, may emphasize the importance of the tax sanction, probability of detection, tax ethics, adoption of tax justice in the public sector and tax authority. Additionally, the findings are important for regulators and decision-makers in announcing new laws and strategies for VAT evasion.

It turns out that the tax authority and public sector can definitely improve their capacity to protect public funds and limit VAT evasion practices within SMEs by adopting increased tax sanctions, probability of detection, tax ethics, tax justice, forensic accounting and government spending.

Numerous studies have been conducted at the individual level in the context of income tax on the link between tax punishment, probability of detection, tax ethics, tax justice, forensic accounting and tax evasion. This study expands on the scant evidence of this connection to the retail business in the context of VAT avoidance. Additionally, it advances prior studies by integrating fresh elements, such as forensic accounting and government expenditure, that have never been considered in connection to VAT evasion in the retail sector.

The study examines the effects of corporate governance and countrywide institutions and risk factors on corporate liquidity.

Using firm-level data, the authors analyze the effect of corporate governance and various economic, regulatory and social institutions on the liquidity of firms operating in the Middle East and North Africa (MENA) region. The authors use fixed-effects, firm-specific and country-level controls, disaggregated analysis, sensitivity and endogeneity analysis to test the robustness of the estimates.

The corporate governance characteristics of firms influence in diverse ways their liquidity decisions. The independence and diversity of the board and institutional ownership are especially strong predictors. The effect also depends on the size of the firm and the degree of economic development and exhibits time sensitivity and nonlinearity. Enforcement institutions and risk factors play a strong role.

The analysis contributes to the literature by using a large sample of countries and firms over a larger period, distinguishing between poorer and richer countries and using sensitivity and endogeneity analysis. The analysis considers explicitly the role of regulatory and enforcement conditions, social structures and religious beliefs.

The COVID-19 pandemic and the onset of the conflict in Ukraine led to a sustained downturn in tourist arrivals (TA) in Russia. This paper aims to explore the influence of geopolitical risk (GPR) and other indices on TA over 1995–2023.

We employ a nonlinear autoregressive distributed lag (NARDL) model to analyze the effects, capturing both the positive and negative shocks of these variables on TA.

Our research demonstrates that the NARDL model is more effective in elucidating the complex dynamics between macroeconomic factors and TA. Both an increase and a decrease in GPR lead to an increase in TA. A 1% negative shock in GPR leads to an increase in TA by 1.68%, whereas a 1% positive shock in GPR also leads to an increase in TA by 0.5%. In other words, despite the increase in GPR, the number of tourists coming to Russia increases by 0.5% for every 1% increase in that risk. Several explanations could account for this phenomenon: (1) risk-tolerant tourists: some tourists might be less sensitive to GPR or they might find the associated risks acceptable; (2) economic incentives: increased risk might lead to a depreciation in the local currency and lower costs, making travel to Russia more affordable for international tourists; (3) niche tourism: some tourists might be attracted to destinations experiencing turmoil, either for the thrill or to gain firsthand experience of the situation; (4) lagged effects: there might be a time lag between the increase in risk and the actual impact on tourist behavior, meaning the effects might be observed differently over a longer period.

Our study, employing the NARDL model and utilizing a dataset spanning from 1995 to 2023, investigates the impact of GPR, gross domestic product (GDP), real effective exchange rate (REER) and economic policy uncertainty (EPU) on TA in Russia. This research is unique because the dataset was compiled by the authors. The results show a complex relationship between GPR and TA, indicating that factors influencing TA can be multifaceted and not always intuitive.

This study aims to understand the interaction between tax fairness perceptions, equitable tax burden distribution and tax compliance within Morocco’s unique socio-economic context, with the goal of uncovering strategies to enhance tax compliance.

Using the Delphi method, this study engaged tax experts in the Moroccan context to explore the impact of taxpayers’ perception of fairness, tax rates and tax burden on compliance. Their responses were gathered and analyzed with the aid of IRaMuTeQ software, which helped the authors identify themes relevant to the research question.

The preliminary results indicate a positive correlation between perceptions of tax fairness and compliance behavior, corroborating earlier studies conducted in different contexts. Notably, a substantial majority of Moroccan taxpayers perceive the current tax system as inequitable, deeming tax rates too high and the tax burden unfairly distributed among various taxpayer categories. This perception potentially influences their voluntary tax compliance behavior.

The findings have significant policy implications for the Moroccan Government and stakeholders. They suggest that by improving tax fairness, particularly by aligning tax assessment and payment modalities for employees, civil servants and small to medium enterprises, policymakers can encourage higher voluntary tax compliance, thereby potentially enhancing the efficiency of the Moroccan tax system.

This study adds to the existing body of knowledge by exploring the dynamics of tax fairness and compliance behavior in Morocco, a context which has been significantly understudied.

Incorporating dynamic spatial effects exhibits considerable potential in improving the accuracy of forecasting tourism demands. This study aims to propose an innovative deep learning model for capturing dynamic spatial effects.

A novel deep learning model founded on the transformer architecture, called the spatiotemporal transformer network, is presented. This model has three components: the temporal transformer, spatial transformer and spatiotemporal fusion modules. The dynamic temporal dependencies of each attraction are extracted efficiently by the temporal transformer module. The dynamic spatial correlations between attractions are extracted efficiently by the spatial transformer module. The extracted dynamic temporal and spatial features are fused in a learnable manner in the spatiotemporal fusion module. Convolutional operations are implemented to generate the final forecasts.

The results indicate that the proposed model performs better in forecasting accuracy than some popular benchmark models, demonstrating its significant forecasting performance. Incorporating dynamic spatiotemporal features is an effective strategy for improving forecasting. It can provide an important reference to related studies.

The proposed model leverages high-frequency data to achieve accurate predictions at the micro level by incorporating dynamic spatial effects. Destination managers should fully consider the dynamic spatial effects of attractions when planning and marketing to promote tourism resources.

This study incorporates dynamic spatial effects into tourism demand forecasting models by using a transformer neural network. It advances the development of methodologies in related fields.

纳入动态空间效应在提高旅游需求预测的准确性方面具有相当大的潜力。本研究提出了一种捕捉动态空间效应的创新型深度学习模型。

本研究提出了一种基于变压器架构的新型深度学习模型, 称为时空变压器网络。该模型由三个部分组成：时空转换器、空间转换器和时空融合模块。时空转换器模块可有效提取每个景点的动态时间依赖关系。空间转换器模块可有效提取景点之间的动态空间相关性。提取的动态时间和空间特征在时空融合模块中以可学习的方式进行融合。通过卷积运算生成最终预测结果。

结果表明, 与一些流行的基准模型相比, 所提出的模型在预测准确性方面表现更好, 证明了其显著的预测性能。纳入动态时空特征是改进预测的有效策略。它可为相关研究提供重要参考。

所提出的模型利用高频数据, 通过纳入动态空间效应, 在微观层面上实现了准确预测。旅游目的地管理者在规划和营销推广旅游资源时, 应充分考虑景点的动态空间效应。

本研究通过使用变压器神经网络, 将动态空间效应纳入旅游需求预测模型。它推动了相关领域方法论的发展。

La incorporación de efectos espaciales dinámicos ofrece un considerable potencial para mejorar la precisión de la previsión de la demanda turística. Este estudio propone un modelo innovador de aprendizaje profundo para capturar los efectos espaciales dinámicos.

Se presenta un novedoso modelo de aprendizaje profundo basado en la arquitectura transformadora, denominado red de transformador espaciotemporal. Este modelo tiene tres componentes: el transformador temporal, el transformador espacial y los módulos de fusión espaciotemporal. El módulo transformador temporal extrae de manera eficiente las dependencias temporales dinámicas de cada atracción. El módulo transformador espacial extrae eficientemente las correlaciones espaciales dinámicas entre las atracciones. Las características dinámicas temporales y espaciales extraídas se fusionan de manera que se puede aprender en el módulo de fusión espaciotemporal. Se aplican operaciones convolucionales para generar las previsiones finales.

Los resultados indican que el modelo propuesto obtiene mejores resultados en la precisión de las previsiones que algunos modelos de referencia conocidos, lo que demuestra su importante capacidad de previsión. La incorporación de características espaciotemporales dinámicas supone una estrategia eficaz para mejorar las previsiones. Esto puede proporcionar una referencia importante para estudios afines.

El modelo propuesto aprovecha los datos de alta frecuencia para lograr predicciones precisas a nivel micro incorporando efectos espaciales dinámicos. Los gestores de destinos deberían tener plenamente en cuenta los efectos espaciales dinámicos de las atracciones en la planificación y marketing para la promoción de los recursos turísticos.

Este estudio incorpora efectos espaciales dinámicos a los modelos de previsión de la demanda turística mediante el empleo de una red neuronal transformadora. Supone un avance en el desarrollo de metodologías en campos afines.

This paper highlights the need for future studies researching the subject of resilience in family firms on different levels.

This paper reviews the literature on resilience in family businesses.

Resilience has become more important due to the recent multiple crises, starting with the coronavirus pandemic, followed by high inflation and energy prices, partly resulting from the war in Ukraine. These multiple crises affect the family and the business level. Future research must account for multiple levels when addressing it, i.e. the individual, the team, the family, and the business level. Resilience has to encompass all levels to sustain family business continuity.

By giving an overview of the concept of resilience, taking the family's perspective, and suggesting future avenues of research, the paper contributes to the development of family business research.

This study aims to explore the constructs of spirituality (SP) and entrepreneurial performance (EP) and their measurements to identify their connections. Attending to the needs of entrepreneurs to face the current global crisis, this research establishes a framework that integrates SP to enhance EP.

This study focuses on a comprehensive literature review and a comparison between constructs to come across with the proposal of a conceptual framework.

For SP, spiritual well-being was found as a good measure which, to the best of the authors’ knowledge, has never been used in entrepreneurship. EP has been typically measured by economic indicators, but recently, noneconomic benefits and effects on stakeholders have also been considered, so an integrated approach is proposed. The main contribution is a framework called holistic entrepreneurial inventory (HEI), which integrates the main elements of the constructs in a matrix showing their interconnection. It is accompanied by a scorecard for entrepreneurs to identify strengths and weaknesses in SP and EP.

This is a theoretical research and proposal; further empirical research could help confirm the present conceptual findings.

To help entrepreneurs identify the areas where they would like to improve, understanding the connection between SP and EP, which are dynamic states in constant change.

EP has been mainly focused on exogenous causes. The HEI scorecard may give entrepreneurs a different perspective from the innermost part of their being.

This study aims to analyze the effects of microentrepreneurs’ knowledge transfer (KT) on personal improvement (PI) and business improvement (BI).

The study was developed in two stages: a literature review based on KT and the learning process in microenterprises to have managerial competence and PI and BI to acquire the managerial competence that entrepreneurs need. The second stage was constructing a structural model based on 107 questionnaires and bootstrapping of 5,000 replications of microentrepreneurs who went through a training program (quantitative) and a focus group (qualitative). This study had a mixed approach, exploratory scope and experimental design.

The research showed real evidence about the performance level of microentrepreneurs when they passed through the process of KT and its impact on PI and BI. This research considers their managerial competencies, and the findings show a relationship between the theory of individual and organizational learning.

This study considered Peruvian microentrepreneurs who participated in a virtual training program that included several courses related to their current environments and topics of interest. The analyzed period covered the years affected by COVID-19.

The model reveals that KT is relevant to PI and BI. Performance was measured regarding growth, income, innovation, productivity and responsibility before and after the program.

This research analyzed the need for training microentrepreneurs for personal and private reasons under a COVID-19 scenario to foster their businesses and assume financial responsibilities. This study considered Peru’s reality, a country in which 94.9% of companies are microenterprises. The study revealed that microentrepreneurs improved their personal and professional lives and addressed relevant social problems that affect their environments because of the KT effects.

This study bridges the gap in the literature on how the theory of KT can be applied to entrepreneurs. This study revealed significant findings in terms of PI and BIs. The impact of KT indicates the relevance of managerial competencies related to the performance level obtained in terms of growth, income, innovation, productivity and responsibility.

This paper aims to investigate if, under which conditions, and with which consequences, nonfamily members have the perception of being discriminated against as a consequence of nepotism and adverse selection practices. This research also aims to investigate whether the carried-out role influences the perception of being discriminated against among nonfamily member employees.

A quantitative approach was carried out by adopting a structural equation model (SEM) analysis. The survey investigated a sample of Italian family SMEs (participating companies N = 186, total questionnaires collected N = 838).

Drawing on the multiple identities theory, findings show that role salience (RS) effectively contributes to reducing the unwanted effects of perceived discrimination (PD) among nonfamily member employees. In doing so, this study deepens the knowledge of nonfamily member employment conditions and their consequences on strategic outcomes such as organizational commitment (OC), organizational justice (OJ) and intention to quit (ITQ).

By adopting a self-categorization approach, this study also advances current theoretical literature, as this methodological lens could help scholars further understand diversity in family business.

This study suggests it would be advisable to implement human resource management practices based on job rotation to promote cohesion and reduce perceived distances.

SMEs are the most widespread type of firm in the world; as a consequence, avoiding PD among nonfamily member employees has general ethical relevance.

This study expands current literature by showing that RS plays an important role in determining levels of PD. This study also advances current literature by focusing on the impact of multiple identities on fairness and commitment at individual and group levels of analysis of family businesses.