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The authors investigate how foreign investment in securities market informs about the future firm performance in emerging markets.

The authors define the independent variable abnormal foreign investment (AFI) as the residuals of the foreign ownership equation. The authors regress foreign ownership on its first lag and factors and define the residuals as the AFI. The AFI is the over- or under-investment reflecting foreign conscious (clear-purpose) investment, thus better indicating how foreign investment affects firm performance. The dependent variable is Tobin’s q (Q), which represents the firm performance. Then, the authors regress the Tobin’s q next quarters (Qt + k) on the AFI current quarter (AFIt). The authors use a two-step generalized method of moments (GMM) and check endogeneity with the D-GMM model for the regression.

The results show that the current AFI is positively correlated with the firm performance in each of the next four quarters (the following one year). This positive relationship is pronounced for large firms, firms with no large foreign investors, liquid firms and firms listed in the active market. The results suggest that foreign investment might choose well-productive firms already. Also, the current AFI is significantly positively correlated with stock returns in each of the next three quarters. These results suggest that the AFI is informative up to one-year period.

The results suggest that foreign investors (most of them are small) in the Vietnamese market might choose well-productive firms already. However, if the large investors have long-term investment in tangible, intangible, human capital and so on, and lead to a significant increase in firms’ performance is still the limitation of this paper.

The results of this paper may guide investors whose portfolios are composed of stocks with foreign investment.

This paper adds to the literature to enrich the conclusion of a positive relationship between foreign ownership and firm performance.

This research is aimed at preparing landslide susceptibility using spatial analysis and soft computing machine learning techniques based on convolutional neural networks (CNNs), artificial neural networks (ANNs) and logistic regression (LR) models.

Using the Geographical Information System (GIS), a spatial database including topographic, hydrologic, geological and landuse data is created for the study area. The data are randomly divided between a training set (70%), a validation (10%) and a test set (20%).

The validation findings demonstrate that the CNN model (has an 89% success rate and an 84% prediction rate). The ANN model (with an 84% success rate and an 81% prediction rate) predicts landslides better than the LR model (with a success rate of 82% and a prediction rate of 79%). In comparison, the CNN proves to be more accurate than the logistic regression and is utilized for final susceptibility.

Land cover data and geological data are limited in largescale, making it challenging to develop accurate and comprehensive susceptibility maps.

It helps to identify areas with a higher likelihood of experiencing landslides. This information is crucial for assessing the risk posed to human lives, infrastructure and properties in these areas. It allows authorities and stakeholders to prioritize risk management efforts and allocate resources more effectively.

The social implications of a landslide susceptibility map are profound, as it provides vital information for disaster preparedness, risk mitigation and landuse planning. Communities can utilize these maps to identify vulnerable areas, implement zoning regulations and develop evacuation plans, ultimately safeguarding lives and property. Additionally, access to such information promotes public awareness and education about landslide risks, fostering a proactive approach to disaster management. However, reliance solely on these maps may also create a false sense of security, necessitating continuous updates and integration with other risk assessment measures to ensure effective disaster resilience strategies are in place.

Landslide susceptibility mapping provides a proactive approach to identifying areas at higher risk of landslides before any significant events occur. Researchers continually explore new data sources, modeling techniques and validation approaches, leading to a better understanding of landslide dynamics and susceptibility factors.

The consolidation behavior of prefabricated vertical drain (PVD)-installed soft deposits mainly depends on the PVD performance. The purpose of this study is to propose a numerical solution for the consolidation of PVD-installed soft soil using the large-strain theory, in which the reduction of discharge capacity of PVD according to depth and time is simultaneously considered.

The proposed solution also takes into account the general constitute relationship of soft soil. Subsequently, the proposed solution is applied to analyze and compare with the monitoring data of two cases, one is the experimental test and another is the test embankment in Saga airport.

The results show that the reduction of PVD discharge capacity according to depth and time increased the duration required to achieve a certain degree of consolidation. The consolidation rate is more sensitive to the reduction of PVD discharge capacity according to time than that according to the depth. The effects of the reduction of PVD discharge capacity according to depth are more evident when PVD discharge capacity decreases. The predicted results using the proposed numerical solution were validated well with the monitoring data for both cases in verification.

In this study, the variation of PVD discharge capacity is only considered in one-dimensional consolidation. However, it is challenging to implement a general expression for discharge capacity variation according to time in the two-dimensional numerical solution (two-dimensional plane strain model). This is the motivation for further study.

A geotechnical engineer could use the proposed numerical solution to predict the consolidation behavior of the drainage-improved soft deposit considering the PVD discharge capacity variation.

The large-strain consolidation of PVD-installed soft deposits could be predicted well by using the proposed numerical solution considering the PVD discharge capacity variations according to depth and time.

This study aims to examine the nonlinear threshold effect of shadow economy on sustainable development in Africa while providing additional evidence on how this nonlinear threshold effect play out in economies with high and low developed financial/credit markets.

This study uses 37 African economies between 2009 and 2017 in a dynamic GMM panel model that controls for country, year and technological effects to ensure consistency and reliability of results and findings.

The results reveal that there is an inverted nonlinear U-shape nexus between the size of shadow economy and sustainable development in both short run and long run in Africa and across economies with high and low developed credit/financial market. Also, the threshold points beyond which the size of shadow economies dampens sustainable development is lower for economies with high financial/credit market development and higher in the long run.

These results have policy implications and recommendations and suggest that shadow economies can be beneficial to sustainable development particularly when the size of shadow economies are restrained from increasing beyond certain thresholds/levels. Moreso, to restrict the adverse effect of shadow economies on sustainable development, policymakers can rely on developing their financial/credit markets to tame the destructive nature of shadow economies on sustainable development. These results are robust to technological, year/time and country effects.

To the best of the author’s knowledge, this study examines for the first in the context of Africa, the nonlinear effect of shadow economies on sustainable development under low and high developed financial markets.

Energy poverty is a global phenomenon, but its prevalence is enormous in most African countries, with a potential impact on quality of life. This study aims to investigate the impact of energy poverty on the shadow economy.

The study uses panel data from 45 countries in Africa over a period of 1996–2018. Using panel cointegrating regression and panel vector auto-regression model in the generalized method of moments technique.

This study provides that energy poverty deepens the size of the shadow economy in Africa. It also documents that there is a bidirectional causality between shadow economy and energy poverty. Therefore, the two variables can predict each other.

The study suggests that lack of access to clean and modern energy services contributes to the depth of the shadow economy in Africa. African authorities are advised to strengthen rural and urban electrification initiatives by providing adequate energy infrastructure so as to reduce the level of energy poverty in the region. To ensure energy sustainability delivery, the study proposes that the creation of national and local capacities would be the most effective manner to guarantee energy accessibility and affordability. Also, priorities should be given to the local capital mobilization and energy subsidies for the energy poor. Energy literacy may also contribute to the sustainability and the usage of modern energy sources in Africa.

Previous studies reveal that income inequality contributes to the large size of shadow economy in developing economies. However, none of these studies analyzed the role of energy poverty and its implications for underground economic operations. Inadequate access to modern energy sources is likely to deepen the prevalence of informality in developing nations. Based on this, this study provides fresh evidence on the implications of energy deprivation on the shadow economy in Africa using a heterogeneous panel econometric framework. The study contributes to the literature by advocating that the provision of affordable modern energy sources for rural and urban settlements, and the creation of good energy infrastructure for the firms in the formal economy would not only improve the quality of life but also important to discourage underground economic operations in developing economies.

The purpose of this paper is to argue for the development of a vibrant domestic tourism sector in emerging economies as a means of moving towards a more sustainable tourism sector and achieving many of the goals outlined in the UNWTO’s 2030 Agenda for Sustainable Development.

It uses a perspective approach through a critical state-of-the-art review of selected domestic and international tourism studies.

This paper illustrates how developing such a sector will provide a range of economic and social benefits to emerging economies and their residents, as well as lowering the per-capita tourism carbon footprint of destination areas.

This study identifies policy initiatives that can be developed to help emerging economies transition from an international tourism focus to a more balanced focus.

This study indicates the social benefits of developing a domestic tourism sector in emerging economies.

It equips national tourism organisations and small and medium tourism enterprises with specific actions for the use of tourism as a prosperity tool in the pursuance of these benefits. It, further, calls for a research agenda on investigating how emerging economies are uniquely progressing towards this global goal through thriving domestic tourism recognising that each economy is culturally different.

本文主张在新兴经济体发展充满活力的国内旅游业, 以此作为迈向更可持续的旅游业和实现联合国世界旅游组织《2030 年可持续发展议程》中概述的许多目标的手段。

通过对选定的国内和国际旅游研究进行批判性的最新文献回顾, 采用了前瞻性的方法。

本文阐述了发展这样一个产业将如何为新兴经济体及其居民提供一系列经济和社会效益, 并降低目的地的人均旅游碳足迹。

确定可以制定的政策举措, 以帮助新兴经济体从国际旅游业向更平衡的旅游业转型

展现了新兴经济体发展国内旅游业的社会效益。

为国家旅游组织和中小型旅游企业提供了将旅游业作为繁荣工具以实现上文提到的这些利益的具体方向。此外, 论文还呼吁制定一项研究议程, 调查新兴经济体如何通过繁荣的国内旅游业独特地朝着这一全球目标前进, 也需要认识到每个经济体的文化都不同。

Este trabajo defiende el desarrollo de un sector turístico interno fuerte en las economías emergentes como medio para avanzar hacia un sector turístico más sostenible y alcanzar muchos de los objetivos esbozados en la Agenda 2030 para el Desarrollo Sostenible de la OMT.

Adopta un enfoque de perspectiva a través de una revisión crítica del estado del arte de estudios turísticos nacionales e internacionales seleccionados.

El trabajo ilustra cómo el desarrollo de este sector aportará una serie de beneficios económicos y sociales a las economías emergentes y a sus residentes, así como la reducción de la huella de carbono per cápita del turismo en las zonas de destino.

Identifica las iniciativas políticas que pueden desarrollarse para ayudar a las economías emergentes en la transición de un enfoque turístico internacional a un enfoque más equilibrado.

Se indican los beneficios sociales de un desarrollo del sector turístico interno en las economías emergentes.

Proporciona a las organizaciones nacionales de turismo y a las pequeñas y medianas empresas turísticas acciones específicas para el uso del turismo como herramienta de bienestar en la consecución de estos beneficios. Además, propone un programa de investigación sobre el modo en que las economías emergentes avanzan hacia este objetivo global a través de un turismo interno floreciente, teniendo en cuenta que cada economía es culturalmente diferente.

This study aims to investigate the possible relationship between financial inclusion and shadow economy in selected African countries.

The study uses panel data estimation technique and Toda and Yamamoto causality approach. The data of selected African counties over a period of 2005–2015 are sourced from World Bank Development Indicators, International Monetary Fund International Financial statistics database and International Country Risk Guide.

The results show that financial inclusion reduces the size of shadow economy. The causality results show that there is a unidirectional causality moving from financial inclusion to shadow economy. The results demonstrate that a country with lower level of corruption and higher level of growth can benefit more in reducing the size of shadow economy through financial inclusion.

This study provides the first evidence of the link between financial inclusion and shadow economy from the Sub-Saharan Africa perspective. The study suggests that financial inclusion may be useful in affecting the size of shadow economy in Africa.

This study focuses on the relationship between foreign direct investment (FDI) and economic growth of the formal sector comprising all foreign and domestic registered enterprises engaged in production of goods and services.

This study uses a balanced longitudinal data set for the period from 2006 to 2014 from secondary sources in 63 provinces/cities of Vietnam. The generalized method of moments (GMM) estimation for a dynamic panel data model is applied.

The greater the share of FDI in capital resource, the more favorable the output growth in the whole formal sector. The FDI enterprises are more productive than domestic formal firms, and the output growth of FDI firms creates a positive spillover effect on the output growth of domestic firms.

The effect of FDI on economic growth is investigated at subnational level for the whole formal economic sector as well as the formal domestic firms. The domestic and foreign industrial agglomerations and the business environment are also examined.

This research examines how shadow economy affects foreign direct investment (FDI).

The study utilizes a panel dataset including 124 nations between 1997 and 2015. Information on shadow economy, FDI and macro-economic characteristics is obtained from the United Nations Conference on Trade and Development (UNCTAD) and World Bank database. Various econometric methods are employed, such as the panel ordinary least squares (OLS) with fixed-effect estimator and the two-step system generalized method of moments estimation.

The findings of the study illustrate that shadow economy negatively influences total FDI inflows, and this adverse impact is mainly driven by greenfield investments – a component of FDI. Moreover, the authors provide evidence that the shadow economy has more devastating influences on FDI inflows in countries with higher corruption levels and fewer land resources.

Overall, this research suggests an important policy implication that the shadow economy should be controlled more strictly since it harms the FDI inflows, especially greenfield investment.

This research is among the first attempt of evaluating the effect of shadow economy on different FDI types. Furthermore, it examines how the shadow economy–FDI inflows nexus is changed when considering factors including corruption and land resource.

Tourism has grown to be one of the world's largest and fastest-growing economic industries. Tourism development is viewed as a tool to improve income distribution as it allows people at the bottom of the pyramid to get involved in the industry. This study aims to examine the impact of tourism on income inequality in the top income equality countries.

The paper employs fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares techniques to investigate the dynamic impact of tourism on income inequality in the world's most income equality countries, from 2001 to 2016.

The result shows that tourism is one of the major drivers of income equality. Thus, tourism can be used to reduce a country's income disparity.

As a result, policymakers should support the tourism industry to reduce income disparity and enhance income distribution.

Given the conflicting findings in the literature, this study reexamines this link and attempts to backwardly assess if the top equal-income countries in the world are heavily dependent on tourism.