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This study aims to examine the impact of economic freedom and corruption on bank stability in sub-Saharan Africa (SSA).

This study uses 38 countries in SSA from 2008 to 2019 using system GMM technique.

The authors found that greater economic freedom increases economic efficiency through improving bank stability. Besides this, the authors also find that banks in environments with greater business freedom, financial freedom, trade freedom and investment freedom are less prone to solvency. The results also show that corruption improves bank stability, suggesting evidence of the “grease the wheels” hypothesis.

The results suggest to policymakers that a high economic freedom may be an appropriate policy toward enhancing bank stability. Besides this, the results also suggest to policymakers to prioritize addressing the core issues that encourage corruption to extort bribes.

This study provides insightful discussion on whether economic freedom and its subcomponents and corruption have an effect on bank stability in SSA.

Digital media platforms on one hand are tools of communication. On the other hand, it is a site where narratives are shared among members of various communities. Thus providing a space to create identities and educate audiences about behaviors toward “them” from “us.” This chapter will highlight how the narratives of Aboriginal Australian women discriminatory issues are conveyed and discussed on Twitter. In attempting so, this chapter will highlight whether the digital space has contributed to equality in the society or is it attempting to reassert the existing hegemonic discourses and status in the Australian Community. Accordingly, this research suggests policies that could help create emancipatory pedagogy.

Boussinesq approximation is widely used in solving natural convection problems, but it has severe practical limitations. Using Boussinesq approximation, the temperature difference should be less than 28.6 K. The purpose of this study is to get rid of Boussinesq approximation and simulates the natural convection problems using an unsteady compressible Navier-Stokes solver. The gravity force is included in the source term. Three temperature differences are used namely 20 K, 700 K and 2000 K.

The calculations are carried out on the square and sinusoidal cavities. The results of low temperature difference have good agreement with the experimental and previous calculated data. It is found that, the high temperature difference has a significant effect on the density.

Due to mass conservation, the density variation affects the velocity distribution and its symmetry. On the other hand, the density variation has a negligible effect on the temperature distribution.

The present calculation method has no limitations but its convergence is slow. The current study can be used in fluid flow simulations for nuclear power applications in natural convection flows subjected to large temperature differences.

This paper explores this relationship between the individual values of managers and human resource (HR) decision‐making.

Questionnaire data were collected from a total of 340 line managers from both Ireland and Canada. The questionnaire instrument comprises three components: Rokeach's instrumental and terminal values instrument; two HR related decision scenarios; and demographic and human capital data.

The results provide modest support for the proposed model that individual values affect HR decision‐making in that capability values were shown to be a significant positive predictor of the importance of health and safety, and peace values were a significant positive predictor of the importance of employment equity.

The findings emphasise the need to simultaneously examine both individual values and organisational factors as predictors of HR decision‐making. Future work should examine the psychometric use of value instruments.

The study underlines the fact that managers need to be aware of the fact that their own values influences how they make decisions. Attention to the values concept amongst managers will improve comprehension of the decision‐making process within organizations.

The value of the paper lies in the fact that the effect of individual values on decision‐making has been under‐researched in the literature.

The purpose of this study is to analyze the dynamic causal relationship between foreign direct investment (FDI), gross domestic product (GDP) and trade openness (TO) on a set of five selected South Asian countries.

This study used newly developed bootstrap auto regressive distributed lags (ARDL) cointegration test to examine the long-run relationship among FDI, GDP and TO for selected South Asian countries for 1975–2016.

The economic growth (EG) is significantly related to TO for Bangladesh, India and Sri Lanka and the expansion of TO is crucial for growth in these countries. The results show that all countries (except Bangladesh) found the existence of long-run cointegration between FDI, GDP and TO, whereas FDI is a dependent variable. These results concluded that FDI and TO are contributing to EG in these selected countries.

This study is one of the first attempts to investigate the causal relationship and address the short and long dynamic among FDI, GDP and TO regarding five south Asian countries such as Bangladesh, India, Nepal, Pakistan and Sri Lanka.

Some scholars argue that corruption hinders economies and investment because it generates extra costs, while others suggest that it can act as a stimulus. Their mixed empirical findings have prompted the analysis of whether investors' attitude towards corruption changes depending on its degree of prevalence.

The authors examined 4,518 public–private partnerships (PPPs) located in 46 developing countries for the period 1997–2017. The data were collected from the World Bank PPP database. The authors investigated the relationship between the amount of investment in PPP projects and the level of corruption using regression with multilevel mixed effects.

Corruption and the amount of investment in PPP projects are inversely related at the low and high end of the spectrum of corruption, but the relationship is positive towards the middle. Further analysis revealed that this was spurred by high investment PPP projects in less developed countries.

The findings allow the authors to reconcile the opposing positions in the literature through a “sand–grease–sand the wheels” effect between the volume of investment and corruption, which can be configured as a reverse S-shape consisting of three stages.

This research aims to examine the macro determinants that significantly affect financial development in the Middle East and North Africa (MENA) region, which could be used furtherly to play a major role in economic sustainability since one of the major driving forces for economic development is the financial development.

The significant determinants of financial development should be efficiently used by the MENA region countries for creating huge financial sector development and innovation, stimulating economic development in turn and leading to the completion of the cycle of development and sustainability. To achieve this study's objective, the researcher employed a quantitative method to develop an econometric model.

This model consisted of two Panel EGLS Cross-Section Random Effects Models (REMs) in which Domestic credit to the private sector as a percentage of GDP (?PCGDP?_it) and stock market capitalization ratio (?SMC?_it) were taken as the dependent variables. In addition, the independent variables included the corruption perception index, financial freedom (FF), political stability (PS) and trade openness (TO). The researcher extracted the data for the analysis from different databases including the World Bank, the Organization for Economic Cooperation and Development and the International Monetary Fund. Throughout the first – Panel EGLS Cross-Section Random Effects Model, it turned out that, while FF, TO and corruption index had a positive relationship with ?PCGDP?_it, PS had an adverse effect on ?PCGDP?_it. The second – Panel EGLS Cross-Section Random Effects Model showed that, while PS and TO had a positive effect on stock market performance, the corruption index and FF had an adverse effect on stock market performance.

Throughout the first – Panel EGLS Cross-Section Random Effects Model, it turned out that, while FF, TO and corruption index had a positive relationship with ?PCGDP?_it, PS had an adverse effect on ?PCGDP?_it. The second – Panel EGLS Cross-Section Random Effects Model showed that, while PS and TO had a positive effect on stock market performance, the corruption index and FF had an adverse effect on stock market performance.

The purpose of this paper is to explore the link between corruption and government debt through a regime-based approach.

The empirical analysis makes use of a panel of 120 countries, spanning the period 1999–2015. The study makes use of the Panel Smooth Transition Regression (PSTR) methodological approach, as well as two alternative measures of corruption.

The empirical results document that the relationship between corruption and debt is non-linear, while a strong threshold effect was present as well. Public debt appears to respond faster to a high corruption regime compared to a low corruption regime, while an increase in the size of the shadow economy, government expenses, the inflation rate, interest payments on debt and military expenditure all increased the debt to GDP ratio. By contrast, an increase in GDP per capita, the secondary school enrollment ratio and the ratio of tax revenues to GDP led to a fall in the debt to GDP ratio. The findings survive certain robust checks when the role of the 2008 financial crisis is explicitly considered, as well as when two separate country samples were considered, i.e. developed vs developing countries.

Governments should aim to control both corruption and the size of the shadow economy if they really wish to reduce any high levels of their public debt. As debt levels respond faster to high corruption regimes, it is necessary that measures to reduce corruption are complemented by higher GDP per capita growth rates, enrolment rates and higher tax revenues.

The novelty of the paper is that it investigates for the first time, to the best of the authors’ knowledge, the presence of non-linearity between corruption and government debt. It proposes non-linear panel cointegration and causality tests, as well as a non-linear panel error correction model that allows for smooth changes between regimes, hence, examining causal relationships in each regime separately.

The study aims to propose a decision-support system to determine the location of a regional disaster logistics warehouse. Emphasizing the importance of disaster logistics, it considers the criteria to be evaluated for warehouse location selection. It is aimed to determine a warehouse location that will serve the disaster victims most efficiently in case of a disaster by making an application for the province of Izmir, where a massive earthquake hit in 2020.

The paper proposes a fuzzy best–worst method to evaluate the alternative locations for the warehouse. The method considers the linguistic evaluations of the decision-makers and provides an advantage in terms of comparison consistency. The alternatives were identified through interviews and discussions with a group of experts in the fields of humanitarian aid and disaster relief operations. The group consists of academics and a vice-governor, who had worked in Izmir. The results of a previously conducted questionnaire were also used in determining these locations.

It is shown how the method will be applied to this problem, and the most effective location for the disaster logistics warehouse in Izmir has been determined.

This study contributes to disaster preparedness and brings a solution to the organization of the logistics services in Izmir.