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This paper aims to investigate the role of corruption and income inequality in three-dimensional sustainable development in the post-Soviet countries.

The methodology is based on dynamic panel regression with the fixed effects approach.

The authors' findings depict that increasing corruption and income inequality undermine sustainable development. Specifically, increasing corruption and income inequality negatively affect sustainable development. Moreover, unemployment and trade liberalization negatively impact sustainable development, whereas foreign direct investments (FDIs) positively affect sustainable development.

Policy implications enclose galvanizing strong institutions and redistributive policy mechanisms that the bottom income groups enjoy in promoting sustainable development to keep away the distressful phase of corruption and income inequality.

This is the first paper on corruption, income inequality and sustainable development in the post-Soviet countries employing a sustainable development index (SDI), which is calculated by considering three factors including economic, social and environmental development.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2023-0065

This paper aims to investigate the correlation between banking sector non-performing loans (NPLs) and the level of sustainable development.

Pearson correlation test statistic was used to assess the correlation between bank NPLs and sustainable development.

There is a significant positive correlation between banking sector NPLs and the level of sustainable development measured by the sustainable development index (SDI). The significant positive correlation is evident in European countries and in countries in the region of the Americas. There is a significant negative correlation between banking sector NPLs and achieving SDG3 and SDG7 in African countries and European countries. There is also a significant negative correlation between NPLs and achieving SDG10 in European countries. There is a significant positive correlation between banking sector NPLs and achieving SDG4 and SDG7 in the region of the Americas. There is also a significant positive correlation between NPLs and achieving SDG10 in African countries and in countries in the region of the Americas.

The present study is unique and different from other studies because it used a unique SDI to capture the level of sustainable development. The analysis is also unique because it covers several regions, which have not been covered in previous studies.

This paper aims to develop a simple model for estimating sustainable development goals index using the capabilities of artificial neural networks.

Sustainable development has three pillars, including social, economic and environmental pillars. Three clusters corresponding to the three pillars were created by extracting sub-indices of three 2018 global reports and performing cluster analysis on the correlation matrix of sub-indices. By setting the sustainable development goals index as the target variable and selecting one indicator from each cluster as input variables, 20 artificial neural networks were run 30 times.

Artificial neural networks with seven nodes in one hidden layer can estimate sustainable development goals index by using just three inputs, including ecosystem vitality, human capital and gross national income per capita. There is an excellent similarity (>95%) between the results of the artificial neural network and the sustainable development goals index.

Instead of calculating 232 indicators for determining the value of sustainable development goals index, it is possible to use only three sub-indices, but missing 5% of precision, by using the proposed artificial neural network model.

The study provides additional information on the estimating of sustainable development and proposes a new simple method for estimating the sustainable development goals index. It just uses three sub-indices, which can be retrieved from three global reports.

This paper aims to examine the dynamic relationship between economic growth and sustainable development, integrating the Environmental Kuznets Curve (EKC) in 22 Organization of Islamic Cooperation (OIC) member countries across income groups.

Using annual data between 1990 and 2022, the authors apply the cross-correlation coefficient (CCC) approach of Narayan et al. (Economic Modeling, 2016, 53, 388–397) to examine the lead/lag relationship between GDP per capita and sustainable development. This study further validates the findings through a panel Granger causality test and a fixed panel regression model.

This research provides evidence of a U-shaped EKC for only 1 out of 22 (5%) OIC countries. For 13 out of the 22 (59%) OIC countries, increasing income growth is expected to enhance sustainable development in the future. The results show that as income levels rise, there will be a more significant decline in sustainable development for high-income OIC countries in the future than for both middle-income groups, contradicting the EKC hypothesis. The findings from the panel Granger causality and panel regression models also support the CCC results.

This study proposes a reverse version of the EKC hypothesis and contributes to the literature on economic growth and environmental sustainability. With increasing economic growth, the results can assist OIC member governments and policy-makers in designing tailored policies and practical measures for future sustainable development.

This study aims to empirically examine the effects of smart cities on sustainable development for the period 1990–2019 for Türkiye.

The relationship between smart cities and sustainable development was analyzed with the help of the ARDL Bounds Test. In addition, the consistency of the model was tested with the FMOLS estimator. The indicators of the smart city were selected following the literature to represent smart cities, and the author created the smart city index. The study used other variables thought to impact sustainable development as secondary data.

The results show that smart cities positively and significantly impact sustainable development in Turkiye in both models during the sampling period. In addition, while real GDP, population density, and financial development variables positively affect sustainable development, population density has a negative effect on sustainable development, according to the results obtained from FMOLS estimators.

The first novelty of this study is the creation of the smart city index. The second novelty is that there are almost no studies on the effects of smart cities on sustainable development, especially for Türkiye.

This study aims at investigating the effect of corporate social responsibility (CSR) and corporate social irresponsibility (CSI) on corporate financial performance (CFP) in firms headquartered in developed versus emerging countries. Drawing upon stakeholder and legitimacy perspectives, the authors argue that the CSR/CSI–CFP relationship differs depending on the home-countries’ level of economic development as this reflects their different sensitivity to sustainability. Indeed, as emerging economies are normally characterized by weaker regulations, they are likely to place lower pressures on companies for superior CSR practices. Therefore, the authors expect the effect of CSR on CFP to be more positive for firms headquartered in advanced than in emerging countries. At the same time, the authors propose a more negative relationship between CSI and CFP for firms headquartered in developed countries due to the higher overall sustainability expectations required to gain legitimacy. The empirical analyses, run on a sample of 1,971 publicly listed firms between 2010 and 2020 from developed and emerging economies, support the expectations, thus confirming that country-specific contextual factors do play a role in shaping both the positive and the negative impact of CSR and CSI on CFP, and that the reactions of stakeholders to responsible and irresponsible behavior are stronger when their sensitivity to sustainability is higher.

The growing use of internet communication technology has led to increased economic growth across the world, and this chapter seeks to assess the case of Czechia. The study also examines the changing employment distribution in the labour market with the growing influence of information and communication technology (ICT). The multiple indicators and multiple causes model as well as changes in employment or earnings shares of occupations are used for the analysis. The findings show that increased use of ICT contributes to growth in GDP and employment. It also shows that ICT has contributed to rising labour and factor productivity through increased innovation. There is also increased demand for highly educated labour leading to growth in employment in high skill occupations, while the share of low and middle skill occupations declines. The situation, however, does not indicate job polarisation in the labour market and total employment is still increasing. The study also finds that investment and use of ICT has led to progressive development in the human development index of the Czech Republic and a decline in the gender inequality index.

The purpose of this paper is to present a methodological framework and practical application of the sustainable development assessment in Lithuania.

The assessment was performed by deriving composite economic, social and environmental indexes and combining them into the integrated sustainable development index. Each composite index aggregates number of selected indicators, which were essential for the assessment of the country's development during the last decade. Having in mind that sustainable development is the development in consistency, the authors have used equal weights for calculation of economic, social and environmental indexes.

The composite indexes indicate rapid economical growth and environmental state; however, social development was comparatively slow. The economical decline in 2008 has influenced also environmental and social development and revealed new trends of sustainable development in Lithuania. The analysis results demonstrate that goals brought forward in the Strategy for Sustainable Development of Lithuania were not achieved.

The paper provides a methodology of integrated sustainable development index and its application for the Lithuanian case. The greatest advantage of a proposed calculation methodology is its flexibility, because it can be applied for any period of sustainable development evaluation, with a possibility to select a desired number of sustainability aspects that reflect an evolution of a country the best.