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The purpose of this study is to evaluate the influence of sustainable business models in building corporate reputation and resilience. Specifically, the financial performance of listed companies will be evaluated following the beginning of the armed conflict in Ukraine on 24 February 2022. Taking as a standpoint the triple bottom line (TBL) theory, the case of firms listed in the Spanish IBEX-35 index is analysed. The present paper evaluates financial performance and corporate reputation, based on the usage of Environment, Social and Corporate Governance (ESG) strategies to adhere to their Corporate Social Responsibility (CSR).

To achieve this goal, energy firms operating in Spain are evaluated. Specifically, companies operating in the energy sector listed in the IBEX35, benchmark index of Spain’s largest trading platform are considered. The analysis comprises evaluating the fluctuation in the value of their stock and the influence of usage of renewable and other power sources that limit dependency on foreign events. In addition, communication and dissemination of non-financial information, and usage of international standards within these areas, are considered as well.

Results show long-term CSR commitments and ESG strategies significantly impact firm’s ability to overcome crises and improve financial performance. Additionally, energy firms that adhered to the energy transition into renewables display stronger performance and lower dependency on uncertain and weakened markets during the Ukraine armed conflict.

The results contribute to the advancement of the TBL theory and the creation of sustainable business models. By introducing ESG strategies, firms are able to improve the people-profit-planet balance and at the same time improve their resilience. This contributes to an overall enhancement of their capacity to overcome crises and sustain their financial performance and corporate reputation over time. Policy makers can also benefit from this knowledge, introducing regulation that promotes and supports companies’ development of their CSR through ESG strategies, to ensure more sustainable organisations that can support the economy in a context of hardship.

The analysis evaluates the results of a firm’s long-term commitment to the TBL through adequate ESG strategies when operating in unexpected and unprecedented hostile environments. Previous research has focused on the link between some variables concerning financial performance and ESG strategies yet not considering the specific context of an enhanced crisis (i.e. a pandemic and armed conflict). This can provide significant insight into the contribution that people, profit and planet can provide in building sustainable and successful organisations. Lastly, the paper outlines the key factors that contributed to the firm’s ability to overcome extreme hardships, such as operating in an environment affected by a combination of two crises.

The purpose of this paper is to establish the empirical link between real exchange rate (RER) undervaluation and sectoral growth in South Africa between 1984 and 2014.

The study employs a dynamic panel data approach estimated by the system generalised method of moments technique in a bid to control for endogeneity.

The authors find a significant positive impact of undervaluation on sectoral growth which increases with capital accumulation. Also, the authors confirm that undervaluation promotes sectoral growth up to a point where further increases in undervaluation retards growth.

The results confirm the importance of policies that keep the domestic currency weaker to foster sectoral growth.

The originality of this paper lies in establishing the impact of exchange rate undervaluation on growth at a sector level in the context of South Africa using a dynamic panel data approach.

The purpose of this paper is to predict the daily accuracy improvement for the Jakarta Islamic Index (JKII) prices using deep learning (DL) with small and big data of symmetric volatility information.

This paper uses the nonlinear autoregressive exogenous (NARX) neural network as the optimal DL approach for predicting daily accuracy improvement through small and big data of symmetric volatility information of the JKII based on the criteria of the highest accuracy score of testing and training. To train the neural network, this paper employs the three DL techniques, namely Levenberg–Marquardt (LM), Bayesian regularization (BR) and scaled conjugate gradient (SCG).

The experimental results show that the optimal DL technique for predicting daily accuracy improvement of the JKII prices is the LM training algorithm based on using small data which provide superior prediction accuracy to big data of symmetric volatility information. The LM technique develops the optimal network solution for the prediction process with 24 neurons in the hidden layer across a delay parameter equal to 20, which affords the best predicting accuracy based on the criteria of mean squared error (MSE) and correlation coefficient.

This research would fill a literature gap by offering new operative techniques of DL to predict daily accuracy improvement and reduce the trading risk for the JKII prices based on symmetric volatility information.

This research is the first that predicts the daily accuracy improvement for JKII prices using DL with symmetric volatility information.

The purpose of this paper is to study the uneven geographies of corruption on the African continent. Corruption is an entrenched part of African political culture. However, the degree and impacts of corruption vary widely across the continent, ranging from failed states such as Somalia to the region’s bright spot Botswana. This paper first defines corruption and discusses its causes and effects. It then delves into the specifics of African corruption, including its causes and effects such as patrimonial political cultures, clientelism and the role of natural resource exports.

The study uses data from Transparency International to assess African corruption empirically and geographically, and links its levels of severity using correlations to gross domestic product per capita, literacy, income inequality and freedom of the media.

The major findings are that while the vast majority of the continent’s one billion people live under very corrupt regimes, the impacts of corruption on economic growth are questionable. Few geographic studies of corruption exist.

The paper’s novelty stems in part from being the first to explore African corruption from a spatial perspective, illustrating its widely varying contexts and consequences.

This paper aims to investigate empirically whether Islamic securities enhance economic growth in the Southeast Asian region based on the endogenous growth theory using the non-parametric analysis.

This paper applies panel quantile regression with Markov chain Monte Carlo optimization as an optimal non-parametric approach to investigate the effect of Islamic securities on economic growth starting from 2013Q4 to 2019Q4 in Southeast Asia. Total issued Islamic securities holdings are employed as a measure for Islamic securities, while the gross domestic product is employed as a proxy for economic growth. The sample includes all working Islamic financial foundations in the top progressive Islamic securities markets' countries of Southeast Asia (Malaysia, Indonesia and Brunei Darussalam).

The findings confirm that the increase of issuing Islamic securities in Islamic capital markets of Southeast Asia is increasing the levels of economic growth, reflecting the weighty role of the Islamic capital market development as an active contributor to economic growth.

This research would fill the literature gap by exploring Islamic securities–economic growth nexus in Southeast Asia using a robust non-parametric approach based on the endogenous growth theory for better estimation results. The findings of this review serve as a roadmap for financial analysts, policymakers and decision makers to stimulate the Islamic securities markets as another source of finance which can promote the economic growth.

This research is the first that investigates empirically the Islamic securities–economic growth nexus in Southeast Asia using a new empirical investigation built on the non-parametric analysis and outlined within the theoretical context of the endogenous growth model to gain robust evidence about this nexus.