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This study aims to examine the influence of internal and external factors on the credit risk (represented by nonperforming financing [NPF]) of Indonesian Sharīʿah rural banks (SRBs) – a type of Islamic bank that provides Islamic financial services especially to small and medium businesses in Indonesia. Internal variables comprise capital adequacy ratio (CAR), financing to deposit ratio (FDR), return on assets (ROA), operating expense ratio (OER), financing to value (FTV) and profit and loss sharing (PLS) financing ratio. External variables comprise inflation, economic growth and interest rate.

The study uses the annual reports of SRBs in Indonesia as secondary data for the years 2010–2019. Auto regressive distributed lag (ARDL) is used as the analysis method to examine the short-run and long-run relationships between the variables.

The findings indicate that four variables experienced a lag in the short run, namely, NPF, inflation, CAR and PLS, with different results recorded for each of the variables. Furthermore, the long-run results show that CAR and ROA influence the NPF of SRBs positively, whereas inflation and PLS have a negative influence on NPF. The rest of the variables – notably economic growth, interest rate, FDR, FTV and OER – do not have an influence on NPF in SRBs.

The level of NPF in SRBs exceeds the provision of the Central Bank of Indonesia. The findings are expected to have implications for SRBs and the regulator to consider and to manage the factors related to NPF properly due to the important role of SRBs in small and medium businesses’ development.

This study measures the determinants of NPF using internal and external variables, including the addition of a dummy variable, notably FTV. This study also uses ARDL to analyze the financial policies involving data at the present time and lagged time.

This study investigates the performance distribution of passive funds in the Korean market and compares it with the performance distribution of active funds. The key findings are as follows, first, the performance distribution of passive funds has a thicker tail compared to that of active funds. There are passive funds that achieve outstanding performance, and both the false discovery rate (FDR) analysis and simulation analysis suggest that their outperformance is driven by managerial skill rather than luck. Second, passive fund performance is more persistent compared to active fund performance. Third, investors are less responsive to passive fund performance compared to active fund performance. The fund flow-performance relationship is significantly positive for active funds but not for passive funds. This implies that investors may not recognize the managerial skills of passive funds.

Purpose – The aim of this study is to analyze the effects of macro- and micro-economic variables on the ratio of troubled financing (Non-Performing Financing, NPF).

Design/Methodology/Approach – The method used in this research is the data panel fixed effect with 13 banks and 4 periods of data report (semi-annual report 2014–2015).

Findings – The regression result achieved that variable inflation significantly influences the ratio of NPF. Variable Gross Domestic Product and assets total significantly influence the ratio of NPF too. While the SBI sharia’s variable and Financing to Deposit Ratio did not significantly affect NPF in Syariah’s Unit of Aceh Bank Pembangunan Daerah (BPD) in Indonesia.

Research Limitations/Implications – This study uses panel data which are a combination of time series data and cross-section.

Practical Implications – The policymakers can design a macro-policy carefully and better fiscal policies.

Originality/Value – This research was conducted on the Syariah’s Unit of BPD in Indonesia during the period 2014–2015 and it has not been done before.

Explore the development trend of chemically-improved soil in railway engineering.

In this paper, the technical standards home and abroad were analyzed. Laboratory test, field test and monitoring were carried out.

The performance design system of the chemically-improved soil should be established.

On the basis of the performance design, the test methods and standards for various properties of chemically-improved soil should be established to evaluate the improvement effect and control the engineering quality.

The purpose of this study was to define and outline areas prone to disease causing elements by analyzing the spatial distribution and concentration of toxic and essential elements in a section of the Voltaian sedimentary basin.

A total of 2,668 soil samples were analysed by the inductively coupled plasma mass spectrometry technique and were re-appraised by comparing with baseline values of elements accepted globally to be in soils. The concentrations of arsenic (As), chromium (Cr), iron (Fe) and magnesium (Mg) were evaluated. Factor analysis, hierarchical cluster analysis and principal component analysis multivariate techniques were used to identify the source patterns of the elements in the soils. The Getis-Ord Gi method was used to generate the optimised maps for these selected elements. These maps spatially defined and outlined high value clusters which imply potential pollution or areas with high background values (hotspots), whereas the low value clusters imply areas with low background values (cold-spots).

The multivariate analysis supports a dominant geogenic source of these heavy elements with obvious influences from variably metamorphosed mafic–ultramafic rocks known to have contributed to the deposition of sediments in the basin. The hotspots for As were located around Nalerigu and to the east of Nawchugu. A Cr hotspot was located to the east of Nawchugu with Cr cold-spots located within Nalerigu and Yunyuo. Fe hotspots were observed to the south of Nalerigu and the east of Nawchugu with Fe cold-spots around Yunyuo, Bongo-Da and Nagbo. The spatial maps demonstrated the presence of toxic and deficient areas of all the selected elements used in the investigation. Therefore, it suggested the likely health implications depending on the exposed elements, their pathways and recommended the usefulness of using the results displayed in the spatial maps to guide in devising appropriate remediation techniques.

This paper fulfils an identified need to study the distribution of elements and the possible effects it may have on the health and livelihoods of those residing in these areas.

Classification techniques have been applied to many applications in various fields of sciences. There are several ways of evaluating classification algorithms. The analysis of such metrics and its significance must be interpreted correctly for evaluating different learning algorithms. Most of these measures are scalar metrics and some of them are graphical methods. This paper introduces a detailed overview of the classification assessment measures with the aim of providing the basics of these measures and to show how it works to serve as a comprehensive source for researchers who are interested in this field. This overview starts by highlighting the definition of the confusion matrix in binary and multi-class classification problems. Many classification measures are also explained in details, and the influence of balanced and imbalanced data on each metric is presented. An illustrative example is introduced to show (1) how to calculate these measures in binary and multi-class classification problems, and (2) the robustness of some measures against balanced and imbalanced data. Moreover, some graphical measures such as Receiver operating characteristics (ROC), Precision-Recall, and Detection error trade-off (DET) curves are presented with details. Additionally, in a step-by-step approach, different numerical examples are demonstrated to explain the preprocessing steps of plotting ROC, PR, and DET curves.

This research evaluated the impact of credit risk, liquidity risk, profitability, economic growth and good governance on the vulnerability of the Islamic banking system in the Association of Southeast Asian Nations (ASEAN).

The panel regression analysis was used to obtain data from five ASEAN countries that had operated Islamic banks from 2010 to 2019.

The results obtained from the vulnerability model indicated that bank liquidity risk, profitability and good governance have significant impacts on vulnerability. Conversely, credit risk and economic growth showed an insignificant effect on susceptibility. Good governance helps increase investment attractiveness for economic growth and development in Islamic banks in ASEAN.

Some of the limitations of this research include its focus on the vulnerability of Islamic banks in ASEAN countries. The average value of six indices is used as a single index per country with good governance. Therefore, further research needs to consider using all six indices of good governance as factors affecting the vulnerability of Islamic banks, such as control of corruption, government effectiveness, political stability, absence of violence, regulatory quality, the rule of law voice and accountability.

This research describes banking financial circumstances and their internal activities. Furthermore, it helps managers or banking practitioners in the proper management of finance, specifically at the vulnerability level, to aid in the early detection of crisis to enable early aversion or minimal impact.

This research is expected to assist governments in ASEAN countries to establish public policies and build good governance to increase investment interest in the Islamic banking industry.

This research is the author's first attempt at discussing the issues of bank vulnerability related to good governance faced by the Islamic banking system in ASEAN.

Starting from the theoretical mechanism of profit sharing between finance and the real economy, this paper reviews and analyzes the profitability of China's banking industry and makes a horizontal comparison with the banking industry of the United States, Japan, and Germany.

Based on the panel threshold model, it is found that there is a dual-threshold asymmetric effect between banking profit and the growth of real economy. When the net profit rate of the banking industry is lower than 0.491%, the increase in banking profitability will inhibit the growth of real economy due to profit grabbing; when the rate falls within the range of 0.491–0.801%, the increase in bank profitability is conducive to the growth of real economy.

Finance and the real economy are in the most comfortable symbiotic state; when the rate is higher than 0.801%, the continued increase in bank profitability will weaken the promotion effect of finance on the real economy, but bank profitability and the growth of real economy are still in a symbiotic state of positive promotion.

The promotion effect of China's bank profitability to the growth of real economy has shifted from the suboptimal state to the optimal range as a whole, which is attributed to the strong deleveraging and strict supervision of the Chinese government after 2016, the timely and decisive “stepping on the brakes”, pulling the financial sector back from the “illusion” caused by “self-circulated” profits and preventing it from harming the real economy.

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.