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Examines the formation of expectations, efficiency and conditional volatility in the foreign exchange market for the Greek drachma using 1987‐1998 data. Presents the statistical results in detail and considers consistency with other research. Identifies the theoretical and empirical implications of the study and suggests further research.

Explains the importance of assessing country risk to lenders and investors, outlines previous research on techniques for doing this and describes a classification method: the multi‐group hierarchical discrimination method (MHD). Applies this to 1978‐1995 data for 143 countries, subdivided into four income groups, and compares the results with those from multiple discriminant, logit and probit analyses using jackknife procedures. Finds MHD more accurate overall and for most income groups except the lower‐middle income economies. Briefly considers other applications for MHD and avenues for further research.

The purpose of this paper is to present an automatic Medical Knowledge Elicitation System (MediKES), which is designed to improve elicitation and sharing of tacit knowledge acquired by physicians. The system leverages the clinical information stored in electronic medical record systems, by representing the acquired information in a series of knowledge maps.

The system architecture of the proposed MediKES is first discussed, and then a case study on an application of the proposed system in a Hong Kong medical organization is presented to illustrate the adoption process and highlight the benefits that can be realized from deployment of the MediKES.

The results of the case study show that the proposed solution is more reliable and powerful than traditional knowledge elicitation approaches in capturing physicians' tacit knowledge, transforming it into a machine‐readable form, as well as enhancing the quality of the medical judgment made by physicians.

A prototype system has been constructed and implemented on a trial basis in a medical organization. It has proven to be of benefit to healthcare professionals through its automatic functions in representing and visualizing physicians' diagnostic decisions.

Knowledge is key to improving the quality of the medical judgment of physicians. However, researchers and practitioners are still striving for more effective ways of capturing tacit knowledge and transforming it into a machine‐readable form so as to enhance knowledge sharing. In this paper, the authors reveal that the knowledge retrieval and the visual knowledge representation functions of the proposed system are able to facilitate knowledge sharing among physicians. Thus, junior physicians can use it as a decision support tool in making better diagnostic decisions.

The purpose of this paper is to identify sustainable supply chain skill and propose a conceptual training framework for sustainable supply chain talent.

The authors have used exhaustive literature review of extant literature published in academic journals, reputable reports, trade magazines, books and monographs. The authors further consulted leading experts from reputable bodies to further finalize the sustainable supply chain skills matrix and check the content validity of the constructs of our proposed conceptual framework.

The sustainable supply chain skill matrix has been identified and a conceptual framework has been proposed. The authors further outlined the future research directions.

This is a conceptual paper based on the literature review and analysis. This offers opportunities for empirical research.

This paper will alert companies to focus on developing talents that would help to achieve sustainable supply chain.

Better talents lead to better support for sustainable supply chains.

The present study is unique in terms of scope and its contribution to theory of supply chain management and operations management and human resource management practice. The study has identified the sustainable supply chain skill matrix and proposed a conceptual training framework for sustainable supply chain talent.

Levels of 12 metals (Ca, K, Na, Mg, Cu, Fe, Mn, Zn, Cd, Cr, Pb and Ni) were estimated in 19 different imported brands of unexpired and expired canned dry milk available from local markets. The HNO₃/HClO₄‐based wet digestion method was used for the analysis of the samples by the FAAS technique under optimum analytical conditions. Of the macronutrients, Ca showed highest at 1,144 μg/g in the dry milk from Holland. In the case of micronutrients, Fe showed the maximum level at 119.15 μg/kg in the milk from UK. Cr dominated at 23.19 μg/kg compared with other heavy toxic trace elements. The following order of decreasing concentration was observed for both unexpired and expired milk: Ca > Na > K > Mg > Fe > Zn > Cr > Pb > Cu > Ni > Cd. All the trace elements were found to have 100 per cent incidence of occurrence. The expired milk samples showed enhanced levels of Fe, Zn, Cr and Pb by a factor of 1.2‐1.6 on average. The results of the metal contents were compared with those for fresh cow milk. The data were statistically evaluated to find bivariate correlation between the metals in pre‐ and post‐expiry milks.

This paper examine whether social performance moderates the linkage between financial risk and financial performance in microfinance institutions (MFIs). The study focuses on the financial self-sufficiency and long-term sustainability of MFIs.

The empirical study uses unbalanced panel data of 2,694 worldwide MFIs from 2009 to 2019. In the first step, the study inspects the impact of social performance and risk on financial performance, proxied as return on assets and operational self-sufficiency. In the second stage, moderated hierarchical regression is applied to test whether social performance moderates the relationship between risk and financial performance. Lastly, the study confirms the significant moderation effects with slope tests.

The study detects robust evidence that financial risk is negatively related to financial performance. Though social performance exhibits a weak positive link with financial performance in silos, the evidence of its moderating effects on risk is mixed and significant. Social performance indicators, such as the borrower retention rate and female representation, positively moderate the relationship between financial risk and financial performance. The study documents that social performance impacts financial performance and operational self-sufficiency through risk moderation. Thus, social performance fosters the sustainability of these institutions over the long haul.

The study is relevant to academics and theorists to consider the stakeholder approach in microfinancing. In the context of stakeholder theory, the study advances the specific social responsiveness process, namely stakeholder engagement.

The evidence that socially sensitive operations can curtail the adverse effects of credit risks on financial performance signify the required attention to social performance. For MFI managers and practitioners, the findings justify the business case for social performance. Stakeholder engagement, under the auspices of social responsiveness, acts as a risk-mitigation mechanism to eventually foster financial performance and self-sufficiency.

The study motivates MFIs to do more for their stakeholders and society by highlighting the benefits of social performance.

The study reaffirms that social performance remains at the epicenter of the MFIs' mission and is an essential risk mitigation mechanism. The study adds to the extant literature on stakeholder engagement and its effects on MFIs.

To examine, determine, investigate and compare the extent to which enterprises in Greece and Cyprus use the theoretical framework to evaluate investments which are the discouraging factors concerning the use of this framework with particular emphasis to investigate the type, size and percentage of total capital expenditures detailed cash flow estimates; cash flow estimation practices and forecasting errors experience in the businesses in Greece and Cyprus.

The investigation was conducted by the distribution of a questionnaire to adequate number of small sized companies of Greece and Cyprus. The study was based on a questionnaire that was promoted to 800 firms in Greece and 120 in Cyprus.

The results of our survey have indicated the perceived important of some financial, marketing, and production factors on the cash flow forecasting process, as borrowing and repayment of funds, sales forecast, and operating expenses. The results of our study have indicated that the majority of forecasting methods used to generate cash flow estimates is management's subjective estimates and that the majority of the Greek firms adjust capital expenditure cash flow for inflation.

This study could potentially stimulate further research on cash flow forecasting practices of firms in other countries, such as Italy, France, and other Mediterranean countries, in order to compare the results.

This study provides evidence on the forecasting practices of small and medium-sized companies of Mediterranean companies.

One of the main theories regarding the relationship between government expenditure and gross domestic product (GDP) is Wagner’s law. This law was developed in the late-19th century by Adolph Wagner (1835–1917), a prominent German economist, and depicts that an increase in government expenditure is a feature often associated with progressive states. This paper aims to examine the validity of Wagner’s law in Egypt for 1960–2018. The relationship between real government expenditure and real GDP is tested using three versions of Wagner’s law.

To test the validity of Wagner in Egypt, law time-series analysis is used. The methodology used in this paper is: unit-root tests for stationarity, Johansen cointegration approach, error-correction model and Granger causality.

The results provide strong evidence of long-term relationship between GDP and government expenditure. Moreover, the causal relationship is found to be bi-directional. Hence, this study provides support for Wagner’s law in the examined context.

It should be noted, however, that there are some limitations to this study. For instance, in this paper, the government’s size was measured through government consumption expenditure rather than government expenditure due to data availability, which does not fully capture the government size. Moreover, the data available was limited and does not fully cover the earliest stages of industrialization and urbanization for Egypt. Furthermore, although time-series analysis provides a more contextualized results and conclusions, the obtained conclusions suffer from their limited generalizability.

This paper aims to specifically make a contribution to the empirical literature for Wagner’s law, by testing the Egyptian data using time-series econometric techniques for the longest time period examined so far, which is 1960–2018.

The purpose of this paper is to put forward an innovative approach for reducing the variation between Type I and Type II errors in the context of ratio‐based modeling of corporate collapse, without compromising the accuracy of the predictive model. Its contribution to the literature lies in resolving the problematic trade‐off between predictive accuracy and variations between the two types of errors.

The methodological approach in this paper – called MCCCRA – utilizes a novel multi‐classification matrix based on a combination of correlation and regression analysis, with the former being subject to optimisation criteria. In order to ascertain its accuracy in signaling collapse, MCCCRA is empirically tested against multiple discriminant analysis (MDA).

Based on a data sample of 899 US publicly listed companies, the empirical results indicate that in addition to a high level of accuracy in signaling collapse, MCCCRA generates lower variability between Type I and Type II errors when compared to MDA.

Although correlation and regression analysis are long‐standing statistical tools, the optimisation constraints that are applied to the correlations are unique. Moreover, the multi‐classification matrix is a first in signaling collapse. By providing economic insight into more stable financial modeling, these innovations make an original contribution to the literature.

This paper seeks to examine the impact of ownership structure on firm performance and the default risk of a sample of publicly listed firms.

This paper examines the impact of ownership structure on firm performance and the default risk of a sample of 59 publicly listed firms in Jordan from 1989 to 2002.

The main findings were: ownership structure has significant effects on the accounting measure of performance return on assets (ROE); government shares are significantly negatively related to the firm's performance ROE; defaulted firms have a high concentration ownership compared with non‐defaulted firms and also high foreign ownership firms have a low incidence of default; government ownership is significantly negatively related to the firm's probability of default; both mix and concentration ownership structure data can be used to predict the probability of default as the largest five shareholders (C5) and government ownership fraction (FGO) are significantly negatively correlated with the probability of the default. These results further suggest that reducing government ownership can increase a firm's performance but will also cause some firms to go bankrupt, at least in the short term.

This paper provides useful information on the impact of ownership structure on firm performance and the default risk of a sample of publicly‐listed firms.