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This study aims to detect the impact of three personality traits on agents' sales performance. The moderating role of the unit manager's leadership style is highlighted too. MLQ-5X and Mini-IPIP questionnaires were distributed to 200 insurance sales agents in Lebanon. Using SEM, extraversion is found to be positively and significantly affecting sales performance whereas the neuroticism's impact is found to be negatively significant. Moreover, the transformational and the laissez-faire leadership styles are found to strengthen the positive relationship between extraversion and sales performance. Transactional leadership seemed to boost the negative relationship between neuroticism and sales performance. This study fills a gap in the literature and enriches it, specifically when it comes to the insurance industry in a Lebanese context.

Purpose The seepage of companies' capital accommodated by weak country-level institutions is inconducive to building sustainable businesses. Companies' performance on environmental, social and governance (ESG) issues is still a challenging question. This study aims to test the predictability of ESG on the performance of the health-care industry from a global perspective, while accounting for the country disclosure and director liability indices and performing robustness tests. Design/methodology/approach This study relies on panel data of 912 companies operating in 38 different countries for 2012–2020. This study controls for firm-level variables (leverage, size and loss), macroeconomic variables (COVID, gross domestic product and inflation) and institutional variables. Findings Findings indicate that countries with different levels of disclosure exhibit different patterns. Distinctly, the environmental pillar has a concave impact on return on assets, and the role of the disclosure index greatly manifests with the environmental pillar. Practical implications This study ponders the impact of country disclosure on sustainability practices from a global health-care perspective. Originality/value This paper is original, as it addresses the relationship between ESG performance and financial performance while accounting for the impact of institutional factors such as the business disclosure and director liability indices.

Purpose This study models the effects of the COVID-19 pandemic on the performance of the private health-care sector in the Middle East and North Africa (MENA) countries. This paper aims to address the economic, societal and sustainability of the health-care sector. Design/methodology/approach Data were collected from Bloomberg and the sample consists of 534 firm-year observations from 55 firms listed over 2010–2020. The authors apply panel data and control for the country and governance effects. Findings The authors found heterogeneous results regarding the three sub-sectors. The pandemic has a negative effect on the accounting and market performances of the “Pharmaceutical companies” and an insignificant impact on “Healthcare Management and Facilities Services.” Moreover, the impact of COVID-19 on health-care firms’ performance depends on the country’s economic classification and the degree of regulatory and governance frameworks. Research limitations/implications Further studies may consider a larger sample and other regions. It is recommended to address the health-care sector's challenges to invest in new technologies such as “digital twin” and predictive and personalized medicine. It is worth testing model development theory and its effects on speeding up and designing models to ensure the proper functioning and developing mathematics to determine uncertainties in patient data and model predictions. Originality/value To the best of the authors’ knowledge, this paper is novel as it is unique in modeling the impact of COVID-19 on the health-care public companies in the MENA region. The findings pinpoint firms’ and countries’ heterogeneous impacts on financial and market performances.

PurposeLebanon has faced one of the most severe financial and economic crises since the end of 2019. The practices of the Lebanese banks are blamed for dangerously exposing economic agents and precipitating the current financial collapse. This paper examines the patterns of manipulation of the 10 biggest banks before and after implementing the financial engineering mechanism.Design/methodology/approachThe authors apply Benford law for the first and second positions of the reports of condition and income and four out of the six aspects of the CAMELS rating system (Capital Adequacy, Assets Quality, Management expertise, Earnings Strength, Liquidity and Sensitivity to the market) by excluding Management and Sensitivity. The deviations from BL frequencies are tested using Z-statistic and Chi-square tests.FindingsBanks seem to have manipulated their Capital Adequacy, Liquidity and Assets Quality in the pre-financial engineering and considerably in the post-financial engineering periods. Fraudulent manipulations in the banking sector can distort depositors, shareholders and regulating authorities.Research limitations/implicationsThis study has many implications for governmental authorities, commercial banks, depositors, businesses, accounting and auditing firms, and policymakers. The Lebanese government needs to implement corrective fiscal and monetary policies and apply amendments to the bank secrecy and capital control law. The central bank should revamp its organizational structure, improve its disclosure practices and significantly reduce its ties to the government and the political elite.Practical implicationsThe study findings suggest that the central bank should revamp its organizational structure, improve its disclosure practices and significantly reduce its ties to the government and the political elite.Originality/valueThe study is the first to examine the patterns of fraudulent manipulation in the Lebanese banking industry using Benford Law (BL).

Purpose As reporting environmental, social and governance (ESG) information is not yet mandatory in all countries, it is intriguing to understand ESG’s underlying driving mechanisms. This study aims to investigate ESG determinants in the banking sector of the Middle East and North Africa countries. Design/methodology/approach The authors gather data for 38 listed banks for the period 2011–2019. The data used is threefold as follows: data related to ESG; firm-level; and country-level data. While ESG and firm’s level data are taken from Refinitiv, country-level data are extracted from the World Bank. Using panel regression, the authors test the effect of firm- and country-specific variables on the overall ESG score and its pillars. Findings Results indicate that banks’ ESG scores are negatively affected by performance and positively affected by size. The level of economic development exerts a negative impact on the environmental pillar while the social development exerts a positive impact on ESG and governance pillar. Corruption is the only country-level that gathers a homogenous effect on ESG scores. Finally, the three pillars follow heterogeneous patterns. Originality/value This study extends the scope of previous studies by introducing new country-level independent variables to contribute to the understanding of ESG antecedents.

PurposeThis study investigates the impact of green supply chain management (GSCM) practices on environmental performance in firms operating in the discretionary sector in the G20 countries. The sample covers 749 firms for the period 2010–2020.Design/methodology/approachThis study combines qualitative and quantitative data to examine the impact of the implementation of GSCM on accounting performance measured by the operating margin (OM) and return on assets (ROA). The authors also moderate the effects of Six Sigma and quality management (QM) and ISO 9000 and control for firm variables and COVID 19.FindingsUsing a panel data regression and structural equation modeling (SEM), results indicate that discretionary firms with internal solid GSCM practices combined with external environmental monitoring of suppliers are likely to outperform their peers in environmental issues. Using hierarchical regression, results indicate that both ISO 9000 and S&QM have moderating effects at some level of performance. Furthermore, environmental performance is positively correlated with accounting performance. This study contributes to the literature by addressing the impact of GSCM and the importance of reinforcing green and social regulations to protect the planet.Originality/valueThe paper is one of the first to measure GSCM triple components and account for COVID-19 in the context of discretionary companies and G20 countries. It highlights the impact of green initiatives to cope with major disruptions and decrease pollution and environmental disasters.

Purpose The credit crunch of 2008 and recent COVID-19 influences underscored the importance of liquidity and credit risk management in businesses and financial institutions. The purpose of this study is to investigate the impact of liquidity risk and credit risk management on accounting and market performances of banks operating in the Middle East and North Africa (MENA) region. Design/methodology/approach This study uses a panel data regression analysis on a sample of 51 listed commercial banks operating in 10 MENA countries during the period 2010–2018. Findings The results show that credit risk management does not affect the accounting performance of banks, while it has a non-linear, convex relationship with market performance. Surprisingly, liquidity risk management is not a significant driver for either performance measure in studied banks. However, when a bank combines credit risk management with liquidity risk management efforts, liquidity risk management actions return significant results on both performances, illustrated by an inverted U-shaped relationship. In addition, this study examines the joint impact of both risks on bank performance. This study reveals that accounting and market performances are differently affected by joint risk management efforts. Their impact depends on the combination of risk management ratios upon which banks choose to focus their efforts. Practical implications The findings help bankers and regulators further consider non-linearities and offer them new tools for managing the impact of credit and liquidity risk interactions towards achieving more financial stability. Originality/value These results contribute to traditional banking in offering bankers and regulators new tools for managing the impact of credit and liquidity risk interactions on bank performance.

In the rise of digital transformation and big data, accounting and auditing professions are required to adopt advanced techniques that help detect irregularities and frauds. This chapter collects 1,112 documents from Scopus database published in 288 sources over the period 2008-2021. A bibliometric analysis is used to depict trends, and applicable methodologies are adopted to build a comprehensible base that will serve to instill a new fraud detection model. More specifically, RStudio through “biblioshiny package”, VOSviewer, and Excel are the tools embraced to analyze the dataset information. The chapter explores the literature growth over time and addresses key aspects of the literature, such as most relevant documents, authors, countries, citation analysis. This chapter applies a network and content analysis using the bibliographical coupling, trend analysis, word cloud, and co-occurrence analysis. The theoretical model helps auditors, forensic accountants, top managements, analysts, and policy makers predict potential anomalies and misstatements.

Purpose This paper provides a state-of-the-art review of the financial development in the Middle East and Central Asia (MECA) and examines its impact on its economic growth. Design/methodology/approach The authors use a Panel Data Regression Analysis on a sample of 21 countries in MECA for the period 2008–2018. Findings Using the financial development indices and subindices retrieved from IMF, the study finds that the whole region has a below average index compared to other developing regions. However, this hides a great deal of variation across MECA countries. Surprisingly, financial development does not necessarily contribute to economic growth. It seems that some developing countries are still not predisposed to benefit from financial development due to several obstacles. Practical implications The authors recommend policymakers and regulators in MECA to promote financial stability and keep inflation in check so that economic agents can reap the fruits of financial development and foster economic growth. Policymakers should also stimulate competition in the financial sector, build skillful human capital, attract foreign direct investments, strengthen supervision and forensic audit and more importantly reinforce the independence of central banks. Originality/value The authors mitigate the shortcomings of single indicators as proxies for financial development by using the IMF Financial Development index that captures the depth, access and efficiency of both financial institutions and financial markets. The authors employ lower-middle-, upper-middle and high-income country groups to test the magnitude of income level on the relationship between financial development and economic growth.

The Journal of Information and Knowledge Management (JIKM) published its first issue in 2002 and celebrated its 19th birthday in 2020. This study aims to assess JIKM performance over its lifetime between 2002 and 2020 by extracting data from the Scopus database and using a combined approach of bibliometric and content analysis. More specifically, we evaluate JIKM’s productivity and stature, discuss its performance compared to other journals, and identify key contributing (authors, institutions, and countries), citation pattern, and conceptual structure. The results highlight JIKM’s growing presence, which is reflected in the dual rise of publication activity and accumulated citation. JIKM becomes one of the preeminent journals in the area of knowledge management, with a broad range of scientific actors’ contributions (authors, institutions and countries) from all over the world. Furthermore, using a bibliographic coupling, keywords’ analysis, and co-authorship analysis, we analyse JIKM’s content and identify the most frequent themes discussed. The analysis reveals that JIKM has expanded its scope from knowledge management to a new array of emerging technologies’ topics such as artificial intelligence and data mining. Graphical visualization of similarities (VOSviewer and Rstudio) shows that the major themes published are clustered into four groups, mainly (i) sustainable knowledge, (ii) emerging technologies, (iii) information management, and (iv) organization culture and knowledge sharing.

This paper analyzes the relationship between change in capital and change in risk for a sample of 23 Lebanese banks between 2009 and 2014. Using the simultaneous equations model, our evidence reveals that banks determine their capital and risk levels simultaneously, with a negative relationship. While banks adjust their capital rapidly, they adjust their risk slowly. Furthermore, undercapitalized banks adjust their capital levels more rapidly than well-capitalized banks, and they increase their capital when they decrease their risk. However, there is no conclusive evidence regarding the role of regulatory pressure in driving risk-taking behavior. Finally, there are no major differences in the relationships between capital and risk regardless of whether banks are listed or not.

Given the unsettled ESG-CFP (Environmental, Social, Governance-Corporate Financial Performance) relationship and the scarcity of research covering emerging markets firms and the impact of each of the ESG pillars on CFP while considering the industry sector categories, this paper is pioneer in investigating this relationship for 108 East Asian listed firms operating in the Industrials sector for the period extending from 2011 to 2017. The overall ESG scores together with their components are used to study their impact on CFP while considering accounting (Return on Assets (ROA) and Return on Equity (ROE)), and market measures (Stock Return (RET) and Price-to-Book ratio (PB)). We used panel corrected standard errors to address contemporaneous cross-correlations related to the panel cross-sections. Our findings showed that the ESG-CFP relationship depends on the ESG pillars, the type of CFP measures, and the industry nature. No relationship was detected between ESG and CFP when proxied by accounting measures while a concave relationship with Stock Return and a convex relationship with Price-to-Book ratio were revealed. When ESG pillars were considered separately, a convex relationship was obtained between Environmental and accounting performances and between Governance and Price-to-Book ratio while a concave relationship was depicted between Social and accounting performances. At the industry level, ESG negatively impacted the market performance in the Transportation industry compared to no impact in the Capital Goods industry. Consequently, ESG investment decisions in East Asian firms must be well calibrated and planned out to avoid undesired financial outcomes, while a shift in the mindset of managers toward a better ESG development is necessary to attain short-term gains and sustainable fiscal and social advantages.

Opaque markets suffer from asymmetry of information and inaccessibility to financial data. SMEs operating in such markets play an important role and substantially contribute to their economy. Evaluating SMEs financial performance for such markets remains a hard task and hence such sector is completely marginalized. This paper attempts to proxy the financial performance by gathering a bundle of qualitative traits that play a mediating role towards financial performance. We support our study by identifying three specific areas that best describe SMEs internal capabilities and environmental conditions. We measure a score, validate it and use it to proxy SMEs financial performance in Lebanon. We find a positive relationship between the score and return on investment (ROI) and return on assets (ROA), which support our hypotheses.

This paper analyzes the volatility dynamics in the financial markets of the (three) most powerful countries from a military perspective, namely, the U.S., Russia, and China, during the period 2015&ndash, 2018 that corresponds to their intervention in the Syrian war. As far as we know, there is no literature studying this topic during such an important distress period, which has had very serious economic, social, and humanitarian consequences. The Generalized Autoregressive Conditional Heteroscedasticity (GARCH (1, 1)) model yielded the best volatility results for the in-sample period. The weighted historical simulation produced an accurate value at risk (VaR) for a period of one month at the three considered confidence levels. For the out-of-sample period, the Monte Carlo simulation method, based on student t-copula and peaks-over-threshold (POT) extreme value theory (EVT) under the Gaussian kernel and the generalized Pareto (GP) distribution, overstated the risk for the three countries. The comparison of the POT-EVT VaR of the three countries to a portfolio of stock indices pertaining to non-military countries, namely Finland, Sweden, and Ecuador, for the same out-of-sample period, revealed that the intervention in the Syrian war may be one of the pertinent reasons that significantly affected the volatility of the stock markets of the three most powerful military countries. This paper is of great interest for policy makers, central bank leaders, participants involved in these markets, and all practitioners given the economic and financial consequences derived from such dynamics.

This paper examines the behavior of Bitcoin and Ripple compared to the three fiat currencies, EURUSD, GBPUSD and CNYUSD, by comparing their volatility and VaR during the period extending from March 01, 2016 to February 28, 2019. EWMA, GARCH (1, 1), GARCH (p, q) and EGARCH (1, 1) were used to forecast volatilities. EWMA model outperformed the rest of the models for all of the selected fiat and cryptocurrencies during the in-sample period and for EURUSD, GBPUSD and Bitcoin during the out-of-sample period. GARCH (p, q) was the optimal model for the CNYUSD and Ripple in the out-of-sample period. Bitcoin and Ripple exhibit an asymmetry in their volatility which is significantly higher than all the volatilities of the studied currencies. When estimated volatilities were compared to the implied volatility, the GARCH (1, 1), GARCH (6, 6) and EWMA were the optimal models for the EURUSD, CNYUSD and GBPUSD, respectively for the in-sample period. VaR results were accepted for the EURUSD, GBPUSD and Bitcoin at all confidence levels. For the CNYUSD, VaR measures underestimated the risk at the 99% confidence level unlike Ripple’s VaR that was accepted at the 90% and 99% confidence levels. Our results suggest that Bitcoin and generally the cryptocurrencies market cannot act as alternatives to fiat currencies at the moment.

This study investigates the relationship between the level of sustainability reporting and firm's performance (operational, financial and market) in the top worldwide 20 smart cities. Using data culled from 3536 observations from 20 different smart cities for ten years (2008–2017), an independent variable derived from ESG score are regressed against dependent manufacture performance indicator variables [Return on Assets (ROA), Return on Equity (ROE) and Tobin's Q (TQ)]. Two types of control variables complete the regression analysis in this study: firm-specific and macroeconomic. The findings elicited from the empirical results demonstrate that there is a positive significant relationship between ESG and operational performance (ROA), financial performance (ROE). However, there is a negative significant relationship between ESG and market performance (TQ). The model in this study presents a valuable analytical framework for exploring sustainability reporting as driver of performance in firms in different smart cities.

This chapter examines whether students’ perceptions of learning, attitudes, and performance are affected by the use of multimedia technology. Both traditional and multimedia methodologies were used in the financial accounting II course offered at one of the leading universities in Lebanon, using data collected from a sample of 110 students. In order to eliminate faculty-specific characteristics, the same professor taught all sections, thereby minimizing the effect different instructors might have had on student evaluations. Results indicate that students perceived the use of multimedia, specifically PowerPoint (PPT) lectures, as being more entertaining and organized than the traditional method; however, the latter methodology demonstrated more efficiency in terms of explaining theories, enhancing problem-solving abilities, and allowing for greater interaction. The two methodologies, however, did not demonstrate a significant statistical difference in terms of student learning and comprehension. Despite the positive student perception of PPT lectures, results suggest that the systematic approach of traditional methodologies exceeds PPT in emphasizing course materials and enhancing problem-solving abilities. As measured by their final grade, PPT methodologies affected student performance negatively, especially for below-average business students.

This research aims at investigating the factors determining the dividend payout policy in the Lebanese banks listed on the Beirut Stock Exchange. This study considers the impact of seven variables, namely, profitability, liquidity, leverage, firm size, growth, firm risk and previous year’s dividend payout on the dividend payout ratios by using an unbalanced panel dataset of listed banks between the years of 2005 and 2011. Two models were tested using the OLS and the dynamic panel regressions. Empirical results show that the dividend payout policies are positively affected by the firm size, risk and previous year’s dividends, but are negatively affected by the opportunity growth and profitability. The results obtained might indicate that firms pay dividends with the intention of reducing the agency conflicts. Furthermore, managers take into consideration the stability of dividends while determining the dividend policy. Moreover, the results suggest that the Lebanese listed firms prefer to invest their earnings to grow rather than to pay more dividends.

Given the fact that the government debt is financed by commercial banks in Lebanon, there is a need to uncover and study the determinants of commercial bank deposits. This paper investigates empirically the main determinants of non-residents deposits in Lebanese commercial banks using monthly time series data covering January 2002 to January 2013 (131 observations). The necessary tests were performed so that the ordinary least square regression can be safely applied. The estimated model had non-resident deposits as the dependent variables, and the explanatory variables as internal factors, external variables, and bank specific variables. The dependent variable was measured in three ways: in the local currency, in foreign currency, and total non-resident deposits. The results show that non-residents’ deposits are shaped differently between domestic and foreign currency. For instance, bank assets, interest rates, and some adverse political situations affect non-resident deposits in all its measures. However, while total non-resident deposits and foreign non-residents deposits are roughly affected by the same factors, local resident deposits seem to be affected by other factors; this fact is attributed to the fact that local currency deposits account for a small percentage of total non-resident deposits. Based on the results, several policy implications were drawn that aim at increasing non-resident deposits. First, the stability of macroeconomic system should be maintained. Second, the government should maintain healthy rate differentials to support the deposit growth. Lastly, Lebanese banks should search for internalization to diversify their losses.

This paper applies the multi-index model to explore the sensitivity of the stock return of European automotive companies to some macroeconomic variables. The analysis involves the monthly returns of nine European companies operating in the automotive industry from January 2003 to April 2012 using 15 macroeconomic variables and the market index represented by S&P 350. The study finds that the S&P 350 positively affects stock returns, supporting the single index model. Furthermore, exchange rate, exports and platinum positively affect stock return, while aluminium and unemployment rate negatively affect stock return. The results suggest that a multi-index model using selected macroeconomics variables provides additional power in explaining the variability of the European stock returns in the automobile industry over a single index model using the market index alone.