Pub Date : 2023-07-12DOI: 10.1108/ejmbe-04-2022-0099
P. Akorsu
PurposeCredit Default Swap (CDS) trading alters equilibrium interactive monitoring of external corporate monitors due to a possible change in private lenders' incentive to monitor client firms. This study explores how audit fees change in response to CDS trade initiation on client firms and how this effect is moderated by investor protection.Design/methodology/approachWith 6,052 cross-country firm observations, the author conducts estimations in the systems dynamic general methods of moments framework.FindingsThe author documents that audit fees rise on average after CDS trade initiations with and/or without investor protection. Meanwhile, change in auditors' risk perception result in increased audit costs when CDS trade initiation and investor protection interact. The effect of CDS trading on audit fees remain after controlling for firm, audit, and auditor features are robust to different proxies of audit cost.Practical implicationsThe need for firms in high investor protection jurisdictions to initiate CDS trade to implement policies in order to maximize their gains from investor protection activities to lessen the overall impact of any increased audit cost that may arise. Furthermore, CDS regulation may be strategically targeted to lessen the effect of increased audit costs on firms after initiation. This would ensure that the resulting increase in audit cost may not materially impact the cash or profitability position of such firms.Originality/valueThis study is distinct from previous ones by focusing on variation in private lenders incentive to monitor after CDS trade initiation after controlling for possible monitoring by short-term creditors. Given that monitoring is not costless for private lenders and CDS trading on their borrowers causes a change in this cost structure, the author documents how auditors react to such changes in incentive to monitor.
{"title":"Credit default swaps, investor protection, and audit cost: international evidence","authors":"P. Akorsu","doi":"10.1108/ejmbe-04-2022-0099","DOIUrl":"https://doi.org/10.1108/ejmbe-04-2022-0099","url":null,"abstract":"PurposeCredit Default Swap (CDS) trading alters equilibrium interactive monitoring of external corporate monitors due to a possible change in private lenders' incentive to monitor client firms. This study explores how audit fees change in response to CDS trade initiation on client firms and how this effect is moderated by investor protection.Design/methodology/approachWith 6,052 cross-country firm observations, the author conducts estimations in the systems dynamic general methods of moments framework.FindingsThe author documents that audit fees rise on average after CDS trade initiations with and/or without investor protection. Meanwhile, change in auditors' risk perception result in increased audit costs when CDS trade initiation and investor protection interact. The effect of CDS trading on audit fees remain after controlling for firm, audit, and auditor features are robust to different proxies of audit cost.Practical implicationsThe need for firms in high investor protection jurisdictions to initiate CDS trade to implement policies in order to maximize their gains from investor protection activities to lessen the overall impact of any increased audit cost that may arise. Furthermore, CDS regulation may be strategically targeted to lessen the effect of increased audit costs on firms after initiation. This would ensure that the resulting increase in audit cost may not materially impact the cash or profitability position of such firms.Originality/valueThis study is distinct from previous ones by focusing on variation in private lenders incentive to monitor after CDS trade initiation after controlling for possible monitoring by short-term creditors. Given that monitoring is not costless for private lenders and CDS trading on their borrowers causes a change in this cost structure, the author documents how auditors react to such changes in incentive to monitor.","PeriodicalId":45118,"journal":{"name":"European Journal of Management and Business Economics","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43207611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-11DOI: 10.1108/ejmbe-10-2022-0320
C. Nicolás, Angélica Urrutia, Gonzalo González
PurposeExplore the use of Gender-Fair Language (GFL) by influencers on Instagram.Design/methodology/approachThe clustering methodology. A digital Bag-of-Words (BoW) Method called GFL Clustering BoW Methodology to identify whether an inclusive marketing (IM) strategy can be used. Thus, this research has a methodological and practical contribution to increasing the number of marketing technology tools.FindingsThis study is original as it proposes an inclusive digital marketing strategy and contributes with methods associated with digital transfers in order to improve marketing strategies, tactics and operations for inclusive content with a data integrity approach.Research limitations/implicationsDue to the limitations of the application programming interface (API) of the social network Instagram, a limited number of text data were used, which allowed for retrieving the last 12 publications of each studied profile. In addition, it should be considered that this study only includes the Spanish language and is applied to a sample of influencers from Chile.Practical implicationsThe practical contribution of this study will lead to a key finding for the definition of communication strategies in both public and private organizations.Originality/valueThe originality of this work lies in its attractive implications for nonprofit and for-profit organizations, government bodies and private enterprises in the measurement of the success of campaigns with an IM communicational strategy and to incorporate inclusive and non-sexist content for their consumers so as to contribute to society.
{"title":"Exploring the use of gender-fair language by influencers","authors":"C. Nicolás, Angélica Urrutia, Gonzalo González","doi":"10.1108/ejmbe-10-2022-0320","DOIUrl":"https://doi.org/10.1108/ejmbe-10-2022-0320","url":null,"abstract":"PurposeExplore the use of Gender-Fair Language (GFL) by influencers on Instagram.Design/methodology/approachThe clustering methodology. A digital Bag-of-Words (BoW) Method called GFL Clustering BoW Methodology to identify whether an inclusive marketing (IM) strategy can be used. Thus, this research has a methodological and practical contribution to increasing the number of marketing technology tools.FindingsThis study is original as it proposes an inclusive digital marketing strategy and contributes with methods associated with digital transfers in order to improve marketing strategies, tactics and operations for inclusive content with a data integrity approach.Research limitations/implicationsDue to the limitations of the application programming interface (API) of the social network Instagram, a limited number of text data were used, which allowed for retrieving the last 12 publications of each studied profile. In addition, it should be considered that this study only includes the Spanish language and is applied to a sample of influencers from Chile.Practical implicationsThe practical contribution of this study will lead to a key finding for the definition of communication strategies in both public and private organizations.Originality/valueThe originality of this work lies in its attractive implications for nonprofit and for-profit organizations, government bodies and private enterprises in the measurement of the success of campaigns with an IM communicational strategy and to incorporate inclusive and non-sexist content for their consumers so as to contribute to society.","PeriodicalId":45118,"journal":{"name":"European Journal of Management and Business Economics","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48151627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-04DOI: 10.1108/ejmbe-03-2023-0085
D. Marino, Jaime Gil Lafuente, D. Tebala
PurposeThe objective of this paper is to analyze the relationship between innovation and the development of artificial intelligence (AI) and digital technologies in Europe. The use of digital technologies among European companies is studied through a composite index, while the relationship between innovation and AI is studied through a log-linear regression model. The results of the model have made possible to develop interesting indications for economic and industrial policy.Design/methodology/approachThe use of digital technologies among European companies is studied through a composite index of AI and information technology (ICT) (using the Fair and Sustainable Welfare methodology) with the aim of measuring territorial gaps and to know which European countries are more or less inclined to its use, while the relationship between innovation and AI is studied through a log-linear regression model.FindingsIn the paper, two different methodologies were used to analyze the relationship between innovation and the development of digital technologies in Europe. The synthetic indicator made possible to develop a taxonomy between the different countries, the log-linear model made possible to identify and explain the determinants of innovation.Originality/valueThe description of the biunivocal relationship between innovation and AI is a topical and relevant issue that is treated in the paper in an original way using a synthetic indicator and a log-linear model.
{"title":"Innovations and development of artificial intelligence in Europe: some empirical evidences","authors":"D. Marino, Jaime Gil Lafuente, D. Tebala","doi":"10.1108/ejmbe-03-2023-0085","DOIUrl":"https://doi.org/10.1108/ejmbe-03-2023-0085","url":null,"abstract":"PurposeThe objective of this paper is to analyze the relationship between innovation and the development of artificial intelligence (AI) and digital technologies in Europe. The use of digital technologies among European companies is studied through a composite index, while the relationship between innovation and AI is studied through a log-linear regression model. The results of the model have made possible to develop interesting indications for economic and industrial policy.Design/methodology/approachThe use of digital technologies among European companies is studied through a composite index of AI and information technology (ICT) (using the Fair and Sustainable Welfare methodology) with the aim of measuring territorial gaps and to know which European countries are more or less inclined to its use, while the relationship between innovation and AI is studied through a log-linear regression model.FindingsIn the paper, two different methodologies were used to analyze the relationship between innovation and the development of digital technologies in Europe. The synthetic indicator made possible to develop a taxonomy between the different countries, the log-linear model made possible to identify and explain the determinants of innovation.Originality/valueThe description of the biunivocal relationship between innovation and AI is a topical and relevant issue that is treated in the paper in an original way using a synthetic indicator and a log-linear model.","PeriodicalId":45118,"journal":{"name":"European Journal of Management and Business Economics","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45501841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-29DOI: 10.1108/ejmbe-02-2022-0041
Margarida Seara, Teresa Proença, Marisa R. Ferreira
PurposeThe purpose of this study is to understand the impact that Corporate Social Responsibility (CSR) practices have on the perceived attractiveness of companies in the eyes of their employees and potential candidates. Moreover, this study assesses the mediation role that Extrinsic (EA) and Intrinsic Attributions (IA) about Corporate Volunteering (CV) have on this relationship.Design/methodology/approachThree hundred and five responses were collected in an online questionnaire and a Structural Equation Modelling model was designed to explain the proposed relationships of the variables under study.FindingsThe authors found that the IA that employees/candidates make about CV programs have a direct and positive impact on the company’s attractiveness; it was not possible to conclude the same about EA.Originality/valueUnlike studies already existing in the area of corporate attractiveness that focus on the perspective of companies and customers, with a high focus on the organizational implementation of CSR and organizational benefits, this study has adopted a different perspective that focuses on the opinion of company employees, as well as the perspective of possible candidates. By not limiting participation to anyone, it covers a wide range of participants, allowing a broader knowledge of the labor market.
{"title":"Do corporate social responsibility practices have an impact on employer attractiveness – an approach to corporate volunteering programs","authors":"Margarida Seara, Teresa Proença, Marisa R. Ferreira","doi":"10.1108/ejmbe-02-2022-0041","DOIUrl":"https://doi.org/10.1108/ejmbe-02-2022-0041","url":null,"abstract":"PurposeThe purpose of this study is to understand the impact that Corporate Social Responsibility (CSR) practices have on the perceived attractiveness of companies in the eyes of their employees and potential candidates. Moreover, this study assesses the mediation role that Extrinsic (EA) and Intrinsic Attributions (IA) about Corporate Volunteering (CV) have on this relationship.Design/methodology/approachThree hundred and five responses were collected in an online questionnaire and a Structural Equation Modelling model was designed to explain the proposed relationships of the variables under study.FindingsThe authors found that the IA that employees/candidates make about CV programs have a direct and positive impact on the company’s attractiveness; it was not possible to conclude the same about EA.Originality/valueUnlike studies already existing in the area of corporate attractiveness that focus on the perspective of companies and customers, with a high focus on the organizational implementation of CSR and organizational benefits, this study has adopted a different perspective that focuses on the opinion of company employees, as well as the perspective of possible candidates. By not limiting participation to anyone, it covers a wide range of participants, allowing a broader knowledge of the labor market.","PeriodicalId":45118,"journal":{"name":"European Journal of Management and Business Economics","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42011979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-26DOI: 10.1108/ejmbe-08-2022-0255
İpek Akad, Çağaçan Değer
PurposeThis study aims to explain the effect of research and development (R&D) incentives on economic growth, focusing on the case of Türkiye. A one-sector endogenous growth model has been constructed. The model includes three actors: firm, consumer and government. The consumer derives utility from consumption, supplies human capital and engages in saving. The representative firm invests in R&D to maximize the current value of profit flows by choosing how much input it will use and how much R&D it will undertake. The public sector provides incentives for labor and capital used in R&D production. R&D has been defined as a function that endogenously increases total factor productivity (TFP).Design/methodology/approachIn line with the stated purpose, this study presents a dynamic general equilibrium model. Then, this study calibrates the model parameters with Türkiye's data.FindingsThe results imply that incentives for R&D personnel instead of physical capital have a stronger impact on economic growth.Practical implicationsThe findings of this study point to an important conclusion on how to distribute R&D incentives across the two main factors in R&D production, labor and capital. Incentives given to R&D personnel are more effective in Türkiye.Originality/valueThis study shows that the R&D incentives provided by the public sector can be important in emerging countries where many firms have just started their R&D activities. In this study, the authors worked on Türkiye as an emerging country. This study discusses policies on how the R&D incentives will be more effective on economic growth in Türkiye. This study considers that these policies may apply to all emerging countries, due to similar R&D activities in countries that cannot export technology and mostly import technology.
{"title":"Does the distribution of R&D incentive among production factors matter? A dynamic general equilibrium model for Türkiye","authors":"İpek Akad, Çağaçan Değer","doi":"10.1108/ejmbe-08-2022-0255","DOIUrl":"https://doi.org/10.1108/ejmbe-08-2022-0255","url":null,"abstract":"PurposeThis study aims to explain the effect of research and development (R&D) incentives on economic growth, focusing on the case of Türkiye. A one-sector endogenous growth model has been constructed. The model includes three actors: firm, consumer and government. The consumer derives utility from consumption, supplies human capital and engages in saving. The representative firm invests in R&D to maximize the current value of profit flows by choosing how much input it will use and how much R&D it will undertake. The public sector provides incentives for labor and capital used in R&D production. R&D has been defined as a function that endogenously increases total factor productivity (TFP).Design/methodology/approachIn line with the stated purpose, this study presents a dynamic general equilibrium model. Then, this study calibrates the model parameters with Türkiye's data.FindingsThe results imply that incentives for R&D personnel instead of physical capital have a stronger impact on economic growth.Practical implicationsThe findings of this study point to an important conclusion on how to distribute R&D incentives across the two main factors in R&D production, labor and capital. Incentives given to R&D personnel are more effective in Türkiye.Originality/valueThis study shows that the R&D incentives provided by the public sector can be important in emerging countries where many firms have just started their R&D activities. In this study, the authors worked on Türkiye as an emerging country. This study discusses policies on how the R&D incentives will be more effective on economic growth in Türkiye. This study considers that these policies may apply to all emerging countries, due to similar R&D activities in countries that cannot export technology and mostly import technology.","PeriodicalId":45118,"journal":{"name":"European Journal of Management and Business Economics","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44878226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-22DOI: 10.1108/ejmbe-06-2022-0176
Ignacio Manuel Luque Raya, Pablo Luque Raya
PurposeHaving defined liquidity, the aim is to assess the predictive capacity of its representative variables, so that economic fluctuations may be better understood.Design/methodology/approachConceptual variables that are representative of liquidity will be used to formulate the predictions. The results of various machine learning models will be compared, leading to some reflections on the predictive value of the liquidity variables, with a view to defining their selection.FindingsThe predictive capacity of the model was also found to vary depending on the source of the liquidity, in so far as the data on liquidity within the private sector contributed more than the data on public sector liquidity to the prediction of economic fluctuations. International liquidity was seen as a more diffuse concept, and the standardization of its definition could be the focus of future studies. A benchmarking process was also performed when applying the state-of-the-art machine learning models.Originality/valueBetter understanding of these variables might help us toward a deeper understanding of the operation of financial markets. Liquidity, one of the key financial market variables, is neither well-defined nor standardized in the existing literature, which calls for further study. Hence, the novelty of an applied study employing modern data science techniques can provide a fresh perspective on financial markets.
{"title":"Machine learning algorithms applied to the estimation of liquidity: the 10-year United States treasury bond","authors":"Ignacio Manuel Luque Raya, Pablo Luque Raya","doi":"10.1108/ejmbe-06-2022-0176","DOIUrl":"https://doi.org/10.1108/ejmbe-06-2022-0176","url":null,"abstract":"PurposeHaving defined liquidity, the aim is to assess the predictive capacity of its representative variables, so that economic fluctuations may be better understood.Design/methodology/approachConceptual variables that are representative of liquidity will be used to formulate the predictions. The results of various machine learning models will be compared, leading to some reflections on the predictive value of the liquidity variables, with a view to defining their selection.FindingsThe predictive capacity of the model was also found to vary depending on the source of the liquidity, in so far as the data on liquidity within the private sector contributed more than the data on public sector liquidity to the prediction of economic fluctuations. International liquidity was seen as a more diffuse concept, and the standardization of its definition could be the focus of future studies. A benchmarking process was also performed when applying the state-of-the-art machine learning models.Originality/valueBetter understanding of these variables might help us toward a deeper understanding of the operation of financial markets. Liquidity, one of the key financial market variables, is neither well-defined nor standardized in the existing literature, which calls for further study. Hence, the novelty of an applied study employing modern data science techniques can provide a fresh perspective on financial markets.","PeriodicalId":45118,"journal":{"name":"European Journal of Management and Business Economics","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46844732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-16DOI: 10.1108/ejmbe-06-2022-0187
Daniel Espinosa Sáez, E. Delgado-Ballester, J. Munuera-Alemán
Purpose The sharing economy (SE) is significantly affecting traditional companies, which have felt a need to adapt their business model. The aim of this study is to identify the different types of adaptation developed by companies within a SE context, and to examine how they relate to their characteristics.Design/methodology/approach A content analysis involving 149 real-world adaptation cases was carried out, after which a Kruskal–Wallis test and a multiple correspondence analysis were used to explore the relationships between the types of adaptation identified, the business characteristics and the strategic decisions taken for these adaptations.Findings Through the analyses proposed in the study, the main conclusions suggest that the way companies adapt to SE is related to business characteristics and the strategic decisions taken for these actions, demonstrating throughout the article what types of adaptations are made depending on variables such as sector of activity or business orientation.Originality/value This study is the first to examine the variables affecting the decisions among traditional companies in response to the SE. In addition, this work explores the SE from the business point of view, shedding light on the participation in SE by traditional companies.
{"title":"Innovation in business model as a response to the sharing economy","authors":"Daniel Espinosa Sáez, E. Delgado-Ballester, J. Munuera-Alemán","doi":"10.1108/ejmbe-06-2022-0187","DOIUrl":"https://doi.org/10.1108/ejmbe-06-2022-0187","url":null,"abstract":"Purpose The sharing economy (SE) is significantly affecting traditional companies, which have felt a need to adapt their business model. The aim of this study is to identify the different types of adaptation developed by companies within a SE context, and to examine how they relate to their characteristics.Design/methodology/approach A content analysis involving 149 real-world adaptation cases was carried out, after which a Kruskal–Wallis test and a multiple correspondence analysis were used to explore the relationships between the types of adaptation identified, the business characteristics and the strategic decisions taken for these adaptations.Findings Through the analyses proposed in the study, the main conclusions suggest that the way companies adapt to SE is related to business characteristics and the strategic decisions taken for these actions, demonstrating throughout the article what types of adaptations are made depending on variables such as sector of activity or business orientation.Originality/value This study is the first to examine the variables affecting the decisions among traditional companies in response to the SE. In addition, this work explores the SE from the business point of view, shedding light on the participation in SE by traditional companies.","PeriodicalId":45118,"journal":{"name":"European Journal of Management and Business Economics","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44287658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-15DOI: 10.1108/ejmbe-10-2022-0332
Marwa Fersi, M. Boujelbene, Feten Arous
PurposeThe purpose of this paper is to evaluate the performance of Microfinance Institutions (MFIs) offering FinTech services. This study contributes to the existing literature on microfinance digitalization, financial inclusion and sustainable development. The study also takes into consideration a behavioral perspective through the efficiency evaluation process of MFIs offering FinTech services.Design/methodology/approachThe following study employs the Stochastic Frontier Analysis approach to estimate the operational and social efficiency scores of the 387 MFIs over the period 2005–2019. Then, it tries to consider factors influencing MFIs' efficiency and assess their effects. Hence, two separate models for operation and social efficiency introducing a set of factors, including FinTech proxies and overconfidence proxies, are tested. The first model for operational efficiency uses a random-effects estimator while the second one for social efficiency uses a fixed-effects estimator.FindingsThe results show that innovative MFIs have weaker averages of operational efficiency than non-innovative ones but higher averages of social efficiency. This was justified by the fact that innovative MFIs are more socially oriented. Further, findings of this study depict that the proxies of FinTech affect negatively the level of operational efficiency of MFIs. They also depict a negative relationship between FinTech proxies and the level of social efficiency. These results hold through robustness tests.Originality/valueThe highlight of this study is that it takes heed of the indirect effect of technological innovation on the efficiency of MFIs. It has been proved that it moderates the impact of managerial overconfidence (manifested by excessive risk-taking, viz., high levels of PAR30, LGR and NIM) on the level of both operational and social efficiencies.
{"title":"Microfinance's digital transformation for sustainable inclusion","authors":"Marwa Fersi, M. Boujelbene, Feten Arous","doi":"10.1108/ejmbe-10-2022-0332","DOIUrl":"https://doi.org/10.1108/ejmbe-10-2022-0332","url":null,"abstract":"PurposeThe purpose of this paper is to evaluate the performance of Microfinance Institutions (MFIs) offering FinTech services. This study contributes to the existing literature on microfinance digitalization, financial inclusion and sustainable development. The study also takes into consideration a behavioral perspective through the efficiency evaluation process of MFIs offering FinTech services.Design/methodology/approachThe following study employs the Stochastic Frontier Analysis approach to estimate the operational and social efficiency scores of the 387 MFIs over the period 2005–2019. Then, it tries to consider factors influencing MFIs' efficiency and assess their effects. Hence, two separate models for operation and social efficiency introducing a set of factors, including FinTech proxies and overconfidence proxies, are tested. The first model for operational efficiency uses a random-effects estimator while the second one for social efficiency uses a fixed-effects estimator.FindingsThe results show that innovative MFIs have weaker averages of operational efficiency than non-innovative ones but higher averages of social efficiency. This was justified by the fact that innovative MFIs are more socially oriented. Further, findings of this study depict that the proxies of FinTech affect negatively the level of operational efficiency of MFIs. They also depict a negative relationship between FinTech proxies and the level of social efficiency. These results hold through robustness tests.Originality/valueThe highlight of this study is that it takes heed of the indirect effect of technological innovation on the efficiency of MFIs. It has been proved that it moderates the impact of managerial overconfidence (manifested by excessive risk-taking, viz., high levels of PAR30, LGR and NIM) on the level of both operational and social efficiencies.","PeriodicalId":45118,"journal":{"name":"European Journal of Management and Business Economics","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41694691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-15DOI: 10.1108/ejmbe-07-2022-0224
A. Hakimi, Rim Boussaada, Majdi Karmani
PurposeThis paper aims to investigate the reciprocal nonlinear relationship between corporate social responsibility (CSR) and firm performance (FP).Design/methodology/approachThe authors used a sample of 814 European firms over the period 2008–2017. The Panel Smooth Transition Regression (PSTR) model was performed as an econometric approach.FindingsFirstly, results show a threshold effect in the CSR–FP relationships within the two directions. More specifically, the authors found that firms are more likely to engage in CSR by surpassing a threshold of 1.231% for return on assets (ROA) and 0.821% for Tobin’s Q ratio. Secondly, the authors also found that the impact of CSR on FP is positive and significant only if the environment, social and governance score surpasses the threshold of 56.780% when the dependent variable is ROA and 41.02% when Tobin’s Q ratio measures performance.Research limitations/implicationsA significant part of the literature supports the linear relationship between CSR and FP from the unique direction (CSR → FP). This study comes to fill this gap by assessing the possible nonlinear relationship. In addition, this nonlinear relationship is tested under the two directions. Therefore, defining the threshold of FP that allows companies to engage in CSR, on the one hand, and the threshold of engagement in CSR that improves FP, on the other hand, could be an exciting topic.Practical implicationsTo get the full benefit from CSR effects, firms should be with better financial performance to be socially responsible.Originality/valueTo the best of our knowledge, few studies have explored the nonlinear relationship between CSR and FP. In addition, this study raises the question of whether this relation is causal. The authors assess the two nonlinear relationships between CSR ? FP and FP ? CSR by determining the optimal thresholds.
{"title":"Corporate social responsibility and firm performance: a threshold analysis of European firms","authors":"A. Hakimi, Rim Boussaada, Majdi Karmani","doi":"10.1108/ejmbe-07-2022-0224","DOIUrl":"https://doi.org/10.1108/ejmbe-07-2022-0224","url":null,"abstract":"PurposeThis paper aims to investigate the reciprocal nonlinear relationship between corporate social responsibility (CSR) and firm performance (FP).Design/methodology/approachThe authors used a sample of 814 European firms over the period 2008–2017. The Panel Smooth Transition Regression (PSTR) model was performed as an econometric approach.FindingsFirstly, results show a threshold effect in the CSR–FP relationships within the two directions. More specifically, the authors found that firms are more likely to engage in CSR by surpassing a threshold of 1.231% for return on assets (ROA) and 0.821% for Tobin’s Q ratio. Secondly, the authors also found that the impact of CSR on FP is positive and significant only if the environment, social and governance score surpasses the threshold of 56.780% when the dependent variable is ROA and 41.02% when Tobin’s Q ratio measures performance.Research limitations/implicationsA significant part of the literature supports the linear relationship between CSR and FP from the unique direction (CSR → FP). This study comes to fill this gap by assessing the possible nonlinear relationship. In addition, this nonlinear relationship is tested under the two directions. Therefore, defining the threshold of FP that allows companies to engage in CSR, on the one hand, and the threshold of engagement in CSR that improves FP, on the other hand, could be an exciting topic.Practical implicationsTo get the full benefit from CSR effects, firms should be with better financial performance to be socially responsible.Originality/valueTo the best of our knowledge, few studies have explored the nonlinear relationship between CSR and FP. In addition, this study raises the question of whether this relation is causal. The authors assess the two nonlinear relationships between CSR ? FP and FP ? CSR by determining the optimal thresholds.","PeriodicalId":45118,"journal":{"name":"European Journal of Management and Business Economics","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44752466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-12DOI: 10.1108/ejmbe-04-2021-0116
Sajid Ali, S. Raza, K. Khan
PurposeThis research paper aims to explore asymmetric market efficiency of the 13 Euro countries, i.e. Austria, Belgium, Finland, France, Germany, Greece, Ireland, Italy, Netherland, Portugal, Slovakia, Slovenia and Spain, concerning the period before global financial crisis (GFC), after GFC and period of COVID-19 pandemic.Design/methodology/approachMultifractal detrended fluctuation analysis (MF-DFA) is applied to examine the persistence and anti-persistency. It also discusses the random walk behavior hypothesis of these 13 countries non-stationary time series. Additionally, generalized Hurst exponents are applied to estimate the relative efficiency between short- and long-run horizons and small and large fluctuations.FindingsThe current study results suggest that most countries' markets are multifractal and exhibit long-term persistence in the short and long run. Moreover, the results with respect to full sample confirm that Portugal is the most efficient country in short run and Austria is the least efficient country. However, in long run, Austria appeared to be highly efficient, and Slovakia is the least efficient. In the pre-GFC period, Greece is said to be the relatively most efficient market in the short run, whereas Austria is the most efficient market in the long run. In the case of Post-GFC, Netherland and Ireland are the most efficient markets in short and long run, respectively. Lastly, COVID-19 results indicate that Finland's stock market is the most efficient in short run. Whereas, in the long run, the high efficiency is illustrated by Germany. In contrast, the most affected stock market due to COVID-19 is Belgium.Originality/valueThis study will add value to the present knowledge on efficient market hypothesis (EMH) with the MF-DFA approach. Also, with the MF-DFA approach, potential investors will be capable of ranking the stock markets of Eurozone countries based on their efficiency in the period before and after GFC and then specifically in the period of COVID-19.
{"title":"Asymmetric market efficiency of the Eurozone using the MF-DFA: a comparison between global financial crisis and COVID-19 era","authors":"Sajid Ali, S. Raza, K. Khan","doi":"10.1108/ejmbe-04-2021-0116","DOIUrl":"https://doi.org/10.1108/ejmbe-04-2021-0116","url":null,"abstract":"PurposeThis research paper aims to explore asymmetric market efficiency of the 13 Euro countries, i.e. Austria, Belgium, Finland, France, Germany, Greece, Ireland, Italy, Netherland, Portugal, Slovakia, Slovenia and Spain, concerning the period before global financial crisis (GFC), after GFC and period of COVID-19 pandemic.Design/methodology/approachMultifractal detrended fluctuation analysis (MF-DFA) is applied to examine the persistence and anti-persistency. It also discusses the random walk behavior hypothesis of these 13 countries non-stationary time series. Additionally, generalized Hurst exponents are applied to estimate the relative efficiency between short- and long-run horizons and small and large fluctuations.FindingsThe current study results suggest that most countries' markets are multifractal and exhibit long-term persistence in the short and long run. Moreover, the results with respect to full sample confirm that Portugal is the most efficient country in short run and Austria is the least efficient country. However, in long run, Austria appeared to be highly efficient, and Slovakia is the least efficient. In the pre-GFC period, Greece is said to be the relatively most efficient market in the short run, whereas Austria is the most efficient market in the long run. In the case of Post-GFC, Netherland and Ireland are the most efficient markets in short and long run, respectively. Lastly, COVID-19 results indicate that Finland's stock market is the most efficient in short run. Whereas, in the long run, the high efficiency is illustrated by Germany. In contrast, the most affected stock market due to COVID-19 is Belgium.Originality/valueThis study will add value to the present knowledge on efficient market hypothesis (EMH) with the MF-DFA approach. Also, with the MF-DFA approach, potential investors will be capable of ranking the stock markets of Eurozone countries based on their efficiency in the period before and after GFC and then specifically in the period of COVID-19.","PeriodicalId":45118,"journal":{"name":"European Journal of Management and Business Economics","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44802094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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