Rasha Istaiteyeh, Maysa’a Munir Milhem, Farah Najem, Ahmed Elsayed
This paper presents a comprehensive analysis of key financial indicators influencing the operational efficiency of banks in Jordan over the period 2006 to 2021. The study, focusing on fifteen commercial banks, employs seven regression models to assess the impact of selected variables on bank operating efficiency. Our findings reveal novel insights with substantial contributions to banking practice. We identify a statistically significant influence of both bank-specific factors and temporal effects, demonstrating the nuanced dynamics shaping the operational efficiency of Jordanian banks. Notably, a positive and significant correlation is established between the operating efficiency ratio and return on assets, bank size, and the ratio of loan loss provisions to net interest income, providing valuable strategic guidance for effective management. Conversely, a significant negative relationship is observed between the operating efficiency ratio and the total expense ratio, underscoring the critical importance of careful cost management. No significant associations are found between the operating efficiency ratio and credit risk, the equity-to-asset ratio, the deposit-to-liability ratio, and the equity-to-liability ratio. This study makes a unique contribution by shedding light on these previously unexplored correlations, offering actionable insights for enhancing operational efficiency in the banking sector. Additionally, our research advocates for the Central Bank of Jordan (CBJ) to persist in adaptive policy measures, which are crucial for ongoing banking reforms and improved monitoring practices. Based on our empirical findings, these recommendations aim to fortify the resilience and adaptability of Jordan’s banking sector, contributing both academically and practically. Importantly, they reinforce the symbiotic link between a stable banking sector and sustained economic development in Jordan.
{"title":"Determinants of Operating Efficiency for the Jordanian Banks: A Panel Data Econometric Approach","authors":"Rasha Istaiteyeh, Maysa’a Munir Milhem, Farah Najem, Ahmed Elsayed","doi":"10.3390/ijfs12010012","DOIUrl":"https://doi.org/10.3390/ijfs12010012","url":null,"abstract":"This paper presents a comprehensive analysis of key financial indicators influencing the operational efficiency of banks in Jordan over the period 2006 to 2021. The study, focusing on fifteen commercial banks, employs seven regression models to assess the impact of selected variables on bank operating efficiency. Our findings reveal novel insights with substantial contributions to banking practice. We identify a statistically significant influence of both bank-specific factors and temporal effects, demonstrating the nuanced dynamics shaping the operational efficiency of Jordanian banks. Notably, a positive and significant correlation is established between the operating efficiency ratio and return on assets, bank size, and the ratio of loan loss provisions to net interest income, providing valuable strategic guidance for effective management. Conversely, a significant negative relationship is observed between the operating efficiency ratio and the total expense ratio, underscoring the critical importance of careful cost management. No significant associations are found between the operating efficiency ratio and credit risk, the equity-to-asset ratio, the deposit-to-liability ratio, and the equity-to-liability ratio. This study makes a unique contribution by shedding light on these previously unexplored correlations, offering actionable insights for enhancing operational efficiency in the banking sector. Additionally, our research advocates for the Central Bank of Jordan (CBJ) to persist in adaptive policy measures, which are crucial for ongoing banking reforms and improved monitoring practices. Based on our empirical findings, these recommendations aim to fortify the resilience and adaptability of Jordan’s banking sector, contributing both academically and practically. Importantly, they reinforce the symbiotic link between a stable banking sector and sustained economic development in Jordan.","PeriodicalId":45794,"journal":{"name":"International Journal of Financial Studies","volume":"76 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139644791","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}
Sherwood Lane Lambert, Kevin Krieger, Nathan Mauck
We propose a generalized, practitioner-oriented operating-leverage model for predicting operating income using net sales, cost of sales, depreciation, and SG&A. Prior research links operating income directly to these items; hence, our model includes all aggregate revenues and expenses that comprise operating income. Prior research finds that the cost of sales is “much less” sticky than depreciation and SG&A; hence, we use the cost of sales as a proxy for the total variable costs and depreciation and SG&A as proxies for the sticky fixed costs. We introduce a new adjustment to the textbook operating-leverage model so that the ratio of sales to the cost of sales remains constant for the reference and forecast periods. Inspired by prior research, we adjust depreciation and SG&A for cost stickiness. We find that using our generalized operating-leverage model improves the forecast accuracy of next-quarter and next-year operating income predictions compared to predictions made using textbook operating leverage, which is a special case of our model.
{"title":"Predicting Operating Income via a Generalized Operating-Leverage Model","authors":"Sherwood Lane Lambert, Kevin Krieger, Nathan Mauck","doi":"10.3390/ijfs12010011","DOIUrl":"https://doi.org/10.3390/ijfs12010011","url":null,"abstract":"We propose a generalized, practitioner-oriented operating-leverage model for predicting operating income using net sales, cost of sales, depreciation, and SG&A. Prior research links operating income directly to these items; hence, our model includes all aggregate revenues and expenses that comprise operating income. Prior research finds that the cost of sales is “much less” sticky than depreciation and SG&A; hence, we use the cost of sales as a proxy for the total variable costs and depreciation and SG&A as proxies for the sticky fixed costs. We introduce a new adjustment to the textbook operating-leverage model so that the ratio of sales to the cost of sales remains constant for the reference and forecast periods. Inspired by prior research, we adjust depreciation and SG&A for cost stickiness. We find that using our generalized operating-leverage model improves the forecast accuracy of next-quarter and next-year operating income predictions compared to predictions made using textbook operating leverage, which is a special case of our model.","PeriodicalId":45794,"journal":{"name":"International Journal of Financial Studies","volume":"6 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139561019","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}
Francesco Fasano, Maurizio La Rocca, F. Javier Sánchez-Vidal, Maria Joshepin Lio, Alfio Cariola
Credit from suppliers is an important source of finance for firms. It can sustain firms’ financial flexibility even in periods of downturn. In this study, using a large database of 90,763 Italian firms in the 2015–2021 period, we investigated how local financial development affects the trade-credit policies of SMEs and how this effect is conditioned by the degree of judicial enforcement. Given that trade credit can be a substitute for bank financing, we find that firms make more use of trade credit in developed financial markets. Moreover, we highlight the finding that a higher degree of judicial enforcement, which reinforces the role of contracts in the market, amplifies this effect. Finally, we observe that the COVID-19 crisis has reduced both the positive effect of local financial development and the positive moderating effect of enforcement in the use of trade credit.
{"title":"How Local Finance and Enforcement Shaped SME Credit Choices before and during the COVID Crisis","authors":"Francesco Fasano, Maurizio La Rocca, F. Javier Sánchez-Vidal, Maria Joshepin Lio, Alfio Cariola","doi":"10.3390/ijfs12010010","DOIUrl":"https://doi.org/10.3390/ijfs12010010","url":null,"abstract":"Credit from suppliers is an important source of finance for firms. It can sustain firms’ financial flexibility even in periods of downturn. In this study, using a large database of 90,763 Italian firms in the 2015–2021 period, we investigated how local financial development affects the trade-credit policies of SMEs and how this effect is conditioned by the degree of judicial enforcement. Given that trade credit can be a substitute for bank financing, we find that firms make more use of trade credit in developed financial markets. Moreover, we highlight the finding that a higher degree of judicial enforcement, which reinforces the role of contracts in the market, amplifies this effect. Finally, we observe that the COVID-19 crisis has reduced both the positive effect of local financial development and the positive moderating effect of enforcement in the use of trade credit.","PeriodicalId":45794,"journal":{"name":"International Journal of Financial Studies","volume":"1 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139515612","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}
Stanislav Letkovský, Sylvia Jenčová, Petra Vašaničová
Predicting bankruptcy within selected industries is crucial because of the potential ripple effects and unique characteristics of those industries. It serves as a risk management tool, guiding various stakeholders in making decisions. While artificial intelligence (AI) has shown high success rates in classification tasks, it remains uncertain whether its use significantly enhances the potential for early warning of impending problems. The following question arises: will classical methods eventually replace the effectiveness of these advanced techniques? This paper sheds light on the fact that even classical methods continue to achieve results that are not far behind, highlighting their enduring importance in financial analysis. This paper aims to develop bankruptcy prediction models for the chemical industry in Slovakia and to compare their effectiveness. Predictions are generated using the classical logistic regression (LR) method as well as AI techniques, artificial neural networks (ANNs), support vector machines (SVMs), and decision trees (DTs). The analysis aims to determine which of the employed methods is the most efficient. The research sample consists of circa 600 enterprises operating in the Slovak chemical industry. The selection of eleven financial indicators used for bankruptcy prediction was grounded in prior research and existing literature. The results show that all of the explored methods yielded highly similar outcomes. Therefore, determining the clear superiority of any single method is a difficult task. This might be partially due to the potentially reduced quality of the input data. In addition to classical statistical methods employed in econometrics, there is an ongoing development of AI-based models and their hybrid forms. The following question arises: to what extent can these newer approaches enhance accuracy and effectiveness?
{"title":"Is Artificial Intelligence Really More Accurate in Predicting Bankruptcy?","authors":"Stanislav Letkovský, Sylvia Jenčová, Petra Vašaničová","doi":"10.3390/ijfs12010008","DOIUrl":"https://doi.org/10.3390/ijfs12010008","url":null,"abstract":"Predicting bankruptcy within selected industries is crucial because of the potential ripple effects and unique characteristics of those industries. It serves as a risk management tool, guiding various stakeholders in making decisions. While artificial intelligence (AI) has shown high success rates in classification tasks, it remains uncertain whether its use significantly enhances the potential for early warning of impending problems. The following question arises: will classical methods eventually replace the effectiveness of these advanced techniques? This paper sheds light on the fact that even classical methods continue to achieve results that are not far behind, highlighting their enduring importance in financial analysis. This paper aims to develop bankruptcy prediction models for the chemical industry in Slovakia and to compare their effectiveness. Predictions are generated using the classical logistic regression (LR) method as well as AI techniques, artificial neural networks (ANNs), support vector machines (SVMs), and decision trees (DTs). The analysis aims to determine which of the employed methods is the most efficient. The research sample consists of circa 600 enterprises operating in the Slovak chemical industry. The selection of eleven financial indicators used for bankruptcy prediction was grounded in prior research and existing literature. The results show that all of the explored methods yielded highly similar outcomes. Therefore, determining the clear superiority of any single method is a difficult task. This might be partially due to the potentially reduced quality of the input data. In addition to classical statistical methods employed in econometrics, there is an ongoing development of AI-based models and their hybrid forms. The following question arises: to what extent can these newer approaches enhance accuracy and effectiveness?","PeriodicalId":45794,"journal":{"name":"International Journal of Financial Studies","volume":"389 1 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139562348","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}
Cláudia Pereira, Beatriz Castro, Luís Gomes, Helena Canha
We investigate whether accounting information system quality has an impact on the level and efficiency of firms’ investments. While firms’ growth depends on investment and financing decisions, accounting information is fundamental for the decision-making of several stakeholders. We assess the accounting information system quality by discretionary accruals, whereas the investment inefficiency is estimated by the residuals of an investment regression for a sample of 3073 Portuguese SMEs from 27 industries, over the period from 2016 to 2021 using a panel regression analysis. The empirical evidence suggests that firms exhibiting higher accounting information system quality tend to invest more. In addition, firms with a lower accounting information system quality have more inefficient investments, as they tend to engage in more overinvestment, although this is not significant for underinvestment. Therefore, this study provides new evidence regarding the impact of accounting information systems on investment that may be useful for several stakeholders, such as managers, creditors, regulators, and academics, by providing evidence for SMEs, where empirical studies are scarce.
{"title":"Firms’ Investment Level and (In)Efficiency: The Role of Accounting Information System Quality","authors":"Cláudia Pereira, Beatriz Castro, Luís Gomes, Helena Canha","doi":"10.3390/ijfs12010009","DOIUrl":"https://doi.org/10.3390/ijfs12010009","url":null,"abstract":"We investigate whether accounting information system quality has an impact on the level and efficiency of firms’ investments. While firms’ growth depends on investment and financing decisions, accounting information is fundamental for the decision-making of several stakeholders. We assess the accounting information system quality by discretionary accruals, whereas the investment inefficiency is estimated by the residuals of an investment regression for a sample of 3073 Portuguese SMEs from 27 industries, over the period from 2016 to 2021 using a panel regression analysis. The empirical evidence suggests that firms exhibiting higher accounting information system quality tend to invest more. In addition, firms with a lower accounting information system quality have more inefficient investments, as they tend to engage in more overinvestment, although this is not significant for underinvestment. Therefore, this study provides new evidence regarding the impact of accounting information systems on investment that may be useful for several stakeholders, such as managers, creditors, regulators, and academics, by providing evidence for SMEs, where empirical studies are scarce.","PeriodicalId":45794,"journal":{"name":"International Journal of Financial Studies","volume":"11 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139560945","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}
Marisa Pessoa Gonçalves, Pedro M. Nogueira Reis, António Pedro Pinto
In this study, we provide a thorough analysis, conducted on a company-by-company basis, of the impact of bank concentration and the bank-relative power of banks on firm profitability, financing costs, and capital structure in a small economy like Portugal. Using a sample of 434,990 Portuguese companies, the study spans a time frame of 13 years (from 2006 to 2018). Principal component analysis (PCA) was used to determine bank concentration, and a new variable, “bank-related power”, was introduced. This work employed linear regression with static panel data for fixed and pooled effects, using Driscoll–Kraay standard errors and robust standard error estimation. A direct association was found between business performance and the use of bank credit in highly concentrated banking markets (SMEs), and there is evidence of an inverse relationship when the relative power of banks increases (small business). Evidence also shows that financing costs increase with greater bank concentration, while firms’ capital structure improves under similar conditions. When a bank holds greater relative market power, it tends to exert a negative impact on the capital structure of large companies. However, an inverse relationship is observed in the case of SMEs. Unlike previous studies, the article assesses the effects of bank market power on each of the different companies involved by using both bank concentration (as a composite variable) and a new variable that measures the relative power of banks. Due to its extensive database and expanded time frame, this research is innovative in the context of small-sized companies.
{"title":"Bank Market Power, Firm Performance, Financing Costs and Capital Structure","authors":"Marisa Pessoa Gonçalves, Pedro M. Nogueira Reis, António Pedro Pinto","doi":"10.3390/ijfs12010007","DOIUrl":"https://doi.org/10.3390/ijfs12010007","url":null,"abstract":"In this study, we provide a thorough analysis, conducted on a company-by-company basis, of the impact of bank concentration and the bank-relative power of banks on firm profitability, financing costs, and capital structure in a small economy like Portugal. Using a sample of 434,990 Portuguese companies, the study spans a time frame of 13 years (from 2006 to 2018). Principal component analysis (PCA) was used to determine bank concentration, and a new variable, “bank-related power”, was introduced. This work employed linear regression with static panel data for fixed and pooled effects, using Driscoll–Kraay standard errors and robust standard error estimation. A direct association was found between business performance and the use of bank credit in highly concentrated banking markets (SMEs), and there is evidence of an inverse relationship when the relative power of banks increases (small business). Evidence also shows that financing costs increase with greater bank concentration, while firms’ capital structure improves under similar conditions. When a bank holds greater relative market power, it tends to exert a negative impact on the capital structure of large companies. However, an inverse relationship is observed in the case of SMEs. Unlike previous studies, the article assesses the effects of bank market power on each of the different companies involved by using both bank concentration (as a composite variable) and a new variable that measures the relative power of banks. Due to its extensive database and expanded time frame, this research is innovative in the context of small-sized companies.","PeriodicalId":45794,"journal":{"name":"International Journal of Financial Studies","volume":"84 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139561018","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}
This research investigates the burgeoning peer-to-peer (P2P) economy, exemplified by platforms such as Airbnb, and its implications within the North American context. The study focuses on understanding the repercussions of Airbnb announcements on capital markets, concentrating specifically on the travel and tourism sector and the real estate sector. The findings unveil a discernible augmentation in index returns preceding the announcement’s publication in both sectors. However, a notable divergence manifests post-announcement: while the real estate sector sustains an upward trajectory in returns, the travel and tourism sector experiences a post-publication decline. These results underscore the strategic advantage available to investors with early access to Airbnb announcements, enabling them to capitalize on excess profits. Furthermore, the broader investor community can leverage the insights gleaned from Airbnb announcements for financial gains. A nuanced examination of regression results reveals the substantial impact of macroeconomic variables on index returns in both the travel and tourism sector and the real estate sector. These insights contribute to a more nuanced understanding of the intricate dynamics shaping these economic domains.
{"title":"The Influence of Airbnb Announcements on North American Capital Markets: Insights for Stakeholders","authors":"Tchai Tavor","doi":"10.3390/ijfs12010006","DOIUrl":"https://doi.org/10.3390/ijfs12010006","url":null,"abstract":"This research investigates the burgeoning peer-to-peer (P2P) economy, exemplified by platforms such as Airbnb, and its implications within the North American context. The study focuses on understanding the repercussions of Airbnb announcements on capital markets, concentrating specifically on the travel and tourism sector and the real estate sector. The findings unveil a discernible augmentation in index returns preceding the announcement’s publication in both sectors. However, a notable divergence manifests post-announcement: while the real estate sector sustains an upward trajectory in returns, the travel and tourism sector experiences a post-publication decline. These results underscore the strategic advantage available to investors with early access to Airbnb announcements, enabling them to capitalize on excess profits. Furthermore, the broader investor community can leverage the insights gleaned from Airbnb announcements for financial gains. A nuanced examination of regression results reveals the substantial impact of macroeconomic variables on index returns in both the travel and tourism sector and the real estate sector. These insights contribute to a more nuanced understanding of the intricate dynamics shaping these economic domains.","PeriodicalId":45794,"journal":{"name":"International Journal of Financial Studies","volume":"4 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139475440","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}
Carla Oliveira Henriques, Maria Elisabete Neves, João Jorge Couceiro
This paper examines the efficiency of alternative energy equity Exchange-Traded Funds (ETFs) and conventional energy equity ETFs from 2018 to 2020, utilizing a combination of an output-oriented Slack-Based Data Envelopment Analysis (DEA) model and cluster analysis. In the context of an output-oriented DEA model, efficiency is defined as the ability of an ETF to maximize its outputs (annualized average return; environmental, social responsibility, and corporate governance; and net asset value) given a fixed level of inputs (expense ratio and beta). The findings indicate that alternative energy ETFs have the potential for long-term outperformance compared to conventional energy ETFs in terms of efficiency. However, during financial crises, the performance differences between the two types of ETFs diminish, with no significant outperformance observed in either category. The expense ratio and net asset value are identified as key factors influencing the efficiency of both ETF types. Additionally, social and governance metrics have a notably stronger positive impact on conventional energy ETFs relative to alternative energy ETFs, highlighting the increasing significance of these factors in financial asset performance.
{"title":"The Efficiency of Alternative and Conventional Energy Exchange-Traded Funds: Are Clean Energy Exchange-Traded Funds a Safer Asset?","authors":"Carla Oliveira Henriques, Maria Elisabete Neves, João Jorge Couceiro","doi":"10.3390/ijfs12010004","DOIUrl":"https://doi.org/10.3390/ijfs12010004","url":null,"abstract":"This paper examines the efficiency of alternative energy equity Exchange-Traded Funds (ETFs) and conventional energy equity ETFs from 2018 to 2020, utilizing a combination of an output-oriented Slack-Based Data Envelopment Analysis (DEA) model and cluster analysis. In the context of an output-oriented DEA model, efficiency is defined as the ability of an ETF to maximize its outputs (annualized average return; environmental, social responsibility, and corporate governance; and net asset value) given a fixed level of inputs (expense ratio and beta). The findings indicate that alternative energy ETFs have the potential for long-term outperformance compared to conventional energy ETFs in terms of efficiency. However, during financial crises, the performance differences between the two types of ETFs diminish, with no significant outperformance observed in either category. The expense ratio and net asset value are identified as key factors influencing the efficiency of both ETF types. Additionally, social and governance metrics have a notably stronger positive impact on conventional energy ETFs relative to alternative energy ETFs, highlighting the increasing significance of these factors in financial asset performance.","PeriodicalId":45794,"journal":{"name":"International Journal of Financial Studies","volume":"16 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139469113","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}
The aim of the present study is to assess the impact of structural capital intensity and utilization on firm profitability in an international setting: the European Union countries, plus Norway, Switzerland and the United Kingdom. The indicators are calculated based on financial data downloaded from the Refinitiv Eikon database. Two financial ratios are used as proxies for the intensity and utilization of structural capital. The balanced panel consists of 625 companies from 25 countries, over the period from 2013 to 2022. The panel includes financial information on two industries that are considered innovation-oriented, namely technology and healthcare. Alternative model specifications are proposed to test the robustness of the basic model, including dynamic models (with lagged dependent variables). The present study indicates that a higher proportion of structural capital (intangible assets, excluding goodwill) is a negative factor for company profitability in the technology and healthcare sectors. There is no indication that a more intense use of intangible assets and more investments in R&D positively contribute to company profitability in the respective industries, for a large sample of listed companies. A higher proportion of intangible assets, as reported in financial statements, is possibly related to inefficiencies in the management of structural capital. The inverse relationship between profitability and investments in intangible assets is likely due to failures in cost accounting. Limitations and future research propositions are provided in the conclusions.
{"title":"The Impact of Intangible Capital on Firm Profitability in the Technology and Healthcare Sectors","authors":"Voicu D. Dragomir","doi":"10.3390/ijfs12010005","DOIUrl":"https://doi.org/10.3390/ijfs12010005","url":null,"abstract":"The aim of the present study is to assess the impact of structural capital intensity and utilization on firm profitability in an international setting: the European Union countries, plus Norway, Switzerland and the United Kingdom. The indicators are calculated based on financial data downloaded from the Refinitiv Eikon database. Two financial ratios are used as proxies for the intensity and utilization of structural capital. The balanced panel consists of 625 companies from 25 countries, over the period from 2013 to 2022. The panel includes financial information on two industries that are considered innovation-oriented, namely technology and healthcare. Alternative model specifications are proposed to test the robustness of the basic model, including dynamic models (with lagged dependent variables). The present study indicates that a higher proportion of structural capital (intangible assets, excluding goodwill) is a negative factor for company profitability in the technology and healthcare sectors. There is no indication that a more intense use of intangible assets and more investments in R&D positively contribute to company profitability in the respective industries, for a large sample of listed companies. A higher proportion of intangible assets, as reported in financial statements, is possibly related to inefficiencies in the management of structural capital. The inverse relationship between profitability and investments in intangible assets is likely due to failures in cost accounting. Limitations and future research propositions are provided in the conclusions.","PeriodicalId":45794,"journal":{"name":"International Journal of Financial Studies","volume":"24 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139471107","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}
Mohammed M. Yassin, Dea’a Al-Deen Al-Sraheen, Khaldoon Ahmad Al Daoud, Mohammad Alhadab, Farouq Altahtamouni
The Financial Accounting Standards Board (FASB) released Accounting Standards Codification (ASC) 606, “Revenue from Contracts with Customers”, with the aim of enhancing transparency to provide fairer representation and inhibit the misuse of revenues to manipulate earnings. During COVID-19, variable considerations in ASC 606 were used to manage earnings as a tool to help firms survive. The study aimed to test the mediating role of earnings management in influencing the effect of variable considerations in ASC 606 on the continuity of the firm. An online questionnaire was sent to financial reporting preparers in US public shareholding firms; 403 valid questionnaires were received. The results of PLS-SEM revealed that crises such as COVID-19 have highlighted the way in which variable considerations in ASC 606 were exploited to manage firms’ earnings to ensure their survival. Companies resort to showing their best financial performance, beautifying its financial reports by manipulating profits, using flexibility in accounting policies, but this may negatively affect the country’s entire economy by collapsing companies and creating more financial crises that cannot be easily addressed.
{"title":"Variable Considerations in ASC 606, Earnings Management and Business Continuity during Crisis","authors":"Mohammed M. Yassin, Dea’a Al-Deen Al-Sraheen, Khaldoon Ahmad Al Daoud, Mohammad Alhadab, Farouq Altahtamouni","doi":"10.3390/ijfs12010001","DOIUrl":"https://doi.org/10.3390/ijfs12010001","url":null,"abstract":"The Financial Accounting Standards Board (FASB) released Accounting Standards Codification (ASC) 606, “Revenue from Contracts with Customers”, with the aim of enhancing transparency to provide fairer representation and inhibit the misuse of revenues to manipulate earnings. During COVID-19, variable considerations in ASC 606 were used to manage earnings as a tool to help firms survive. The study aimed to test the mediating role of earnings management in influencing the effect of variable considerations in ASC 606 on the continuity of the firm. An online questionnaire was sent to financial reporting preparers in US public shareholding firms; 403 valid questionnaires were received. The results of PLS-SEM revealed that crises such as COVID-19 have highlighted the way in which variable considerations in ASC 606 were exploited to manage firms’ earnings to ensure their survival. Companies resort to showing their best financial performance, beautifying its financial reports by manipulating profits, using flexibility in accounting policies, but this may negatively affect the country’s entire economy by collapsing companies and creating more financial crises that cannot be easily addressed.","PeriodicalId":45794,"journal":{"name":"International Journal of Financial Studies","volume":"26 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139374321","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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