Search results

This study aims to apply machine learning (ML) to identify new financial elements managers might use for earnings management (EM), assessing their impact on the Standard Jones Model and modified Jones model for EM detection and examining managerial motives for using these components.

Using eXtreme gradient boosting on 23,310 the US firm-year observations from 2012 to2021, the study pinpoints nine financial variables potentially used for earnings manipulation, not covered by traditional accruals models.

Cost of goods sold and earnings before interest, taxes, depreciation and amortization are identified as the most significant for EM, with relative importances of 40.2% and 11.5%, respectively.

The study’s scope, limited to a specific data set and timeframe, and the exclusion of some financial variables may impact the findings’ broader applicability.

The results are crucial for researchers, practitioners, regulators and investors, offering strategies for detecting and addressing EM.

Insights from the study advocate for greater financial transparency and integrity in businesses.

By incorporating ML in EM detection and spotlighting overlooked financial variables, the research brings fresh perspectives and opens new avenues for further exploration in the field.

This study aims to present a model for detecting and predicting creative accounting in companies listed on the Tehran Stock Exchange (TSE).

The authors conduct this research in three stages. First, the authors review the literature to determine the dimensions, components, indicators and techniques of creative accounting. Second, the authors conduct semi-structured interviews with experts using the fuzzy Delphi technique to obtain screening and reach a consensus. Finally, the authors develop a model to predict creative accounting by classifying the financial statements of the sample companies into two groups based on the use or non-use of creative accounting techniques, measuring the indicators determined in the previous stage, running various machine learning algorithms and choosing the superior algorithm.

The results indicate the usefulness of accounting information for detecting and predicting creative accounting and the relevance of several financial attributes as important predictors. The results also indicate the superiority of extremely randomized trees over other algorithms in predicting creative accounting and suggest that the primary purpose of creative accounting in Iran is earnings management. Contrary to the political cost hypothesis, large Iranian companies use creative accounting to inflate profits.

The present research also has several limitations that must be considered, and caution must be exercised in interpreting and generalizing the findings as specified in the revised manuscript.

This study’s implications are significant for policymakers, standard-setters and practitioners. By recognizing the detrimental effects of creative accounting on financial transparency within companies, policymakers can address existing gaps in accounting standards to minimize the potential for earnings manipulation. Consequently, strengthening internal and external mechanisms related to a firm’s financial performance becomes achievable. The study provides evidence of the need for audit firms to recognize the importance of creative accounting and consider creative accounting in their audit plans to prevent insufficient or even misleading disclosure by companies that extensively use creative accounting practices in their financial reporting. Moreover, knowledge of creative accounting techniques can help auditors assess audit and detection risks and serve as a valuable guide for reducing audit costs and improving audit quality.

Given that creative accounting practices distort the true or real accounting results, curbing creative accounting practices reduces corporate failures and could lead to the reduction of job losses and other social consequences.

This study uses a unique database in Iran to determine a model for predicting creative accounting using a mixed-method methodology, qualitative and quantitative, to identify creative accounting techniques and run various machine learning algorithms.

Public-private partnerships (PPPs) have become integral in delivering public services and infrastructure, particularly in the context of megaprojects. This paper focuses on the interplay between stakeholder management, challenges, critical success factors (CSFs), and the overall success of PPP-arranged civil infrastructure megaprojects.

Using the PRISMA methodology, we comprehensively analyze challenges and critical success factors (CSFs) influencing stakeholder engagement within PPP megaprojects. A focused search equation identified 595 papers, which were distilled down to 34 relevant papers and case studies. Qualitative analysis of these papers revealed 48 CSFs categorized into 11 challenges from a stakeholder management perspective, which were further delineated across public, private, and combined sectors, and then mapped along the PPP megaproject lifecycle.

Informed by a diverse amalgam of civil and project management literature, this research reveals the intricate dynamics of PPP megaprojects across the globe that emphasize the critical nature of stakeholder engagement, analysis, and management practices. Key findings highlighted conflicting interests between public and private stakeholders, manifesting in challenges like project performance versus profitability. The literature emphasized instances where neglect of local community culture led to adverse social outcomes. A universal conclusion underscored the context-specific nature of challenges and CSFs, stressing the need for a holistic understanding of stakeholders and project dynamics.

The paper acknowledges that it focused on 34 selected papers out of 595 identified. This sample focuses on civil engineering megaprojects which may not fully represent the breadth of research in the field, potentially missing out on valuable insights from excluded studies.

We believe that the compiled list of CSFs, organized according to stakeholder relationships and the project lifecycle, serves as a potent tool for managers and planners. By enabling the identification of complexity from diverse perspectives, this research allows elucidating the challenges faced by the management team in PPP megaproject.

This research identifies several social outcomes related to PPP megaprojects. Critical Success Factors identified as such should allow the project managers to maximize benefits for society and minimize risk and negative externalities.

This study contributes valuable insights for policies and practices by systematically describing challenges and related CSFs throughout the PPP megaproject lifecycle. Additionally, it addresses the nuanced aspects of internal and external stakeholder management, thereby contributing to the overall understanding and best practices required to confront complex megaprojects involving a wide range of stakeholder groups.

The objective of the study is to investigate the factors that differentiate long-term shareholder value (LTSV) creating firms from LTSV destroying firms.

Through the review of literature, the hypothesis for the study is developed. To test the hypothesis, the study collects data from S&P BSE 500 companies listed in Bombay Stock Exchange (BSE). Based on the average overall return to shareholders for the period from year 1991 to 2019, the study identifies top 25 LTSV creating and LTSV destroying firms. The top 50 firms form the basis of this study. The study uses descriptive statistics and independent sample t-test to test the hypothesis of the study.

Among the variables investigated such as capital management policy and effective capital management practices, business and financial strategy, intellectual capital strategy, relational capital strategy and human capital strategy, the study found effective capital management and governance as a long-term source of value for shareholders.

The study highlights the importance of inclusion of value-relevant information in the annual report of the company. The study also supports the proposition that discretionary disclosure of intangible assets is relevant for the market to enable market participants to reasonably comprehend the fair value of the firm.

Adoption of a reporting framework that ensures the availability of all value-relevant information including off-balance-sheet resources is in the interest of the investors and policymakers alike.

This is a first such study exploring the value-relevant information and the source of long-term value for listed firms.

The purpose of our study is to investigate the effects of politically-connected boards (PCBs) on over-(under-)investment in labor. We also examine the impacts of the supervisory board (SB)’s optimal tenure on the association between PCBs and over-investment in labor.

We constructed the proxy for PCBs using a dummy variable set to 1 (one) if a firm has politically-connected boards and zero (0) otherwise. For the robustness check, we used the number of politically-connected members on the boards as the proxy for PCBs.

We find that the presence of PCBs reduces over-investment in labor. Consistent with our prediction, we found no significant association between PCBs and under-investment in labor. We also find that the SB with optimal tenure strengthens the negative association between PCBs and over-investment in labor. In our channel analysis, we find that the presence of PCB mitigates over-investment in labor through a higher dividend payout ratio.

Due to the unavailability of data in firms’ annual reports regarding the number of poorly-skilled and highly skilled employees, we were not able to examine the effect of low-skilled and high-skilled employees on over-investment in labor. Also, we were not able to examine over-(under-)investment in labor by drawing a distinction between general (generalist) and firm-specific human capital (specialist) as suggested by Sevcenko, Wu, and Kacperczyk (2022). Generally, it is more difficult for managers to hire highly-skilled employees, specialists in particular, thereby driving the choice of either over- or under-investing in the labor forces. In addition, in the firms’ annual reports, there is no information regarding temporary employees. Therefore, if and when such data become available, this would provide another avenue for future research.

Our study offers several practical implications and insights to stakeholders (e.g. insiders or management, shareholders, investors, analysts and creditors) in the following ways. First, our study highlights significant differences between capital investment and labor investment. For instance, labor investment is considered an expense rather than an asset (Wyatt, 2008) because, although such investment is human capital and is not recognized on the firm’s balance sheet (Boon et al., 2017). In addition, labor investment is characterized by: its flexibility which enables firms to make frequent adjustments (Hamermesh, 1995; Dixit & Pindyck, 2012; Aksin et al., 2015), its non-homogeneity since every employee is unique (Luo et al., 2020), its direct impact on morale and productivity of a firm (Azadegan et al., 2013; Mishina et al., 2004; Tatikonda et al., 2013), and its financial outlay which affects the ongoing cash flows of a firm (Sualihu et al., 2021; Khedmati et al., 2020; Merz & Yashiv, 2007). Second, our findings reveal that the presence of PCBs could help to reduce over-investment in labor. However, if managers of a firm choose to under-invest in labor in order to obtain better profit in the short-term through cost saving, they should be aware of the potential consequences of facing a financial loss when a new business opportunity suddenly arises which requires a larger labor force. Third, our findings help stakeholders to re-focus on the labor investment. This is crucial due to the fact that labor investment is often neglected by those stakeholders because the expenditure of labor investment is not recognized on the firm’s balance sheet as an asset. Instead, it is written off as an expense in the firm’s income statement. Fourth, our findings also provide insightful information to stakeholders, suggesting that an SB with optimal tenure is more committed to a firm, and this factor plays an important role in strengthening the negative association between PCBs and over-investment in labor.

First, our findings provide a valuable understanding of the effects of PCBs on over-(under-)investment in labor. Stakeholders could use information disclosed in the financial statements of a publicly-listed firm to determine the extent of the firm’s investment in labor and PCBs, and compare this information with similar firms in the same industry sector. Second, our findings give a better understanding of the association between investment in labor and political connections , which are human and social capital that could determine the long-term survival and success of a firm. Third, for shareholders, the appointment of board members with political connections is an important strategic decision to build political capital, which is likely to have a long-term impact on the financial performance of a firm; therefore, it requires thoughtful consultation with firm insiders.

Our findings highlight the role of PCBs in reducing over-investment in labor. These findings are significant because both investment in labor and political connections as human and social capital can play an important role in determining the long-term survival and success of a firm.

The aim of this paper is to determine whether the efficiency of banks’ human capital (HC) has moderating effects on the relationship between asset diversification and bank performance over the 2008–2020 period.

Our study considers generalized least squares estimation in fixed effects panel.

Results show that banks with higher levels of HC and higher degree of diversification reduce bank profitability and efficiency. The results also depict that the financial stability-reducing effects of Income diversification decrease as bank HC efficiency increases. At the same time, the effects of income and asset diversity on financial stability change depending on the performance aspect.

Previous research on banks’ performance is concentrated on asset diversification. This article broadens to the HC, Asset diversification and the moderating effects of the profitability, stability and efficiency of French Banks.

The study seeks to evaluate the effect of capital adequacy and competition on the liquidity creation of Kenyan commercial banks.

Unbalanced panel data from 36 Kenyan commercial banks with licenses from 2001 to 2020 is used in the study. The generalized method of moments (GMM), a two-step system, is employed in the investigation. To increase the robustness and prevent erroneous findings, serial correlation tests and instrumental validity analyses are used. The methodology developed by Berger and Bouwman (2009) is used to estimate the commercial banks' levels of liquidity creation.

The study supports the financial fragility-crowding out hypothesis by finding a significant negative effect of capital adequacy on the liquidity creation of commercial banks. The research also identifies a significant inverse relationship between competition and liquidity creation, depicting competition's value-destroying effect.

A trade-off exists between capital adequacy and liquidity creation, which must be carefully evaluated as changes in capital requirements are considered. The value-destroying effect of competition on liquidity creation presents a case for policy geared toward consolidating banks' operations through possible mergers and acquisitions.

To the best of the authors' knowledge, this is the first study to empirically offer evidence concurrently on the effect of competition and capital adequacy on the liquidity creation of commercial banks in a developing economy such as Kenya. Additionally, the authors employ a novel measure of competition at the firm level.

This study aims to examine the nonlinear threshold effect of female board gender diversity (FBGD) on debt financing (DF) and equity financing (EF) decisions arguing that the effect of FBGD varies/changes depending on the numerical strength of the women on the board.

This study uses seemingly unrelated simultaneous panel equation modeling of 19 listed firms on the Ghana Stock Exchange (GSE) between 2010 and 2021. Although natural logs of equity and debts are used to proxy financing decisions, FBGD is measured as a percentage of total female board members to total board members.

This study reveals a nonlinear inverted U-shape effect of FBGD on EF and DF options. Although this result implies that the positive effects transit to negative effects when FBGD reaches numerical thresholds 34.20% and 35.11%, respectively, it also suggests that the risk averse nature of women on EF and DF usage becomes more visible and intense when the percentage of women on board increases above the mentioned thresholds, respectively. Clearly, the effect gender diversity on DF and EF depends on the numerical strength of the women on a board.

These results suggest that corporate entities and managers must be careful in the formation and implementation of gender diversity policies as gender diversity policies can influence/change debt and EF decisions. In addition, the thresholds show that a smaller number of women on board is required to lower EF compared to debt and this highlights risk-aversion nature women toward riskier financing decision. Also, the nonlinear inverted U-shape nexus from FBGD to EF and DF confirms the inverted U curve theory implying that the numerical strength of females on boards is critical for financing decisions.

This study contributes to the “gender diversity-financing decision” literature by simultaneously conceptualizing and modellng debt and EF structures and providing an emerging economy perspective on how gender diversity nonlinearly affects financing decisions.

This paper investigates the moderating role of uncertainty in the impact of monetary policy on bank liquidity creation.

Utilizing data from Vietnam spanning 2007–2022, the paper measures uncertainty in the banking industry through the dispersion of shocks to crucial bank-level variables and considers both interest rate- and quantity-based tools of the monetary policy regime. The study regresses economic models using different econometric methods, including the generalized method of moments (GMM) estimator in the main section and the least squares dummy variable corrected (LSDVC) estimator for the robustness check.

Monetary expansion enhances banks’ ability to create liquidity, affirming the existence of the bank liquidity creation channel. Further analyses suggest that monetary policy adjustments aimed at regulating bank liquidity creation may be less effective in the presence of higher uncertainty in the banking system. This observation holds for both interest rate- and quantitative-based monetary policy tools, emphasizing the functioning of the monetary policy transmission mechanism through bank liquidity creation and the mitigating effect of uncertainty.

This study contributes novel insights to the existing literature by presenting the first attempt to explore the dynamics of monetary policy transmission through the bank liquidity creation channel in the context of banking sector uncertainty. Moreover, our contribution extends to examining a multi-tool environment, incorporating both interest rate- and quantitative-based indicators.