Search Results (23)

This study examines the impact of tax avoidance practices on investment efficiency in Egypt, with particular emphasis on the moderating role of earnings management by exploring whether these tactics reflect managerial opportunism or serve as a mechanism to ease financial constraints. We employ panel data regression to analyze a sample of 58 non-financial firms listed on the Egyptian Exchange (EGX) over the period 2017–2024, yielding 464 firm-year observations. Data are collected from official corporate websites, EGX, and Egypt for Information Dissemination (EGID). Grounded in agency theory, signaling theory, and pecking order theory, this study reveals how conflicts of interest and information asymmetry between managers and stakeholders lead to managerial opportunism. The findings show that tax avoidance undermines the investment efficiency in the Egyptian market. Earnings manipulation further intensified this effect due to the financial statements’ opacity. A closer examination reveals that earnings management exacerbates overinvestment by masking managerial decisions. Conversely, for financially constrained firms with a tendency to underinvest, tax avoidance and earnings management may contribute to improved efficiency by generating internal liquidity and alleviating external financing constraints. These results provide valuable insights for regulators, highlighting that policy should be directed against managerial opportunism and improving transparency, instead of focusing solely on curbing tax avoidance. From an investor perspective, they should closely monitor and understand the tax-planning strategies to ensure they enhance the firm’s value. Full article

This study examines whether audit quality enhances the value relevance of earnings and book value of equity in explaining market prices of common shares in Thailand’s emerging market. Using data from 401 non-financial firms listed on the Stock Exchange of Thailand between 2021 and 2023, we analyze 1203 firm-year observations collected from Bloomberg and company annual reports. Multiple regression results show that earnings per share (EPS), book value per share (BVPS), and audit quality measures are significantly associated with share prices. Audit quality is proxied by audit firm size, audit fees, and financial statement irregularities (Beneish M-score). Big 4 auditors increase the relevance of book value, while higher audit fees strengthen the earnings–price relationship. Conversely, firms with higher M-scores, signaling potential earnings manipulation, display weakened associations between accounting metrics and share value. These findings highlight audit quality’s role in reducing information asymmetry, reinforcing investor trust, and supporting market efficiency in a post-crisis environment. By integrating audit quality into the Ohlson valuation framework, this study contributes to the literature on audit assurance and capital market behavior in emerging economies, offering insights for investors, regulators, and managers regarding the credibility of financial reporting. Full article

Smallholder irrigation farmers play a vital role in sustaining rural communities in South Africa. However, the performance of smallholder irrigators, both as income generators and job creators, has come under scrutiny in recent years. In Limpopo province, a study was conducted in the Vhembe District using cross-sectional data from 95 independent and 165 public smallholder irrigators, which are privately established farmers and users of government-supported and managed irrigation systems, respectively. Qualitative data were collected through questionnaires, key informant interviews, and group discussions. Quantitative data were analyzed by SPSS version 30 using themes and codes, employing inferential statistical methods such as chi-square and t-tests to assess variables related to agrifood systems, crop selection, and market access. The study found that smallholders predominantly favor the production of grains, vegetables, and horticultural crops, with a statistically significant (p < 0.05) similarity between independent and public irrigators. Public irrigators dominate within irrigation schemes at 64% of the total, with X² of 22.7 with 0.001 p-value. Amongst the groups, the income distribution shows a statistically significant difference in earnings between independent and public irrigators (χ² = 25.83, p < 0.001). Informal and formal markets are accessible and available to 59% of independent irrigators, but 30% of public irrigators only access the informal market (p < 0.001). The major identified challenge across all smallholders is the lack of food value addition and commercial packaging. The study recommends the development of food value addition initiatives, adoption of climate-smart practices, maintenance of infrastructure, and improvement of market access to enhance productivity and sustainability. Full article

This paper concentrates on the valuation of big data assets within the digital transformation of logistics enterprises. As data evolve into a core production factor in the logistics industry, their valuation is essential, not only for enterprises’ resource allocation decisions, but also as a key indicator for measuring the effectiveness of digital transformation. This paper combines the multiperiod excess earnings model with the analytic hierarchy process (AHP), creating an evaluation system through a comprehensive weighting method. Initially, the multiperiod excess earnings model is used to calculate the excess earnings of off-balance-sheet intangible assets. The AHP is subsequently applied to construct a hierarchical structural model of the enterprise, identifying the core factors that influence the excess earnings of off-balance-sheet intangible assets. This allows for precise segmentation and determination of the distribution rate of the value of data assets. The evaluation model fully accounts for the diversity, dynamics, and potential value of big data assets, effectively identifying and quantifying factors that are not easily observable directly. The findings not only provide a novel evaluation tool for data asset management in logistics enterprises but also offer theoretical support and practical guidance for enhancing the industry’s data asset valuation system and facilitating the realization of data asset value. Full article

With the increasing demand for electricity in modern society, the scale of substation construction projects has greatly expanded, and the ever-increasing technical requirements have led to rising project costs year by year. Effective cost management not only enhances a company’s market competitiveness but also ensures the construction quality of projects. This paper addressed the issues of cost management in substation projects by exploring the application of unbalanced bidding, target costing, and improved earned value management (EVM) in cost control. By introducing quality indicators to improve traditional EVM, this study proposed a comprehensive evaluation model that considers cost, schedule, and quality to ensure a good construction performance of substations. Using LT 220 kV substation of Company A project as a case study, the paper analyzed specific measures of cost management in the bidding decision, preparation, and construction phases, verifying the feasibility and effectiveness of the improved model. The results indicated that the enhanced EVM can effectively improve cost control in substation projects, achieving an optimal balance among quality, schedule, and cost with significant practical application value. Full article

Timely and informed decision-making is essential for the successful execution of construction projects, where delays and cost overruns frequently pose significant risks. Earned value analysis (EVA) provides a robust, integrated framework that combines scope, schedule, and cost performance to support proactive project control. This study investigates the effectiveness of EVA as a decision-support tool by applying it to two real-life construction case studies. Key performance indicators, including Cost Performance Index (CPI), Schedule Performance Index (SPI), Estimate at Completion (EAC), and Estimate to Complete (ETC), are calculated and analyzed over a specific monitoring period. The analysis revealed a 15.36% cost savings and a 10.42% schedule improvement during the monitored period. By comparing planned and actual performance data, the study demonstrates how EVA enables early detection of deviations, thereby empowering project managers to implement timely corrective actions. The findings highlight EVA’s practical utility in improving project transparency, enhancing cost and schedule control, and supporting strategic decision-making in real-world construction environments. Full article

Temporary book-tax differences (BTDs) serve as critical proxies for understanding corporate earnings management and tax planning. However, the drivers of large negative BTDs (LNBTDs)—where book income falls below taxable income—remain underexplored. This study investigates the determinants and components of LNBTDs, focusing on their relationship with deferred tax assets (DTAs) and liabilities (DTLs). Utilizing hand-collected data from the tax disclosures of S&P 500 firms’ 10-K filings (2007–2023), I analyze 4685 firm-year observations to identify specific accounting items driving LNBTDs. Findings reveal that deferred revenue, goodwill impairments, R&D, CapEx, environmental obligations, pensions, contingency liabilities, leases, and receivables are significant contributors, often generating substantial DTAs due to timing mismatches between book and tax recognition. Notably, high-tech industries, like the pharmaceutical, medical, and computers and software industries, exhibit pronounced LNBTDs, driven by upfront revenue recognition for tax purposes and deferred recognition for financial reporting, capitalization, amortization and depreciation effects, and other deferred tax components. Regression analyses confirm strong associations between these components and LNBTDs, with asymmetry in reversal patterns suggesting that initial differences do not always offset symmetrically over time. While prior research emphasizes large positive BTDs and tax avoidance, this study highlights economic and industry-specific characteristics as key LNBTD drivers, with limited evidence of earnings manipulation via deferred taxes. These insights enhance the value relevance of deferred tax disclosures and offer implications for reporting standards, tax policy, and research into BTD dynamics. Full article

Machine learning technologies have recently emerged as transformative tools for enhancing project management accuracy and efficiency. This study introduces a data-driven model that leverages the hybrid eXtreme Gradient Boosting-Simulated Annealing (XGBoost-SA) algorithm to predict the time and cost of construction projects. By accounting for the complexity of activity networks and uncertainties within project environments, the model aims to address key challenges in project forecasting. Unlike traditional methods such as Earned Value Management (EVM) and Earned Schedule Method (ESM), which rely on static metrics, the XGBoost-SA model adapts dynamically to project data, achieving 92% prediction accuracy. This advanced model offers a more precise forecasting approach by incorporating and optimizing features from historical data. Results reveal that XGBoost-SA reduces cost prediction error by nearly 50% and time prediction error by approximately 80% compared to EVM and ESM, underscoring its effectiveness in complex scenarios. Furthermore, the model’s ability to manage limited and evolving data offers a practical solution for real-time adjustments in project planning. With these capabilities, XGBoost-SA provides project managers with a powerful tool for informed decision-making, efficient resource allocation, and proactive risk management, making it highly applicable to complex construction projects where precision and adaptability are essential. The main limitation of the developed model in this study is the reliance on data from similar projects, which necessitates additional data for application to other industries. Full article

As sustainability rises in significance in the construction industry, there is a need to adopt new project management techniques to help achieve increases in sustainability objectives. There have been several research works that have investigated the integration of sustainability in construction. However, there is a gap in addressing performance measurement and evaluation during the construction phase. Traditional project performance evaluation methods use the Earned Value Management (EVM) technique to assess time, cost, and scope performance. However, EVM does not address the performance of sustainability goals. The main objective of this paper is to develop a new project controls method for sustainable construction projects. Sustainability performance indicators can play an essential role in advancing the practice of sustainable construction. Accordingly, a Sustainable Earned Value Management (SEVM) model incorporating sustainability indicators was developed to monitor the attainment of sustainability objectives in construction projects in addition to the traditional objectives. The proposed SEVM model uses the construction planning optimization model to prepare the baseline plan to monitor the project’s time, cost, and sustainability performance. The proposed model enhances the monitoring and control of sustainable construction projects in terms of time, cost, and sustainability using sustainability indicators. Full article

The prediction of bankruptcy risk poses a formidable challenge in the fields of economics and finance, particularly within the healthcare industry, where it carries significant economic implications. The burgeoning field of healthcare electronic commerce, continuously evolving through technological advancements and changing regulations, introduces additional layers of complexity. We collected financial data from 1265 U.S. healthcare industries to predict bankruptcy based on 40 financial ratios using multi-class classification machine learning models across various industry subsectors and market capitalizations. The exceptionally high post-tuning accuracy rates, exceeding 90%, along with high-performance metrics solidified the robustness and exceptional predictive capability of the gradient boosting model in bankruptcy prediction. The results also demonstrate the power and sensitivity of financial ratios in predicting bankruptcy based on financial ratios. The Altman models highlight the return on investment (ROI) as the most important parameter for predicting bankruptcy risk in healthcare industries. The Ohlson model identifies return on assets (ROA) as an important ratio specifically for predicting bankruptcy risk within industry subsectors. Furthermore, it underscores the significance of both ROA and the enterprise value to earnings before interest and taxes (EV/EBIT) ratios as important parameters for predicting bankruptcy based on market capitalization. Recognizing these ratios enables proactive decision making that enhances resilience. Our findings contribute to informed risk management strategies, allowing for better management of healthcare industries in crises like those experienced in 2022 and even on a global scale. Full article

The purpose of this study was to examine the determinants of cash distribution options by critically considering the effects of earnings, dividends, firm size, and economic value added. The distribution of cash dividends to shareholders serves as a basic means by which shareholders receive returns on their investments, so it is essential to examine share repurchases alongside dividends to enhance management’s efforts in maximising shareholder value. This study utilised panel data from 52 companies listed on the Johannesburg Security Exchange (JSE) that engaged in open market share repurchases for at least 2 years between 2000 and 2019. The data were extracted from the IRESS database. The panel data regression model was fitted with the ordinary least squares (OLS), difference generalised moment method (Diff-GMM), system generalised moment method (Sys-GMM), and least-squares dummy variable correction estimator (LSDVC). The findings revealed that there was a positive and significant relationship between the earnings per share and the payoff flexibility, implying that there was an inherent flexibility of repurchases as a payout option in the sampled firms. Additionally, the study revealed a significant negative relationship between the firm size, economic value added, and payoff flexibility. This suggests that larger companies tend to distribute a lower proportion of their earnings as share repurchases and opt for higher cash dividends instead. The implications of these findings provide financial managers with valuable insights into the role of share repurchases as a cash distribution choice. By recognising share repurchases as a viable option, financial managers can enhance their efforts to create and maximise shareholder value, particularly in emerging market settings. This evidence should encourage financial managers to recognise share repurchases more as a distribution choice, diffusing the tension regarding share repurchases replacing the payment of cash dividends and some doubt that they may not possess attributes complimentary to cash dividends. The study recommended relevant academic, industry, and policy implications in the South African context. Full article

Proper planning and management of construction projects have long been regarded as a necessity. The ability to make sound decisions and solve problems using appropriate performance reports related to the project implementation process are the two most key factors in controlling the performance of construction project management. Even though these factors considerably contribute to controlling precise project performance, previous research has failed to investigate them to their fullest potential. Therefore, this research seeks to fill the existing gap by determining the influential factors on construction project management performance through earned value-based value engineering strategy. In this line, a comprehensive literature analysis was undertaken to extract the influential factors on construction project management performance. Then, three rounds of a Delphi survey were conducted to consolidate the influential factors. There were a total of 39 factors that were grouped into four categories. The identified influential factors were then evaluated through the analysis of quantitative data. The findings showed that the dimension of “Engineering economics” was ranked first in terms of importance, followed by “Project management performance”, “Value engineering approach”, and “Earned value management” at the second to fourth ranks, respectively. The overall ranking of the factors placed “Project Stakeholder Management” in the first position and “Project Management Software” in the bottom place. It is anticipated that the key findings and effective recommendations of this study will considerably contribute to the improvement of decisions on project planning and improve the performance of construction project management while enhancing different stakeholders’ understanding of the most influential factors on the performance of construction project management. Full article

Financial management is important for the construction sector, as construction companies contribute to the development of countries. Malaysia encourages the construction sector to develop advanced infrastructure related to transport and housing. Financial management is a multi-criteria decision making (MCDM) problem, since companies have to consider multiple goals in order to make the optimal decision. Therefore, goal programming is proposed in financial management to solve optimization in MCDM problems. According to previous studies, there has been no comprehensive study conducted on optimization and comparison among the construction companies with a goal programming model. Thus, this study aims to propose a goal programming model to optimize and compare the financial management of listed construction companies in Malaysia for benchmarking purposes. Six goals of financial management, namely the total assets, total liabilities, equity, profit, earnings, and optimum management of construction companies are examined in this study. The results of this study show that the goal programming model is able to determine the optimal solution and goal achievement for each construction company. In addition, the model value can be further enhanced according to the optimal solution of the goal programming model. This study provides insights to the listed construction companies in Malaysia to identify the potential improvement based on the benchmarking and optimal solution of the goal programming model. Full article

The purpose of this article is to examine the academic literature about the function, structure, calculation, and weaknesses of economic value added (EVA). EVA has been used as a measure of economic profit and captures the inadequacies of using traditional rates of return. In addition, this article tackles the main residual earnings (RI) modifications used to calculate EVA. A keyword search for publications was conducted in early 2022. This study couples an inferential analysis with descriptive analyses of the existing research. The articles were sorted into different clusters based on bibliographic coupling analysis. This study identifies the main areas and current dynamics of EVA research while evaluating the quality and impact of the scientific output. Three broad themes emerged from the analysis of the cluster related to the use and application of EVA: residual income and valuation, financial performance, and performance management. In doing so, we hope to enhance the understanding and contributions of EVA research to advance its theory and practice. Full article

A corporate socially responsible-focused approach adds value to a firm in the form of financial benefits in addition to improving its corporate image. To meet the demands of various stakeholders, including consumers, employees, and shareholders, and to produce high-quality financial reporting, some managers participate in CSR initiatives. The investigation of the relationship between corporate social responsibility and earnings management in publicly listed Visegrad companies is the main aim of the paper. The purpose is to identify the correlation between the CSR concept (measured by ESG score) and earnings management behavior determined by discretionary accrual levels (using the modified Jones model). To ascertain the association between CSR and earnings/discretionary accrual levels or to describe the major changes in the development of these variables, several statistical techniques were applied (correlation analysis, one-way ANOVA, and one-way ANOVA with repeated measures). As this is a pioneering study in the Visegrad environment (analyzing 35 publicly listed enterprises reporting ESG score), the research findings may have significant policy implications for decision-makers, regulators, auditors, and investors in their efforts to restrict earnings management techniques and enhance the quality of financial reporting. Full article