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The current study aims to analyze the role of International Federation of Accountants (IFAC) in sustainability issues and its impact on the attitude of practitioners (auditors) in industrial companies. The current study relies on the analytical method, one of the tools of the inductive approach, by examining the literature of researchers, international and local organizations, publications, series, alerts, and topics dealt with by the IFAC, as well as reviewing studies, theoretical and applied research, periodicals, books, and statistics. And specialized publications for this subject, which is related to other sciences – such as – environmental science, economic, and political sciences. The study reached many results, the most important of which are: (1) The first half of the current decade has seen high interest from the IFAC, has led to the issuance of International Auditing and Assurance Standards Board (IAASB) international standard on assurance engagements 3410, (GHG) Statements. (2) Sustainability has become important to a growing number of enterprises, and may have a significant influence, in certain cases, the financial statements, also became the sustainability of the topics under increasing attention from users of financial statements. Thus, the financial statements will need a practitioner to take into consideration sustainability issues and a private greenhouse gas when auditing the financial statements. This study is distinguished by analyzing the role of the IFAC and the IAASB for the period from 1998 to 2023 regarding sustainability issues.

In a virtual interconnected digital space, the metaverse encompasses various virtual environments where people can interact, including engaging in business activities. Machine learning (ML) is a strategic technology that enables digital transformation to the metaverse, and it is becoming a more prevalent driver of business performance and reporting on performance. However, ML has limitations, and using the technology in business processes, such as accounting, poses a technology governance failure risk. To address this risk, decision makers and those tasked to govern these technologies must understand where the technology fits into the business process and consider its limitations to enable a governed transition to the metaverse. Using selected accounting processes, this study aims to describe the limitations that ML techniques pose to ensure the quality of financial information.

A grounded theory literature review method, consisting of five iterative stages, was used to identify the accounting tasks that ML could perform in the respective accounting processes, describe the ML techniques that could be applied to each accounting task and identify the limitations associated with the individual techniques.

This study finds that limitations such as data availability and training time may impact the quality of the financial information and that ML techniques and their limitations must be clearly understood when developing and implementing technology governance measures.

The study contributes to the growing literature on enterprise information and technology management and governance. In this study, the authors integrated current ML knowledge into an accounting context. As accounting is a pervasive aspect of business, the insights from this study will benefit decision makers and those tasked to govern these technologies to understand how some processes are more likely to be affected by certain limitations and how this may impact the accounting objectives. It will also benefit those users hoping to exploit the advantages of ML in their accounting processes while understanding the specific technology limitations on an accounting task level.

The current study uses an advanced machine learning method and aims to investigate whether auditors perceive financial statements that are principles-based as less risky. More specifically, this study aims to explore the association between principles-based accounting standards and audit pricing and between principles-based accounting standards and the likelihood of receiving a going concern opinion.

The study uses an advanced machine-learning method to understand the role of principles-based accounting standards in predicting audit fees and going concern opinion. The study also uses multiple regression models defining audit fees and the probability of receiving going concern opinion. The analyses are complemented by additional tests such as economic significance, firm fixed effects, propensity score matching, entropy balancing, change analysis, yearly regression results and controlling for managerial risk-taking incentives and governance variables.

The paper provides empirical evidence that auditors charge less audit fees to clients whose financial statements are more principles-based. The finding suggests that auditors perceive financial statements that are principles-based less risky. The study also provides evidence that the probability of receiving a going-concern opinion reduces as firms rely more on principles-based standards. The finding further suggests that auditors discount the financial numbers supplied by the managers using rules-based standards. The study also reveals that the degree of reliance by a US firm on principles-based accounting standards has a negative impact on accounting conservatism, the risk of financial statement misstatement, accruals and the difficulty in predicting future earnings. This suggests potential mechanisms through which principles-based accounting standards influence auditors’ risk assessments.

The authors recognize the limitation of this study regarding the sample period. Prior studies compare rules vs principles-based standards by focusing on the differences between US generally accepted accounting principles (GAAP) and international financial reporting standards (IFRS) or pre- and post-IFRS adoption, which raises questions about differences in cross-country settings and institutional environment and other confounding factors such as transition costs. This study addresses these issues by comparing rules vs principles-based standards within the US GAAP setting. However, this limits the sample period to the year 2006 because the measure of the relative extent to which a US firm is reliant upon principles-based standards is available until 2006.

The study has major public policy suggestions as it responds to the call by Jay Clayton and Mary Jo White, the former Chairs of the US Securities and Exchange Commission (SEC), to pursue high-quality, globally accepted accounting standards to ensure that investors continue to receive clear and reliable financial information globally. The study also recognizes the notable public policy implications, particularly in light of the current Chair of the International Accounting Standards Board (IASB) Andreas Barckow’s recent public statement, which emphasizes the importance of principles-based standards and their ability to address sustainability concerns, including emerging risks such as climate change.

The study has major public policy suggestions because it demonstrates the value of principles-based standards. The study responds to the call by Jay Clayton and Mary Jo White, the former Chairs of the US SEC, to pursue high-quality, globally accepted accounting standards to ensure that investors continue to receive clear and reliable financial information as business transactions and investor needs continue to evolve globally. The study also recognizes the notable public policy implications, particularly in light of the current Chair of the IASB Andreas Barckow’s recent public statement, which emphasizes the importance of principles-based standards and their ability to address sustainability concerns, including emerging risks like climate change. The study fills the gap in the literature that auditors perceive principles-based financial statements as less risky and further expands the literature by providing empirical evidence that the likelihood of receiving a going concern opinion is increasing in the degree of rules-based standards.

The purpose of this study is to determine the relationship between accounting fraud and corporate sustainability.

Companies listed on the Shenzhen Stock Exchange in 2019 are used to estimate a pooled ordinary least square regression model using panel data. Accounting fraud is represented by accounting disclosure, which is measured by its quality and timeliness, while corporate sustainability is measured by earnings management and corporate social responsibility.

Empirical findings support the hypothesis that the quality and timeliness of accounting disclosure have a statistically favorable impact on the management of company earnings and corporate social responsibility, respectively. Accounting fraud also has an impact on the sustainable development of the company.

Although the inferences of this study are limited to Chinese listed companies, this study may interest other scholars to explore similar topics.

To complete this case, students will need to access financial statements from the Securities and Exchange Commission’s webpage. The links are provided. Students will also need to review the conceptual framework that is typically covered in Intermediate 1 to respond to question 5.

This case is based on the three financial statement restatements that Weatherford International Ltd. made over an approximately 18-month period. The restatements were due to a fraud committed by manipulating the income tax accrual in the financial statements. The manipulation used was to overstate the amount of income used to calculate the dividend exclusion and then use a relatively high tax rate to calculate the resulting tax benefit. The tax rate used for the fraud was substantially more than Weatherford’s effective tax rate (ETR), which was a prominent part of the company’s strategic growth plan. The tax senior with the external auditors who reviewed the entry made for the dividend exclusion captured the inconsistency with the comment that “This [the entry] deserves a huh?” The case is intended for students in Intermediate 2, where financial statement restatements and their effect on the company’s financial statements are typically covered. During the years covered in this case, Weatherford was also under investigation for violations of the Foreign Corrupt Practices Act (FCPA). Weatherford’s FCPA violations included multiple instances of bribery, the inappropriate use of volume discounts, improper payments and kickbacks in the United Nation’s Oil for Food program. Weatherford received the eighth-largest fine in the history of FCPA violations (at that time) of $152m. Weatherford’s FCPA investigation expanded, and the company paid another $100m in fines for violations of sanctions law and export control law. This case focuses only on the fraudulent manipulation of the financial statements through the tax accrual and does not delve into the other investigations. However, the linkage between those investigations and the fraud in this case is Weatherford’s nonexistent internal controls.

This case was designed to be used in Intermediate 2 financial accounting classes to highlight financial statement restatements and review the conceptual framework and materiality. The students who used the case did not have difficulty with the tax aspect of the case. However, most of the students had taken one tax class previously or concurrently. If students have not had any exposure to tax, the instructor might want to walk students through the tax aspects of the case.

This paper aims to conduct a systematic review of the literature on the quality of integrated reports (IR) and highlight the gaps in the existing research to provide directions and suggestions for future research.

This study was conducted through a systematic literature review using content analysis based on 40 papers from the Scopus, Web of Science and EBSCOhost databases on IR quality. While reading the full-text papers, the authors found six additional papers referenced by the literature being reviewed that were relevant to IR quality. Thus, there were 46 papers in the final review. The analysis begins with the definition and dimension of IR quality and theoretical lenses. Furthermore, this study outlines constructs or variables used in the previous literature.

The authors found that most studies used the quantitative method (41 papers or 89%). Five papers in the literature used qualitative methods (11%). Most researchers (34 papers or 72%) defined IR quality as consistent with the International Integrated Reporting Council framework, specifically the eight content elements. In particular, with the constructs that make up the quality of the IR, variations between researchers were found. Furthermore, there were some gaps that could be the directions for future research.

The literature that provides academic knowledge about IR quality is still limited, and research on IR is still growing. The literature review conducted by this study can provide an overview of the current research positions on the quality of IR and directions for future research in this area.

This study intends to show corporate executives a framework demonstrating the quality of corporate reporting. It can impact not only investors as a specific stakeholder group but also other stakeholder groups.

To the best of the authors’ knowledge, this study is the first literature review to examine the quality of IR, thus providing a map of current research to suggest directions for future research. Most of the previous literature reviews have been focused on integrated reporting (IR) in general and not quality.

The purpose of this study is to examine the association between carbon emissions and earnings management (EM). This study also considers the effect of female CEOs on the association between carbon emissions and EM.

This study uses the carbon disclosure project (CDP) for carbon emissions data, the Compustat database for financial information and the ExecuComp database for female CEOs. The empirical sample of this study consists of 1,692 firm-year observations in the USA that voluntarily participated in the CDP survey from 2007 to 2015. Regression analysis and robustness tests are conducted for this study and both accrual and real EM are considered.

This study provides evidence that firms with female CEOs who voluntarily disclose their carbon emissions information engage in less real EM. Thus, the presence of female CEOs moderates the association between carbon emissions and EM. This study/paper also finds a positive association between carbon emissions and real EM, although there is an insignificant association between carbon emissions and accruals EM.

The association between carbon emissions and EM has important implications for investors, regulators and policymakers. This study suggests that policymakers should improve the conditions that promote inclusion of females in the top management positions to constrain EM.

This study focuses on the USA, which is one of the major contributors to carbon emissions in the world. The presence of female CEOs moderates the association between carbon emissions and EM and firms with female CEOs show a greater impact on EM.

The prolonged training time of the neural network (NN) has sparked considerable debate regarding their application in the field of optimization. The purpose of this paper is to explore the beneficial assistance of NN-based alternative models in inductance design, with a particular focus on multi-objective optimization and uncertainty analysis processes.

Under Gaussian-distributed manufacturing errors, this study predicts error intervals for Pareto points and select robust solutions with minimal error margins. Furthermore, this study establishes correlations between manufacturing errors and inductance value discrepancies, offering a practical means of determining permissible manufacturing errors tailored to varying accuracy requirements.

The NN-assisted methods are demonstrated to offer a substantial time advantage in multi-objective optimization compared to conventional approaches, particularly in scenarios where the trained NN is repeatedly used. Also, NN models allow for extensive data-driven uncertainty quantification, which is challenging for traditional methods.

Three objectives including saturation current are considered in the multi-optimization, and the time advantages of the NN are thoroughly discussed by comparing scenarios involving single optimization, multiple optimizations, bi-objective optimization and tri-objective optimization. This study proposes direct error interval prediction on the Pareto front, using extensive data to predict the response of the Pareto front to random errors following a Gaussian distribution. This approach circumvents the compromises inherent in constrained robust optimization for inductance design and allows for a direct assessment of robustness that can be applied to account for manufacturing errors with complex distributions.

Corporate Social Responsibility (CSR) reporting has been widely accepted as a vital tool for communicating with stakeholders on a range of social, environmental, and governance issues, but how companies define, interpret, apply, integrate, and communicate their CSR efforts and impacts in corporate reporting is anything but a straightforward task. The purpose of this chapter is to explore the concept of materiality in CSR reporting and demonstrate practical examples of good CSR and Sustainable Development Goals (SDGs) reporting practices. We chose the aviation industry because of its economic relevance, constant growth, and future expected changes in the aftermath of COVID-19. In addition, airlines affect many of the SDGs directly and indirectly with contending results. This chapter is timely because of the growing willingness by companies to integrate CSR and environmental, social, and governance (ESG) thinking into the corporate strategy and business operations using materiality assessment and enhancing their competitive advantage and ability to maintain long-term value and because ESG and ethical investing have become part of the mainstream investing. Thus, this chapter contributes to an understanding of the wide range of existing and new reporting frameworks and regulations and reinforces the importance of discussing how this diversity of approaches can affect the work toward worldwide comparability of CSR and sustainability reporting.

In typical model-based calibration, linearization errors are derived inevitably, and non-negligible negative impact will be induced on the identification results if the rotational kinematic errors are not small enough or the lengths of links are too long, which is common in the industrial cases. Thus, an accurate two-step kinematic calibration method minimizing the linearization errors is presented for a six-DoF serial robot to improve the calibration accuracy.

The negative impact of linearization on identification accuracy is minimized by removing the responsible linearized kinematic errors from the complete kinematic error model. Accordingly, the identification results of the dimension-reduced new model are accurate but not complete, so the complete kinematic error model, which achieves high identification accuracy of the rest of the error parameters, is combined with this new model to create a two-step calibration procedure capable of highly accurate identification of all the kinematic errors.

The proportions of linearization errors in measured pose errors are quantified and found to be non-negligible with the increase of rotational kinematic errors. Thus, negative impacts of linearization errors are analyzed quantitatively in different cases, providing the basis for allowed kinematic errors in the new model. Much more accurate results were obtained by using the new two-step calibration method, according to a comparison with the typical methods.

This new method achieves high accuracy with no compromise on completeness, is easy to operate and is consistent with the typical method because the second step with the new model is conveniently combined without changing the sensors or measurement instrument setup.