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Готові списки джерел за темами / Detecting Earnings Management

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Добірка наукової літератури з теми "Detecting Earnings Management"

Автор: Grafiati

Опубліковано: 3 червня 2025

Оновлено: 31 липня 2025

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Статті в журналах з теми "Detecting Earnings Management"

1

Shanwari, Imran, and S. M. Aamir Shah. "Detecting Earning Management: Deferred Taxes vs Accruals: A Pakistani Perspective." Journal of Accounting and Finance in Emerging Economies 1, no. 2 (2015): 111–34. http://dx.doi.org/10.26710/jafee.v1i2.68.

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Objective: Earning Management has been one of the major areas of accounting research which has received a great attention in the past and also quite recently. Detecting earning management has always been one of the major areas of concern for the researchers. Earnings Management is pervasive. There are a number of models available to Detect and measure the earnings management activity. Methodology: The accrual models are the most used models to proxy the discretionary accruals and the earnings management. The effectiveness of the accrual models is somewhat skeptical at times when research

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2

Martorelli, Michael A. "Detecting Earnings Management (a review)." Financial Analysts Journal 60, no. 3 (2004): 92–93. http://dx.doi.org/10.2469/faj.v60.n3.2626.

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3

Rahayu, S. K. "Tax Audit Effectiveness: Detection of Tax Sheltering Through Implication Book Tax Differences on Earnings Management." Proceeding of International Conference on Business, Economics, Social Sciences, and Humanities 3 (December 1, 2022): 247–56. http://dx.doi.org/10.34010/icobest.v3i.143.

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The objectives of the study were to (1) analyze the effectiveness of tax audits by detecting earnings management and tax sheltering and those carried out by audited taxpayers, (2) to examine the effect of Book Tax Difference on earnings management, and (3) to examine the impact of earnings management on tax sheltering. This research uses a quantitative approach with philosophical considerations of positivism, belongs to applied research, and includes descriptive research. The research design used is correlational research, namely testing and estimating the relationship of many variables either

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4

Abu Bakar, Dalila, Mohamed Hisham Haji Yahya, and Norhuda Abdul Rahim. "A Review Analysis of Earnings Management Report Disclosure." Journal of Governance and Integrity 6, no. 1 (2023): 462–69. http://dx.doi.org/10.15282/jgi.6.1.2023.9106.

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Occupational fraud costs the average firm 5% of its annual income. This equates to a $3.7 trillion yearly loss due to fraud worldwide. The bulk of reported losses (51.9%) were less than $200,000. Financial statement fraud is the most expensive type of occupational fraud, with an average loss of $1,000,000. The most popular methods of detecting fraud are tips (42.2%), management reviews (16.0%), and internal audits (14.1%). Surprisingly, external audits (done by CPA firms) account for just about 3.0% of fraud detection. The majority of cases of fraud identified through tips come from workers (4

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5

Phillips, John, Morton Pincus, and Sonja Olhoft Rego. "Earnings Management: New Evidence Based on Deferred Tax Expense." Accounting Review 78, no. 2 (2003): 491–521. http://dx.doi.org/10.2308/accr.2003.78.2.491.

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We assess the usefulness of deferred tax expense in detecting earnings management. Assuming greater discretion under GAAP than under tax rules, and assuming managers exploit such discretion to manage income upward primarily in ways that do not affect current taxable income, then such earnings management will generate book-tax differences that increase deferred tax expense. Our results provide evidence consistent with deferred tax expense generally being incrementally useful beyond total accruals and abnormal accruals derived from two Jones-type models in detecting earnings management to avoid

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6

DECHOW, PATRICIA M., AMY P. HUTTON, JUNG HOON KIM, and RICHARD G. SLOAN. "Detecting Earnings Management: A New Approach." Journal of Accounting Research 50, no. 2 (2012): 275–334. http://dx.doi.org/10.1111/j.1475-679x.2012.00449.x.

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7

Höglund, Henrik. "Detecting earnings management with neural networks." Expert Systems with Applications 39, no. 10 (2012): 9564–70. http://dx.doi.org/10.1016/j.eswa.2012.02.096.

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8

Susana, Callao, I. Jarne José, and Wróblewski David. "DETECTING EARNINGS MANAGEMENT INVESTIGATION ON DIFFERENT MODELS MEASURING EARNINGS MANAGEMENT FOR EMERGING EASTERN EUROPEAN COUNTRIES." International Journal of Research - Granthaalayah 5, no. 11 (2017): 222–59. https://doi.org/10.5281/zenodo.1095448.

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Анотація:

Earnings management has received considerable attention as numerous papers were investigated different hypotheses. However, there is still no consensus on how efficiently detect and measure earnings managements. Nevertheless, most authors use methodology based on accruals, sophisticated models that attempt to separate total accruals into discretionary and nondiscretionary components. We may find wide range of use of alternative models to measure earnings management. Nevertheless, the researchers typically used five the most popular models: the Jones (1991) model, the modified Jones model (Dech

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Kourdoumpalou, Stavroula. "Detecting tax evasion when tax and accounting earnings match." Corporate Ownership and Control 14, no. 2 (2017): 289–95. http://dx.doi.org/10.22495/cocv14i2c2p1.

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This paper attempts to review on how the effectiveness of board of directors and the executive compensations are moderated by internal ownership such as managerial and family ownership to mitigate earnings management. Most of prior studies focused on the traditional interaction among corporate governance mechanisms and earnings management, thus neglected that the variance of these practices that can be attributed to the business environment and the nature of ownership structure. This paper revisits the literature on the relationship between the factors of effectiveness of the board of director

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Callao, Susana, José I. Jarne, and David Wróblewski. "DETECTING EARNINGS MANAGEMENT INVESTIGATION ON DIFFERENT MODELS MEASURING EARNINGS MANAGEMENT FOR EMERGING EASTERN EUROPEAN COUNTRIES." International Journal of Research -GRANTHAALAYAH 5, no. 11 (2017): 222–59. http://dx.doi.org/10.29121/granthaalayah.v5.i11.2017.2351.

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Анотація:

Earnings management has received considerable attention as numerous papers were investigated different hypotheses. However, there is still no consensus on how efficiently detect and measure earnings managements. Nevertheless, most authors use methodology based on accruals, sophisticated models that attempt to separate total accruals into discretionary and nondiscretionary components. We may find wide range of use of alternative models to measure earnings management. Nevertheless, the researchers typically used five the most popular models: the Jones (1991) model, the modified Jones model (Dech

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Дисертації з теми "Detecting Earnings Management"

1

Perols, Johan L. "Detecting Financial Statement Fraud: Three Essays on Fraud Predictors, Multi-Classifier Combination and Fraud Detection Using Data Mining." [Tampa, Fla] : University of South Florida, 2008. http://purl.fcla.edu/usf/dc/et/SFE0002486.

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Nguyen, Nguyet Thi Minh. "Earnings management : detection, application and contagion." Thesis, University of Kent, 2017. https://kar.kent.ac.uk/59823/.

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The accounting scandals in the 2000s and 2010s have led to a number of large-scale reforms in financial reporting and corporate governance regulations around the world, and still attract a lot of public debates recently. In that context, the demand for further knowledge on earnings management is very topical. What we have known is earnings management does exist. What we have not known, however, seems still overwhelming. We need to know more about issues such as how earnings management could be detected, to what extent earnings management has an impact on investment decisions, what drives earni

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3

Garner, Jeffrey Lee. "Forensic Detection for Earnings Management in Selected Code Law Nations of Europe." Thesis, Walden University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10932861.

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<p> This study investigated earnings management in European firms. The private investors became victims of manipulated earnings where few laws offered regulatory oversight. The study forensically examined the attributes of earnings management identified using a discretionary accrual model published in Jones’ work and Schippers’ work. The firms’ managers should fulfil agency theory when they made reporting decisions, and they should act in the investors’ best interests to fulfil stewardship theory. The managers failed as they seemed to favor insiders when they reported m

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Garner, Jef Lee. "Forensic Detection for Earnings Management in Selected Code Law Nations of Europe." ScholarWorks, 2018. https://scholarworks.waldenu.edu/dissertations/5863.

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Анотація:

This study investigated earnings management in European firms. The private investors became victims of manipulated earnings where few laws offered regulatory oversight. The study forensically examined the attributes of earnings management identified using a discretionary accrual model published in Jones' work and Schippers' work. The firms' managers should fulfil agency theory when they made reporting decisions, and they should act in the investors' best interests to fulfil stewardship theory. The managers failed as they seemed to favor insiders when they reported manipulated earnings to outsi

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5

Tun-Chiao, Chang, and 張惇喬. "Detecting earnings management." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/15326460099048250097.

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碩士<br>國立臺灣大學<br>會計學研究所<br>93<br>When Researchers in Taiwan deal with earnings-management-related issues, they adopt accrual- based models frequently. Especially, the Healy, DeAngelo, Jones, Modified Jones, and Industry Model are most commonly considered among these accrual-based models. However, there is no study about the fitness of these five models when they are applied to the Taiwan capital market. This article adopts Dechow and Sloan (1995)’s methodology. We build two samples which probably lead to the type I error to access the relative specification of these five models. Also, we prepa

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Van, de Wouw Paula. "Detecting earnings management: the South African evidence." Thesis, 2016. http://hdl.handle.net/10539/20192.

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Yin, Chen Chun, and 陳俊尹. "Detecting Long-run Stock Returns and Earnings Management of IPOs." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/92951848002976310614.

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碩士<br>輔仁大學<br>金融研究所<br>90<br>Consistent with the outcomes from several studies related to long-run stock performance of IPOs, we find that the IPO firms underperform over a three-year holding period. Among them, only the electronic companies post double-digit positive returns even though they are inferior to their peers. Comparing with non-electronics companies of IPOs, they are still a good investment if the investors really want to buy and hold the stock of IPO. To test whether the higher magnitude of earnings management prior to the issuance will cause the issuing firms to post a poor stock

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林昱成. "An Empirical Study of Detecting Effectiveness of Detecting Business Earnings Management Using Cross-Sectional Two-Stage Regressions." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/56472837604875808971.

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碩士<br>逢甲大學<br>會計與財稅研究所<br>90<br>The main purposes of the study are to develop a new accruals model which labeled the “WHL model” and to empirically compare the relative examine specification and power effectiveness of Modified-Jones（Dechow et al.,1995）, Margin（Peasnell et al.,2000）and WHL model in detecting business income manipulations. In addition, we also develop a detecting abnormal related-party sales model-RPS model, and examine specification and power effectiveness of RPS model in detecting business related-party sales manipulations. The following conclusions are found in the

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Wang, Yi-Cheng, and 汪奕丞. "Applying Bayesian Network, Decision Tree, Rough Set Theory, and Back Propagation Network Analysis for Detecting Accrual Earnings Management." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/td74j6.

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碩士<br>中國文化大學<br>會計學系<br>102<br>Enterprise reliability in financial statements and management manipulated ac-cruals formed earnings management behavior has been a major topic of accounting. Previous studies in accrual earnings management are using traditional regression model. In recent years, a number of scholars have been doing research using data mining methods for accruals earnings management and accuracy was improved, but it is not enough to complete the whole literature. Therefore, this study use data mining method in the decision tree and back-propagation neural network to make predictio

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Chen, Pi-Hsia, and 陳碧霞. "Detection of quarterly earnings management." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/16455706381815516740.

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碩士<br>中原大學<br>會計研究所<br>95<br>This study examines specification and power tests results of alternative remedies to detecting earnings management and control extreme performance problems in discretionary accrual estimation. We use a simulation procedure developed by Brown and Warner (1980, 1985) to assess the power of each model. The power of the models is based on the inclusion of an artificially induced amount of accruals manipulation and the assessment of the different models’ ability to detect it. We focus on the specification of cross-sectional models of expected accruals using quarterly as

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Книги з теми "Detecting Earnings Management"

1

Detecting Earnings Management. Wiley, 2003.

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Zarowin, Paul. Estimation of Discretionary Accruals and the Detection of Earnings Management. Edited by Michael A. Hitt, Susan E. Jackson, Salvador Carmona, Leonard Bierman, Christina E. Shalley, and Douglas Michael Wright. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780190650230.013.20.

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This article reviews recent research on the estimation of discretionary accruals and the detection of earnings management. There has been an explosive growth in research on accrual earnings management over the past twenty years, and almost all has used the Jones (1991) model or one of its close derivatives. Nevertheless, a growing literature has addressed the model’s problems and attempted to improve its estimation of discretionary accruals. The model’s incomplete characterization of how nondiscretionary accruals are determined by the firm’s operations can cause either Type I or Type II errors

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Zarowin, Paul. Estimation of Discretionary Accruals and the Detection of Earnings Management. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199935406.013.20.

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Частини книг з теми "Detecting Earnings Management"

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Kadhim, Yahia Ali, and Safaa Ahmed Mohammed Al Ani. "The Effect of Using an Accounting Information System Based on Artificial Intelligence in Detecting Earnings Management to Enhance the Sustainability of Economic Units." In Studies in Systems, Decision and Control. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-62106-2_26.

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2

Sanad, Zakeya. "Machine Learning and Earnings Management Detection." In Studies in Computational Intelligence. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73057-4_6.

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3

Kang, Sohyeon, and Sorah Park. "Artificial Intelligence-based Detection and Prediction of Corporate Earnings Management." In Fintech with Artificial Intelligence, Big Data, and Blockchain. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6137-9_8.

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4

"Detecting Earnings Management." In Asian Financial Statement Analysis. John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119204763.ch4.

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Callao, Susana, José Ignacio Jarne, and David Wroblewski. "How Different Corporate Governance and Corporate Social Responsibility Impact Earnings Management." In Advances in Finance, Accounting, and Economics. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7596-3.ch010.

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Nowadays, companies increasingly focus on corporate concerns as they are in need of the detecting and controlling management activities in order to improve good business practices, objectivity, and integrity. This research addresses the question of the role of corporate governance and corporate social responsibility in earnings management. Previous studies confirmed that both mechanisms play an important role in limiting earnings management. In this context, the objective of the study is to test whether the effectiveness of both in constraining earnings management is the same or vary within th

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6

Callao, Susana, José Ignacio Jarne, and David Wroblewski. "How Different Corporate Governance and Corporate Social Responsibility Impact Earnings Management." In Research Anthology on Developing Socially Responsible Businesses. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-5590-6.ch100.

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Nowadays, companies increasingly focus on corporate concerns as they are in need of the detecting and controlling management activities in order to improve good business practices, objectivity, and integrity. This research addresses the question of the role of corporate governance and corporate social responsibility in earnings management. Previous studies confirmed that both mechanisms play an important role in limiting earnings management. In this context, the objective of the study is to test whether the effectiveness of both in constraining earnings management is the same or vary within th

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7

Ebrahimi, Maryam. "The Detection of Profit Manipulation." In Advances in Social Networking and Online Communities. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-8235-0.ch009.

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Profit manipulation refers to bringing reported profits closer to the intended level, which is classified into categories of earnings management, falsification, and creative accounting practices. It is extremely difficult to detect manipulated financial statements using standard business audit procedures because there is a lack of knowledge about extensions and features of management fraud. Auditors have a shortage of the experience to detect falsified financial statements, and managers deliberately attempt to deceive auditors using new methods. The goal of this study is to review mathematical

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Bešlić Obradović, Dragana, Ivana Bešlić Rupić, and Bojan Rupić. "INVESTIGATING INCOME SMOOTHING: EMPIRICAL EVIDENCE FROM SERBIAN’S HOTEL COMPANIES." In 5th International Thematic Monograph: Modern Management Tools and Economy of Tourism Sector in Present Era. Association of Economists and Managers of the Balkans; Faculty of Tourism and Hospitality, Ohrid, North Macedonia, 2020. http://dx.doi.org/10.31410/tmt.2020.347.

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The flexibility in accounting standards and principles, lead to incentives for managers to show a good picture of the companies. It is logical and rational for managers to attempt to smooth income by using certain accounting devices to reduce the companies’ income fluctuation over time to improve relations with creditors, investors, and employees. Income smoothing enables companies to stabilize earnings and thereby increase earnings predictability. For detecting income smoothing through examining the financial statements Eckel’s (1981) approach (income variability approach) has been the most p

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Das, Ramesh Chandra. "Earnings Management Detection Using Digital Analysis: A Concept in Benford’s Law." In Research Developments in Arts and Social Studies Vol. 1. Book Publisher International (a part of SCIENCEDOMAIN International), 2022. http://dx.doi.org/10.9734/bpi/rdass/v1/3183e.

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Geetha, R., T. Veena, E. Kamalaban, Srinath Doss, Prashant Nair, and Turgay Ibrikci. "IoT-Enabled Steganography-Based Smart Agriculture Using Machine Learning Models in Industry 5.0." In Advances in Information Security, Privacy, and Ethics. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-2223-9.ch014.

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Farmers are facing a lot of hurdles in cultivation and earning profit out of it. The advancements in technology are growing rapidly and can be used by the farmers to increase their yield. This work enables the use of artificial intelligence-enabled Industry 5.0 in the field of agriculture. The farmers can manage their farms by using smart IoT-enabled technologies in three phases. The first stage is farm management where they can manage planting time and harvest. The second stage is internet of things (IoT)-enabled monitoring in which IoT devices such as node MCU, soil moisture sensor, and DHT1

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Тези доповідей конференцій з теми "Detecting Earnings Management"

1

Malkogianni, Ioanna, and Dimitrios Kourtidis. "Detecting Discontinuities in the Distribution of Earnings Around Zero as an Indication of Earnings Management." In ICPA 2024. MDPI, 2025. https://doi.org/10.3390/proceedings2024111012.

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Fernandes, Susana, Raul M. S. Laureano, Catarina Abrantes, and Luis M. S. Laureano. "Earnings management detection and its impact on european funds: a data analytics approach." In 2021 16th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, 2021. http://dx.doi.org/10.23919/cisti52073.2021.9476453.

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Dascalu, Iulian, Veronica Grosu, and Svetlana Mihailă. "Assessing conceptual dynamics and collaborative networks in forensic accounting through a bibliometric approach." In International scientific conference "Development Through Research and Innovation" IDSC-2025. Academy of Economic Studies, 2025. https://doi.org/10.53486/dri2025.53.

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This paper investigates how forensic accounting-particularly judicial and fiscal expertise-has evolved conceptually and collaboratively over the last quarter-century. A customised search of the Web of Science Core Collection retrieved 1 255 records (articles, book chapters and early-access papers, 2009-2025) filtered to the Business, Economics, Management and Finance categories. After preprocessing, the database was analysed with SciMAT to map thematic structure and longitudinal shifts. The science-mapping workflow (standardisation, theme detection, longitudinal overlay and network analysis) r

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Handoko, Bambang Leo, and Agata Laras Permana Gita Prastiwi. "Financial Statement Fraud Detection using Analysis of Corporate Social Responsibility Disclosure and Annual Report Readability with Earnings Management as Moderating Variable." In ICMECG 2022: 2022 The 9th International Conference on Management of e-Commerce and e-Government. ACM, 2022. http://dx.doi.org/10.1145/3549823.3549832.

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