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Titlebook: Handbook of Big Data and Analytics in Accounting and Auditing; Tarek Rana,Jan Svanberg,Alan Lowe Book 2023 The Editor(s) (if applicable) a

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發(fā)表于 2025-3-21 18:06:27 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Handbook of Big Data and Analytics in Accounting and Auditing
編輯Tarek Rana,Jan Svanberg,Alan Lowe
視頻videohttp://file.papertrans.cn/421/420874/420874.mp4
概述Presents analysis by the leading scholars in the field on their particular area of research expertise.Provides critical evaluations and guidance from all branches of accounting and auditing.Illustrate
圖書封面Titlebook: Handbook of Big Data and Analytics in Accounting and Auditing;  Tarek Rana,Jan Svanberg,Alan Lowe Book 2023 The Editor(s) (if applicable) a
描述.This handbook collects the most up-to-date scholarship, knowledge, and new developments of big data and data analytics by bringing together many strands of contextual and disciplinary research. In recent times, while there has been considerable research in exploring the role of big data, data analytics, and textual analytics in accounting, and auditing, we still lack evidence on what kinds of best practices academics, practitioners, and organizations can implement and use..?.To achieve this aim, the handbook focuses on both conventional and contemporary issues facing by academics, practitioners, and organizations particularly when technology and business environments are changing faster than ever. All the chapters in this handbook provide both retrospective and contemporary views and commentaries by leading and knowledgeable scholars in the field, who offer unique insights on the changing role of accounting and auditing in today’s data andanalytics driven environment..?.Aimed at academics, practitioners, students, and consultants in the areas of accounting, auditing, and other business disciplines, the handbook provides high-level insight into the design, implementation, and worki
出版日期Book 2023
關(guān)鍵詞Accounting; Data Analytics; Textual Analytics; Big Data; Business Intelligence
版次1
doihttps://doi.org/10.1007/978-981-19-4460-4
isbn_softcover978-981-19-4462-8
isbn_ebook978-981-19-4460-4
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Singapor
The information of publication is updating

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https://doi.org/10.1007/978-3-540-30033-5In concluding the chapter, the use of Artificial Intelligence to predict deficient sustainability reporting practices caused by behavioral issues relating to incentives to improper sustainability reporting is identified.
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Ressourcenorientierte Psychotherapiegagement and help to address cognitive load challenges experienced by students. This paper also provides a case of detailed, practical insights for academics interested in digitizing and gamifying pedagogy for learning, while citing the benefits of serious game use in verifying assessment authenticity.
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Artificial Intelligence and Environmental, Social and Governmental Issues: A Current PerspectiveIn concluding the chapter, the use of Artificial Intelligence to predict deficient sustainability reporting practices caused by behavioral issues relating to incentives to improper sustainability reporting is identified.
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Data Sources for Predictive Analytics and Decision Making: A Management Perspectiveot their use) of social media positively influences the preference for non-traditional data sources. These findings indicate that non-traditional data sources appear to coexist and become complementary to traditional accounting sources and do not substitute them.
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