Tax avoidance research: exploring networks and dynamics of global academic collaboration

By:

De Vito, Antonio

Contributor(s):

Grossetti, Francesco

Material type: Text

TextSeries: SIDREA Series in Accounting and Business AdministrationPublication details: Springer Cham 2024Description: xiv, 175 pISBN:

9783031517648

Subject(s):

Tax planning

DDC classification:

343.05 DE

Summary: This book explores the intricate realm of tax avoidance, synthesizing existing empirical literature in the field. The work starts by exploring the theoretical underpinnings of tax avoidance, dissecting its unique features compared to tax evasion. It delves into measurement methodologies and dissects the determinants contributing to its prevalence. Moreover, it analyzes the economic consequences of tax avoidance, emphasizing its impact on critical accounting issues, including financial reporting transparency, cost of capital, and firm value. Next, the book offers a foundational understanding of graph theory, unveiling the core elements of networks, such as nodes and edges. The book covers the theoretical fundamentals and addresses the practical side of constructing networks based on real-world relational systems. It emphasizes the importance of effective data collection and representation methods and underscores the importance of optimizing network layouts for enhanced visual representation. Using network analysis, the book further offers a deep dive into empirical studies on tax avoidance over the past two decades, revealing insights into the collaborative nature of this stream of research. Finally, the book summarizes the key insights of the network analysis on tax avoidance. It underscores the dynamic nature of individual authors' roles and affiliations, shedding light on the collaborative dynamics within institutions (https://link.springer.com/book/10.1007/978-3-031-51765-5)

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Finance & Accounting	343.05 DE (Browse shelf(Opens below))	1	Available		007242

Table of content:
Introduction
Antonio De Vito, Francesco Grossetti
Pages 1-4
Exploring Tax Avoidance: A Synthesis of the Literature
Antonio De Vito, Francesco Grossetti
Pages 5-31
Network Analysis: A Mathematical Framework
Antonio De Vito, Francesco Grossetti
Pages 33-49
Networks of Tax Avoidance Research
Antonio De Vito, Francesco Grossetti
Pages 51-127
Conclusion
Antonio De Vito, Francesco Grossetti
Pages 129-132

[https://link.springer.com/book/10.1007/978-3-031-51765-5]

This book explores the intricate realm of tax avoidance, synthesizing existing empirical literature in the field. The work starts by exploring the theoretical underpinnings of tax avoidance, dissecting its unique features compared to tax evasion. It delves into measurement methodologies and dissects the determinants contributing to its prevalence. Moreover, it analyzes the economic consequences of tax avoidance, emphasizing its impact on critical accounting issues, including financial reporting transparency, cost of capital, and firm value. Next, the book offers a foundational understanding of graph theory, unveiling the core elements of networks, such as nodes and edges. The book covers the theoretical fundamentals and addresses the practical side of constructing networks based on real-world relational systems. It emphasizes the importance of effective data collection and representation methods and underscores the importance of optimizing network layouts for enhanced visual representation. Using network analysis, the book further offers a deep dive into empirical studies on tax avoidance over the past two decades, revealing insights into the collaborative nature of this stream of research. Finally, the book summarizes the key insights of the network analysis on tax avoidance. It underscores the dynamic nature of individual authors' roles and affiliations, shedding light on the collaborative dynamics within institutions

(https://link.springer.com/book/10.1007/978-3-031-51765-5)

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