Use of Big Data Analytics by Tax Authorities

2020 ◽

pp. 86-110

Author(s):

Brendan Walker-Munro

Keyword(s):

Big Data ◽

Thematic Analysis ◽

Data Analytics ◽

Due Process ◽

Big Data Analytics ◽

Federal Court ◽

Tax Administration ◽

Australian Context

This chapter provides a thematic analysis for the Australian context of the legality and challenges to the use of big data analytics to identify risk, conduct compliance action, and make decisions within the tax administration space. Recent federal court jurisprudence and research is discussed to identify common themes (i.e., privacy/opacity, inaccuracy/bias, and fairness/due process) currently influencing the legal treatment of big data analytics within the tax administration and compliance environment in Australia.

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Using big data analytics to improve efficiency of tax collection in the tax Administration of the Republic of Serbia

Ekonomika preduzeca ◽

10.5937/ekopre1808115a ◽

2019 ◽

Vol 67 (1-2) ◽

pp. 115-130

Author(s):

Jasna Atanasijević ◽

Dušan Jakovetić ◽

Nataša Krejić ◽

Nataša Krklec-Jerinkić ◽

Dragana Marković

Keyword(s):

Big Data ◽

Data Analytics ◽

Big Data Analytics ◽

Tax Administration ◽

Tax Collection ◽

Improve Efficiency ◽

The Republic

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A new theoretical understanding of big data analytics capabilities in organizations: a thematic analysis

Journal Of Big Data ◽

10.1186/s40537-021-00543-6 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Renu Sabharwal ◽

Shah Jahan Miah

Keyword(s):

Big Data ◽

Thematic Analysis ◽

Data Analytics ◽

Big Data Analytics ◽

Development Theory ◽

Research Model ◽

Theoretical Understanding ◽

The Past ◽

Validity Assessment

AbstractBig Data Analytics (BDA) usage in the industry has been increased markedly in recent years. As a data-driven tool to facilitate informed decision-making, the need for BDA capability in organizations is recognized, but few studies have communicated an understanding of BDA capabilities in a way that can enhance our theoretical knowledge of using BDA in the organizational domain. Big Data has been defined in various ways and, the past literature about the classification of BDA and its capabilities is explored in this research. We conducted a literature review using PRISMA methodology and integrated a thematic analysis using NVIVO12. By adopting five steps of the PRISMA framework—70 sample articles, we generate five themes, which are informed through organization development theory, and develop a novel empirical research model, which we submit for validity assessment. Our findings improve effectiveness and enhance the usage of BDA applications in various Organizations.

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Extending The Theoretical Understanding of Big Data Analytics Capabilities In Organizations: A Thematic Analysis

10.21203/rs.3.rs-820711/v1 ◽

2021 ◽

Author(s):

Renu Sabharwal ◽

Shah Jahan Miah

Keyword(s):

Big Data ◽

Thematic Analysis ◽

Data Analytics ◽

Big Data Analytics ◽

Development Theory ◽

Research Model ◽

Theoretical Understanding ◽

The Past ◽

Validity Assessment

Abstract Big Data Analytics (BDA) usage in industry has been increased markedly in recent years. As a data-driven tool to facilitate informed decision making, the need for BDA capability in organizations is recognized, but few studies have communicated an understanding of BDA capabilities in a way that can enhance our theoretical knowledge of using BDA in organizational domain. Big Data has been defined in various ways and , the past literature about classification of BDA and its capabilities is explored in this research . We conduct a literature review using PRISMA methodology, and integrate a thematic analysis using NVIVO12. By adopting five steps of PRISMA framework - , 70 sample articles we generate five themes, which informed through organization development theory, and develop a novel empirical research model which we submit for validity assessment. Our findings improve effectiveness and enhance the usage of BDA applications in various Organizations.

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Big Data Analytics for Tax Administration

Electronic Government and the Information Systems Perspective - Lecture Notes in Computer Science ◽

10.1007/978-3-030-27523-5_4 ◽

2019 ◽

pp. 47-57

Author(s):

Priya Mehta ◽

Jithin Mathews ◽

Sandeep Kumar ◽

K. Suryamukhi ◽

Ch. Sobhan Babu ◽

...

Keyword(s):

Big Data ◽

Data Analytics ◽

Big Data Analytics ◽

Tax Administration

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Extending Theoretical Understanding for Defining the Capabilities of Big Data Analytics in Organisations: a Thematic Analysis

10.21203/rs.3.rs-694446/v1 ◽

2021 ◽

Author(s):

Renu Sabharwal ◽

Shah Jahan Miah

Keyword(s):

Big Data ◽

Thematic Analysis ◽

Data Analytics ◽

Big Data Analytics ◽

Development Theory ◽

Theoretical Understanding ◽

Organisation Development ◽

Validity Assessment ◽

Academic Researchers

Abstract Big Data Analytics (BDA) have been proliferated to academic researchers and industry practitioners over the past few years. As a prominent data-driven decision application, the BDA capabilities in organisation have been recognised, but limited studies have successfully attempted to communicate an authentic understanding on BDA capabilities that may enhance the current theoretical knowledge. While big data have been defined in various ways with its characteristics of shared definitions, it is important to explore the classification of BDA and its capabilities considering its advantageous opportunities. This study conducts a review study adopting the well-known PRISMA methodology, integrating a thematic analysis approach using NVIVO12. The study analyses 70 elected sample articles for generating new insights of BDA, informing through organisation development theory and leading to this an empirical research model is outlined for further validity assessment. It is anticipated that the findings would be contributing to address dynamic clarity and relevance of adopting BDA application.

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Big Data Analytics: The Next Big Thing

The Management Accountant Journal ◽

10.33516/maj.v54i5.20-24p ◽

2019 ◽

Vol 54 (5) ◽

pp. 20

Author(s):

Dheeraj Kumar Pradhan

Keyword(s):

Big Data ◽

Data Analytics ◽

Big Data Analytics

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Strategy in Discovery Mode - Wie Big Data & Analytics strategisches Denken verdrängen kann

WiSt - Wirtschaftswissenschaftliches Studium ◽

10.15358/0340-1650-2020-5-11 ◽

2020 ◽

Vol 49 (5) ◽

pp. 11-17

Author(s):

Thomas Wrona ◽

Pauline Reinecke

Keyword(s):

Big Data ◽

Data Analytics ◽

Big Data Analytics

Big Data & Analytics (BDA) ist zu einer kaum hinterfragten Institution für Effizienz und Wettbewerbsvorteil von Unternehmen geworden. Zu viele prominente Beispiele, wie der Erfolg von Google oder Amazon, scheinen die Bedeutung zu bestätigen, die Daten und Algorithmen zur Erlangung von langfristigen Wettbewerbsvorteilen zukommt. Sowohl die Praxis als auch die Wissenschaft scheinen geradezu euphorisch auf den „Datenzug“ aufzuspringen. Wenn Risiken thematisiert werden, dann handelt es sich meist um ethische Fragen. Dabei wird häufig übersehen, dass die diskutierten Vorteile sich primär aus einer operativen Effizienzperspektive ergeben. Strategische Wirkungen werden allenfalls in Bezug auf Geschäftsmodellinnovationen diskutiert, deren tatsächlicher Innovationsgrad noch zu beurteilen ist. Im Folgenden soll gezeigt werden, dass durch BDA zwar Wettbewerbsvorteile erzeugt werden können, dass aber hiermit auch große strategische Risiken verbunden sind, die derzeit kaum beachtet werden.

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