The Effect of Trust and Ease of Use of E-filling on Tax Compliance in the Era of Big Data Analytics

A Big Data maturity model (BDMM) is one of the key tools for Big Data assessment and monitoring, and a guideline for maximizing the usage and opportunity of Big Data in organizations. The development of a BDMM for SMEs is a new concept and is challenging in terms of development, application, and adoption. This article aims to create the novel online adaptive BDMM via responsive web application for SMEs. We develop the BDMM API and a responsive web application for easy access via mobile phone. We developed a model by analyzing the factors impacting the success of implementing Big Data Analytics (BDA) in SMEs based on literature reviews. The model was verified by conducting a survey of 180 SMEs in Thailand, interviewed against four extracted domains. Then, the scoring and classified levels for the model was developed through Latent Class Analysis (LCA) to depict four levels of each domain and four final maturity levels to create an adaptive model. As the experimental results with 33 users including executive officers, managers, IT and data analytic officers .The user acceptance for our mobile application using TAM indicates that executive officers group and non-executive group satisfied perceived usefulness, perceived ease of use, and intention to use factor. Use cases of the application include SMEs monitoring for their Big Data Analytics capability for improvement, and the Government Agency providing proper support on SMEs’ level of competency.

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Big Data Analytics in IRS Audit Procedures and Its Effects on Tax Compliance: A Moderated Mediation Analysis

Journal of the American Taxation Association ◽

10.2308/jata-2020-038 ◽

2021 ◽

Author(s):

Erica Neuman ◽

Robert Sheu

Keyword(s):

Big Data ◽

Data Analytics ◽

Big Data Analytics ◽

Tax Compliance ◽

Moderated Mediation ◽

Perceived Fairness ◽

Fair Information Practices ◽

Moderated Mediation Model ◽

Advanced Technologies ◽

The Relationship

Big data analytics could be a panacea for the IRS by enabling creation of taxpayer profiles to better capture noncompliance using artificial intelligence and machine learning, requiring fewer costly manpower hours. Privacy, fair information practices, and embedded biases are critiques of such practices, and it is unknown how taxpayers will respond. Deterrence theory suggests improved audit effectiveness will increase compliance but excludes elements of tax morale, including perceived fairness. We find evidence supporting a moderated mediation model where procedural fairness mediates the relationship between audit procedures and tax compliance, moderated by participatory monitoring, which captures how effects vary when taxpayers willingly increase traceability of their income by advertising online. When taxpayers advertise business online, use of advanced technologies in audit selection significantly increases compliance with no significant effect on perceived fairness; when they do not, use of advanced technologies has no effect on compliance, but significantly decreases perceived fairness.

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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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