Digital advertising fraud prediction using OLS regression

Ng, Kah Mun (2023) Digital advertising fraud prediction using OLS regression. Final Year Project, UTAR.

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Abstract

Digital advertising has become the essential tools for every business. The digital advertising budget is increasing over the years. There are more businesses transform to digital advertising during the pandemic, however, the beginner of advertiser might lack of knowledge on digital advertisement at the same time pouring extra capital into digital advertising. Furthermore, the fraudulent activity in digital advertisement is also increasing which is harming the current digital marketing environment as well as every party involved. This study examines the factors affect conversion fraud in digital advertising. A sample of 956 observation of computing generate data is used to examine the variables towards conversion fraud. The result shows that advertiser, ad log, item, goal, and ad slot have positive relationship towards conversion fraud.

Item Type:	Final Year Project / Dissertation / Thesis (Final Year Project)
Subjects:	H Social Sciences > HD Industries. Land use. Labor
Divisions:	Faculty of Accountancy and Management > Bachelor of International Business (Honours)
Depositing User:	Sg Long Library
Date Deposited:	06 Jul 2023 21:52
Last Modified:	06 Jul 2023 21:52
URI:	http://eprints.utar.edu.my/id/eprint/5671

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