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ALGORITHMIC BIAS IN DIGITAL ADVERTISING: ITS EFFECTS ON ETHICAL MARKETING PRACTICES Radhi , Shaher Rekan; Dakhyliy, Aysar Abduladheem
International Journal of Business, Law and Political Science Vol. 3 No. 4 (2026): International Journal of Business, Law and Political Science
Publisher : PT. Antis International Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61796/ijblps.v3i4.478

Abstract

Objective: This study examines the effect of algorithmic bias in digital advertising on ethical marketing practices in Iraqi organizations. The study focuses on three dimensions of algorithmic bias: demographic targeting bias, data-driven personalization bias, and algorithmic transparency and accountability deficiency. Ethical marketing practices were measured through fairness, transparency, privacy protection, accountability, non-discrimination, and respect for consumer rights. Method:The study adopted a quantitative approach based on a structured questionnaire distributed to a sample of 270 respondents working in advertising agencies, e-commerce companies, telecommunications firms, banking institutions, retail companies, technology companies, and related organizations in Iraq. The data were analyzed using reliability testing, KMO and Bartlett’s test, descriptive statistics, and generalized linear regression. Results: The results showed that the questionnaire had strong reliability, with Cronbach’s Alpha values ranging from 0.814 to 0.922, and strong construct validity, with an overall KMO value of 0.924. The descriptive results indicated high levels of awareness regarding algorithmic bias and ethical marketing practices. The regression results confirmed that the three dimensions of algorithmic bias had statistically significant effects on ethical marketing practices. Algorithmic transparency and accountability deficiency had the strongest effect, followed by data-driven personalization bias and demographic targeting bias. Novelty: The study concludes that ethical digital marketing requires systematic auditing of algorithms, stronger transparency, clear accountability mechanisms, responsible use of consumer data, and fair treatment of all consumer groups. .