Problem:
Programmatic advertising, defined as a digital advertising system grounded in real-time analysis of users’ behavioral data and instantaneous auction mechanisms, has emerged as one of the most significant approaches to the intelligent allocation of advertising budgets. Despite the rapid expansion of this system, the research literature still lacks a comprehensive and integrated understanding of its nature and operational mechanisms within platform-based ecosystems.
Method:
This study adopted a systematic literature review approach following the PRISMA framework. The search process was conducted across two major international databases—Scopus and Web of Science—and from an initial pool of 961 records, 19 relevant articles published in reputable journals were selected for detailed analysis. The data were coded using thematic analysis and subsequently organized into three conceptual layers, enabling the identification of dominant patterns, mechanisms, and theoretical orientations in the existing body of work.
Findings:
The analysis revealed that the nature of programmatic advertising can be interpreted through three core dimensions: (1) a technological dimension encompassing automation, data-driven processes, and machine learning; (2) an economic–managerial dimension involving allocation efficiency, brand safety, and multi-criteria decision-making; and (3) a behavioral–social dimension including user experience, privacy concerns, and platform trust. The interaction among these dimensions creates a dynamic, adaptive, and self-learning ecosystem.
Conclusion:
By proposing an integrated three-dimensional conceptual framework, the study contributes to advancing theoretical discourse in digital marketing and media management and fills a notable gap in both domestic and international literature.