The Ecological Delivery Paradox in the Programmatic Advertising System Under Predictive Marketing

Creative Commons License

KIRÇOVA İ., SAĞLAM M. H., ENGİNKAYA ERKENT E.

Systems, vol.13, no.12, 2025 (SSCI, Scopus)

  • Publication Type: Article / Article
  • Volume: 13 Issue: 12
  • Publication Date: 2025
  • Doi Number: 10.3390/systems13121059
  • Journal Name: Systems
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, Compendex, Directory of Open Access Journals
  • Keywords: carbon-aware bidding, data-driven marketing, ecological delivery paradox, greenwashing, marketing systems theory, programmatic advertising, reflexive thematic analysis, transparency, trust in advertising
  • Open Archive Collection: AVESIS Open Access Collection
  • Yıldız Technical University Affiliated: Yes

Abstract

Data-driven marketing analytics has advanced targeting and optimization, yet its underlying infrastructure now functions as a complex sociotechnical system with overlooked ecological costs. This study conceptualizes programmatic advertising through a systems lens. It introduces the Ecological Delivery Paradox, a structural incongruity where environmentally friendly advertising messages are transmitted via energy-intensive delivery pipelines. Using an interpretivist–abductive design, we conducted 38 in-depth interviews with consumers and professionals, which were analyzed using reflexive thematic analysis in MAXQDA. Results show that awareness of hidden delivery costs emerges through a concretization threshold and crystallizes into metaphors such as “clean message, dirty conduit,” which trigger differentiated cognitive–affective pathways. These pathways shape trust trajectories across four profiles: cliff erosion, slow seep, suspended risk, and resilient cores. System-level moderators, including rationalization buffers, efficiency beliefs, and the visibility of low-data alternatives, determine outcomes. The findings extend marketing systems theory by reframing greenwashing as message–infrastructure misalignment and by integrating delivery congruence into advertising trust models. We propose a data-driven control architecture that aligns predictive analytics with ecological proportionality through mechanisms such as lightweight creatives, carbon-aware bidding coefficients, frequency–data quotas, and ad-level transparency labels. This systemic approach advances legitimacy, audience trust, and sustainability as joint objectives in programmatic advertising.