Designing a Conceptual Model for Digital Advertising Optimization Based on Cognitive Attention and Engagement

RAJABVAND, REZVAN; Paslary, Payam; Ranjbar, Mohammad Hossein; Safari, Mir Shahram

doi:10.22054/jims.2026.93984.3050

Designing a Conceptual Model for Digital Advertising Optimization Based on Cognitive Attention and Engagement

Articles in Press

Document Type : Research Paper

Authors

REZVAN RAJABVAND ¹

payam paslary ²

Mohammad Hossein Ranjbar ³

mir shahram safari ⁴

¹ گروه مدیریت بازرگانی ، واحد بین الملل قشم، دانشگاه آزاد اسلامی،بندرعباس، ایران

² Department of Business Management, BA.C. , Islamic Azad University, Bandar abbas, Iran

³ Department of Accounting and Finance, BA.C., Islamic Azad University, Bandar Abbas, Iran.

⁴ Department of Neuroscience, Faculty of Advanced Technologies in Medicine, Neuroscience and Cognition Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

https://doi.org/10.22054/jims.2026.93984.3050

Abstract

In the contemporary era, the inefficiency of traditional metrics in digital advertising and their inability to assess the quality of cognitive engagement within the context of the “attention economy” have posed a significant challenge for intelligent marketing. This study aims to design a conceptual model for the optimization of digital advertising based on the cognitive constructs of “Attention” and “Cognitive Engagement.” The research employed a qualitative approach utilizing thematic analysis. The statistical population consisted of experts in cognitive science, digital marketing, and information technology, from which 15 individuals were selected via purposive sampling. Data were collected through semi-structured interviews and analyzed using open, axial, and selective coding methods. The validity of the findings was confirmed through member checking and data triangulation, while reliability was ensured via parallel coding. The research findings indicate that advertising optimization can be explained through four primary axes: Cognitive Attention Engineering, Dynamics of Interaction and Deep Engagement, Technological and Algorithmic Infrastructures, and Cultural-Ethical Ecosystem. Results demonstrate that an optimal advertisement must function as a meaning-making platform that, by managing cognitive load and balancing content challenge with cognitive skill, elevates behavioral conversion rates to sustainable persuasion. This study highlights the necessity of transitioning from a paradigm of behavior-based advertising to one based on real-time cognitive states within the national digital ecosystem

Keywords

Digital Advertising

Cognitive Attention

Cognitive Engagement

Attention Economy

Advertising Optimization

Subjects