ECONOMIC AND GOVERNANCE IMPLICATIONS OF AI-DRIVEN MARKETING SYSTEMS: A MIXED-METHODS STUDY ON PERFORMANCE, TRANSPARENCY, AND POLICY ALIGNMENT

This proposal examines the two aspects of AI marketing adoption, economic performance and ethical governance, through a mixed-methods study design. Quantitative methods will assess the effect of AI on efficiency in budgeting, labor productivity, and marketing return on investment. Qualitative interviews will test organizational challenges related to algorithmic bias, data clarity, and policy enforcement. By grounding itself in Normalization Process Theory (NPT) and Strategic Management theory, the research will construct a convergent model that pertains to marketing performance improvement through AI, as well as economic and ethical practices in decision-making. The findings of this study will strive to empower policymakers, business strategists, and information managers to appreciate high-level marketing trade-offs and synergies in the exploitation of AI.

Authors

Publication Details

Journal
Lex localis - Journal of Local Self-Government
Published
2025-08-25
DOI
https://doi.org/10.52152/arsynj63
Primary Topic
Big Data and Business Intelligence
Type
article
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article

ECONOMIC AND GOVERNANCE IMPLICATIONS OF AI-DRIVEN MARKETING SYSTEMS: A MIXED-METHODS STUDY ON PERFORMANCE, TRANSPARENCY, AND POLICY ALIGNMENT

Prof. Dr. Satya Subrahmanyam Roger Halabi
Lex localis - Journal of Local Self-Government
Big Data and Business Intelligence
article

ECONOMIC AND GOVERNANCE IMPLICATIONS OF AI-DRIVEN MARKETING SYSTEMS: A MIXED-METHODS STUDY ON PERFORMANCE, TRANSPARENCY, AND POLICY ALIGNMENT

Prof. Dr. Satya Subrahmanyam Roger Halabi
article en

Abstract

This proposal examines the two aspects of AI marketing adoption, economic performance and ethical governance, through a mixed-methods study design. Quantitative methods will assess the effect of AI on efficiency in budgeting, labor productivity, and marketing return on investment. Qualitative interviews will test organizational challenges related to algorithmic bias, data clarity, and policy enforcement. By grounding itself in Normalization Process Theory (NPT) and Strategic Management theory, the research will construct a convergent model that pertains to marketing performance improvement through AI, as well as economic and ethical practices in decision-making. The findings of this study will strive to empower policymakers, business strategists, and information managers to appreciate high-level marketing trade-offs and synergies in the exploitation of AI.

Lex localis - Journal of Local Self-GovernmentVol. 23(S4)
Openalex Percentile: Top 60%
Big Data and Business Intelligence
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