المجلة الدولية للاداء الاقتصادي
Volume 8, Numéro 2, Pages 251-268
2025-12-20
Authors : Amina Lahmari . Khaled Redjem . Doaa Shohaieb .
This study employs a qualitative adaptation of the Autoregressive Distributed Lag (ARDL) model to examine the interrelationships between artificial intelligence (AI) adoption, big data utilization, customer trust, and global marketing performance with projections toward 2030. Using annual data from 2020-2024, the analysis reveals strong positive long-term relationships between AI/big data adoption and marketing performance, while highlighting the complex mediating role of customer trust in this ecosystem. The findings indicate that AI demonstrates the largest impact coefficient (2.71), followed by big data (1.22) and customer trust (0.89). The bounds test confirms cointegration (F-statistic = 5.90 > critical value = 4.10), establishing a long-run equilibrium relationship. Projections suggest marketing performance will reach 11.3% by 2030, with AI contributing 4.1%, big data 2.8%, and customer trust 1.5% to this growth. However, these results are constrained by the limited sample size (5 years) and require cautious interpretation.
Artificial Intelligence ; Big Data ; Customer Trust ; Marketing Performance ; ARDL Model ; Digital Transformation ; Data Privacy ; Consumer Behavior
Touati Karima
.
Keddari Nassim
.
pages 512-535.
Boulkroun Fouad
.
pages 2100-2124.
Akram Akram
.
pages 551-579.
Mohammed Akram
.
pages 430-451.
Akram Abd Eldaim
.
pages 377-396.