Transforming data to delight: AI-led campaign personalization shapes digital natives’ intention to accept over a TAM-VAM approach

To explain consumers' intention to accept artificial intelligence (AI)-led campaign personalization in cause-related marketing, this study integrates the technology acceptance model (TAM) and value-based adoption model (VAM). While TAM explains acceptance through functional and usability-driven evaluations of technology, it is insufficient to capture the emotional and value-driven judgments that are central to cause-related marketing contexts. VAM complements TAM, which is critical when AI-led campaign personalization is used to promote socially and ethically oriented initiatives. Focusing on digitally savvy consumers with high expectations for personalized initiatives, the study empirically examines these relationships using a purposive sample of 270 university students from Chennai, India. The data were collected through an online survey assessing key TAM factors, such as technology readiness, perceived usefulness, and perceived ease of use (PEOU), and VAM factors, such as perceived enjoyment and perceived value. Structural equation modeling using AMOS revealed that technology readiness strongly influences perceived ease of use (<i>β</i> = 0.48) and perceived enjoyment (<i>β</i> = 0.52), while perceived usefulness (<i>β</i> = 0.46) and perceived enjoyment (<i>β</i> = 0.49) significantly enhance perceived value. Perceived value emerged as the most substantial predictor of intention to accept AI-led campaign personalization (<i>β</i> = 0.60). These findings indicate that both functional and emotional benefits drive consumers' intention to accept AI-led marketing. By integrating TAM and VAM, this study provides an empirical insight into how digital natives perceive and engage with AI-led strategies. The research offers theoretical contributions of AI intention to acceptance models and practical insights for businesses aiming to design personalized, value-driven, and emotionally engaging AI-led campaigns.

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Publication Details

Journal
Frontiers in Artificial Intelligence
Published
2026-02-18
DOI
https://doi.org/10.3389/frai.2026.1734151
Primary Topic
Technology Adoption and User Behaviour
Type
article
Field-Weighted Citation Impact
0.00

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article

Transforming data to delight: AI-led campaign personalization shapes digital natives’ intention to accept over a TAM-VAM approach

Thangaraja Arumugam, L. Durgha Devi
Frontiers in Artificial Intelligence
Technology Adoption and User Behaviour
article

Transforming data to delight: AI-led campaign personalization shapes digital natives’ intention to accept over a TAM-VAM approach

Thangaraja Arumugam, L. Durgha Devi
article en

Abstract

To explain consumers' intention to accept artificial intelligence (AI)-led campaign personalization in cause-related marketing, this study integrates the technology acceptance model (TAM) and value-based adoption model (VAM). While TAM explains acceptance through functional and usability-driven evaluations of technology, it is insufficient to capture the emotional and value-driven judgments that are central to cause-related marketing contexts. VAM complements TAM, which is critical when AI-led campaign personalization is used to promote socially and ethically oriented initiatives. Focusing on digitally savvy consumers with high expectations for personalized initiatives, the study empirically examines these relationships using a purposive sample of 270 university students from Chennai, India. The data were collected through an online survey assessing key TAM factors, such as technology readiness, perceived usefulness, and perceived ease of use (PEOU), and VAM factors, such as perceived enjoyment and perceived value. Structural equation modeling using AMOS revealed that technology readiness strongly influences perceived ease of use (<i>β</i> = 0.48) and perceived enjoyment (<i>β</i> = 0.52), while perceived usefulness (<i>β</i> = 0.46) and perceived enjoyment (<i>β</i> = 0.49) significantly enhance perceived value. Perceived value emerged as the most substantial predictor of intention to accept AI-led campaign personalization (<i>β</i> = 0.60). These findings indicate that both functional and emotional benefits drive consumers' intention to accept AI-led marketing. By integrating TAM and VAM, this study provides an empirical insight into how digital natives perceive and engage with AI-led strategies. The research offers theoretical contributions of AI intention to acceptance models and practical insights for businesses aiming to design personalized, value-driven, and emotionally engaging AI-led campaigns.

Frontiers in Artificial IntelligenceVol. 9
Vellore Institute of Technology University (IN)
Vellore Institute of Technology, Chennai, VIT University
Openalex Percentile: Top 55%
Technology Adoption and User Behaviour
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