Understanding Algorithmic Personalization in Instagram Ads: The Role of Perceived Creativity, Authenticity & Need for Cognition in Shaping Generation Z’s Purchase Intentions

Algorithmic personalization has transformed the dynamic of consumer engagement with social media advertising, yet its underlying psychological mechanisms remain underexplored. Drawing upon the Elaboration Likelihood Model (ELM) and the Theory of Planned Behavior (TPB), this study examines how personalized Instagram advertisements shape purchase intention through perceived creativity and authenticity, and how Need for Cognition (NFC) moderates these relationships. Data from 458 Pakistani Generation Z users were analyzed using covariance-based structural equation modeling (CFI = 0.997, RMSEA = 0.016, SRMR = 0.024). The results show that personalization significantly enhances perceived creativity (β = 0.578, p < 0.001) and authenticity (β = 0.664, p < 0.001), both of which positively influence purchase intention trough indirect effects (β = 0.195 and β = 0.258, respectively). NFC further strengthens the personalization-intention link (β = 0.142, p < 0.001). These findings extend ELM by situating algorithmic personalization within central-route processing and complement the TPB by demonstrating how creativity and authenticity function as attitudinal mechanisms shaping purchase intention in algorithmically mediated digital advertising.