AI‐Driven Marketing Strategy as a Catalyst for Circular Economy Participation

ABSTRACT

This study examines how sustainable marketing communication and AI‐driven marketing personalization influence circular economy participation through marketing automation maturity, carbon‐aware digital infrastructure, and willingness to purchase low‐carbon products. Drawing on dynamic capabilities theory, it explains the capability‐building mechanisms underlying digitally enabled sustainability. We collected data from 3253 middle‐ and senior‐level marketing and advertising managers across five countries. We tested the proposed model using partial least squares structural equation modeling (PLS‐SEM). We also used Jeffreys's Amazing Statistics Program (JASP) to run machine learning analyses, including support vector machine regression, regularized linear regression, and random forest regression, to assess predictive performance. Marketing automation maturity and carbon‐aware digital infrastructure significantly mediate the relationship between sustainable marketing communication and circular economy participation. Low‐carbon product willingness to purchase emerged as the strongest market‐level mechanism, whereas AI‐driven marketing personalization primarily influenced circular economy participation through sequential capability pathways. Random forest regression demonstrated superior predictive performance and confirmed the dominant importance of willingness to purchase low‐carbon products. By integrating explanatory and predictive analytics, this study extends dynamic capabilities theory by demonstrating that circular economy participation stems from sequential development of digital capabilities rather than direct marketing effects, offering actionable implications for organizations pursuing AI‐enabled sustainability and circular transformation.

JEL Classification: M31, Q56, O33