Abstract
Purpose – The development of digital technologies has led to changes in how consumers perceive privacy. This systematic literature review (SLR) aims to introduce human–artificial intelligence (AI) synthesis (HAIS) as a novel methodology for extending traditional SLRs. Design/methodology/approach – A comprehensive review of the privacy literature is conducted to demonstrate the efficacy of the SLR with HAIS (SLR-HAIS) approach, using 149 articles published by top marketing journals on consumer privacy. The PRISMA approach is adopted as the organizing framework. In addition, the TCCM framework is applied in conjunction with Leximancer-driven HAIS analysis, which utilizes natural language processing techinques for thematic analysis, including text mining, topic modeling, and data visualization. Findings – This review demonstrates that privacy research has not yet fully matured as a field of inquiry. A wide range of theories and methods is used, with a focus on surveys and quantitative approaches within a limited context, mainly studying Western countries and e-commerce. Of concern is the lack of behavioral research, research examining policy changes and a few studies examining moderation and mediation. This review points the way forward for researchers in this field and provides several important research avenues. Originality/value – To bridge the gap between traditional systematic reviews and automated text analytics, this paper introduces the HAIS framework. The framework extends standard SLRs by using AI, specifically Leximancer, to systematically analyze future research directions suggested within the literature. This approach offers a sophisticated means of uncovering latent gaps in privacy research and establishes a scalable methodology for future literature reviews.
Keywords
Consumer privacy, Human–artificial intelligence synthesis, Scientometric analysis, Sensemaking approach, SLR-HAIS, Systematic literature review, TCCM
Document Type
Journal Article
Date of Publication
6-15-2026
ISSN
07363761
Publication Title
Journal of Consumer Marketing
Publisher
Emerald
School
School of Business and Law
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
First Page
1
Last Page
17
Recommended Citation
Zaveri, M. M., Pandit, A., Wilk, V., & D’Alessandro, S. (2026). Where to now with privacy? A systematic literature review with human–artificial intelligence synthesis (SLR-HAIS). Journal of Consumer Marketing. Advance online publication. https://doi.org/10.1108/JCM-01-2025-7545