Navigating a paradigm shift: Technology and user acceptance of big data and artificial intelligence among advertising and marketing practitioners

Pooja Iyer and Laura F. Bright

Journal of Business Research, 2024, vol. 180, issue C

Abstract: The advertising and marketing industry is witnessing a paradigm shift with the inclusion of big data and artificial intelligence, expecting practitioners to adapt to this rapidly transforming environment. Utilizing the Unified Theory of Acceptance and Use of Technology (UTAUT) model, a mixed methods approach examines how performance and effort expectancy mediate the psychological factors of anxiety and self-efficacy on behavioral intention to accept and engage with big data and AI systems amongst practitioners. To examine the psychological factors of UTAUT in relation to behavior, this research surveyed 100 mid-level advertising and marketing practitioners and found performance expectancy fully mediated anxiety, and effort expectancy partially mediated self-efficacy on behavioral intention. Qualitative insights identified psychological, social, and organizational factors, including fear of losing jobs, collaboration, motivation, training, social influence, and facilitating factors are critical to technology acceptance. Theoretical and managerial implications are discussed as they relate to this ongoing paradigm shift.

Keywords: Big data; Artificial intelligence; Technology acceptance; Advertising; Marketing; Agencies (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0148296324002030
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:180:y:2024:i:c:s0148296324002030

DOI: 10.1016/j.jbusres.2024.114699

Access Statistics for this article

Journal of Business Research is currently edited by A. G. Woodside

More articles in Journal of Business Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().