Enhancing value in customer journey by considering the (ad)option of artificial intelligence tools

Neeraj Dhiman, Mohit Jamwal and Ajay Kumar

Journal of Business Research, 2023, vol. 167, issue C

Abstract: Artificial intelligence(AI) technologies are revolutionizing the customer journey remarkably. Current research employsextended value-based adoption model (VAM) incorporating mediating and moderating variables to predict the adoption intentions of AI technologies. Using a structured questionnaire, 392 responses were collected and analyzed using partial least square structural equation modelling. Results showed that AI technology's usefulness, fascinating features, and trustpositively impact its value in customers' eyes. Technological anxiety related to AI dampensAI tools’ value. Making AI tools human like (anthropomorphic) do not enhance its value. This study establishes that the value associated with AI tools leads to relationship (parasocial) formation with them and itincreases the possibility of AI technologies use. Study showed that the users who have different liking towards AI tools usage (AI fans, detractors and indifferent) influence the relationship between AI tools’ value and intentions to use AI differently. The study further offers valuable theoretical and practical implications.

Keywords: Artificial intelligence technologies; Adoption intention; Perceived value; Anthropomorphism; Parasocial relationship; Customer journey (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0148296323005015
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:167:y:2023:i:c:s0148296323005015

DOI: 10.1016/j.jbusres.2023.114142

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 ().