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Reshaping the contexts of online customer engagement behavior via artificial intelligence: A conceptual framework

Perez-Vega, Rodrigo, Kaartemo, Valtteri, Lages, Cristiana R., Borghei Razavi, Niloofar, Männistö, Jaakko (2021) Reshaping the contexts of online customer engagement behavior via artificial intelligence: A conceptual framework. Journal of Business Research, 129 . pp. 902-910. ISSN 0148-2963. (doi:10.1016/j.jbusres.2020.11.002) (KAR id:85801)

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Official URL:
https://doi.org/10.1016/j.jbusres.2020.11.002

Abstract

As new applications of artificial intelligence continue to emerge, there is an increasing interest to explore how this type of technology can improve automated service interactions between the firm and its customers. This paper aims to develop a conceptual framework that details how firms and customers can enhance the outcomes of firm-solicited and firm-unsolicited online customer engagement behaviors through the use of information processing systems enabled by artificial intelligence. By building on the metaphor of artificial intelligence systems as organisms and taking a Stimulus-Organism-Response theory perspective, this paper identifies different types of firm-solicited and firm-unsolicited online customer engagement behaviors that act as stimuli for artificial intelligence organisms to process customer-related information resulting in both artificial intelligence and human responses which, in turn, shape the contexts of future online customer engagement behaviors.

Item Type: Article
DOI/Identification number: 10.1016/j.jbusres.2020.11.002
Uncontrolled keywords: Artificial intelligence, Online customer engagement behaviors, Stimulus-organism-response, Information processing systems
Subjects: H Social Sciences > HF Commerce > HF5415 Marketing
Q Science > Q Science (General) > Q335 Artificial intelligence
Divisions: Divisions > Kent Business School - Division > Department of Marketing, Entrepreneurship and International Business
Depositing User: Rodrigo Perez Vega
Date Deposited: 01 Feb 2021 17:14 UTC
Last Modified: 04 Mar 2024 15:14 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/85801 (The current URI for this page, for reference purposes)

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