TY - JOUR
T1 - Reshaping the contexts of online customer engagement behavior via artificial intelligence
T2 - a conceptual framework
AU - Perez-Vega, Rodrigo
AU - Kaartemo, Valtteri
AU - Lages, Cristiana R.
AU - Razavi, Niloofar Borghei
AU - Männistö, Jaakko
N1 - Funding Information:
This research is funded by the Academy of Finland (315604).
Publisher Copyright:
© 2020 The Authors
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2021/5
Y1 - 2021/5
N2 - 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.
AB - 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.
KW - Artificial intelligence
KW - Information processing systems
KW - Online customer engagement behaviors
KW - Stimulus-organism-response
UR - http://www.scopus.com/inward/record.url?scp=85096560269&partnerID=8YFLogxK
U2 - 10.1016/j.jbusres.2020.11.002
DO - 10.1016/j.jbusres.2020.11.002
M3 - Article
AN - SCOPUS:85096560269
SN - 0148-2963
VL - 129
SP - 902
EP - 910
JO - Journal of Business Research
JF - Journal of Business Research
ER -