Universität zu Köln

Kopalle, Praveen K., Gangwar, Manish ORCID: 0000-0003-0661-5922, Kaplan, Andreas ORCID: 0000-0002-5016-0841, Ramachandran, Divya, Reinartz, Werner and Rindfleisch, Aric (2022). Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities. Int. J. Res. Mark., 39 (2). S. 522 - 541. AMSTERDAM: ELSEVIER. ISSN 1873-8001

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Abstract

Artificial intelligence (AI) has captured substantial interest from a wide array of marketing scholars in recent years. Our research contributes to this emerging domain by examining AI technologies in marketing via a global lens. Specifically, our lens focuses on three levels of analysis: country, company, and consumer. Our country-level analysis emphasizes the heterogeneity in economic inequality across countries due to the considerable economic resources necessary for AI adoption. Our company-level analysis focuses on glocalization because while the hardware that underlies these technologies may be global in nature, their application necessitates adaptation to local cultures. Our consumer-level analysis examines consumer ethics and privacy concerns, as AI technologies often collect, store and process a cornucopia of personal data across our globe. Through the prism of these three lenses, we focus on two important dimensions of AI technologies in marketing: (1) human-machine interaction and (2) automated analysis of text, audio, images, and video. We then explore the interaction between these two key dimensions of AI across our three-part global lens to develop a set of research questions for future marketing scholarship in this increasingly important domain. (c) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Kopalle, Praveen K. UNSPECIFIED UNSPECIFIED UNSPECIFIED Gangwar, Manish UNSPECIFIED orcid.org/0000-0003-0661-5922 UNSPECIFIED Kaplan, Andreas UNSPECIFIED orcid.org/0000-0002-5016-0841 UNSPECIFIED Ramachandran, Divya UNSPECIFIED UNSPECIFIED UNSPECIFIED Reinartz, Werner UNSPECIFIED UNSPECIFIED UNSPECIFIED Rindfleisch, Aric UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-688220
DOI:	10.1016/j.ijresmar.2021.11.002
Journal or Publication Title:	Int. J. Res. Mark.
Volume:	39
Number:	2
Page Range:	S. 522 - 541
Date:	2022
Publisher:	ELSEVIER
Place of Publication:	AMSTERDAM
ISSN:	1873-8001
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language BIG DATA; CONSUMER; INFORMATION; PRIVACY; EXPERIENCES; KNOWLEDGE; NETWORKS; HUMANS; BIAS Multiple languages Business Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/68822