Artificial Intelligence and Machine Learning: Exploring drivers, barriers, and future developments in marketing management

被引:22
|
作者
Volkmar, Gioia [1 ]
Fischer, Peter M. [1 ]
Reinecke, Sven [1 ]
机构
[1] Univ St Gallen, Inst Mkt & Customer Insight, Dufourstr 40a, CH-9000 St Gallen, Switzerland
基金
瑞士国家科学基金会;
关键词
Artificial Intelligence; Machine Learning; Marketing Management; Decision; Making; Delphi Method; Ethics; BIG DATA; DECISION-MAKING; DELPHI METHOD; WORK HUMAN; AI; CHALLENGES; KNOWLEDGE; CONSUMER; BEHAVIOR; ADOPTION;
D O I
10.1016/j.jbusres.2022.04.007
中图分类号
F [经济];
学科分类号
02 ;
摘要
Companies neither fully exploit the potential of Artificial Intelligence (AI), nor that of Machine Learning (ML), its most prominent method. This is true in particular of marketing, where its possible use extends beyond mere segmentation, personalization, and decision-making. We explore the drivers of and barriers to AI and ML in marketing by adopting a dual strategic and behavioral focus, which provides both an inward (AI and ML for marketers) and an outward (AI and ML for customers) perspective. From our mixed-method approach (a Delphi study, a survey, and two focus groups), we derive several research propositions that address the challenges facing marketing managers and organizations in three distinct domains: (1) Culture, Strategy, and Implementation; (2) Decision-Making and Ethics; (3) Customer Management. Our findings contribute to better understanding the human factor behind AI and ML, and aim to stimulate interdisciplinary inquiry across marketing, organizational behavior, psychology, and ethics.
引用
收藏
页码:599 / 614
页数:16
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