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Artificial intelligence (AI) and its implications for market knowledge in B2B marketing
KTH, School of Industrial Engineering and Management (ITM), Industrial Economics and Management (Dept.), Industrial Marketing and Entrepreneurship.
Univ Victoria, Peter B Gustavson Sch Business, Victoria, BC, Canada..
Univ Cambridge, MRC Cognit & Brain Sci Unit, Cambridge, England..
2019 (English)In: Journal of business & industrial marketing, ISSN 0885-8624, E-ISSN 2052-1189, Vol. 34, no 7, p. 1410-1419Article in journal (Refereed) Published
Abstract [en]

Purpose The purpose of this paper is to explain the technological phenomenon artificial intelligence (AI) and how it can contribute to knowledge-based marketing in B2B. Specifically, this paper describes the foundational building blocks of any artificial intelligence system and their interrelationships. This paper also discusses the implications of the different building blocks with respect to market knowledge in B2B marketing and outlines avenues for future research. Design/methodology/approach The paper is conceptual and proposes a framework to explicate the phenomenon AI and its building blocks. It further provides a structured discussion of how AI can contribute to different types of market knowledge critical for B2B marketing: customer knowledge, user knowledge and external market knowledge. Findings The paper explains AI from an input-processes-output lens and explicates the six foundational building blocks of any AI system. It also discussed how the combination of the building blocks transforms data into information and knowledge. Practical implications - Aimed at general marketing executives, rather than AI specialists, this paper explains the phenomenon artificial intelligence, how it works and its relevance for the knowledge-based marketing in B2B firms. The paper highlights illustrative use cases to show how AI can impact B2B marketing functions. Originality/value The study conceptualizes the technological phenomenon artificial intelligence from a knowledge management perspective and contributes to the literature on knowledge management in the era of big data. It addresses calls for more scholarly research on AI and B2B marketing.

Place, publisher, year, edition, pages
EMERALD GROUP PUBLISHING LTD , 2019. Vol. 34, no 7, p. 1410-1419
Keywords [en]
B2B marketing, Customer knowledge, Artificial intelligence, Market knowledge, Machine learning, Natural language processing, Knowledge-based marketing, User knowledge
National Category
Economics and Business
Identifiers
URN: urn:nbn:se:kth:diva-262991DOI: 10.1108/JBIM-10-2018-0295ISI: 000489029000003Scopus ID: 2-s2.0-85067848547OAI: oai:DiVA.org:kth-262991DiVA, id: diva2:1366971
Note

QC 20191031

Available from: 2019-10-31 Created: 2019-10-31 Last updated: 2019-10-31Bibliographically approved

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Paschen, Jeannette

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