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Artificial intelligence adoption in business-to-business marketing: toward a conceptual framework

Lujie Chen (International Business School Suzhou (IBSS), Xi'an Jiaotong-Liverpool University, Suzhou, China)
Mengqi Jiang (International Business School Suzhou (IBSS), Xi'an Jiaotong-Liverpool University, Suzhou, China)
Fu Jia (Management School, University of York, York, UK)
Guoquan Liu (International Business School Suzhou (IBSS), Xi'an Jiaotong-Liverpool University, Suzhou, China)

Journal of Business & Industrial Marketing

ISSN: 0885-8624

Article publication date: 17 September 2021

Issue publication date: 15 April 2022

7275

Abstract

Purpose

The purpose of this study is to develop a synthesized conceptual framework for artificial intelligence (AI) adoption in the field of business-to-business (B2B) marketing.

Design/methodology/approach

A conceptual development approach has been adopted, based on a content analysis of 59 papers in peer-reviewed academic journals, to identify drivers, barriers, practices and consequences of AI adoption in B2B marketing. Based on these analyses and findings, a conceptual model is developed.

Findings

This paper identifies the following two key drivers of AI adoption: the shortcomings of current marketing activities and the external pressure imposed by informatization. Seven outcomes are identified, namely, efficiency improvements, accuracy improvements, better decision-making, customer relationship improvements, sales increases, cost reductions and risk reductions. Based on information processing theory and organizational learning theory (OLT), an integrated conceptual framework is developed to explain the relationship between each construct of AI adoption in B2B marketing.

Originality/value

This study is the first conceptual paper that synthesizes drivers, barriers and outcomes of AI adoption in B2B marketing. The conceptual model derived from the combination of information processing theory and OLT provides a comprehensive framework for future work and opens avenues of research on this topic. This paper contributes to both AI literature and B2B literature.

Keywords

Acknowledgements

The authors gratefully acknowledge the financial support by Natural Science Foundation of China Young Scientist Fund (no. 71902159), Haixi Finance Development Centre (Open fund scheme, grant number HXCJ1901, Minjiang University and the Research Development Funding (RDF-19-01-17) of Xi’an Jiaotong-Liverpool University.

Citation

Chen, L., Jiang, M., Jia, F. and Liu, G. (2022), "Artificial intelligence adoption in business-to-business marketing: toward a conceptual framework", Journal of Business & Industrial Marketing, Vol. 37 No. 5, pp. 1025-1044. https://doi.org/10.1108/JBIM-09-2020-0448

Publisher

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Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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