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Progress in Artificial Intelligence

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28.07.2023 | Review

Two decades of agent-based modeling in marketing: a bibliometric analysis

verfasst von: Elena Romero, Manuel Chica, Sergio Damas, William Rand

Erschienen in: Progress in Artificial Intelligence | Ausgabe 3/2023

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Abstract

Agent-based modeling has proven to be a useful simulation tool in marketing to analyze what-if scenarios and support strategic marketing decisions. Over the years, the field has evolved and there is a substantial number of scientific publications that focus on different aspects of agent-based modeling. However, there is no recent bibliometric analysis covering the entire marketing area. This article provides an updated bibliometric analysis on agent-based modeling in marketing in the last 2 decades. The goal of this study is to provide both a performance and a science mapping analysis. The performance analysis explores highly cited articles, researchers, and geographical features. The science mapping analysis examines the relationships between words, authors, and citations of the literature. Moreover, this survey includes a comprehensive reference table characterizing the agent-based models collected. The results show that the most common aspects studied are related with diffusion and social networks. Additionally, we see that extensive research has been mainly carried out for the study of the effects of topology and innovation diffusion.

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Titel: Two decades of agent-based modeling in marketing: a bibliometric analysis
verfasst von: Elena Romero
Manuel Chica
Sergio Damas
William Rand
Publikationsdatum: 28.07.2023
Verlag: Springer Berlin Heidelberg
Erschienen in: Progress in Artificial Intelligence / Ausgabe 3/2023
Print ISSN: 2192-6352
Elektronische ISSN: 2192-6360
DOI: https://doi.org/10.1007/s13748-023-00303-y

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