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Influence of Online Forums on Customers’ Buying Decisions: A Machine Learning Approach Cover

Influence of Online Forums on Customers’ Buying Decisions: A Machine Learning Approach

By: Reeti Agarwal and  Ankit Mehrotra  
Open Access
|Jan 2024

Abstract

Online forums are becoming increasingly important in influencing customers’ buying decision process, hence understanding customers’ likelihood to rely on online forums while making buying decisions is of major concern for marketers. The companies should also be aware of how reliance-likelihood differs with the introversion/extraversion nature of customers. Using factor analysis as data reduction technique and classification and regression tree as machine learning technique, the current study categorizes customers and builds decision rules based on their self-perception related to their inter-intra communication comfort level (introversion/extraversion level). Based on customers’ self-perception of their inter-intra communication comfort level, four groups were identified as: Extroverts, Introverts, Socially Active and Vacillators. Analysis of the data collected from 209 respondents revealed that being socially active is a common trait for both introverts and extroverts in being influenced by online forums while making buying decisions. The current study will be useful for companies in understanding the effect of the level of introversion-extraversion in making customers more likely to be influenced by online forums for making buying decisions and hence will help firms in formulating more effective strategies and better predictive models related to online forums.

DOI: https://doi.org/10.2478/sbe-2023-0042 | Journal eISSN: 2344-5416 | Journal ISSN: 1842-4120
Language: English
Page range: 5 - 23
Published on: Jan 11, 2024
In partnership with: Paradigm Publishing Services
Publication frequency: 3 issues per year

© 2024 Reeti Agarwal, Ankit Mehrotra, published by Lucian Blaga University of Sibiu
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.