The word-of-mouth (WOM) marketing process is one of the main means by which consumers obtain information. As a communication channel between consumers in economically developing countries, WOM may contribute to the development of the organic food market. The primary objective of this study is to segment organic saffron consumers in Mashhad, Iran, and determine how they engage in WOM marketing. Data were collected through questionnaires from 13 districts of Mashhad using a stratified sampling method. In this study, 400 organic saffron consumers were grouped using a self-organizing map (SOM) neural network based on consumer neobehavioristic theory, and then, using decision trees, consumer behavior rules were extracted for participating in the WOM for each group. According to the results, less than fifty percent of consumers in each of the four market segments are willing to participate in WOM advertising for organic saffron. A lack of awareness of the characteristics of organic saffron is also found to be the main reason for consumers' reluctance to recommend organic saffron to others. Mass-media advertising is an effective way to raise consumer awareness and influence opinion leaders, ultimately resulting in WOM recommendations.
Keywords: Machine learning; Market segmentation; Organic consumers; WOM.
Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.