Let us talk about something: The evolution of e-WOM from the past to the future

Akbari, Morteza; Foroudi, Pantea; Zaman Fashami, Rahime; Mahavarpour, Nasrin; Khodayari, Maryam

Abstract

Because e-WOM is one of the useful digital marketing elements for any organization, a better understanding of its process will help individuals take more advantage of this concept. e-WOM enables individuals to form relationships with firms, brands, and other customers, which leads to benefits for both consumers and companies. It plays a significant role in a firm's performance. The present study implements a different approach to reviewing by combining two bibliometric methods, multidimensional scaling analysis (MDS) and hierarchical cluster analysis (HCA), via Bibexcel software to have a deeper investigation of the process. Considering the 468 journal papers on e-WOM allowed us to study the intellectual streams and significant perceptions underpinning e-WOM. By dividing the study timeframe into three periods, we realized that there have always been three main concepts in this field: consumer behavior, sales, and the tourism and hotel industry. Further, by proposing a framework, we have expanded these concepts accompanied by the role of artificial intelligence and robots in the process of e-WOM. Consequently, new concepts "r-WOM", "automated user engagement", and "smart selling" are introduced and demonstrated as a consequence of using technology-based tools in the process of e-WOM. Finally, the future scope of this field has been designed. We contribute to the literature by offering theoretical and managerial implications.

Citation

Akbari, M., Foroudi, P., Zaman Fashami, R., Mahavarpour, N., & Khodayari, M. (2022). Let us talk about something: The evolution of e-WOM from the past to the future. Journal of Business Research, 149, 663-689. https://doi.org/10.1016/j.jbusres.2022.05.061

• Journal Article Type: Article
• Acceptance Date: May 23, 2022
• Online Publication Date: Jun 2, 2024
• Publication Date: 2022-10
• Deposit Date: Aug 21, 2024
• Print ISSN: 0148-2963
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 149
• Pages: 663-689
• DOI: https://doi.org/10.1016/j.jbusres.2022.05.061
• Keywords: e-WOM, Multidimensional scaling analysis, Hierarchical cluster analysis, Bibliometric, r-WOM