The impact of electronic word-of-mouth on corporate performance during COVID-19

Ali Haj Khalifa (), Khakan Najaf (), Osama Fayez Atayah () and Mohamed Dhiaf ()
Additional contact information
Ali Haj Khalifa: University of Khorfakkan
Khakan Najaf: Monash University
Osama Fayez Atayah: Abu Dhabi University
Mohamed Dhiaf: Emirates College of Technology

Electronic Commerce Research, 2024, vol. 24, issue 1, No 23, 655-674

Abstract: Abstract This study attempts to understand the impact of electronic Word of Mouth (eWOM) on corporate financial performance during the COVID-19 pandemic. A supervised machine learning is used to determine the investors’ sentiment of a news story (eWOM) towards a given company from a long position (buying) investors perspective. Ordinary Least Square (OLS) and dynamic quantile regression are used to test the role of eWOM on financial performance. Results reveal no significant relationship between eWOM and the firm’s financial performance. Similarly, we do not find any evidence of an association between eWOM and corporate performance at different quantiles of financial performance. The findings contribute to the existing literature on eWOM and its impact on the financial performance during specific circumstances or financial crises. This study offers insights to researchers, policymakers, regulators, financial report users, investors, employees, clients, and society.

Keywords: eWOM; OLS; Quantile regression; COVID-19; Heterogeneity (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10660-023-09750-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:elcore:v:24:y:2024:i:1:d:10.1007_s10660-023-09750-0

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10660

DOI: 10.1007/s10660-023-09750-0

Access Statistics for this article

Electronic Commerce Research is currently edited by James Westland

More articles in Electronic Commerce Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().