Accepted for/Published in: JMIR Formative Research
Date Submitted: Nov 6, 2023
Open Peer Review Period: Nov 6, 2023 - Nov 20, 2023
Date Accepted: Apr 3, 2024
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Exploring Consumers' Negative Electronic Word-of-Mouth through SERVQUAL and Service Flower Theory: A Case Study of Five Military Hospitals in Taiwan
ABSTRACT
Background:
In recent years, with the widespread use of the internet, the influence of electronic word-of-mouth (eWOM) has been increasingly recognized, particularly the significance of negative eWOM, which has surpassed positive eWOM in importance. Such reviews play a pivotal role in research related to service industry management, particularly in intangible service sectors like hospitals, where they have become a reference point for improving service quality.
Objective:
This study comprehensively collected negative eWOM reviews of military hospitals in Taiwan, all regionally graded and above, to investigate the issues related to service quality that emerged before and after the pandemic. These findings serve as crucial references for developing strategies to enhance service quality.
Methods:
In this study, we employed web scraping techniques to gather 1259 valid negative online reviews of five military hospitals in Taiwan, covering the period from the inception of the first review to December 31, 2022. These reviews were categorized using content analysis based on the modified PZB SERVQUAL scale and the Service Flower theory. Statistical data analysis was conducted to investigate the performance of service quality.
Results:
The annual count of negative reviews for each hospital has exhibited a consistent upward trajectory over the years, with a more pronounced increase following the onset of the pandemic. In the analysis, among the five dimensions of the PZB SERVQUAL framework, the “Assurance” dimension yielded the least favorable results, registering a negative review rate as high as 58.3%. Closely trailing, the “Responsiveness” dimension recorded a negative review rate of 34.2%. Within the “Assurance” dimension, the sub-category pertaining to “healthcare personnel lacking professional service communication attitudes and etiquette” garnered the highest negative review rate at 80.8%. Within the “Responsiveness” dimension, the sub-category concerning “healthcare personnel's inability to promptly provide service requests (service waiting time)” garnered a negative review rate of 60.7%. Furthermore, when evaluating the service process, the sub-item “Service in Process: Diagnosis/Examination/Medical/Hospitalization” exhibited the least satisfactory performance, with a negative review rate of 46.2%. This was followed by the sub-item “Service in Process: Pre-diagnosis Waiting,” which had a negative review rate of 20.2%.
Conclusions:
Before and after the pandemic, there were significant differences in evaluating hospital services, and a higher word count in negative reviews indicated greater dissatisfaction with the service. Therefore, it is recommended that hospitals establish more comprehensive service quality management mechanisms, carefully respond to negative reviews, and categorize significant service deficiencies as critical events to prevent a decrease in overall service quality. Furthermore, during the service process, customers are particularly concerned about the attitude and responsiveness of healthcare personnel in the treatment process. Therefore, hospitals should enhance training and management in this area. Clinical Trial: NONE
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Copyright
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