Li, Z. and Stamolampros, P. orcid.org/0000-0001-8143-7244 (2026) Listening to internal voices: unveiling healthcare employee satisfaction through big data analysis of online feedback. Personnel Review. ISSN: 0048-3486
Abstract
Purpose
Healthcare online feedback is widely used to improve service quality. This study aims to explore the determinants and evolving dynamics of healthcare employee satisfaction as reflected in employee-generated content.
Design/methodology/approach
This study analyzes structured (numerical ratings) and unstructured (textual feedback) data from over 300,000 online employee reviews of 9,103 US healthcare organizations. Using topic modeling, it identifies key satisfaction and dissatisfaction factors and examines their variations across job roles and tenure lengths, with a particular focus on the impact of the COVID-19 pandemic.
Findings
Our analysis reveals that job satisfaction determinants vary by role and tenure. During the initial phase of the COVID-19 pandemic, satisfaction temporarily increased due to a heightened sense of purpose and strong peer relationships. However, as the crisis persisted, satisfaction declined due to mounting stress, staff shortages, irregular shifts, and inadequate compensation.
Practical implications
These findings can guide healthcare organizations in developing targeted management strategies to enhance employee satisfaction and retention.
Originality/value
This study offers a novel perspective on healthcare online feedback by analyzing large-scale employee reviews from the service provider's standpoint, providing valuable insights into workplace experiences. Additionally, it contributes to employee satisfaction research by examining its dynamic changes across different phases and role-specific variations.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | This is an author produced version of an article published in Personnel Review, made available via the University of Leeds Research Outputs Policy under the terms of the Creative Commons Attribution License (CC-BY), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | Employee satisfaction, Online reviews, Covid-19, Big data, Topic modeling |
| Dates: |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Analytics, Technology & Ops Department |
| Date Deposited: | 04 Feb 2026 15:51 |
| Last Modified: | 18 May 2026 15:34 |
| Status: | Published online |
| Publisher: | Emerald |
| Identification Number: | 10.1108/PR-03-2025-0280 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:237440 |
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