Mobility, stress, and coping strategy: A qualitative investigation of migrant hospitality workers in India post the Covid crisis.
Published In: Journal of Public Affairs (14723891), 2024, v. 24, n. 3. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Gupta, Himanshu; Dhar, Rajib L. 3 of 3
Abstract
Migrant workers in India represent one of the most marginalised segments of the population and often find employment in highly vulnerable sectors such as construction, tourism, and hospitality, making their lives more stressful. This study, based on a qualitative approach, explores the reasons for migration, stress‐related experiences, and the coping strategies of migrant hospitality workers in India following the Covid crisis. Primary data through personal interviews has been collected from 21 migrant workers employed in hospitality organisations in the Delhi‐NCR (National Capital Region) region of India. A thematic analysis was performed to extract key themes from the qualitative data. The findings show that a lack of employment opportunities and rigid societal norms drive these workers towards cities. The stressors include family obligations, precarious work, and entrapping debt. Further, these workers typically cope by managing their emotions, acknowledging that they cannot address the problems that are leading to their stress. The study puts forth practical steps that public actors/government can take to implement policies designed to enhance the living and working conditions of these migrant workers. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Public Affairs (14723891). 2024/08, Vol. 24, Issue 3, p1
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2024
- ISSN:1472-3891
- DOI:10.1002/pa.2927
- Accession Number:179254359
- Copyright Statement:Copyright of Journal of Public Affairs (14723891) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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