Developing an Emotional Labor Scale for Employees in the Service Industry

Minnicha Yarosake (), Associate Prof. Dr. Juthamas Haenjohn () and Assistant Prof. Dr. Warakorn Sapwirapakorn ()

Human Resource and Leadership Journal, 2024, vol. 9, issue 3, 62 - 77

Abstract: Purpose: This research aims to develop an emotional labor scale and examine the consistency of the emotional labor measurement model with empirical data. The study focuses on individuals with long-term work experience and incorporates cross-cultural perspectives to address gaps in current research. Additionally, it seeks to create a standardized model for measuring and evaluating emotional labor that is applicable to contemporary work environments. Methodology: The population is front-service employees of hotels in Chonburi Province, and the sample consists of 280 front-service employees of hotels in Pattaya City, Chonburi Province. The research methodology for developing the emotional labor scale in this phase is quantitative research, using confirmatory factor analysis to examine the consistency of the emotional labor measurement model. Findings: The results of the model fit analysis and quality assessment of the CFA model found that the RMSEA (Root Mean Square Error of Approximation) was 0.217, indicating a lack of fit between the model and data. The CFI (Comparative Fit Index) was 0.591. The TLI (Tucker-Lewis Index) was 0.442. Finally, the IFI (Incremental Fit Index) was 0.595. Based on the presented indices, this model has a poor fit with the data. The RMSEA, CFI, TLI, and IFI values are lower than the recommended criteria, indicating a discrepancy between the model and data. Unique Contribution to Theory, Policy and Practice: These findings suggest that current emotional labor measurement models may not accurately capture the experiences of workers across different cultures and with varying lengths of work experience. Policymakers and organizations should consider developing more nuanced and culturally sensitive approaches to assess and manage emotional labor in the workplace. This could involve creating tailored training programs, revising performance evaluation metrics, and implementing supportive policies that acknowledge the complexity of emotional labor across diverse work environments.

Date: 2024
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