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The objectives of the study were 1) to ascertain the level of well-being of the employees working for Thai airlines, 2) to find out the variables or factors affecting their well-being, and 3) to identify the factors that have the most, moderate and no effect on their well-being. A survey was conducted to collect the data from employees of five Thai airline companies: Thai airways, Bangkok Airways, Air Asia, Nok Air, and Orient Thai Airline. The sample of 400 employees was selected from the total population of 24,631 employees by systematic random sampling. A questionnaire was used as the instrument. The data were processed by SPSS for Windows. The statistics for data analysis were percentage, mean, standard deviation, maximum and minimum values, Chi-square, Gamma, Multiple Regression, and Path analysis. It was found that 1) most of the respondents had a healthy well-being and 2) the factors significantly affecting their well-being were age, education, number of working years, organizational climate, work characteristic, work environment, compensation, and work-life balance. When gamma (G) was calculated to measure the rigor of the relationship between variables, the factors found to be significantly related to the employee well-being were compensation, work characteristic, work-life balance, organizational climate, work environment, number of working years, age and education, with the G value of .75, .73, .72, .66, .57, .37 , .20, and .19, respectively 3) There were four factors that could predict the employee well-being at the .05 level when Multiple Regression Coefficient was calculated. These factors, which had a positive effect on the employee well-being, were work characteristic, compensation, work-life balance, and work environment, respectively. On the contrary, organizational climate had no significant relationship the employee well-being and thus could not account for their well-being. All the independent variables could account for 61.6 percent of employee well-being (R2 = .611) When the hypothesized correlation model was tested, it was found that the R2 of the full model (R2 FM) was .8068 while the R 2 of the hypothesized correlation model was .0849 (Q= .9903 and W = 3.8606), which had no statistical significance. The finding indicated that the hypothesized correlation model was not significantly different from the empirical data; in other words, it had goodness of fit with the empirical data.
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