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Evaluation of Hotel Employees’ Satisfaction Using Ugc (User Generated Content)
Abstract:
Job satisfaction is correlated with employees on job performance, guest satisfaction and implicitly with financial performance of a hotel. Previous studies showed that employees’ satisfaction when published online can influence guests booking intentions. We argue that it can influence and that it should be used to facilitate the human resource management process and prevent high turnover rates which are characteristic for hospitality. User generated content created a space for hotel employees to share their satisfaction/dissatisfaction online with thousands of other jobseekers. This giant database could be used to improve working conditions, increase job satisfaction, and consequentially increase performance and guest satisfaction. This paper presents initial results from data collected from one of the most visited websites in the world glassdoor.com. In total, primary findings from more than 10.000 workers reviews were presented. Results show that culture and values and career opportunities are ranked as top variables that contribute to the overall job satisfaction. In addition, these two variables showed strong correlation with rating of senior management. This could be understood that employees their career opportunities and culture and values that prevail in organisation significantly associate with senior management.
CITATION:
IEEE format
D. Borovčanin, N. Kilibarda, M. Milošević, M. Knežević, “Evaluation of Hotel Employees’ Satisfaction Using Ugc (User Generated Content),” in Sinteza 2020 - International Scientific Conference on Information Technology and Data Related Research, Belgrade, Singidunum University, Serbia, 2020, pp. 134-138. doi:10.15308/Sinteza-2020-134-138
APA format
Borovčanin, D., Kilibarda, N., Milošević, M., Knežević, M. (2020). Evaluation of Hotel Employees’ Satisfaction Using Ugc (User Generated Content). Paper presented at Sinteza 2020 - International Scientific Conference on Information Technology and Data Related Research. doi:10.15308/Sinteza-2020-134-138
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