An Analysis on Factors Influencing Job Satisfaction of Employees: A Case Study on Sarova White Sands Beach Resort & Spa

Ahlam, Seif Mbaruk (2011) An Analysis on Factors Influencing Job Satisfaction of Employees: A Case Study on Sarova White Sands Beach Resort & Spa. Masters thesis, INTI International University.

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Abstract

The tourism industry in Kenya is forecasted to grow and as employment is common in this type of service industry it is likely to increase concurrently. Having motivated and satisfied employees are fundamental in all organizations and especially in the service industry where front-line employees play an important role for the customers’ perceived service quality. Therefore the human resource management applied should be in accordance to the desire of employees as properly managed employees could be of competitive advantages and contribute to the success of an organization. The study hence focuses on the relationships between the factors that influence job satisfaction and job satisfaction. As the ultimate goal in the hotel environment is service delivery, it is imperative that employees perform optimally and maintains acceptable levels of job satisfaction, hence, contributing to the vision and mission of providing better service to customers. This study had a quantitative approach and a questionnaire was carried out at White Sands Beach Resort with 200 respondents. Correlation and regression analyses were made and it was found that certain factors such as Feedback, advancement, responsibility and management attitude & compensation were all found to predict employees’ overall job satisfaction. The result provides further understanding as regards to workers’ motivation and behavior. However the study also presents recommendations for managerial use at Sarova White Sands Beach Resort and Spa as well as the hotel industry as a whole. Lastly, due to the composition of the sample, results of this study cannot be inferred to other similar occupational classes in other institutions. Therefore, it is recommended that a proportionate stratified random sample be utilized for future research.

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