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This study aims to investigate ergonomic risk factors and improve the process in hotel enterprises. The research focused on the main operational process such as food preparation, material supply, and warehouse, in the kitchen, housekeeping and warehouse departments. In the first step, a checklist is prepared according to ILO, OSHA, NIOSH and IEA documents. In this checklist job tasks, workstations and working environment are subject to the study. After controlled by industry experts checklist implemented and results show that there are some ergonomic risk factors in the kitchen. In order to improve the ergonomic conditions 2³, (3 factors, 2 level) factorial design was put into practice. Results show that the greatest effect is caused by Factor 2 (presence of underfoot mat) comes first, Factor 1 (height of the workbench is at elbow level) comes second and Factor 3 (job rotation) comes third.


 
 
 Today, companies are planning their own activities depending on efficiency and effectiveness. In order to have plans for the future activities they need historical data coming from outside and inside of the companies. However, this data is in huge amounts to understand easily. Since, this huge amount of data creates complexity in business for many industries like hospitality industry, reliable, accurate and fast access to this data is to be one of the greatest problems. Besides, management of this data is another big problem. In order to analyze this huge amount of data, Data Mining (DM) tools, can be used effectively. In this study, after giving brief definition about fundamentals of data mining, Chi Squared Automatic Interaction Detection (CHAID) algorithm, one of the mostly used DM tool, will be introduced. By CHAID algorithm, the most used materials in room cleaning process and the relations of these materials based on in a five star hotel data are tried to be determined. At the end of the analysis, it is seen that while some variables have strong relation with the number of rooms cleaned in the hotel, the others have no or weak relation.