Academic journal article International Journal of Business and Society

The Evaluation of Five-Star Hotel: A Case in Iran

Academic journal article International Journal of Business and Society

The Evaluation of Five-Star Hotel: A Case in Iran

Article excerpt


Tourism industry is one of the major factors in the economy of many countries. Iran with historical culture and natural attraction has a good standing in tourism industry. Selecting the most appropriate hotel is a concern for travelers which requires assessment and analysis of several factors. Travelers who seek economical vacation opt for low quality hotels and do not care much about facilities, in the other words hotels with fewer stars. On the hand, the rich look for five-star hotels for whom luxury and facility is a top priority. In this regard, the main aim of this study is to evaluate the performance and to select the optimal five-star hotels in Iran. The results of this case study will benefit both tourism industry and international travelers alike. To do so, an integrated MCDM model based on analytic network process (ANP) and technique for order preference by similarity to ideal solution (TOPSIS) is utilized. We initially extracted critical evaluation indices (e.g. Hotel Facilities, Price, Room and Front desk, Service Quality, Security and Location) and further developed the evaluation structure for hotel industry in accordance with findings of current studies. Four five-star hotels are employed in this study: Esteghlal, Laleh, Homa, Espinas. The ANP is applied to find the weights among the proposed indices and to discover the interdependent relationships among indices. Besides, the TOPSIS is applied to rank four famous five star hotels in Tehran based on the result of ANP. As the results demonstrate, location is the most important index for customers and after that security, price, room and frontdesk, service quality and hotel facilities come respectively. According to there indices the ranking was as follow Esteghlal was first, Espinas came second followed by Homa and Laleh. Findings of this study can also be used for future research on performance evaluation of the hotels in general and can be a guideline for travelers to select the best hotel appropriate to their needs. The results can benefit managers of certain hotels to obtain an intellectual framework and to identify potential travelers.

Keywords: Five-star hotels; Analysis network process (ANP); Technique for Order Preference by Similarity to Ideal Solution (TOPSIS); Multiple criteria decision making (MCDM)

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The service industry is the fastest growing industry in the 21st century (Fatma & Timothy, (2005), and tourism is viewed as having excellent prospects, along with high-tech industries. Tourism is a major industry in many countries and an important factor in global economic development (Hung, et al., 2010).

Tourism is one of the most locative business 21st century and it should be pointed out the hotel industry, another words "Hotel Section" plays an important role in this regard. Hotels hold the key role to success and development of Tourism and result in economic growth of a region as a tourist resort (Mahdavinia, 2007). Since this section directly deals with tourists and travelers, hotels play a big role in the tourist satisfaction (Mahdavinia, 2007). On the other hand, there is a boom in construction of luxurious hotels; however, it is absolutely difficult to meet infinitive variety of hotel guest's expectations. To gain a comparative advantage over the rival hotels, hotel managers have to provide their customers with the service quality and meet their expectations (Mahdavinia, 2007). However, during recent years, there is a decrease number in tourist arrival in Iran.

Since the improvement for tourism industry gradually highlighted by the Iran government in 1988 with the beginning of a well political relationship with tourist generating countries, Iran faced an outstanding growth in this industry (Ministry of Islamic guidance, 2006). In 2005 the number of tourists visiting Iran reached up to 1.3 of a million and as predictions showed by the end of the year 2009 we will see an increase in this number by the rate of 24%. …

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