THE EVALUATION OF FIVE-STAR HOTEL: A CASE IN IRAN

ABSTRACTTourism 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)(ProQuest: ... denotes formulae omitted.)1. INTRODUCTIONThe 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%. …

[1]  C. Hwang.  Multiple Objective Decision Making - Methods and Applications: A State-of-the-Art Survey , 1979 .

[2]  T. Saaty,et al.  Dependence and independence: From linear hierarchies to nonlinear networks , 1986 .

[3]  Peter Franz Renner,et al.  Basic Hotel Front Office Procedures , 1988 .

[4]  Margaret F. Shipley,et al.  A decision making model for multi-attribute problems incorporating uncertainty and bias measures , 1991, Comput. Oper. Res..

[5]  Peter J. Danaher,et al.  Cumulative Encounter Satisfaction in the Hotel Conference Process , 1994 .

[6]  Thomas L. Saaty,et al.  Decision making with dependence and feedback : the analytic network process : the organization and prioritization of complexity , 1996 .

[7]  Stowe Shoemaker,et al.  Price-Sensitivity Measurement: A Tool for the Hospitality Industry , 1997 .

[8]  I. Buick.  A Preliminary study of the operational aspects of providing room service to hotel guests in Edinburgh’s principal hotels , 1998 .

[9]  Joseph Sarkis,et al.  Strategic analysis of logistics and supply chain management systems using the analytical network process , 1998 .

[10]  Joseph Sarkis,et al.  Analyzing organizational project alternatives for agile manufacturing processes: An analytical network approach , 1999 .

[11]  Domingo Ribeiro Soriano.  Total Quality Management , 1999 .

[12]  Chung-Hsing Yeh,et al.  Inter-company comparison using modified TOPSIS with objective weights , 2000, Comput. Oper. Res..

[13]  Lisa Bowman,et al.  Selecting a hotel and determining salient quality attributes: a preliminary study of mature British travellers. , 2000 .

[14]  Soung Hie Kim,et al.  Using analytic network process and goal programming for interdependent information system project selection , 2000, Comput. Oper. Res..

[15]  Tat Y. Choi,et al.  An importance-performance analysis of hotel selection factors in the Hong Kong hotel industry: a comparison of business and leisure travellers , 2000 .

[16]  Shinhong Kim,et al.  An integrated approach for interdependent information system project selection , 2001 .

[17]  R. J. Callan,et al.  Business travellers' perception of service quality: a prefatory study of two European city centre hotels. , 2001 .

[18]  Adrien Presley,et al.  R&D project selection using the analytic network process , 2002, IEEE Trans. Engineering Management.

[19]  Fariborz Y. Partovi,et al.  Quality function deployment for the good of soccer , 2002, Eur. J. Oper. Res..

[20]  Hokey Min,et al.  Dynamic benchmarking of hotel service quality , 2002 .

[21]  A. Mattila,et al.  Relationships between Hotel Room Pricing, Occupancy, and Guest Satisfaction: A Longitudinal Case of a Midscale Hotel in the United States , 2003 .

[22]  Haemoon Oh,et al.  Price fairness and its asymmetric effects on overall price, quality, and value judgments: the case of an upscale hotel , 2003 .

[23]  Cihan Cobanoglu,et al.  Service quality in Cretan accommodations: marketing strategies for the UK holiday market , 2003 .

[24]  Eric W.T. Ngai,et al.  Design and development of a fuzzy expert system for hotel selection , 2003 .

[25]  Sevin Sozer,et al.  Product planning in quality function deployment using a combined analytic network process and goal programming approach , 2003 .

[26]  Fatma Pakdil,et al.  Patient satisfaction in a preoperative assessment clinic: an analysis using SERVQUAL dimensions , 2005 .

[27]  T. Lockyer.  The perceived importance of price as one hotel selection dimension , 2005 .

[28]  Wei-Ting Hung,et al.  Measuring the Cost Efficiency of International Tourist Hotels in Taiwan , 2006 .

[29]  H. G. Parsa,et al.  Pricing strategies to maximize revenues in the lodging industry , 2006 .

[30]  Ainhoa Urtasun,et al.  Hotel location in tourism cities: Madrid 1936–1998 , 2006 .

[31]  Ying-Ming Wang,et al.  Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment , 2006, Expert Syst. Appl..

[32]  W. Hung,et al.  Productivity and service quality changes in international hotels in Taiwan. , 2006 .

[33]  Huan-Jyh Shyur,et al.  COTS evaluation using modified TOPSIS and ANP , 2006, Appl. Math. Comput..

[34]  Hsu-Shih Shih,et al.  A hybrid MCDM model for strategic vendor selection , 2006, Math. Comput. Model..

[35]  Metin Dagdeviren,et al.  Using the analytic network process (ANP) in a SWOT analysis - A case study for a textile firm , 2007, Inf. Sci..

[36]  B. Merrilees,et al.  Towards an understanding of total service quality in hotels , 2007 .

[37]  Yu-Jie Wang,et al.  Applying FMCDM to evaluate financial performance of domestic airlines in Taiwan , 2008, Expert Syst. Appl..

[38]  Hessamaldin Mahdavinia Seyed.  Customer satisfaction in four star Isfahan hotels : an application of SERVQUAL model , 2008 .

[39]  Ling-Feng Hsieh,et al.  A service quality measurement architecture for hot spring hotels in Taiwan , 2008 .

[40]  İhsan Yüksel,et al.  A fuzzy analytic network process (ANP) model to identify faulty behavior risk (FBR) in work system , 2008 .

[41]  Semih Onüt,et al.  Transshipment site selection using the AHP and TOPSIS approaches under fuzzy environment. , 2008, Waste management.

[42]  Ching-Shih Tsou,et al.  Multi-objective inventory planning using MOPSO and TOPSIS , 2008, Expert Syst. Appl..

[43]  Irfan Ertugrul,et al.  Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods , 2009, Expert Syst. Appl..

[44]  Wei-Ting Hung,et al.  Pricing determinants in the hotel industry: Quantile regression analysis , 2010 .

[45]  Ling-Feng Hsieh,et al.  A performance evaluation model for international tourist hotels in Taiwan—An application of the relational network DEA , 2010 .

[46]  Metin Dagdeviren,et al.  A hybrid multi-criteria decision-making model for personnel selection in manufacturing systems , 2010, J. Intell. Manuf..