Hotel Management Essay

Formally, the determinants of the room rate (R) a consumer must pay for a hotel stay is a function of various objective hotel attributes (O) (egg, type of board; distance to downtown; presence of swimming pool, bar and restaurant etc. ) and, possibly, more subjective attributes (S) (egg, service quality; hotel star rating; atmosphere etc. ).
Accordingly, the room rate for the tit hotel stay (RI) can be described as Ri h P(Ii, S’) where both Ii and Is are vectors f attributes.
Ordinary Least Squares (LOS) regression or the related log-linear form have in prior hospitality or tourism applications mostly been used to estimate this type of hedonistic price model. As there exists no official star-rating classification for the hotels that make up the data in this study, the subsequent analysis focuses solely on objective attributes. At first glance this might appear as a limitation because most Macmillan Ltd, 1476-6930 Throne previous scholars have included both star rating and objective attributes in their price hedonistic regressions.

However, as argued by Petrodollar (2002) and Throne (2005), using tar rating as an independent variable alongside objective attributes amounts to a specification error because star rating is an endogenous independent variable. The simple reason for this is that the star rating variable becomes a function of objective attributes to a substantial degree, in much the same sense as price. Another problem that arises with this procedure is that it likely will cause multimillionaires in many cases (e, high correlations between the independent variables).
Thus, the lack of an official star rating classification for the hotels in the data does not create problems in the present Monnet. In summary, prior research has clearly demonstrated that the prices faced by consumers in their choice of accommodation depend on the attributes embedded in the lodging facilities. In line with this research the purpose of the present study is to examine the relationships between a number of hotel attributes and room rates in and around the Norwegian capital of Oslo. Read about Golden Arch Hotel Switzerland
Data The data for this study were extracted from the Internet-based search engine for hotels in Norway in March 2005 (whim. Hotel. No). Originally 88 hotels came up on this list. Seven of these lodging premises could, however, not e classified as hotels and were therefore discarded from the sample. Furthermore, because an important aspect of hedonistic price modeling is to make sure that the data are homogeneous enough to make relevant comparisons, seven more hotels that could be classified as either very influential cases or as outliers were deleted from the sample.
Thus, the present analysis is restricted to 74 hotels. Arguably these data come closer to a population than to a sample. Nevertheless, the statistical analysis since there were few obvious reasons for why the data could not be envisioned as a random sample from a universe f hypothetical cases (Hinkle, 1976). The two dependent price variables in the study were the weekday rates in March 2005 for a one-night stay in a single or a double room.
It is important to note that these room rates do not necessarily reflect the price consumers actually pay because stays booked a long time in advance usually are bought at discount prices. As the hotels or hotel chains set their prices in advance, however, they signal hotel quality. For this reason it is unproblematic to use these ‘price-proposals’ as dependent variables within a price hedonistic framework (CB. Israeli 2002; Petrodollar 2002). Table 1 presents descriptive statistics for these dependent variables, both in level and logged form.

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