Regression Analysis of American Hotels Having Price as Dependent Variable

7488 Words Apr 4th, 2013 30 Pages
ABM PROJECT 2013

1. INTRODUCTION AND SUMMARY OF RESEARCH HYPOTHESIS

It is common knowledge that the prices people have to pay for accommodation in hotels vary enormously. Furthermore, hotel revenue managers probably posses or more or less accurate intuition of what causes room rates to diverge. However, they do not know how Online Travel Agent sites select the leading hotels to be placed on their first search page. In this respect, some determinants are expected to be associated with hotel prices in a more or less linear way. To say it differently, price differences between hotels underscore the presence or not of some variables expected to influence the latter. It is essential for hotels to understand how they can price
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TABLE 1.1 LIST OF INDEPENDENT VARIABLES Name | Description | Categories | Nature | page | Page number of hotel entry in Orbitz listings | 1 = first page2 = second pagex = page x | Quantitative | reviews | Number of customer rating for the hotel on Orbitz. | | Quantitative | rating | Average Orbitz customer-rating score | On a 1-5 scale | Quantitative | stars | Hotel star-rating | 1,2,3,4 or 5 stars | Nominal - Qualitative | property_type | Property type | 0 = full service (hotel)1 = motel 2 = Inn/lodge 3 = bed and breakfast 4 = condominium 5 = youth hostel 6 = camping 7 = resort 8 = apartment hotel 9 = apartments | Nominal - Qualitative | pool | Swimming pool facility presence | 0 = no 1 = yes | Nominal - Qualitative | dest_id | Destination (city name) | 1 = Atlanta2 = Chicago3 = Los Angeles6 = Las Vegas7 = New York City13 = Orlando24 = Honolulu112 = Myrtle Beach | Nominal - Qualitative | Promo | Is the price a promotion? | 0 = no 1 = yes | Nominal - Qualitative |
1.3 Causal Relationship Scheme Below there is a graphical relationship of the relationships between all the variables. The nature of the relationships is indicated with a +, - or ?, signifying a positive, negative or unknown relationship. Independent variables with a (*) are qualitative. An explanation of these relationships is given in sections 1.4 Direct Relationships and 1.5 Indirect Relationships.

Figure 1.1 Causal
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