Hotel_Wide: Data from a Major Hotel Chain

Hotel_WideR Documentation

Data from a Major Hotel Chain

Description

'Hotel_Wide', a 'Wide format', is a preprocessing data of the publicly available 'Hotel 1' data introduced in Bodea et al. (2009).

Usage

Hotel_Wide

Format

'Hotel_Wide': A data frame with 1,100 rows and 22 variables:

Booking_ID

ID associated with a booking. Begins at one for each hotel property.

Party_Size

Number of adults and children associated with the booking.

Membership_Status

Status in rewards program (0—not a member, 1—basic, 2—elevated, 3—premium).

VIP_Membership_Status

Membership status of a VIP rewards program member (0—not a VIP, 1—basic VIP, 2—premium VIP member).

Booking_Date

Date the booking was created (e.g., 20070303 = March 3, 2007).

Check_In_Date

Check-in date (e.g., 20070307 = March 7, 2007).

Check_Out_Date

Check-out date (e.g., 20070310 = March 10, 2007).

Length_of_Stay

Length of stay/number of nights (e.g., three).

Room_Type

Code describing the room type associated with the product ID.

Purchased_Prod_Code

Unique number of products associated with room type.

Exposed_Choice_Set

Choice set exposed to individual

Exposed_Choice_Set_Code

Unique number of choice sets associated with Exposed_Choice_Set

Price_1 ~ Price_10

The average nightly rate the customer pays in USD (e.g., $199.99). Note that the average nightly rate will not match the rate of any available product rates if an upsell occurs at time of check-in, if the customer requests a specific discount rate at time of check-in, etc.

Details

'Hotel 1' data contains information on the available alternatives, i.e., choice sets and the associated prices at the time of each customer’s booking decision. We preprocessed 'Hotel 1' data and provide it in two types of data format, 'Hotel_Long' and 'Hotel_Wide'.

The following are the preprocessing of 'Hotel 1' data.

1. Customers' booking transactions that had only one room type available in their choice set were removed as our methods require at least two different products in each choice set.

2. Duplicate records was removed.

3. Choice sets with less than 30 observations, representing rare case were removed.

Source

doi:10.1287/msom.1080.0231


RMM documentation built on May 9, 2022, 5:08 p.m.

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