Chapter 13 Measuring and Forecasting Demand Virginia Tech HTM 2454

downloaded from

Scholarfriends

https://scholarfriends.com Downloaded by: writerforacademic@gmail.com | https://scholarfriends.com/singlePaper/275523/chapter-13-measuring-and-forecastingdemand-virginia-tech-htm-2454 Distribution of this document is illegal.

Measuring and Forecasting Demand Chapter 13

Department of Hospitality and Tourism Management

Overview  Propensity and Resistance  Methods of Forecasting Tourism Demand  Meaningful Measures of Demand  Questions to consider

Department of Hospitality and Tourism Management

Demand to a Destination Depends on Propensity and Resistance Demand = f(propensity, resistance)

 Propensity depends  Resistance depends on: on:  Psychographics  Demographics  Motivations

 Economic distance  Cultural distance  Cost of services  Quality of services  Effectiveness of advertising and promotion Department of Hospitality and Tourism  Seasonality Management

3 Meaningful Measures of Actual Demand  Visitor arrivals

 Easiest type of data to obtain, but sometimes inadequate: doesn’t tell us anything about the amount of money each visitor has spent while at the destination

 Visitor-days or –nights  Practical and useful for transportation and other public facilities, as well as hoteliers, but still results in the need to estimate expenditures

 Amount spent  *Most meaningful measure of demand, but the most difficult to obtain Department of Hospitality and Tourism Management

Types of Demand Projection Methods  Trend Analysis  Simple Regression  Multiple Regression  Computer Simulations and Models  Why predicting demand is important:  Want to be able to be predict how many customers will be comingDepartment and of Hospitality and Tourism Management price hotel rooms accordingly to

Trend Analysis  Involves interpreting historical data  Can be calculated with basic data like past visitor arrivals  BUT you get what you pay for: trend analysis does not explain the “why”

Department of Hospitality and Tourism Management

Simple Regression  Explains the relationship between demand and one particular variable (income, age, etc.)  BUT you can only consider one variable at a time

Department of Hospitality and Tourism Management

Multiple Regression  Explains the relationship between demand and several other variables, so it’s more reliable  Similar to simple regression but can use multiple variables  Income  Past visitor arrivals  Age  Cost  distance

 BUT data collection can be costly Department of Hospitalityand and Tourism Management

Computer Simulations and Models  The most comprehensive  BUT requires a great deal of expensive data and expertise

Department of Hospitality and Tourism Management

Delphi Method  Simply ask the experts!  Systematic survey of experts in a particular field  BUT requires the cooperation and time of a group of very busy people

Department of Hospitality and Tourism Management

Best Method  A combination of a delphi method and computer simulations  But expensive and involves a lot of time

Department of Hospitality and Tourism Management

Questions to consider  What method(s) produce(s) the most reliable demand estimates in any given situation? Read the textbook and find out!  Why is predicting demand important for those in the tourism industry?

Department of Hospitality and Tourism Management