Deck 14: Forecasting Demand for Services
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Deck 14: Forecasting Demand for Services
1
The key feature of the historical analogy method is that it assumes some future event is related to the occurrence of an earlier event.
False
2
Exponential smoothing prevents overreaction to extremes in the actual observed values.
True
3
Costs for preparing time-series forecasts generally are lower than for other models.
True
4
The greatest advantage of subjective techniques like Delphi and cross-impact analyses, is that the methods are fairly standardized and do not require much expertise in actual use.
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5
Because of the nontangible nature of a service, forecasting does not play as important a role in service operations as in manufacturing operations.
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6
Both measures of forecast accuracy, MAD and MSD, give equal weight to all forecasting errors.
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7
The trade-off to be made with respect to accuracy is between the costs of inaccurate forecasts and the costs of increasing the accuracy of forecasts.
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8
The selection of candidate independent variables for a regression model to forecast motel occupancy requires input from knowledgeable marketing personnel.
Multiple Choice
Multiple Choice
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9
Historical analogy involves comparative analysis of the introduction and growth patterns of new items with similar previously-introduced items.
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10
Most forecasting models assume that the underlying pattern of behavior of their data will remain the same. The only component of error is attributable to random fluctuations that are not under the control of anyone.
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11
Both trend and seasonal adjustments can augment a single exponential-smoothing model.
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12
Seasonal adjustment involves the deseasonalization of data in a given cycle after smoothing.
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13
The cost of formulating, developing, and testing regression models, plus the expertise required to interpret results, often dictates the use of this model only for medium-term or long-term forecasting.
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14
One reason exponential smoothing is so popular is the ease with which it can be made to accommodate trend and seasonality in its forecasts.
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15
Subjective models are used to assess the future impact of changing demographics.
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16
The main advantage that simple moving-average models have over exponentially-smoothed models is that they can be made to give any desired weight to specific periods in the past.
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17
Econometric models are basically regression models that involve a system of equations.
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18
In the Delphi method, the opinions of experts are collected, then the analyst resolves differences of opinion to arrive at a consensus.
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19
The forecast horizon for a cross-impact analysis method is medium-term.
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20
Fast-food restaurants use a causal model to forecast daily demand for menu items.
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21
The Delphi method is best used when forecasting:
A) customer demand.
B) technological change.
C) correlations between events.
D) future economic conditions.
A) customer demand.
B) technological change.
C) correlations between events.
D) future economic conditions.
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22
All but one of the following are characteristics of the moving-average model:
A) very low relative cost.
B) short term forecast horizon.
C) uses all past data in forecast.
D) used for demand forecastsing.
A) very low relative cost.
B) short term forecast horizon.
C) uses all past data in forecast.
D) used for demand forecastsing.
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23
Survey results are used in:
A) regression.
B) cross-impact anlaysis.
C) econometric models.
D) Delphi method.
A) regression.
B) cross-impact anlaysis.
C) econometric models.
D) Delphi method.
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24
____ is the smoothing constant for the trend adjustment in an exponential smoothing forecast.
A) Alpha
B) Beta
C) Gamma
D) Delta
A) Alpha
B) Beta
C) Gamma
D) Delta
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25
The ___________ forecasting method requires the most computer power.
A) econometric
B) cross-impact
C) regression
D) historical analogy
A) econometric
B) cross-impact
C) regression
D) historical analogy
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26
Demand for hotel services will require the use of which one of the following forecasting models:
A) subjective and causal.
B) subjective and time series.
C) time series and causal.
D) only time series.
A) subjective and causal.
B) subjective and time series.
C) time series and causal.
D) only time series.
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27
Long-term forecasts do not deal with predictions for:
A) new services.
B) changes in mix of services.
C) overtime or temporary labor requirements.
D) process technology.
A) new services.
B) changes in mix of services.
C) overtime or temporary labor requirements.
D) process technology.
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28
_____________ is used best to forecast demand.
A) Exponential smoothing
B) Historical analogy
C) Dephi method
D) Econometrics
A) Exponential smoothing
B) Historical analogy
C) Dephi method
D) Econometrics
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29
Characteristics of forecasting models include all but one of the following:
A) data required.
B) economic conditions.
C) relative cost.
D) forecast horizon.
A) data required.
B) economic conditions.
C) relative cost.
D) forecast horizon.
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30
The usual range of the smoothing constant for a simple exponential smoothing forecast is:
A) 0.1-0.5
B) 0.3-0.7
C) 0.5-0.7
D) 0.5-1.0
A) 0.1-0.5
B) 0.3-0.7
C) 0.5-0.7
D) 0.5-1.0
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31
The forecast horizon for regression methods is _________.
A) short term.
B) medium term.
C) long term.
D) medium to long term.
A) short term.
B) medium term.
C) long term.
D) medium to long term.
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32
In forecasting, the term "cycle" refers to repetition of data:
A) once a year, if seasonal.
B) once in a period.
C) within a week.
D) during a day.
A) once a year, if seasonal.
B) once in a period.
C) within a week.
D) during a day.
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33
Exponential smoothing uses a feedback control mechanism because:
A) is less than 1.
B) calculations are based on modifying the previous smooth value.
C) the calculation contains the forecast error.
D) the weights given to past data are exponentially distributed.
A) is less than 1.
B) calculations are based on modifying the previous smooth value.
C) the calculation contains the forecast error.
D) the weights given to past data are exponentially distributed.
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34
Which one of the following is not an advantage of the Simple Exponential Smoothing model over the N-period Moving Average model?
A) Old data are never dropped.
B) Older data are given progressively less weight.
C) Calculation is simple.
D) None of the above.
A) Old data are never dropped.
B) Older data are given progressively less weight.
C) Calculation is simple.
D) None of the above.
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35
All of the following are forecasting models, except:
A) subjective.
B) objective.
C) causal.
D) time series.
A) subjective.
B) objective.
C) causal.
D) time series.
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36
Which oneof the following is an example of a causal model?
A) Delphi method
B) Moving average
C) Cross-impact analysis
D) Regression
A) Delphi method
B) Moving average
C) Cross-impact analysis
D) Regression
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37
Regression models require all but one of the following:
A) numerical data.
B) subjective data.
C) independent variables.
D) dependent variable.
A) numerical data.
B) subjective data.
C) independent variables.
D) dependent variable.
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38
In regression models, the variable of interest (being forecast) is called a(an):
A) defining variable.
B) independent variable.
C) basic variable.
D) dependent variable.
A) defining variable.
B) independent variable.
C) basic variable.
D) dependent variable.
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39
Subjective forecasting models are best characterized by:
A) the use of experts.
B) the use of opinion as a basis for a forecast.
C) the absence of data manipulation.
D) the use of simultaneous equations.
A) the use of experts.
B) the use of opinion as a basis for a forecast.
C) the absence of data manipulation.
D) the use of simultaneous equations.
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40
The accuracy of a time-series model is dependent upon:
A) the nature of past data.
B) the weight given to past data.
C) the treatment of seasonality and trend.
D) the assumption that the future is a projection of the past.
A) the nature of past data.
B) the weight given to past data.
C) the treatment of seasonality and trend.
D) the assumption that the future is a projection of the past.
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