Deck 21: Operational Decison-Making Tools: Transportation and Transshipment Models

Question 1

A seasonal pattern is an oscillating movement in demand that occurs periodically over the short-run and is repetitive.

Answer 1

True

Question 2

Movements in demand that do not follow a given pattern are referred to as random variations.

Answer 2

True

Question 3

In today's competitive environment, effective supply chain management requires absolute demand forecasts.

Answer 3

False

Question 4

A gradual, long-term up or down movement of demand over time is referred to as a trend.

Question 5

The type of forecasting method selected depends on time frame, demand behavior and causes of behavior.

Question 6

Because of globalization of markets, managers are finding it increasingly more difficult to create accurate demand forecasts.

Question 7

The trend toward continuous replenishment in supply chain design has shifted the need for accurate forecasts from long-term to short-term.

Question 8

One way to deal with the bullwhip effect is to develop and share the forecasts with other supply chain members.

Question 9

Because of advances in technology, many service industries no longer require accurate forecasts to provide high quality service.

Question 10

Forecasts based on mathematical formulas are referred to as qualitative forecasts.

Question 11

Many companies are shifting from long-term to short-term forecasts for strategic planning.

Question 12

Short-midrange forecasts tend to use quantitative models that forecast demand based on historical demand.

Question 13

Sharing demand forecasts with supply chain members has resulted in an increased bullwhip effect.

Question 14

The type of forecasting method selected depends on time frame, demand behavior, and causes of behavior.

Question 15

Long-range quantitative forecasts are used to determine future demand for new products, markets, and customers.

Question 16

Forecasting customer demand is often a key to providing good quality service.

Question 17

Qualitative forecasts use mathematical techniques and statistical formulas.

Question 18

The type of forecasting method used depends entirely on whether the supply chain is continuous replenishment or not.

Question 19

Continuous replenishment systems rely heavily on extremely accurate long-term forecasts.

Question 20

Because of heightened competition resulting from globalization most companies find little strategic value in long-range forecasts.

Question 21

Correlation in linear regression is a measure of the strength of the relationship between the dependent variable, demand, and an independent (explanatory) variable.

Question 22

Because of the development of advanced forecasting models managers no longer track forecast error.

Question 23

A linear regression model that relates demand to time is known as a linear trend line.

Question 24

Multiple regression analysis can be used to relate demand to two or more dependent variables.

Question 25

Because of ease of use and simplicity, exponential smoothing is preferred over smoothing average.

Question 26

One reason time series methods are popular for forecasting is that they are relatively easy to use and understand.

Question 27

The larger the mean absolute deviation (MAD) the more accurate the forecast.

Question 28

The moving average method is used for creating forecasts when there is no variation in demand.

Question 29

Time series methods use historical data to predict future demand.

Question 30

A correlation coefficient is a measure of the strength of the linear relationship between an independent and a dependent variable.

Question 31

The long-term strategic planning process is dependent upon qualitative forecasting methods.

Question 32

The Delphi method generates forecasts based on informed judgments and opinions from knowledgeable individuals.

Question 33

Linear regression relates two variables using a linear model.

Question 34

The most common type of forecasting method for long-term strategic planning is based on quantitative modeling

Question 35

Exponential smoothing is an averaging method for forecasting that reacts more strongly to recent changes in demand.

Question 36

The demand behavior for skis is considered cyclical.

Question 37

Forecast bias is measured by the per-period average of the sum of forecast errors.

Question 38

Regression is used for forecasting when there is a relationship between the dependent variable, demand, and one or more independent (explanatory) variables.

Question 39

The average, absolute difference between the forecast and demand is a popular measure of forecast error.

Question 40

Time series methods assume that demand patterns in the past are a good predictor of demand in the future.

Question 41

Given the demand and forecast values below, the naïve forecast for September is

A) 100.6.
B) 99.0.
C) 102.0.
D) cannot be determined.

Question 42

Continuous replenishment relies heavily on ____________term forecast.

A) short-
B) medium-
C) long-
D) All of these answer choices are correct.

Question 43

Forecasts of product demand determine how much

A) inventory is needed.
B) product to make.
C) material to purchase from suppliers.
D) All of these answer choices are correct.

Question 44

In ___________________ replenishment, the supplier and customer care continuously update data.

A) demand
B) ongoing
C) continuous
D) forecasted

Question 45

A forecast

A) predicts what will occur in the future.
B) results from an uncertain process.
C) support strategic planning.
D) All of these answer choices are correct.

Question 46

An exponential smoothing forecasting technique requires all of the following except

A) the forecast for the current period.
B) the actual demand for the current period.
C) a smoothing constant.
D) large amounts of historical demand data.

Question 47

A long-range forecast would normally not be used to

A) design the supply chain.
B) implement strategic programs.
C) determine production schedules.
D) plan new products for changing markets.

Question 48

The _______ method uses demand in the first period to forecast demand in the next period. a) naïve
B) moving average
C) exponential smoothing
D) linear trend

Question 49

Selecting the type of forecasting method to use depends on

A) the time frame of the forecast.
B) the behavior of demand and demand patterns.
C) the causes of demand behavior.
D) All of these answer choices are correct.

Question 50

Forecast methods based on judgment, opinion, past experiences, or best guesses are known as ___________ methods.

A) quantitative
B) qualitative
C) time series
D) regression

Question 51

The closer the smoothing constant, α, is to 1.0 the

A) greater the reaction to the most recent demand.
B) greater the dampening, or smoothing, effect.
C) more accurate the forecast.
D) less accurate the forecast.

Question 52

The sum of the weights in a weighted moving average forecast must

A) equal the number of periods being averaged.
B) equal 1.00.
C) be less than 1.00.
D) be greater than 1.00.

Question 53

The exponential smoothing model produces a naïve forecast when the smoothing constant, α, is equal to

A) 0.00.
B) 1.00.
C) 0.50.
D) 2.00

Question 54

A ___________ is an up-and-down movement in demand that repeats itself over a period of more than a year.

A) trend
B) seasonal pattern
C) random variation
D) cycle

Question 55

Which of the following is not a type of predictable demand behavior?

A) trend
B) random variation
C) cycle
D) seasonal pattern

Question 56

A forecast where the current period's demand is used as the next period's forecast is known as a

A) moving average forecast.
B) naïve forecast.
C) weighted moving average forecast.
D) Delphi method.

Question 57

________________ demand is a key to providing good-quality service.

A) Predicted
B) Forecasted
C) Anticipated
D) Unknown

Question 58

The ______________ effect is caused in part by distortion in product demand information caused by inaccurate forecasts.

A) bullwhip
B) regression
C) error
D) None of these answer choices is correct.

Question 59

A qualitative procedure used to develop a consensus forecast is known as

A) exponential smoothing.
B) regression methods.
C) the Delphi technique.
D) naïve forecasting.

Question 60

The smoothing constant, α, in the exponential smoothing forecast

A) must always be a value greater than 1.0.
B) must always be a value less than 0.10.
C) must be a value between 0.0 and 1.0.
D) should be equal to the time frame for the forecast.

Question 61

If the forecast for July was 3,300 and the actual demand for July was 3,250, then the exponential smoothing forecast for August using α = 0.20 is

A) 3,300.
B) 3,290.
C) 3,275.
D) 3,250.

Question 62

The mean absolute percentage deviation (MAPD) measures the absolute error as a percentage of

A) all errors.
B) per-period demand.
C) total demand.
D) the average error.

Question 63

For the demand values and the January forecast shown in the table below the exponential smoothing forecast for March using α = 0.40 is
A) 1,200.

A) 1,220.
B) 1,222.
C) 1,225.

Question 64

The per-period average of cumulative error is called

A) cumulative forecast variation.
B) absolute error.
C) average error.
D) noise.

Question 65

Given the demand and forecast values shown in the following table, calculate the three-period moving average forecast for November.

A) 516.
B) 528.
C) 524.
D) 515.

Question 66

Given the demand and forecast values shown in the table below, the mean absolute deviation (MAD) through the end of October is

A) 9.20
B) -9.20
C) 1.00
D) 7.00

Question 67

A forecasting model has produced the following forecasts: The mean absolute percent deviation (MAPD) for the end of May is

A) 0.0250.
B) 0.0583.
C) 0.5830.
D) 0.6670.

Question 68

A forecasting model has produced the following forecasts: At the end of May the average error would be

A) 7.
B) 5.
C) 3.
D) 1.

Question 69

Given the following demand data for the past five months, the three-period moving average forecast for June is

A) 103.33.
B) 99.00.
C) 95.00.
D) 92.50

Question 70

A forecasting model has produced the following forecasts, the forecast error for February is

A) 10.
B) -10.
C) -15.
D) -5

Question 71

Given the demand and forecast values shown in the table below, the exponential smoothing forecast for November using α = 0.35 is

A) 552.45.
B) 553.50.
C) 554.55.
D) 557.50.

Question 72

A forecasting model has produced the following forecasts: The mean absolute deviation (MAD) for the end of May is

A) 7.0.
B) 7.5.
C) 10.0.
D) 3.0

Question 73

Given the following demand data for the past five months, the four-period moving average forecast for June is

A) 96.25.
B) 99.00.
C) 110.00.
D) 93.75.

Question 74

The _________________ forecast method consists of an exponential smoothing forecast with a trend adjustment factor added to it. a) exponentially smoothed
B) adjusted exponentially smoothing
C) time series
D) moving average

Question 75

For the demand values and the January forecast shown in the table below the exponential smoothing forecast for March using α = 0.30 is

A) 489.
B) 486.
C) 483.
D) 480.

Question 76

Given the demand and forecast values shown in the table below, the forecast error for September is

A) 10.00.
B) -10.00.
C) 1.00.
D) 39.00.

Question 77

The weighted moving average forecast for the fifth period, with weights of 0.15 for period 1, 0.20 for period 2, 0.25 for period 3, and 0.40 for period 4, using the demand data shown below is

A) 3,760.
B) 3,700.
C) 3,650.
D) 3,325.

Question 78

If forecast errors are normally distributed then

A) 1 MAD = 1σ
B) 1 MAD ≈ 0.8 σ
C) 0.8 MAD ≈ 1σ
D) 1 MAD ≈ 1.96 σ

Question 79

A company wants to produce a weighted moving average forecast for April with the weights 0.40, 0.35, and 0.25 assigned to March, February, and January respectively. If the company had demands of 5,000 in January, 4,750 in February, and 5,200 in March, then April's forecast is

A) 4983.33.
B) 4992.50.
C) 4962.50.
D) 5000.00.

Question 80

A forecasting model has produced the following forecasts: At the end of May the tracking signal would be

A) 0.000.
B) 0.667.
C) 1.333.
D) 2.143.