Operations and Supply Chain Management 9th edition
9th Edition
ISBN: 9781119320975
Author: Roberta S. Russell, Bernard W. Taylor III
Publisher: WILEY
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Textbook Question
Chapter 12, Problem 14Q
What determines the choice of the smoothing constant for trend in an adjusted exponential smoothing model?
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What is the difference between adjusted exponential smoothing and exponential smoothing?
Sales of Volkswagen's popular Beetle have grown steadily at auto dealerships in Nevada during the past 5 years (see table below). Using exponential smoothing with a smoothing constant
(α)
of
0.30
and a starting forecast of
420.00,
the following sales forecast has been developed:
Year
Sales
Forecasted Sales
1
460
420.00
2
510
432.00
3
520
455.40
Using smoothing constants of
0.60
and
0.90,
develop forecasts for the sales of VW Beetles. Use MAD to determine which of the three smoothing constants
(0.30,
0.60,
or
0.90)
gives the most accurate forecast.
The MAD for a forecast developed using exponential smoothing with
α=0.30
is
nothing
sales. (Round your response to two decimal places.)
The data shown in the following table represent visitors to the Hawaiian Islands over the past several years, by quarter. Use the
data for the first five years to estimate the seasonal and trend factors. Then build an exponential smoothing model (incorporating
both trend and seasonal factors) to provide for the forecasts of the remaining periods. Plot the actual visitors and the forecasts.
Compare the accuracy of the forecasts in the 1985 to 1990 period with those subsequent to that period.
Thousands of Persons
Second
Third
Fourth
Annual
First Quarter
Year
Quarter
Quarter
Quarter
Visitors
1980
1,004.8
942.9
1,047.3
939.5
3,934.5
1981
959.0
984.5
1,042.3
948.8
3,934.6
1982
1,054.0
1,048.7
1,110.7
1,029.5
4,242.9
1983
1,069.9
1,071.5
1,146.4
1,080.2
4,368.0
1984
1,218.5
1,206.8
1,222.9
1,207.4
4,855.6
1985
1,301.5
1,129.6
1,266.9
1,186.2
4,884.2
1986
1,393.2
1,421.2
1,450.9
1,341.8
5,607.1
1987
1,448.9
1,370.0
1,555.2
1,425.8
5,799.9
1988
1,484.9
1,488.2
1,635.6
1,533.7
6,142.4
1989…
Chapter 12 Solutions
Operations and Supply Chain Management 9th edition
Ch. 12 - List some of the operations and functions in a...Ch. 12 - What is the difference between quantitative...Ch. 12 - Describe the difference between short- and...Ch. 12 - Prob. 4QCh. 12 - Why is accurate forecasting so important to...Ch. 12 - Discuss the relationship between forecasting and...Ch. 12 - Prob. 7QCh. 12 - Describe the Delphi method for forecasting.Ch. 12 - What is the difference between a trend and a cycle...Ch. 12 - How is the moving average method similar to...
Ch. 12 - In the chapter examples for time series methods,...Ch. 12 - What effect on the exponential smoothing model...Ch. 12 - How does adjusted exponential smoothing differ...Ch. 12 - What determines the choice of the smoothing...Ch. 12 - How does the linear trend line forecasting model...Ch. 12 - Of the time series models presented in this...Ch. 12 - What advantages does adjusted exponential...Ch. 12 - Describe how a forecast is monitored to detect...Ch. 12 - Explain the relationship between the use of a...Ch. 12 - Selecting from MAD, MAPD, MSE, E, and E, which...Ch. 12 - What is the difference between linear and multiple...Ch. 12 - Define the different components (y, x, a, and b)...Ch. 12 - A company that produces video equipment, including...Ch. 12 - The Hartley-Davis motorcycle dealer in the...Ch. 12 - The manager of the I-85 Carpet Outlet needs to be...Ch. 12 - The LawnPlus Fertilizer Company distributes...Ch. 12 - Graph the demand data in Problem 12.3. Can you...Ch. 12 - The chairperson of the department of management at...Ch. 12 - The manager of the Excom Service Station wants to...Ch. 12 - The Intrepid mutual fund of growth stocks has had...Ch. 12 - The Oceanside Hotel is adjacent to City Coliseum,...Ch. 12 - Mary Hernandez has invested in a stock mutual fund...Ch. 12 - Globetron manufactures components for use in small...Ch. 12 - The Bee Line Caf is well known for its popular...Ch. 12 - For the demand data in Problem 12.11, develop a...Ch. 12 - Develop a seasonally adjusted forecast for the...Ch. 12 - Backstreets Pizza delivery service has randomly...Ch. 12 - The Willow River Mining Company mines and ships...Ch. 12 - The Great Northwest Outdoor Company is a catalog...Ch. 12 - Townside Food Vending operates vending machines in...Ch. 12 - The town aquatic center has an indoor pool that...Ch. 12 - Develop an adjusted exponential smoothing forecast...Ch. 12 - During the past five months the emergency room at...Ch. 12 - At its craft store and through its website, the...Ch. 12 - A group of business students at Tech organized a...Ch. 12 - Temco Industries has developed a forecasting model...Ch. 12 - Monitor the forecast in Problem 12.23 for bias...Ch. 12 - Develop a statistical control chart for the...Ch. 12 - Monitor the adjusted exponential smoothing...Ch. 12 - Develop an exponential smoothing forecast with =...
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Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, operations-management and related others by exploring similar questions and additional content below.Similar questions
- Under what conditions might a firm use multiple forecasting methods?arrow_forwardThe owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?arrow_forwardThe Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?arrow_forward
- The file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars) through credit unions. a. Use these data to forecast consumer revolving credit through credit unions for the next 12 months. Do it in two ways. First, fit an exponential trend to the series. Second, use Holts method with optimized smoothing constants. b. Which of these two methods appears to provide the best forecasts? Answer by comparing their MAPE values.arrow_forwardThe file P13_29.xlsx contains monthly time series data for total U.S. retail sales of building materials (which includes retail sales of building materials, hardware and garden supply stores, and mobile home dealers). a. Is seasonality present in these data? If so, characterize the seasonality pattern. b. Use Winters method to forecast this series with smoothing constants = = 0.1 and = 0.3. Does the forecast series seem to track the seasonal pattern well? What are your forecasts for the next 12 months?arrow_forwardDo the sales prices of houses in a given community vary systematically with their sizes (as measured in square feet)? Answer this question by estimating a simple regression equation where the sales price of the house is the dependent variable, and the size of the house is the explanatory variable. Use the sample data given in P13_06.xlsx. Interpret your estimated equation, the associated R-square value, and the associated standard error of estimate.arrow_forward
- How to use the simple exponential smoothing methodarrow_forwardQuantitative forecasting should be preferred over qualitative forecasting since they involve computations and are, therefore, more accurate. True Falsearrow_forwardPlease do not give solution in image formate thanku. The Willow River Mining Company mines and ships coal. It has experienced the following demand for coal during the past eight years: Year Coal Sales (tonnes) 1 4260 2 4510 3 4050 4 3720 5 3900 6 3470 7 2890 8 3100 Develop an adjusted exponential smoothing model (α=0.30, β=0.20) and a linear trend line model, and compare the forecast accuracy of the two using MAD. Indicate which forecast seems to be most accurate.arrow_forward
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