Operations Management: Sustainability and Supply Chain Management (12th Edition)
12th Edition
ISBN: 9780134130422
Author: Jay Heizer, Barry Render, Chuck Munson
Publisher: PEARSON
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Chapter 4, Problem 13DQ
Explain the value of seasonal indices in
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Chapter 4 Solutions
Operations Management: Sustainability and Supply Chain Management (12th Edition)
Ch. 4 - What is a qualitative foretasting model, and when...Ch. 4 - Identify and briefly describe the two general...Ch. 4 - Identify the three forecasting time horizons....Ch. 4 - Briefly describe the steps that are used to...Ch. 4 - A skeptical manager asks what medium-range...Ch. 4 - Explain why such forecasting devices as moving...Ch. 4 - What is the basic difference between a weighted...Ch. 4 - What three methods are used to determine the...Ch. 4 - Research and briefly describe the Delphi...Ch. 4 - What is the primary difference between a...
Ch. 4 - Define time series.Ch. 4 - What effect does the value of the smoothing...Ch. 4 - Explain the value of seasonal indices in...Ch. 4 - Which forecasting technique can place the most...Ch. 4 - In your own words, explain adaptive forecasting.Ch. 4 - What is the purpose of a tracking signal?Ch. 4 - Explain, in your own words, the meaning of the...Ch. 4 - What is the difference between a dependent and an...Ch. 4 - Give examples of industries that are affected by...Ch. 4 - Give examples of industries in which demand...Ch. 4 - Prob. 21DQCh. 4 - Prob. 22DQCh. 4 - The following gives the number of pints of type B...Ch. 4 - 4.2 a. Plot the above data on a graph. Do you...Ch. 4 - Refer to Problem 4.2. Develop a forecast for years...Ch. 4 - A check-processing center uses exponential...Ch. 4 - The Carbondale Hospital is considering the...Ch. 4 - The monthly sales for Yazici Batteries, Inc., were...Ch. 4 - The actual demand for the patients at Omaha...Ch. 4 - Daily high temperatures in St. Louis for the last...Ch. 4 - Lenovo uses the ZX-81 chip in some of its laptop...Ch. 4 - Data collected on the yearly registrations for a...Ch. 4 - Use exponential smoothing with a smoothing...Ch. 4 - Consider the following actual and forecast demand...Ch. 4 - As you can see in the following table, demand for...Ch. 4 - Following are two weekly forecasts made by two...Ch. 4 - Refer to Solved Problem 4.1 on page 138. a. Use a...Ch. 4 - Solved example 4.1 Sales of Volkswagens popular...Ch. 4 - Refer to Solved Problem 4.1. Using smoothing...Ch. 4 - Consider the following actual (At) and forecast...Ch. 4 - Income at the architectural firm Spraggins and...Ch. 4 - Question 4.20 Resolve Problem 4.19 with =.1 and ...Ch. 4 - Question 4.21 Refer to the trend-adjusted...Ch. 4 - Question 4.22 Refer to Problem 4.21. Complete the...Ch. 4 - Question 4.23 Sales of quilt covers at Bud Baniss...Ch. 4 - Question 4.25 The following gives the number of...Ch. 4 - Prob. 25PCh. 4 - Question 4.27 George Kyparisis owns a company...Ch. 4 - Question 4.28 Attendance at Orlandos newest...Ch. 4 - Question 4.29 North Dakota Electric Company...Ch. 4 - Question 4.33 The number of internal disk drives...Ch. 4 - Dr. Lillian Fok, a New Orleans psychologist,...Ch. 4 - Emergency calls to the 911 system of Durham, North...Ch. 4 - Using the 911 call data in Problem 4.43, forecast...Ch. 4 - Question 4.47 Storrs Cycles has just started...Ch. 4 - Question 4.49 Boulanger Savings and Loan is proud...Ch. 4 - Question 4.24 Mark Gershon, owner of a musical...Ch. 4 - Lori Cook has developed the following forecasting...Ch. 4 - Prob. 45PCh. 4 - Question 4.32 The following data relate the sales...Ch. 4 - Question 4.34 The number of auto accidents in...Ch. 4 - Question 4.35 Rhonda Clark, a Slippery Rock,...Ch. 4 - Accountants at the Tucson firm, Larry Youdelman,...Ch. 4 - Sales of tablet computers at Ted Glickmans...Ch. 4 - Question 4.38 City government has collected the...Ch. 4 - Using the data in Problem 4.39, apply linear...Ch. 4 - Bus and subway ridership for the summer months in...Ch. 4 - Thirteen students entered the business program at...Ch. 4 - Question 4.48 Dave Fletcher, the general manager...Ch. 4 - The following are monthly actual and forecast...Ch. 4 - Prob. 1CSCh. 4 - Prob. 2CSCh. 4 - Prob. 3CSCh. 4 - For its first 2 decades of existence, the NBAs...Ch. 4 - For its first 2 decades of existence, the NBAs...Ch. 4 - For its first 2 decades of existence, the NBAs...Ch. 4 - For its first 2 decades of existence, the NBAs...Ch. 4 - Forecasting at Hard Rock Cafe Video Case With the...Ch. 4 - Forecasting at Hard Rock Cafe Video Case With the...Ch. 4 - Forecasting at Hard Rock Cafe Video Case With the...Ch. 4 - Forecasting at Hard Rock Cafe Video Case With the...Ch. 4 - Forecasting at Hard Rock Cafe Video Case With the...
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- Under what conditions might a firm use multiple forecasting methods?arrow_forwardThe 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 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 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 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_forwardThe file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your model. What makes this time series more challenging to forecast?arrow_forward
- The file P13_26.xlsx contains the monthly number of airline tickets sold by the CareFree Travel Agency. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think will provide the best forecasting model? Why? b. Use simple exponential smoothing to forecast these data, using a smoothing constant of 0.1. c. Repeat part b, but search for the smoothing constant that makes RMSE as small as possible. Does it make much of an improvement over the model in part b?arrow_forwardThe file P13_02.xlsx contains five years of monthly data on sales (number of units sold) for a particular company. The company suspects that except for random noise, its sales are growing by a constant percentage each month and will continue to do so for at least the near future. a. Explain briefly whether the plot of the series visually supports the companys suspicion. b. By what percentage are sales increasing each month? c. What is the MAPE for the forecast model in part b? In words, what does it measure? Considering its magnitude, does the model seem to be doing a good job? d. In words, how does the model make forecasts for future months? Specifically, given the forecast value for the last month in the data set, what simple arithmetic could you use to obtain forecasts for the next few months?arrow_forwardThe file P13_28.xlsx contains monthly retail sales of U.S. liquor stores. 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_forward
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