Principles of Operations Management: Sustainability and Supply Chain Management (10th Edition)
10th Edition
ISBN: 9780134181981
Author: Jay Heizer, Barry Render, Chuck Munson
Publisher: PEARSON
expand_more
expand_more
format_list_bulleted
Concept explainers
Question
Chapter 4, Problem 17P
Summary Introduction
To determine: Find the forecast of sales using exponential smoothing with smoothing constant 0.6 and 0.9 and infer the effect of exponential smoothing on forecast. Using MAD, determine the accurate forecast of exponential smoothing with given smoothing constant 0.3, 0.6 and 0.9.
Introduction: A sequence of data points in successive order is known as time series. Time series
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
14
Community General Hospital finds itself treating many bicycle accident victims. Data from the last seven 24-hour periods is shown below:
Day Bicycle Victims
1 8
2 14
3 8
4 14
5 18
6 15
With an alpha value of 0.31 and a starting forecast in day 3 equal to the 21 , what is the exponentially smoothed forecast for day 4? (Round to two decimal places)
15
What is the exponentially smoothed forecast for day 5? (Round to two decimal places)
Use the trend projection method, and the trend projection with seasonal adjustment method to create forecasting models in Excel. Next, using the two models, compute the forecasted values of monthly total passengers between 2010 to 2012
Compare the above two models using MAD, MSE, and MAPE Please explain which of the two models is performing better and why?
Use the best model to forecast the monthly total passengers for year 2013
The manager of a popular tourist resort wants to use the manual trend projection forecasting technique and exponential smoothing without trend to forecast room occupancy at the resort for the next 4 years. Using a numerical example, demonstrate how these techniques can be used to do the forecast.
REQUIREMENT- USE EXPONENTIAL SMOOTHING(WITHOUT TREND) ONLY
Chapter 4 Solutions
Principles of Operations Management: Sustainability and Supply Chain Management (10th Edition)
Ch. 4 - Ethical Dilemma We live in a society obsessed with...Ch. 4 - What is a qualitative forecasting 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 - Prob. 14DQCh. 4 - In your own words, explain adaptive forecasting.Ch. 4 - Prob. 16DQCh. 4 - Explain, in your own words, the meaning of the...Ch. 4 - Prob. 18DQCh. 4 - Give examples of industries that are affected by...Ch. 4 - Prob. 20DQCh. 4 - Prob. 21DQCh. 4 - CEO John Goodale, at Southern Illinois Power and...Ch. 4 - The following gives the number of pints of type B...Ch. 4 - a) Plot the above data on a graph. Do you observe...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 - Prob. 12PCh. 4 - At you can see in the following table, demand for...Ch. 4 - Prob. 14PCh. 4 - Refer to Solved Problem 4.1 on page 144. a) Use a...Ch. 4 - Prob. 16PCh. 4 - Prob. 17PCh. 4 - Prob. 18PCh. 4 - Income at the architectural firm Spraggins and...Ch. 4 - Resolve Problem 4.19 with = .1 and =.8. Using...Ch. 4 - Prob. 21PCh. 4 - Refer to Problem 4.21. Complete the trend-adjusted...Ch. 4 - Prob. 23PCh. 4 - The following gives the number of accidents that...Ch. 4 - In the past, Peter Kelles tire dealership in Baton...Ch. 4 - George Kyparisis owns a company that manufactures...Ch. 4 - Attendance at Orlandos newest Disneylike...Ch. 4 - Prob. 28PCh. 4 - The number of disk drives (in millions) made at a...Ch. 4 - Prob. 30PCh. 4 - Emergency calls to the 911 system of Durham, North...Ch. 4 - Using the 911 call data in Problem 4.31, forecast...Ch. 4 - Storrs Cycles has just started selling the new...Ch. 4 - Boulanger Savings and Loan is proud of its long...Ch. 4 - Mark Gershon, owner of a musical instrument...Ch. 4 - Prob. 44PCh. 4 - Cafe Michigans manager, Gary Stark, suspects that...Ch. 4 - Prob. 46PCh. 4 - The number of auto accidents in Athens, Ohio, is...Ch. 4 - Rhonda Clark, a Slippery Rock, Pennsylvania, real...Ch. 4 - Accountants at the Tucson firm, Larry Youdelman,...Ch. 4 - Prob. 50PCh. 4 - Using the data in Problem 4.30, apply linear...Ch. 4 - Bus and subway ridership for the summer months in...Ch. 4 - Prob. 53PCh. 4 - Dave Fletcher, the general manager of North...Ch. 4 - Sales of tablet computers at Ted Glickmans...Ch. 4 - The following are monthly actual and forecast...Ch. 4 - Develop a forecasting model, justifying its...Ch. 4 - Prob. 2CSCh. 4 - Discuss the schools options.Ch. 4 - Prob. 1.1VCCh. 4 - Prob. 1.2VCCh. 4 - Using Perezs multiple-regression model, what would...Ch. 4 - Prob. 1.4VCCh. 4 - Describe three different forecasting applications...Ch. 4 - What is the role of the POS system in forecasting...Ch. 4 - Justify the use of the weighting system used for...Ch. 4 - Name several variables besides those mentioned in...Ch. 4 - Prob. 2.5VC
Knowledge Booster
Learn more about
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 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_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_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_forward
- The number of fishing rods selling each day is given below. Perform analyses of the time series to determine which model should be used for forecasting. 3 day moving average analysis 4 day moving average analysis 3 day weighted moving average analysis with weights W1=0.2, W2=0.3 and W3=0.5 with W1 on the oldest data. Exponential smoothing analysis with A=0.3 Which model provides a better fit of the data? Forecast day 13 sales of fishing rods using the model chosen in part (e) Day Rods Sold 1 60 2 70 3 110 4 80 5 70 6 85 7 115 8 105 9 65 10 75 11 95 12 85 Please read the relevant article, found in the VLE, before answering the question. Discuss the process and findings of the study of the article. Suggest a possible study that could be done at your current or past job that could use a similar methodology and analysis.arrow_forwardCompute a 3-month weighted average forecast for months 4 through 9. Assign weights of 0.55, 0.33 and 0.12 to the months in sequence, starting with the most recent month. Compare the two forecasts using MAD. Which forecast is better the 3-month moving average or the 3-month weighted moving average and why?arrow_forwardBased on the following equation for a moving average forecast, what would have been the three week moving average forecast for week 53 for Small Town Restaurant (see downloaded file for actual demand)? Provide two decimal places and use normal rounding. What happens if we increase the time periods in our moving average forecast to six weeks opposed to three? Group of answer choices It would be more accurate because it includes more data. There would be no change. It would be less sensitive to changes. It would be better at predicting a trend.arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- Practical Management ScienceOperations ManagementISBN:9781337406659Author:WINSTON, Wayne L.Publisher:Cengage,Contemporary MarketingMarketingISBN:9780357033777Author:Louis E. Boone, David L. KurtzPublisher:Cengage LearningMarketingMarketingISBN:9780357033791Author:Pride, William MPublisher:South Western Educational Publishing
Practical Management Science
Operations Management
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:Cengage,
Contemporary Marketing
Marketing
ISBN:9780357033777
Author:Louis E. Boone, David L. Kurtz
Publisher:Cengage Learning
Marketing
Marketing
ISBN:9780357033791
Author:Pride, William M
Publisher:South Western Educational Publishing
Single Exponential Smoothing & Weighted Moving Average Time Series Forecasting; Author: Matt Macarty;https://www.youtube.com/watch?v=IjETktmL4Kg;License: Standard YouTube License, CC-BY
Introduction to Forecasting - with Examples; Author: Dr. Bharatendra Rai;https://www.youtube.com/watch?v=98K7AG32qv8;License: Standard Youtube License