Setting an advertising budget is a forecasting exercise. What are the fundamental principles that should be adhered to when undertaking forecasting?
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K 2.
Setting an advertising budget is a
Be conservative and use the best evidence-based technique available
Be innovative and use multiple methods and choose the optimal one
Be conservative and use multiple evidence-based techniques, taking the average result
Be innovative and use multiple evidence-based techniques, taking the average result
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- 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.The 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?What forecasting techniques are used in the management of technology and innovation?
- 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?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?The 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?
- The 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?Q2 (a) Understanding the inherent strengths and weaknesses of each forecasting method is important for technology managers to ensure technological development and innovation can be conducted successfully. Compare the strengths and weaknesses of TWO (2) technology forecasting methods.Qualitative forecasting methods should be used only asa last resort. Agree or disagree? Comment.
- Tools Add-ons Help Accessibllity Last al text Calibri 11 BIUA = ニ三▼三 + 1 2 3 TI 4 I 5. 6. Using your own words, describe the drawbacks of the moving average forecasting model and the drawbacks of the nalve forecasting model. Provide an example to contrast these two methods. acerWhat forecasting methods should the company consider? Please justify.which of the following are charactersitics of qualitative forecasting methods? 1. Function of past data,2. Non numerical data , 3. useful when past data is avaialable , based on 4. broad range of knowledge , personal judgement, and intuition?
