London School of Marketing Assignment Module: Emerging Themes An Analysis of the Events Industry in Brazil: How Government Policies coupled with Exponential Growth influence competition. Submission Deadline: 25th May 2012 1 INTRODUCTION TASK 1 - THEORETICAL FRAMEWORK (520 words) 1.1 The Macro-Economic Theme: Exponential economic growth 1.2 The Meso Theme Identified 1.3 Literature Review 3 3 3 4 TASK 2 - DISCUSSION PAPER (2362 words) Abstract Introduction Aims & Objectives
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Which of the following is the least useful sales forecasting model to use when sales are increasing? Select one: Trend adjusted exponential smoothing Weighted moving average Naïve Exponential smoothing ? Simple mean x Which of the following forecasting methods is most likely to be implemented to change an existing quantitative forecast to account for a new competitor in the marketplace? Select one: Gamma method Executive opinion Market research Naïve method Delphi method
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1. INTRODUCTION 1.1 Company Profile Toyota Motor‚ the world’s largest automotive manufacturer (overtaking GM in 2008)‚ designs and manufactures a diverse product line-up that includes subcompacts to luxury and sports vehicles‚ as well as SUVs‚ trucks‚ minivans‚ and buses. Its vehicles are produced either with combustion or hybrid engines‚ as with the Prius. Toyota’s subsidiaries also manufacture vehicles: Daihatsu Motor produces mini-vehicles‚ while Hino Motors produces trucks and buses. Additionally
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2009. A new Bayesian formulation for Holt’s exponential smoothing 3. Andrew‚ W.‚ Cranage‚ D.‚ Lee‚ C.‚ 1990. Forecasting hotel occupancy rates with time series models: an empirical analysis 4. Chow‚ W. S.‚ Shyu‚ J.-C.‚ Wang‚ K.-C.‚ 1998. Developing a forecast sys- tem for hotel occupancy rate using integrated ARIMA models 5. Franses‚ P. H.‚ 1998. Time Series Models for Business and Economic Fore- casting 6. Gardner‚ E. S.‚ 2006. Exponential smoothing: The state of the art Part II. 7. Hyndman
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weighted moving averages‚ exponential smoothing‚ and time series regression. For moving averages and weighted moving averages‚ use only the data for the past three fiscal years. For weighted moving averages‚ assign a value of 1 to the data for 20 X 2‚ a value of 2 to the data for 20 X 3‚ and a value of 3 to the data for 20 X 4. For exponential smoothing‚ assume that the last forecast for fiscal year 20 X 4 was $6‚300‚000. You decide on the alpha to be used for exponential smoothing. For time series regression
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Composition E) Consumer Market Survey Answer: B Page Ref: 477 Topic: Types of Forecasts Difficulty: Easy 4) Which of the following is NOT considered to be a Time-Series method of forecasting? A) Simple Linear Regression B) Moving Average C) Exponential Smoothing D) Seasonality Analysis E) Multiplicative/Additive Decomposition Answer: A Page Ref: 477 Topic: Types of Forecasts Difficulty: Moderate 5) An iterative group process that allows experts‚ who may be located in different places‚ to make forecasts
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weighted moving averages‚ assign a value of 1 to the data for 20X2‚ a value of 2 to the data for 20X3‚ and a value of 3 to the data for 20X4. Forecast personnel expenses for fiscal year 20X5 using moving averages‚ weighted moving averages‚ exponential smoothing‚ and time series regression. Moving Averages Fiscal Year Expenses 20X2 $5‚500‚000 20X3 $6‚000‚000 20X4 $6‚750‚000 20X2-4 $18‚250‚000 20X5 $18‚250‚000/3 = $6‚083‚333 Weighted
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(Time-series forecasting‚ easy) 11. One advantage of exponential smoothing is the limited amount of record keeping involved. True (Time-series forecasting‚ moderate) 12. The larger the number of periods in the simple moving average forecasting method‚ the greater the method’s responsiveness to changes in demand. False (Time-series forecasting‚ moderate) 13. Forecast including trend is an exponential smoothing technique that utilizes two smoothing constants: one for the average
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So the reason I have chosen MAD in exponential smoothing is that‚ in order to determine which of the values of alpha that are being considered as the lowest value‚ MAD can be used to identify which alpha is more effective and useful during forecasting. Mean square error help in order to determine the minimized optimal value of the constant‚ so in this method Clear Skies Airlines (CSA) can compute the optimal value of the exponential smoothing constant and also to improve the accuracy of
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$6‚750‚000 3 $20‚250‚000 __ ___________ 6 $37‚750‚000 20X5 $37‚750‚000 /6 = $6‚291‚667 Exponential Smoothing NF = $6‚300‚000 + 0.95($6‚750‚000 - $6‚300‚000) = $6‚300‚000 + 0.95(45‚000) = $6‚300‚000 + (42‚750) = $6‚342‚750 I would rather use moving averages‚ weighted moving averages‚ or exponential smoothing because I can better understand how the formulas and numbers turn out and how you get the answers from them. Even though the Time
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