管理信息系统 MIS课件：ch08 Models and Decision Support.pptVIP

* * * * * * * * * * * * * * * * * Tampa Miami Fort Myers Jacksonville Tallahassee Gainesville Ocala Orlando Clewiston Perry 17,000 15,800 14,600 13,400 12,200- 1990 2000 20,700 19,400 18,100 16,800 15,500- per capita income 2000 Hard Goods 2000 Soft Goods 1990 Hard Goods 1990 Soft Goods Cases: Computer Hardware Industry Cases: Dell Computer Gateway 2000, Inc. What is the company’s current status? What is the Internet strategy? How does the company use information technology? What are the prospects for the industry? Appendix: Forecasting Uses Marketing Future sales Consumer preferences/trends Sales strategies Finance Interest rates Cash flows Financial market conditions HRM Labor costs Absenteeism Turnover Strategy Rivals’ actions Technological change Market conditions Forecasting Methods Structural Models Derive underlying models Estimate parameters Evaluate model Focus on explanation and cause Time Series Collect data over time Identify trends Identify seasonal effects Forecast based on patterns Q P S D D’ Increase in income time sales trend Structural Equations Demand is a function of Price Income Prices of related products QD = b0 + b1 Price + b2 Income + b3 Substitute QD = 1114 - 0.1 Price + 1.2 Income - 1.0 Substitute Model Estimate Data Forecast 33318 = 1114 - 0.1 (155) + 1.2 (20000) - 1.0 (160) Need to know (estimate) future price, income, and substitute price. Time Series Components time sales Dec Dec Dec Dec 1. Trend 2. Seasonal 3. Cycle 4. Random Trend Seasonal A cycle is similar to the seasonal pattern, but covers a time period longer than a year. Exponential Smoothing St = ?Yt + (1 - ?) St-1 S is the new data point ? is the smoothing factor Use Excel: Tools, Data Analysis Exponential Smoothing Exponential Smoothing Choosing the smoothing factor (?): It is usually between 0.01 and 0.20 Test multiple values and compare errors: (actual - smooth) * (actual - smooth) Compute the sum. Choose the factor with the least total sum-of-squared error. Sum S