Modeling Demand Module 7. Conceptual Structure of SIMQ Market Model Firm Demand = Total Industry Demand * Share of Market Firm Demand = Average Firm Demand.

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Presentation transcript:

Modeling Demand Module 7

Conceptual Structure of SIMQ Market Model Firm Demand = Total Industry Demand * Share of Market Firm Demand = Average Firm Demand * n * Share of Market Firm Demand = Average Firm Demand * Normalized Share of Market Macro-economic Influences Seasonal Patterns Stage of Life Cycle Industry Activity Pricing, Promotion, Quality Competitive Profile Relative Pricing, Promotion, Quality, and Loyalty FD Relative Demand Exogenous Demand Endogenous Demand AFD NSOM

Normalised Share of Market NSOM is firm specific and a measure of relative demand, the predictor variables should also be relative to industry averages. For example, relative price of the firm is PREL = Firm’s Price / Industry Avg. Price NSOM Quality Promotion Pricing Loyalty Relative Price (current) Relative Advertising (current, t-1, t-2 ) Relative R&D (t-1, t-2) NSOM (t-1) NSOM = Firm Demand / Avg Firm Demand

Calculating NSOM 11) Use a multiple regression to estimate NSOM.

Average Firm Demand How many units will any firm sell on the average. AFD = Exogenous demand + Endogenous demand Exogenous demand = “Base demand” X Seasonal effects Endogenous demand = Influence of aggregate industry behavior Exog Endog Error

Average Firm Demand AFD Exogenous Demand Endogenous Demand Macro-Economic Influences - Seasonality - Stage of Life Cycle Estimate Trend and Seasonality using Time Series Analysis Industry Behavior - Pricing (Avg Price) - Promotion (Avg. Advertising) - Product Quality (Avg. R&D) Estimate weights of these factors using Regression Analysis AFD = {(T*S) + (B0+B1*Avg P+..)}

AFD: Exogenous Demand Base demand Population, Income, Tastes, Product life cycle, Substitutes and complements (Macro-economic influences) Seasonal demand Weather, Customs, Holidays Not all products are affected Estimation is done using: Time Series Decomposition

Calculating Exogenous AFD 1) Use Statpro to generate Seasonal Indices

Calculating Exogenous AFD 2) Use Seasonal Indices to De-seasonalize observations /.895 = 1607

Calculating AFD 3) Fit a simple regression line to the de-seasonalized observations.

Calculating AFD 4) Use the regression line to create a ‘de-seasonalized’ forecast. 11 * =

Calculating AFD 5) Re-seasonalize the predicted forecast. This is the exogenous portion of demand * =

Calculating AFD 6) Calculate the residual error from the forecast. This is the endogenous portion of demand – = 488.7

Calculating AFD 7) Fit a multiple regression with the residuals as the dependent variable and the firm data as the independent variables.

Calculating AFD 8) Use the new regression equation to forecast residuals. These are estimated of endogenous demand ( ) * (.0032) * (.0127) * = 4.2

Calculating AFD 9) Add the exogenous forecast to the endogenous forecast to create a composite forecast =

Calculating AFD 10) Subtract the composite forecast from the observations to find a total error – = 284.4

Calculating AFD 11) Calculate the standard deviation of the residuals. Because there may be more explanation that can be squeezed out of the trend and attributed to the dependent variables, repeat the process. For subsequent iterations, Raw AFD – Estimated Endogenous as starting data for time series. Continue till error stops decreasing.

Conceptual Structure of SIMQ Market Model With Average Firm Demand and Normalized Share of Market modeled, we can now create a decision support system for any individual firm. FD Relative Demand Exogenous Demand Endogenous Demand AFD NSOM

Example DSS