# Modeling Price Elasticity Kiran Ravulapati, Katia Frank, Wassim Chaar Delta Technology, Atlanta, GA 30354.

## Presentation on theme: "Modeling Price Elasticity Kiran Ravulapati, Katia Frank, Wassim Chaar Delta Technology, Atlanta, GA 30354."— Presentation transcript:

Modeling Price Elasticity Kiran Ravulapati, Katia Frank, Wassim Chaar Delta Technology, Atlanta, GA 30354

2 What is Price Elasticity ? Price Elasticity (PE) A PE of -1.5 means there is a 1.5% drop in demand for a 1% increase in price.

3 Price Elasticity - Literature Past research modeled price elasticity at a macro level using aggregated, high level data. - Oum, Tae H., Zhang, Anmin and Zhang, Yimin (1993) Inter-Firm Rivalry and Firm- Specific Price elasticities in Deregulated Airline Markets, Journal of Transport Economics and Policy,27, 171-192 Price elasticity at product level received little attention. Perhaps, this is because of the revenue management effects involved.

4 Price Elasticity - Assumptions We modeled simple price elasticity only. Interaction between products is not considered. We studied the vacuum scenario i.e., all airlines in the market have same prices. Revenue management effects are consistent.

5 Price Elasticity - Vacuum Step 1: Divide historical demand/price data into fare bands.

6 Price Elasticity - Vacuum Step 2: Remove RM effect by cumulating demand. Bookings for market XXX-YYY Discounted Coach 0-10 30-4060-70 90-100 120-130150-160180-190210-220240-250270-280300-310330-340360-370390-400420-430 fareband Cumulative Demand

7 Price Elasticity - Vacuum Step 3: Adjust the curve for sell up. Bookings for market XXX-YYY Discounted Coach 0-10 30-4060-70 90-100 120-130150-160180-190210-220240-250270-280300-310330-340360-370390-400420-430 fareband Cumulative Demand Adjusted Cumulative Demand

8 Price Elasticity - Sell Up Total Demand = 16 + 50 + 30 = 96 \$50-\$70 \$70-\$90\$90-\$110 2050 30 Demand 300.8*20 = 16

9 Price Elasticity - Vacuum Step 4: Fit a function to the adjusted demand curve using regression analysis and calculate price elasticity. Price Vs Demand Curve for market XXX-YYY Discounted Coach 0-10 30-4060-70 90-100 120-130150-160180-190210-220240-250270-280300-310330-340360-370390-400420-430 fareband Demand

10 Price Elasticity - Vacuum

11 Price Elasticity - Results

12 Price Elasticity - Results

13 Price Elasticity - Results

14 Price Elasticity - Summary This model is a first step towards developing a methodology for price elasticity. Select a representative sample of historical data. Group only similar markets/products for this analysis. To capture seasonal changes in prices, this analysis should be repeated for each season using new data.

15 Price Elasticity - Summary Revenue management effects, spill and capacity limits, should be used to determine the impact of fare increase/decrease. Methodology can be used at various aggregate levels - market/region/airline/products. Possible extensions - Impact of fare rules - Interaction between substitutable products