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Demand function and forcasting

This is to help developing demand function for price setting business entity and forecasting the future demand

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Demand function and forcasting

  1. 1. Demand Estimation and Forecasting “Domino’s Barbeque Chicken Pizza” By Group 14
  2. 2. 2 • Introduced to Sri Lanka in 2011 by Jubilant Food Works with their strong strategy of ‘think global and act local’. Vision “Exceptional people on a mission to be the best pizza delivery company in the world!" • Currently, they operate 20 outlets in Colombo with more than 400 employees. Domino’s Sri Lanka
  3. 3.  Product : Domino’s Barbeque Chicken Pizza- Large  Considered only “Colombo area” due to there is an increase in demand.  Substitute: Assume Domino’s Spicy Chicken Pizza- Large portion as the substitute as information are not available for Pizza Hut. 3 Selections Used for the Assignment
  4. 4. Why We Selected “Domino’s Barbeque Chicken Pizza- Large”?  Due to the expansion of number of outlets to fulfill pizza demand  The price is set by Domino’s  Accessibility to information  Apparently, the demand for pizza depends advertisements, speed delivery service and promotions. 4
  5. 5. Demand for Domino’s Barbeque Chicken Pizza- Large Depend on, 5 Price of the product Prices of the substitutes No. of outlets in Colombo Advertisement cost No. of promotions Disposable incomeConsumer expenditure on Food Delivery Service Women employment No. of product varieties Performance incentives Other factors
  6. 6. The Demand Function 6 • Price of Domino’s Barbeque Chicken Pizza- Large portion - Pb • Price of Domino’s Spicy Chicken Pizza- Large portion ( price of the substitution) - Ps • Number of outlets in Colombo - O • Advertisement cost - A • Number of promotions conducted - R • Consumer expenditure on food per household in Western Province- C • Disposable income per person in Western Province- I Qd = Pb+Ps+O+ A + R + C + I
  7. 7. Sources and Units of Measurement Data Collected from Units of measurement Qd Domino’s Sri Lanka Numbers Pb Domino’s Sri Lanka LKR Ps Domino’s Sri Lanka LKR O Domino’s Sri Lanka Numbers R Domino’s Sri Lanka Numbers A Domino’s Sri Lanka LKR I Department of Census and Statistics LKR C Department of Census and Statistics LKR CCPI Central Bank of Sri Lanka (http://www.cbsl.gov.lk). LKR 7
  8. 8. Relevancy of the Sample Period and Frequency  Analyzed quarterly data from 2012 to 2015  Frequency: 16 quarters considered  Since pizza is a seasonal product to Domino’s, quarterly information represent entire population. 8
  9. 9. Estimation of Demand  Functional form: Linear function used as R2 Value is 0.9708 and elasticity of Pb is varying  Statistical Software: MS Excel  Estimation Process: 9 Obtain raw data Adjust raw data for CCPI Run the regression in MS Excel (data analysis)
  10. 10. Results of the Demand Estimation Regression Statistics Multiple R 0.9853 R Square 0.9708 Adjusted R Square 0.9452 Standard Error of the estimate 1,059.38 Observations 16 10 Model Summary
  11. 11. Results of the Demand Estimation ( Cont.) 11 Coefficients Standard Error t Stat P-value Intercept -35,557.30 14,081.45 -2.5251 0.0355 Pb -807.9744 281.8357 -2.8668 0.0209 Ps 848.9894 290.7003 2.9205 0.0192 O -148.1808 357.2717 -0.4148 0.6892 A 0.0001 0.00008 1.2225 0.2563 P 912.7613 186.2663 4.9003 0.00119 C -0.0641 0.2871 -0.2232 0.8290 I 0.1773 0.1871 0.9476 0.3711
  12. 12. Interpreting Parameters 12 Qd = -35,557.3 – 807.974 Pb + 848.9894 Ps – 148.1801O + 0.0001 A + 912.761 R - 0.0641 C + 0.1773 I • R2 value is 0.9708 • Coefficient of Pb is negative • Coefficient of Ps is positive • Coefficient of O is negative • Coefficient of A is positive • Coefficient of C is negative 1 Price 808 Qd 1 Price 849 Qd 1 Outlet 148 Qd 1 Ad. 0.0001 Qd 1 C 0.0641 Qd
  13. 13. Interpreting Parameters (Cont.) 13 1 R 913 Qd 1 I 0.177 Qd • Coefficient of R is positive • Coefficient of I is positive Since P Value is greater than 0.05, number of outlets in Colombo, advertisement cost, consumer expenditure on food per household in Western Province and disposable income per person in Western Province I are not statistically significant. After removing all insignificant factors the demand function is, 1 R Qd = -52299.5939 – 683.9388 Pb + 740.78809 Ps + 962.6143 R
  14. 14. Elasticity of Demand 14 1250 1300 1350 1400 1450 1500 1550 1600 1650 4720 6334 4947 9011 6790 11988 7112 14123 11665 12442 10001 17012 10317 15330 11712 21133 PRICEOFBBQPIZZA Demand Curve Quantity Sold • Price Elasticity of Demand is - 49.9% It towards perfect elasticity • Demand is mainly depend on promotions. Promotion Elasticity of Demand is 0.44%
  15. 15. Demand Forecasting 15 Forecasting Techniques :Linear trend forecasting & Time series forecasting (simple moving average method) Qt = 4449.47 + 760.62 t year Quarter T T^ 2016 Q1 17 17380 Q2 18 18141 Q3 19 18901 Q4 20 19662 year Quarter T^ S^ Y^ = T^ x S^ 2016 Q1 17380 1.0008 17393.90 Q2 18141 1.0774 19545.11 Q3 18901 0.7109 13436.72 Q4 19662 1.2109 23808.72 74184.45Total sales in 2016 Adjusted Forecast Trend Forecast Year Q1 Q2 Q3 Q4 2012 0.7597 1.2051 2013 0.8031 1.2802 0.6701 1.2522 2014 0.9973 1.0019 0.7930 1.3286 2015 1.3286 1.0866 Total 3.1290 3.3687 2.2228 3.7859 Total Average 1.0430 1.1229 0.7409 1.2620 4.1688 Adj. S 1.0008 1.0774 0.7109 1.2109 4 Seasons Seasonal Adjustment Table
  16. 16. Assumptions and Limitations  10% increment in consumer expenditure on food for western province after 2013  10% of Sri Lanka per capita income is considered as, per capita income of western province after 2013  Qualitative factors which are significant cannot be used for demand estimation  Time constraints 16
  17. 17. THANK YOU 17

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