The study is related to the petrol retail pricing, which aims to work on the price response demand model, pricing optimization models and derive the optimal pricing strategies. These aspects of the study are crucial as it guides in determining the suitable strategies of optimized prices of petrol. In particular, the study focuses on the following:
Hypotheses
HO1: There is an association of volume of regular unleaded petrol with its price.
HO2: There is an association of volume of regular unleaded petrol with its average price.
HO3: There is an association of log of volume of regular unleaded petrol with its log price.
HO4: There is an association of log of volume of regular unleaded petrol with its log average price.
Variables
The variables which are included in the study entail the following:
Vol = Volume in gallons of regular unleaded petrol sold at the site on that day
Price = price per gallon in dollars changed by that site
AvgCompPrice = average price charged by competitors to the site
LN_ Vol = log of volume of regular unleaded petrol sold
LN_ P0 = log of price
Weekday = Dummy variable
LN_ AvgCompPrice = log of average price charged by competitors
Preliminary Analysis
Descriptive Statistics
N
Range
Minimum
Maximum
Mean
Standard Deviation
Variance
Vol
1737
5024.00
1468.00
6492.00
3755
979.52892
9.595E5
P0
1737
1.34
2.96
4.30
3.5767
.42041
.177
AvgCompPrice
1737
1.37
2.92
4.29
3.5461
.41879
.175
MinCompPrice
1737
1.38
2.88
4.26
3.4889
.41695
.174
MaxCompPrice
1737
1.38
2.96
4.34
3.5907
.42033
.177
Valid N (listwise)
1737
From the above table which relates to the descriptive statistics indicates volume regular unleaded petrol sold, price of petrol, average, minimum and maximum price charged by the competitors. From these variables of the study, it can be observed that the mean value of the volume of regular unleaded petrol is 3755; however, it is found that mean of maximum price charged by the competitors which is close normal price charged; furthermore, the total numbers of cases are 1737. On the contrary, it is revealed that there is too much deviation in the average price charged by the competitors as the standard deviation and also the variance is high for average price charged in comparison to other prices.
Pricing Analytics
Regression with volume (sales) as the dependent variable and price and average competitor price as the independent variables
Model Summary b
Model
R
R Square
Adjusted R Square
Standard Error of the Estimate
Change Statistics
R Square Change
F Change
df 1
df 2
Significance value F change
1
.281 a
.079
.078
940.71914
.079
74.097
2
1734
.000
a. Predictors: (Constant), AvgCompPrice, P0
b. Dependent Variable: Vol
The above regression analysis relates to volume, price and average competitor price, in which the table of model summary shows that value of R Square is 0.079 and adjusted R Square is 7.8%, which indicates that there is an association of volume with the price and average competitor price of the petrol; however, this 7.8% shows weak association of dependent variable with the independent variable.
Analysis of Varianceb
Model
Sum of Squares
df
Mean Square
F
Significance value
1
Regression
1.311E8
2
6.557E7
74.097
.000 a
Residual
1.535E9
1734
884952.493
Total
1.666E9
1736
a. Predictors: (Constant), AvgCompPrice, P0
b. Dependent Variable: Vol
Furthermore, the analysis of variance table is presenting that the level of significance is zero that presents that there confirms the result of the model summary table that is there is an association of volume with the price and average competitor price of the petrol. However, for the detailed analysis of association, consider the following table;