PETROL RETAIL PRICING

Petrol Retail Pricing

Petrol Retail Pricing

Introduction

Overview

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;

Coefficients a

Model

Un-standardized Coefficients

Standardized Coefficients

t

Significance value

Collinearity Statistics

B

Standard Error

Beta

Tolerance

Variance inflation ...