Petrol Retail Pricing

Petrol Retail Pricing

This exercise is based on a sample provided by a fuel pricing solution provider. Imagine that you are a pricing analyst and helping a US petrol retailer to analyze its pricing strategies. A sample of data was collected from one of sites this retailer operated. You shall produce a business analytical report to help the client understand its demand structure, modelling the pricing decisions and provide insights into the pricing strategies.
The data in the file shows Petrol sales in gallons and prices in dollars. The columns are as follows:
• Date
• Weekday
• Vol – the volume in gallons of regular unleaded petrol sold at the site on that day
• Price – the price per gallon in dollars changed by that site
• AvgCompPrice – The average price charged by competitors to the site
• MinCompPrice – The lowest priced competitor to the site on the given day
• MaxCompPrice – The highest priced competitor to the site on the given day
Marking principle:
1. Understanding on the retail fuel (petrol) market and provide prescriptive analytic insight into the pricing decisions in such as a business context. (10%)
Note: You may want to associate spot market price with the retail fuel pricing. Some market information and data can be found in websites like (http://www.eia.gov/petroleum/data.cfm#prices). You should be able to use summary statistics to provide descriptive analytics and insights for the pricing data, and ask relevant research questions and hypotheses which will be studied in the following analysis.

2. Fit the price-response demand model and compare different demand models, analyze the own price elasticity and competitor’s price elasticity, and more importantly provide insights into petrol pricing using the predictive analytics. (45%)
Notes: You should compare at least the following demand models and discuss the corresponding hypothesis behind the model.
a. Linear regression with volume (sales) as the response (dependent variable) and own price and average competitor price as the predictors (independent variables).
b. Linear regression with natural logarithm (LN) of volume as the response and LN(price) and LN(average comp price) as the independent variables.
c. Include the weekday as a predictor by creating dummy variables (Note that you need to remove linear dependency).
d. You can also include the month or season as the predictor to address the seasonality effect.
e. You can further improve the model performance by examining the reference price effect and competition effect. You can then measure the competitive price elasticity.
f. Compare the above models to other model specifications you are interested.
Write down the model coefficients and R squared output (and adjusted-R squared output), then compare the goodness-of-fit using the (adjusted-)R squared output. Next, choose the best performance model and write down the demand function. You should also provide the model diagnosis to ensure that the model is specified properly. Finally, comment on the price elasticity of the sales and the impact of different characteristics (e.g., weekday, seasonality) on the price elasticity. You should be able to interpret the results clearly. As a business report, only presenting the statistical results is not enough. More importantly, you should use the statistical results (including the comparison of the models) to provide insights into the pricing strategies (even before you formally formulate the optimization models).

3. Propose the pricing optimization models and derive the optimal pricing strategies. You should be able to state the model formulation clearly, explaining the meanings and implications of each term. Then you should show how you develop the optimal solutions and analyze the characteristics of the pricing solutions. Finally, you should be able to examine the performance of the proposed pricing solutions using the sample data. Since the cost information is not available. You can use the regular gasoline spot price in the same period of time as the proxy (http://www.eia.gov/petroleum/data.cfm#prices). For those days without spot price information (as there was no trading in spot market), using the available price of the previous day. (40%)

Notes: First, you can choose a demand model from the above to formulate the optimization problem. Second, formulate the pricing decision problem, describing the assumptions, objective function, decision variables and constraints. Third, you should find the optimal pricing strategies by analyzing the optimization model. Fourth, you should apply your strategies to the sample data and compare the performances of your model and the actual performance. Finally, you should provide insights from the optimization analysis.
4. Summarize the key results and insights. Point out the limitations of the research and improvement opportunities. (5%)

Report Format and Structure
The main body of the report must be no more than 2000 words in length and NO more than 10 pages in the main body of the report. This limit does NOT include appendices but you should keep the whole report as short as possible. The main body of the report focuses on managerial discussion, modelling, results and insights. The details of the statistical analysis should be presented in the appendix unless you feel that it is important to highlight some of the technical details in the main body.
The reference structure:
Section 1: An overview of the characteristics of the petrol market and the retail petrol pricing problem.
Section 2: Preliminary analysis for the data with descriptive statistics.
Section 3: Pricing analytics – estimate the price response and price elasticity.
Section 4: Pricing decision modelling and optimization.
Section 5: Concluding remarks.
Technical appendix (optional)
You should use single line spacing and a font size no less than 11. As this is such a short report you do not need to start different sections on separate pages and you do not need to include a table of contents or an executive summary. You do not need to review the literature. But if you cite a paper or a piece of news, you should provide the reference or the link.
On your title page please include:
• your name and college;
• your library card number;
• the following statement: “I accept the University rules on cheating and plagiarism. I state that the work submitted is my own and does not contain any unacknowledged work from other sources. As the author of the submitted work I am prepared to undertake an oral examination of its contents.”

In all other respects the choice of format is yours.
Submission
Your report should be submitted online as a single Word document. The deadline for submission is Monday 21th Jan 12pm 2013. (Note that when you submit your coursework you can see it on Moodle VLE but other students cannot.)
Please submit a paper copy of your report that explains clearly how you address the following research questions. You can enclose part of your spreadsheet or SPSS outputs into the Appendix section and use the annotation feature to comment on the content in cell. But you should NOT simply copy the software output in the main body of your report. In addition, please submit two pieces of your course work in electronic form. First, please submit your printed report as a word file. Please name your file MSCI381-LastName-LibraryCardNumber.docx, e.g., in my case the file name will be MSCI381-Pang-00XXXX.docx. Second, please also submit your excel-workbooks with your numerical answers for the two exercises. This will be used only if your paper answer is not self-explaining and we need to check how you derived the solutions. If you use SPSS, please copy the output to the excel sheet. Please put the answer for each question on a separate sheet within the Excel-workbook. Please name your file MSCI381-LastName-LibraryCardNumber.xlsx.

Please post it, in an unsealed envelope with your name written clearly on the front in the appropriate box near the Skein Room (Management Science Staff coffee room) opposite room A50 in the Management School. You should also complete a Coursework Declaration Form and hand it in at the same time as your work. Your work (electronic copies) should also be submitted to Moodle, and it will be processed via the Turn It In plagiarism detection software.
This coursework is to be done as an individual piece of work. Your analysis and report must be your own work alone. You should not discuss it with other students. Collusion and plagiarism are regarded as serious offences. Please note that software to detect plagiarism and collusion will be used.

Late work without an agreed extension will be penalised according to the University rules: 10% is deducted for work up to one week late; 0 marks are given for work more than a week late.

 

 

 

Declaration

I accept the University rules on cheating and plagiarism. I state that the work submitted with this declaration is my own and does not contain any unacknowledged work from other sources. As the author of the submitted work I am prepared to undertake an oral examination of its contents.
Signature …………………………………………………………….
Name in capitals ……………………………………………………..
Library card no. ……………………………………………………..
Course ………………………………………………………….…….
Coursework title ……………………………………………………..
Date ………………………………………………………………….
Notes
1. Additional advice on plagiarism is given on LUVLE at: http://luvle.lancs.ac.uk/MSci/FAQ.nsf

2. Cases of plagiarism may be brought to the attention of the External Examiners at the Examination Board and may also be referred to in any references to prospective employers and others which members of the department are asked to provide.

University rules on cheating and plagiarism in coursework

The following are extracts from the rules of the University (Sections 1.1, 1.3 and 1.4 from Appendix A). The complete rules can be found at http://www.lancs.ac.uk/users/acadreg/calendar/rules.htm
“1.1 It is an academic offence for a candidate to commit any act designed to obtain for himself/herself, or another, an unfair advantage with a view to achieving a higher grade or mark than his/her abilities would otherwise secure. Any such attempt to convey deceitfully the impression of acquired knowledge, skills, understanding, or credentials shall represent a contravention of Rule 6 of the University, and may constitute grounds for exclusion. The following list details examples of such contraventions. This list is not, and does not purport to be, comprehensive.
1.3 Plagiarism occurs when a candidate appropriates the thoughts, writings or results of another, and presents these as his/her own. Assessed work undertaken outside formal and class examinations must be the candidate’s own work, and acknowledge both assistance given and the major source(s) involved. All forms of plagiarism are considered serious academic offences but plagiarism which involves intrusion upon the work of fellow students will normally be viewed more severely than plagiarism which involves the misuse of secondary sources.

1.4 Fabrication of results occurs when a candidate claims deceitfully to have carried out tests, research, experiments or observations as part of his/her assessed work, or presents fabricated results arising from the same with the object of gaining an unfair advantage.

 

 

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