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Rent-A-Car: an integrated team-based case study




Question;Rent-A-Car Project;Due date: June 15, 2014;Datasets;and description for the case assignments;In this project, you are;required estimate the demand for ?economy? vehicles using the variables;provided. The dependent variable is QE_Y and there are 11 independent variables;(X1 to X11)Identify the relationship;between the dependent variable (Y) and each of the independent variables (X).;For example, the relationship between variable QE_Y and variable PownL_X2 is;positive. Economy vehicles and Luxury;vehicles are substitute. If the rate of;luxury vehicles (and PownL_X2) rises, the quantity demanded for economy;vehicles (QE_Y) increases. Using Excel or any other;statistical software to run regression analysis and estimate the coefficients;of each independent variable X. Your;model should look like the following:QE_Y = constant (or intercept) + a1X1+;a2X2+ a3X3+ a4X4+;a5X5+ a6X6+ a7X7+;a8X8+ a9X9+ a10X10+;a11X11+ a12X12Compute elasticities for;PownE_X1, PownL_X2, and pcomp_X3 for week 30.What other factors besides;price might be included in this equation? Do you foresee any difficulty in;obtaining these additional data or incorporating them in the regression;analysis?What proportion of the;variation in the dependent variable is explained by the independent variables;in the equations?;Rent-A-Car: Description of the variables in the data;set;Variable Type;Variable Name;Variable Explanation;Dependent;variable;QE_Y;Number of;rental contracts initiated each week in the economy category;Independent;variable;PownE_X1;Average daily;rate Rent-A-Car charged for its economy cars in a given week;Independent;variable;PownL_X2;Average daily;rate Rent-A-Car charged for its luxury vehicles in a given week;Independent;variable;Pcomp_X3;Average daily;rate of the only competitor across all vehicle categories;Independent;variable;Session_X4;Binary;variable with 1 indicating weeks when college is in session;Independent;variable;Weather_X5;Number of;days in a week with severe weather;Independent;variable;Unemployment_X6;Number of;unemployed workers in the county as of Tuesday each week;Independent;variable;FlghtWk_X7;Number of;flights (in- and outbound) serving the local airport that week;Independent;variable;CancWk_X8;Total number;of flights cancelled that week;Independent;variable;Holiday_X9;Binary;variable with 1 indicating weeks of national holidays (long weekends);Independent;variable;Wrecks_x10;Number of;major accidents that week;Independent;variable;TotalAd_X11;Amount spent;on local advertising each week;Independent;variable;FleetAge_X12;Average age;of our fleet measured in weeks


Paper#57097 | Written in 18-Jul-2015

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