Major Project Step-By-Step Guidance Follow The Materials Lis

Major Project Step By Step Guidancefollow The Materials Listed Below

Follow the materials listed below (find attached documents and links in Course Content, Period 3, Study Materials) and practice with the pricing simulation. The material is foundational to your developing and implementing a pricing strategy to maximize profits in the rental car simulation. Study and practice with these materials. Then, replicate these steps with the Major Project simulation scenario. The Major Project Report is essentially your explanation of these steps.

The Major Project will utilize two spreadsheets that don’t apply to the Scenario A (Introductory). You will use the Seasonality spreadsheet mentioned in the section below on Demand in the Orlando Rental Car Market, and you will use the elasticity spreadsheet titled Elasticities for Major Project Scenario w Compet charging 36,32 rather than the one for the constant demand scenario (A). Both are available in Period 3 Study Materials.

Paper For Above instruction

The Major Project in the context of rental car pricing strategies requires a systematic approach grounded in economic principles, data analysis, and strategic decision-making. This paper delineates the step-by-step guidance based on the provided materials and simulations to develop an optimal pricing and fleet management strategy aimed at maximizing profits.

Understanding the foundational concepts begins with familiarizing oneself with the pricing simulation tools. The introductory materials, such as the Panopto videos on the dashboard interface and decision variables—weekday and weekend prices—are essential. By interacting with the simulation environment, one develops an intuitive understanding of how demand responds to pricing and how to experiment within the system to observe outcomes. This experiential learning creates a basis for more advanced analysis, like elasticity estimation and contribution margin calculations.

The economics of the Orlando rental car market, particularly the demand and supply curves, form a core component of the strategic framework. The supply curve is vertical, reflecting a fixed fleet size in the short-term, while demand varies with price. Panopto videos explaining the demand and elasticity provide insights into how rental prices influence quantities demanded, emphasizing price elasticity of demand as an essential measure of customer responsiveness. Elasticities derived from simulation data, especially the scenario accounting for competition charges of 36 and 32, are vital for understanding how rental demand might change with price fluctuations.

Conceptually, price elasticity of demand measures the percentage change in quantity demanded resulting from a 1% change in price. In the simulation, elasticity was calculated by examining two data points at known prices and quantities to measure how quantity demand shifts with price. The spreadsheet of elasticities for the major project scenario demonstrates that elasticities increase in magnitude as prices rise; this indicates demand becomes more responsive—small price increases lead to larger drops in demand. Weekend demand tends to be more elastic than weekday demand, likely because customers have more flexible scheduling and alternatives on weekends.

Understanding the relationship between price elasticity and revenue is crucial. When demand is inelastic (|ε|1), increasing prices diminishes revenue because demand drops disproportionately. The elasticity spreadsheet and simulation data enable managers to identify price points where revenue peaks, guiding optimal pricing decisions.

Estimating background demand involves analyzing the Market Demand Tab in the simulation, which accounts for shifts in demand due to external factors such as seasonality. The seasonality spreadsheet tracks monthly demand variations from November to September, enabling the identification of trends and potential anomalies. These data contextualize demand changes, helping managers distinguish between seasonal effects and demand shifts attributable to pricing or competitive actions.

The concept of optimal price is rooted in profit maximization principles. Using contribution margin analysis, the optimal price is where marginal revenue equals marginal cost (MR=MC). The marginal cost in rental car operations primarily includes variable costs (e.g., $15 per unrented car), and the marginal revenue considers the impact of price changes on demand elasticity. The contribution margin can increase with price even when total revenue decreases if the reduction in demand causes MR to decrease less than MC. This occurs in the elastic range of pricing, where increasing price slightly reduces sales but increases profit margin per unit.

The iterative process involves calculating contribution margins at various price points, often on a monthly basis, to determine whether the profit at a given price exceeds that at alternative prices. Changes in background demand, seasonal factors, and competitor prices influence the optimal price. For instance, a decrease in background demand from November to December would likely increase the price elasticity of demand at the previous optimal price, suggesting a potential need to lower prices to maintain demand. Similarly, if competitors raise their prices, Universal’s demand elasticity may decrease, possibly allowing for higher prices without losing customers.

Pricing strategies also include indirect price discrimination, which involves charging different prices to different customer segments based on willingness or ability to pay. The simulation’s quantitative measures illustrate that this approach can increase profitability by capturing consumer surplus. Benefits to customers include access to lower prices for less elastic segments, but costs may include perceived unfairness or reduced transparency. Conditions necessary for effective indirect price discrimination—such as segmenting customers, preventing resale, and knowing customer willingness to pay—must be assessed based on actual data. When these conditions are met, Universal can enhance margins significantly.

Fleet size decisions are a critical component, given capacity constraints and inventory costs. The fixed fleet incurs ongoing costs for unrented cars, which can be substantial if capacity utilization is low. The process involves a MR=MC analysis similar to pricing decisions: reducing fleet size saves on inventory costs but may lead to unfilled demand if too small. The optimal fleet size balances these factors, maximizing total profit by considering the additional revenue gained from fuller utilization against the costs of idle vehicles.

Choosing the right fleet size requires sensitivity analysis—testing different fleet sizes and assessing the impact on profit margins. If fleet inventory is reduced below the level that fully meets demand at the optimal price, profits decline due to lost sales. Conversely, a larger fleet than necessary leads to excessive idle costs, eroding profits. The goal is to identify the point where the marginal benefit of additional capacity equals its marginal cost, factoring in predicted demand and operational costs.

Monitoring competitors is essential. Their pricing strategies impact Universal’s demand elasticity, unit sales, and market share. A competitor’s decision to set lower prices may provoke price wars, reducing profits across the market. Conversely, higher competitor prices might allow Universal to raise its prices, improving margins. Consistent tracking and strategic adaptation based on market conditions are vital for sustained profitability.

In conclusion, constructing an effective pricing and fleet management strategy in the rental car market involves integrating demand elasticity, seasonal and background demand patterns, contribution margin analysis, and competitive actions. The process requires iterative testing, sensitivity analysis, and continuous market monitoring. Applying these methods enables managers to find prices that maximize revenue and profit while maintaining competitive advantage and operational efficiency.

References

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• Nagle, T. T., & Müller, G. (2018). The Strategy and Tactics of Pricing: A Guide to Profitable Decision Making. Routledge.
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