Can anyone please help me answer Part A) Q1)

Ford's management believes that in its first year of significant EV production, the company will secure 5% of the total U.S. EV market share. Over the following five years, this share is expected to steadily rise (equivalent annual percentage increase) to 30%. This projection takes into account Ford's established brand strength and existing market reach. After this period, we assume Ford's market share will remain consistent. Considering Ford's historical market positioning as a more affordable option compared to Tesla, it is assumed that the average selling price of a Ford-produced EV will be $45,000, in contrast to Tesla's average selling price of $55,000. Cost of Goods Sold (COGS): Assume that COGS for Ford's EVs will amount to 75% of the revenue generated from the EV segment. This estimation takes into account potential efficiencies derived from Ford's current manufacturing processes. R&D Expenses: Given Tesla's pioneering role in technological advancements, Ford might benefit from existing innovations. Assume that for the first 6 years, the R\&D expenses for the EV business will be 20% of its total R\&D expenses in 2022. Subsequent to this period, it is projected that Ford will allocate 5% of its anticipated EV-related revenue to R\&D. inventory. Other elements in current assets and liabilities can be challenging to interpret and may not give a true representation of the project's NWC.) Instructions: Please note that identifying the reliable data sources is very important for conducting a rigorous capital budgeting analysis. For this project, you may consult the following online data sources: I. Official/public institutions: World Bank, International Monetary Fund (IMF), Federal Reserve Economic Data (FRED), U.S. Securities and Exchange Commission (SEC), U.S. Bureau of Economic Analysis (BEA), U.S. Census Bureau, ... II. Other online sources: Wsj.com, Yahoo!Finance, Investing.com, Google Finance, ... Part A: Baseline Analysis (Total: 12/20) (1) Please retrieve additional data from reliable online resources and estimate the variable values highlighted in blue for subsequent analysis. (2/20)