Instructions Step 1: Prepare The Date Replace All Bundle Pri

Instructionsstep 1prepare The Date Replace All Bundle Prices Highlig

Prepare the date - Replace all bundle prices (highlighted in YELLOW) on the Analysis tab of the working sheet -- “Bundling - PSet1 – Part 2” -- by following these steps: Go to the WTP tab and locate the row with total willingness to pay for each bundle (row 103, Bundle WTP). Create a new sheet and use Excel’s transpose function to copy and paste these values vertically. Copy this array and paste it as values only in a separate column. Sort this column from smallest to largest values. Then, copy and paste the sorted values into the Analysis tab to replace the existing bundle prices.

Observe the new Bundle Demand and Bundle Profit curves. For students in the EU: You may need to adjust Excel settings so that all periods’ decimal points are not mistakenly converted to commas. Instructions are provided to change settings if necessary to avoid this issue. Additionally, for changing column labels from numbers to letters: Select File > Options > Formulas, then uncheck "R1C1 reference style" and save changes.

In the Analysis tab, calculate the empty cells highlighted in YELLOW to answer the questions below. Use other tabs as needed, reviewing prompts and formulas. Enter numeric values with up to 2 decimal places, following the exact format given.

Paper For Above instruction

This analysis involves updating bundle prices based on total willingness-to-pay data, examining demand and profit curves, and calculating key economic metrics such as optimal prices, firm profits, consumer surplus, and social value loss within an Excel framework. The process begins with accessing the WTP data, transforming it via Excel functions, and securely replacing price inputs on the analysis sheet. Adjustments for regional settings ensure accurate data interpretation, especially regarding decimal notation.

The primary objective is to compute the optimal price a firm should charge for a bundle to maximize profit, considering consumers’ valuations and willingness-to-pay. Using the sorted willingness-to-pay data, the analysis enables identification of the profit-maximizing bundle price. Calculates include total firm profits at this price, consumer surplus remaining after sale, and the proportion of consumers who do not purchase songs with positive value — all through precise data entry into yellow-highlighted cells based on predefined formulas.

Additional questions focus on evaluating consumer behavior and societal efficiency, such as whether consumers purchase bundles containing songs they did not rate, and estimating the social value potentially lost due to suboptimal bundling. Changes in the pricing strategy may be recommended if the marginal cost of goods shifts from zero to $0.12, requiring a critical assessment of whether to adjust bundle prices, remove low-WTP items, or retain the current strategy.

This comprehensive approach emphasizes meticulous data handling, accurate formula application, and sensitivity to pricing and market dynamics. Correct execution provides a framework for understanding consumer valuation, optimal bundling, and profit maximization, which are fundamental concepts in microeconomic analysis and managerial decision-making in digital content markets.

References

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