學門類別
最新個案
- Leadership Imperatives in an AI World
- Vodafone Idea Merger - Unpacking IS Integration Strategies
- V21 Landmarks Pvt. Ltd: Scaling Newer Heights in Real Estate Entrepreneurship
- Snapchat’s Dilemma: Growth or Financial Sustainability
- Did I Just Cross the Line and Harass a Colleague?
- Predicting the Future Impacts of AI: McLuhan’s Tetrad Framework
- Porsche Drive (A) and (B): Student Spreadsheet
- Porsche Drive (B): Vehicle Subscription Strategy
- TNT Assignment: Financial Ratio Code Cracker
- Winsol: An Opportunity For Solar Expansion
Glitz Investments: Predicting a Blockbuster
內容大綱
An investment manager at Glitz Investments, a firm based in the United States with a focus on the entertainment industry, wanted to identify potential blockbuster movies in the Indian film industry for the firm’s potential investment purposes. The investment manager received a report compiled by analysts at the firm indicating that Bollywood would be an attractive industry for investment. The firm’s analysts had collected data but could the manager determine a quantitative relationship between box office performance and the factors the team had identified? Could Glitz Investments choose movies based on this analysis alone? The investment manager's boss was looking for more specific data on which to base the firm’s investment decisions.
學習目標
This case is suitable to illustrate the application of quantile regression in an advanced analytics course at the undergraduate or graduate level. The case can also be used as part of a core course in a master of science program in analytics. It illustrates the extreme uncertainty associated with revenue outcomes in the film industry—a factor that is common across various cultural industries, including theatre, music, and book publishing. The two analytical techniques explored in this case are log linear regression and quantile regression. Quantile regression is a particularly useful technique in scenarios where outcomes follow a power-law distribution, as is the case with Bollywood and other cultural industries. After completion of this case, students will be able to<ul><li>interpret the coefficients from log linear and quantile regression analyses; and</li><li>understand how these regression techniques can be useful in an environment with power-law distributed outcomes.</li></ul>