學門類別
政大
哈佛
- General Management
- Marketing
- Entrepreneurship
- International Business
- Accounting
- Finance
- Operations Management
- Strategy
- Human Resource Management
- Social Enterprise
- Business Ethics
- Organizational Behavior
- Information Technology
- Negotiation
- Business & Government Relations
- Service Management
- Sales
- Economics
- Teaching & the Case Method
最新個案
- Leadership Imperatives in an AI World
- Vodafone Idea Merger - Unpacking IS Integration Strategies
- Predicting the Future Impacts of AI: McLuhan’s Tetrad Framework
- Snapchat’s Dilemma: Growth or Financial Sustainability
- V21 Landmarks Pvt. Ltd: Scaling Newer Heights in Real Estate Entrepreneurship
- Did I Just Cross the Line and Harass a Colleague?
- Winsol: An Opportunity For Solar Expansion
- Porsche Drive (B): Vehicle Subscription Strategy
- Porsche Drive (A) and (B): Student Spreadsheet
- TNT Assignment: Financial Ratio Code Cracker
-
Predicting Automobile Prices Using Neural Networks
The chief marketing officer (CMO) at an automobile agency was looking at a list of car model features, which he had received from the manufacturing plant. He was expected to provide the manufacturer's suggested retail prices of the cars to dealers the following week and had to decide on the base prices. The CMO asked a data scientist at the research lab to predict prices using the data of past car models. Each car model had different features that could affect the price. The data scientist decided to use feed-forward neural networks as a tool for predicting the prices of new models. After comparing different prediction models, he also wanted to determine which prediction model was suitable for car manufacturing plants.