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
Hind Oil Industries: Demand Analysis
內容大綱
In September 2015, the manager of Hind Oil Industries (HOI), a small edible oil manufacturer in Asansol, West Bengal, was challenged by a dilemma in pricing strategy. HOI had seen the price of mustard seeds, its primary raw ingredient, rise steeply because of harsh weather conditions in the previous harvesting season. HOI would need to raise the price of its product significantly in a price-competitive market dominated by larger companies. The manager wondered if he could increase the price of his only product, Maa mustard oil, to cover the substantial increase in production costs without suffering a loss in total revenue earned. If so, what would be the optimum price under various scenarios related to his competitors’ expected price hikes? Could HOI’s price be raised even if the competitors decided against raising their prices?
學習目標
This case has been designed for senior undergraduate and graduate students in managerial economics and microeconomics courses dealing with quantitative demand analysis, demand estimation and forecasting, demand modelling, pricing decisions, and entrepreneurial decision-making for small organizations. After completion of this case, students will be able to<br><ul><li>apply quantitative demand analysis to a real business problem using a multiple regression technique;</li><li>understand the various elasticities of demand and their implications;</li><li>describe the concept of the total revenue test;</li><li>apply the concepts of elasticities of demand and the total revenue test to a real business situation;</li><li>calculate the optimum price for maximizing total revenue using the demand function;</li><li>use a regression technique for forecasting demand; and</li><li>analyze a scenario in order to make business decisions.