Pricing decisions in competitive gasoline market

Abstract

In the dynamic gasoline market oil prices are changing on daily basis and the locations have different effect on demand and customer price. The thesis explores about the interesting price-setting behavior for the gasoline market In a local market, the behavior depends upon their desire and interest that is affected by price changes and brands. Decision support systems and quantitative data analysis can measure and predict this market behavior. In addition scenario analysis was adopted to find possible outcome of price decisions. The best scenario can be chosen considering inventory, production and distribution costs, production and distribution capacity, demand and margins. Price and demand elasticity, demand curves, data collection and pattern analysis are factors to figure out the way to get maximum profit. Price and demand elasticity relates demand changes with price changes and is a measure of demand variations. An inverse relationship holds between price and demand. Price and demand elasticity is a key factor to measure future variations in the demand. Demand curves are used to show the general trend in the market. This analysis can help to change prices in different locations and also makes us updated with competitors pricing behavior. A system can be developed for forecasting future gasoline prices using important factors which cause major variations.