Pricing with efficient frontiers

Pricing is the culmination of all marketing and operational efforts. The optimal pricing and positioning of a product line while balancing company and consumer welfare is an acute problem. This research determines an optimal product line pricing strategy that optimizes both customer utility and firm profits simultaneously. A dual objective mixed integer programming model is developed in order to consider supply chain costs and customer preferences simultaneously while estimating strategic price points. The model also positions the products across multiple customer segments. Efficient frontiers are generated in order to manage the mix of company profit and consumer welfare and determine performance levels. The advantages of this methodology are discussed in detail along with a comparison of the results from the model to the actual prices charged at an IT firm.; The concept of dual optimization and efficient frontiers is employed for establishing strategic price points for multiple product lines and bundles. Mathematical models compare the various bundling strategies and suggest optimal pricing and positioning options for the offerings, both bundles and individual products. The efficient frontiers generated by the integer programming models are also used as tools to measure the variance reduction effects and profit potential of bundling.; The final contribution of this research involves the estimation of strategic price points for products in a product line in a dynamic supply chain environment. Two interconnected mathematical models are developed to factor in both customer related parameters and supply chain parameters. The model studies the influence of multiple demand distributions and efficient frontier points on profit and other supply chain variables. The long term and short term ramifications of pricing are studied in the single and multi-period models where the decisions made in the previous periods influence the factors in the subsequent period. A sensitivity analysis on the optimal capacity levels under various demand distributions and pricing points is also performed in this research.