Batting Average: a Composite Measure of Risk for Assessing Product Differentiation in a Simulation Model

The paper simulates how market power affects electricity retailing to households. A pseudo-random number seeding algorithm creates representative product differentiation in repeated drawings, for an incumbent and seven challengers. A ninth player competitor decides how to distinguish her product. The simulation creates an efficient starting market, adjusted for competitor dominance; and, over a 12month horizon, uses topology to develop unexploited profit opportunities for all competitors. A best solution criterion punishes nonconformists. Results of repeated drawings varying opposition to the player’s constant product differentiation feed a batting average risk assessment. Decision rules reward hits based on profit and year’s end market share. The market simulation tool supports conjectural assessment of social policy – household direct access to wholesale power, incentive for product differentiation versus that for mergers and acquisitions, and allocation of deregulation benefits to shareholders versus ratepayers.