Abstract
The article describes the features of a system-dynamics-based game for new product growth. The problem situation is discussed in the framework of a system dynamics model. The model is converted into a game form by following certain generalized principles that help in identifying the decision variables for the players, redefining players' decisions to maintain dimensional consistency, storing these decisions in files, invoking game-related equations, selecting the length of the game-simulation run, storing the end-period values of stock variables, deciding on the report structure, and storing the output in the files. This computerized game can accommodate simultaneous play by a maximum of four teams. Each team makes annual decisions on eight variables representing capacity acquisition, production, workforce hiring, borrowing, and profit margin. This article describes in detail the performance and the learning behavior of three teams during a particular play. The ability of a team to estimate the end-period values of performance measures was used as a criterion of learning by the team. The team that achieved the best value of this criterion also achieved the best company performance, corroborating our hypothesis that learning and performance are positively correlated.