| Internet-based electronic commerce is now the fastest growing segment of the US economy. The instant nature of online transaction leads to more fluctuations in demand, while being digital facilitates more frequent monitoring of demand change. This study develops a demand-monitoring-pricing mechanism to show how to design an online monitoring system that helps the vendor improve profit. By formulating and solving a joint monitoring and pricing optimization model, we determine the best frequency to monitor demand change, the results of which are used as feedback for setting profit-maximizing prices. The optimization is obtained by balancing the losses caused by inaccurate demand parameter estimates and the costs of updating those parameters more frequently. The monitoring cost is explained from the perspectives of the automated demand data capturing process, the data digesting and understanding process, and the decision making process. We emphasize the human involvement as the major factor that invites cost. We also introduced application service providers (ASPs) to the study to help illustrate the monitoring cost. Analytical solution is provided for a simplified model. We discuss the application of our model to different cases through numerical analyses and simulations. This study has important implications for many e-commerce applications where information goods or services, such as financial information services and online entertainment, can be produced at negligible marginal cost. |
