Dynamic pricing of network goods with boundedly rational consumers.

Area of Science:

• Behavioral Economics
• Industrial Organization
• Marketing Strategy

Background:

• Traditional economic models assume rational consumers, which may not reflect real-world behavior for network goods.
• Network effects, where a product's value increases with its user base, complicate standard pricing strategies.
• Existing models often overlook consumer bounded rationality in price perception and adoption forecasting.

Purpose of the Study:

• To develop a dynamic monopoly pricing model for goods with network effects, incorporating boundedly rational consumers.
• To analyze how consumer limitations in attention and forecasting influence optimal pricing strategies.
• To compare model predictions with observed pricing of network goods in practice.

Main Methods:

• Developed a dynamic monopoly pricing model with boundedly rational consumers.
• Incorporated consumer limitations in processing price changes and forecasting adoption.
• Analyzed optimal price trajectories under various consumer expectation scenarios (myopic, stubborn).

Main Results:

• Optimal pricing involves an initial low price to build the user base, followed by a high price.
• The strategy aims to stabilize the user base at a target level once achieved.
• This dynamic pricing policy differs significantly from rational-expectations equilibrium predictions.

Conclusions:

• Bounded rationality in consumers necessitates dynamic pricing strategies for network goods.
• The proposed pricing model aligns better with practical observations of network good pricing.
• Monopoly pricing for network goods should adapt to user base growth and consumer behavior.