An action associated with a small cost is commonly taken by humans for preventing a potential big loss in a wide range of domains. For example, technicians decide whether to do preventive maintenance now or to wait for the next updated machine status information. We model such decisions as a dynamic cost-loss game. We analytically show that using a probability threshold is an optimal policy. We next conduct a controlled laboratory observing how human decision makers behave in this environment.

Resource-based contracts fail to motivate suppliers to provide reliable services as they are paid for after-sales services. Performance-based contracts shifts much of the downtime risk to the supplier by making him responsible for machine uptime, but then customers might reduce care efforts. We propose the full-care contract to achieve both high reliability and care, and show that the FCC not only the best contract analytically but also can motivate risk averse suppliers to bear the chain risk.

Using a behavioral game of supply rationing, we investigate the consequences of sharing information about competing retailers’ historical orders on the Bullwhip Effect. We find that decision makers act more strategically and closer to Nash equilibrium predictions if information about competitors’ historical orders is shared; however, sharing the entire order history does not accelerate the convergence to theoretical Nash equilibrium as much as sharing orders from the last period only.