Knowledge that Transforms

We consider a supply chain where a contract manufacturer (CM) serves a number of original equipment manufacturers (OEMs). Investment into productive resources is made before demand realization, hence the supply chain faces the risk of under- or overinvestment. The CM and OEMs differ in their forecast accuracy and in their resource pooling capabilities, leading to a disparity in their ability to minimize costs due to demand uncertainty. We consider two scenarios in which this risk is borne by the OEM and CM, respectively. We determine which party should bear the risk so that maximum supply chain profits are achieved. We investigate the effectiveness of premium-based schemes in inducing the best party to bear the risk, and conclude that they function well despite information asymmetry when double marginalization is not very high.

This paper investigates the conditions under which frontline employees take initiative to improve their work systems to prevent operational failures. Drawing on the system improvement and team learning literatures, we develop a framework of frontline system improvement and test it using survey data from 37 workgroups. We find that psychological safety—the belief that one can talk about errors without risk of punishment—and problem-solving efficacy—the belief that the organization will support employees' system improvement efforts—were positively correlated with frontline system improvement (FLSI). Surprisingly, felt responsibility was negatively associated with FLSI. These findings suggest that rather than relying on hiring motivated individuals, managers need to support employees' efforts to improve their work systems by creating a work environment where it is safe to talk about operational failures and responding to employee communication about operational failures. Doing this may result in higher levels of FLSI efforts and ultimately improve work processes.

We consider the problem of a newsvendor that is served by multiple suppliers, where any given supplier is defined to be either perfectly reliable or unreliable. By perfectly reliable we mean a supplier that delivers an amount identically equal to the amount desired, as is the case in the most basic variant of the newsvendor problem. By unreliable, we mean a supplier that with some probability delivers an amount strictly less than the amount desired. Our results indicate the following effects of unreliability: From the perspective of the newsvendor, the aggregate quantity ordered is higher than otherwise would be ordered if the newsvendor’s suppliers were completely reliable. From the perspective of end customers, however, the service level provided is lower than otherwise would be provided if the newsvendor’s suppliers were completely reliable. From the perspective of the suppliers, although reliability affects how much is ordered from a selected supplier, cost generally takes precedence over reliability when it comes to selecting suppliers in the first place. Even perfect reliability is no guarantee for qualification since, in an optimal solution, a given supplier will be selected only if all less-expensive suppliers are selected, regardless of the given supplier’s reliability level. Nevertheless, the relative size of a selected supplier’s order depends on its reliability.