William Schmidt

Identifying Risks and Mitigating Disruptions in the Automotive Supply Chain

Firms are exposed to a variety of low-probability, high-impact risks that can disrupt their operations and supply chains. These risks are difficult to predict and quantify; therefore, they are difficult to manage. As a result, managers may suboptimally deploy countermeasures, leaving their firms exposed to some risks, while wasting resources to mitigate other risks that would not cause significant damage. In a three-year research engagement with Ford Motor Company, we addressed this practical need by developing a novel risk-exposure model that assesses the impact of a disruption originating anywhere in a firms supply chain. Our approach defers the need for a company to estimate the probability associated with any specific disruption risk until after it has learned the effect such a disruption will have on its operations. As a result, the company can make more informed decisions about where to focus its limited risk-management resources. We demonstrate how Ford applied this model to identify previously unrecognized risk exposures, evaluate predisruption risk-mitigation actions, and develop optimal postdisruption contingency plans, including circumstances in which the duration of the disruption is unknown.

Variations in prenatal care and well-child supervision in a New England city**

It was found that time of the initial visit for prenatal care, the frequency of visits for infant health supervision, and whether the child was cared for by a pediatrician or a general practitioner were associated with the extent of the mothers formal education, parity, and husbands social class. More visits to a physician because of illness were reported by mothers residing in less favorable areas of the city. A suggestion is made regarding case finding of pregnancies among those groups now receiving inadequate prenatal care and infant health supervision.

Supply Chain Disruptions and the Role of Information Asymmetry

This research investigates how information asymmetry between the firm and its investors can influence supply chain disruptions. In such settings, these actors may be induced to take steps which exacerbate rather than ameliorate both the likelihood and impact of disruptions. By better understanding these mechanisms, managers and investors alike are better armed to avoid the costly consequences.

Experimental Evidence of Pooling Outcomes Under Information Asymmetry

Operational decisions under information asymmetry can signal a firms prospects to less-informed parties, such as investors, customers, competitors, and regulators. Consequently, managers in these settings often face a tradeoff between making an optimal decision and sending a favorable signal. We provide experimental evidence on the choices made by decision makers in such settings. Equilibrium assumptions that are commonly applied to analyze these situations yield the least cost separating outcome as the unique equilibrium. In this equilibrium, the more informed party undertakes a costly signal to resolve the information asymmetry that exists. We provide evidence, however, that participants are much more likely to pursue a pooling outcome when such an outcome is available. This result is important for research and practice because pooling and separating outcomes can yield dramatically different results and have divergent implications. We find evidence that the choice to pool is influenced by changes in the underlying newsvendor model parameters in our setting. In robustness tests, we show that choosing a pooling outcome is especially pronounced among participants who report a high level of understanding of the setting and that participants who pool are rewarded by the less informed party with higher payoffs. Finally, we demonstrate through a reexamination of Lai et al. (2012) and Cachon and Lariviere (2001) how pooling outcomes can substantively extend the implications of other extant signaling game models in the operations management literature.