The standard method for establishing the comparative statics of risk changes in optimization problems has been confined to comparing unique interior solutions, relying on strong assumptions about payoff functions and decision variables. We propose a simple and intuitive approach that hinges on considerably weaker assumptions. Merging insights from the monotone comparative statics literature with insights from the risk apportionment literature, we show that the ranking of simple lottery pairs is all that is needed for establishing the comparative statics of risk changes. We use this approach to analyze the comparative statics of Nth-degree stochastic dominance shifts in a general setting with one and with multiple decision variables, and we show how these results can be applied to generalize the classical theories of precautionary saving, self-protection, and others. This paper was accepted by James Smith, decision analysis.

This study finds that large marketwide declines in stock prices are associated with higher litigation incidence and settlements even though marketwide events are legally irrelevant. The probability of litigation nearly doubles (from 0.29% to 0.55%) and the amount of settlements also doubles (from $5.0 million to $10.1 million) when earnings disclosures occur during a large market decline, even after controlling for the firm’s market-adjusted return. Furthermore, judges with (without) specialized experience in securities litigation are more (less) likely to dismiss cases triggered by disclosures during large market declines. This pattern is consistent with experienced judges recognizing and dismissing weaker cases. Finally, managers are less likely to disclose adverse news at the end of trading days with large market declines. Although we cannot definitively identify the motive behind this pattern, it is consistent with managers recognizing increased litigation risk during large market declines. This paper was accepted by Mary Barth, accounting.

Daily deal websites help small local merchants to attract new consumers. A strategy adopted by some websites is to continually track and display the number of deals sold by a merchant. We investigate the strategic implications of displaying deal sales and the website’s incentive to implement this feature. We analyze a market in which a merchant offering an experience good is privately informed of its type. Whereas daily deals cannibalize a merchant’s revenue from experienced consumers, we show that, by displaying deal sales, the website can transform this cannibalization into an advantage. Displaying deal sales can leverage discounted sales to experienced consumers to help a high-quality merchant signal its type and acquire new consumers at a higher margin. Signaling is supported through observational learning from displayed deal sales since it reveals how experienced consumers respond to the deal. Nevertheless, the website may not implement this feature if signaling entails too much distortion in the merchant’s deal price. We also find that it can be optimal for the website to offer the merchant an up-front subsidy, but only if the website displays deal sales. Our analysis leads to managerial insights for daily deal websites. This paper was accepted by J. Miguel Villas-Boas, marketing.

This study provides novel evidence that cash-flow news quantitatively explains the investment effect in the cross section of stock returns. The negative return predictability of asset growth, investment growth, and accruals is evident only through the cash-flow news component of returns. The cash-flow news returns associated with investment-sorted portfolios exhibit a reversal from the preformation period to the postformation period. Such a return reversal is in line with reversals in firm fundamentals and becomes stronger for stocks with higher information uncertainty. Our findings are consistent with the expectational errors hypothesis and fail to support the risk-based explanation for the investment effect. This paper was accepted by Neng Wang, finance.

This paper studies government subsidies for green technology adoption while considering the manufacturing industry’s response. Government subsidies offered directly to consumers impact the supplier’s production and pricing decisions. Our analysis expands the current understanding of the price-setting newsvendor model, incorporating the external influence from the government, who is now an additional player in the system. We quantify how demand uncertainty impacts the various players (government, industry, and consumers) when designing policies. We further show that, for convex demand functions, an increase in demand uncertainty leads to higher production quantities and lower prices, resulting in lower profits for the supplier. With this in mind, one could expect consumer surplus to increase with uncertainty. In fact, we show that this is not always the case and that the uncertainty impact on consumer surplus depends on the trade-off between lower prices and the possibility of underserving customers with high valuations. We also show that when policy makers such as governments ignore demand uncertainty when designing consumer subsidies, they can significantly miss the desired adoption target level. From a coordination perspective, we demonstrate that the decentralized decisions are also optimal for a central planner managing jointly the supplier and the government. As a result, subsidies provide a coordination mechanism. This paper was accepted by Yossi Aviv, operations management.

Research in industrial organization and strategic management has shown that rivals competing with each other in multiple markets are more willing to show each other mutual forbearance, i.e., compete less aggressively, within their spheres of influence, i.e., the markets in which each firm dominates. Sell-side equity analysts typically cover multiple stocks in common with their rivals. We examine the impact of this “multipoint contact” for mutual forbearance on two key dimensions of competition among security analysts: forecast accuracy and information leadership (issuing earnings forecasts or stock recommendations that influence rival analysts). We find that multipoint contact is associated with analysts exerting greater information leadership on stocks within their own spheres of influence. We also find greater forbearance related to information leadership under Regulation Fair Disclosure (Reg FD). In contrast, multipoint contact was not associated with greater forecast accuracy on stocks within analysts’ spheres of influence, either before or under Reg FD. Our analysis is among the first to consider mechanisms of competition among securities analysts and also adds to the literature on Reg FD by demonstrating that the increased workload imposed on analysts after Reg FD fostered mutual forbearance as a response. This paper was accepted by Mary Barth, accounting.

Out-of-hospital cardiac arrest is a significant public health issue, and treatment, namely, cardiopulmonary resuscitation and defibrillation, is very time sensitive. Public access defibrillation programs, which deploy automated external defibrillators (AEDs) for bystander use in an emergency, reduce the time to defibrillation and improve survival rates. In this paper, we develop models to guide the deployment of public AEDs. Our models generalize existing location models and incorporate differences in bystander behavior. We formulate three mixed integer nonlinear models and derive equivalent integer linear reformulations or easily computable bounds. We use kernel density estimation to derive a spatial probability distribution of cardiac arrests that is used for optimization and model evaluation. Using data from Toronto, Canada, we show that optimizing AED deployment outperforms the existing approach by 40% in coverage, and substantial gains can be achieved through relocating existing AEDs. Our results suggest that improvements in survival and cost-effectiveness are possible with optimization. This paper was accepted by Dimitris Bertsimas, optimization.

Selecting among alternative projects is a core management task in all innovating organizations. In this paper, we focus on the evaluation of frontier scientific research projects. We argue that the "intellectual distance" between the knowledge embodied in research proposals and an evaluator's own expertise systematically relates to the evaluations given. To estimate relationships, we designed and executed a grant proposal process at a leading research university in which we randomized the assignment of evaluators and proposals to generate 2,130 evaluator-proposal pairs. We find that evaluators systematically give lower scores to research proposals that are closer to their own areas of expertise and to those that are highly novel. The patterns are consistent with biases associated with boundedly rational evaluation of new ideas. The patterns are inconsistent with intellectual distance simply contributing "noise" or being associated with private interests of evaluators. We discuss implications for policy, managerial intervention, and allocation of resources in the ongoing accumulation of scientific knowledge.

One key factor contributing to emergency department (ED) overcrowding is prolonged waiting time for admission to inpatient wards, also known as ED boarding time. To gain insights into reducing this waiting time, we study operations in the inpatient wards and their interface with the ED. We focus on understanding the effect of inpatient discharge policies and other operational policies on the time-of-day waiting time performance, such as the fraction of patients waiting longer than six hours in the ED before being admitted. Based on an empirical study at a Singaporean hospital, we propose a novel stochastic processing network with the following characteristics to model inpatient operations: (1) A patient’s service time in the inpatient wards depends on that patient’s admission and discharge times and length of stay. The service times capture a two-time-scale phenomenon and are not independent and identically distributed. (2) Pre- and post-allocation delays model the extra amount of waiting caused by secondary bottlenecks other than bed unavailability, such as nurse shortage. (3) Patients waiting for a bed can overflow to a nonprimary ward when the waiting time reaches a threshold, where the threshold is time dependent. We show, via simulation studies, that our model is able to capture the inpatient flow dynamics at hourly resolution and can evaluate the impact of operational policies on both the daily and time-of-day waiting time performance. In particular, our model predicts that implementing a hypothetical policy can eliminate excessive waiting for those patients who request beds in mornings. This policy incorporates the following components: a discharge distribution with the first discharge peak between 8 a.m. and 9 a.m. and 26% of patients discharging before noon, and constant-mean allocation delays throughout the day. The insights gained from our model can help hospital managers to choose among different policies to implement depending on the choice of objective, such as to reduce the peak waiting in the morning or to reduce daily waiting time statistics. This paper was accepted by Assaf Zeevi, stochastic models and simulation.