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Do gender diversity quotas enhance firm value? This broad question has sparked significant debate because, whereas diversity is generally thought to improve board functioning, prior research in international settings suggests mandating diversity may have adverse consequences if it moves firms away from market equilibrium. Exploiting the political events leading up to the passage of California Senate Bill (SB) 826 as an exogenous shock to assess the market implications of board gender composition, we document either significantly positive or insignificant two-day abnormal returns for California firms across a variety of model specifications. Importantly, this finding contradicts the strong claims of contemporary studies of SB 826 that the California mandate was value-destructive. We reconcile these findings by providing critical evidence that contemporaneous results lack robustness to alternative model specifications and provide an incomplete picture by failing to comprehensively examine a broader set of event dates or account for mixed messaging on the final event date. We also provide some evidence of significant negative abnormal returns to litigation milestones that threaten to overturn SB 826 with the magnitude increasing in the size of board gender deficits. Finally, we provide evidence that there is no observable decline in newly appointed female director quality following the implementation of SB 826 relative to either preregulation or male director appointments. Collectively, our results suggest nonnegative (if not positive) consequences to California firms arising from SB 826 and directly counter assertions that mandated gender diversity is detrimental to firm value. This paper was accepted by Brian Bushee, accounting. Funding: The authors gratefully acknowledge research funding from Brigham Young University and the University of Toronto. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4825. [ABSTRACT FROM AUTHOR]

Quality disclosures regarding medical outcomes such as patient mortality are common healthcare policy instruments. Mixed evidence exists on whether quality disclosures improve outcomes for disclosed ailments. Moreover, disclosure policies can generate spillovers and impact ailments not targeted by the policy. We examine the effects of quality disclosure regulation on mortality improvements in disclosed and nondisclosed ailments. We use patient records for California hospitals for 1995–2014 and construct three groups of ailments: those that were the target of disclosure regulation, complementary ailments that were not the target of disclosure regulation but are medically related to the disclosed ailments, and medically unrelated ailments. Using a difference-in-differences design, we find that quality disclosure regulation is associated with declines in mortality risk of disclosed ailments ranging from 11.5% to 23%. Quality disclosure regulation is also associated with improvements for complementary ailments that are not the target of the disclosure policy. Such positive spillover effects yield an estimated 15.2% decline in mortality risk. Consistent with demand-side pressures driving improvements, market shares become sensitive to disclosed quality measures after disclosure regulation. Our findings of direct and spillover effects have implications for disclosure regulation. This paper was accepted by David Simchi-Levi, accounting. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4817. [ABSTRACT FROM AUTHOR]

Electricity end-users have been increasingly generating their own electricity via rooftop solar panels. We study the impact of such distributed renewable energy (DRE) on utility profits and social welfare under net metering, which is a widespread policy in the United States. Utilities have been lobbying against net-metered distributed solar based on the common belief that it harms utility profits. We find that when wholesale market dynamics are considered, net-metered DRE may be a positive for utilities. That is, net-metered DRE strictly improves the expected utility profit when the utility's self-supply is below a threshold and the wholesale electricity price is sufficiently responsive to wholesale demand fluctuations. Our paper distinctively considers both downstream and upstream impacts of net-metered DRE on utilities and analyzes the tradeoff between these impacts. Net-metered DRE can increase utilities' expenses because of their required buyback from generating customers, and reduces their retail sales revenues. In addition, it can either reduce utilities' wholesale procurement costs or affect their wholesale market revenues. Our results suggest that utilities might benefit from emerging business strategies that motivate their customers to install solar panels. Our numerical study uses data on the distributed solar in California and the wholesale electricity market operated by the California Independent System Operator, and demonstrates that our findings hold under realistic parameters. This paper was accepted by David Simchi-Levi, operations management. [ABSTRACT FROM AUTHOR]

We study direct load control contracts that utilities use to curtail customers' electricity consumption during peak-load periods. These contracts place limits on the number of calls and total number of hours of power reduction per customer per year as well as the duration of each call. The stochastic dynamic program that determines how many customers to call and the timing and duration of each call for each day is an extremely difficult (NP-hard) optimization problem. We design a scenario-based approximation method to generate probabilistic allocation polices in a reasonable amount of time. Our approach consists of three approximations: deterministic approximation of demand, discretization of the expected demand, and aggregation/disaggregation of the resources. We show the relative information error resulting from the deterministic approximation is O (1 / n) , the discretization error is O (1 / n) , and the aggregation/disaggregation error is O (1 / n) , where n represents the length of the horizon. Finally, we show the total relative error is O (1 / n). Our error analysis establishes that our approximation method is near optimal. In addition, our extensive numerical experiments verify the high quality of our approximation approach. The error, conservatively measured, is quite small and has an average and standard deviation of 8.6% and 1.4%, respectively. We apply our solution approach to the data provided by three major utility companies in California. Overall, our study shows our procedure improves the savings in energy-generation cost by 37.7% relative to current practices. This paper was accepted by Chung Piaw Teo, optimization. Funding: The authors thank the UCLA Ziman Center's Howard and Irene Levine Program in Housing and Social Responsibility and the Morrison Family Center for Marketing Studies and Data Analytics for generous funding. Supplemental Material: The online appendices are available at https://doi.org/10.1287/mnsc.2022.4493. [ABSTRACT FROM AUTHOR]

We use a unique feature of California's property tax system to empirically identify the causal effect of selling homeowners' past property tax payments on their choice of listing price. Although past property taxes are sunk costs, we find that they have a significant positive effect on the sellers' choice of listing price, which is inconsistent with rational models of decision making. This effect is stronger when sellers expect to sell at a loss relative to their purchase price and for properties whose value is harder to assess. The effect of property taxes on listing price is mostly transmitted to the selling price, which is consistent with the idea that buyers use listing prices as anchors to assess property values. Overall, our results suggest that sunk costs affect prices in the housing market. This paper was accepted by Tomasz Piskorski, finance. Supplemental Material: Data files are available at https://doi.org/10.1287/mnsc.2021.4285. [ABSTRACT FROM AUTHOR]

The author presents commentary on his earlier article, "Jobshop-Like Queueing Systems," published in the November 1963 issue of the periodical "Management Science." He notes that his interest in jobshop manufacturing provided the subject matter of the article, which stemmed from his work with the Management Science Research Project at the University of Los Angeles in Los Angeles, California. The author discusses his position on doctorial committees headed by Professor Leonard Kleinrock, whose work was instrumental in the development of the Internet.

This paper develops models for water planning that simultaneously consider investment and allocation decisions. The framework is demonstrated for a region which includes the counties of San Luis Obispo and Santa Barbara in California. The quadratic discontinuous mathematical programming problems resulting from such models are solved optimally by using generalized Benders decomposition. Benders decomposition is a method for breaking a larger problem into a series of manageable subproblems which yield feasible solutions to the overall system. In this case the decomposition is used to incorporate a quadratic programming allocation subproblem with an integer programming investment sequencing problem. [ABSTRACT FROM AUTHOR]

We use hospital-level discharge data from cardiac patients in California to estimate the effects of focus on operational performance. We examine focus at three distinct levels of the organization-at the firm level,at the operating unit level, and at the process flow level. We find that focus at each of these levels is associated with improved outcomes, namely, faster services at higher levels of quality, as indicated by lower lengths of stay(LOS) and reduced mortality rates. We then analyze the extent to which the superior operational outcome is driven by focused hospitals truly excelling in their operations or by focused hospitals simply "cherry-picking"easy-to-treat patients. To do this, we use an instrumental variables estimation strategy that effectively randomizes the assignment of patients to hospitals. After controlling for selective patient admissions, the previously observed benefits of firm level focus disappear; focused hospitals no longer demonstrate a statistically significant reduction in LOS or mortality rate. However, at more granular measures of focus within the hospital (e.g., operating unit level), we find that more focus leads to a shorter LOS, even after controlling for selective admission effects. [ABSTRACT FROM AUTHOR]

In a recent article in Management Science. W. F. Massy [2] outlines an interesting difference equation model of the Stanford University budget system. He proceeds then to solve for first and second order (i.e., short-term) balanced budget conditions. However. Massy's assertion that the balanced budget requirement cannot be modeled "effectively" for an extended time horizon is inaccurate. This note shows that such long-range solutions are readily available from the eigenstructure of his model. We derive simple sufficient conditions for maintaining balanced university budgets. Related issues of balanced budget attainability, empirical correspondence, and policy feasibility are also discussed. [ABSTRACT FROM AUTHOR]