Problem definition: Excessive and highly variable waiting times for specialty services are a long-standing problem for public healthcare systems. Healthcare authorities in some jurisdictions have begun to experiment with schemes to improve system performance, including cross-cluster referrals which allow patients to switch from their home cluster to other clusters with shorter waiting times, and opt-out subsidies which help patients seeking services from private providers outside the public system. However, few studies in the literature have examined the structure of the problem or offered analytical insights to the design of such schemes. Methodology/results: We construct a multi-cluster service network model to study optimal routing policies under both individual and system optimization. We define externalities in a network setting and establish their properties, and further identify conditions under which referrals are effective or counterproductive in reducing system costs. We also show that lowering the switching cost could inadvertently degrade overall system performance. In contrast to the classic result for single-cluster systems (e.g. Naor 1969), our analysis of opt-out and switching incentives reveals that fixed subsidies generally cannot fully coordinate a multi-cluster system due to the cross-cluster effect of externalities. However, they can effectively reduce system costs in wide ranges of system parameter values. We further show that dynamic (state-dependent) subsidies can achieve perfect alignment between individual and system optimization. Managerial implications: Our study suggests that cross-cluster referrals are effective when there is a substantial workload imbalance but without excessive system congestion. They should be implemented with proper operational control: referrals should be promoted when the workload imbalance is high, but discouraged when the overall system workload is very high while the imbalance is insubstantial. Furthermore, fixed opt-out and switching subsidies can effectively improve system performance under different demand conditions and should be applied strategically: focusing on switching subsidies when the system workload is moderate and the imbalance is substantial, but shifting the focus to opt-out subsidies when the overall system workload is high.
Problem Definition: In many crisis contexts, such as armed conflicts, natural disasters, or refugee emergencies, one of the most pressing challenges is to regulate the delivery of humanitarian aid to the final beneficiaries in the presence of both corruptible agents (those responsible for delivering aid) and corruptible inspectors (who may be bribed not to report uncovered misappropriations). Strengthening anti-corruption efforts by hiring more inspectors and/or rewarding inspectors’ truthful reporting can reduce corruption but draws on the finite humanitarian aid financing, reducing the aid delivered to the beneficiaries. Methodology/Results: We develop a three-stage game-theoretic model in which a government agency chooses inspection intensity and the reward rate for inspectors’ truthful reporting, managers decide how much aid to misappropriate, and inspectors decide whether to report detected misconduct or accept a bribe to conceal misappropriation. The government agency aims to maximize the amount of humanitarian aid reaching the beneficiaries. We find that the role of inspectors depends on the financing available. When the financing is low, inspectors serve to detect misconduct; when the financing is sufficiently high, inspectors also affect managers' behavior and deter misappropriation. The reward can also serve two purposes. It can either induce truthful reporting and eliminate bribery, or increase the bribe that managers must pay, thereby reducing their incentive to misappropriate. We characterize the impact of key parameters on the optimal anti-corruption levers. Managerial Implications: Our results provide guidance for agencies and donors on how to balance aid provision with anti-corruption measures, and how to adjust inspection intensity and incentive for truthful reporting to maximize the amount of aid reaching its intended recipients. As financing changes, resources should be allocated toward adjusting inspection intensity. In contrast, the reward rate for truthful reporting should be calibrated to the enforcement environment, and not be mechanically increased with the amount of financing.
Problem definition: While organizations are adopting hybrid and even remote-first work schedules, the potentially gendered impact of work-from-home (WFH) on operational outcomes remains poorly understood. Methodology/results: To examine this question, we combine a crisis-induced shock (i.e., the Covid-19 lockdown) that forced a shift to WFH due to stay-at-home orders, with a novel methodology to gather contextualized digital trace data. We examine the online time allocation — akin to a time-motion study for white collars — of 1,094 individuals across various activities and industries, when in-person work related and leisure activities were abruptly curtailed by the pandemic, inducing a shift to home-based work and online activities. Analysis of over 30 million website visits reveals that overall, this crisis-induced WFH increased the time devoted to both work-related and leisure pursuits online. However, these gains are significantly larger for men, giving rise to new gender gaps. We observe notable disparities in online work and leisure activities, including on smartphones, suggesting that crisis-induced WFH reshapes workers’ daily activities differently across genders. These gender differences are amplified among parents — a pattern consistent with increased household obligations placing greater constraints on women’s ability to fully benefit from the flexibility offered by WFH. Furthermore, we observe a substantial relative decline in women’s job search activities after the WFH shock, also corroborated using a large, external dataset from a major online recruitment platform. Managerial implications: These results underscore how sudden WFH mandates as response to a major crisis can differentially affect women’s work, employment prospects and long-term career trajectories. Our findings call attention to the importance of factors outside of the office in determining the success of WFH arrangements. Even though WFH could lower facilities cost and carbon footprint and increase workers’ flexibility, gender-specific constraints — especially those related to household responsibilities — can produce uneven outcomes. These results highlight the need for organizations and policymakers to design WFH policies that effectively address gender disparities, particularly in environments where childcare and other domestic duties fall disproportionately on women.
Problem Definition: Diagnostic discrepancies, defined as mismatches between patients’ admitting and principal diagnoses, are common but heterogeneous claims-based markers. These discrepancies represent a misalignment in the diagnostic process, reflecting diagnostic updating, reprioritization, residual clinical complexity, documentation practices, or error, without establishing clinical preventability, and may signal latent operational burden in subsequent physician decision-making. We examine whether this retrospective operational flag identifies inpatient stays with larger adjusted resource-use differentials and whether those differentials vary with physician experience. Methodology/Results: Leveraging a patient-level dataset of 5.7 million emergency-department-origin inpatient stays from Florida hospitals, we examine the operational burden associated with diagnostic discrepancies, measured by total costs per hospitalization. Our results show that discrepancy-flagged inpatient stays have a 6.62% higher adjusted total cost after rich patient risk adjustment and high-dimensional fixed effects. The adjusted differential is smaller at higher focal experience (treating similar diagnoses) and larger at higher related experience (treating diverse diagnoses). The pattern remains qualitatively similar across alternative discrepancy definitions, richer diagnosis and service-line controls, risk-adjusted benchmarking, physician matching, alternative experience measures, and alternative samples. Exploratory analyses further show that flagged inpatient stays exhibit higher costs across multiple resource-use domains with varying intensity, higher diagnostic and procedural intensity, and longer adjusted time to first procedure. Managerial Implications: The discrepancy flag is most appropriately used for retrospective monitoring, benchmarking, and case-review triage, not as a direct measure of preventable error or as an automatic performance score. The physician experience patterns motivate prospective evaluation of assignment, consultation, training, and decision-support practices.
The rapid growth of the sharing economy over the past decade has changed many industries in profound ways. The innovative business models that have emerged in the sharing economy present unique opportunities as well as challenges, which have attracted a significant amount of attention from researchers in the operations management field. In this paper, we discuss the advances, challenges, and opportunities for research on operations management in the sharing economy. We divide sharing economy into eight categories: Ride Sharing, Space Sharing, Bike Sharing, Vehicle Sharing, Group Buying, Crowdfunding, Freelancing, and Last-Mile Delivery. For each business category, we identify the gaps and current challenges in the existing literature, discuss emerging industry trends and research topics, and suggest several future research directions. Our goal is to stimulate discussion and ideas about future studies in this area.
