学术论文

Emergency department (ED) overcrowding and long patient wait times have become a worldwide problem. We propose a novel approach to assigning physicians to shifts such that ED wait times are reduced without adding new physicians. In particular, we extend the physician rostering problem by including heterogeneity among emergency physicians in terms of their productivity (measured by the number of new patients seen in 1 hour) and by considering the stochastic nature of patient arrivals and physician productivity. We formulate the physician rostering problem as a two-stage stochastic program and solve it with a sample average approximation and the L-shaped method. To formulate the problem, we investigate the major drivers of physician productivity using patient visit data from our partner ED, and find that the individual physician, shift hour, and shift type (e.g., day or night) are the determining factors of ED productivity. A simulation study calibrated using real data shows that the new scheduling method can reduce patient wait times by as much as 13% compared to the current scheduling system at our study ED. We also demonstrate how to incorporate physician preference in scheduling through physician clustering based on productivity. Our simulation results show that EDs can receive almost the full benefit of the new scheduling method even when the number of clusters is small.

For a queueing system with multiple customer types differing in service-time distributions and waiting costs, it is well known that the cµ-rule is optimal if costs for waiting are incurred linearly with time. In this paper, we seek to identify policies that minimize the long-run average cost under nonlinear waiting cost functions within the set of fixed priority policies that only use the type identities of customers independently of the system state. For a single-server queueing system with Poisson arrivals and two or more customer types, we first show that some form of the cµ-rule holds with the caveat that the indices are complex, depending on the arrival rate, higher moments of service time, and proportions of customer types. Under quadratic cost functions, we provide a set of conditions that determine whether to give priority to one type over the other or not to give priority but serve them according to first-come, first-served (FCFS). These conditions lead to useful insights into when strict (and fixed) priority policies should be preferred over FCFS and when they should be avoided. For example, we find that, when traffic is heavy, service times are highly variable, and the customer types are not heterogenous, so then prioritizing one type over the other (especially a proportionally dominant type) would be worse than not assigning any priority. By means of a numerical study, we generate further insights into more specific conditions under which fixed priority policies can be considered as an alternative to FCFS.

Using China's 2008 four-trillion-yuan economic stimulus as a setting and proprietary loan data, we study how a large publicly listed state-owned bank responds to the government's countercyclical financing initiative while trying to meet the expectations of bank regulators and public investors. We find that the bank exhibited little changes in the process of setting internal credit ratings of borrowers, and internal ratings remain a valid, albeit weaker, predictor of interest rates in the stimulus period. Interest rates also remain a valid predictor of loan delinquency in the stimulus period. Evidence from analyzing unlisted borrowers is broadly similar. Overall, there is no systematic evidence that loan decisions of the state-owned bank are severely compromised in the stimulus period. The study adds to the limited understanding of how partially privatized state-owned banks balance different objectives in managing credit risk and is relevant to the longstanding debate over the roles of state-owned banks.

社会信任能够减轻契约不完备性，因而会对委托投资组合管理的活跃度和成效有重要的影响。我们利用一个环球开放互惠基金的完整样本进行研究，发现社会信任度与基金的活跃度属正相关关系，而由此带来主动投资表现卓越（例如：每年产生约2%的收益）。此外，「信任市场」和「信任投资经理」两者在不同类型的跨境委托投资组合管理方面，发挥着重要但不同的作用。总体而言，该研究结果证明信任度是委托投资组合管理的重要基石。

研究利用中国引入高速铁路 (HSR) 的项目作为获取讯息成本的外来冲击因素，发现获取讯息成本降低可导致 (i) 讯息生产量显著增加 (从分析师更频密地到访投资组合公司足可证明)，以及 (ii) 生产质量有所提升 (从分析师能够提高预测准确度及提出更好的投资建议中展现)。对于难以生产讯息的公司，以上的影响尤其明显。重要的是，讯息生产量提升与改善价格效益有所关联。通过对财务分析师进行大规模统计调查，我们进一步证实了上述的发现。最后，实证和调查结果都指出软讯息对分析师建立独特讯息十分重要。

研究透过薪资保护计划向上市公司提供贷款的数据，区分银行和公司因人际关系而造成偏袒和信息优势这两个因素。由于薪资保护计划的贷款由政府作担保，因此银行毋需对贷款人进行严格的审查，这有效减少信息摩擦，并可量化偏袒行为的效应。研究发现与银行有私人联系的公司，较容易获取薪资保护计划的贷款。当公司的财务越透明，此等私人联系的作用会因而减弱，但并不会因银行的企业管治而产生变化。研究亦指出，为避免监管审查，关联公司还款机率较大。整体而言，我们就银行借贷的偏袒行为提出清晰的估算，并突显政府计划利用银行体系分配资本时，所带来意想不到的后果。

中国在不同县市实施的最低工资政策有所不同。此研究透过使用中国制造业企业的工业普查数据，探讨最低工资政策如何影响资本投资。利用最低工资政策在县市边界的不连续性，我们发现最低工资政策会增加资本投资。企业的劳动密集度越高，技术提升空间越大，以及企业无法将劳动成本转嫁予消费者时，其对于最低工资政策所作出的投资反应越大。研究中一项基于县市管辖权变化的自然实验进一步确定了最低工资与资本投资的因果关系。

通过分析中国各地监管政策力度的变化和中国企业的地理分布，我们研究了政府外部监管对国有企业绩效的影响。该研究利用结构化的分析方法，使用常用的企业级别生产数据，估算出企业的生产率和中间投入品价格。研究显示，加强外部监管是提高企业治理的关键，可大幅消减中间投入品的采购价格并大幅减少生产管理中的懈怠现象。结果表面，政府监管可以成为改善国有企业绩效的有效政策工具。

日常生活中很多专家的服务属于信任品。我们从多个角度研究专家如何在信任品市场建立起顾客的信任。当消费者预期自身有严重问题的机会不高，并且专家服务用于解决较严重问题才具经济效益的情况下，单次交易将不会成交。而在重覆交易的环境中，消费者会通过拒绝接受专家的建议来监察他的诚实程度。在专家追求利润最大化的情况下，虽然利润会随着专家注重信誉的程度而增加，但是达不到理论上的最高水准，这与体验品市场的情况形成鲜明对比。当专家非常在乎自己的信誉时，会出现顾客拒绝解决严重问题的情况。当专家不够重视自己的信誉时，他们会过度治疗顾客的问题。两种情况都不是最理想。