Competition and The Operational Performance of Hospitals: The Role of Hospital Objectives

We examine the effect of a hospital's objective (i.e., non‐profit vs. for‐profit) in hospital markets for elective care. Using game‐theoretic analysis and queueing models to capture the operational performance of hospitals, we compare the equilibrium behavior of three market settings in terms of such criteria as waiting times and patient costs from waiting and hospital payments. In the first setting, a monopoly, patients are served exclusively by a single non‐profit hospital; in the second, a homogeneous duopoly, patients are served by two competing non‐profit hospitals. In our third setting, a heterogeneous duopoly, the market is served by one non‐profit hospital and one for‐profit hospital. A non‐profit hospital provides free care to patients, although they may have to wait; for‐profit hospitals charge a fee to provide care with minimal waiting. A comparison between the monopolistic and each of the duopolistic settings reveals that the introduction of competition can hamper a hospital's ability to attain economies of scale and can also increase waiting times. Moreover, the presence of a for‐profit sector may be desirable only when the hospital market is sufficiently competitive. A comparison across the duopolistic settings indicates that the choice between homogeneous and heterogeneous competition depends on the patients' willingness to wait before receiving care and the reimbursement level of the non‐profit sector. When the public funder is not financially constrained, the presence of a for‐profit sector may allow the funder to lower both the financial costs of providing coverage and the total costs to patients. Finally, our analysis suggests that the public funder should exercise caution when using policy tools that support the for‐profit sector—for example, patient subsidies—because such tools may increase patient costs in the long run; it might be preferable to raise the non‐profit sector's level of reimbursement.     

How to Compete Against a Behavioral Newsvendor

We investigate newsvendor ordering behavior under competition. We present a laboratory experiment that documents the behavioral ordering regularities in competitive newsvendor environments, and an analytical model extending the standard theory of newsvendor competition by including an optimal best‐response policy for competing with a behaviorally biased newsvendor. We test the effectiveness of this policy using an out‐of‐sample experiment and find that it results in improved market share, service level and profitability.     

动态环境下联盟竞合、治理机制与创新绩效的关系研究

本文从竞合视角审视联盟组合,结合动态关系观探讨有效的联盟治理机制,揭示了联盟组合中竞合关系(横向竞合、纵向竞合)、治理机制(契约治理、关系治理)和创新绩效之间的关系,并考察了动态环境特征(技术波动、竞争强度)的二次调节作用。在不同的竞合关系中,由于合作和竞争的强度不同,契约治理与关系治理机制的作用也存在差异,同时,治理机制与创新绩效之间的关系也受到两种不同环境动态性特征的影响。研究结果显示,在纵向竞合中,运用关系治理比运用契约治理能更好地提升创新绩效,技术波动正向调节契约治理、关系治理与创新绩效间的关系。在横向竞合中,运用契约治理比运用关系治理有效,竞争强度加强了契约治理对创新绩效的影响,即关系治理在波动的环境中更有效,契约治理在竞争的环境中更有效。本文为企业开展研发联盟组合管理提供了新的视角和管理对策。     

中国人力资本积累与国际竞争力比较

从国际视角对全球129个国家的人力资本结构进行了比较分析。研究发现：中国人力资本存量国际综合排名第92位,位于第4梯队。人力资本存量(健康性人力资本、技能性人力资本)对经济增长有显著的正向影响机制。经济增长通过对教育性人力资本的再投入推动创新性人力资本的提升。比较中国和世界发达国家之间的人力资本结构差距,可以看到：未来15年中国人力资本将面临国际适应性和竞争性的重大挑战。应当通过提升职业与产业结构的匹配度,增强教育性人力资本与技能性人力资本的深化,从而为提升我国创新性人力资本做准备,增强我国国际竞争力。     

基于财政竞争力分析的福建省经济发展策略研究

财政对经济增长起着不可替代的促进作用,而财政竞争力也是经济综合竞争力的重要组成部分,分析福建省各地市的财政竞争力以寻找经济发展策略,对促进福建省经济有重大意义。本文对各地市财政收支现状进行初步比较,构建财政竞争力三级指标体系以分析财政竞争力水平,同时利用主成分因子得分分析财政竞争力与经济发展之间的关系。研究结果表明,厦门、福州及泉州财政竞争力较强,以这三个地市为例,从财政竞争实力和竞争潜力两个方面提出进一步提升财政竞争力的建议。     

电子商务市场产品多元化战略的销售绩效及驱动因素研究

结合电子商务市场特征,从理论方面分析电子商务市场产品多元化战略的驱动因素及其销售绩效,利用正则表达式等数据挖掘技术形成电子商务市场的面板数据库,并对相关研究假设进行实证检验。结果表明：在电子商务市场上,产品多元化战略与企业销售绩效正相关,而市场同质化竞争程度与产品多元化战略负相关,企业经营时间、顾客好评率抑制了企业对产品多元化战略的选择。研究结论对于电子商务市场的企业产品多元化战略选择具有重要参考意义。     

论公司理财权力竞争与运用

从公司理财权力概念、基本特征着手,分析了公司理财中客观上存在着的理财权力竞争。认为公司理财权力的价值、金字塔形的组织结构、资源的稀缺、绩效标准、环境的不确定性、权谋倾向,意见分歧是公司理财权力竞争的动因;公司及公司利益相关者可以通过法定程序、特殊才能和资源、特殊的行为等途径获得公司理财权力;公司理财人员要善于运用法定权力、奖酬权力、强制权力、专家权力和参照权力。     

中美铁路行业治理制度及其效率的比较分析

本文从铁路行业治理的视角,以铁路企业间的相互依赖性及其行业内协调制度为分析对象,分析中美铁路行业治理制度环境的相似性与差异性,探讨中美铁路行业内协调的制度安排的细节及其差异性,并运用比较制度分析的理论研究中美铁路行业内运营协调的信息体制及其效率差异,分析其清算制度的不同激励效果与适应性差异,阐述其对中国铁路重组的启示。     

The West,Russia, and China in Central Asia: What Kind of Game Is Being Played in the Region?

The article discusses the nature of the tangled interaction between the ex-Soviet Central Asian republics and the outside great powers – Russia, the United States and China. Although the so-called Great Game model is often used to explain the geopolitical rivalry in the region, the current pattern of relations between various international actors is much more complex than a traditional tug-of-war between the old colonial empires. While Russia's strategic role in Central Asia appears to be on the rise, the capacity of the West to influence political developments in the region has diminished. However, the overall situation in Central Asia remains volatile and its geopolitical landscape is far from being settled.     

State transition modeling of complex monitored health data

This article considers the analysis of complex monitored health data, where often one or several signals are reflecting the current health status that can be represented by a finite number of states, in addition to a set of covariates. In particular, we consider a novel application of a non-parametric state intensity regression method in order to study time-dependent effects of covariates on the state transition intensities. The method can handle baseline, time varying as well as dynamic covariates. Because of the non-parametric nature, the method can handle different data types and challenges under minimal assumptions. If the signal that is reflecting the current health status is of continuous nature, we propose the application of a weighted median and a hysteresis filter as data pre-processing steps in order to facilitate robust analysis. In intensity regression, covariates can be aggregated by a suitable functional form over a time history window. We propose to study the estimated cumulative regression parameters for different choices of the time history window in order to investigate short- and long-term effects of the given covariates. The proposed framework is discussed and applied to resuscitation data of newborns collected in Tanzania.