和谐医患关系模型设计与分析

医患关系和谐有赖于医学伦理道德体系的重建,只有从医学伦理道德体系上创设一个互助友爱的氛围,才可能从根本上改善医患关系。本文在医学伦理道德的基础上,分析了当前医患关系建设与医学伦理道德认知存在的问题,并构建了使双方获益的模型设计与分析。     

人力资本投资的资产专用性问题及其防范机制研究

专用性人力资本投资所具有的不完全契约性及资产专用性等特征必然导致了投资双方的激励缺乏问题。文章通过构建专用性人力资本投资的“囚徒困境”模型说明了该现状，并在此模型基础上从不完全信息下的静态博弈到动态博弈再到无限次合作博弈构建了专用性人力资本投资的决策模型。通过对决策模型的分析，文章找出了防范机制的三个关键点，即：稳定的雇佣关系、充分的授权激励以及充分的流动机制。     

Shadow costs of incomplete information and short sales in the valuation of the firm and its assets

This paper presents a simple framework for the valuation of compound options within shadow costs of incomplete information and short sales. The shadow cost includes two components. The first component is the product of pure information cost due to imperfect knowledge and heterogeneous expectations. The second component represents the additional cost caused by the short-selling constraint. Information costs are linked to Merton's (1987. Journal of Finance 42, 510) model of capital market equilibrium with incomplete information, CAPMI. This model is extended by Wu et al. (1996. Review of Quantitative Finance and Accounting, 7, 136) who propose an incomplete-information capital market equilibrium with heterogeneous expectations and short sale restrictions, GCAPM. This model is used in our paper to provide for the first time in the literature analytic solutions for derivatives in the presence of both shadow costs of incomplete information and short sales.When deriving the compound call option formula, we consider a call option on a stock, which is itself an option on the assets of the firm. Our methodology incorporates shadow costs of incomplete information and short sales on the firm's assets as well as the effects of leverage in the capital structure. The formula can be useful in the valuation of several corporate liabilities in the presence of information uncertainty and short sales constraints about the firm and its cash flows. Our analysis can be used for the valuation of several real options.     

Online social network fundraising: Threats and potentialities

There has been a growth in online fundraising from crowdfunding apps, like GoFundMe, that propagate fundraising appeals on social networking sites. In the online space, these crowdfunding apps pose a potential threat to the traditional intermediation role of charities. The disintermediation threat is that donors choose crowdfunding intermediaries instead of charities to channel their giving. In this article, we discuss what makes crowdsourced fundraising effective and how charities can adapt to this new dynamic for more effective online fundraising emphasizing two key success factors: brand strength/reputation and managing the donor experience. In addition, we explain the advantages and disadvantages of social media fundraising and giving and propose ways charities can leverage their good reputations and public trust to stimulate reintermediation. Finally, we propose a landscape for future research based on model that emphases the fundraising campaign's ability to stimulate viral sharing within and between online social networks.     

注重人文关怀,构建和谐医患关系

医务人员在和谐医患关系的构建中,发挥着不可替代的主导作用,医院需要帮助医务人员调节自身,掌握与患者心理沟通的必要技巧和自我心理舒解的方法。对患者实行有效的人性化关怀服务和心理疏导,坚持以人为本,注重医患沟通,提高医疗执业素质,从而营造和谐的医患关系。     

铁路军事运输保障作战模拟不完全信息动态博弈模型研究

通过分析战时铁路军事运输过程中的博弈问题,提出了基于红蓝对抗的不完全信息动态博弈,并构建了相应的博弈模型,通过模拟实验分析单列车梯队的不完全信息动态博弈过程。     

浅谈如何构建和谐医患关系

近年来,医疗卫生管理部门和医疗机构为构建和谐医患关系进行了积极的探索。许多医院实行开放式管理,建立医患沟通监督机制,保证医疗信息畅通,在这方面取得一定成效。但是,医患关系紧张,彼此缺乏信任,医疗纠纷增加,是当前一个十分突出的问题。本文主要对如何构建和谐医患关系进行了探讨。     

A bargaining set for roommate problems

Since stable matchings may not exist, we propose a weaker notion of stability based on the credibility of blocking pairs. We adopt the weak stability notion of Klijn and Massó (2003) for the marriage problem and we extend it to the roommate problem. We first show that although stable matchings may not exist, a weakly stable matching always exists in a roommate problem. Then, we adopt a solution concept based on the credibility of the deviations for the roommate problem: the bargaining set. We show that weak stability is not sufficient for a matching to be in the bargaining set. We generalize the coincidence result for marriage problems of Klijn and Massó (2003) between the bargaining set and the set of weakly stable and weakly efficient matchings to roommate problems. Finally, we prove that the bargaining set for roommate problems is always non-empty by making use of the coincidence result.     

Wikipedia matters

We document a causal impact of online user-generated information on real-world economic outcomes. In particular, we conduct a randomized field experiment to test whether additional content on Wikipedia pages about cities affects tourists' choices of overnight visits. Our treatment of adding information to Wikipedia increases overnight stays in treated cities compared to nontreated cities. The impact is largely driven by improvements to shorter and relatively incomplete pages on Wikipedia. Our findings highlight the value of digital public goods for informing individual choices.     

Effect of Online Dating on Assortative Mating: Evidence from South Korea

Online dating services have increased in popularity around the world, but a lack of quality data hinders our understanding of their role in family formation. This paper studies the effect of online dating services on marital sorting, using a novel dataset with verified information on people and their spouses. Estimates based on matching techniques suggest that, relative to other spouse search methods, online dating promotes marriages that exhibit weaker sorting along occupation and geographical proximity but stronger sorting along education and other demographic traits. Sensitivity analysis, including the Rosenbaum Bounds approach, suggests that online dating's impact on marital sorting is robust to potential selection bias. Copyright © 2015 John Wiley & Sons, Ltd.     

Sequential Monte Carlo Methods for Estimating Dynamic Microeconomic Models

This paper develops estimators for dynamic microeconomic models with serially correlated unobserved state variables using sequential Monte Carlo methods to estimate the parameters and the distribution of the unobservables. If persistent unobservables are ignored, the estimates can be subject to a dynamic form of sample selection bias. We focus on single‐agent dynamic discrete‐choice models and dynamic games of incomplete information. We propose a full‐solution maximum likelihood procedure and a two‐step method and use them to estimate an extended version of the capital replacement model of Rust with the original data and in a Monte Carlo study. Copyright © 2015 John Wiley & Sons, Ltd.     

Improving an outpatient clinic utilization using decision analysis-based patient scheduling

This study presents a predictive model to be used in scheduling patients in an urban outpatient clinic. The model is based upon actual patient characteristics from a physical therapy clinic within an urban health and wellness center situated in a public university. A number of reported patients' characteristics such as age, education level, distance from the clinic, historical attendance records, etc. were examined to determine if they significantly impacted the patients' missing scheduled appointments (no-shows.) Decision tree analysis was used to develop a model that assessed the likelihood of a patient's no-show, using key patient characteristics and attendance records. Such a model can be used to assist with scheduling patients in an outpatient clinic, while attempting to increase the clinic's overall utilization. Four tree growing criteria were examined to develop the model with the strongest predictive power. Predictive power of each method was assessed by using the entire dataset as well as using split sampling. The results were then compared with those of a Bayesian networks model and a neural networks model. In addition, the trade-off between the selected decision tree model's predictive power versus simplicity of the associated classification rules was examined. We also assessed the impact of various levels of overbooking on the clinic's utilization when using patients' schedules based on the predictive model.     

Dynamic prediction of mortality among patients in intensive care using the sequential organ failure assessment (SOFA) score: a joint competing risk survival and longitudinal modeling approach

In intensive care units (ICUs), besides routinely collected admission data, a daily monitoring of organ dysfunction using scoring systems such as the sequential organ failure assessment (SOFA) score has become practice. Such updated information is valuable in making accurate predictions of patients' survival. Few prediction models that incorporate this updated information have been reported. We used follow‐up data of ICU patients who either died or were discharged at the end of hospital stay, without censored cases. We propose a joint model comprising a linear mixed effects submodel for the development of longitudinal SOFA scores and a proportional subdistribution hazards submodel for death as end point with discharge as competing risk. The two parts are linked by shared latent terms. Because there was no censoring, it was straightforward to fit our joint model using available software. We compared predictive values, based on the Brier score and the area under the receiver operating characteristic curve, from our model with those obtained from an earlier modeling approach by Toma et al . [Journal of Biomedical Informatics 40, 649, (2007)] that relied on patterns discovered in the SOFA scores over a given period of time.     

Optimal pricing strategy for foreign market entry: a game theoretic approach

Given that pricing plays an important role in a company's international competitive strategy, researchers have long argued the need for theory building in the area of international pricing. This study develops an optimal pricing strategy for foreign market entry using a game theoretic framework. The proposed model assumes two firms, a local incumbent and a foreign entrant, competing in a market. Consumers know the quality of the incumbent's offering, but do not know how it compares to that of the foreign entrant's. Based on these assumptions, and using the theory of inference making, we propose an upward price distortion by the entrant firm as an optimal entry strategy under incomplete information. The paper presents a game theoretic derivation to establish that the game has a unique intuitive separating equilibrium where the entrant firm stands to gain by engaging in upward price distortion to signal high quality to consumers. Copyright © 2006 John Wiley & Sons, Ltd.     

Information criteria for impulse response function matching estimation of DSGE models

We propose new information criteria for impulse response function matching estimators (IRFMEs). These estimators yield sampling distributions of the structural parameters of dynamic stochastic general equilibrium (DSGE) models by minimizing the distance between sample and theoretical impulse responses. First, we propose an information criterion to select only the responses that produce consistent estimates of the true but unknown structural parameters: the Valid Impulse Response Selection Criterion (VIRSC). The criterion is especially useful for mis-specified models. Second, we propose a criterion to select the impulse responses that are most informative about DSGE model parameters: the Relevant Impulse Response Selection Criterion (RIRSC). These criteria can be used in combination to select the subset of valid impulse response functions with minimal dimension that yields asymptotically efficient estimators. The criteria are general enough to apply to impulse responses estimated by VARs, local projections, and simulation methods. We show that the use of our criteria significantly affects estimates and inference about key parameters of two well-known new Keynesian DSGE models. Monte Carlo evidence indicates that the criteria yield gains in terms of finite sample bias as well as offering tests statistics whose behavior is better approximated by the first order asymptotic theory. Thus, our criteria improve existing methods used to implement IRFMEs.     

基于供应链节点供需企业间的价格博弈分析

运用博弈论原理,基于节点条件下,建立不完全动态博弈模型,并对价格博弈的过程进行分析和讨论,得出了最佳的博弈策略。     

Agreement toward stability in matching markets

For firms with responsive preferences, we prove that the set of stable matchings unanimously preferred by workers to any firm quasi-stable matching has a lattice structure. This follows from a generalization of the Decomposition Lemma. The result does not hold when firms have q-substitutable preferences. Nevertheless, we show that the set of stable matchings unanimously preferred by workers to a firm quasi-stable matching contains an element which is unanimously least preferred by workers, and most preferred by firms. When a firm quasi-stable matching is fed into our extension of the Deferred Acceptance algorithm (where firms propose), the existence of this matching guarantees the success of the algorithm.     

Team trust over time: Modeling reciprocal and contextual influences in action teams

Team trust is increasingly being recognized as important for team performance, but little is currently understood about how it develops and evolves over the course of a team's lifespan. Because trust and related team constructs are inherently dynamic, this represents a critical gap in the literature that needs to be addressed before team trust can be fully understood and effectively facilitated in practice. Of particular relevance to these gaps are action teams – those that come together to perform under time-constrained, yet often high-stakes conditions. While scholars have begun to explore how trust develops in these contexts, little is understood about how it evolves over time. As such, we propose a theoretical model of team trust in action teams that incorporates its dynamic nature, models the reciprocal relationship between team trust and team performance, delineates unique mediating pathways based on the team's progression in the multiphasic performance cycle, and considers the role of moderating influences that may strengthen or attenuate the impact of performance feedback on subsequent team trust. Specific research implications are discussed, providing a rich foundation for future empirical studies, and ultimately, the generation of evidence-based interventions for facilitating trust as teams cycle through multiple performance episodes over time.     

领导社交媒介自我表露、领导可信度与上下级关系:内隐领导原型匹配的权变作用

社交媒介自我表露是一种具体的社交媒介使用行为,对现代人的工作和生活都产生了不可忽视的影响。在工作情境中,领导的社交媒介自我表露尤其容易引起员工的高度关注。然而,领导的社交媒介自我表露对其在组织中的上下级关系将会产生何种影响有待深入探讨。鉴于此,基于社会信息加工理论和内隐领导理论,本文提出领导社交媒介自我表露的影响效应取决于内隐领导原型匹配的程度。当员工认为领导与其心目中内隐领导原型匹配程度高时,领导的社交媒介自我表露能够提升员工对领导的可信度感知,从而促进上下级关系,而当领导与员工心目中的内隐领导原型匹配程度低时,上述影响效果会减弱。通过对204份企业领导-下属配对问卷调查数据进行分析,本研究提出的被中介的调节模型得到支持。本研究的发现有利于深入认识组织中社交媒介自我表露的有效性,启发了领导需要考虑下属对表露解读的能动性,从而更合理地利用社交媒介平台进行自我表露,促进上下级关系良性发展。     

Measuring predictability: theory and macroeconomic applications

We propose a measure of predictability based on the ratio of the expected loss of a short‐run forecast to the expected loss of a long‐run forecast. This predictability measure can be tailored to the forecast horizons of interest, and it allows for general loss functions, univariate or multivariate information sets, and covariance stationary or difference stationary processes. We propose a simple estimator, and we suggest resampling methods for inference. We then provide several macroeconomic applications. First, we illustrate the implementation of predictability measures based on fitted parametric models for several US macroeconomic time series. Second, we analyze the internal propagation mechanism of a standard dynamic macroeconomic model by comparing the predictability of model inputs and model outputs. Third, we use predictability as a metric for assessing the similarity of data simulated from the model and actual data. Finally, we outline several non‐parametric extensions of our approach. Copyright © 2001 John Wiley & Sons, Ltd.