Bracing for demand shocks: An experimental investigation

We investigate inventory ordering decisions when decision makers anticipated a demand shock. Decision makers anticipating an event have been shown to brace for an uncertain negative outcome by overestimating the likelihood of that event. Decision makers faced with a spike in demand may incur increased holding costs because they may brace, exhibiting a judgment bias, and consequently a decision bias by over-ordering inventory. Three studies span conditions of uncertainty regarding the timing and magnitude of a demand shock: Employing three between-subjects experiments, Study 1 investigates behavior when decision makers were faced with uncertainty in timing and in magnitude of demand at the most elemental level, manipulating holding and stock out costs. The three experimental tasks feature uncertainty about the magnitude of demand (Experiment 1.1), uncertainty about the timing of demand (Experiment 1.2), and uncertainty about both the magnitude and timing of demand (Experiment 1.3). Study 2 uses a dynamic, multi-period replenishment task and a between-subjects manipulation regarding the uncertainty of timing and magnitude of a demand shock. Study 3 also employs a multi-period decision environment, but compares behavior under a demand shock condition with that in a condition featuring only random variability. The collective results from the three studies identify a bias toward over-ordering in response to a demand shock, relative to the optimal orders. The between-subjects manipulations in Study 2 points toward a possible remedy as we found that providing information concerning the timing and magnitude of a shock ameliorated the bias. The primary revelation was that decision makers had more difficulty dealing with uncertain timing than with uncertain magnitude of demand. One implication is that it is particularly critical for retailers to carefully plan and manage how they share information with upstream supply chain partners regarding when they plan to introduce store-level promotions.     

Predicting the failures of prediction markets: A procedure of decision making using classification models

Prediction markets have been an important source of information for decision makers due to their high ex post accuracies. Nevertheless, recent failures of prediction markets remind us of the importance of ex ante assessments of their prediction accuracy. This paper proposes a systematic procedure for decision makers to acquire prediction models which may be used to predict the correctness of winner-take-all markets. We commence with a set of classification models and generate combined models following various rules. We also create artificial records in the training datasets to overcome the imbalanced data issue in classification problems. These models are then empirically trained and tested with a large dataset to see which may best be used to predict the failures of prediction markets. We find that no model can universally outperform others in terms of different performance measures. Despite this, we clearly demonstrate a result of capable models for decision makers based on different decision goals.     

浅谈医院精细化管理推进的重要意义

"服务好、质量好、医德好,群众满意"的"三好一满意"是全国医疗卫生系统切实提高医疗服务质量,提升医疗卫生行业社会形象而开展的活动。本文通过无锡市第二人民医院运用精细化管理推进"三好一满意"活动的具体做法进行了探讨和介绍。     

Inter-temporal preference for flexibility and risky choice

We derive an inter-temporal theory of choice, in the spirit of Kreps and Porteus [Kreps, D.M., Porteus, E.L., 1978. Temporal resolution of uncertainty and dynamic choice theory. Econometrica 46, 185–200], where decision makers have incomplete preferences. This can be used to model indecisiveness as well as unforeseen contingencies. The key to our approach is a time consistency condition and therefore the normative connection between ex-ante and ex-post choice. The time consistency condition enables a representation that is a straight forward extension of recursive utility with the exception that it features an inter-temporal ‘utility for flexibility’.     

输气管道设备远程监测及决策支持系统开发

通过研发输气管道设备远程监测及决策支持系统,对现场运行设备状态、运行状况进行监测,对于出现的问题及时进行报警并提供历史数据分析,使运维人员及时解决隐患问题,真正实现设备运行状态远程监测、诊断和维护等功能,降低设备故障率,减少设备维护时间,确保生产安全、稳定运行。     

口腔科医疗设备与仪器维护方法探讨

目的:探讨口腔科设备与仪器的维护保养方法,以延长设备的使用寿命,发挥设备的高效性能及用途。方法:对比实施相关口腔科医疗设备的维护保养措施前与采取措施之后,口腔科医疗设备的使用和保养情况,分析口腔科医疗设备维护保养措施的可行性和有效性。结果:实施口腔科医疗设备专项维护保养措施后,口腔科设备仪器平均使用寿命比之前延长1.5年,设备仪器故障率降低了4.5%。结论:实施科学合理的设备维护保养措施,培养专业的仪器保养维修团队能够有效提高口腔医疗设备的使用效率和使用寿命,不仅能够更好的服务于社会,也为医院节省了一大笔设备仪器维护费用,值得借鉴推广。     

Applying lot-by-lot double sampling plan to reform Taiwan National Health Insurance auditing system

This paper seeks to design an elaborate and effective “sampling audit and payment process” for a single-payer system of national health insurance. Furthermore, contrive incentive mechanisms in the “sampling audit and payment process” to make the healthcare providers willing to apply for their medical claim payments straightforwardly. A framework of “medical claim payment auditing by double sampling plan (MCPAD)” procedure based on the lot-by-lot double sampling plan was proposed to curb the growth of medical expenses. The proposed procedure entertains several advantages, including: (1) it meets international standards of sampling plan; (2) it simplifies the auditing process; (3) it reduces sample size and auditing costs; and (4) it encourages healthcare providers using an honest medical claim payment through the incentive mechanisms. This study successfully reduces the sampling cost and effectively audits the claimed medical fees as well as encourages healthcare providers to straightforwardly apply for their medical claim payments. Practically, the proposed MCPAD procedure is also applied to healthcare provider. It is anticipated that the proposed procedure in other nations in the future.     

浅析医疗设备常见故障与维修养护措施

医疗设备在使用过程中,不可避免的会出现各种故障,妨碍设备的正常使用,只有及时维修消除故障,才能确保在使用时医疗设备的安全有效。文章对医疗设备常见故障与维修养护措施做一下分析总结。     

Application and extension of the Moore and ReVelle Hierarchical Maximal Covering Model

In a paper published in Management Science in 1982, George Moore and Charles ReVelle proposed a location model for siting a hierarchical system of medical facilities. In this paper we apply the Moore and ReVelle Hierarchical Maximal Covering Model to the location of medical facilities in the Kohat district in Pakistan. Optimal solutions of the Moore and ReVelle model are compared against the actual location of medical facilities in this district. We then extend the Moore and ReVelle formulation to include fixed and variable costs for siting and operating the facilities. We compare the solutions of that formulation with the results of the original Moore and ReVelle model.     

Remaining useful life in theory and practice

Remaining useful life (RUL) is nowadays in fashion, both in theory and applications. Engineers use it mostly when they have to decide whether to do maintenance, or to delay it, due to production requirements. Most often, it is assumed that in later life of an equipment (in wear-out period), the hazard function is increasing, and then the expected RUL, μ(t), is decreasing. We noticed that the standard deviation of RUL, σ(t), is also decreasing, which was expected and known, but that the ratio σ(t)/μ(t) is also increasing, which was a surprise. Initiated by this observation, we have proved that under some general conditions, which include Weibull distribution with shape parameter  > 1, this is indeed the case. Even more, we have proved that the limiting distribution of standardized RUL is exponential, so that the variability of RUL is relatively large. The role of condition monitoring in the evaluation of RUL is discussed. Various models for RUL depending on covariates are considered.     

Bayesian learning with variable prior

How much can be learned from a noisy signal about the state of the world not only depends on the accuracy of the signal, but also on the distribution of the prior. Therefore, we define a general information system as a tuple consisting of both a signal technology and a prior. In this paper we develop a learning order for general information systems and characterize the order in two different ways: first, in terms of the dispersion of posterior beliefs about state quantiles and, second, in terms of the value of learning for two different classes of decision makers. The first class includes all agents with quasi-linear quantile preferences, and the second class contains all agents with supermodular quantile preferences.     

Decision making in the beer game and supply chain performance

The beer game has been used to emphasize, investigate, and analyze supply chain inefficiencies as well as the effect of decision makers’ biases. This paper investigates the short- and long-run performance in the beer distribution game by analyzing Sterman’s (Manag Sci 35(3): 321–339, 1989) model that simulates decision-making. In this model, the system may have chaotic behavior depending on the heuristics used by decision makers. We investigate how quickly the system reaches a steady state (if at all). It is known that ignoring supply line (outstanding orders) leads to the bullwhip effect in experimental research. Among other results, we show that the short-term performance of a supply chain is not a predictor of the long-term performance even when decision makers fully recognize outstanding orders. Results of the simulation and practical implications are discussed.     

医疗仪器设备维修管理方法的研究

对医疗仪器设备的维修和管理是医院一项至关重要的工作,它会直接关系到临床医疗效果乃至医院的声誉,也会影响到医院的运行的经济效益。本文就医疗仪器设备维修管理方法进行研究。     

Group-based judgmental forecasting: An integration of extant knowledge and the development of priorities for a new research agenda

We review and integrate the extant knowledge on group-based forecasting, paying particular attention to the papers included in this special issue of the International Journal of Forecasting. We focus on the relative merits of different methods of aggregating individual forecasts, the advantages of heterogeneity in group memberships, the impact of others’ opinions on group members, and the importance of perceptions of trust. We conclude that a change of opinion following group-based deliberation is most likely to be appropriate where the group membership is heterogeneous, the minority opinion is protected from pressure to conform, information exchange between group members has been facilitated, and the recipient of the advice is able — by reasoning processes — to evaluate the reasoning justifying the proffered advice. Proffered advice is least likely to be accepted where the advisor is not trusted — an evaluation which is based on the advisor having different perceived values to the recipient and being thought to be self-interested. In contrast, the outcome of a group-based deliberation is most likely to be accepted when there is perceived to be procedural fairness and the participants in the process are perceived to be trustworthy. Finally, we broaden our discussion of group-based forecasting to include a consideration of other group-based methodologies which are aimed at enhancing judgment and decision making. In particular, we discuss the relevance of research on small-group decision making, the nature and quality of the advice, group-based scenario planning, and public engagement processes. From this analysis, we conclude that, for medium- to long-term judgemental forecasting, a variety of non-outcome criteria need to be considered in the evaluation of alternative group-based methods.     

A note on the existence of CAPM equilibria with homogeneous cumulative prospect theory preferences

This note identifies and fixes a minor gap in Proposition 1 in Barberis and Huang (Am Econ Rev 98(5):2066–2100, 2008). Assuming homogeneous cumulative prospect theory decision makers, we show that CAPM is a necessary (though not sufficient) condition that must hold in equilibrium. We support our results with numerical examples where security prices become negative.     

Welfare-improving policy on medical tourism and labor productivity: A theoretical analysis

This paper considers welfare and wage inequality effects of developing medical tourism on the host country from a theoretical point of view. Due to the competition between public healthcare provision and medical tourism, the development of medical tourism might reduce labor productivity and thus widen wage inequality via the increased wage rates of healthcare workers and decreased wage rates of production workers. In addition, the expansion of medical tourism can lower social welfare of the host country through a decline in labor productivity caused by reduced public healthcare provision. A tax-subsidy welfare-improving scheme is suggested to mitigate the unfavorable productivity effect of medical tourism on the host economy. This theoretical result fits into current empirical evidence on medical tourism.     

配送中心的产品供给-分配随机决策系统的设计

本文在考虑随机因素的基础上，使用随机规划的方法，建立多个供应商、一种产品以及多个经销商组成的供应链系统的多目标随机规划模型，使得与实际有较高的实用价值。     

Use of a Markov decision process model for treatment selection in an asymptomatic disease with consideration of risk sensitivity

Some potentially dangerous diseases are completely asymptomatic. Their diagnosis as incidental findings of ever-more-sensitive medical imaging can leave patients and physicians in something of a quandary. The patient feels well, and potential interventions to stave off long-term deterioration or death bring with them immediate risks. We discuss the use of a Markov Decision Process (MDP) model (rather than Monte Carlo simulation of a Markov Model) to create a tool for analyzing individual treatment decisions for asymptomatic chronic diseases where a patient’s condition cannot improve. We formulate a finite-horizon MDP model to determine optimal treatment plans and discuss three distinct optimality criteria: (a) maximizing expected quality-adjusted-life years with and without discounting, (b) maximizing the expected number of life years in good health, and (c) maximizing the expected utility for number of years in good health. In (c) we assume exponential utility and consider different risk aversion factors reported in the medical literature. We illustrate the model’s use by considering asymptomatic intracranial aneurysm. Our model builds on a simulation model [19] created to examine treatment recommendations based on cost-effectiveness. We demonstrate that incorporating risk aversion leads to “no treatment” recommendations for some types of aneurysm. Furthermore, the use of alternate patient-selected criteria leads to recommendations that vary from [19] in several scenarios. We also discuss the use of the software as a decision support tool to help make individualized treatment recommendations and demonstrate that the computational performance of the algorithm makes its use feasible during a short office visit.     

Cardinal versus ordinal criteria in choice under risk with disconnected utility ranges

This paper provides a formal justification for the existence of subjective random components intrinsic to the outcome evaluation process of decision makers and explicitly assumed in the stochastic choice literature. We introduce the concepts of admissible error function and generalized certainty equivalent, which allow us to analyze two different criteria, a cardinal and an ordinal one, when defining suitable approximations to expected utility values. Contrary to the standard literature requirements for irrational preferences, adjustment errors arise in a natural way within our setting, their existence following directly from the disconnectedness of the range of the utility functions. Conditions for the existence of minimal errors are also studied. Our results imply that neither the cardinal nor the ordinal criterion do necessarily provide the same evaluation for two or more different prospects with the same expected utility value. As a consequence, a rational decision maker may define two different generalized certainty equivalents when presented with the same prospect in two different occasions.