国有饭店管理层收购的实证分析--以浙江开元旅业集团为例

本文在分析MBO对国有饭店改革借鉴意义的基础上,通过浙江开元旅业集团MBO的案例分析,指出MBO是饭店业国有资本从竞争性领域中退出的重要手段和新突破,但在实践中需要规范,加强监管,防止创新过程中出现新问题.     

《南开管理评论》1998-2002年被引分析研究

本文运用CSSCI统计了《南开管理评论》1998年至2002年被引情况,对该刊在被引数量、被引著者及分布、被引文献来源期刊等方面进行了分析,通过计算CSSCI收录的所有管理学期刊的被引总篇次、影响因子及即年指标等数据,分析了《南开管理评论》在管理学期刊中的学术影响和地位。     

福建省建瓯市生殖健康/计划生育项目情景分析调查(上)

本文采用情景分析定性研究方法, 对联合国人口基金援华项目点福建省建瓯市的生殖健康／ 计划生育基础情况进行了全面的考察和深入的讨论, 并为进一步开展项目活动提出了相应的建议本文采用情景分析定性研究方法, 对联合国人口基金援华项目点福建省建瓯市的生殖健康／ 计划生育基础情况进行了全面的考察和深入的讨论, 并为进一步开展项目活动提出了相应的建议     

机器人教育市场发展现状及存在问题分析

近几年,由于国家、社会、家庭对机器人教育的高度重视,国内机器人教育机构如"雨后春笋、排山倒海"般的涌现,机器人教育市场发展也遇到了诸如教师专业化水平不高、教育研发相对滞后、家长的教育理念偏差等问题,本文以长春市机器人教育市场为例进行调研,分析问题成因并给出相对应的解决方案。     

中国雾霾污染的空间关联研究

本文利用非线性Granger因果检验识别了中国279个城市间雾霾污染的空间依赖关系,结合多样化的网络分析方法与滚动窗口技术揭示出雾霾污染空间关联的整体特征与微观模式,进而基于指数随机图模型考察了雾霾污染空间关联的影响因素及作用机制。研究发现：样本城市间普遍存在雾霾污染依赖关系并且这种空间关联的紧密程度逐渐上升,近年来中国大范围雾霾污染的频繁爆发与雾霾污染区域性特征的日趋强化密切相关。除了自然因素之外,人类经济社会活动在雾霾污染空间关联的形成中发挥了重要作用。本文的研究结论对雾霾污染及其区域传输的还原论、自然决定论等观点进行了有力的反驳,有助于确立人在雾霾治理中的主观能动性。     

国际比较项目中的中国PPP偏差问题

2014年世界银行公布的2011年轮全球国际比较项目（ICP）测算结果与发展中国家真实经济规模存在偏差,引发了发展中国家购买力平价是否被系统性低估的疑问。为此,基于ICP中中国部分的测算结果,立足于国际比较项目支出法测算的角度,对中国PPP偏差问题进行了分析。分析认为,从理论上看,ICP要求参与国提供GDP支出项数据与规格品价格数据在大国内部受到 了市场分割的影响,识别这种分割程度即空间关联性是ICP数据调查的前提。基于空间计量模型的实证结果表明：①在ICP的第七轮与第八轮调查期内,中国内部市场分割导致了价格水平存在时空两个方面的差异,影响了中国PPP计算的准确性;②市场分割导致的中国各地区的价差在短期内呈现随机性,只有长期才有可能出现趋同性。但2017年轮ICP调查周期由6年缩短为3年,使得这种趋同性难以出现在ICP活动的调查期内;③虽然ICP2017年轮采用滚动基期计算PPP,仍无法涵盖中国分割市场各自支出项目在空间上的不同作用力,这会使得支出法角度测算PPP时依然不能完全消除它的偏差,需要根据不同规格品的归属赋予不同权重才能较好地提高PPP测算的准确性。     

Marginal maximum likelihood estimation methods for the tuning parameters of ridge,power ridge,and generalized ridge regression

This study introduces fast marginal maximum likelihood (MML) algorithms for estimating the tuning (shrinkage) parameter(s) of the ridge and power ridge regression models, and an automatic plug-in MML estimator for the generalized ridge regression model, in a Bayesian framework. These methods are applicable to multicollinear or singular covariate design matrices, including matrices where the number of covariates exceeds the sample size. According to analyses of many real and simulated datasets, these MML-based ridge methods tend to compare favorably to other tuning parameter selection methods, in terms of computation speed, prediction accuracy, and ability to detect relevant covariates.     

Coordinating Service‐Sensitive Demand and Capacity by Adaptive Decision Making: An Application of Case‐Based Decision Theory*

The subject of this article is the simultaneous choice of product price and manufacturing capacity if demand is stochastic and service‐level sensitive. In this setting, capacity as well as price have an impact on demand because several aspects of service level depend on capacity. For example, delivery time will be reduced if capacity is increased given a constant demand rate. We illustrate the relationship between service level, capacity, and demand reaction by a stylized application problem from the after‐sales services industry. The reaction of customers to variations in service level and price is represented by a kinked price‐demand‐rate function. We first derive the optimal price‐capacity combination for the resulting decision problem under full information. Subsequently, we focus on a decision maker (DM) who lacks complete knowledge of the demand function. Hence the DM is unable to anticipate the service level and consequently cannot identify the optimal solution. However, the DM will acquire additional information during the sales process and use it in subsequent revisions of the price‐capacity decision. Thus, this decision making is adaptive and based on experience. In contrast to the literature, which assumes certain repetitive procedures somewhat ad hoc, we develop an adaptive decision process based on case‐based decision theory (CBDT) for the price‐capacity problem. Finally, we show that a CBDT DM in our setting eventually finds the optimal solution, if the DM sets the price based on absorption costs and adequately adjusts the capacity with respect to the observed demand.     

Sequential Search and Selection Problem Under Uncertainty

This paper formulates and discusses a series of sequential decision problems of the following common structure: A decision alternative of multiple attributes‐that is, a job, an employee, or an investment alternative‐is to be selected within a certain fixed length of time. An unknown number of alternatives are presented sequentially, either deterministically or in a random manner. The decision maker can rank all the alternatives from best to worst without ties, and the decision to accept or reject an alternative is based solely on the relative ranks of those alternatives evaluated so far. The nonparametric sequential decision problem is first studied for a model involving a discrete time period and then generalized in terms of continuous time. Also considered is a variant of this problem involving a Bayesian estimation of (1) the uncertain probability of having an alternative at a given stage in the discrete‐time model and (2) the arrival rate of alternatives in the continuous‐time model. The optimal selection strategy that maximizes the probability of selecting the absolute best alternative is illustrated with the job search problem and the single‐machine job assignment problem.     

A Framework for Measuring the Importance of Variables with Applications to Management Research and Decision Models*

In many disciplines, including various management science fields, researchers have shown interest in assigning relative importance weights to a set of explanatory variables in multivariable statistical analysis. This paper provides a synthesis of the relative importance measures scattered in the statistics, psychometrics, and management science literature. These measures are computed by averaging the partial contributions of each variable over all orderings of the explanatory variables. We define an Analysis of Importance (ANIMP) framework that reflects two desirable properties for the relative importance measures discussed in the literature: additive separability and order independence. We also provide a formal justification and generalization of the “averaging over all orderings” procedure based on the Maximum Entropy Principle. We then examine the question of relative importance in management research within the framework of the “contingency theory of organizational design” and provide an example of the use of relative importance measures in an actual management decision situation. Contrasts are drawn between the consequences of use of statistical significance, which is an inappropriate indicator of relative importance and the results of the appropriate ANIMP measures.