Defining Problems Fast and Slow: The U‐shaped Effect of Problem Definition Time on Project Duration

This study examines how time spent in problem definition affects problem solving in projects such as Six Sigma projects. Our hypotheses are tested using data collected from 1558 Six Sigma projects in a company. The results show evidence of a U‐shaped relationship between the amount of time spent in the Define phase and project duration. This finding suggests that spending too little time on problem definition potentially causes poor problem formulation, which leads to deficient problem solving and lengthens overall project time. On the other hand, too much time spent on problem definition can lead to unneeded delays in project completion due to diminishing returns on problem definition efforts. Furthermore, the optimal balance between spending too little and too much time depends on prior project experience and project complexity. Prior project experience reduced project completion time and weakened the U‐shaped effect. Conversely, complex projects took longer and appeared to show some evidence of a stronger U‐shaped effect; this suggests balancing the time spent in the Define phase was more challenging for complex projects. Our study also underscores the importance of managing project duration, as projects that were completed faster tended to be associated with higher project savings.     

关于旧证据问题的争论——评豪森的反事实策略

介绍了学界关于旧证据问题进行争论的情况.主张在豪森的反事实策略的基础上区分理论解释性证据和理论预见性证据,以应对反事实概率的可测度性问题.反事实策略并不要求在指派反事实概率上遵循理性的标准,反事实概率实质上是一种先验概率,即无条件的主观置信度,主观贝叶斯主义并不承诺其指派合理性标准.反事实概率的可测度性并不能构成对反事实策略的挑战.     

Exact and Monte Carlo calculations of integrated likelihoods for the latent class model

The latent class model or multivariate multinomial mixture is a powerful approach for clustering categorical data. It uses a conditional independence assumption given the latent class to which a statistical unit is belonging. In this paper, we exploit the fact that a fully Bayesian analysis with Jeffreys non-informative prior distributions does not involve technical difficulty to propose an exact expression of the integrated complete-data likelihood, which is known as being a meaningful model selection criterion in a clustering perspective. Similarly, a Monte Carlo approximation of the integrated observed-data likelihood can be obtained in two steps: an exact integration over the parameters is followed by an approximation of the sum over all possible partitions through an importance sampling strategy. Then, the exact and the approximate criteria experimentally compete, respectively, with their standard asymptotic BIC approximations for choosing the number of mixture components. Numerical experiments on simulated data and a biological example highlight that asymptotic criteria are usually dramatically more conservative than the non-asymptotic presented criteria, not only for moderate sample sizes as expected but also for quite large sample sizes. This research highlights that asymptotic standard criteria could often fail to select some interesting structures present in the data.     

Conditionally Reducible Natural Exponential Families and Enriched Conjugate Priors

Consider a standard conjugate family of prior distributions for a vector-parameter indexing an exponential family. Two distinct model parameterizations may well lead to standard conjugate families which are not consistent, i.e. one family cannot be derived from the other by the usual change-of-variable technique. This raises the problem of finding suitable parameterizations that may lead to enriched conjugate families which are more flexible than the traditional ones. The previous remark motivates the definition of a new property for an exponential family, named conditional reducibility. Features of conditionally-reducible natural exponential families are investigated thoroughly. In particular, we relate this new property to the notion of cut, and show that conditionally-reducible families admit a reparameterization in terms of a vector having likelihood-independent components. A general methodology to obtain enriched conjugate distributions for conditionally-reducible families is described in detail, generalizing previous works and more recent contributions in the area. The theory is illustrated with reference to natural exponential families having simple quadratic variance function.     

关于先验批判的回应与阐释(下)

在理性精神的再生产过程中,尽管充满思辨色彩的先验批判不是最直接的,但作为一种原理却无疑是最根本的。如果这个深层结构中的诸问题不能得到很好的解决,那么其他一切的经验批判在根基上就不会变得真正牢固起来。针对目前学术界对先验批判的一些疑问和批评,表文从先验批判的概念问题、先验哲学与西方现代哲学的关系、先验批判话题本身的意义、先验批判作为学术批评的合法性、先验批判与道德批判的关系、先验批判与意志独断论、先验批判与思想生产的关系以及先验批判的实践意义等八个方面阐释了作者的一些基本观点和价值立场。     

CONFIDENCE INTERVALS UTILIZING PRIOR INFORMATION IN THE BEHRENS–FISHER PROBLEM

Consider two independent random samples of size f + 1 , one from an N (μ₁, σ²₁) distribution and the other from an N (μ₂, σ²₂) distribution, where σ²₁/σ²₂∈ (0, ∞) . The Welch ‘approximate degrees of freedom’ (‘approximate t‐solution’) confidence interval for μ₁?μ₂ is commonly used when it cannot be guaranteed that σ²₁/σ²₂= 1 . Kabaila (2005, Comm. Statist. Theory and Methods 34 , 291–302) multiplied the half‐width of this interval by a positive constant so that the resulting interval, denoted by J₀, has minimum coverage probability 1 ?α. Now suppose that we have uncertain prior information that σ²₁/σ²₂= 1. We consider a broad class of confidence intervals for μ₁?μ₂ with minimum coverage probability 1 ?α. This class includes the interval J₀, which we use as the standard against which other members of will be judged. A confidence interval utilizes the prior information substantially better than J₀ if (expected length of J)/(expected length of J₀) is (a) substantially less than 1 (less than 0.96, say) for σ²₁/σ²₂= 1 , and (b) not too much larger than 1 for all other values of σ²₁/σ²₂ . For a given f, does there exist a confidence interval that satisfies these conditions? We focus on the question of whether condition (a) can be satisfied. For each given f, we compute a lower bound to the minimum over of (expected length of J)/(expected length of J₀) when σ²₁/σ²₂= 1 . For 1 ?α= 0.95 , this lower bound is not substantially less than 1. Thus, there does not exist any confidence interval belonging to that utilizes the prior information substantially better than J₀.     

佛教哲学与中国儒学的内在关系问题

儒家学说的底层解释模式是天人合德的宇宙哲学,具体表现为气感论学说以及这一学说所具有的自然主义形而上学特点。佛教的理论基础是缘起理论,业感缘起学说是其突出的特色。气感论与业感说的关系反映了儒家文化与佛教文化的差异,但因为“感”这一学说而使儒佛二种文化又具有某种沟通的内在基础。研究这两种学说的意义在于,可以进一步加深我们对中国传统文化的整体发展与演变的理解和把握。     

先前经验、学习风格与创业能力的实证研究

如何提升创业者的创业能力是目前创业实践中亟待解决的问题。在将经验和能力区分开的基础上,从创业学习的视角出发,深入挖掘创业者先前经验与创业能力之间的作用关系机制,探讨创业者经验向创业能力转化的内在机理,采用探索性因子分析、验证性因子分析、层级回归分析等方法,对173家中国新创企业的调查问卷进行分析。研究结果表明,学习风格在创业者先前经验与创业能力的关系中发挥调节作用,不同类型的先前经验对不同类型的创业能力产生影响,创业者的学习风格也并非像以往研究所认为的那样存在优劣之分,而是存在一个匹配关系,当创业者的信息获取/转化方式与他的先前经验类型相匹配时,这一类型的经验才能更好的转化为创业能力。     

转型经济体制下创业团队的先前经验、无力感与适应能力

在资源依赖理论的基础上,从创业团队的先前经验出发,通过分析4家高科技创业企业的案例资料,考察了创业团队无力感与适应能力之间的关联性,并分析了创业团队的认知趋同性对该作用过程的影响机制,从而为新创企业提高在动态环境中的生存能力提供建议.研究表明,创业团队先前经验可以降低团队成员的无力感,从而提升团队的适应能力,且当创业团队认知趋同性越高时,无力感与适应能力的负向作用越强.     

引入信息成本的信息结构与股权融资成本

本文放松了Easley和O’Hara信息成本为0的假设,在他们的信息结构模型的理论框架下,构建了一个引入信息成本因素的信息结构模型。从信息结构的四个方面：信息成本、信息风险、信息披露的质量和先验信息质量研究了信息结构与股权融资成本之间的关系,得出了四个推论,从而拓展了信息结构模型。在进一步的实证研究中,选取市场微观结构理论中的逆向选择成本、知情交易概率-PIN分别作为信息成本和信息风险的衡量指标,研究发现：信息成本与股权融资成本之间呈倒‘U’型曲线关系;信息风险越高的股票股权融资成本越高;信息披露质量越高的公司,股权融资成本越低;先验信息质量越高,股权融资成本越低;从而对推论进行了有效验证。本文与Easley和O’Hara最大不同在于引入了信息成本因素,并且用实证方法对推论进行了验证,具有一定的开创性。