Learning to let go: Social influence,learning, and the abandonment of corporate venture capital practices

Research summary: This study examines the abandonment of organizational practices. We argue that firm choices in implementing practices affect how firms experience a practice and their subsequent likelihood of abandonment. We focus on utilization of the practice and staffing (i.e. career backgrounds of managers), as two important implementation choices that firms make. The findings demonstrate that practice utilization and staffing choices not only affect abandonment likelihood directly but also condition firms' susceptibility to pressures to abandon when social referents do. Our study contributes to diffusion research by examining practice abandonment—a relatively unexplored area in diffusion research—and by incorporating specific aspects of firms' post‐adoption choices into diffusion theory. Managerial summary: When do firms shut down practices? Prior research has shown that firms learn from the actions of other firms, both adopting and abandoning practices when their peers do. But unlike adoption decisions, abandonment decisions need to account for firms' own experiences with the practice. We study the abandonment of corporate venture capital (CVC) practices in the U.S. IT industry, which has experienced waves of adoption and abandonment. We find that firms that make more CVC investments are less likely to abandon the practice, and are less likely to learn vicariously from other firms' abandonment decisions, such that they are less likely to exit CVC when other firms do. Staffing choices also matter: hiring former venture capitalists makes firms less likely to abandon CVC practices, while hiring internally makes abandonment more likely. Plus, staffing choices affect how firms learn from the environment, as CVC managers pay attention to and learn more from the actions of firms that match their work backgrounds; i.e., firms that staff CVC units with former venture capitalists are more likely to follow exit decisions of VC firms, while those that staff with internal hires are more likely to follow their industry peers. Our results suggest that firms wanting to retain CVC practices should think carefully about the implementation choices they make, as they may be inadvertently sowing seeds of abandonment. Copyright © 2015 John Wiley & Sons, Ltd.     

工程项目采购中供应商优先关系模型研究

基于模糊优先关系比较法能科学地解决供应商选择中的不合理问题,对于实际工程材料采购有一定的现实指导意义;实例求解表明此法与层次分析法的解一致。     

先备知识对二语听力理解影响实证研究

本研究以112名非英语专业大学生为对象,调查了听力水平和背景知识对长对话理解的影响。学生按照听力水平和背景知识被分为四组。研究结果显示:①听力水平对于学生长对话的理解有显著影响;②背景知识对于学生理解长对话细节内容没有影响,但是对于主题内容的理解有显著影响;③对于细节内容的理解,学生的听力水平和背景知识之间没有交互作用,但对于主题内容的理解,这两者之间有交互作用,即听力水平高的学生能够更好运用他们的背景知识,理解主题内容。     

The surplus prior to ruin and the deficit at ruin for a correlated risk process

This paper presents an explicit characterization for the joint probability density function of the surplus immediately prior to ruin and the deficit at ruin for a general risk process, which includes the Sparre-Andersen risk model with phase-type inter-claim times and claim sizes. The model can also accommodate a Markovian arrival process which enables claim sizes to be correlated with the inter-claim times. The marginal density function of the surplus immediately prior to ruin is specifically considered. Several numerical examples are presented to illustrate the application of this result.     

BAYESIAN INFERENCE METHODS FOR UNIVARIATE AND MULTIVARIATE GARCH MODELS: A SURVEY

This survey reviews the existing literature on the most relevant Bayesian inference methods for univariate and multivariate GARCH models. The advantages and drawbacks of each procedure are outlined as well as the advantages of the Bayesian approach versus classical procedures. The paper makes emphasis on recent Bayesian non‐parametric approaches for GARCH models that avoid imposing arbitrary parametric distributional assumptions. These novel approaches implicitly assume infinite mixture of Gaussian distributions on the standardized returns which have been shown to be more flexible and describe better the uncertainty about future volatilities. Finally, the survey presents an illustration using real data to show the flexibility and usefulness of the non‐parametric approach.     

最大熵模型在物流量分布预测中的应用

引入最大熵模型的原理和方法,对物流分布预测的“四阶段方法”中的重力模型做了一定的改进,可以将发生概率最大的物流分布视为预测的物流分布,使得模型参数容易标定。示例表明该方法在物流量分布预测中具有较好的应用前景。     

Bayesian Calibration of p‐Values from Fisher's Exact Test

p‐Values are commonly transformed to lower bounds on Bayes factors, so‐called minimum Bayes factors. For the linear model, a sample‐size adjusted minimum Bayes factor over the class of g‐priors on the regression coefficients has recently been proposed (Held & Ott, The American Statistician 70(4), 335–341, 2016). Here, we extend this methodology to a logistic regression to obtain a sample‐size adjusted minimum Bayes factor for 2 × 2 contingency tables. We then study the relationship between this minimum Bayes factor and two‐sided p‐values from Fisher's exact test, as well as less conservative alternatives, with a novel parametric regression approach. It turns out that for all p‐values considered, the maximal evidence against the point null hypothesis is inversely related to the sample size. The same qualitative relationship is observed for minimum Bayes factors over the more general class of symmetric prior distributions. For the p‐values from Fisher's exact test, the minimum Bayes factors do on average not tend to the large‐sample bound as the sample size becomes large, but for the less conservative alternatives, the large‐sample behaviour is as expected.     

Prior Payment Status and the Likelihood to Pay Dividends: International Evidence

By using the signaling model and the life‐cycle theory, I examine the importance of prior payment status in determining the likelihood to pay dividends. I categorize firms into those that paid dividends previously and those that did not. My results show that strong dividend stickiness exists and the determinants to pay differ significantly for the two groups of firms. High growth and low insider holdings make prior payers more likely to pay but prior nonpayers less likely to pay. Furthermore, prior payers are more sensitive to profitability and earned/contributed equity mix, while prior nonpayers are more sensitive to risk and dividend premiums. Finally, taking the prior payment status into account eliminates the problem of overestimating the portion of payers put forth by previous studies.     

Hierarchical Bayesian Whittaker Graduation

Abstract

The Whittaker method of graduation has been known and used for a long time and has remained popular due to its possession of a number of ideal properties. They include being nonparametric and having an easy to understand foundation. The latter means that it makes sense and thus the user of the method has a good idea of what it can and cannot do. As well, there is a statistical derivation available that uses Bayesian notions. A problem with the derivation is that it is more intuitive than precise and as such does not provide a useful frame of reference for the graduator. Regardless of the point of view, the graduation cannot be completed until the smoothing parameter is selected and this has always relied on the judgment of the analyst.

In this paper, three tasks will be undertaken. The first is to replace the ad-hoc Bayesian derivation of the method with a formal Bayesian specification. The second is to show that with this specification it is possible to complete the graduation without making an arbitrary selection of the smoothing parameter. The third is to provide a Monte Carlo Bayesian approach for the incorporation of constraints in the graduated values. The ideas will be illustrated with a numerical example.