高科技企业人才流失预警机制研究

以风险信息采集—风险预警指标库构建—风险评估—预警警报发布为逻辑思路阐述高科技企业人才流失风险预警模式。根据对人才流失风险的识别,从个体、组织、环境3个方面构建高科技企业人才流失风险预警指标体系,并利用层次分析法和熵权法对风险指标进行评估。最后,根据BP神经网络原理确定高科技企业人才流失风险预警模型,设计预警模型的构建步骤,进一步对风险等级及临界值进行设计和界定。     

A Classroom Exercise to Examine the Trade‐off between Mission Capacity and Life Cycle Cost

This article presents a classroom exercise, centered on a simulation that has been used for 4 years in an MBA program to help students develop an understanding of the trade‐offs involved in managing capital assets in the public sector. Though often ignored in business schools, mission is a key criterion that must be considered when managing such assets, and acts as a surrogate for profit. The case presents a rich environment in which the impact of cost reductions (or additional investments) on mission can be quantified, and trade‐offs can be assessed and discussed. It gives students a chance to develop creative ideas for process improvement, and provides sufficient data for them to analyze the impact of their suggestions in a rigorous way.     

互联网金融借贷平台的法律问题研究:以P2P为例

本文主要通过介绍互联网金融P2P借贷发展的概念,详细分析了互联网金融最具代表性的P2P网络借贷平台最近的发展状况及其带来的各种法律风险。然后运用国内外互联网金融理论对我国P2P网络借贷平台的现实问题进行具体阐述,提出一系列完善法律制度、建立完善互联网金融体系的建议。     

基于马尔可夫模型的风险型客户预测与管理

客户是企业的重要资产之一,是企业实现利润的源泉。客户关系的发展形成一个完整的生命周期,处于生命周期形成阶段的客户往往要消耗较多的资源却甚少为企业创造价值,企业的投入具有风险性。本文对风险型客户发展过程中的特点进行分析,同时提出基于马尔科夫模型的风险型客户预测方法,掌握风险型客户在市场竞争过程中的市场占有率信息,从而为企业的战略决策提供支持。     

基于Noisy-or gate 和贝叶斯网络的研发项目风险评估方法

在没有充足样本数据时,为有效地管理各种风险,本文提出了一个全新的研发项目风险评估模型,这个模型主要是基于Noisy-or gate 和贝叶斯网络进行评估。该模型在贝叶斯网络节点满足构成Noisy-or gate模型的前提下,利用历史数据或专家判断得到有效的网络参数,进而推断出每一项风险因素发生的概率,结合风险影响权重得到综合风险影响值,并对比得到高风险因素,为风险管理提供依据。通过与AHP方法评估结果对比表明,该模型可以准确地评估研发项目的风险,从而提高风险管理的效率。     

Multi-stage Internet public opinion risk grading analysis of public health emergencies: An empirical study on Microblog in COVID-19

In the period of Corona Virus Disease 2019 (COVID-19), millions of people participate in the discussion of COVID-19 on the Internet, which can easily trigger public opinion and threaten social stability. This paper creatively proposes a multi-stage risk grading model of Internet public opinion for public health emergencies. On the basis of general public opinion risk grading analysis, the model continuously pays attention to the risk level of Internet public opinion based on the time scale of regular or major information updates. This model combines Analytic Hierarchy Process Sort II (AHPSort II) and Swing Weighting (SW) methods and proposes a new Multi-Criteria Decision Making (MCDM) method – AHPSort II-SW. Intuitionistic fuzzy number and linguistic fuzzy number are introduced into the model to evaluate the criteria that cannot be quantified. The multi-stage model is tested using more than 2,000 textual data about COVID-19 collected from Microblog, a leading social media platform in China. Seven public opinion risk assessments were conducted from January 23 to April 8, 2020. The empirical results show that in the early COVID-19 outbreak, the risk of public opinion is more serious on macroscopic view. In details, the risk of public opinion decreases slowly with time, but the emergence of important events may still increase the risk of public opinion. The analysis results are in line with the actual situation and verify the effectiveness of the method. Comparative analysis indicates the improved method is proved to be superior and effective, sensitivity analysis confirms its stability. Finally, management suggestions was provided, this study contributes to the literature on public opinion risk assessment and provides implications for practice.     

Teaching Prospect Theory with the Deal or No Deal Game Show

Recent evidence indicates that decision makers are more sensitive to potential losses than gains. Loss aversion psychology has led behavioural economists to look beyond expected utility by developing prospect theory. We demonstrate this theory using the Deal or No Deal game show.     

Screening for potential child maltreatment in parents of a newborn baby: The predictive validity of an Instrument for early identification of Parents At Risk for child Abuse and Neglect (IPARAN)

For preventive purposes it is important to be able to identify families with a high risk of child maltreatment at an early stage. Therefore we developed an actuarial instrument for screening families with a newborn baby, the Instrument for identification of Parents At Risk for child Abuse and Neglect (IPARAN). The aim of this study was to assess the predictive validity of the IPARAN and to examine whether combining actuarial and clinical methods leads to an improvement of the predictive validity. We examined the predictive validity by calculating several performance indicators (i.e., sensitivity, specificity and the Area Under the receiver operating characteristic Curve [AUC]) in a sample of 4692 Dutch families with newborns. The outcome measure was a report of child maltreatment at Child Protection Services during a follow-up of 3 years. For 17 children (.4%) a report of maltreatment was registered. The predictive validity of the IPARAN was significantly better than chance (AUC = .700, 95% CI [.567–.832]), in contrast to a low value for clinical judgement of nurses of the Youth Health Care Centers (AUC = .591, 95% CI [.422–.759]). The combination of the IPARAN and clinical judgement resulted in the highest predictive validity (AUC = .720, 95% CI [.593–.847]), however, the difference between the methods did not reach statistical significance. The good predictive validity of the IPARAN in combination with clinical judgment of the nurse enables professionals to assess risks at an early stage and to make referrals to early intervention programs.     

企业技术创新风险分析

实践证明,技术创新风险越来越成为我国工业企业技术创新的障碍.本文分析了企业技术创新风险的来源,讨论了企业技术创新风险管理的主要内容,并对企业技术创新风险评价问题进行了详细探讨.