基于规范场理论的技术创新网络知识时空测度

基于分形的技术创新网络的数学描述,解决研究方法中个人主义与集体主义的冲突;在此基础上,将技术创新网络中不同结点间的相互作用抽象为对应的主丛联络,分别建立技术创新网络知识时空在不同结点处的时空曲率和时空温标的数学结构,并进一步对其进行经验解释.研究表明,对技术创新网络的分形描述可以克服不同层次技术创新网络研究中集体主义与个人主义的冲突,引入知识规范可以形成知识时空,研究知识时空可以决定真实世界的技术创新活动;知识时空是对应技术创新过程中信息场与其上面特定的结构形成的,可以与信息流结合研究技术创新过程中创新企业之间的交互作用;知识时空的曲率特征刻画技术创新网络中特定知识对外部信息(不确定性)的作用,而知识时空温标特征刻画技术创新网络的能量状态,并进一步确定创新网络知识的有序状态.     

核电厂人因失误机理研究:QAP分析

为了明确核电厂人因失误机理并为后期人因失误的精准防控提供理论依据,文章采用“组织定向人因失误分析技术”对2010—2020年核电厂208件人因失误事件报告进行分析,获得样本数据,经统计辨识主要的人因失误类型(知识型、规则型和技能型)和影响因素(如教育培训、组织设计、规程、人机界面等),结合影响因素之间的相关性及因子分析构建主要人因失误场景(如知识/技能经验、注意力、压力和态度等)。由于各因素之间存在相互影响,因而采用QAP方法(Quadratic Assignment Procedure,二次指派程序)对人因失误场景进行相关分析和回归分析,建立知识型、规则型、技能型人因失误因果模型,辨识不同的人因失误场景,揭示人因失误机理。结果表明,不同的人因失误类型其产生机理以及场景显著性不同,为人因失误的精准防控提供理论依据。     

科研项目风险管理刍议

科研项目的风险管理至今仍是个管理学上的空白点,也正是因为人们缺乏对科研项目的风险管理意识才使得大量的科研项目无法取得预期效果。文章在探讨科研项目自身特征的基础上,提出了一套科研项风险管理模式。     

公示语翻译错误之分析——以金华地区广告、标识和招牌英语使用错误为例

本文从金华市公示语,包括广告、标识和招牌等英语使用调查入手,分析了公示语翻译错误的类型,以及产生这些翻译错误的原因。最后从实际出发提出了两点结论和四条如何改进这些翻译错误的建议。     

基于鲁棒性的关键链二次资源冲突消除策略

以关键链方法中的二次资源冲突困境为切入点,从鲁棒调度优化角度提出一种解决策略.首先,采用定量化建模对问题进行数学描述和表达,剖析插入输入缓冲引起二次资源冲突的原理,进而采用场景分析法从复杂的冲突表象中分解出四种基本的冲突场景构成要素.其次,基于鲁棒调度优化理论,探究各种冲突子问题的有效对策并归类,据此开发出一种消除二次资源冲突的局部重调度启发式协调策略;根据策略设计基于两次调度进程和两类缓冲动态消耗的鲁棒性指标,采用鲁棒性关键链项目调度问题输出鲁棒性最大的调度方案.再次,设计仿真程序和三个测试指标:项目实际按期完工率、活动开始时间偏差绝对值之和及偏差绝对值的方差;基于ProGen随机地生成测试算例集合进行数值实验.结果发现,以鲁棒性调度方案为依据安排项目的实施过程,三个统计指标值都优于以传统关键链调度方案为依据时相对应的指标值.结论表明:基于鲁棒调度优化的二次资源冲突消除策略及设计的关键链鲁棒性指标在项目实施中具有较好的稳定性效果.     

创新活动空间集聚及其驱动因素国外研究进展评述

对国外有关创新活动空间集聚的研究文献进行梳理,分析了现有研究取得的成就和存在的问题,对未来研究的几个待突破的方面进行了展望。     

Developing a Broadly Applicable Measure of Risk Perception

Decades of research identify risk perception as a largely intuitive and affective construct, in contrast to the more deliberative assessments of probability and consequences that form the foundation of risk assessment. However, a review of the literature reveals that many of the risk perception measures employed in survey research with human subjects are either generic in nature, not capturing any particular affective, probabilistic, or consequential dimension of risk; or focused solely on judgments of probability. The goal of this research was to assess a multidimensional measure of risk perception across multiple hazards to identify a measure that will be broadly useful for assessing perceived risk moving forward. Our results support the idea of risk perception being multidimensional, but largely a function of individual affective reactions to the hazard. We also find that our measure of risk perception holds across multiple types of hazards, ranging from those that are behavioral in nature (e.g., health and safety behaviors), to those that are technological (e.g., pollution), or natural (e.g., extreme weather). We suggest that a general, unidimensional measure of risk may accurately capture one's perception of the severity of the consequences, and the discrete emotions that are felt in response to those potential consequences. However, such a measure is not likely to capture the perceived probability of experiencing the outcomes, nor will it be as useful at understanding one's motivation to take mitigation action.     

The Practical Significance of Measurement Error in Pulmonary Function Testing Conducted in Research Settings

Conventional spirometry produces measurement error by using repeatability criteria (RC) to discard acceptable data and terminating tests early when RC are met. These practices also implicitly assume that there is no variation across maneuvers within each test. This has implications for air pollution regulations that rely on pulmonary function tests to determine adverse effects or set standards. We perform a Monte Carlo simulation of 20,902 tests of forced expiratory volume in 1 second (FEV₁), each with eight maneuvers, for an individual with empirically obtained, plausibly normal pulmonary function. Default coefficients of variation for inter‐ and intratest variability (3% and 6%, respectively) are employed. Measurement error is defined as the difference between results from the conventional protocol and an unconstrained, eight‐maneuver alternative. In the default model, average measurement error is shown to be ～5%. The minimum difference necessary for statistical significance at p < 0.05 for a before/after comparison is shown to be 16%. Meanwhile, the U.S. Environmental Protection Agency has deemed single‐digit percentage decrements in FEV₁ sufficient to justify more stringent national ambient air quality standards. Sensitivity analysis reveals that results are insensitive to intertest variability but highly sensitive to intratest variability. Halving the latter to 3% reduces measurement error by 55%. Increasing it to 9% or 12% increases measurement error by 65% or 125%, respectively. Within‐day FEV₁ differences ≤5% among normal subjects are believed to be clinically insignificant. Therefore, many differences reported as statistically significant are likely to be artifactual. Reliable data are needed to estimate intratest variability for the general population, subpopulations of interest, and research samples. Sensitive subpopulations (e.g., chronic obstructive pulmonary disease or COPD patients, asthmatics, children) are likely to have higher intratest variability, making it more difficult to derive valid statistical inferences about differences observed after treatment or exposure.     

Measuring operational excellence: an operational excellence profitability (OEP) approach

The pursuit of operational excellence in the manufacturing industry is at rise but its measurement still lacks of appropriate indicators to determine its financial benefits. The ambiguity is due to the impact arisen from manufacturing fluctuations such as price and cost, production mix and direct and indirect parameters variations. Manufacturing fluctuations distort the cost benefit of operational excellence. This paper, therefore, proposes the OEP (Operational Excellence Profitability) indicators to isolate the impact of manufacturing fluctuation and distinctly identify the payback of operational excellence strategies and initiatives through cost benefits of achieving higher efficiency and yield. The paper presents the conceptual and mathematical development of the proposed OEP indicators and the formulas used for their calculation. Hypothetical and industrial-based investigations and applications of the OEP indicators are conducted for their validation. The results obtained from the hypothetical exercise and industrial case suggest that OEP indicators can provide an effective cost-benefit analysis of operational excellence. This would contribute in providing manufacturing organizations with more complete information regarding the performance of their processes, which will allow their directors and managers to take better decisions related to the management and improvement of their processes.     

From design to operations: a process management life-cycle performance measurement system for Public-Private Partnerships

Public–Private Partnerships (PPPs) have become a critical vehicle for delivering infrastructure worldwide. Yet, the use of such a procurement strategy has received considerable criticism, as they have been prone to experiencing time/cost overruns and during their operation poorly managed. A key issue contributing to the poor performance of PPPs is the paucity of an effective and comprehensive performance measurement system. There has been a tendency for the performance of PPPs to be measured based on their ex-post criteria of time, cost and quality. Such criteria do not accommodate the complexities and lifecycle of an asset. In addressing this problem, the methodology of sequential triangulation is used to develop and examine the effectiveness of a ‘Process Management Life Cycle Performance Measurement System’. The research provides public authorities and private-sector entities embarking on PPPs with a robust mechanism to effectively measure, control and manage their projects’ life cycle performances, ensuring the assets are ‘future proofed’.