基于属性水平的品牌来源国作用机制研究——信息处理的视角

制造和质量控制技术在全球范围的转移,导致制造国影响减弱,这对传统原产地研究提出了新的挑战。本研究在区分品牌来源国和产品制造国的基础上,通过把产品属性划分为搜索属性和信任属性,探索品牌来源国如何在属性评价层面上影响消费者。本研究发现,品牌来源国主要在信任属性上影响消费者对产品的评价。不仅如此,与新手型消费者相比,专家型消费者评价信任属性时更多地受到品牌来源国刻板印象的影响。     

Assessment of Catastrophic Risk Using Bayesian Network Constructed from Domain Knowledge and Spatial Data

Prediction of natural disasters and their consequences is difficult due to the uncertainties and complexity of multiple related factors. This article explores the use of domain knowledge and spatial data to construct a Bayesian network (BN) that facilitates the integration of multiple factors and quantification of uncertainties within a consistent system for assessment of catastrophic risk. A BN is chosen due to its advantages such as merging multiple source data and domain knowledge in a consistent system, learning from the data set, inference with missing data, and support of decision making. A key advantage of our methodology is the combination of domain knowledge and learning from the data to construct a robust network. To improve the assessment, we employ spatial data analysis and data mining to extend the training data set, select risk factors, and fine‐tune the network. Another major advantage of our methodology is the integration of an optimal discretizer, informative feature selector, learners, search strategies for local topologies, and Bayesian model averaging. These techniques all contribute to a robust prediction of risk probability of natural disasters. In the flood disaster's study, our methodology achieved a better probability of detection of high risk, a better precision, and a better ROC area compared with other methods, using both cross‐validation and prediction of catastrophic risk based on historic data. Our results suggest that BN is a good alternative for risk assessment and as a decision tool in the management of catastrophic risk.     

组织网络隐性知识扩散及学习策略分析

知识主要以显性知识和隐性知识两种方式存在,隐性知识是组织获得竞争优势的主要源泉.隐性知识为组织个体所拥有,这种私有性的特征使其在组织内部的扩散需要通过组织个体之间的交互才能完成.组织网络连接强度对扩散具有影响,可利用具有边权重的组织网络研究隐性知识的扩散行为.在分析隐性知识和相关扩散特点的基础上,基于组织成员之间的关系网络和小世界网络模型,建立组织网络上的知识扩散模型.根据认识论的观点,提出个体3种知识学习策略,结合知识扩散模型进行计算仿真实验.仿真结果显示,综合考虑关系和知识差别的知识学习策略最有效,不考虑连接强度下的各种策略都具有较快的知识学习速率,并且连接强度对组织内隐性知识扩散具有明显的作用.     

基于知识量的知识作业评测研究

以知识量作为作业难度表征的重要指标;在讨论信息量、教学时间与知识量关系的基础上,根据BROOKES信息基本方程,建立了社会标准教学时间与知识量的映射关系;根据知识表达系统提出了基于社会标准教学时间的知识测度原理及其测度方法;结合岗位知识量的测度进行了算例说明.     

Information Independence and Common Knowledge

In Bayesian environments with private information, as described by the types of Harsanyi, how can types of agents be (statistically) disassociated from each other and how are such disassociations reflected in the agents' knowledge structure? Conditions studied are (i) subjective independence (the opponents' types are independent conditional on one's own) and (ii) type disassociation under common knowledge (the agents' types are independent, conditional on some common‐knowledge variable). Subjective independence is motivated by its implications in Bayesian games and in studies of equilibrium concepts. We find that a variable that disassociates types is more informative than any common‐knowledge variable. With three or more agents, conditions (i) and (ii) are equivalent. They also imply that any variable which is common knowledge to two agents is common knowledge to all, and imply the existence of a unique common‐knowledge variable that disassociates types, which is the one defined by Aumann.     

学习迁移的系统理论:PPEE理论模型的建构和意义

学习是人类社会永恒的主题。为了更好地利用过去的经验,增强学习效果,个人和组织进行学习迁移具有重要意义。学习迁移是指将在以往通过学习或解决问题所获得的经验,用于解决之后所遇到的问题。本文力图建立系统的学习迁移理论,研究人、问题、环境的因素对于学习迁移的影响。本文采用理论推导的研究方法,在前人研究的基础上,提出相应的理论模型。本文运用系统的观点,构建了学习迁移的PPEE理论模型,认为人的因素、问题的因素、人和问题的交互作用、以及环境的调节作用,会共同影响学习迁移的效果。本理论主要从五个方面论述学习迁移的机制。首先,将人的因素按照不同层面划分为后端基本能力、中端心理过程、前端知识结构,讨论了其各自对学习迁移效果的直接影响。其次,将问题的因素划分为形象相似性和抽象相似性,并根据这两个维度构建了四种问题间关系类型,并探究了其与学习迁移效果之间的关系。第三,同时考虑人的因素和问题的因素,研究了二者之间的互动对于学习迁移效果的影响。第四,将环境因素划分为时间紧迫性和空间重要性两个维度,探讨了人和环境,以及问题和环境之间的互动对学习迁移效果的影响。第五,基于系统整体的方面,研究人、问题、环境三者之间的互动对学习迁移效果的交互影响。本文还认为,该模型不仅适用于个人,也同样适用于团队、组织、地区、甚至国家和社会等各个层面,影响各个层面主体的学习迁移。本文最后总结了研究的理论和实践贡献,并提出了未来研究课题。本文对丰富学习理论、特别是学习迁移理论,以及推动教育和管理实践的发展进步具有重要的意义。     

中介机构参与下联盟企业知识转移的三方利益博弈分析

知识转移是企业保存知识、提升创新能力的重要途径,中介机构在转移过程中发挥了重要作用。本文以联盟企业间知识转移为研究对象,考虑了企业的不同心理压力,首先建立了联盟企业双方的讨价还价博弈模型;其次构建了考虑中介机构参与知识转移的博弈模型,分析和讨论三方收益变化的影响因素及策略选择。结果表明,在直接知识转移博弈中,转移主体的收益大小与自身的心理压力呈负相关,而与对方的心理压力呈正相关,同等心理压力下知识转出方占优;中介机构参与博弈情形下,中介机构作为协作角色的博弈收益仅受博弈双方心理压力影响,且与知识接收方协作可获得更大收益,而主导角色博弈情形下收益受到三方主体心理压力的综合影响,并在主导知识接收博弈时获得收益更大;中介机构的角色选择与知识转出方心理压力变化相关性不明显,主要受到知识接收方及自身心理压力影响。     

知识分布、衰减程度与产业集群创新模式的内在机制研究

以知识流动为研究视角,将集群创新过程中的知识溢出、吸收能力内生化,构建包含三种创新模式下的产业集群演化模型,重点分析集群知识分布和知识衰减程度与集群创新模式的内在机制及其对创新产出的影响,并进行仿真实验。研究表明：不同知识分布下,混合创新模式的创新产出表现最好,外部吸收创新模式与内部自主创新模式呈现出不同的创新产出演化路径;在外部吸收创新和混合创新模式下,均匀分布型产业集群的创新产出表现最好,集中分布型表现次之,异质分布型表现最差,而在内部自主创新模式下,集中分布型则表现最好;不同创新模式对知识衰减的敏感程度呈现阶段性差异特征。这些结论对产业集群创新和可持续发展具有很好的理论和实践指导意义。     

Public Perception of Uncertainties Within Climate Change Science

Climate change is a complex, multifaceted problem involving various interacting systems and actors. Therefore, the intensities, locations, and timeframes of the consequences of climate change are hard to predict and cause uncertainties. Relatively little is known about how the public perceives this scientific uncertainty and how this relates to their concern about climate change. In this article, an online survey among 306 Swiss people is reported that investigated whether people differentiate between different types of uncertainty in climate change research. Also examined was the way in which the perception of uncertainty is related to people's concern about climate change, their trust in science, their knowledge about climate change, and their political attitude. The results of a principal component analysis showed that respondents differentiated between perceived ambiguity in climate research, measurement uncertainty, and uncertainty about the future impact of climate change. Using structural equation modeling, it was found that only perceived ambiguity was directly related to concern about climate change, whereas measurement uncertainty and future uncertainty were not. Trust in climate science was strongly associated with each type of uncertainty perception and was indirectly associated with concern about climate change. Also, more knowledge about climate change was related to less strong perceptions of each type of climate science uncertainty. Hence, it is suggested that to increase public concern about climate change, it may be especially important to consider the perceived ambiguity about climate research. Efforts that foster trust in climate science also appear highly worthwhile.     

External knowledge search,absorptive capacity and radical innovation in high-technology firms

Open innovation and absorptive capacity are two concepts based on the idea that companies can leverage the knowledge generated externally to improve their innovation performance. The aim of this paper is to analyse the joint effect of open innovation and absorptive capacity on a firm's radical innovation. Open innovation is expressed in terms of external search breadth and depth strategies and absorptive capacity is described by distinguishing between potential and realized absorptive capacity. In order to test our hypotheses, we carried out empirical research in firms operating in high-technology industries. The results indicate that internal routines and processes for absorbing external knowledge help explain radical innovation as they show a significant effect of potential and realized absorptive capacity. Also, there is a moderating effect of absorptive capacity on open innovation. Specifically, potential absorptive capacity exerts a positive effect on the relationship between external search breadth and depth and radical innovation. Realized absorptive capacity moderates the influence of external search breadth. These findings confirm the complementary nature of absorptive capacity and open innovation search strategies on radical innovation.