基于和谐管理理论的企业动态能力研究

基于和谐管理理论的组织运行模式,从组织学习的角度,以横向基于认知的构建和纵向基于适应性的演化两个维度展开,界定了动态能力的内涵.首先,认为动态能力包括组织对环境变化的认知能力以及在新主题导引下对原有资源配置方式做出调整以适应变化的能力,是组织在日常运行过程中应对外界变化时全体组织成员的学习能力;其次,认为动态能力是在构建与演化两个维度的耦合中演化的;第三,从组织运行的主题形成、主题实现和反馈学习三个阶段归纳了影响动态能力形成和演化的因素,这些因素主要分布在组织和领导两个层次上,最后针对已有动态能力研究中存在的一些问题进行了讨论.     

基于企业动态能力的新兴技术演化模型及案例研究

结合新兴技术的特点,在动态能力组织学习模型研究成果的基础上,提出了一个基于企业动态能力的新兴技术演化模型。结合该模型探讨了企业动态能力推动新兴技术演化的路径。并以SONY Walkman的演化过程为例对模型进行了检验,结果表明动态能力的形成有利于新兴技术的演化。     

The Dynamic Pivot Mechanism

We consider truthful implementation of the socially efficient allocation in an independent private‐value environment in which agents receive private information over time. We propose a suitable generalization of the pivot mechanism, based on the marginal contribution of each agent. In the dynamic pivot mechanism, the ex post incentive and ex post participation constraints are satisfied for all agents after all histories. In an environment with diverse preferences it is the unique mechanism satisfying ex post incentive, ex post participation, and efficient exit conditions. We develop the dynamic pivot mechanism in detail for a repeated auction of a single object in which each bidder learns over time her true valuation of the object. The dynamic pivot mechanism here is equivalent to a modified second price auction.     

Machine learning for multi-criteria inventory classification applied to intermittent demand

Multi-criteria inventory classification groups inventory items into classes, each of which is managed by a specific re-order policy according to its priority. However, the tasks of inventory classification and control are not carried out jointly if the classification criteria and the classification approach are not robustly established from an inventory-cost perspective. Exhaustive simulations at the single item level of the inventory system would directly solve this issue by searching for the best re-order policy per item, thus achieving the subsequent optimal classification without resorting to any multi-criteria classification method. However, this would be very time-consuming in real settings, where a large number of items need to be managed simultaneously.

In this article, a reduction in simulation effort is achieved by extracting from the population of items a sample on which to perform an exhaustive search of best re-order policies per item; the lowest cost classification of in-sample items is, therefore, achieved. Then, in line with the increasing need for ICT tools in the production management of Industry 4.0 systems, supervised classifiers from the machine learning research field (i.e. support vector machines with a Gaussian kernel and deep neural networks) are trained on these in-sample items to learn to classify the out-of-sample items solely based on the values they show on the features (i.e. classification criteria). The inventory system adopted here is suitable for intermittent demands, but it may also suit non-intermittent demands, thus providing great flexibility. The experimental analysis of two large datasets showed an excellent accuracy, which suggests that machine learning classifiers could be implemented in advanced inventory classification systems.     

Validation of the Learning Transfer System Inventory (LTSI) in the Korean corporate context

Lack of a valid instrument to measure learning transfer predictors has been the major obstacle hindering Human Resource Development (HRD) professionals from moving forward. This problem is one of the lingering HRD issues in South Korea, in which human resources have been strategically emphasized as a critical asset due to the scarcity of natural resources. To address this issue, this study aims at testing the validity and reliability of the data collected with the Korean Learning Transfer System Inventory (LTSI) Version 4. A sample of 753 managers from 16 Korean industries was divided into two subsamples for exploratory and confirmatory factor analyses. Reliability and the effect of common method variance on the factor structure were examined, with the results suggesting that the LTSI is valid for use in the Korean industry.     

Toward Probabilistic Prediction of Flash Flood Human Impacts

This article focuses on conceptual and methodological developments allowing the integration of physical and social dynamics leading to model forecasts of circumstance‐specific human losses during a flash flood. To reach this objective, a random forest classifier is applied to assess the likelihood of fatality occurrence for a given circumstance as a function of representative indicators. Here, vehicle‐related circumstance is chosen as the literature indicates that most fatalities from flash flooding fall in this category. A database of flash flood events, with and without human losses from 2001 to 2011 in the United States, is supplemented with other variables describing the storm event, the spatial distribution of the sensitive characteristics of the exposed population, and built environment at the county level. The catastrophic flash floods of May 2015 in the states of Texas and Oklahoma are used as a case study to map the dynamics of the estimated probabilistic human risk on a daily scale. The results indicate the importance of time‐ and space‐dependent human vulnerability and risk assessment for short‐fuse flood events. The need for more systematic human impact data collection is also highlighted to advance impact‐based predictive models for flash flood casualties using machine‐learning approaches in the future.     

Flood Risk Perceptions and Insurance Choice: Do Decisions in the Floodplain Reflect Overoptimism?

In the presence of rare disasters, risk perceptions may not always align with actual risks. These perceptions can nevertheless influence an individual's willingness to mitigate risks through activities such as purchasing flood insurance. In a survey of Maryland floodplain residents, we find that stated risk perceptions predict voluntary flood insurance take‐up, while perceptions themselves varied widely among surveyed residents, owing in large part to differences in past flood experience. We use a formal test for overoptimism in risk perceptions and find that, on aggregate, floodplain residents are overly optimistic about flood risks.     

A Collaborative View of Knowledge in a Knowledge Society: An International Perspective

This paper focuses on key topics that rose to the fore at the `Getting the Story Right' Joint Forum Assembly Meeting between business and higher education leaders of Australia, Canada, Japan, Poland, and the United States which was held in October 1998 in Banff, Canada. Arising from participant observation notes, conversations, document analysis, and reflective writing, the work centers on four major themes: the nature of knowledge and knowledge workers, the fundamental difference between training and learning, the short-term effects of shifting workplace and economic situations, and the long-term impact of intergenerational influences. Each of these knowledge-related themes emerged in collaborative discussions that transcended national, occupational, and cultural boundaries. The paper takes the position that dialogue regarding the nature and usefulness of knowledge paradoxically takes an inward view as it develops outwardly to the case of others and the world. In a collaborative process of this nature, an important dimension of shared human meaning making becomes briefly revealed.     

泛在学习环境下中美高校教师信息文化素养比较

在泛在学习环境下,高校教师作为教学的设计者、引领者、组织者和管理者,面对灵活多样的学习手段和海量的学习资源,必须具备较高的信息文化素养。比较中美信息文化素养的概念认知理解、中美高校教师信息文化素养建设标准以及中美高校教师信息素养提升途径与效果等方面的差异,学习和借鉴美国的成功经验,对从国情出发,制定出适合我国的高校教师信息文化素养标准,拓宽提升高校教师信息文化素养路径,推进我国教育现代化,实施人才强国战略具有重要意义。     

Organisational Learning and Governance Through Embedded Practices

This article has two principal aims. The first is to reconcile thecompetence based approach to the firm with traditional contractualapproaches, instead of treating them as incompatible. The mainthesis advanced is that firms manage simultaneously competencesand transactions, but they do so in accordance with a specificlexicographic order of priorities. The second aim is to explorein detail the sources of knowledge formation in the firm. Theanalysis privileges anthropological readings which stress the roleof learning – both radical and incremental – within distributed communities of practice.