More (new) products,more problems? A systems perspective on increased capability deployment and organizational errors

The capabilities-based view postulates that organizational capabilities are a key driver of competitive advantage. However, while increasing the pace of deploying organizational capabilities, such as new product development (NPD), may enable alignment with changing environments, it may also have unintended consequences. In this study, we advance theory on these unintended consequences by investigating how the increased deployment of NPD capability leads to organizational errors. Borrowing from organizational research employing systems theory, we argue that an increase in NPD deployment may increase the likelihood of routine discoordination and, thus, the incidence of intra-firm and interfirm errors. However, we also proffer that firms can mitigate errors from increases in NPD capability deployment by engaging in distinct internal and external activities that enable the accumulation of knowledge on how to coordinate systemic change. We distinguish between internal and external errors, demonstrating that in the context of increased NPD deployments, internal voluntary investigations ameliorate internal manufacturing errors, while supplier alliances mitigate outsourced component errors. We find support for our predictions using data from new product introductions and recalls in the U.S. automotive industry. This study sheds light on the tension inherent to accelerating the deployment of patterned organizational activities and suggests that the outcomes of deploying an organizational capability are best viewed holistically within the milieu of organizational systems the capability spans.     

基于SRFML-Lift的流程制造产品质量状态监测

对流程制造型企业而言,产品质量状态的监测精度直接影响了企业的生产与运营成本。面对流程工业的多变量监测要求和数据不均衡性,以往研究主要采取局部建模策略或多输出模型,存在特征选择偏差和分类精度不高的问题。对此,本文设计了一种结合SRFML特征选择和Lift学习策略的质量状态监测模型,通过共享不同目标之间的信息以期提升模型的监测效果。首先,根据ReliefF过滤机制,引入重采样赋权思想对工业特征的选择过程进行优化(SRFML);然后,将选择结果作为Lift学习框架的输入,通过类属属性学习方式重塑各待监测特性的特有关联属性;最后采用多个SVM分类器进行训练,得到各目标的质量状态结果。结果表明,本文构建的SRFML-Lift充分学习了原始特征的关键信息,与其他组合策略相比,对质量状态的监测效果更佳,可应用于流程工业的生产管理实践。     

基于“学习领导”理念的幼教名师工作室建设现状与对策

：强调以学习为核心的学习领导为理解与支持幼儿园教师学习与专业发展提供了一种全新的、系统的视角。在学习领导 理念下,幼教名师工作室应积极构建发展愿景;坚持持续对话,产生共识行动;引导建立安全、鼓励尝试的氛围;发挥行政力量 构建和完善幼教名师工作室运行机制。     

新时代党政干部学 习教育常态化制度化的若干思考

新时代党政干部学习教育常态化制度化是遵循执政能力提升规律的必然选择、应对意识形态领域斗争的战略需要以及形塑百年大党光辉形象的内在要求。常态化制度化推进党政干部学习教育在样态上突出日常化与规范性、方式上注重理论性与实践性、过程中彰显适宜度与有序性、效果上具有针对性与可持续等基本特征。党政机关主管部门要从把握常态化制度化学习教育内外张力、构建常态化制度化学习教育制度体系、保障常态化制度化学习教育资源供给、加强常态化制度化学习教育监督考核、完善常态化制度化学习教育评价激励等方面入手,确保学习教育常态化制度化推进,切实提升党政干部治国理政的能力和素养。     

当代科技翻译工作者职业发展的挑战和对策

近代以来,科技翻译有力推动了我国的科技发展和社会进化,在民族复兴的新征程中,科技翻译事业仍有重要意义。在当今科技进步与社会变迁对科技翻译职业带来诸多挑战的背景下,探讨了当代科技译者面临的职业难题与对策,以及科技译者应具备的专业素养。青年译者宜利用好新技术,产出更优质的成果,并调整职业规划,将翻译与专业方向相结合,成长为复合型人才,以翻译为核心竞争力胜任多种专业工作。为应对科技文献的新特点,优秀译者需具备坚实的翻译能力基础、充分的专业知识储备和基本的翻译理论素养。同时,译者还可培养编辑、写作等能力和专业敏感度、跨学科视野等综合素质,从而满足职业融合的需要。     

Sampling from spatial databases

This paper deals with techniques for obtaining random point samples from spatial databases. We seek random points from a continuous domain (usually ²) which satisfy a spatial predicate that is represented in the database as a collection of polygons. Several applications of spatial sampling (e.g. environmental monitoring, agronomy, forestry, etc) are described. Sampling problems are characterized in terms of two key parameters: coverage (selectivity), and expected stabbing number (overlap). We discuss two fundamental approaches to sampling with spatial predicates, depending on whether we sample first or evaluate the predicate first. The approaches are described in the context of both quadtrees and R-trees, detailing the sample first, acceptance/rejection tree, and partial area tree algorithms. A sequential algorithm, the one-pass spatial reservoir algorithm is also described. The relative performance of the various sampling algorithms is compared and choice of preferred algorithms is suggested. We conclude with a short discussion of possible extensions.     

Can we rationally learn to coordinate?

In this paper we examine the issue whether individual rationality considerations are sufficient to guarantee that individuals will learn to coordinate. This question is central in any discussion of whether social phenomena (read: conventions) can be explained in terms of a purely individualistic approach. We argue that the positive answers to this general question that have been obtained in some recent work require assumptions which incorporate some convention. This conclusion may be seen as supporting the viewpoint of institutional individualism in contrast to psychological individualism.     

我国企业学习取向的初步研究

组织学习取向的研究有助于理解和改善组织学习过程,从而提升组织学习能力。实证研究得出我国企业有五个学习取向:知识来源、学习效果、学习幅度、学习投入、传播形式。我国企业在各个学习取向上都不太极端,都采取比较折衷的学习方式;但是也存在着比较偏重于内部开发知识、渐进式的学习取向、侧重群体学习的特点。我国企业学习风格可以称之为不断改良型和实践共同体型(community of practice:即非正式的、集体学习实践)。     

Early experiences of mentoring: Design and use of multimedia materials for teaching OR/MS

The MENTOR project, based at the University of Strathclyde, is producing multimedia computer based learning materials with the aim of improving both the effectiveness and the efficiency of teaching Operational Research/Management Science in higher education. The process of development has been carefully designed to encourage ownership of and commitment to the materials amongst lecturing staff in Universities, with the aim of ensuring widespread use. The paper outlines this process of development and design of materials. Experiences in introducing students to the use of these materials as an integrated part of a Management Science class are reported. Feedback from students has been very positive but also indicates the need for ongoing support and direction.     

对学习历史事件法的一种改进

依据组织学习理论,对学习历史事件法进行了改进。由于企业的经验知识不完全等同于隐性知识,学习历史事件法同样不能直接应用于隐性知识的转化,为此,提出了适合隐性知识转化的改进型学习历史事件法。改进充分考虑了隐性知识的特征,并专门对隐性知识和经验知识进行了区分。同时,改进的学习历史事件法充分考虑了企业应用的可操作性,保留了量表的形式。最后,将该方法应用于MIS项目开发中,对新改进的量表进行了定量解析。