The influence of informal social media practices on knowledge sharing and work processes within organizations

Contemporary information technologies such as social media have invigorated the way knowledge is shared within organizations to the extent that we have to rethink and reassess our understanding of the role and influence of technology in organizational processes and knowledge sharing. This paper uses the strategy as practice lens guided by the interpretivist philosophy to understand the influence of informal social media practices on knowledge sharing and work processes within an organization. The paper uses empirical evidence from the case study of a telecom organization in Tanzania to gain theoretical insight into informal social media practices and knowledge sharing. This research contributes to the Information Systems (IS) literature by asserting that organizational processes are achieved by mundane knowledge sharing mediated by informal social media use within the organization. Also, the study contributes to IS literature by highlighting how emerging informal practices are essential to daily processes within organizations.     

KRL_MLCCL: Multi-label classification based on contrastive learning for knowledge representation learning under open world

Knowledge representation learning(KRL) transforms knowledge graph(KG) from symbol space to vector space. However, KRL under open world assumption(OWA) is deeply trapped in the dilemma of lack of labels due to difficulty or high cost in labeling. To address this problem, we propose KRL_MLCCL:Multi-Label Classification based on Contrastive Learning(CL) Knowledge Representation Learning method. Specifically, (1)we formalize a problem of solving true knowledge graph objects(KGOs) matchings(KGOMs) under the OWA in the original KGOM sample space(KGOMSS)(multi-label classification with one known true matching(positive-example)). (2)we solve the problem in the new KGOMSS, generated through augmenting the true matching according to CL’s idea(multi-label classification with multiple known true matching). (3)we score the true matchings based on hermitian inner product and softmax and minimize a negative logarithm likelihood loss to establish KRL_MLCCL model preliminarily. (4)we migrate the learned model back to the original KGOMSS to solve the true matching problem. We creatively design and apply a positive-example augmentation way of CL enabling KRL_MLCCL with back migration ability: “pulling KGOs in true matching close and pushing KGOs in false matching away”, which helps KRL out of the labels shortage dilemma faced in modeling. We also propose a negative-example noise filtering algorithm to enhance this ability. The open world entity prediction(OWEP) experiment on dataset FB15K-237-OWE shows that the performance of KRL_MLCCL is increased by 3% in Hits@10 and 1.32% in MRR compared with the state-of-the-art in the baselines. The experiments of OWEP in KG also show that KRL_MLCCL has a better back migration ability.     

The role of knowledge base homogeneity in learning from strategic alliances

Strategic alliances are important channels for interfirm learning, especially for small firms that are resource constrained. Of the several alliance attributes, technological distance between partners (measured as the distance between partners’ innovative outcomes) is shown to have a significant influence on the learning benefits from strategic alliances. Drawing upon the theory of recombination, our study argues that the influence of technological distance on learning is best understood by not only measuring the distance between innovative outcomes, but by also taking into consideration the knowledge elements underlying the innovative outcomes. We develop a concept of knowledge base homogeneity that captures the extent to which the innovative outcomes of partnering firms draw upon similar sets of knowledge elements. Using patent and alliance data from 201 small biotechnology firms during the period 1996–2010, we confirm that the technological distance has an inverted u-shaped relationship on interfirm learning. We further demonstrate that this u-shaped relationship is moderated by the knowledge base homogeneity between partners, such that benefits of technological distance are enhanced and the costs of technological distance are mitigated when the knowledge base homogeneity between alliance partners is high. The results have important implications for interfirm learning, especially in the context of small firms that are limited in their knowledge stocks.     

ARL: An adaptive reinforcement learning framework for complex question answering over knowledge base

Recently, reinforcement learning (RL)-based methods have achieved remarkable progress in both effectiveness and interpretability for complex question answering over knowledge base (KBQA). However, existing RL-based methods share a common limitation: the agent is usually misled by aimless exploration, as well as sparse and delayed rewards, leading to a large number of spurious relation paths. To address this issue, a new adaptive reinforcement learning (ARL) framework is proposed to learn a better and interpretable model for complex KBQA. First, instead of using a random walk agent, an adaptive path generator is developed with three atomic operations to sequentially generate the relation paths until the agent reaches the target entity. Second, a semantic policy network is presented with both character-level and sentence-level information to better guide the agent. Finally, a new reward function is introduced by considering both the relation paths and the target entity to alleviate sparse and delayed rewards. The empirical results on five benchmark datasets show that our model is more effective than state-of-the-art approaches. Compared with the strong baseline model SRN, the proposed model achieves performance improvements of 23.7% on MetaQA-3 using the metric Hits@1.     

基于顿悟学习的Q-SECI模型及其应用研究

本文借鉴顿悟学习的心理学成果和"量子学习"模型的概念,提出应结合华人企业和科研机构普遍存在的顿悟文化对SECI模型进行改进,构建了基于顿悟学习的量子知识创造(Q-SECI)模型,并定义了知识创造力和知识集成力分析该模型知识创造螺旋跃迁机制。在此理论基础上,本文通过对知识管理实证案例的探讨,尝试提出一种基于"实践社群"的应用方案来检验Q-SECI模型的合理性。     

Three steps in knowledge communication: the emergence of knowledge transformers

The purpose of this paper is to reexamine the role of gatekeeper in R&D organizations through the data collected from a midium-sized machine tool firm. Although the related literature points out (1) information gathering and (2) information transmitting functions as main roles of gatekeeper, this paper further suggests (3) knowledge transforming function that has to be executed within R&D organizations. We will argue that since the latter function often requires distinctive skills that impede information gathering activities, there emerges a three-step flow of communication instead of a two-step flow of communication. We define persons fulfilling this new role as a knowledge transformer, and related testable hypotheses are derived. The latter part of this paper proposes new measuring methods that identify knowledge transformers and test these hypotheses.     

Understanding the formation mechanism of high-quality knowledge in social question and answer communities: A knowledge co-creation perspective

The social question and answer (Q&A) community provides people with an effective tool to obtain high-quality information. From the perspective of reciprocal determinism and value co-creation, this study aims to investigate the formation mechanism of high-quality knowledge in the community. We develop a model to investigate how cognitive factors and community technological factors influence users’ knowledge co-creation behavior, thereby influencing knowledge quality in the community. A survey of 382 knowledge contributors in a social Q&A community shows that knowledge self-efficacy, topic richness, personalized recommendation, and social interactivity have a positive impact on users' knowledge sharing and integration behavior, which subsequently affect the community’s knowledge quality. Moreover, users' ratings moderate the influence of knowledge sharing on knowledge quality. This research demonstrates the synergistic effect of people and technology in knowledge co-creation, thus advances literature about value co-creation and content quality in online communities.     

任务驱动的隐性知识学习研究

针对隐性知识的隐蔽性、非结构化等特点,借鉴经验学习和知识转移理论,从任务视角出发用仿真方法研究了任务分配策略、任务到达速率、不同复杂任务比重对隐性知识学习的作用机制。仿真结果表明,以知识增长为目的的学习策略最有利于隐性知识学习;以当前时间成本最小化为目的的策略会引起原有知识的损失;随机分配策略对隐性知识学习无显著作用。任务到达速率衡量了员工的任务压力,适当增加员工任务压力能够极大地促进隐性知识学习。不同复杂任务的比重通过影响整体任务复杂度而作用于隐性知识学习,且任务复杂度与隐性知识学习之间呈现倒U型关系,无论各种任务之间的比重如何,只要整体任务复杂度维持在适中水平,就可以显著促进隐性知识学习。     

内隐学习理论在公安院校散打教学中的应用研究

公安院校的教学质量和教学效果关系着社会的稳定和发展,如何培养出一批具有高技能素质和合格的人才成为了当前每一位公安院校教师所思考的重点内容。本篇文章主要对内隐学习理论在公安院校散打教学中应用的意义及策略进行分析和研究,以期能够更好的指导学生学习散打技术,提升学生的知识灵活应用水平,为学生未来的成长和发展奠定良好的基础。     

The impact of initial learning experience on digital services usage diffusion: A field study of e-services in Lebanon

The initial learning experience is crucial for understanding digital services adoption and usage diffusion. Using a UTAUTv2 model, we explore the effect of process- and content-oriented knowledge on behavioral intentions to use e-government services. The adoption of e-government systems is lower than desired in general and faces considerable resistance in many developing countries. Scholars suggest that more knowledge and better training are critical to increasing adoption and usage rates. We conducted a survey of 262 citizens in Lebanon to investigate how consumers cope with high and moderate levels of complexity during their initial learning experience with a technology-based product. The results show that a moderate degree of content- and process-oriented knowledge about e-government services during an initial learning experience improves usage habits, performance expectancy, effort expectancy, and facilitating conditions. The challenge for service providers is to understand consumers’ learning experience and coping strategies and to provide mechanisms that make the transition to e-services easier and more intuitive. This can be achieved by developing new infrastructure for e-services to facilitate easier access to e-government websites and to improve site performance. Marketers can also develop more effective communications that offer easy and flexible specific steps for using the portal.     

基于组织学习的知识动态传播模型

组织为了保持其竞争优势和创新能力必须开展组织学习。组织学习首先发生在非正式团体中，通过非正式团体中个体间的知识传播，最后传播到正式团体并最终成为组织知识。本文在分析并提出必要假设基础上，给出一个数学模型，探讨了知识传播的高峰期及其影响因素，为组织管理者促进知识的高效传播提供理论依据。     

A framework of industrial knowledge spillovers in big-science centers

We employed the grounded theory method to construct a framework describing the distinctive mechanisms through which big-science centers generate industrial knowledge spillovers in the economy. Our focus is on large-scale big-science installations typically associated with experimental physics. We draw on social network, social capital, and inter-organizational learning theories to examine knowledge spillovers accruing to industrial partner companies in big-science-industry dyads. The context for the study is provided by CERN’s new particle accelerator project, the Large Hadron Collider (LHC). In addition to building a grounded theory framework for the study of industrial knowledge spillovers, our study demonstrates the distinctive potential that big-science centers offer as a source of knowledge spillovers in national innovation systems.     

基于顿悟学习的知识创造模型研究

本文在Nonaka等提出的SEC I模型基础上,借鉴顿悟学习的心理学研究成果,以量子能级跃迁作为知识创造螺旋上升的理论隐喻,构建了基于顿悟心理的量子知识创造模型(Q-SEC I模型),进而通过对知识创造力和知识集成力这两种动力的分析探讨了Q-SEC I模型知识创造螺旋跃迁机制,并运用于企业组织学习的管理实践。     

Knowing in action: Beyond communities of practice

This paper engages with the recent turn in the social sciences towards communities of practice as a driver of learning and knowledge generation across a variety of different working environments. While agreeing with the broad reinstatement of situated social practice in thinking on the dynamics of knowledge capitalism, the paper takes issue with the increasingly homogeneous and instrumentalist use of the term communities of practice to encapsulate ‘knowing in action’. On the basis of an extensive review of the available literature, the paper argues for the importance of differentiating between different varieties of knowing in action. The paper notes the differences - in organisation, spatial dynamics, innovation outcomes, and knowledge processes - between four modes: craft or task-based knowing; epistemic or high creativity knowing; professional knowing; and virtual knowing. The proposed typology is used to illustrate the insight gained from such analytical precision, through a discussion of the spatial configuration of knowing in action, long assumed to require spatial proximity. It is shown that spatial and relational proximity - which can be struck at a distance - should not be treated as one and the same.     

The role of knowledge codification in the emergence of consensus under uncertainty: empirical analysis and policy implications

The aim of the article is to empirically analyse the main factors, which allow the emergence of consensus. Moreover, we raise the question of the nature of the codified process involved which seems to be too reducing to promote knowledge flows within the community and, therefore, to contribute to learning processes and better choices about the future. Our analysis relies on a prospective investigation based on a Delphi type study carried out by BETA in 1994.     

科研机构学科带头人绩效考核办法与实践

根据相关绩效管理理论,首先探讨科研机构中学科带头人绩效考核的原则和主要指标;其次根据主要考核指标和实际情况,采用定性和定量相结合的办法从科研业绩、管理能力和发展前景三类指标建立了对学科带头人评价考核的多维模型;然后,通过使用考核模型从投入、产出、时间、实力、声誉和士气等细化因素对具体实例进行了实践检验,收到了良好的效果,从而指导进行了对学科带头人的年度考核评价工作;最后,提出了指导今后绩效考核评价工作的建议。     

Knowledge map creation and maintenance for virtual communities of practice

This paper proposes a knowledge map management system to facilitate knowledge management in virtual communities of practice. To realize the proposed knowledge map management, we develop knowledge map creation and maintenance functions by utilizing information retrieval and data mining techniques. The knowledge maps created respectively from the documents of the teachers’ professional community, SCTNet, and the thesis repository at Taiwan’s National Central Library, are evaluated by experts of these two domains. Knowledge maps generated by the system are accepted by domain experts from the evaluation since the degree of their modification of the automatically created knowledge maps is proportionally small. The knowledge structure representing the categories of community documents maintains its high purity, diversity, specificity, and structure adaptation by using the knowledge map maintenance function with limited computational cost. Thus, the knowledge map creation and maintenance mechanisms developed in this research enable the dynamic knowledge management of communities of practice on the Internet.     

Innovating strategically in information and knowledge management: Applications of organizational behavior theory

A business school declares its strategy as becoming a leading European institution. As main vehicle for achieving recognition is the implementation of a top-down strategy naming five academic fields as key – (a) finance, (b) economics, (c) marketing, (d) law, accounting, and auditing, and (e) organizational behavior (OB). Top management allocates resources for research, academic activities, and positions to these five strategically chosen areas. Academic areas that are not strategically named must generate their own income through educational programs and research grants. Can OB serve as the platform to ensure the survival of IS/KMS? In our analysis, we found no other business school formulating a strategy along these lines; dominating strategic themes are internationalization, research excellence, and student environment. No academic field is singled out as strategic. We argue that selecting a few academic areas as a strategy is dysfunctional. We also found that OB is not very actively employed in research, be it positioning, theory, research model, analysis, or discussion. Hence, we do not find that OB offers any theorizing help to IS/KMS – this in contrast to innovation and change theories, for which we propose an framework as a means of defining IS/KMS research projects.     

创业知识视角下创业学习对创业成长的影响研究

通过构建创业知识、创业学习和创业成长间的理论关系模型,基于288份全国大学生创业实践样本数据,使用结构方程模型验证了创业知识、创业学习以及创业成长之间的关系。研究表明：相比创业默会知识,创业确定知识对创业成长的直接影响作用更大;创业学习在创业知识影响创业成长中发挥不完全中介作用,在创业默会知识影响创业成长中发挥的不完全中介效应更为明显;默会知识会通过创业学习转化为确定性知识从而间接影响创业绩效。