Artificial intelligence and knowledge management: questioning the tacit dimension

Knowledge management (KM) has matured to the point that many organisations either believe they have such practices in place or at least understand they are relevant to the knowledge work commonly undertaken in many industries. What is lacking from the literature, however, is a solid foundation for the philosophies underpinning KM and particularly for how tacit knowledge informs the KM space. Research over decades shows tacit knowledge underpins all other forms of knowledge, enabling the interpretation and judicious application of knowledge, leading (at its highest levels) to the concept of wisdom. As an academic discipline, artificial intelligence (AI) was established before KM, has been grounded in the computing discipline for many decades, and is applied broadly in many domains. This paper explores how AI can inform the KM debate. Rather than simply provide examples of AI success stories as applied to KM in practice, it explores the theoretical and practical limitations of AI and KM in unison, providing at the same time a strong epistemological understanding of both disciplines as a means of furthering the knowledge debate, with particular emphasis on the role of tacit knowledge within this jurisdiction.     

Does R&D performance decline with firm size?—A re-examination in terms of elasticity

There have been many previous studies exploring the relationship between R&D performance and firm size; however, to our knowledge, this issue has never been examined in terms of R&D output elasticity. This paper therefore sets out to re-examine the relationship of the two variables using R&D output elasticity as a measure of R&D performance. A total of 126 manufacturing firms, listed on the Taiwan Stock Exchange over the period from 1994 to 2000, are taken as the analytical sample. One practical consideration for choosing these particular firms is the relative abundance of data available for the variables for a longitudinal investigation. The estimates suggest that there is an approximating ‘U-type’ relationship between R&D productivity and firm size. This finding suggests that both large and small firms have higher R&D productivity, and even when the sample is divided into the high-tech and traditional sectors, such a finding still holds. Therefore, in contrast to the prior studies, this study shows that size offers advantage in R&D performance.     

国外IT能力研究的演化路径及热点领域探索

本文用与IT能力有关的23个主题词从Web of Science收集了2 640篇文献记录,利用信息可视化软件citespaceⅡ绘制出文献共被引知识网络图,研读相关文献分析IT能力研究的演化路径并归纳总结其特点;结合主题词共被引图,分析信息技术能力研究领域的研究热点;用涌现的专业术语来确定研究前沿。     

Inter‐firm Migration of Tacit Knowledge: Law and Policy1

Abstract

Much knowledge is diffused by the exchange of property rights in intangibles. But tacit knowledge, not being subject to property rights, is instead diffused by migration of knowledgeable individuals between firms. The law impacts significantly on this diffusion mechanism, in particular those rules that determine the use individuals may make of their tacit knowledge after migration to a different firm. The general principle underlying the relevant law is that individuals are free to migrate with all their tacit knowledge. Nonetheless there are some narrow exceptions to this principle. That these exceptions remain narrow and carefully policed by the courts is important because imposing too many restraints on use of tacit knowledge post‐term would have a negative impact on real innovation.     

Shaping the national system of inter-industry knowledge exchange : Vertical integration, licensing and repeated knowledge transfer in the German plastics industry

We will claim in this paper that it was in particular the above-average propensity to share innovative information with customers and competitors which caused the exceptional international competitiveness of the West German plastics industry including chemical firms, plastics fabricators and machine makers. The system of knowledge exchange of this national cluster was shaped in two main steps. In the first half of the 20th century, cartellization and mergers were first tolerated and then even supported by the German government. It was in this period when German chemical firms formed the vertically integrated I.G. Farben concern which provided an optimal organisational framework to explore the new technological path of plastics. After the breaking up of I.G. Farben the firms of the West German chemical firms had to find new ways to maintain inter-industry technological co-operation in the second half of the 20th century. It turned out that they became aware of both contractual and non-contractual solutions of bundling standard good and information which were often placed somewhere between “market” and “hierarchy”. It seems to be no accident that all these different institutions did primarily encourage knowledge exchange between firms in geographical and cultural proximity. That is why the knowledge exchanging network of the plastics industry described in this paper has been in particular concentrated on German firms. Even so the question is still open whether this localisation is just a curiosity limited to a special industry cluster or part of a broader German system of knowledge exchange.     

“三元”知识的整体平衡运作管理模型——设计与应用分析的基点

知识整体理论的提出为时下的管理思想注入了新的元素,但对这一理论应用研究是未给予充分研究的管理领域。本文依据杨百寅教授提出的感性知识、理性知识和活性知识设计了一个"三元"知识的整体平衡运作管理新模型。在管理领域首次分析了这一模型在人力资源管理、知识管理和战略管理等领域现实应用价值,以期从一个全新的视角掀开并填补其在管理界应用分析的空白。     

论高校英语专业本科基础英语教学误区

在高校英语专业本科教学中,基础英语课程的重要地位毋庸置疑。基础英语教学改革进行了很多年,但效果一直不佳,很大原因在于教师对课程教学存在的误区缺乏清醒认识,教学中无法做到有的放矢。本文详细解析基础英语教学中的三个误区,即偏重教学进度,课堂教师讲解与学生参与比例失调;偏重基础知识掌握,忽视语言基本技能操练及学生思辨能力培养;偏重文章内容学习,忽视理论实际联系及文化信息传达,探究现存教学问题解决方法,从而更好地提高基础英语教学质量。     

Deriving kernels from generalized Dirichlet mixture models and applications

In the last few years hybrid generative discriminative approaches have received increasing attention and their capabilities have been demonstrated by several applications in different domains. Hybrid approaches allow the incorporation of prior knowledge about the nature of the data to classify. Past work on hybrid approaches has focused on Gaussian data, however, and less attention has been given to other kinds of non-Gaussian data which appear in many applications. In this article we introduce a class of generative kernels based on finite mixture models for non-Gaussian data classification. This particular class is based on the generalized Dirichlet distribution which have been shown to be effective to model this kind of data. We demonstrate the efficacy of the proposed framework on two challenging applications namely object detection and content-based image classification via the integration of color and spatial information.     

Knowledge space oddity: How to increase the intensity and relevance of the technological progress of European regions

This work contributes to previous research on the relationship between specific features of a regional knowledge space and the technological progress of the region. In particular, the main element of originality of this work is to have singled out the determinants of the technological progress intensity and relevance. We acknowledge the importance of knowledge assets for new knowledge production, and we identify path-dependent processes that allow a region to become increasingly competitive in terms of innovation potential. In particular, adopting an evolutionary view of regional development, we describe the regional knowledge space through four crucial characteristics: 1) technological knowledge base, 2) technological cumulativeness, 3) technological diversification, and 4) technological relatedness. We then measure to what extent each of the knowledge space’s characteristics differently affects the technological progress intensity and relevance of the region. A longitudinal study of 269 European regions over the period 1996–2012 was organized using data from REGPAT and Eurostat databases. Results show that technological relatedness affects positively both the intensity and relevance of the technological progress of European regions and that the other components of the knowledge space show a different impact on the two features of the technological progress. Finally, implications for EU policies supporting and stimulating regional technological progress are discussed.     

Exploiting prior knowledge in compressed sensing to design robust systems for endoscopy image recovery

In this work, we investigate compressed sensing (CS) techniques based on the exploitation of prior knowledge to support telemedicine. In particular, prior knowledge is obtained by computing the probability of appearance of non-zero elements in each row of a sparse matrix, which is then employed in sensing matrix design and recovery algorithms for CS systems. A robust sensing matrix is designed by jointly reducing the average mutual coherence and the projection of the sparse representation error. A Probability-Driven Normalized Iterative Hard Thresholding (PD-NIHT) algorithm is developed as the recovery method, which also exploits the prior knowledge of the probability of appearance of non-zero elements and can bring performance benefits. Simulations for synthetic data and different organs of endoscopy image are carried out, where the proposed sensing matrix and PD-NIHT algorithm achieve a better performance than previously reported algorithms.     

企业信息资源开发与利用中的问题及影响因素分析

本文叙述了知识经济时代企业信息资源的特点，指出了当前企业信息资源开发与利用过程中出现的问题，并对产生这些问题的影响因素进行了进一步分析。     

1998-2015:中国广告学研究热点、趋势及网络

研究热点反映出某一学科或领域的研究行为在特定时期的偏好，这种偏好的出现与那个“当下”的历史整体性紧密相关。本文采用文献计量学方法，选择CSSCI数据库中1998—2015年间收录的广告学论文为研究对象，在Citespace 软件辅助下绘制关键词共现图谱、时区知识演化视图。从30个高频关键词中筛选出6个高中介中心度和强突现的词汇，据此分析我国该阶段广告学科的研究热点和趋势。同时，相关学者与文献介入到以上关键词盛行的社会和历史现场，使得广告学研究活动与宏观社会历史背景发生关联。研究结果表明，由特定社会情境引发的广告业界前沿议题直接影响了学界的研究热点及偏向。而从更为广泛的意义上说，广告学研究重应用、轻理论的状况没有发生根本性转变。     

Entry, exit and knowledge: evidence from a cluster in the info-communications industry

The process by which knowledge is created, accumulated and eventually destroyed appears crucial to many industrial dynamics patterns, since it shapes the profile of evolution of industries by favouring the entry of new companies, the co-existence of incumbents and new entrants and, eventually, their selective or joint exit over time. Though problematic, and all too often neglected, the connection between two nodes of interest, Industrial Dynamics on the one hand, and Knowledge Dynamics on the other hand, thus appears as a promising field of research. On the basis of a case study in the info-communications industry, we start by emphasizing that this field of research has direct importance at the empirical level. Knowledge dynamics can create specific models of evolution among firms at the local level, such as non-shakeout patterns within the cluster, which significantly differ from more global patterns of evolution in the info-communications industry, now generally oriented towards trends of decline and bust. We further argue in favour of the development of Knowledge-Based Industrial Dynamics, an approach that lies at the interface of industry and knowledge dynamics, and which can explain how a cluster may decrease the barriers to knowledge of clustered companies and, further, create a specific knowledge dynamics that is able to shape the industrial dynamics. Finally, we document how this process of knowledge dynamics was collectively implemented in our case study on the info-communications cluster and decompose the mechanisms that led to a local non-shakeout pattern of industrial dynamics. We conclude with some remarks on the policy implications.     

Science policy: two views from two decades

Science policy, as the theme appears in Prometheus over the last 20 years, has been represented by discussions of industrial competitiveness. Many comparative articles have appeared under this theme, as well as evaluations of policies aimed at innovation. By the mid‐1980s, articles in Prometheus were tracing the emergence of the knowledge economy, with some of its associated issues. The issue of human resources for the knowledge economy has received scant attention, however, but Prometheus authors have discussed public participation in science policymaking and setting priorities. Finally, authors have noted and analyzed the closer management of Australian science to direct it toward economic ends. Overall, Prometheus has tracked the dominant themes of science policy in other OECD countries well, and also given space to issues that are less prominent but nonetheless important.     

Querying the French yellow pages: Natural language access to the directory

ERLI was asked by the French TELECOM to develop a specific system to query the professional headings of the French Yellow Pages directory. Approximately 4 million end users now have access (via their “Minitel” terminals) to some 6 million professionals registered under 2500 different headings. (A second application has also been developed using a similar system: the Minitel Applications Directory, which gives information on all the available applications in the Minitel network.)Although the retrieval of a heading is a necessary step in accessing data, it is of no real interest to the user, who wishes only to retrieve the phone number of a given professional or tradesperson.The general aims of the Natural Language System (NLS) are to facilitate access to headings by intelligent query processing (or even to bypass completely the necessity of choosing between headings).This is done through: • The association of a specific knowledge base to the list of headings, • The construction of a “grammar” ensuring a consistent interpretation of the queries.ERLI's system is as an alternative to the existing one, which is based on a key-word indexing technique. The weaknesses and insufficiencies of such a technique are well known, especially in this context, where queries are expressed by unqualified users, who are unfamiliar with the data (i.e., the headings of the directory).Finally, it is important to note that the NLS was developed with regard to industrial considerations (in particular, the minimizing of the average processing time per query). The system is not a prototype. Extensive on-side testing is scheduled to begin in July 1988 and a complete installation will be carried out at the end of the year.     

Using the taxonomy of cognitive learning to model online searching

In this research, we investigated whether a learning process has unique information searching characteristics. The results of this research show that information searching is a learning process with unique searching characteristics specific to particular learning levels. In a laboratory experiment, we studied the searching characteristics of 72 participants engaged in 426 searching tasks. We classified the searching tasks according to Anderson and Krathwohl’s taxonomy of the cognitive learning domain. Research results indicate that applying and analyzing, the middle two of the six categories, generally take the most searching effort in terms of queries per session, topics searched per session, and total time searching. Interestingly, the lowest two learning categories, remembering and understanding, exhibit searching characteristics similar to the highest order learning categories of evaluating and creating. Our results suggest the view of Web searchers having simple information needs may be incorrect. Instead, we discovered that users applied simple searching expressions to support their higher-level information needs. It appears that searchers rely primarily on their internal knowledge for evaluating and creating information needs, using search primarily for fact checking and verification. Overall, results indicate that a learning theory may better describe the information searching process than more commonly used paradigms of decision making or problem solving. The learning style of the searcher does have some moderating effect on exhibited searching characteristics. The implication of this research is that rather than solely addressing a searcher’s expressed information need, searching systems can also address the underlying learning need of the user.     

基于知识根植性视角的联盟协作创新研究

联盟协作创新,已经引起研究者们的广泛关注并从不同角度,运用不同方法作了分析研究．在此,从知识根植性的视角,采用结构方程模型的方法构建理论模型,对知识根植性的影响变量进行系统分析,并明确了战略联盟中知识根植性对协作创新中的作用及中间调节变量的影响．     

University spillovers and new firm location

This paper examines the impact of locational choice as a firm strategy to access knowledge spillovers from universities. Based on a large dataset of publicly listed, high-technology startup firms in Germany, we test the proposition that proximity to the university is shaped by different spillover mechanisms—research and human capital—and by different types of knowledge spillovers—natural sciences and social sciences. The results suggest that spillover mechanisms as well as spillover types are heterogeneous. In particular, the evidence suggests that new knowledge and technological-based firms have a high propensity to locate close to universities, presumably in order to access knowledge spillovers. However, the exact role that geographic proximity plays is shaped by the two factors examined in this paper—the particular knowledge context, and the specific type of spillover mechanism.     

Learning capability: the effect of existing knowledge on learning

It has been observed that different people learn the same things in different ways – increasing their knowledge of the subject/domain uniquely. One plausible reason for this disparity in learning is the difference in the existing personal knowledge held in the particular area in which the knowledge increase happens. To understand this further, in this paper knowledge is modelled as a ‘system of cognitive schemata’, and knowledge increase as a process in this system; the effect of existing personal knowledge on knowledge increase is ‘the Learning Capability’. Learning Capability is obtained in form of a function, although it is merely a representation making use of mathematical symbolism, not a calculable entity. The examination of the function tells us about the nature of learning capability. However, existing knowledge is only one factor affecting knowledge increase and thus one component of a more general model, which might additionally include talent, learning willingness, and attention.     

基于自主创新的组织知识创造机制研究

近年来,知识的研究已经成为学术界关注的热点,许多学者从不同的视角做了大量的研究。本文尝试从自主创新的角度,运用组织学习机制揭示组织知识创造过程的内在机理,构造了自主创新与组织知识创造的关系模型,以揭示二者的关系,为企业进行知识创造活动提供一种思路。