Rethinking the multi-level perspective of technological transitions

In recent years numerous articles have been published which advocate a multi-level perspective (MLP) for the analysis of long-term technological transitions. This paper reviews current transitions research and considers the limitations of the MLP which need to be addressed to enhance understanding of processes of innovation affecting the transformation of technology and society. The paper suggests ways in which the MLP may be effectively rethought, based on more thoroughgoing application of a co-evolutionary concept of technological transitions.     

Corporate governance and technological dynamism of Chinese firms in mobile telecommunications: A quantitative study

This paper sets out two frameworks, one for measuring static and dynamic technological capability in developing countries, one for predicting the effects on this of finance and corporate governance characteristics, and applies them together to Chinese mobile telecommunications manufacturing. Hypotheses on the effect of access to finance, ownership type and other corporate governance factors on capability are generated and tested on survey data for this industry. It is found that ownership type matters, but government's influence over management selection, matters more. Semi-privatised firms with arms-length relationships to government are most dynamic.     

Close to you? Bias and precision in patent-based measures of technological proximity

Patent data have been widely used in research to characterize firms’ locations in technological or knowledge space, as well as the proximities among firms. Researchers have measured firms’ technological or knowledge proximities with a variety of measures based on patent data, including Euclidean distances (using the technological classifications listed on patents), and overlap in cited patents. Often research has employed only the first listed patent classification in measures of proximities. We explore the effects of using the first listed patent class as well as other methods to measure proximities. We point out that measures of proximity based on small numbers of patents are imprecisely measured random variables. Measures computed on samples with few patents or a single patent class generate both biased and imprecise measures of proximity. We discuss the implications of this for typical research questions employing measures of proximity, and explore the effects of larger sample sizes and coarser patent class breakdowns in mitigating these problems. Where possible, we suggest that researchers increase their sample sizes by aggregating years or using all of the listed patent classes on a patent, rather than just the first.     

从知识地图到数字地球——谈人类信息基础环境的演变

人类社会信息基础环境的每一次发展 ,都辩证地促进了人类社会及其信息基础设施的良性循环和发展。从“知识地图”到“数字地球” ,本质地昭示出人类信息不断朝着“有序化”和“序变能力”双向递进发展 ,数字化、网络化、智能性和虚拟化是其物化的技术保障。参考文献 12。     

Predictors of Downsizing in the U.S. Local Telephone Industry

Present U.S. local exchange employment is less than half of what it was in 1981. This study tests several alternative explanations from labor economics, industrial organization, and political economy for employment reductions by U.S. local telephone companies. It evaluates the relative strength of the relationship between each explanatory factor and employment change. The contributions of six potential explanatory factors (wages, sales, technological change, competition, productivity, and profit rate) were investigated. Regression equation models were formulated and tested using crosssectional time-series data on 50 local carriers who provided 90% of the service between 1988 and 1995. We found that digitalization and productivity increases were the most important factors in explaining employment reductions by firms. Wage increases and computerization were significant sources for employment reduction only in the short term.     

科技术语属性抽取方法研究*

使用共现分析的方法从术语定义抽取术语属性，然后使用对应分析的方法对科技术语和术语属性之间的关系进行分析，并使用图形作为表达方式。最后利用市场营销学科领域的科技文献进行实证研究，对市场营销的概念进行深入挖掘，发现市场营销领域学科研究重点和研究内容等有价值的信息。     

基于二级嵌套CES生产函数的工业企业创新效度研究——基于江苏省电子信息和新材料行业数据

对传统CES生产函数进行改进,构建三种二级嵌套CES生产函数,针对江苏省两大主导产业——电子信息、新材料进行创新效度评估。研究表明,对于电子信息行业,(LS)K嵌套方式的拟合度最好,且更倾向于"开放式创新"模式;对于新材料行业,(SK)L嵌套方式的拟合度最好,且更倾向于"封闭式创新"模式。最终,根据拟合结果并结合行业特征进行综合分析,给出针对性建议。     

Understanding the topic evolution of scientific literatures like an evolving city: Using Google Word2Vec model and spatial autocorrelation analysis

Topic evolution has been described by many approaches from a macro level to a detail level, by extracting topic dynamics from text in literature and other media types. However, why the evolution happens is less studied. In this paper, we focus on whether and how the keyword semantics can invoke or affect the topic evolution. We assume that the semantic relatedness among the keywords can affect topic popularity during literature surveying and citing process, thus invoking evolution. However, the assumption is needed to be confirmed in an approach that fully considers the semantic interactions among topics. Traditional topic evolution analyses in scientometric domains cannot provide such support because of using limited semantic meanings. To address this problem, we apply the Google Word2Vec, a deep learning language model, to enhance the keywords with more complete semantic information. We further develop the semantic space as an urban geographic space. We analyze the topic evolution geographically using the measures of spatial autocorrelation, as if keywords are the changing lands in an evolving city. The keyword citations (keyword citation counts one when the paper containing this keyword obtains a citation) are used as an indicator of keyword popularity. Using the bibliographical datasets of the geographical natural hazard field, experimental results demonstrate that in some local areas, the popularity of keywords is affecting that of the surrounding keywords. However, there are no significant impacts on the evolution of all keywords. The spatial autocorrelation analysis identifies the interaction patterns (including High-High leading, High-Low suppressing) among the keywords in local areas. This approach can be regarded as an analyzing framework borrowed from geospatial modeling. Moreover, the prediction results in local areas are demonstrated to be more accurate if considering the spatial autocorrelations.     

A knowledge-based semantic framework for query expansion

Searching for relevant material that satisfies the information need of a user, within a large document collection is a critical activity for web search engines. Query Expansion techniques are widely used by search engines for the disambiguation of user’s information need and for improving the information retrieval (IR) performance. Knowledge-based, corpus-based and relevance feedback, are the main QE techniques, that employ different approaches for expanding the user query with synonyms of the search terms (word synonymy) in order to bring more relevant documents and for filtering documents that contain search terms but with a different meaning (also known as word polysemy problem) than the user intended. This work, surveys existing query expansion techniques, highlights their strengths and limitations and introduces a new method that combines the power of knowledge-based or corpus-based techniques with that of relevance feedback. Experimental evaluation on three information retrieval benchmark datasets shows that the application of knowledge or corpus-based query expansion techniques on the results of the relevance feedback step improves the information retrieval performance, with knowledge-based techniques providing significantly better results than their simple relevance feedback alternatives in all sets.     

应用TPI系统建设特色型数字图书馆

以某科技情报知识仓库为例介绍了如何应用TPI系统建设特色型的数字图书馆,为图书馆及科技情报界建设具有单位特色的数字图书馆提供了参考。