How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

The knowledge-creating company : how Japanese companies create the dynamics of innovation

2 1 The innovative transport systems and the CityMobil project 10 1.1 The research questions 10 2 The state of art in the field of automatic transport systems 12 2.1 Case studies and demand studies for innovative transport systems 12 3 The design and implementation of surveys 14 3.1 Definition of experimental design 14 3.2 Questionnaire design and delivery 16 3.3 First analyses on the collected sample 18 4 Calibration of Logit Multionomial demand models 21 4.1 Methodology 21 4.2 Calibration of the “full” model. 22 4.3 Calibration of the “final” model 24 4.4 The demand analysis through the final Multinomial Logit model 25 5 The analysis of interaction between the demand and socioeconomic attributes 31 5.1 Methodology 31 5.2 Application of Mixed Logit models to the demand 31 5.3 Analysis of the interactions between demand and socioeconomic attributes through Mixed Logit models 32 5.4 Mixed Logit model and interaction between age and the demand for the CTS 38 5.5 Demand analysis with Mixed Logit model 39 6 Final analyses and conclusions 45 6.1 Comparison between the results of the analyses 45 6.2 Conclusions 48 6.3 Answers to the research questions and future developments 52

The European commission

bibliometrix: An R-tool for comprehensive science mapping analysis

Evaluating scientific quality is a notoriously difficult problem which has no standard solution. Ideally, published scientific results should be scrutinised by true experts in the field and given scores for quality and quantity according to established rules. In practice, however, what is called peer review is usually performed by committees with general competence rather than with the specialist's insight that is needed to assess primary research data. Committees tend, therefore, to resort to secondary criteria like crude publication counts, journal prestige, the reputation of authors and institutions, and estimated importance and relevance of the research field,1 making peer review as much of a lottery as of a rational process.2 3

On this background, it is hardly surprising that alternative methods for evaluating research are being sought, such as citation rates and journal impact factors, which seem to be quantitative and objective indicators directly related to published science. The citation data are obtained from a database produced by the Institute for Scientific Information (ISI) in Philadelphia, which continuously records scientific citations as represented by the reference lists of articles from a large number of the world's scientific journals. The references are rearranged in the database to show how many times each publication has been cited within a certain period, and by whom, and the results are published as the Science Citation Index (SCI) . On the basis of the Science Citation Index and authors' publication lists, the annual citation rate of papers by a scientific author or research group can thus be calculated. Similarly, the citation rate of a scientific journal—known as the journal impact factor—can be calculated as the mean citation rate of all the articles contained in the journal.4 Journal impact factors, which are published annually in SCI Journal Citation Reports , are widely regarded as …

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Why the impact factor of journals should not be used for evaluating research

The co-authorship network of scientists represents a prototype of complex evolving networks. In addition, it o8ers one of the most extensive database to date on social networks. By mapping the electronic database containing all relevant journals in mathematics and neuro-science for an 8-year period (1991–98), we infer the dynamic and the structural mechanisms that govern the evolution and topology of this complex system. Three complementary approaches allow us to obtain a detailed characterization. First, empirical measurements allow us to uncover the topological measures that characterize the network at a given moment, as well as the time evolution of these quantities. The results indicate that the network is scale-free, and that the network evolution is governed by preferential attachment, a8ecting both internal and external links. However, in contrast with most model predictions the average degree increases in time, and the node separation decreases. Second, we propose a simple model that captures the network’s time evolution. In some limits the model can be solved analytically, predicting a two-regime scaling in agreement with the measurements. Third, numerical simulations are used to uncover the behavior of quantities that could not be predicted analytically. The combined numerical and analytical results underline the important role internal links play in determining the observed scaling behavior and network topology. The results and methodologies developed in the context of the co-authorship network could be useful for a systematic study of other complex evolving networks as well, such as the world wide web, Internet, or other social networks. c

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Evolution of the social network of scientific collaborations

The main objective of this study is the elaboration of national characteristics in international scientific co-authorship relations. An attempt is made to find statistical evidence of symmetry and asymmetry in co-publication links, of the relation between international co-authorship and both national research profiles and citation impact. Four basic types can be distinguished in the relative specialisation of domestic and internationally co-authored publications of 50 most active countries in 1995/96 concerning the significance of the difference between the two profiles. Co-publication maps reveal structural changes in international co-authorship links in the last decade. Besides stable links and coherent clusters, new nodes and links have also been found. Not all links between individual countries are symmetric. Specific (unidirectional) co-authorship affinity could also be detected in several countries. As expected, international co-authorship, on an average, results in publications with higher citation rates than purely domestic papers. However, the influence of international collaboration on the national citation impact varies considerably between the countries (and within one individual country between fields). In some cases there is, however, no citation advantage for one or even for both partners.

National characteristics in international scientific co-authorship relations

Co-authorship is one of the most tangible and well documented forms of scientific collaboration Almost every aspect of scientific collaboration networks can be reliably tracked by analysing co-authorship networks by bibliometric methods In the present study, scientific collaboration is considered both at individual and national levels, with special focus given to multinational collaborations Both literature data and original results witnessed a dramatic quantitative and structural change in the last decades of the 20th century The changes, to great extent, can be attributed to the universal tendencies of globalisation and the political restructuring of Europe The standards and, particularly, the visibility of scientific research, as a rule, benefit from the ever increasing level of collaboration, but the profits do not come automatically This fact underlines the necessity of a regular quantitative monitoring of inputs and outcomes, ie, bibliometric surveys

Analysing Scientific Networks Through Co-Authorship

We suggest that a h-type index - equal to h if you have published h papers, each of which has at least h citations - would be a useful supplement to journal impact factors.

A Hirsch-type index for journals

Handbook of Quantitative Science and Technology Research

The Impact Factor introduced by Eugene Garfield is a fundamental citation-based measure for significance and performance of scientific journals. It is perhaps the most popular bibliometric product used in bibliometrics itself, as well as outside the scientific community. First, a concise review of the background and history of the ISI impact factor and the basic ideas underlying it are given. A cross-citation matrix is used to visualise the construction of the Impact Factor and several related journal citation measures.Both strengths and flaws of the impact factor are discussed. Several attempts made by different authors to introduce more sophisticated journal citation measures and the reasons why many indicators aiming at a correction of methodological limitations of the Impact Factor were not successful are described. The next section is devoted to the analysis of basic technical and methodological aspects. In this context, the most important sources of possible biases and distortions for calculation and use of journal citation measures are studied. Thereafter, main characteristics of application contexts are summarised. The last section is concerned with questions of statistical reliability of journal citation measures. It is shown that in contrast to a common misbelief statistical methods can be applied to discrete "skewed" distributions, and that the statistical reliability of these statistics can be used as a basis for application of journal impact measures in comparative analyses. Finally, the question of sufficiency or insufficiency of a single, howsoever complex measure for characterising the citation impact of scientific journals is discussed.

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Wolfgang Glänzel

Papers

National characteristics in international scientific co-authorship relations

Analysing Scientific Networks Through Co-Authorship

A Hirsch-type index for journals

Handbook of Quantitative Science and Technology Research

Journal impact measures in bibliometric research