International collaboration development in nanotechnology: a perspective of patent network analysis

International collaboration has played an important role in the development of nanotechnology. Patents encompass valuable technological information and collaborative efforts. Thus, this paper examines international collaboration development in nanotechnology using patent network analysis. The results show that the number of international collaboration nanotechnology patents has increased steadily and the proportion of them of total nanotechnology patents has likewise exhibited an upward trend. USA has always been the most influential participant with largest number of international collaboration patents. Asian countries/regions have shown an obvious increase in the number of international collaboration patents. By contrast, there have shown a generally decline in European countries. More and more countries have become actively engaged in international collaboration in nanotechnology with increasingly closer relationships. Two styles of international collaboration exit: while USA, Germany, UK and Japan collaborate with a wide range of countries/regions; Spain, Israel, Russia, Singapore and Taiwan are more selective in their collaboration partners. Though International collaboration has yet to find global significance in terms of patent citation impacts, it has nevertheless been incremental in improving patent citation impacts for most of the top 20 countries/regions since 2004.     

Exploring and visualizing spatial-temporal evolution of patent collaboration networks: A case of China's intelligent manufacturing equipment industry

With the integration of intelligent manufacturing (IM) technology and the manufacturing industry, the intelligent manufacturing equipment industry (IMEI) has become the focus of a new round of industrial revolution. This integration has led to a new revolution in the manufacturing industry and is key to transforming China into a manufacturing country with international competitiveness. However, China's IMEI is in the development stage, thus presenting a major challenge to it becoming a competitive core industry. Therefore, there is an urgent need to explore the IMEI patent collaboration network and analyze its evolutionary characteristics, which can improve not only the innovation ability of network organizations but also the overall competitiveness of the IMEI. This study employs social network analysis (SNA) to study the evolution of the patent collaboration network of China's IMEI. The results show that the number of co-patents for the IMEI field in China has obvious stage characteristics, the collaborative innovation patterns adopted by different provinces vary, and the State Grid has a strong influence on the network. The scale of the patent collaboration network is gradually expanding, exhibiting a “small-world” structure. Jiangsu mainly innovates through intra-provincial collaboration. Provinces such as Beijing, Guangdong and Shandong are more inclined to inter-provincial collaboration.     

Dynamic patterns of technology collaboration: a case study of the Chinese automobile industry, 1985–2010

To investigate patterns of technology collaboration within the Chinese automobile industry, this study employs a unique dataset of patent applications that reveal a record of 64,938 collaborative relations in the industry during the period from 1985 to 2010. Our results indicate that over 60 % of the total collaborations were conducted after China entered the WTO. The invention and utility types of patents account for 98 % of the total collaborations throughout the sample period. Using a network analysis method, we find that the key differences between domestic enterprises collaborating with indigenous enterprises (DD collaboration) and with foreign firms (DF collaboration) are in patent types and technology domains. The DF network is also denser and more centralized than the DD network, although the amount of nodes and links of the DD network is greater than that of the DF collaboration network. The analysis and visualization of the collaboration networks and corresponding largest components reveal that a large number of domestic enterprises prefer to collaborate with top global automobile manufacturers. We also find that a number of universities have become key players in the collaborations among industry, universities and research institutes. This study provides a deeper understanding of technology collaborations from various perspectives and also highlights several avenues for future research.     

Research and innovation in South African universities: from the triple helix’s perspective

Different from most prior research studying the influence of networks on scientific knowledge creation by taking on a single social-based perspective, this study offers an integrated frame based upon both social-based and knowledge-based views. This study incorporates quantitative bibliometric methods of analysis and network analysis. Based on 51,972 alternative energy patents in 1998–2012, we build knowledge networks composed of technological classifications and social networks capturing collaborations. Based on patent citation networks, we use citations in every period to calculate researcher’s knowledge creation performance. We hypothesize that centrality of researchers in the knowledge network and their knowledge creation display an inverted-U relationship. What’s more, we propose that this curvilinear relation is moderated by their structural holes and centrality in the collaboration network. Based on the negative binomial model with fixed effects and robust tests, results indicate that (1) locations of the researchers in knowledge network contribute more to knowledge creation when their centrality is moderate, rather than high or low; (2) at a moderate level of knowledge network centrality, the researchers, who occupy more central positions or span more structural holes in collaboration network, will benefit more than the ones who do not. The findings of this research, besides having implications for research on knowledge networks, have implications on scientometric indicators, multiple networks study, and knowledge creation process.     

Extracting knowledge patterns with a social network analysis approach: an alternative methodology for assessing the impact of power inventors

This paper proposes a new, alternative analysis of patent data in order to extract knowledge patterns from inventors’ collaboration networks. Indeed, moving from a basic network analysis, we provide new developments to map and study co-inventorship. The goal of this research is to provide an overall understanding of the dynamics concerning knowledge flows in inventive activities. We show how the network of inventors is, on average, increasing in size: more and more inventors are contributing to technology innovations and they are more connected to each other. We also show to what extent inventors from different countries tend to cooperate with their local peers or internationally. Furthermore, an analysis of the clustering of inventors is carried out to show differences across countries in the structure of inventors’ communities, with a particular focus on the dynamics of collaboration for power inventors (i.e. star inventors).     

Evolving collaboration networks in Scientometrics in 1978–2010: a micro–macro analysis

This paper reports first results on the interplay of different levels of the science system. Specifically, we would like to understand if and how collaborations at the author (micro) level impact collaboration patterns among institutions (meso) and countries (macro). All 2,541 papers (articles, proceedings papers, and reviews) published in the international journal Scientometrics from 1978–2010 are analyzed and visualized across the different levels and the evolving collaboration networks are animated over time. Studying the three levels in isolation we gain a number of insights: (1) USA, Belgium, and England dominated the publications in Scientometrics throughout the 33-year period, while the Netherlands and Spain were the subdominant countries; (2) the number of institutions and authors increased over time, yet the average number of papers per institution grew slowly and the average number of papers per author decreased in recent years; (3) a few key institutions, including Univ Sussex, KHBO, Katholieke Univ Leuven, Hungarian Acad Sci, and Leiden Univ, have a high centrality and betweenness, acting as gatekeepers in the collaboration network; (4) early key authors (Lancaster FW, Braun T, Courtial JP, Narin F, or VanRaan AFJ) have been replaced by current prolific authors (such as Rousseau R or Moed HF). Comparing results across the three levels reveals that results from one level might propagate to the next level, e.g., top rankings of a few key single authors can not only have a major impact on the ranking of their institution but also lead to a dominance of their country at the country level; movement of prolific authors among institutions can lead to major structural changes in the institution networks. To our knowledge, this is the most comprehensive and the only multi-level study of Scientometrics conducted to date.     

Who are the international research collaboration partners for China? A novel data perspective based on NSFC grants

International research collaboration is vital to the success of scientific development of China, and the identification of collaboration partners is the basic unit of collaboration. While many researchers have investigated international research collaboration using publication data, grant data have rarely been used. This paper explores the international research collaboration partners of China from a new data perspective, based on grant data. Using data from the National Natural Science Foundation of China (NSFC) joint grants between China and 75 countries from 2006 to 2016, this study examines the collaboration partners in three aspects: overall collaboration activity, relative research effort, and collaboration groups of countries. Some interesting results are obtained as follows. Among 75 partners, the top 15 account for 95.42% of the total grants, but they are quite uneven in collaborating grant numbers and shares. The USA ranks far ahead of the others with a share of 53.27%, but China maintained a steady, approximately average collaborative effort with it from 2006 to 2016. China shows a growing preference for collaborating with Australia, the Netherlands, and Spain, while the preferences for Japan, Germany, and Sweden are the opposite. The collaborative number of grants among five collaboration groups varies greatly because of different features of constituents’ countries. The G7 and Asia–Pacific both own more than 75% of all the grants, while the BRICS and “The Belt and Road” are relatively weak in research collaboration, but China has maintained a rising trend of collaboration with them over the past 11 years.     

Mapping the evolving patterns of patent assignees’ collaboration networks and identifying the collaboration potential

The purpose of this article is to map the evolving patterns of patent assignees’ collaboration networks and build a latent collaboration index (LCI) model for evaluating the collaboration probability among assignees. The demonstration process was carried on the field of industrial biotechnology (IB) from 2000 to 2010. The results show that the number of assignees in the field of IB grew steadily, while the number of patents decreased slowly year by year after it reached peak in 2002 and 2003. Densification and growth analysis, average degree, density and components analysis showed that the collaboration networks tended to density. Especially the diameter analysis indicated that the IB field had come into a mature mode after finishing the topological transition occurred in about 2002 or 2003. The nodes had degree k followed a power law distribution, which implied a preferential linking feature of the network evolving and thus provided a foundation for link prediction from the aspect of network evolving. Basing on this, two network-related factors had been brought into the LCI model, which were degree and network distance. Their values were positive and negative for link prediction respectively. In addition, types of assignees, geographical distances and topics similarities had also been added into the LCI model. Different types of assignees had also different probabilities to be linked, such as corporations had been collaborated more frequently, while universities ranked lowest based on collaborations. Assignees from the same countries seemed to be likely to collaborate to each other. It have to been noted that the LCI model is flexible that can be adjusted of the factors or their weights according to different subjects, time or data. For instance, the topics similarities between assignees would be removed from the LCI model for link prediction in the field of IB because of the poor inference from topics similarities to collaborations. Actually, many promising pairs of assignees that seemed to have the potential to collaborate to each other according to one or more of these factors have never collaborated. One possible reason might be that collaboration is not popular behaviours among assignees during the process of patent application or maintain. Another reason could be the competitions between assignees. Many a time the promising pairs are competing pairs. Therefore, it was hard to carry out regression analysis basing on those four factors to get usable coefficients set of the four factors. The LCI model could only be used to make qualitative analysis on collaboration potential when it was revised.     

Graph-based models to classify effective collaboration in SME networks

During the last decades, globalisation of goods’ markets and large disequilibrium amongst labour markets in different countries had a remarkable impact on small and medium enterprises – SMEs, which have been for many years the actual engine of industrial development in Europe. An ‘antidote’ to this crisis is the development of more profitable SME networks in the forms of either ‘clusters’, ‘competitiveness poles’, ‘industrial districts’ or ‘scientific parks’. A more strategic approach is needed, that builds upon existing SME aggregations and explores their main strong and weak points, such as to establish a framework for new innovative networks. The goal of this study is to offer a method to analyse the main features of existing SME networks, in order to offer to the network coordination/management committees some key parameters (KP) to evaluate the network composition and potentially to select networks modifications. The study analyses an archive of industrial networks provided by the European project CODESNET and defines different types of networks and their main KP. A further result of the analysis will be the modelling of each network type in terms of a specific graph. Graphs give a more intuitive representation of the network and an easier comprehension of its organisation. In a second stage, by a probabilistic approach, the authors propose an identification procedure to classify existing and new networks.     

Patent statistics as related to the industrial development trend in Sweden in the period 1925–1936—I

This article sets out to use statistics on the number of patent applications as a basis for discussing and explaining the industrial development trend in Sweden during the period 1925–1936 from various standpoints. The following topics are examined: The extent and depth of the Depression; Structural changes; Foreign activity in Swedish trade and industry; and the increase in systematic research by firms. The first two of these topics are examined here in Part I of the article. The second two will be dealt with later in Part II.     

Patent statistics as related to the industrial development trend in Sweden in the period 1925–1936—II

This article sets out to use statistics on the number of patent applications as a basis for discussing and explaining the industrial development trend in Sweden during the period 1925–1936 from various standpoints. The following topics are examined: The extent and depth of the Depression; Structural changes; Foreign activity in Swedish trade and industry; and the increase in systematic research by firms. The first two of these topics were examined in Part I of the article. The second two are dealt with here in Part II.     

Relative visibility of authors’ publications in different information services

This study is to examine the structure, characteristics, and change of a research collaboration network using co-assignee information of joint patents in Korea. The study was conducted in three stages: data collection, network construction, and network analysis. For network analysis, network topological analysis, node centrality analysis, and block modeling were performed in sequence. The analysis results revealed that the network has small-world properties. The results also showed that while government-sponsored research institutes (GRIs) played a role as a hub and bridge in the network in the early 2000s, universities gradually took their place to play a key role as a hub and bridge in the network. In addition, the block modeling analysis indicated that while, in the early 2000s, GRI-centered network density was shown to be high, the network density became concentrated around universities after 2004, and this tendency intensified after 2008. Bearing in mind a lack of empirical studies on inter-organizational research collaboration networks using patent data, this study made an academic contribution by specifically analyzing the structure and change of research collaboration networks by targeting Korea’s major innovative actors. From the policy perspective, it provides important implications for figuring out the effects of university–industry–GRI (UIG) collaboration policies implemented so far, and can be of assistance for making evidence-based policies to build up a more effective UIG collaboration network or establish a new national science and technology innovation system.     

Developing and sustaining new regional industrial paths: investigating the role of ‘outsiders’ and factors shaping long-term trajectories

This article casts light on the development of new regional industrial paths. We explore factors explaining why regional industries with similar early path development trajectories may exhibit diverging outcomes in the longer run and pay particular attention to the role of ‘outsiders’ in the initiation and further development of regional industrial paths. Drawing on a comparative case study of IT industries in Linköping and Karlskrona, two medium-sized Swedish city regions, we find that the inflow of outsiders was an important driver of early path development processes. However, we find that the interplay between regional preconditions and arriving outsiders, and between outsiders and existing actors, substantially shaped the long-term sustainability of the industrial paths in our study. In particular, the role of agency in fostering positive self-reinforcing mechanisms and structure–agency dynamics are highlighted as key factors for understanding how new industrial development paths are unfolding in the longer term.     

The function of ability,benevolence, and integrity-based trust in innovation networks

ABSTRACT

This study contributes to the understanding of how trust based on perceived ability, benevolence, and integrity functions in networks. It adopts a mixed-method approach with quantitative and qualitative data from five Norwegian innovation networks. The study demonstrates how trust based on perceived benevolence, ability, and integrity influences different aspects of network interaction and network outcomes against the background of the network members’ perceptions of risk. Moreover, it finds that these dimensions of trust function differently at the inter-organisational and at the network level. The former level here concerns trust between the organisations in the network, while the latter concerns trust in the network more generally. Benevolence-based trust is identified as particularly salient at both levels for promoting open and honest communication as well as knowledge sharing, enabling both more successful collaboration in general, and more innovation specifically.     

Technological collaboration patterns in solar cell industry based on patent inventors and assignees analysis

This study examines technological collaboration in the solar cell industry using the information of patent assignees and inventors as defined by the United States Patent and Trademark Office. Three different collaborative types, namely local (same city), domestic (different cities of the same country), and international collaboration, are discussed. The general status of solar cell patent collaborations, transforming trends of collaborative patterns, average numbers of assignees and inventors for three collaborative types, and international collaboration countries are studied. It is found that co-invented patents and co-assigned patents have both increased in numbers during the four decades studied, and that collaboration between technology owners is very low while the collaboration between inventors is active. Domestic collaboration is the main collaborative pattern for both assignee collaboration and inventor collaboration. The other two collaborative types show contrary trends: international collaboration has slowly risen in the past decades while local collaboration has dwindled. The US has the largest number of internationally collaborative patents worldwide, though such patents account for a low portion of total US patents. In contrast, China has a small total number of patents and internationally collaborative patents, however its international collaborative shares are higher. The international collaboration patents among countries are few. A co-assigned patent analysis indicates that the main international cooperation partner of the United States is Japan. Based on an international co-invented patent analysis, the main international collaboration partners of the United States are Britain, Japan, and Germany; and the United States is also the most important collaboration partner of China.     

The use of patent information for the identification of development trends

The publications on a specific technical field issued by the patent officers within a certain period of time do not only reflect the inventive activities and the “production” of new technical knowledge in a country, but also signalize forthcoming industrial activities and therefore indicate new technological trends. The focal points of these inventive activities may e.g. be ascertained from the bibliographical data on published patent applications compiled according to the International Patent Classification. These data also provide information on the granting of existing and imminent patents in the different industrial countries.     

Bibliometric overview of the utilization of artificial neural networks in medicine and biology

The distribution of articles involving artificial neural networks (ANN) in the fields of medicine and biology and appearing in the ISI (Institute for Scientific Information) databases during the period 2000-2001 was analysed. The following parameters were considered: the number of articles, the total impact factor, the ISI journal category, the source country population, and the gross domestic product. Among the 803 articles and the 49 countries considered, the 5 most prolific (in term of the number of publications) were the USA, The United Kingdom, Germany, Italy, and Canada; other active countries included Sweden, Netherlands, Spain, France, Japan, and China. Comparison between the USA and the European Union, and the distribution of ANN publications among the subdisciplines of the life sciences and clinical medicine are also presented.     

Evolutionary dynamics of scientific collaboration networks: multi-levels and cross-time analysis

Several studies exist which use scientific literature for comparing scientific activities (e.g., productivity, and collaboration). In this study, using co-authorship data over the last 40 years, we present the evolutionary dynamics of multi level (i.e., individual, institutional and national) collaboration networks for exploring the emergence of collaborations in the research field of “steel structures”. The collaboration network of scientists in the field has been analyzed using author affiliations extracted from Scopus between 1970 and 2009. We have studied collaboration distribution networks at the micro-, meso- and macro-levels for the 40 years. We compared and analyzed a number of properties of these networks (i.e., density, centrality measures, the giant component and clustering coefficient) for presenting a longitudinal analysis and statistical validation of the evolutionary dynamics of “steel structures” collaboration networks. At all levels, the scientific collaborations network structures were central considering the closeness centralization while betweenness and degree centralization were much lower. In general networks density, connectedness, centralization and clustering coefficient were highest in marco-level and decreasing as the network size grow to the lowest in micro-level. We also find that the average distance between countries about two and institutes five and for authors eight meaning that only about eight steps are necessary to get from one randomly chosen author to another.     

Important institutions of interinstitutional scientific collaboration networks in materials science

Interinstitutional scientific collaboration plays an important role in knowledge production and scientific development. Together with the increasing scale of scientific collaboration, a few institutions that positively participate in interinstitutional scientific collaboration are important in collaboration networks. However, whether becoming an important institution in collaboration networks could be a contributing factor to research success and how these important institutions collaborate are still indistinct. In this paper, we identified the scientific institutions that possess the highest degree centrality as important institutions of an interinstitutional scientific collaboration network in materials science and examined their collaboration preferences utilizing several network measures. We first visualized the appearance of these important institutions that had the most positive collaborations in the interinstitutional scientific collaboration networks during the period of 2005–2015 and found an obvious scale-free feature in interinstitutional scientific collaboration networks. Then, we measured the advantages of being important in collaboration networks to research performance and found that positive interinstitutional collaborations can always bring both publication advantages and citation advantages. Finally, we identified two collaboration preferences of these important institutions in collaboration networks—one type of important institution represented by the Chinese Academy of Science plays an intermediary role between domestic institutions and foreign institutions with high betweenness centrality and a low clustering coefficient. This type of important institution has better performance in the number of publications. The other type of important institution represented by MIT tends to collaborate with similar institutions that have positive collaborations and possess a larger citation growth rate. Our finding can provide a better understanding of important institutions’ collaboration preferences and have significant reference for government policy and institutional collaboration strategies.     

Patterns of scientific collaboration between Japan and France: Inter-sectoral analysis using Probabilistic Partnership Index (PPI)

Summary In this article we present an indicator - Probabilistic Partnership Index (PPI) - for use in measuring scientific linkages. This indicator is based on the Monte-Carlo simulation which provides a standard model to each network established in collaboration between two countries. Any relationship that occurs within a (whole) network can be projected to a standard model respectively and thus PPI is useful in examining individual networks within complex exchanges. We investigate inter-sectoral cooperation between France and Japan for the period of 1981-2004, by classifying every research unit appearing in the data set by its sector. We examine international collaborative patterns, domestic collaborative patterns and multilateral relationships established within the French-Japanese cooperation. We also compare PPI with the classic collaborative linkage indexes - Jaccard Index, Salton-Ochiai Index and Probabilistic Affinity Index - in order to describe the specificity of the new indicator. Our hope is that PPI will prove to be a useful and complementary tool for the analysis of international collaboration.