Patent Network Research Articles

Uncovering emerging technologies in intelligent manufacturing via graph classification of community characteristics

Advancing the identification of emerging technology trends is pivotal for informed design decisions and risk mitigation. Our research introduces a novel methodology, centered on technology subgraphs within a patent knowledge graph, utilising graph neural networks combined with data augmentation techniques. This approach deviates from traditional methods, which primarily focus on individual patent nodes or the entire patent network. Instead, it segments the patent knowledge graph into subgraphs, analyzing them based on structural features to identify emerging technologies. Our method is further strengthened by employing an expert-curated emerging technology tag library, enabling a quantitative, rather than solely qualitative, assessment of the subgraphs’ relevance to emerging technologies. Additionally, we integrate comparative learning to enhance subgraph data quality, thereby boosting the reliability and accuracy of our approach. The results demonstrate a significant improvement in the accurate identification of emerging technologies, underscoring the effectiveness of our proposed model.

Patent mining and diversity assessment of nuclear power technologies

Nuclear power technology is one of the pivotal avenues for ensuring a clean global energy transition. Bolstering technological diversity is critical for the sustainable advancement of nuclear power worldwide. However, a gap exists in investigating the trends and diversification of nuclear power technology over the past decade. This study proposes a data-driven integrated approach, leveraging descriptive statistics, co-occurrence analysis, network analysis, and multi-criteria decision-making methods to delve into the patent development, research and development (R&D) landscapes, and international layouts of nuclear power technology. Furthermore, the diversity of nuclear power technology globally and specifically within China is assessed. The findings unveil a substantial surge in nuclear power technology patents since 2020, with China, Japan, and Korea emerging as prominent R&D hubs. The R&D efforts in nuclear power technology predominantly concentrate on the design of nuclear reactor structures and cooling systems. Europe and the United States occupy significant positions within the nuclear power technology patent network. While China's nuclear power technology diversity slightly lags the global average, it has demonstrated a marginal lead since 2021. This study offers a comprehensive decision-support tool for trend analysis and diversity assessment in nuclear power technology.

Mapping the Nanotechnology Patent Landscape in the Field of Cancer.

Currently, cancer is still a significant disease that seriously endangers human health. Therefore, advanced diagnostic technology and treatment protocols are urgently needed. The rapid development of nanotechnology is expected to provide new ideas for cancer diagnosis and treatment. The research aims to comprehensively demonstrate the hotspots of nanotechnology applications in cancer. In this study, an International Patent Classification codes co-occurrence network is constructed to visualize the technology landscape by simultaneously locating and ranking technologies that play an integral role in nanotechnology diffusion and bridging in the field of cancer. In addition, community identification and topic modeling highlight the latent topics in patent documents. The visualization results of the patent network yield five main clusters: Cluster 0 is a nanoparticle composition delivery system with liposomes as the primary carrier. Cluster 1 is mainly represented by nano-immunotherapy with immune checkpoint inhibitors. Cluster 2 is nano phototherapy based on photodynamic therapy and photothermal therapy. Cluster 3 is diagnostic imaging involving nanotechnology. Cluster 4 is a drug delivery system with nanovesicles and albumin nanoparticles as carriers. It was found that carriers represented by liposomes, vesicles, and albumin nanoparticles are essential nanomaterials in the current anticancer drug delivery systems. Integrating next-generation immunosuppressants and nanotechnology will become an important development direction for future immunotherapy. Organic/inorganic nanomaterials are pivotal in cancer imaging diagnosis and phototherapy.

Drifting towards multidimensional collaborative innovation: the co-evolution of collaboration networks and policy in China’s nuclear power industry

Purpose Nuclear power is a stable and reliable energy source that can improve energy structure while reducing carbon emissions, which is of great significance for environmental protection and combating climate change. As a unique industry, it is facing rare development opportunities in China and has broad market prospects. However, the characteristics of technical difficulty, loose organizational structure and uneven regional distribution limit the expansion of the nuclear power industry. This paper aims to a better understanding of the accumulation process for innovation capability from the perspective of network evolution and provides policy guidance for the market development of the nuclear power industry (NPI). Design/methodology/approach Methodologically, social network analysis is used to explore the co-evolution of multidimensional collaboration networks. First, the development and policy evolution of the NPI is introduced to divide the evolution periods. Then, the authors identify and analyze the core organizations, technologies and regions that promote nuclear power patent collaboration. Furthermore, three levels of collaboration networks based on organizations, technologies and regions are constructed to analyze the coevolution of patent networks in China’s NPI. Findings The results show that nuclear power enterprises always play the foremost role in the organizational collaboration network (OCN), and the dominance of foreign enterprises is replaced by Chinese state-owned enterprises in the third period. The technology hotspot has shifted from nuclear power plant construction to the control system. The regional collaboration network was initially formed in the coastal areas and gradually moved inland, with Guangdong and Beijing becoming the two cores of the network. The scale of three collaboration networks is still expanding but the speed has slowed down. Originality/value In response to the pain points of the NPI, this research focuses on multidimensional collaborative innovation, investigates the dynamic evolution process of collaborative innovation networks in China’s NPI and links policy evolution with network evolution creatively. The ultimate result not only helps nuclear power enterprises integrate innovative resources in complex environments but also promotes industrial upgrading and market development.

China’s technological footprint in Africa: A patent network analysis

Purpose: The study aims to examine China’s rising technological influence in Africa within the context of Industry 5.0 and how it compares to traditional powers like the European Union (EU) and the United States (US).Design/methodology/approach: Utilising an innovative patent network analysis methodology, this study draws on data from the World Intellectual Property Organization’s (WIPO) Centre for Intellectual Property Statistics from 2001 to 2021.Findings/results: The analysis reveals China’s significant and growing presence in technological diffusion throughout Africa, potentially surpassing regional historical players.Practical implications: These findings have far-reaching implications for policy formulation and management strategies, particularly in a global landscape where technology standards and patents can significantly influence economic and business dynamics.Originality/value: This study contributes to the existing literature by offering a nuanced understanding of power dynamics in African value chains and a new context for relations between developed and developing countries. It emphasises the strategic importance of understanding technological centrality in emerging regions.

5G wireless technology evolution: identifying evolution pathways of core technologies based on patent networks

5G wireless technology evolution: identifying evolution pathways of core technologies based on patent networks

Absorptive capacities and external openness in underdeveloped innovation systems: a patent network analysis for Latin American countries 1970–2017

Abstract This paper contributes to the literature on innovation and development by analysing the absorptive and connectivity capacities of Latin American innovation systems between 1970 and 2017. Applying network analysis to a USPTO database containing Latin American inventors, we build and analyse collaboration networks in the process of invention and knowledge appropriation. The structural properties and the evolution of such networks allow us to measure critical attributes of the Latin American innovation systems. Specifically, the networks exhibit low absorptive capacity and high external openness, which are critical linkages with external nodes in the network growth process. We identify different trajectories of innovation systems within the region, analysing specific paths of capability (de)accumulation and network maturity against the backdrop of national development trajectories.

What drives network evolution? Comparing R&D project and patent networks in the EU

Abstract Collaboration networks are the main mechanisms through which regional innovation capacities are enhanced. These networks have been analyzed by using data either on research projects or patents. However, analyzing only one type of network can limit our understanding of regional innovation dynamics. In this paper, we investigate the drivers of network evolution in two inter-regional network types within the European Union: R&D project networks and co-patenting networks. Specifically, we examine data on Framework Program project collaborations and patent collaborations at the NUTS2 regional level between 2011 and 2019. Our empirical strategy is based on Stochastic Actor-Oriented Model where we analyze and compare the factors that affect the evolution of two networks. We find that path-dependent processes resulting from past networks, such as triadic closure, preferential attachment, and tie repetition, play a more important role in explaining the evolution of R&D project networks compared with patent networks. On the other hand, regional characteristics, particularly the patenting intensity of a region and similarity in patenting between regions appear to be more influential in shaping patent networks. These results have important implications for the future evolution of knowledge networks in Europe.

Design is Everywhere, But Nowhere in Patent Analytics

The number of design patents has grown significantly in the last 140 years. However, a data-driven approach for design patents has been overlooked and underutilised in the design management and innovation research communities. Through the prism of a patent professional, data analyst and designer, this photo essay demystifies the complexity of design patent data and sheds light on the underlying value of design as it features among a range of diverse innovation activities. Patent network analysis and visualisation techniques enable the building of a series of patent citation maps and co-inventor networks. Cases from renowned companies—Apple, Dyson, Samsung, and LG electronics— reveal different shapes of innovation activities, focusing on product diversification strategies, collaboration patterns and design-technology cross-pollination flows.

Exploration of Technological Collaboration Trends in Ulsan through Patent Network Analysis

Exploration of Technological Collaboration Trends in Ulsan through Patent Network Analysis

Drivers of the decrease of patent similarities from 1976 to 2021.

The citation network of patents citing prior art arises from the legal obligation of patent applicants to properly disclose their invention. One way to study the relationship between current patents and their antecedents is by analyzing the similarity between the textual elements of patents. Many patent similarity indicators have shown a constant decrease since the mid-70s. Although several explanations have been proposed, more comprehensive analyses of this phenomenon have been rare. In this paper, we use a computationally efficient measure of patent similarity scores that leverages state-of-the-art Natural Language Processing tools, to investigate potential drivers of this apparent similarity decrease. This is achieved by modeling patent similarity scores by means of generalized additive models. We found that non-linear modeling specifications are able to distinguish between distinct, temporally varying drivers of the patent similarity levels that explain more variation in the data (R2 ∼ 18%) compared to previous methods. Moreover, the model reveals an underlying trend in similarity scores that is fundamentally different from the one presented previously.

Structure of university licensing networks

We study the structure and evolution of networks of inventors involved in university licensing and patenting. In particular, we focus on networks of inventors that have successfully licensed a university patent (i.e., licensing networks), and investigate levels of their fragmentation, cliquishness, and whether they exhibit the small world phenomenon. We find that these licensing networks are more fragmented and cliquish than the networks of inventors engaged in all (not necessarily licensed) patents (i.e., patenting networks), and that they are not small worlds. Additionally, by comparing the created licensing networks to random subnetworks of the patenting networks, we find that concerns in regard to the potential effects of opportunistic behavior are, to some degree, justified. We detect an interesting collaboration behavior of inventors who license, which we designate as dualistic opportunistic behavior.

Regional industrial growth and biopharma patent networks: empirical insights from the UK

The COVID-19 pandemic has once again brought the significance of biopharmaceutical and medical technology sectors to the spotlight. Seeing that some of the most critical medical breakthroughs such as the speedy mRNA vaccine development were results of cross-border patenting collaboration, we have proposed in a previous work a new method to identify the cross-border collaborative regional centres in the patent networks, using a clustering comparison approach based on adjusted mutual information (AMI). In this paper, we focus on the UK industrial landscape. We use the UK bioscience and health technology sector statistics from 2015 to 2020 and look into the regional growth of each postcode area. We compare the top growth regions with the cross-border collaborative centres identified using AMI comparison at the postcode area level, and find that both long-term and short-term AMI gains show an increase in the correlation with regional annual growth rates of firm numbers in the studied sectors from 2016 to 2020, and the increase is more consistent with the short-term AMI gain. We also found that areas more central in the long-term cross-regional R&D collaboration demonstrate a stronger association with more developed industrial settings indicated by more firms and, potentially more employment and turnover in the field. However, AMI gains are found to have negative correlations with the industrial growths as a sign of possible trade-offs of being central.

A Study on Finding Partners through Patent Network Analysis of UAM (Urban Air Mobility)

This paper presents an open innovation strategy by identifying the patent impact index and cooperation network through patent analysis for leading companies developing technology in the UAM field. Among companies developing UAM technology, patent analysis was conducted on the leading companies with active patent activities, technology classification was used to match companies by parts, and a technical capability index was utilized to identify the companies. When developing UAM technology in the future, this can help companies seek effective partners to improve competitiveness in technology development. To the best of our knowledge, the work done in this paper is unprecedented, as it suggests methods for patent analysis and verifies them by analyzing the UAM patents with the proposed method.

Knowledge Generation and Knowledge-, Individual-, and Interfirm-Level Network Structural Features

Although there has been consensus that networks play critical roles in organizations’ innovation, the multilevel feature of networks that nest into each other is underexplored. Despite empirical evidence that has been found at various levels of our social system, without multilevel analysis, our understanding in the relationship between networks and knowledge generation and innovation is limited. To address this limitation, this study adopts a multilevel lens to analyze the three level networks that composed of patent network, individual collaboration network, and interorganizational network in China’s railway industry in a decade to illustrate how network positions at different levels are related to knowledge generation. We find that both knowledge network and interorganizational network contribute to knowledge generation.

Technology network and development trends of government-funded patents

PurposeHow prospective or emerging technologies can be supported through government-funded research projects has gradually received global attention. However, previous studies have primarily focused on the effects of government funding on subsequent technological development, the overall economy or social welfare of a country or corporate research and development (R&D) activities. These studies have not examined the technology distribution and development trends of government-funded research from a comprehensive technology perspective. In addition, previous measurements of the influence of government-funded R&D projects faced the difficulty of transferring the research achievements of government-funded research to the commercial market.Design/methodology/approachPatents can provide a preliminary understanding of the collaboration, development focus and status of market technologies. Accordingly, the purpose of this study was to examine the development directions of patented technologies engendered from government-funded research projects. Analyzing the network of government-funded patented technologies helped identify the current status and location of specific technologies in a patent network as well as the hotspot technologies in government-funded research projects that correspond to the market.FindingsThe results of this study indicated that the technologies obtaining government-funded patents mainly consist of advanced materials and semiconductors and that the technological focus has shifted over the years. Nanotechnology, pharmaceutical technology and sanitary technology have gradually become the technologies receiving most of government-funded patents. The trend of development of these technologies also corresponds to the emerging technologies advocated by countries worldwide in recent years.Originality/valueThis study provided a comprehensive verification of the government-funded patented technologies from a macro perspective by identifying key technologies using technology network analysis. The findings of this study can serve as a reference for the allocation of governmental R&D resources and the promotion of novel technologies in the private sector.

Cooperation in R&D in the pharmaceutical industry: Technological and clinical trial networks in oncology

• Cooperation is essential for the technological and clinical advances of new drugs. • There is more interaction in the development of CTs than patent deposit. • Geographic location is still a relevant factor for cooperation. Organizations cooperate according to their interests in the development of a specific technology. Research and development (R&D) in pharmaceutical industries is essential for the development of new drugs and partnerships are responsible to achieve and maintain competitiveness in the market. Cancer represents a global health problem and new oncology drugs are essential. This study verified how cooperation takes place aimed at the invention (patents) and development (clinical trials - CT) of treatments with the primary target being oncology. Using social network analyses to generate technological discoveries, cooperation networks using patents, and a CT development collaboration network, the 526 CT and 294 patents were analyzed in collaboration between universities, hospitals, companies, and other institutions. The results show the evolution of patents from chemical synthetic processes to biomarkers and immunological checkpoint inhibitors. The associations of the CT network tend to have more partnerships than the patent network, which indicates greater trust and the need for complementary expertise. This study indicates that during the R&D stages of new oncology drugs, organizations search for actors of different types, as experts are needed for each stage. Although companies are predominant in both networks, research institutes play a central role in this connection. This study can be applied for researchers, universities, institutes and companies interested in R&D and in the other therapeutic areas.

Temporal motifs in patent opposition and collaboration networks

Patents are intellectual properties that reflect innovative activities of companies and organizations. The literature is rich with the studies that analyze the citations among the patents and the collaboration relations among companies that own the patents. However, the adversarial relations between the patent owners are not as well investigated. One proxy to model such relations is the patent opposition, which is a legal activity in which a company challenges the validity of a patent. Characterizing the patent oppositions, collaborations, and the interplay between them can help better understand the companies’ business strategies. Temporality matters in this context as the order and frequency of oppositions and collaborations characterize their interplay. In this study, we construct a two-layer temporal network to model the patent oppositions and collaborations among the companies. We utilize temporal motifs to analyze the oppositions and collaborations from structural and temporal perspectives. We first characterize the frequent motifs in patent oppositions and investigate how often the companies of different sizes attack other companies. We show that large companies tend to engage in opposition with multiple companies. Then we analyze the temporal interplay between collaborations and oppositions. We find that two adversarial companies are more likely to collaborate in the future than two collaborating companies oppose each other in the future.

Organization-oriented technology opportunities analysis based on predicting patent networks: a case of Alzheimer’s disease

Organization-oriented technology opportunities analysis based on predicting patent networks: a case of Alzheimer’s disease

Understand technological innovation investment performance: Evolution of industry-university-research cooperation for technological innovation of lithium-ion storage battery in China

The evolution characteristics of the core network of the patent collaboration network in the field of lithium battery storage are compared with other fields such as phase change materials (PCMs) and the overall storage field in China by using the data from the Patsnap. Based on the trend of patent quantity, this paper chooses 2009 as the starting year to discuss the patent network in three stages: 2009–2012, 2013–2016, and 2017–2020. After 2009, new enterprises and institutions are more inclined to cooperate with institutions with high centrality when entering the energy storage field. Nodes with high centrality are mostly state-owned organizations or institutions with key technologies, which control network resources and influence network development. However, at the same time, the status of state-owned energy enterprises/institutions and universities in the cooperation network fluctuates, and they do not occupy an absolute leading position in the fields of lithium battery. The industry-university-research (IUR) cooperative network of lithium battery industry has the characteristics of tight internal node connection and sparse node connection among communities. On the whole, there is no continuous single (few) center (s) pattern in the three stages. This trend is contrary to previous studies on the overall field of energy storage. The different results got here maybe helpful for future IUR technology investment and decision-making.