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Defining and validating a map of related technologies is critical for managers, investors and inventors. Because of the increase in the applications of and demand for semiconductor lasers, analyzing the technological position of developers has become increasingly critical. Therefore, the purpose of this study is to adopt the technological position analysis to identify mainstream technologies and developments relevant to semiconductor lasers.

Correspondence analysis and k-means cluster analysis, which are data mining techniques, are used to reveal strategic groups of major competitors in the semiconductor laser market according to their Patent Cooperation Treaty (PCT) patent applications.

The results of this study reveal that PCT patent applications are generally obtained for masers, optical elements, semiconductor devices and methods for measuring and that technology developers have varying technological positions.

Through position analysis, this study identifies the technological focuses of different manufacturers to obtain information that can guide the allocation of research and development resources.

Defining key artificial intelligence (AI) technologies is especially fundamental because AI applications involve the development of multiple technical fields and have the potential to generate numerous business opportunities in the future. However, most related studies have examined patent grants granted by or patent applications filed to major patent offices; few studies have employed the perspective of standard-essential patents (SEPs) from a holistic technical view. In addition, because few studies have explored the status signals of countries in relation to SEPs, the present study integrated “country” into the model and determined differences among countries in terms of their technological focus.

In this study, through patent technological network analysis in various periods, the author not only observed the focus fields of AI-related SEPs but also examined temporal trends to determine technical development trends.

This study identified technologies that have been key players in the SEP network in recent years; these technologies were centered on electric digital data processing, recognition of data and transmission of digital information. Moreover, many of these technologies have been applied in areas such as management and commerce and radio navigation. Furthermore, the USA plays a crucial role in the global development of AI technical network.

This study constructs a technical network model to identify key technologies and trends that can serve as a reference for national research and development resource allocation.

The development of oil shale has become a popular technique in the energy industry in recent years. Although more research attention has been paid to this topic, there are scanty studies on patent portfolios. This study aims to explore this current mainstream technique and the patent portfolios of oil shale developers and investigates the major assignees at present to find the technical development trend of oil shale as a reference for government, policy makers, investors and industrial strategic development.

This study applies correspondence analysis and K-means clustering analysis on data mining and probes into the competitive techniques and strategic groups of the main enterprises in the oil shale industry. In addition, by approval dates, this study analyzes technical directions and the development trends of the current main oil shale enterprises.

The findings show differences in the enterprises regarding technical positions and patent portfolio strategies.

Differential positioning analysis suggests the relative technical advantages of the various enterprises and evaluates the competition among oil shale enterprises.

In the current knowledge-based economy era, national innovation ability is crucial. Abundant information can be obtained through patent analysis, and such information can help in the formulation of policies and the making of R&D decisions; numerous researchers thus continue to make patent analyses. The quality of patents possessed by a country indicates the level of innovation and technology in the country, and this study aims to assess the quality of patents possessed by various countries.

In this study, the authors determined patent quality in various countries from the perspective of the reflective measurement model and used a novel method to construct a structural model of patent quality.

This study discovered that patent family, number of claims, number of international patent classifications, forward citations, nonpatent references and maintenance time are the structural factors that affect patent quality. Forward citations and the number of claims are particularly highly explained by patent quality, which is a latent construct.

The results of this study provide valuable information to the government and help in the assessment of patent quality in various countries. In addition, the assessment model proposed in this study can be used in the investigation of patent quality in academic research and can predict patent quality, which will be of interest to the government and industry.

Innovation plays a pivotal role in a national economy and in the research and development of science and technology. Because the elements, capability and development direction of innovation in various countries are dissimilar, national innovative capacity also varies by country. However, previous studies have predominantly measured national innovative capacity through empirical studies by using a single index of innovation output, ignoring that the forms of innovation are heterogeneous across countries and failing to examine the influence exerted by various innovation models on economic development. Thus, the purpose of this study is to fill this gap by using scientific driving force and technological driving force to present the influence of national innovative capacities on economic development.

This study used regression models to test the influence of different national innovative capacities (i.e. scientific and technological driving forces) on economic development and stability.

Using the data of 60 countries, this study determined that both scientific and technological driving forces influenced economic development; specifically, scientific driving force affected economic development through technological driving force. Moreover, both research paper quality and patent quality positively influenced economic stability, but patent quality was the mediator.

This study examined scientific output from both quantitative and qualitative perspectives to determine their influence on economic growth and particularly on economic stability, which lacks dedicated studies. This study strives to bridge this gap in the literature by asserting, from the concept of economic resilience, that high-quality science and technology can strengthen the stability of a country’s economy.

How 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.

Patents 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.

The 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.

This 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.

As the university–industry collaboration (UIC) gradually attracts the attention of various national governments, the number of studies on UIC has increased substantially. Past UIC studies have mostly focused on investigating the incentives and the motivation for UIC, forms of UIC and performance output of UIC. However, they have not actively identified the key technologies and technology distribution that are conductive to the commercialization of UIC outcomes. Therefore, this study aims to adopt the licensed UIC patents as the basis for analysis and to construct a patent licensing technology network.

This study focused on licensed patents because past studies have indicated that such patents usually have higher value. Moreover, patent licensing can be seen as the final step for the commercialization of UIC outcomes. Finally, past studies have rarely explored patent examiners’ views on key technologies. However, during the substantive examination of patents, patent examiners often use their background knowledge regarding the technology to include citations to other patented technologies that they consider valuable or indispensable. Therefore, this study focused on investigating the patents recognized and cited by patent examiners and conducted key technology identification.

The results indicated that past key technologies in UIC focused on surveying, medicine, biochemistry and electric digital data processing; these fields are crucial to the commercialization of key UIC technologies. Finally, the USA, Japan, Sweden and Germany play critical roles in the network of global university–industry cooperation and technology licensing.

Patent examiners’ perspectives were adopted to establish a patent licensing technology network, through which the key technologies that could promote UIC patent licensing were mined. This study can also serve as a reference for resource allocation in university research and development and for governments to promote new technologies.

The application of laser and optical technologies in the industry is wide and extensive; the development and application of laser and optical technologies have become a promising research domain. However, most existing studies have focused on the technical aspects or the application aspects; these studies have not highlighted the technology distribution and application development of laser and optical technologies from the big picture. Additionally, the manner in which the research and development (R&D) results of universities correspond to the needs of enterprises and industry has become a topic of concern for the public. Therefore, this study aims to adopt the academic patents as the basis for analysis and to construct a laser and optical technology network.

Therefore, in the current study, the researchers have analyzed relevant academic patent technology networks, using academic patents of laser and optical technologies as a basis of analysis.

The study results indicated that the key technologies mainly lie in nanostructures, metal-working, material analysis and semiconductor devices. Additionally, these technologies are mainly applied in industries, such as optics, medical technology, pharmaceuticals, biotechnology and organic fine chemistry; this indicated that a large proportion of academia’s R&D outcomes are applied in these industries.

In this study, the researchers have constructed a technology network model to explore the technical development direction of laser and optical technologies; the results of the current study could serve as a reference for universities and industry for allocation of R&D resources.

The purpose of this paper is to present a model developed for emergent formation of multi‐unmanned aerial vehicles (UAVs) into functional teams that cooperatively complete a mission in which they search for specific mobile targets and escape obstacles.

The design and development of distributed UAVs simulator use agent‐based platform employing a decentralized control which follows the flocking behavior‐based design philosophy.

The results of the simulation indicate that the emergent behavior‐based search procedure for UAVs is autonomous, effective and robust. It is especially well suited for emergent teams to quickly solve dynamic teaming and task allocation.

The development of a UAV is expensive, and a small error in automatic control results in a crash. Therefore, the platform is useful to develop and verify the coordination behavior of UAVs through software simulation prior to real testing.

The proposed emergent behavior simulated environment is working on an agent‐based UAV simulated platform, and hence, it naturally adapts to the behavior of a distributed and concurrent situation. The authors' can easily improvise the execution environment without changing the UAV simulator.

The open innovation paradigm is an important topic of management thought in national innovation systems. Previous studies of open national innovation systems have almost always focused on concepts or theoretical exploration. There is a great lack of integrated frameworks for the process and mechanism of open national innovation systems. Therefore, the research adopts a structural approach and provides an open national innovation model to verify the influence of different mechanisms on open innovation outputs. As well, we argue that open national innovation systems will change over time, as the mechanisms are dynamic, linking, and coexistent. The study adopts a latent growth curve model to verify the growth tendency and progressive change. The policymaker’s perspective of exploring open national innovation systems is important. Building open national innovation capabilities is based on cumulativeness conditions, diffusion capabilities, and international linkages. The results show that cumulativeness conditions and international linkages will positively affect the growth rate of open innovation outputs. Consequently, this study adopts a dynamic experimental map to validate the relationship of the dimensions to provide government with some practical suggestions for making effective policy.