Abstract ：

Identifying the development trends of emerging technologies with disruptive potential as early as possible is crucial for enterprise research and development (R&D) investment planning and government R&D strategic planning. Many researchers have used academic papers and patent data to identify trends in emerging technologies, although they rarely have made use of web news data focused on emerging technologies. Web news contains a large amount of social awareness data that represents the public's sense of and response to emerging technologies, and the social awareness data is of great significance for identifying the development trends of emerging technologies. Therefore, this article presented a research framework to identify the development trends of emerging technologies using patent analysis and web news data mining. In the research framework, first, we have used patent analysis to analyze the evolution topics of these emerging technologies, and have applied the topic model to study the changing patterns of publics' topics of concern regarding emerging technologies contained in web news. Second, we have made a comparison analysis of the results of patent analysis and the public' sense of and response to emerging technologies contained in web news. Then, we have applied an improved sentiment analysis to study the changing patterns of publics' expectations for emerging technologies contained in web news. Finally, by studying the changes in publics' topics of concern and publics' expectations for emerging technologies over time, we have identified the development trends of emerging technologies. The perovskite solar cells technology is used as a case study to analyze the effectiveness and feasibility of the framework. This article provides a new research perspective to identify technology trends, and contribute to the technology forecasting methodology.

Keyword ：

social awareness social awareness perovskite solar cells perovskite solar cells patent analysis patent analysis technology forecasting technology forecasting web news web news Emerging technologies Emerging technologies

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Abstract ：

Breakthrough research may signal shifts in science, technology, and innovation systems. Early identification of breakthrough research is important not only for scientists, but also for policy makers and R&D experts in developing R&D strategies and allocating R&D resources. Researchers mostly use scientific papers data to identify potential breakthrough research, but they rarely make use of Twitter data related to scientific research and machine learning methods. Analysis of Twitter data is of great significance for us to understand the public's perception of potential breakthrough research and to identify potential breakthrough research. Machine learning methods can assist us in predicting the trend of events by utilizing prior knowledge and experience. Therefore, this paper proposes a framework for identifying potential breakthrough research using machine learning methods with scientific papers and Twitter data. We select solar cells as a case study to verify the valid and flexible of this framework. In this case, we use machine learning method to discover potential breakthrough research from scientific papers, and we use Twitter data mining to analyze Twitter users' sense of and response to the discovered potential breakthrough research, which aims to achieve a more extensive and diverse assessment of the discovered potential breakthrough research. This paper contributes to identifying potential breakthrough research, as well as understanding the emergence and development of breakthrough research. It will be of interest to R&D experts in the field of solar cell technology.

Keyword ：

Breakthrough research Breakthrough research Solar cell technology Solar cell technology Topic model Topic model Machine learning Machine learning Twitter data mining Twitter data mining

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Abstract ：

Digital twin is increasingly prominent for realizing the digital and intelligent transformation of various industries as an emerging technological means to connect the physical and virtual world. While there has been a recent growth of interest in digital twin in industry, finance, and academia, most relevant studies lack a systematic analysis of the status quo, development trends, and technological competition situations for digital twin. In this article, we used bibliometrics and patent analysis to conduct comprehensive and in-depth research of digital twin by reviewing the current status of academic research and technological development, distribution of countries and institutions, and technological competition situations. We found that academic research and technological development in digital twin are currently in the early stages of rapid growth, which is radiating from applications in smart manufacturing to other scenarios such as medical and health, smart cities, energy, transportation, public emergency, and agricultural food. Artificial intelligence technology, digital twin integrated architecture and system, intelligent real-time control have gradually become the key topics of academic research and technology research and development in the field of digital twin in recent years. The digital framework, sustainable digital twin, deep learning and neural network algorithms, and full lifecycle management have the potential to become technology development trends. USA and Germany are the technology leaders and occupy first-mover advantage at present, while China, the U.K., and South Korea are the powerful chasers in the future.

Keyword ：

Hidden Markov models Hidden Markov models Bibliometrics Bibliometrics Digital twin Digital twin evolutionary trends evolutionary trends competitive situation competitive situation Industries Industries Patents Patents Market research Market research digital twin digital twin patent analysis patent analysis Analytical models Analytical models Bibliometric analysis Bibliometric analysis

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Abstract ：

How to understand the innovation pathways of emerging technologies emerge from technology to market and identifing the future changes and trends in innovation pathways is crucial for enterprises' research and development (R&D) strategic planning, and new production development decision making. The technology roadmapping (TRM) is considered as an effective method to study innovation pathways, and provides a structured approach to map how emerging technologies have evolved from technology to market, and visualize the development relationships among markets, products, and technologies. However, the traditional TRM methods to visualize the innovation pathways, and identify the relationships among markets, products, and technologies mainly relied on experts' opinions, which are considered as time consuming and costly. The technology-relationship-technology (TRT) semantic analysis can semiautomatically extract technology information and the relationships among products, functions, and technologies from patents, which can significantly reduce the bias due to using experts' opinions that are based on intuitive knowledge when roadmapping the innovation pathways from technology to market activities. Therefore, this article integrates TRT semantic analysis and TRM method to propose a framework for monitoring the innovation pathways of emerging technologies and identifying future changes and trends in innovation pathways of emerging technologies. In this framework, first, we use the TRT semantic analysis to extract the TRT structures containing various structural relationships from the patents, and determine the analytical dimensions of TRM based on the TRT structures' characteristics and experts' knowledge. Second, we analyze the various structural relationships in-depth to explore their particular contributions in the process of TRM construction, and construct the technology roadmap to monitor the innovation pathways. Finally, after completing the construction of the TRT-based technology roadmap, we in-depth analyze the technology, function, product evolution paths in the TRM to identify the future changes and trends in innovation pathways with the help of domain experts. To illustrate the implementation of the research framework, we employ the elderly smart wear technology as the case study. This article will contribute to the TRM methodology, and will be of interest to elderly smart wear technology R&D experts and new production development experts.

Keyword ：

Senior citizens Senior citizens technology-relationship-technology (TRT) technology-relationship-technology (TRT) Innovation pathways Innovation pathways Transmission line measurements Transmission line measurements Text mining Text mining Market research Market research technology roadmap- ping (TRM) technology roadmap- ping (TRM) text mining text mining Semantics Semantics elderly smart wear elderly smart wear Technological innovation Technological innovation Patents Patents

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Abstract ：

As one of the strategic emerging industries, the new energy vehicle (NEV) industry receives strong support from the Chinese government. The Chinese government has formulated a large number of policies to promote the development of NEV industry. Evaluating and analyzing the NEV policies are of great significance for improving policy formulation. In this study, we comprehensively analyze 253 NEV policy texts by employing quantitative and qualitative methods. We present the policy instrument types and semantic structure characteristics of policy texts based on the content analysis. The advantages and disadvantages of policy texts are identified by using a quantitative evaluation model. Our results show that the most frequently used policy instrument is regulatory, and the main policy objective is the demand-pull. The policies with higher scores are more comprehensive. Three suggestions are put forward to improve NEV policies.

Keyword ：

Policy texts Policy texts New energy vehicle New energy vehicle Policy evaluation Policy evaluation

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Abstract ：

Artificial intelligence (AI) technology is a new focus for international competition, with countries around the world accelerating major outlay to enhance their innovation competitiveness. Identifying the global situation of AI technology is a strategic issue for enterprises and countries. Considering current deficiencies in research directed towards this, the content for analysing technological competition situations should be determined from the two most relevant levels of: 1) technology's dimension; 2) research and development (R&D) actors' dimension, with time (T), market (M), technology (T) and subject (S) as its four elements. This paper, therefore, proposes an analytical framework of technological competition situation, based on the four dimensions of TMTS. AI technology is taken as an example to verify the feasibility and effectiveness of the analytical framework. This paper will contribute to our understanding of the global competitive situation of AI technology, and will be of interest to AI technology's R&D experts.

Keyword ：

artificial intelligence artificial intelligence four-dimensional analysis four-dimensional analysis competitive situation competitive situation patent analysis patent analysis

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Abstract ：

Monitoring the emergence of emerging technologies helps managers and decision makers to identify development trends in emerging technologies is crucial for government research and development (R&D), strategic planning, social investment, and enterprise practices. Researchers usually use academic papers and patent data to identify and monitoring the trends of emerging technologies from a technological perspective, but they rarely make use of social media data (e.g., such as Twitter data) related to emerging technologies. Analysis of this social media data is of great significance to understand the emergence of emerging technologies and gain insight into development trends. Therefore, this paper proposes a framework that uses patent analysis and Twitter data mining to monitoring the emergence of emerging technologies and identify changing trends of these emerging technologies. The perovskite solar cell technology is selected as a case study. In this case, we used patent analysis to monitoring the evolutionary path of perovskite solar cell technology. We applied Twitter data mining to analyze Twitter users' sense of, response to, and expectations for this perovskite solar cell technology. We also identified the professional types of Twitter users and examined changes in their topics of interest over time to track the emergence of perovskite solar cell technology. We analyzed a comparison of the results of patent analysis and Twitter data mining to identify development trends of perovskite solar cell technology. This paper contributes to our understanding of how technologies emerge and develop, as well as the technology forecasting and foresight methodology, and will be of interest to solar photovoltaic technology R&D experts.

Keyword ：

Twitter data mining Twitter data mining Technologies emerge Technologies emerge Patent analysis Patent analysis Perovskite solar cell technology Perovskite solar cell technology Technology trends Technology trends Emerging technologies Emerging technologies

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Abstract ：

Disruptive technology introduces new competitive platforms, possesses the ability of initiating new markets, and changes firms' technological competition status. Early identification of candidate application areas will allow for timely adjustment of technology innovation strategies and minimization of risks at firm level. This paper proposes a framework of application areas forecasting process for disruptive technology based on patent data. SIRS epidemic model is analogically introduced by measuring transition velocity of all the entities in the technology diffusion system respectively. We implement the model deterministically to forecast the potential of industrial and technological disruption in the short run, and stochastically to forecast the disruptive technology's major outbreak in candidate application areas in the long run. Radio-frequency identification technology is selected as case study. We conclude by discussing the major outbreak probabilities and potential disruptions of RFID in three different application areas. The results will provide practical suggestion to firms and other stakeholders to facilitate their strategy making when faced with disruptive technologies. (C) 2016 Elsevier Inc. All rights reserved.

Keyword ：

Technology forecasting Technology forecasting SIRS epidemic model SIRS epidemic model Application areas forecasting Application areas forecasting Industrial disruption Industrial disruption Technological disruption Technological disruption Disruptive technology Disruptive technology

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Abstract ：

In recent years, emerging technologies have been attracting increasing attention, especially when those technology-follower countries attempt to develop new technology-based industries that contribute to their global innovation competitiveness. This paper proposes a framework for strategising and planning the emerging technologies-based industry in developing countries like China. This framework addresses three key issues for the technology-followers: 1) the significant capability gaps to catching-up in innovation; 2) the future external environment factors that may influence the innovation gaps; 3) the strategic development pathways that reduce these gaps. This framework integrates traditional roadmapping workshops and patent analysis. The organic light emitting diode (OLED) industry in China is selected as a case study. This study will contribute to the roadmapping and innovation catch-up literature, and will be of interest to OLED industry researchers.

Keyword ：

technology roadmapping technology roadmapping bibliometrics bibliometrics organic light emitting diode organic light emitting diode OLED OLED emerging technologies emerging technologies TRM TRM patents analysis patents analysis

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