Open access peer-reviewed chapter

Patent Research in a Period of Industry Transformation: A Focus on Electromobility

Written By

Zhao Qu

Submitted: November 28th, 2017 Reviewed: February 17th, 2018 Published: March 20th, 2018

DOI: 10.5772/intechopen.75579

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Scientometrics

Edited by Mari Jibu and Yoshiyuki Osabe

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Abstract

Patent, as a valuable collection of technical information, is gaining momentum as proxy measures of innovative activities and is ascribed a unique role in tracking the rise of emerging technologies. The last 30 years have seen a dramatic transformation of the world’s manufacturing landscape, for instance, a greening development in the automotive sector. A typical example of this practice is the emergence of electromobility (e-mobility)—an integrated approach addressing issues from sustainable transportation to revolutionary driving behavior adopted to circumvent problems concerning both resources and pollution while meeting mobility demands. Since novel technologies covered by e-mobility are not yet entirely attainable in the market, the only metric particularly is patent data. However, a correspondingly bright light seems not to be shined on e-mobility patent research, even in the area of engineering. This paper employs bibliometric and sentence-by-sentence analysis coupled with visualization tools to illustrate how the patent examines e-mobility-oriented issues in a contextualized and multivalent way. The conclusion reached is that patent research on e-mobility still has more spaces to move up, not only in improving its efficiency in plotting evolution of technologies but with regard to interpreting patents across the historical background of the industrial revolution.

Keywords

  • patent research
  • electromobility
  • bibliometric analysis
  • methods and design practices
  • conclusive and citing parts
  • sentence-by-sentence analysis

1. Introduction

As reported by WIPO, after 7 years of straight increases, global patent filings reached new highs in 2016—3.1million with annual growth of 8% [1]. It has correspondingly caught considerable interests ranging from social science research to economic analysis [2, 3, 4], accumulating more than 16,000 international publications over the past 10 years. Conversely, patent study on e-mobility failed to go up by the same proportion even though it plays a tremendous role in promoting the development of technological innovation while being the focal point of a thoroughly international academic discourse. Referring to vehicles that rely on plug-in electricity for their primary energy [5], e-mobility is currently supported as a favorable approach to transform road transport by reducing carbon emissions and discussing drivers of change in the automotive industry [6, 7]. For accelerating technological progress, e-mobility has been extensively explored from commercial, political, and social network perspectives [8, 9, 10], indicating that this field represents a significant technical challenge and requires complex social changes. Even some deficiencies inherent in patent research are not to be neglected, for instance, not every technical invention is patented [11, 12]. Patent data as a special type of literature still has the advantage of being more retrievable and well organized in research for supporting scientific and technological decision, creating preferential development domains and protecting enterprise rights. Amid the rising concern and limited publication counts, new questions arise: How are patents integrated into e-mobility studies? How do e-mobility studies in turn shape them? And how, if at all, might scholars intervene in these processes?

In retrospect, patent documents have been assessed in conjunction with data extracted from scientific publications and industry products to examine recent developments and research progress on cold startup of automotive proton exchange membrane fuel cells (PEMFC), complete oxidation of methane at low temperature over noble metal, powertrain architectures, adsorbed natural gas technologies, and robust battery pack for electric vehicles (EVs) [13, 14, 15, 16, 17]. To trace the commercial pathway for ultra-capacitor technology, patents, especially the assignment information, are analyzed combined with investment figures [18]. However, the reason for applying patents to those studies has not been pointedly outlined and reviewed. Recent articles focus on patent-based indicators as to counts, families, portfolios, and citations in evaluating the effectiveness of e-mobility technology forcing policies and identifying technological changes, particularly around EVs [19, 20, 21, 22], while the existing literature lacks details in conclusion on specific approaches and findings. The methods and design practices of e-mobility patent studies deserving of greater attention are the ones that place references at the forefront of the discussion about technology-driven innovation.

The present study, with a data set of 48 journal papers, is developed to review the patent research in the field of e-mobility by integrating a bibliometric overview on keywords and citations for insights into relevant research topics and knowledge base, then to trace back to the texts for an in-depth understanding of patent-use in practice and its contexts for answering the question: Does a lower share of international publications correspond to a less useful or more difficult intersection of patent analysis, especially into a field like e-mobility involving both traditional and emerging technologies? This special issue is a bridging effort to bring together patent study and bibliometric analysis by putting a spotlight on research progress, limitations, and potential topics in a period of industry transformation.

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2. E-mobility and significance of patent research

The invention of automobiles has been perceived as the promotion of global economic development and improvement of living standards by enabling mobile freedom. However, the growing concern for energy, environment, traffic safety, industrial competitiveness, and technology improvements raises the question of whether this freedom of mobility would be sustainable in the new era [7, 23]. The current and renewed interest in e-mobility can be explained in accordance with drivers of change earlier in the automotive industry. This term is not entirely new, and its central idea is urban electric cars which can be traced back to 50 years earlier than the first petrol-powered internal combustion engine vehicle (ICEV) [24, 25]. For stimulating technological progress, EVs in principle should now have a bright future; however, a lighter, cleaner, and smarter automobile era with adoption of wireless connections is in the movement [8, 9]. There is still considerable concern that efforts to date on making conventional powertrains more fuel efficient and less-polluting are insufficient [26]. This study thus is more inclined to adopt an expanded scope of e-mobility technologies other than the single category of EV-based technologies. Academics in this field are traditionally identified as having strong connections to governments and industries, as it is associated with the shift to a broader network of actors and stakeholders, ranging from automotive giants to battery-charging services providers [10, 27]. Thus, research on e-mobility not only seeks to answer the question of technology updating but is designed to give a sharp focus on changes caused by automotive industry transformation.

A wealth of technological, geographical, and industry information provided by patent has generated it to be a frequently used measure for studying basic research and anticipating emerging trends in automobile innovation [19, 21]. Bibliographic data extracted from patent documents is largely publicly available and quantitatively measurable [28, 29], which offers clear benefits in comparison with other indicators, for example, the one built upon R&D, to identify and measure patterns concerning innovative activities in uncertain technological fields [21]. Despite the controversial debate on the use of patent statistics to evaluate technological progress, the advantages prevail and empirical studies, particularly in research-intensive areas like e-mobility, support the application in obtaining an adequate output with a minimized input [11, 30]. The current publication counts contrast starkly with the significance of delving into patent issues of e-mobility. Hence, to drive further adoption of patent analysis as for e-mobility, scrutinizing related articles for progress, limitations, and potential topics is causally necessary.

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3. Data and methodology

Advanced bibliometric analysis is regarded as a powerful method to answer questions, such as “How can we keep track of the increasing number of scientific articles? Are there specific patterns hidden in this mass of published knowledge at a meta-level, and if so, how can these patterns be interpreted?” which enable us to analyze structures and dynamics of fields [31, 32]. Forty-eight articles in English identified by merging the query of terms1 in the scope of e-mobility (e.g., electric vehicles, hybrid electric vehicle, etc.) with the topic search of patent (TS = patent*) from the Web of Science™ Core Collection (WoS) database up to 2017 are discussed in this chapter aiming to investigate the current progress of patent research on e-mobility. Visualizations are addressed throughout the discussion by explaining how they are produced and how they can be interpreted. Extrinsic data to the text such as the publication year, keywords, and citations are synthetically measured in a co-occurrence analysis, a technique that captures the frequency of pairs of words, phrases, or references in and between articles [33]. The first step is to represent the association of research topics and to observe the progress along with the time, source, and flow of knowledge, eventually to understand the development of scientific fields. The common base and expansion of knowledge are structured through backward and forward references by performing a co-citation and bibliographic coupling analysis, respectively, and the former depends on the frequency when two documents are cited together whereas the latter occurs when two works reference a common third work [33, 34]. Then, intrinsic information regarding the reason for performing patent analysis of e-mobility issues, research limitations, and trends dug out from abstracts, methods, conclusive parts, and recent highly cited papers are collected and categorized on a sentence-by-sentence basis in order to advocate for greater attention to article content in addition to the bibliometric analysis.

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4. Patent research on e-mobility

4.1. A bibliometric overview

4.1.1. General trend and main research topics

The earliest publication involved in the present data set could be traced back to 1993 [35] and the pressing environmental concern has renewed calls for a shift toward internationalization of e-mobility research since 2012. Even the number of patent researches is limited, the sources are relatively scattered (132 authors from 58 affiliations), and their collaborations could not be captured in an extensive network (only 3 authors are engaged in the co-authorship more than once). In Figure 1 323 authors’ keywords are cleaned up manually considering the problem of variants (e.g., “electric vehicles” and “EVs”) and then 48 terms meeting the threshold (occurrences ≥2) are processed into 6 main clusters and colored using average publication year by VOSviewer. Patents have been employed to reveal the hype cycle for emerging technologies between 2001 and 2013 and then are discussed by introducing novel techniques (e.g., Google search) after 2014. Terms of “innovation” and “EV” as key nodes have been continuously explored ranging from the topics of patent-based indicators and approaches to technologies and the automotive industry as well as green products and market since 2013. Recently, the focus of patent research lies with the emergence of hybrid devices. E-mobility issues are inevitably tied to carbon emissions, efficient strategy, and sustainable development, which is proved in cluster 5 and 6.

Figure 1.

Co-occurrence analysis of keywords with average publication year.

4.1.2. Citation-based knowledge flows

Filtered by the minimum number of citations, 51 of 1788 references are collected and form four main clusters (Figure 2). The paper published by van den Hoed in 2005 [36] is represented as a key node among a group of emerging technology-based studies in red at the interface between discussions on emerging eco-innovation evaluation (green nodes on the top) and the cluster of papers adopting patent-based indicators in measuring technological change (yellow nodes in the middle). Note that citation is more frequent and probably more disciplined on the overall innovation performance research side, which also provides us with different kinds of evidence for the deficiency in e-mobility patent study. Among the technological forecasting-focused papers on the right side of Figure 2 (blue nodes), the co-citation analysis highlights authors [37, 38, 39] who have engaged in discussions with the joint use of bibliometric and patent analysis. The first cluster indicated in red is led by research from van den Hoed and Bakker [36, 40], who share an interest in the development of fuel cell technology. Citations categorized into the second cluster have an earlier average publication year than that of the first cluster, including studies on e-mobility innovation coupled with policy, economic, and technology analysis [41, 42, 43]. Patent citation analysis is the central topic of discussion involved in the fourth cluster with the earliest average publication year of 2000 [44, 45, 46]. Namely, the core documents providing a common knowledge base for e-mobility patent study are relatively new and it is partly an effect of emerging technologies and the changing field.

Figure 2.

Co-citation analysis of references listed in 48 papers.

By contrast, an analogous network structure could not be found through a bibliographic coupling analysis of 462 citing papers owing to the unclear layout of nodes and their links. It may indicate that the knowledge of these 48 patent studies is expanded to a much broader scientific field with more creative and diverse approaches to exploring e-mobility issues. Moreover, the share of self-citations is comparatively high and implies that there has existed specific groups of authors in this research area and their studies possess certain coherence.

4.2. The usage of patent

For answering the question of how patents are involved in e-mobility study and thus providing a reference point for further adoption of patent research, three main categories of the introduction of patents differed in research perspectives, and data formats are identified. Table 1 outlines the direct use of patent-based indicators (e.g., counts, families, and citations) or patent documents (e.g., abstracts and literature) in view of reasons, including main routes as tracing the technological and industry trend, evaluating policies and innovation, as well as improving patenting activities and patent-based analysis [19, 22, 47, 48, 49, 50]. Besides, the importance of patented technologies is highlighted while the rise in patenting activities and their commercialization indicate that a clean technology revolution staged by e-mobility is approaching [51, 52].

ReasonsPatent as the proxy for innovative output is the most common way in the automotive industry to protect intellectual property.Patent documents include potential information on developed technologies
MeasuresPatent—applications, counts, grants, families, origin countries and priority years, publications, citation networks, assignees, organizations, portfolios, keywords, International Patent Classifications (IPC)Patent—pending applications, abstracts, literatures
AimsTo assess industry structure; examine the patterns of technological change; forecast diffusion or adoption patterns of new technologies; understand technology maturity; evaluate the effectiveness of technology-forcing policies; measure the incentive and opportunity to innovate; operationalize the R&D and commercialization aspects of innovation strategies; study the relationship between competitive forces and technological development; propose a predictive model of the patent registration time; find differences between patents and research publications for technology road mapping; filter the irrelevant patent citations; and verify components of the hype cycleTo describe technology in detail; explore technology clusters; give an indication as to main technical challenges for the relevant technology; assess technological evolvement or accelerate literature-based science discovery

Table 1.

The usage of patent in an e-mobility study extracted from abstracts and methods.

4.3. Limitations and potential topics

4.3.1. Recent research limitations

Some of the deficiencies inherent in patent research are synthesized and divided into groups of limitations regarding patents or data sources [21, 53, 54] and patent-based indicators or approaches [47, 55, 56], respectively, thereby pinpointing areas of improvement in the further study on e-mobility. However, the following limitations should not be viewed in isolation, and the specificity of e-mobility field, especially the novelty and complexity of technologies [19, 21], needs to be considered in addition to patent-oriented issues (Table 2).

CategoryLimitations of patents or data sources in itselfShortcomings of patent-based indicators or approaches
Limitations and drawbacks-Not all technological knowledge is covered by patent data as not all inventions are patentable and not all patentable innovations are really being patented.
-Web search is relied on secondary, and other sources are emerging, which may cause a shift in the category of search engine users.
-Firms may exhibit differences in their tendencies to patent and their willingness to publish strategic decisions, thus affecting patent database.
-It is difficult to cover every value chain step with relevant IPC codes.
-The analysis of the revealed technological advantage (RTA) is always subject to consideration of absolute numbers within the technologies.
-Forming technology clusters through affinity propagation (AP) is susceptible and the interpretation of the technology clusters by using extracted core keywords is qualitative judgment.
-Identifying important groups and the total groups that form a particular technology affects forecast.
-Patent counts are not always representative for the success of the invention as its commercialization is not guaranteed.

Table 2.

Recent research limitations stated in conclusive parts of publications (since 2015).

4.3.2. Potential topics

A series of up-to-date topics captured from citing articles based on recent highly cited ones in Table 3 could be classified into the extension of the specific technology discussion, patent-based analysis, and research on innovation system or policies in the field of e-mobility [47, 57, 58, 59, 60, 61, 62]. The classification of additional research perspectives is inevitably influenced by the usage of patent in highly cited papers (Table 1). More specifically, a review on patented technologies has developed the base for further experimental studies, and papers adopting patent-based indicators could arouse growing interests in examining the pattern of technological change [21, 63]. Patents combined with other format of data, such as scientific literatures, surveys, interviews, or press releases, may contribute to a more comprehensive understanding of relevant policy and innovation system research [48, 54].

Times cited/Tittle (purpose)Cited ideaFurther study
18/Recent commercial free-piston engine developments for automotive applications (reviewing commercial developments in free-piston engine systems by looking at recent publications and patent documents)“…discussed the basic features of a free-piston engine generator and the dynamics of the engine …”Experimental study of a free-piston linear generator
15/Identifying trends in battery technologies with regard to electric mobility: evidence from patenting activities along and across the battery value chain (applying patent families as technological indicators in order to analyze the research activities of each step of the designed battery value chain individually and in comparison with each other to identify and discuss trends regarding the technologies associated with electric vehicles)“…lithium-ion batteries have dominated very quickly…”
“…the booming consumer electronics industry rapidly changed the economic and social landscape…”
“…patent based studies have noted strong interest in radical innovation paths…”
Patent study on the automotive supply industry, technologies’ diffusion, technological distance, technology landscape, and innovation network
9/Business strategies of incumbents in the market for electric vehicles: Opportunities and incentives for sustainable innovation (analyzing how environmental regulation and the firm’s incentive and opportunity to innovate affected EV sales)“…finds the same contrasting technology strategies employed by electric passenger vehicle manufacturers and companies need both incentives and opportunities…”Review the proposal of conceptual framework regarding green innovation system; evaluate environmental policy and innovation
5/On the relation between communication and innovation activities: A comparison of hybrid electric and fuel cell vehicles (analyzing the relation between research and innovation activities and communication activities in the automotive industry using patent statistics, press releases, and interviews)“…vehicle electrification can ease environmental problems …”
“…the changing perception of the hybrid technology led to a ‘hybrid race’ testified by the significant increase in patents…”
analysis on drivers, the current momentum, and policies for accelerating EV development

Table 3.

Highly cited publications and cited ideas (times cited ≥5 since 2015).

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5. Discussion and conclusion

The present findings drawn from the bibliometric and sentence-by-sentence analysis of 48 journal papers indicate that patents, as indicators or references alike, still occupy an irreplaceable position in tracking the rise of emerging technologies. Since 2001, a sequence of structural data extracted from patents, like counts, grants, or classifications, has been employed to assess industry structure and examine the patterns of technological change. Assignees, organizations, and portfolios involved in patents are analyzed to measure the R&D and commercialization aspects of innovation strategies. New technologies’ forecasting has been increasingly produced by keywords and patent citations accompanied with the emergence of advanced data search and mining techniques. Details of e-mobility technologies, ranging from batteries to smart grids, are scrutinized as references based on patent documents. Contents are continuously being specified and updated in line with the overall trend in the development of e-mobility, accounting for elements behind pure statistics. Even the patent study on e-mobility has not already accumulated a remarkable number of publications; the potential topics revealed by extended use of recent highly citied papers are researchable, including the analysis of automotive supply industry, technology diffusion, and landscape as well as the evaluation of green innovation system and policies. A specific focus in latter the e-mobility patent study is to expound key technical problems regarding free-piston linear generator. Drivers, the current momentum, and policies are constantly analyzed to answer the question of how EV development is accelerated. However, limitations rooted in patent data concerning patentability, search engine, willingness to publish, and the IPC-based bias with the one-sidedness of certain patent-based indicators mentioned as earlier should be noticed in further adoption of patents in e-mobility analysis, especially for improving its efficiency in plotting evolution of technologies and interpreting patents in a specific context. The limitation of such a study is that characteristics of patent study could not be fully identified because they are only identified from publications in an emerging field and the relevant search terms have not been unified in the past research. Nevertheless, it could be a sign of renewal when issues highlighted by those articles are explored in depth.

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Acknowledgments

The author would like to thank for financial support provided by the China Scholarship Council (No.201506060153), the National Science Foundation of China (No.71673036), and the Consulting Project of Chinese Academy of Engineering (2016-XZ-03-05).

References

  1. 1. WIPO. World Intellectual Property Indicators - 2017 [Internet]. 2017. Available from: http://www.wipo.int/edocs/pubdocs/en/wipo_pub_941_2017.pdf [Accessed: 2018-01-15]
  2. 2. Jaffe, Adam B, Gaétan de Rassenfosse. Patent citation data in social science research: Overview and best practices. Journal of the Association for Information Science and Technology. 2017;68(6):1360-1374. DOI: 10.1002/asi.23731
  3. 3. Lai Jessica C. The changing function of patents: A reversion to privileges? Legal Studies. 2017. DOI: 10.1111/lest.12176
  4. 4. Gambardella A, Harhoff D, Verspagen B. The economic value of patent portfolios. Journal of Economics and Management Strategy. 2017;26(4):735-756
  5. 5. Fédération Internationale de l’Automobile. Towards E-Mobility: The Challenges Ahead. [Internet]. 2011. Available from: http://www.lowcvp.org.uk/assets/reports/emobility_full_text_fia.pdf. [Accessed: 2017-11-10]
  6. 6. Figenbaum E, Kolbenstvedt M. Electromobility in Norway-experiences and opportunities with Electric Vehicles (No. 1281/2013); 2013
  7. 7. Sanden B. Systems Perspectives on Electromobility 2013. Chalmers University of Technology; 2013
  8. 8. Fernandes SJV. Electric Vehicles: Technology, Policy and Commercial Development. Routledge; 2013
  9. 9. Aichele C, Doleski OD, editors. Smart Market: Vom Smart Grid Zum Intelligenten Energiemarkt. Springer-Verlag; 2014. DOI: 10.1007/978-3-658-02778-0
  10. 10. Capgemini. Managing the Change to E-Mobility [Internet]. 2012. Available from: https://www.capgemini.com/wp-content/uploads/2017/07/Managing_the_Change_to_e-Mobility___Capgemini_Automotive_Study_2012.pdf [Accessed: 2017-12-15]
  11. 11. Qu Z, Zhang S, Zhang C. Patent research in the field of library and information science: Less useful or difficult to explore?. Scientometrics 2017;111(1):205-217. DOI: 10.1007/s11192-017-2269-2
  12. 12. Tijssen R, Buter R, Van Leeuwen T. Technological relevance of science: An assessment of citation linkages between patents and research papers. Scientometrics. 2000;47(2):389-412
  13. 13. Amamou AA, Kelouwani S, Boulon L, Agbossou K. A comprehensive review of solutions and strategies for cold start of automotive proton exchange membrane fuel cells. IEEE Access. 2016;4:4989-5002. DOI: 10.1109/ACCESS.2016.2597058
  14. 14. Gélin P, Primet M. Complete oxidation of methane at low temperature over noble metal based catalysts: A review. Applied Catalysis B: Environmental. 2002;39(1):1-37
  15. 15. Wu G, Zhang X, Dong Z. Powertrain architectures of electrified vehicles: Review, classification and comparison. Journal of the Franklin Institute. 2015;352(2):425-448
  16. 16. Nie Z, Lin Y, Jin X. Research on the theory and application of adsorbed natural gas used in new energy vehicles: A review. Frontiers of Mechanical Engineering. 2016;11(3):258-274. DOI: 10.1007/s11465-016-0381-2
  17. 17. Arora S, Shen W, Kapoor A. Review of mechanical design and strategic placement technique of a robust battery pack for electric vehicles. Renewable and Sustainable Energy Reviews. 2016;60:1319-1331. DOI: 10.1016/j.rser.2016.03.013
  18. 18. Schultz LI, Querques NP. Tracing the ultracapacitor commercialization pathway. Renewable and Sustainable Energy Reviews. 2014;39:1119-1126. DOI: 10.1016/j.rser.2014.07.145
  19. 19. Sierzchula W, Nemet G. Using patents and prototypes for preliminary evaluation of technology-forcing policies: Lessons from California’s Zero Emission Vehicle regulations. Technological Forecasting and Social Change. 2015;100:213-224. DOI: 10.1016/j.techfore.2015.07.003
  20. 20. Lee SL, Chen PC, Chan WC, Hung SW. A three-stage decision-making model for selecting electric vehicle battery technology. Transportation Planning and Technology. 2015;38(7):761-776. DOI: 10.1080/03081060.2015.1059122
  21. 21. Golembiewski B, vom Stein N, Sick N, Wiemhöfer HD. Identifying trends in battery technologies with regard to electric mobility: Evidence from patenting activities along and across the battery value chain. Journal of Cleaner Production 2015;87: 800-810. DOI: 10.1016/j.jclepro.2014.10.034
  22. 22. Yuan F, Miyazaki K. Trajectory identification as proxies for discerning the dynamic nature of technological change—The case of electric vehicles industry. International Journal of Innovation and Technology Management. 2017;14(01):1740006
  23. 23. Chan CC. The rise & fall of electric vehicles in 1828-1930: Lessons learned [scanning our past]. Proceedings of the IEEE. 2013;101(1):206-212
  24. 24. Adam M. Accelerating E-Mobility in Germany: A Case for Regulation. Springer; 2016. DOI: 10.1007/978-3-319-44884-8
  25. 25. Santini DJ. Electric vehicle waves of history: Lessons learned about market deployment of electric vehicles. In: Electric Vehicles-The Benefits and Barriers. InTech; 2011
  26. 26. Liesenkotter B, Schewe G. E-Mobility: Zum Sailing-Ship-Effect in Der Automobilindustrie. Wiesbaden: Springer Gabler; 2014. DOI: 10.1007/978-3-658-06310-8
  27. 27. Kaltenbrunner W. Situated Knowledge Production, International Impact. Minerva: Changing Publishing Practices in a German Engineering Department; 2017. DOI: 10.1007/s11024-017-9337-x
  28. 28. Narin F. Patent bibliometrics. Scientometrics. 1994;30(1):147-155
  29. 29. Lerner J, Seru A. The use and Misuse of Patent Data: Issues for Corporate Finance and Beyond (No. w24053). National Bureau of Economic Research; 2017. DOI: 10.2139/ssrn.3071750
  30. 30. Oltra V, Saint Jean M. Sectoral systems of environmental innovation: An application to the French automotive industry. Technological Forecasting and Social Change. 2009;76:567-583. DOI: 10.1016/j.techfore.2008.03.025
  31. 31. Van Raan AF. Advances in bibliometric analysis: Research performance assessment and science mapping. Bibliometrics. Use and Abuse in the Review of Research Performance. 2014:17-28
  32. 32. Ebrahim NA. Analysis of Bibliometrics Information for Selecting the Best Field of Study; 2016
  33. 33. Wyatt S, Milojević S, Park H, Leydesdorff L. Quantitative and Qualitative STS: The Intellectual and Practical Contributions of Scientometrics; 2015. DOI: 10.2139/ssrn.2588336
  34. 34. Zhuge H. Discovery of knowledge flow in science. Communications of the ACM. 2006;49(5):101-107. DOI: 10.1145/1125944.1125948
  35. 35. Bai L, Qu DY, Conway BE, Zhou YH, Chowdhury G, Adams WA. Rechargeability of a chemically modified MnO2/Zn battery system at practically favorable power levels. Journal of the Electrochemical Society. 1993;140(4):884-889. DOI: 10.1149/1.2056222
  36. 36. van den Hoed R. Commitment to fuel cell technology?: How to interpret carmakers’ efforts in this radical technology. Journal of Power Sources. 2005;141(2):265-271. DOI: 10.1016/j.jpowsour.2004.09.017
  37. 37. Daim TU, Rueda G, Martin H, Gerdsri P. Forecasting emerging technologies: Use of bibliometrics and patent analysis. Technological Forecasting and Social Change. 2006;73(8):981-1012. DOI: 10.1016/j.techfore.2006.04.004
  38. 38. Geels FW. Technological transitions as evolutionary reconfiguration processes: A multi-level perspective and a case-study. Research Policy. 2002;31(8):1257-1274. DOI: 10.1016/s0048-7333(02)00062-8
  39. 39. Watts RJ, Porter AL. Innovation forecasting. Technological Forecasting and Social Change. 1997;56(1):25-47. DOI: 10.1016/s0040-1625(97)00050-4
  40. 40. Bakker S. The car industry and the blow-out of the hydrogen hype. Energy Policy. 2010;38(11):6540-6544. DOI: 10.1016/j.enpol.2010.07.019
  41. 41. Oltra V, SaintJean M. Variety of technological trajectories in low emission vehicles (LEVs): A patent data analysis. Journal of Cleaner Production. 2009;17(2):201-213. DOI: 10.1016/j.jclepro.2008.04.023
  42. 42. Frenken K, Hekkert M, Godfroij P. R&D portfolios in environmentally friendly automotive propulsion: Variety, competition and policy implications. Technological Forecasting and Social Change. 2004;71(5):485-485. DOI: 10.1016/s0040-1625(03)00010-6
  43. 43. Sierzchula W, Bakker S, Maat K, Van Wee B. Technological diversity of emerging eco-innovations: A case study of the automobile industry. Journal of Cleaner Production. 2012;37:211-220. DOI: 10.1016/j.jclepro.2012.07.011
  44. 44. Archibugi D, Planta M. Measuring technological change through patents and innovation surveys. Technovation. 1996;16(9):451519-451468. DOI: 10.1016/0166-4972(96)000314
  45. 45. Von Wartburg I, Teichert T, Rost K. Inventive progress measured by multi-stage patent citation analysis. Research Policy. 2005;34:1591-1607. DOI: 10.1016/j.respol.2005.08.001
  46. 46. Pilkington A, Dyerson R. Innovation in disruptive regulatory environments: A patent study of electric vehicle technology development. European Journal of Innovation Management. 2006;9(1):79-91. DOI: 10.1108/14601060610640032
  47. 47. Borgstedt P, Neyer B, Schewe G. Paving the road to electric vehicles–A patent analysis of the automotive supply industry. Journal of Cleaner Production. 2017;167:75-87. DOI: 10.1016/j.jclepro.2017.08.161
  48. 48. Budde B, Alkemade F, Hekkert M. On the relation between communication and innovation activities: A comparison of hybrid electric and fuel cell vehicles. Environmental Innovation and Societal Transitions. 2015;14:45-59. DOI: 10.1016/j.eist.2013.11.003
  49. 49. Jun S, Uhm D. A predictive model for patent registration time using survival analysis. Applied Mathematics & Information Sciences. 2013;7(5):1819-1823. DOI: 10.12785/amis/070520
  50. 50. Yeh HY, Sung YS, Yang HW, et al. The bibliographic coupling approach to filter the cited and uncited patent citations: A case of electric vehicle technology. Scientometrics. 2013;94(1):75-93. DOI: 10.1007/s11192-012-0820-8
  51. 51. Linnenluecke MK, Smith T, McKnight B. Environmental finance: A research agenda for interdisciplinary finance research. Economic Modelling. 2016;59:124-130. DOI: 10.1016/j.econmod.2016.07.010
  52. 52. Coates D, Ferreira E, Charkey A. Development of a long cycle life sealed nickel-zinc battery for high energy-density applications. IEEE Aerospace and Electronic Systems Magazine. 1997;12(6):35-38. DOI: 10.1109/62.587056
  53. 53. Jun SP, Sung TE, Park HW. Forecasting by analogy using the web search traffic. Technological Forecasting and Social Change. 2017;115:37-51. DOI: 10.1016/j.techfore.2016.09.014
  54. 54. Wesseling JH, Niesten E, Faber J, et al. Business strategies of incumbents in the market for electric vehicles: Opportunities and incentives for sustainable innovation. Business Strategy and the Environment. 2015;24(6):518-531. DOI: 10.1002/bse.1834
  55. 55. Kim G, Lee J, Jang D, et al. Technology clusters exploration for patent portfolio through patent abstract analysis. Sustainability. 2016;8(12):1252. DOI: 10.3390/su8121252
  56. 56. Nagula M. Forecasting of fuel cell technology in hybrid and electric vehicles using Gompertz growth curve. Journal of Statistics and Management Systems. 2016;19(1):73-88. DOI: 10.1080/09720510.2014.1001601
  57. 57. Hou X, Zhang H, Yu F, Liu H, Yang F, Xu Y, et al. Free piston expander-linear generator used for organic Rankine cycle waste heat recovery system. Applied Energy. 2017;208:1297-1307. DOI: 10.1016/j.apenergy.2017.09.024
  58. 58. Abdalla II, Zainal AE, Ramlan NA, Aziz ARA, Heikal MR. Cogging force investigation of a free piston permanent magnet linear generator. IOP Conference Series: Materials Science and Engineering. 2017;257(1):012055. DOI: 10.1088/1757-899X/257/1/012055
  59. 59. Karvonen M, Kapoor R, Uusitalo A, Ojanen V. Technology competition in the internal combustion engine waste heat recovery: A patent landscape analysis. Journal of Cleaner Production. 2016;112:3735-3743. DOI: 10.1016/j.jclepro.2015.06.031
  60. 60. Binz C, Truffer B. Global Innovation Systems—A conceptual framework for innovation dynamics in transnational contexts. Research Policy. 2017
  61. 61. Özel FM, Davies H, Wells P. What works? An ANFIS-based policy evaluation framework for electric vehicle technology development. International Journal of Electric and Hybrid Vehicles. 2017;9(3):222-252
  62. 62. Bakker S, Farla J. Electrification of the car–Will the momentum last?: Introduction to the special issue; 2015
  63. 63. Hanipah MR, Mikalsen R, Roskilly AP. Recent commercial free-piston engine developments for automotive applications. Applied Thermal Engineering. 2015;75:493-503. DOI: 10.1016/j.applthermaleng.2014.09.039

Notes

  • Each term in the present query is sorted and filtered based on expert advice received from National Science Foundation of China (No.71673036) and Consulting Project of Chinese Academy of Engineering (2016-XZ-03-05).

Written By

Zhao Qu

Submitted: November 28th, 2017 Reviewed: February 17th, 2018 Published: March 20th, 2018