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Mei Hsiu-Ching Ho

Personal Details

First Name:Mei
Middle Name:Hsiu-Ching
Last Name:Ho
Suffix:
RePEc Short-ID:pho285
[This author has chosen not to make the email address public]
Terminal Degree:2007 Eindhoven Centre for Innovation Studies (Ecis); Technische Universiteit Eindhoven (from RePEc Genealogy)

Affiliation

National Taiwan University of Science and Technology (NTUST) (Graduate institute of Science and Technology, NTUST)

http://www.ntust.edu.tw
Taipei

Research output

as
Jump to: Working papers Articles

Working papers

  1. Ho, M., 2004. "Differences between European Regional Innovation Systems in Terms of Technological and Economic Characteristics," Working Papers 04.06, Eindhoven Center for Innovation Studies.

Articles

  1. Mei Hsiu-Ching Ho & John S. Liu, 2021. "The swift knowledge development path of COVID-19 research: the first 150 days," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2391-2399, March.
  2. John S. Liu & Louis Y. Y. Lu & Mei Hsiu-Ching Ho, 2020. "A note on choosing traversal counts in main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 783-785, July.
  3. John S. Liu & Louis Y. Y. Lu & Mei Hsiu-Ching Ho, 2019. "A few notes on main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 379-391, April.
  4. Mei Hsiu-Ching Ho & John S. Liu & Kerr C.-T. Chang, 2017. "To include or not: the role of review papers in citation-based analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 65-76, January.
  5. Mei Hsiu-Ching Ho & John S. Liu & Max C.-H. Kuan, 2016. "Torn between Academic Publications and University–Industry Collaboration," Research Evaluation, Oxford University Press, vol. 25(2), pages 151-160.
  6. John S. Liu & Hsiao-Hui Chen & Mei Hsiu-Ching Ho & Yu-Chen Li, 2014. "Citations with different levels of relevancy: Tracing the main paths of legal opinions," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(12), pages 2479-2488, December.
  7. Mei Ho & John Liu & Wen-Min Lu & Chien-Cheng Huang, 2014. "A new perspective to explore the technology transfer efficiencies in US universities," The Journal of Technology Transfer, Springer, vol. 39(2), pages 247-275, April.
  8. Mei Hsiu-Ching Ho & Vincent H. Lin & John S. Liu, 2014. "Exploring knowledge diffusion among nations: a study of core technologies in fuel cells," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(1), pages 149-171, July.
  9. Mei Hsiu-Ching Ho & John S. Liu, 2013. "The motivations for knowledge transfer across borders: the diffusion of data envelopment analysis (DEA) methodology," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 397-421, January.
  10. Liu, John S. & Lu, Louis Y.Y. & Ho, Mei Hsiu-Ching, 2012. "Total influence and mainstream measures for scientific researchers," Journal of Informetrics, Elsevier, vol. 6(4), pages 496-504.
  11. Mei Hsiu-Ching Ho, 2009. "How Regional Innovation Systems Play a Relative Competitive Role Within Knowledge Networks," European Planning Studies, Taylor & Francis Journals, vol. 17(12), pages 1881-1905, December.
  12. Mei Hsiu-Ching Ho, 2007. "Explaining subsidiaries' knowledge-diffusion behaviours within MNEs," International Journal of Globalisation and Small Business, Inderscience Enterprises Ltd, vol. 2(2), pages 220-240.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

    Sorry, no citations of working papers recorded.

Articles

  1. Mei Hsiu-Ching Ho & John S. Liu, 2021. "The swift knowledge development path of COVID-19 research: the first 150 days," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2391-2399, March.

    Cited by:

    1. Beniamino Callegari & Christophe Feder, 2022. "The long-term economic effects of pandemics: toward an evolutionary approach [Epidemics and trust: the case of the Spanish flu]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 31(3), pages 715-735.
    2. Török, Ádám & Konka, Boglárka & Nagy, Andrea Magda, 2023. "A koronavírus-járvány a közgazdasági szakirodalomban. Egy új határterület tudománymetriai elemzése [The coronavirus pandemic in the economics literature. The scientometric analysis of a new discipl," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 284-304.
    3. Zhentao Liang & Jin Mao & Kun Lu & Gang Li, 2021. "Finding citations for PubMed: a large-scale comparison between five freely available bibliographic data sources," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(12), pages 9519-9542, December.
    4. Mona Farouk Ali, 2022. "Between panic and motivation: did the first wave of COVID-19 affect scientific publishing in Mediterranean countries?," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3083-3115, June.
    5. Huang, Chen-Hao & Liu, John S. & Ho, Mei Hsiu-Ching & Chou, Tzu-Chuan, 2022. "Towards more convergent main paths: A relevance-based approach," Journal of Informetrics, Elsevier, vol. 16(3).

  2. John S. Liu & Louis Y. Y. Lu & Mei Hsiu-Ching Ho, 2020. "A note on choosing traversal counts in main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 783-785, July.

    Cited by:

    1. Chen, Liang & Xu, Shuo & Zhu, Lijun & Zhang, Jing & Xu, Haiyun & Yang, Guancan, 2022. "A semantic main path analysis method to identify multiple developmental trajectories," Journal of Informetrics, Elsevier, vol. 16(2).
    2. Xiaorui Jiang & Junjun Liu, 2023. "Extracting the evolutionary backbone of scientific domains: The semantic main path network analysis approach based on citation context analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(5), pages 546-569, May.
    3. Liao, Shu-Chun & Chou, Tzu-Chuan & Huang, Chen-Hao, 2022. "Revisiting the development trajectory of the digital divide: A main path analysis approach," Technological Forecasting and Social Change, Elsevier, vol. 179(C).

  3. John S. Liu & Louis Y. Y. Lu & Mei Hsiu-Ching Ho, 2019. "A few notes on main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 379-391, April.

    Cited by:

    1. Fan Zeng & Stacy Hyun Nam Lee & Chris Kwan Yu Lo, 2020. "The Role of Information Systems in the Sustainable Development of Enterprises: A Systematic Literature Network Analysis," Sustainability, MDPI, vol. 12(8), pages 1-29, April.
    2. Kuang-Sheng Liu & Ming-Hung Lin, 2021. "Performance Assessment on the Application of Artificial Intelligence to Sustainable Supply Chain Management in the Construction Material Industry," Sustainability, MDPI, vol. 13(22), pages 1-15, November.
    3. Flavia Filippin, 2021. "Do main paths reflect technological trajectories? Applying main path analysis to the semiconductor manufacturing industry," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6443-6477, August.
    4. Alessandri, Enrico, 2023. "Identifying technological trajectories in the mining sector using patent citation networks," Resources Policy, Elsevier, vol. 80(C).
    5. Kim, Erin H.J. & Jeong, Yoo Kyung & Kim, YongHwan & Song, Min, 2022. "Exploring scientific trajectories of a large-scale dataset using topic-integrated path extraction," Journal of Informetrics, Elsevier, vol. 16(1).
    6. Shuo Xu & Liyuan Hao & Xin An & Hongshen Pang & Ting Li, 2020. "Review on emerging research topics with key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 607-624, January.
    7. Chen, Liang & Xu, Shuo & Zhu, Lijun & Zhang, Jing & Xu, Haiyun & Yang, Guancan, 2022. "A semantic main path analysis method to identify multiple developmental trajectories," Journal of Informetrics, Elsevier, vol. 16(2).
    8. Na Liu & Philip Shapira & Xiaoxu Yue & Jiancheng Guan, 2021. "Mapping technological innovation dynamics in artificial intelligence domains: Evidence from a global patent analysis," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-20, December.
    9. Xiaorui Jiang & Junjun Liu, 2023. "Extracting the evolutionary backbone of scientific domains: The semantic main path network analysis approach based on citation context analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(5), pages 546-569, May.
    10. Jakob Hoffmann & Johannes Glückler, 2023. "Technological Cohesion and Convergence: A Main Path Analysis of the Bioeconomy, 1900–2020," Sustainability, MDPI, vol. 15(16), pages 1-17, August.
    11. Yu, Dejian & Sheng, Libo, 2021. "Influence difference main path analysis: Evidence from DNA and blockchain domain citation networks," Journal of Informetrics, Elsevier, vol. 15(4).
    12. Stacy H. Lee & Yang Zhou, 2022. "The Outlook for Sustainable Development Goals in Business and Management: A Systematic Literature Review and Keyword Cluster Analysis," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
    13. Dejian Yu & Libo Sheng, 2020. "Knowledge diffusion paths of blockchain domain: the main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 471-497, October.
    14. Song-Chia Hsu & Kai-Ying Chen & Chih-Ping Lin & Wei-Hao Su, 2022. "Knowledge Development Trajectories of Crime Prevention Domain: An Academic Study Based on Citation and Main Path Analysis," IJERPH, MDPI, vol. 19(17), pages 1-20, August.
    15. Kuan, Chung-Huei & Chen, Dar-Zen & Huang, Mu-Hsuan, 2020. "The overlooked citations: Investigating the impact of ignoring citations to published patent applications," Journal of Informetrics, Elsevier, vol. 14(1).
    16. Lai, Kuei-Kuei & Bhatt, Priyanka C. & Kumar, Vimal & Chen, Hsueh-Chen & Chang, Yu-Hsin & Su, Fang-Pei, 2021. "Identifying the impact of patent family on the patent trajectory: A case of thin film solar cells technological trajectories," Journal of Informetrics, Elsevier, vol. 15(2).
    17. Chung-Huei Kuan, 2020. "Regarding weight assignment algorithms of main path analysis and the conversion of arc weights to node weights," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 775-782, July.
    18. Yu, Dejian & Pan, Tianxing, 2021. "Tracing the main path of interdisciplinary research considering citation preference: A case from blockchain domain," Journal of Informetrics, Elsevier, vol. 15(2).
    19. Liao, Shu-Chun & Chou, Tzu-Chuan & Huang, Chen-Hao, 2022. "Revisiting the development trajectory of the digital divide: A main path analysis approach," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    20. Abderahman Rejeb & Alireza Abdollahi & Karim Rejeb & Mohamed M. Mostafa, 2023. "Tracing knowledge evolution flows in scholarly restaurant research: a main path analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2183-2209, June.
    21. Huang, Chen-Hao & Liu, John S. & Ho, Mei Hsiu-Ching & Chou, Tzu-Chuan, 2022. "Towards more convergent main paths: A relevance-based approach," Journal of Informetrics, Elsevier, vol. 16(3).
    22. Bhatt, Priyanka C. & Lai, Kuei-Kuei & Drave, Vinayak A. & Lu, Tzu-Chuen & Kumar, Vimal, 2023. "Patent analysis based technology innovation assessment with the lens of disruptive innovation theory: A case of blockchain technological trajectories," Technological Forecasting and Social Change, Elsevier, vol. 196(C).

  4. Mei Hsiu-Ching Ho & John S. Liu & Kerr C.-T. Chang, 2017. "To include or not: the role of review papers in citation-based analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 65-76, January.

    Cited by:

    1. Petr Praus, 2023. "Empirical relationship between the number of review and research articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2201-2209, April.
    2. Clemens Blümel & Alexander Schniedermann, 2020. "Studying review articles in scientometrics and beyond: a research agenda," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 711-728, July.
    3. Dejian Yu & Libo Sheng, 2020. "Knowledge diffusion paths of blockchain domain: the main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 471-497, October.
    4. Paulo Henrique Santos Gonçalves & Thiago Gonçalves-Souza & Ulysses Paulino Albuquerque, 2020. "Chronic anthropogenic disturbances in ecology: a bibliometric approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 1103-1117, May.
    5. Martin Eling & Omid Ghavibazoo, 2019. "Research on long-term care insurance: status quo and directions for future research," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 44(2), pages 303-356, April.
    6. John S. Liu & Louis Y. Y. Lu & Mei Hsiu-Ching Ho, 2019. "A few notes on main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 379-391, April.
    7. Hansin Bilgili & Jonathan L. Johnson & Tsvetomira V. Bilgili & Alan E. Ellstrand, 2022. "Research on social relationships and processes governing the behaviors of members of the corporate elite: a review and bibliometric analysis," Review of Managerial Science, Springer, vol. 16(8), pages 2285-2339, November.
    8. Saeed Samiee & Brian R. Chabowski, 2021. "Knowledge structure in product- and brand origin–related research," Journal of the Academy of Marketing Science, Springer, vol. 49(5), pages 947-968, September.

  5. Mei Hsiu-Ching Ho & John S. Liu & Max C.-H. Kuan, 2016. "Torn between Academic Publications and University–Industry Collaboration," Research Evaluation, Oxford University Press, vol. 25(2), pages 151-160.

    Cited by:

    1. Chi-Yo Huang & Min-Jen Yang & Jeen-Fong Li & Hueiling Chen, 2021. "A DANP-Based NDEA-MOP Approach to Evaluating the Patent Commercialization Performance of Industry–Academic Collaborations," Mathematics, MDPI, vol. 9(18), pages 1-26, September.
    2. Andrea Bonaccorsi & Brigida Blasi & Carmela Anna Nappi & Sandra Romagnosi, 2022. "Quality of research as source and signal: revisiting the valorization process beyond substitution vs complementarity," The Journal of Technology Transfer, Springer, vol. 47(2), pages 407-434, April.
    3. Alexandre Dias & Beatriz Selan, 2023. "How does university-industry collaboration relate to research resources and technical-scientific activities? An analysis at the laboratory level," The Journal of Technology Transfer, Springer, vol. 48(1), pages 392-415, February.
    4. Soo Jeung Lee, 2019. "Academic entrepreneurship: exploring the effects of academic patenting activity on publication and collaboration among heterogeneous researchers in South Korea," The Journal of Technology Transfer, Springer, vol. 44(6), pages 1993-2013, December.
    5. Huan Li & Xi Yang & Xinlan Cai, 2022. "Academic spin-off activities and research performance: the mediating role of research collaboration," The Journal of Technology Transfer, Springer, vol. 47(4), pages 1037-1069, August.

  6. John S. Liu & Hsiao-Hui Chen & Mei Hsiu-Ching Ho & Yu-Chen Li, 2014. "Citations with different levels of relevancy: Tracing the main paths of legal opinions," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(12), pages 2479-2488, December.

    Cited by:

    1. Christian Moretti & Blanca Corona & Robert Edwards & Martin Junginger & Alberto Moro & Matteo Rocco & Li Shen, 2020. "Reviewing ISO Compliant Multifunctionality Practices in Environmental Life Cycle Modeling," Energies, MDPI, vol. 13(14), pages 1-24, July.
    2. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    3. Hiran H. Lathabai & Susan George & Thara Prabhakaran & Manoj Changat, 2018. "An integrated approach to path analysis for weighted citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 1871-1904, December.
    4. Xiaorui Jiang & Junjun Liu, 2023. "Extracting the evolutionary backbone of scientific domains: The semantic main path network analysis approach based on citation context analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(5), pages 546-569, May.
    5. Chaomei Chen & Min Song, 2019. "Visualizing a field of research: A methodology of systematic scientometric reviews," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-25, October.
    6. Yu, Dejian & Sheng, Libo, 2021. "Influence difference main path analysis: Evidence from DNA and blockchain domain citation networks," Journal of Informetrics, Elsevier, vol. 15(4).
    7. John S. Liu & Louis Y. Y. Lu & Mei Hsiu-Ching Ho, 2019. "A few notes on main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 379-391, April.
    8. Bruno Miranda Henrique & Vinicius Amorim Sobreiro & Herbert Kimura, 2018. "Building direct citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(2), pages 817-832, May.
    9. Jiang, Xiaorui & Zhuge, Hai, 2019. "Forward search path count as an alternative indirect citation impact indicator," Journal of Informetrics, Elsevier, vol. 13(4).
    10. Yu, Dejian & Pan, Tianxing, 2021. "Tracing the main path of interdisciplinary research considering citation preference: A case from blockchain domain," Journal of Informetrics, Elsevier, vol. 15(2).
    11. Ba, Zhichao & Ma, Yaxue & Cai, Jinyao & Li, Gang, 2023. "A citation-based research framework for exploring policy diffusion: Evidence from China's new energy policies," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    12. Huang, Chen-Hao & Liu, John S. & Ho, Mei Hsiu-Ching & Chou, Tzu-Chuan, 2022. "Towards more convergent main paths: A relevance-based approach," Journal of Informetrics, Elsevier, vol. 16(3).

  7. Mei Ho & John Liu & Wen-Min Lu & Chien-Cheng Huang, 2014. "A new perspective to explore the technology transfer efficiencies in US universities," The Journal of Technology Transfer, Springer, vol. 39(2), pages 247-275, April.

    Cited by:

    1. Soares, Thiago J. & Torkomian, Ana L.V., 2021. "TTO's staff and technology transfer: Examining the effect of employees' individual capabilities," Technovation, Elsevier, vol. 102(C).
    2. Hyensup Shim & Kiyoon Shin, 2021. "Empirical Analysis of Evidence-Based Policymaking in R&D Programmes," Sustainability, MDPI, vol. 14(1), pages 1-15, December.
    3. Benjamin Yeo, 2019. "What Drives University Technological Innovation Outcomes? A Re-Vitalised Investigation," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 18(03), pages 1-28, September.
    4. Shui‐ying Jin & Xiao‐lin Zhou & Yung‐ho Chiu, 2021. "The parent–subsidiary knowledge transfer efficiency of Chinese–African multinational enterprises based on a metafrontier epsilon‐based measure model," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(2), pages 479-492, March.
    5. Wuzhao Xue & Hua Li & Rizwan Ali & Ramiz ur Rehman & Gonzalo Fernández-Sánchez, 2021. "Assessing the Static and Dynamic Efficiency of Scientific Research of HEIs China: Three Stage DEA–Malmquist Index Approach," Sustainability, MDPI, vol. 13(15), pages 1-21, July.
    6. Son, Hosung & Chung, Yanghon & Yoon, Sangpil, 2022. "How can university technology holding companies bridge the Valley of Death? Evidence from Korea," Technovation, Elsevier, vol. 109(C).
    7. H. Pierre Hsieh & Yueh‐Cheng Wu & Wen‐Min Lu & Yao‐Chieh Chen, 2020. "Assessing and ranking the innovation ability and business performance of global companies in the aerospace and defense industry," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(6), pages 952-963, September.
    8. Bai, Xue-Jie & Li, Zhen-Yang & Zeng, Jin, 2020. "Performance evaluation of China's innovation during the industry-university-research collaboration process—an analysis basis on the dynamic network slacks-based measurement model," Technology in Society, Elsevier, vol. 62(C).
    9. Lim, Dong-Joon & Kim, Moon-Su, 2022. "Measuring dynamic efficiency with variable time lag effects," Omega, Elsevier, vol. 108(C).
    10. See, Kok Fong & Ma, Zhanxin & Tian, Yuzhen, 2023. "Examining the efficiency of regional university technology transfer in China: A mixed-integer generalized data envelopment analysis framework," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    11. Shu-Hao Chang, 2018. "A pilot study on the connection between scientific fields and patent classification systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 951-970, March.
    12. Clovia Hamilton & Simon P. Philbin, 2020. "Knowledge Based View of University Tech Transfer—A Systematic Literature Review and Meta-Analysis," Administrative Sciences, MDPI, vol. 10(3), pages 1-28, September.
    13. Xiong, Xi & Yang, Guo-liang & Guan, Zhong-cheng, 2018. "Assessing R&D efficiency using a two-stage dynamic DEA model: A case study of research institutes in the Chinese Academy of Sciences," Journal of Informetrics, Elsevier, vol. 12(3), pages 784-805.
    14. Ma, Ding & Cai, Zhishan & Zhu, Chengkai, 2022. "Technology transfer efficiency of universities in China: A three-stage framework based on the dynamic network slacks-based measurement model," Technology in Society, Elsevier, vol. 70(C).
    15. Alice Bertoletti & Geraint Johnes, 2021. "Efficiency in university-industry collaboration: an analysis of UK higher education institutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7679-7714, September.
    16. Fernández-López, Sara & Rodríguez-Gulías, María Jesús & Dios-Vicente, Adrián & Rodeiro-Pazos, David, 2020. "Individual and joint effect of patenting and exporting on the university spin-offs’ survival," Technology in Society, Elsevier, vol. 62(C).
    17. Dorys Y. Rodríguez-Castro & Juan Aparicio, 2021. "Introducing a functional framework for integrating the empirical evidence about higher education institutions’ functions and capabilities: A literature review," Journal of Entrepreneurship, Management and Innovation, Fundacja Upowszechniająca Wiedzę i Naukę "Cognitione", vol. 17(1), pages 231-267.
    18. Laura Calzada-Infante & Sebastián Lozano, 2022. "Computing multiperiod efficiency using dominance networks," Annals of Operations Research, Springer, vol. 309(1), pages 37-57, February.
    19. Lu, Wen-Min & Kweh, Qian Long & Nourani, Mohammad & Huang, Feng-Wen, 2016. "Evaluating the efficiency of dual-use technology development programs from the R&D and socio-economic perspectives," Omega, Elsevier, vol. 62(C), pages 82-92.
    20. Zhang, Shaopeng & Wang, Xiaohong, 2022. "Does innovative city construction improve the industry–university–research knowledge flow in urban China?," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    21. Hsu, David W.L. & Shen, Yung-Chi & Yuan, Benjamin J.C. & Chou, Chiyan James, 2015. "Toward successful commercialization of university technology: Performance drivers of university technology transfer in Taiwan," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 25-39.

  8. Mei Hsiu-Ching Ho & Vincent H. Lin & John S. Liu, 2014. "Exploring knowledge diffusion among nations: a study of core technologies in fuel cells," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(1), pages 149-171, July.

    Cited by:

    1. Lai, Kuei-Kuei & Chen, Yu-Long & Kumar, Vimal & Daim, Tugrul & Verma, Pratima & Kao, Fang-Chen & Liu, Ruirong, 2023. "Mapping technological trajectories and exploring knowledge sources: A case study of E-payment technologies," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    2. Blandy Pamplona Solis & Julio César Cruz Argüello & Leopoldo Gómez Barba & Mayra Polett Gurrola & Zakaryaa Zarhri & Danna Lizeth TrejoArroyo, 2019. "Bibliometric Analysis of the Mass Transport in a Gas Diffusion Layer in PEM Fuel Cells," Sustainability, MDPI, vol. 11(23), pages 1-18, November.
    3. Xia Cao & Chuanyun Li & Jinqiu Li & Yunchang Li, 2022. "Modeling and simulation of knowledge creation and diffusion in an industry-university-research cooperative innovation network: a case study of China’s new energy vehicles," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 3935-3957, July.
    4. Ying Huang & Donghua Zhu & Yue Qian & Yi Zhang & Alan L. Porter & Yuqin Liu & Ying Guo, 2017. "A hybrid method to trace technology evolution pathways: a case study of 3D printing," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 185-204, April.
    5. Roman Jurowetzki, 2015. "Unpacking Big Systems - Natural Language Processing meets Network Analysis. A Study of Smart Grid Development in Denmark," SPRU Working Paper Series 2015-15, SPRU - Science Policy Research Unit, University of Sussex Business School.
    6. Chi, Yuxue & Tang, Xianyi & Liu, Yijun, 2022. "Exploring the “awakening effect” in knowledge diffusion: a case study of publications in the library and information science domain," Journal of Informetrics, Elsevier, vol. 16(4).
    7. Lai, Kuei-Kuei & Bhatt, Priyanka C. & Kumar, Vimal & Chen, Hsueh-Chen & Chang, Yu-Hsin & Su, Fang-Pei, 2021. "Identifying the impact of patent family on the patent trajectory: A case of thin film solar cells technological trajectories," Journal of Informetrics, Elsevier, vol. 15(2).
    8. Yoonjung An & Mintak Han & Yongtae Park, 2017. "Identifying dynamic knowledge flow patterns of business method patents with a hidden Markov model," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 783-802, November.

  9. Mei Hsiu-Ching Ho & John S. Liu, 2013. "The motivations for knowledge transfer across borders: the diffusion of data envelopment analysis (DEA) methodology," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 397-421, January.

    Cited by:

    1. Shi‐Xiao Wang & Wen‐Min Lu & Shiu‐Wan Hung, 2020. "Improving innovation efficiency of emerging economies: The role of manufacturing," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(4), pages 503-519, June.
    2. Mei Hsiu-Ching Ho & Vincent H. Lin & John S. Liu, 2014. "Exploring knowledge diffusion among nations: a study of core technologies in fuel cells," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(1), pages 149-171, July.
    3. Kairui Zuo & Jiancheng Guan, 2017. "Measuring the R&D efficiency of regions by a parallel DEA game model," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 175-194, July.
    4. José-Antonio Belso-Martínez & Manuel Expósito-Langa, 2015. "Persistence and extinction of brokerage roles in clusters: the role of status, former experiences and extra-cluster relationships," Papers in Evolutionary Economic Geography (PEEG) 1501, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jan 2015.
    5. S. Lozano & L. Calzada-Infante & B. Adenso-Díaz & S. García, 2019. "Complex network analysis of keywords co-occurrence in the recent efficiency analysis literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 609-629, August.
    6. Jiancheng Guan & Kairui Zuo, 2014. "A cross-country comparison of innovation efficiency," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(2), pages 541-575, August.
    7. José Antonio Belso-Martínez & Manuel Expósito-Langa & Francisco Mas-Verdú & F. Xavier Molina-Morales, 2017. "Dynamics of Brokerage Positions in Clusters: Evidence from the Spanish Foodstuffs Industry," Sustainability, MDPI, vol. 9(2), pages 1-18, February.

  10. Liu, John S. & Lu, Louis Y.Y. & Ho, Mei Hsiu-Ching, 2012. "Total influence and mainstream measures for scientific researchers," Journal of Informetrics, Elsevier, vol. 6(4), pages 496-504.

    Cited by:

    1. Chao Min & Qingyu Chen & Erjia Yan & Yi Bu & Jianjun Sun, 2021. "Citation cascade and the evolution of topic relevance," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(1), pages 110-127, January.
    2. Yan, Jianghui & Tseng, Fang-Mei & Lu, Louis Y.Y., 2018. "Developmental trajectories of new energy vehicle research in economic management: Main path analysis," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 168-181.
    3. Jiang, Xiaorui & Zhuge, Hai, 2019. "Forward search path count as an alternative indirect citation impact indicator," Journal of Informetrics, Elsevier, vol. 13(4).

  11. Mei Hsiu-Ching Ho, 2009. "How Regional Innovation Systems Play a Relative Competitive Role Within Knowledge Networks," European Planning Studies, Taylor & Francis Journals, vol. 17(12), pages 1881-1905, December.

    Cited by:

    1. Strand, Øivind & Leydesdorff, Loet, 2013. "Where is synergy indicated in the Norwegian innovation system? Triple-Helix relations among technology, organization, and geography," Technological Forecasting and Social Change, Elsevier, vol. 80(3), pages 471-484.
    2. Hai-Ping Lin & Tai-Shan Hu, 2017. "Knowledge Interaction and Spatial Dynamics in Industrial Districts," Sustainability, MDPI, vol. 9(8), pages 1-18, August.
    3. Zhang, Yi & Chen, Kaihua, 2022. "Network growth dynamics: The simultaneous interaction between network positions and research performance of collaborative organisations," Technovation, Elsevier, vol. 115(C).

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