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Entry strategies in an emerging technology: a pilot web-based study of graphene firms

Author

Listed:
  • Sanjay K. Arora

    (Georgia Institute of Technology)

  • Jan Youtie

    (Georgia Institute of Technology)

  • Philip Shapira

    (Georgia Institute of Technology
    University of Manchester)

  • Lidan Gao

    (Chengdu Library of the Chinese Academy of Sciences)

  • TingTing Ma

    (Beijing Institute of Technology)

Abstract

We explore pilot web-based methods to probe the strategies followed by new small and medium-sized technology-based firms as they seek to commercialize emerging technologies. Tracking and understanding the behavior of such early commercial entrants is not straightforward because smaller firms with limited resources do not always widely engage in readily visible and accessible activities such as publishing and patenting. However, many new firms, even if small, present information about themselves that is available online. Focusing on the early commercialization of novel graphene technologies, we introduce a “web scraping” approach to systematically capture information contained in the online web pages of a sample of small and medium-sized high technology graphene firms in the US, UK, and China. We analyze this information and devise measures that gauge how firm specialization in the target technology impacts overall market orientation. Three groups of graphene enterprises are identified which vary by their focus on product development, materials development, and integration into existing product portfolios. Country-level factors are important in understanding these early diverging commercial approaches in the nascent graphene market. We consider management and policy implications of our findings, and discuss the value, including strengths and weaknesses, of web scraping as an additional information source on enterprise strategies in emerging technologies.

Suggested Citation

  • Sanjay K. Arora & Jan Youtie & Philip Shapira & Lidan Gao & TingTing Ma, 2013. "Entry strategies in an emerging technology: a pilot web-based study of graphene firms," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(3), pages 1189-1207, June.
  • Handle: RePEc:spr:scient:v:95:y:2013:i:3:d:10.1007_s11192-013-0950-7
    DOI: 10.1007/s11192-013-0950-7
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    References listed on IDEAS

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    Cited by:

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    2. Jan Kinne & Janna Axenbeck, 2020. "Web mining for innovation ecosystem mapping: a framework and a large-scale pilot study," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2011-2041, December.
    3. MOTOHASHI Kazuyuki, 2023. "Identifying Technology Opportunity Using a Dual-attention Model and a Technology-market Concordance Matrix," Discussion papers 23024, Research Institute of Economy, Trade and Industry (RIETI).
    4. Xu, Haiyun & Winnink, Jos & Yue, Zenghui & Zhang, Huiling & Pang, Hongshen, 2021. "Multidimensional Scientometric indicators for the detection of emerging research topics," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    5. Sanjay K. Arora & Yin Li & Jan Youtie & Philip Shapira, 2020. "Measuring dynamic capabilities in new ventures: exploring strategic change in US green goods manufacturing using website data," The Journal of Technology Transfer, Springer, vol. 45(5), pages 1451-1480, October.
    6. Rammer, Christian & Es-Sadki, Nordine, 2023. "Using big data for generating firm-level innovation indicators - a literature review," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    7. Veronika Belousova & Oxana Bondarenko & Nikolay Chichkanov & Denis Lebedev & Ian Miles, 2022. "Coping with Greenhouse Gas Emissions: Insights from Digital Business Services," Energies, MDPI, vol. 15(8), pages 1-26, April.
    8. Kinne, Jan & Axenbeck, Janna, 2018. "Web mining of firm websites: A framework for web scraping and a pilot study for Germany," ZEW Discussion Papers 18-033, ZEW - Leibniz Centre for European Economic Research.
    9. Krzysztof Klincewicz, 2016. "The emergent dynamics of a technological research topic: the case of graphene," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 319-345, January.
    10. Blazquez, Desamparados & Domenech, Josep, 2018. "Big Data sources and methods for social and economic analyses," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 99-113.
    11. Janna Axenbeck & Patrick Breithaupt, 2021. "Innovation indicators based on firm websites—Which website characteristics predict firm-level innovation activity?," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-23, April.
    12. Li, Yin & Arora, Sanjay & Youtie, Jan & Shapira, Philip, 2018. "Using web mining to explore Triple Helix influences on growth in small and mid-size firms," Technovation, Elsevier, vol. 76, pages 3-14.
    13. Motohashi, Kazuyuki & Zhu, Chen, 2023. "Identifying technology opportunity using dual-attention model and technology-market concordance matrix," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    14. Axenbeck, Janna & Breithaupt, Patrick, 2019. "Web-based innovation indicators: Which firm website characteristics relate to firm-level innovation activity?," ZEW Discussion Papers 19-063, ZEW - Leibniz Centre for European Economic Research.
    15. Desamparados Blazquez & Josep Domenech & Jose-Maria Garcia-Alvarez-Coque, 2018. "Assessing Technology Platforms for Sustainability with Web Data Mining Techniques," Sustainability, MDPI, vol. 10(12), pages 1-15, November.
    16. Xu, Shuo & Hao, Liyuan & Yang, Guancan & Lu, Kun & An, Xin, 2021. "A topic models based framework for detecting and forecasting emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    17. Abdullah Gök & Alec Waterworth & Philip Shapira, 2015. "Use of web mining in studying innovation," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 653-671, January.

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    More about this item

    Keywords

    Emerging technology; Graphene; Small and medium enterprise; Commercialization; Market entry; Web scraping; United States; United Kingdom; China;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • M13 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - New Firms; Startups
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries
    • Z18 - Other Special Topics - - Cultural Economics - - - Public Policy

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