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What determines how long an innovative spell will last?

Author

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  • Show-Ling Jang

    (National Taiwan University)

  • Jennifer H. Chen

    (Nanhua University)

Abstract

This paper is set out to examine the temporal pattern of innovative activities: what might have affected a firm’s patenting from one period to the next. Based upon data on ‘information technology’ (IT) manufacturing firms in Taiwan covering the years 1990–2001, we develop a survival model to analyze the underlying drivers of patenting duration. Our results indicate that the level of the patent stock at the onset of the patent spell, defined as the number of successive years during which a firm produced at least one patent per year, has a non-linear effect on spell duration. Other factors, such as industrial growth, firm size and firm profitability, have a positive effect on patenting duration, while firm age and spell sequence affect negatively to spell duration. We conclude that state dependence is demonstrated by innovative behavior, yet the advantages gained from such creative accumulation can easily be dissipated, thereby illustrating the transient nature of dynamic capabilities.

Suggested Citation

  • Show-Ling Jang & Jennifer H. Chen, 2011. "What determines how long an innovative spell will last?," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(1), pages 65-76, January.
    • Handle: RePEc:spr:scient:v:86:y:2011:i:1:d:10.1007_s11192-010-0247-z
    DOI: 10.1007/s11192-010-0247-z
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    References listed on IDEAS

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    Cited by:

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    2. Córcoles, David & Triguero, Ángela & Cuerva, María Carmen, 2016. "Comparing persistence of product and process innovation: A discrete-time duration analysis of innovation spells," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 10, pages 1-35.
    3. Rammer, Christian & Schubert, Torben, 2016. "Concentration on the few? R&D and innovation in German firms 2001 to 2013," ZEW Discussion Papers 16-005, ZEW - Leibniz Centre for European Economic Research.
    4. Yagi, Michiyuki & Managi, Shunsuke, 2018. "Shadow price of patent stock as knowledge stock: Time and country heterogeneity," Economic Analysis and Policy, Elsevier, vol. 60(C), pages 43-61.
    5. Juan Máñez & María Rochina-Barrachina & Amparo Sanchis-Llopis & Juan Sanchis-Llopis, 2015. "The determinants of R&D persistence in SMEs," Small Business Economics, Springer, vol. 44(3), pages 505-528, March.
    6. Jinlou Zhao & Hongyu Gao & Yongli Li & Jiaguo Liu, 2017. "Which factors affect the duration of hot topics on social media platforms?," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(5), pages 2395-2407, September.
    7. Fontana, Roberto & Vezzulli, Andrea, 2016. "Technological leadership and persistence in product innovation in the Local Area Network industry 1990–1999," Research Policy, Elsevier, vol. 45(8), pages 1604-1619.

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