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Evaluating the performance of biotechnology companies by causal recipes

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  • Huang, Chieh-Wei
  • Huarng, Kun-Huang

Abstract

This study empirically investigates six variables and their combinations that may affect revenues of Taiwan's biotechnology industry. Examine variables include annual government investment, annual private investment, number of national biotechnology incubator yearly, number of manufacturers that biotechnology incubators foster yearly, number of patents that listed companies own yearly, and listed companies' annual R&D expenses. Using original and incremental Taiwanese data, this study contrasts conventional multiple regression analysis (MRA) of net effects and fuzzy-set qualitative comparative analysis (fsQCA) of causal complexities. Results indicate that fsQCA outperforms MRA and successfully models both types of data with causal complexities.

Suggested Citation

  • Huang, Chieh-Wei & Huarng, Kun-Huang, 2015. "Evaluating the performance of biotechnology companies by causal recipes," Journal of Business Research, Elsevier, vol. 68(4), pages 851-856.
    • Handle: RePEc:eee:jbrese:v:68:y:2015:i:4:p:851-856
    DOI: 10.1016/j.jbusres.2014.11.040
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    Cited by:

    1. Yang, Chih-Ching, 2016. "Correlation coefficient evaluation for the fuzzy interval data," Journal of Business Research, Elsevier, vol. 69(6), pages 2138-2144.
    2. Hakim Lyngstadaas, 2020. "Packages or systems? Working capital management and financial performance among listed U.S. manufacturing firms," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 31(4), pages 403-450, December.
    3. Huang, Kuo-En & Wu, Jih-Hwa & Lu, Shiau-Yun & Lin, Yi-Chia, 2016. "Innovation and technology creation effects on organizational performance," Journal of Business Research, Elsevier, vol. 69(6), pages 2187-2192.
    4. Ho, Joanne & Plewa, Carolin & Lu, Vinh Nhat, 2016. "Examining strategic orientation complementarity using multiple regression analysis and fuzzy set QCA," Journal of Business Research, Elsevier, vol. 69(6), pages 2199-2205.
    5. Sascha Kraus & Domingo Ribeiro-Soriano & Miriam Schüssler, 2018. "Fuzzy-set qualitative comparative analysis (fsQCA) in entrepreneurship and innovation research – the rise of a method," International Entrepreneurship and Management Journal, Springer, vol. 14(1), pages 15-33, March.
    6. Leischnig, Alexander & Kasper-Brauer, Kati, 2016. "How to sell in diverse markets? A two-level approach to industry factors and selling factors for explaining firm profitability," Journal of Business Research, Elsevier, vol. 69(4), pages 1307-1313.
    7. Jenson, Ian & Leith, Peat & Doyle, Richard & West, Jonathan & Miles, Morgan P., 2016. "Testing innovation systems theory using Qualitative Comparative Analysis," Journal of Business Research, Elsevier, vol. 69(4), pages 1283-1287.
    8. Vizcaíno, Marcos & Chousa, Juan P., 2016. "Analyzing the influence of the funds' support on Tobin's q using SEM and fsQCA," Journal of Business Research, Elsevier, vol. 69(6), pages 2118-2124.
    9. Lin, Feng-Jyh & Wu, Shang-He & Hsu, Maw-Shin & Perng, Chyuan, 2016. "The determinants of government-sponsored R&D alliances," Journal of Business Research, Elsevier, vol. 69(11), pages 5192-5195.

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