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R&D, productivity, and market value: An empirical study from high-technology firms


  • Wang, Chun-Hsien
  • Lu, Yung-Hsiang
  • Huang, Chin-Wei
  • Lee, Jun-Yen


Although prior research has addressed the influence of production activity and research and development (R&D) on productivity, it is not clear whether production and R&D affect the market value of a firm. This study proposes and verifies an R&D value chain framework to explore the relationship among productivity, R&D, and firm market values, as measured by Tobin's q theory. By doing so, we attempt to link new theoretical insights and empirical evidence on the effects of R&D efforts and basic production activities to the market valuations of high-technology firms. The value chain data envelopment analysis approach was proposed to estimate parallel-serial processes of basic operations and R&D efforts. This approach can be used to simultaneously estimate the profitability efficiency and marketability efficiency of high-technology firms. This area has rarely been studied, but it is particularly important for high-technology R&D policies and for further industrial development. Using the R&D value chain perspectives of model innovations and extensions proposed in several previous studies, we examined the appropriate levels of intermediate outputs. Production efficiency and R&D were combined to estimate the appropriate levels of intermediate outputs for high-technology firms. Based on the intermediate output analyses, we developed an R&D efforts decision matrix to explore and identify operational and R&D efficiency for high-technology firms. Our sample firms are displayed on a four-quadrant action grid that provides visual information on current short-term operational efficiency and decision making on long-term R&D strategic positions. The empirical findings from the R&D value chain model can provide information for policymakers and managers and suggest the adoption of various policies that place more emphasis on profitability and marketability strategies.

Suggested Citation

  • Wang, Chun-Hsien & Lu, Yung-Hsiang & Huang, Chin-Wei & Lee, Jun-Yen, 2013. "R&D, productivity, and market value: An empirical study from high-technology firms," Omega, Elsevier, vol. 41(1), pages 143-155.
  • Handle: RePEc:eee:jomega:v:41:y:2013:i:1:p:143-155 DOI: 10.1016/

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    References listed on IDEAS

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    Cited by:

    1. Chandan Sharma, 2016. "R&D, Technology Transfer And Productivity In The Indian Pharmaceutical Industry," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 20(01), pages 1-24, January.
    2. Kwon, He-Boong, 2017. "Exploring the predictive potential of artificial neural networks in conjunction with DEA in railroad performance modeling," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 159-170.
    3. Lee, Jooh & Kwon, He-Boong, 2017. "Progressive performance modeling for the strategic determinants of market value in the high-tech oriented SMEs," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 91-102.
    4. repec:eee:touman:v:65:y:2018:i:c:p:303-316 is not listed on IDEAS
    5. repec:gam:jsusta:v:9:y:2017:i:11:p:1964-:d:116709 is not listed on IDEAS
    6. Huang, Chin-wei & Ho, Foo Nin & Chiu, Yung-ho, 2014. "Measurement of tourist hotels׳ productive efficiency, occupancy, and catering service effectiveness using a modified two-stage DEA model in Taiwan," Omega, Elsevier, vol. 48(C), pages 49-59.
    7. Hyeokseong Lee & Namil Kim & Kiho Kwak & Wonjoon Kim & Hyungjoon Soh & Kyungbae Park, 2016. "Diffusion Patterns in Convergence among High-Technology Industries: A Co-Occurrence-Based Analysis of Newspaper Article Data," Sustainability, MDPI, Open Access Journal, vol. 8(10), pages 1-18, October.
    8. Wang, Qunwei & Hang, Ye & Sun, Licheng & Zhao, Zengyao, 2016. "Two-stage innovation efficiency of new energy enterprises in China: A non-radial DEA approach," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 254-261.
    9. Yu, Ming-Miin & Chen, Li-Hsueh & Hsiao, Bo, 2016. "Dynamic performance assessment of bus transit with the multi-activity network structure," Omega, Elsevier, vol. 60(C), pages 15-25.


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