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Productive performance based on R&D activities of low-tech firms: an antecedent of the decision to export?

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  • Areti Gkypali
  • Kostas Tsekouras

Abstract

We argue that technical efficiency, when R&D stock is considered as a crucial resource, reflects the effectiveness of the underlying firm governance mechanism which transforms competencies into capabilities. We argue that for the case of low-tech R&D active firms (i) their R&D-based productive performance and their decision to export are endogenously related 'due to self-selection', (ii) the examined low-tech R&D active firms are dichotomized in two regimes, exporters and non-exporters, and (iii) the role of innovation patterns is a premise in determining low-tech firms' R&D-based productive performance and export decision-making. We provide empirical evidence on the above hypotheses exploiting information from a unique data set regarding Greek low-tech R&D active manufacturing firms and adopting bootstrap data envelopment analysis techniques as well as an appropriate endogenous switching regressions, of the Mover-Stayer type, econometric model.

Suggested Citation

  • Areti Gkypali & Kostas Tsekouras, 2015. "Productive performance based on R&D activities of low-tech firms: an antecedent of the decision to export?," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 24(8), pages 801-828, November.
    • Handle: RePEc:taf:ecinnt:v:24:y:2015:i:8:p:801-828
    DOI: 10.1080/10438599.2015.1006041
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    Citations

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    Cited by:

    1. Gkypali, Areti & Arvanitis, Spyros & Tsekouras, Kostas, 2018. "Absorptive capacity, exporting activities, innovation openness and innovation performance: A SEM approach towards a unifying framework," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 143-155.
    2. Dmitriy Grigorievich Rodionov* & Evgenii Alexandrovich Konnikov & Olga Anatolievna Konnikova, 2018. "Approaches to Ensuring the Sustainability of Industrial Enterprises of Different Technological Levels," The Journal of Social Sciences Research, Academic Research Publishing Group, pages 277-282:3.
    3. Alex Coad & Nanditha Mathew & Emanuele Pugliese, 2017. "What's good for the goose ain't good for the gander: cock-eyed counterfactuals and the performance effects of R&D," LEM Papers Series 2017/21, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    4. Gkypali, Areti & Filiou, Despoina & Tsekouras, Kostas, 2017. "R&D collaborations: Is diversity enhancing innovation performance?," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 143-152.
    5. Jiahui Xu & Chee-Pung Ng & Toong Hai Sam & Asokan Vasudevan & Poh Kiong Tee & Alex Hou Hong Ng & Wong Chee Hoo, 2023. "Fiscal and Tax Policies, Access to External Financing and Green Innovation Efficiency: An Evaluation of Chinese Listed Firms," Sustainability, MDPI, vol. 15(15), pages 1-19, July.
    6. Zhao, Chuanmin & Qu, Xi & Luo, Shougui, 2019. "Impact of the InnoCom program on corporate innovation performance in China: Evidence from Shanghai," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 103-118.
    7. Vassilis Kanellopoulos & Kostas Tsekouras, 2023. "Innovation efficiency and firm performance in a benchmarking context," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(1), pages 137-151, January.
    8. Gabriele Pellegrino & Mariacristina Piva, 2020. "Innovation, industry and firm age: are there new knowledge production functions?," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 10(1), pages 65-95, March.
    9. Sreejith Aravindakshan & Frederick Rossi & T. S. Amjath-Babu & Prakashan Chellattan Veettil & Timothy J. Krupnik, 2018. "Application of a bias-corrected meta-frontier approach and an endogenous switching regression to analyze the technical efficiency of conservation tillage for wheat in South Asia," Journal of Productivity Analysis, Springer, vol. 49(2), pages 153-171, June.

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