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Innovation performance evaluation for high-tech companies using a dynamic network data envelopment analysis approach

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  • Yu, Anyu
  • Shi, Yu
  • You, Jianxin
  • Zhu, Joe

Abstract

This study examines innovation performance of high-tech companies in China, using a dynamic network data envelopment analysis (DEA) approach. The innovation process is decomposed into a research and development (R&D) stage and a commercialization stage. In addition, innovation is conceptualized as a consecutive event that goes through multiple time intervals, requiring a dynamic structure of the methodological framework. Using a newly developed dynamic network DEA, the current study calculates a R&D performance index and a commercialization index for the R&D stage and commercialization stage, respectively. The multi-process innovation system is integrated with dynamic carryover items. This results in a highly non-linear dynamic network DEA model. Second order cone programming and nested partitions strategies are employed to solve the nonlinear dynamic network DEA model. Our empirical study indicates disparities in innovation performance among different Chinese high-tech companies. The innovation heterogeneity and inefficient performance sources are also investigated.

Suggested Citation

  • Yu, Anyu & Shi, Yu & You, Jianxin & Zhu, Joe, 2021. "Innovation performance evaluation for high-tech companies using a dynamic network data envelopment analysis approach," European Journal of Operational Research, Elsevier, vol. 292(1), pages 199-212.
    • Handle: RePEc:eee:ejores:v:292:y:2021:i:1:p:199-212
    DOI: 10.1016/j.ejor.2020.10.011
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    Citations

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    Cited by:

    1. Jacqueline Tsz Yin Lo & Calvin Kam, 2021. "Innovation Performance Indicators for Architecture, Engineering and Construction Organization," Sustainability, MDPI, vol. 13(16), pages 1-25, August.
    2. Chen, Yufeng & Zhang, Shun & Miao, Jiafeng, 2023. "The negative effects of the US-China trade war on innovation: Evidence from the Chinese ICT industry," Technovation, Elsevier, vol. 123(C).
    3. Yang, Yefei & Chen, Jiayi & Lee, Peter K.C. & Cheng, T.C.E., 2023. "How to enhance the effects of the green supply chain management strategy in the organization: A diffusion process perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    4. Wu, Jie & Xu, Guangcheng & Zhu, Qingyuan & Zhang, Chaochao, 2021. "Two-stage DEA models with fairness concern: Modelling and computational aspects," Omega, Elsevier, vol. 105(C).
    5. Andrey V. Lychev & Svetlana V. Ratner & Vladimir E. Krivonozhko, 2023. "Two-Stage Data Envelopment Analysis Models with Negative System Outputs for the Efficiency Evaluation of Government Financial Policies," Mathematics, MDPI, vol. 11(24), pages 1-21, December.
    6. Shu-Chuan Chen & Da-Sheng Lee & Chien-Yi Huang, 2021. "Evaluating the Sustainable Operating Performance of Electronics Industry Groups: Taiwanese Firms in Mainland China," Sustainability, MDPI, vol. 13(21), pages 1-28, October.
    7. Chen, Xiaoqing & Liu, Xinwang & Zhu, Qingyuan, 2022. "Comparative analysis of total factor productivity in China's high-tech industries," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    8. Xiaoqing Chen & Xinwang Liu, 2023. "Comparing Malmquist and Hicks–Moorsteen productivity changes in China’s high-tech industries: exploring convexity implications," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(4), pages 1209-1237, December.
    9. Bresciani, Stefano & Puertas, Rosa & Ferraris, Alberto & Santoro, Gabriele, 2021. "Innovation, environmental sustainability and economic development: DEA-Bootstrap and multilevel analysis to compare two regions," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    10. Svetlana V. Ratner & Artem M. Shaposhnikov & Andrey V. Lychev, 2023. "Network DEA and Its Applications (2017–2022): A Systematic Literature Review," Mathematics, MDPI, vol. 11(9), pages 1-24, May.
    11. Yang, Jiawei & Li, Yuanyu & Fang, Lei, 2023. "Financing capacity planning with environmental considerations: A non-parametric analysis," Omega, Elsevier, vol. 118(C).
    12. Lim, Dong-Joon & Kim, Moon-Su, 2022. "Measuring dynamic efficiency with variable time lag effects," Omega, Elsevier, vol. 108(C).
    13. Sueyoshi, Toshiyuki & Ryu, Youngbok, 2022. "Performance assessment on technology transition from small businesses to the U.S. Department of Defense," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    14. Han, Jing & Guo, Ju-E & Cai, Xun & Lv, Cheng & Lev, Benjamin, 2022. "An analysis on strategy evolution of research & development in cooperative innovation network of new energy vehicle within policy transition period," Omega, Elsevier, vol. 112(C).
    15. Chen, Hao, 2022. "Industrial production evaluation with the consideration of technology accumulation," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 72-84.
    16. Amir Hossein Azadnia & Simon Stephens & Pezhman Ghadimi & George Onofrei, 2022. "A comprehensive performance measurement framework for business incubation centres: Empirical evidence in an Irish context," Business Strategy and the Environment, Wiley Blackwell, vol. 31(5), pages 2437-2455, July.
    17. Shiping Mao & Marios Dominikos Kremantzis & Leonidas Sotirios Kyrgiakos & George Vlontzos, 2022. "R&D Performance Evaluation in the Chinese Food Manufacturing Industry Based on Dynamic DEA in the COVID-19 Era," Agriculture, MDPI, vol. 12(11), pages 1-19, November.
    18. Yu, Anyu & Zhang, Qin & Yu, Rongjian & Cheng, Yu, 2023. "More is better or in waste? A resource allocation measure of government grants for facilitating firm innovations," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    19. Fariba Goodarzian & Ali Navaei & Behdad Ehsani & Peiman Ghasemi & Jesús Muñuzuri, 2023. "Designing an integrated responsive-green-cold vaccine supply chain network using Internet-of-Things: artificial intelligence-based solutions," Annals of Operations Research, Springer, vol. 328(1), pages 531-575, September.
    20. Zhang, Chunyang & Zhang, Dongsheng, 2023. "Executive incentives, team stability and corporate innovation performance," Finance Research Letters, Elsevier, vol. 58(PD).
    21. Yu Zhu & Feng Yang & Bengang Gong & Wei Zeng, 2023. "RETRACTED ARTICLE: Assessing the efficiency of innovation entities in China: evidence from a nonhomogeneous data envelopment analysis and Tobit," Electronic Commerce Research, Springer, vol. 23(1), pages 175-205, March.
    22. Fanshun Zhang & Zhuorui Zhang & Quanquan Zhang & Xiaochun Zhu, 2023. "Dynamic Evaluation of Product Innovation Knowledge Concerning the Interactive Relationship between Innovative Subjects: A Multi-Objective Optimization Approach," Mathematics, MDPI, vol. 11(9), pages 1-33, April.
    23. Yang, Yefei & Yee, Rachel W.Y., 2022. "The effect of process digitalization initiative on firm performance: A dynamic capability development perspective," International Journal of Production Economics, Elsevier, vol. 254(C).

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