IDEAS home Printed from https://ideas.repec.org/a/spr/opmare/v15y2022i3d10.1007_s12063-022-00280-w.html
   My bibliography  Save this article

RETRACTED ARTICLE: Efficiency evaluation of the high-tech industry chain with a two-stage data envelopment analysis approach

Author

Listed:
  • Jing Feng

    (Tiangong University)

  • Longlong Geng

    (Tiangong University)

  • Hui Liu

    (Tiangong University)

  • Xuehua Zhang

    (Tiangong University)

Abstract

The efficiency evaluation of the high-tech industrial chain was crucial to optimize the regional industrial structure and improve economic development quality. This paper used the two-stage correlation DEA method to evaluate the efficiency of the high-tech industrial chain in the Beijing-Tianjin-Hebei region and constructed a Tobit regression model to study the external factors of the efficiency in each stage. The results were presented as follows. First, the low efficiency of the high-tech industry chain was caused by the low efficiency in the industrialization stage. Second, the average overall efficiency of high-tech industrial chain in the three regions was the highest in Hebei Province, followed by Tianjin city, and the lowest in Beijing city, while the mean efficiency in the innovation stage was the highest in Tianjin city, followed by Beijing city and the lowest in Hebei Province, and the mean efficiency in the industrialization stage was the highest in Hebei Province, followed by Beijing city and the lowest in Tianjin city. The final analysis concluded that the level of economic development, industrial structure, property rights structure, financial support, and educational support were important external factors that influenced the efficiency of the industrialization stage. These findings provided policy recommendations for high-tech development in the Beijing-Tianjin-Hebei region.

Suggested Citation

  • Jing Feng & Longlong Geng & Hui Liu & Xuehua Zhang, 2022. "RETRACTED ARTICLE: Efficiency evaluation of the high-tech industry chain with a two-stage data envelopment analysis approach," Operations Management Research, Springer, vol. 15(3), pages 1071-1080, December.
  • Handle: RePEc:spr:opmare:v:15:y:2022:i:3:d:10.1007_s12063-022-00280-w
    DOI: 10.1007/s12063-022-00280-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12063-022-00280-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s12063-022-00280-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
    2. Zoltan J. Acs & David B. Audretsch, 2008. "Innovation in Large and Small Firms: An Empirical Analysis," Chapters, in: Entrepreneurship, Growth and Public Policy, chapter 1, pages 3-15, Edward Elgar Publishing.
    3. Dongphil Chun & Yanghon Chung & Chungwon Woo & Hangyeol Seo & Hyesoo Ko, 2015. "Labor Union Effects on Innovation and Commercialization Productivity: An Integrated Propensity Score Matching and Two-Stage Data Envelopment Analysis," Sustainability, MDPI, vol. 7(5), pages 1-19, April.
    4. Cruz-Cázares, Claudio & Bayona-Sáez, Cristina & García-Marco, Teresa, 2013. "You can’t manage right what you can’t measure well: Technological innovation efficiency," Research Policy, Elsevier, vol. 42(6), pages 1239-1250.
    5. Horta, I.M. & Camanho, A.S. & Moreira da Costa, J., 2012. "Performance assessment of construction companies: A study of factors promoting financial soundness and innovation in the industry," International Journal of Production Economics, Elsevier, vol. 137(1), pages 84-93.
    6. Prieto, Angel M. & Zofio, Jose L., 2007. "Network DEA efficiency in input-output models: With an application to OECD countries," European Journal of Operational Research, Elsevier, vol. 178(1), pages 292-304, April.
    7. Chunguang Quan & Shasha Yu & Xiaojuan Cheng & Feiyue Liu, 2022. "Comprehensive efficiency evaluation of social responsibility of Chinese listed logistics enterprises based on DEA-Malmquist model," Operations Management Research, Springer, vol. 15(3), pages 1383-1398, December.
    8. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    9. Kao, Chiang & Hwang, Shiuh-Nan, 2011. "Decomposition of technical and scale efficiencies in two-stage production systems," European Journal of Operational Research, Elsevier, vol. 211(3), pages 515-519, June.
    10. Li, Lan-bing & Liu, Bing-lian & Liu, Wei-lin & Chiu, Yung-Ho, 2017. "Efficiency evaluation of the regional high-tech industry in China: A new framework based on meta-frontier dynamic DEA analysis," Socio-Economic Planning Sciences, Elsevier, vol. 60(C), pages 24-33.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Bin & Luo, Yuan & Chiu, Yung-Ho, 2019. "Efficiency evaluation of China's high-tech industry with a multi-activity network data envelopment analysis approach," Socio-Economic Planning Sciences, Elsevier, vol. 66(C), pages 2-9.
    2. Lin, Tzu-Yu & Chiu, Sheng-Hsiung & Yang, Hai-Lan, 2022. "Performance evaluation for regional innovation systems development in China based on the two-stage SBM-DNDEA model," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    3. Wen-Min Lu & Qian Long Kweh & Kai-Chu Yang, 2022. "Multiplicative efficiency aggregation to evaluate Taiwanese local auditing institutions performance," Annals of Operations Research, Springer, vol. 315(2), pages 1243-1262, August.
    4. Khalili-Damghani, Kaveh & Tavana, Madjid & Santos-Arteaga, Francisco J. & Mohtasham, Sima, 2015. "A dynamic multi-stage data envelopment analysis model with application to energy consumption in the cotton industry," Energy Economics, Elsevier, vol. 51(C), pages 320-328.
    5. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    6. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2022. "Innovation efficiency and technology heterogeneity within China's new energy vehicle industry: A two-stage NSBM approach embedded in a three-hierarchy meta-frontier framework," Energy Policy, Elsevier, vol. 161(C).
    7. Suhyeon Han & Shinyoung Park & Sejin An & Wonjun Choi & Mina Lee, 2023. "Research on Analyzing the Efficiency of R&D Projects for Climate Change Response Using DEA–Malmquist," Sustainability, MDPI, vol. 15(10), pages 1-23, May.
    8. Zanella, Andreia & Camanho, Ana S. & Dias, Teresa G., 2015. "Undesirable outputs and weighting schemes in composite indicators based on data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 245(2), pages 517-530.
    9. Peter Fernandes Wanke & Rebecca de Mattos, 2014. "Capacity Issues and Efficiency Drivers in Brazilian Bulk Terminals," Brazilian Business Review, Fucape Business School, vol. 11(5), pages 72-98, October.
    10. Chen, Ping-Chuan & Hung, Shiu-Wan, 2016. "An actor-network perspective on evaluating the R&D linking efficiency of innovation ecosystems," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 303-312.
    11. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.
    12. Alberca-Oliver, Pilar & Rodríguez-Oromendía, Ainhoa & Parte-Esteban, Laura, 2015. "Measuring the efficiency of trade shows: A Spanish case study," Tourism Management, Elsevier, vol. 47(C), pages 127-137.
    13. Muhammet Enis Bulak & Murat Kucukvar, 2022. "How ecoefficient is European food consumption? A frontier‐based multiregional input–output analysis," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(5), pages 817-832, October.
    14. Alessandra Cepparulo & Gilles Mourre, 2020. "How and How Much? The Growth-Friendliness of Public Spending through the Lens," European Economy - Discussion Papers 132, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    15. Peyrache, Antonio & Rose, Christiern & Sicilia, Gabriela, 2020. "Variable selection in Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 282(2), pages 644-659.
    16. E G Gomes & M P E Lins, 2008. "Modelling undesirable outputs with zero sum gains data envelopment analysis models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(5), pages 616-623, May.
    17. Richard Simper & Maximilian J.B. Hall & Wenbin B. Liu & Valentin Zelenyuk & Zhongbao Zhou, 2014. "How Relevant is the Choice of Risk Management Control Variable to Non-parametric Bank Profit Efficiency Analysis?," CEPA Working Papers Series WP122014, School of Economics, University of Queensland, Australia.
    18. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    19. Ti-An Chen, 2022. "Business Performance Evaluation for Tourism Factory: Using DEA Approach and Delphi Method," Sustainability, MDPI, vol. 14(15), pages 1-19, July.
    20. H. Pierre Hsieh & Yueh‐Cheng Wu & Wen‐Min Lu & Yao‐Chieh Chen, 2020. "Assessing and ranking the innovation ability and business performance of global companies in the aerospace and defense industry," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(6), pages 952-963, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:opmare:v:15:y:2022:i:3:d:10.1007_s12063-022-00280-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.