IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i22p9976-d1521819.html
   My bibliography  Save this article

Research on Neutral Dynamic Network Cross-Efficiency Modeling for Low-Carbon Innovation Development of Enterprises

Author

Listed:
  • Zhiying Liu

    (College of Science, North China University of Science and Technology, Tangshan 063210, China
    Hebei Key Laboratory of Data Science and Application, North China University of Science and Technology, Tangshan 063210, China
    The Key Laboratory of Engineering Computing in Tangshan City, North China University of Science and Technology, Tangshan 063210, China)

  • Danping Wang

    (College of Science, North China University of Science and Technology, Tangshan 063210, China
    Hebei Key Laboratory of Data Science and Application, North China University of Science and Technology, Tangshan 063210, China
    The Key Laboratory of Engineering Computing in Tangshan City, North China University of Science and Technology, Tangshan 063210, China)

  • Wanrong Xie

    (College of Science, North China University of Science and Technology, Tangshan 063210, China
    Hebei Key Laboratory of Data Science and Application, North China University of Science and Technology, Tangshan 063210, China
    The Key Laboratory of Engineering Computing in Tangshan City, North China University of Science and Technology, Tangshan 063210, China)

  • Jian Ma

    (College of Science, North China University of Science and Technology, Tangshan 063210, China
    Hebei Key Laboratory of Data Science and Application, North China University of Science and Technology, Tangshan 063210, China
    The Key Laboratory of Engineering Computing in Tangshan City, North China University of Science and Technology, Tangshan 063210, China)

  • Aimin Yang

    (College of Science, North China University of Science and Technology, Tangshan 063210, China
    Hebei Key Laboratory of Data Science and Application, North China University of Science and Technology, Tangshan 063210, China
    The Key Laboratory of Engineering Computing in Tangshan City, North China University of Science and Technology, Tangshan 063210, China)

Abstract

To evaluate the effectiveness of the low-carbon innovation development of enterprises, this paper proposes a neutral dynamic network cross-efficiency model and introduces the bootstrap sampling method to correct the model. The model categorizes the low-carbon green innovation R&D activities of enterprises into two distinct stages, as follows: the green R&D stage and the results transformation stage. It then assesses the efficiency of each stage and provides an overall efficiency rating. The model has been applied to a sample of listed Chinese iron and steel enterprises (CISES). The results of the study show that the overall efficiency of low-carbon innovation and development of CISES is on the low side, with the highest efficiency achieved in the green R&D stage, which is less than the lowest efficiency attained in the transformation stage, and most of the enterprises are in the stage of high green R&D and low transformation of the results. The ability of marketization of the R&D results still needs to be strengthened.

Suggested Citation

  • Zhiying Liu & Danping Wang & Wanrong Xie & Jian Ma & Aimin Yang, 2024. "Research on Neutral Dynamic Network Cross-Efficiency Modeling for Low-Carbon Innovation Development of Enterprises," Sustainability, MDPI, vol. 16(22), pages 1-18, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:9976-:d:1521819
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/22/9976/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/22/9976/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fare, Rolf & Grosskopf, Shawna, 1996. "Productivity and intermediate products: A frontier approach," Economics Letters, Elsevier, vol. 50(1), pages 65-70, January.
    2. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    3. Li, Ke & Zou, Danyu & Li, Hailing, 2023. "Environmental regulation and green technical efficiency: A process-level data envelopment analysis from Chinese iron and steel enterprises," Energy, Elsevier, vol. 277(C).
    4. Kao, Chiang & Hwang, Shiuh-Nan, 2008. "Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan," European Journal of Operational Research, Elsevier, vol. 185(1), pages 418-429, February.
    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. Calogero Guccio & Anna Mignosa & Ilde Rizzo, 2017. "Disentangle inefficiency in the production activities of Italian national libraries: A network DEA approach," ACEI Working Paper Series AWP-04-2017, Association for Cultural Economics International, revised Mar 2017.
    2. Guccio, Calogero & Mignosa, Anna & Rizzo, Ilde, 2018. "Are public state libraries efficient? An empirical assessment using network Data Envelopment Analysis," Socio-Economic Planning Sciences, Elsevier, vol. 64(C), pages 78-91.
    3. Chiu, Yung-ho & Huang, Chin-wei & Ma, Chun-Mei, 2011. "Assessment of China transit and economic efficiencies in a modified value-chains DEA model," European Journal of Operational Research, Elsevier, vol. 209(2), pages 95-103, March.
    4. Michali, Maria & Emrouznejad, Ali & Dehnokhalaji, Akram & Clegg, Ben, 2023. "Subsampling bootstrap in network DEA," European Journal of Operational Research, Elsevier, vol. 305(2), pages 766-780.
    5. Hadi Ghafoorian & NikIntan Norhan & Mohammed Ndaliman Abubakar & Fazel Mohammadi Nodeh, 2013. "Efficiency Considering Credit Risk in Banking Industry, Using Two-stage DEA," Journal of Social and Development Sciences, AMH International, vol. 4(8), pages 356-360.
    6. 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.
    7. Bao-Ngoc Tong & Cheng-Ping Cheng & Lien-Wen Liang & Yi-Jun Liu, 2023. "Using Network DEA to Explore the Effect of Mobile Payment on Taiwanese Bank Efficiency," Sustainability, MDPI, vol. 15(8), pages 1-18, April.
    8. Yung‐ho Chiu & Tai‐Yu Lin & Tzu‐Han Chang & Yi‐Nuo Lin & Shih‐Yung Chiu, 2021. "Prevaluating efficiency gains from potential mergers and acquisitions in the financial industry with the Resample Past–Present–Future data envelopment analysis approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(2), pages 369-384, March.
    9. Guccio, Calogero & Martorana, Marco & Mazza, Isidoro & Pignataro, Giacomo & Rizzo, Ilde, 2020. "An assessment of the performance of Italian public historical archives: Preservation vs utilisation," Journal of Policy Modeling, Elsevier, vol. 42(6), pages 1270-1286.
    10. Halkos, George E. & Aslanidis, Panagiotis – Stavros C., 2023. "Sustainable energy development in an era of geopolitical multi-crisis. Applying productivity indices within institutional framework," Resources Policy, Elsevier, vol. 85(PB).
    11. AGRELL, Per & HATAMI-MARBINI, Adel, 2011. "Frontier-based performance analysis models for supply chain management; state of the art and research directions," LIDAM Discussion Papers CORE 2011069, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Kaffash, Sepideh & Azizi, Roza & Huang, Ying & Zhu, Joe, 2020. "A survey of data envelopment analysis applications in the insurance industry 1993–2018," European Journal of Operational Research, Elsevier, vol. 284(3), pages 801-813.
    13. Azadi, Majid & Yousefi, Saeed & Farzipoor Saen, Reza & Shabanpour, Hadi & Jabeen, Fauzia, 2023. "Forecasting sustainability of healthcare supply chains using deep learning and network data envelopment analysis," Journal of Business Research, Elsevier, vol. 154(C).
    14. Fukuyama, Hirofumi & Weber, William L., 2010. "A slacks-based inefficiency measure for a two-stage system with bad outputs," Omega, Elsevier, vol. 38(5), pages 398-409, October.
    15. Xianhua Tan & Danting Zheng & Yuanyuan Zhu & Sanggyun Na, 2023. "The Financing Efficiency of China’s Industrial Listed Enterprises Based on the Dynamic–Network SBM Model," Sustainability, MDPI, vol. 15(6), pages 1-19, March.
    16. Despotis, Dimitris K. & Koronakos, Gregory & Sotiros, Dimitris, 2016. "The “weak-link” approach to network DEA for two-stage processes," European Journal of Operational Research, Elsevier, vol. 254(2), pages 481-492.
    17. Jorge Antunes & Peter Wanke & Thiago Fonseca & Yong Tan, 2023. "Do ESG Risk Scores Influence Financial Distress? Evidence from a Dynamic NDEA Approach," Sustainability, MDPI, vol. 15(9), pages 1-32, May.
    18. Ibrahim Alnafrah, 2021. "Efficiency evaluation of BRICS’s national innovation systems based on bias-corrected network data envelopment analysis," Journal of Innovation and Entrepreneurship, Springer, vol. 10(1), pages 1-28, December.
    19. Simona Cohen-Kadosh & Zilla Sinuany-Stern, 2020. "Hip fracture surgery efficiency in Israeli hospitals via a network data envelopment analysis," 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. 28(1), pages 251-277, March.
    20. Eucabeth Majiwa & Boon L. Lee & Clevo Wilson & Hidemichi Fujii & Shunsuke Managi, 2018. "A network data envelopment analysis (NDEA) model of post-harvest handling: the case of Kenya’s rice processing industry," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(3), pages 631-648, June.

    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:gam:jsusta:v:16:y:2024:i:22:p:9976-:d:1521819. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.