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Research on efficiency measurement of information industry chain integration based on multiple structures and its application in carbon management industrial park
[Measuring efficiency in the hotel industry: a stochastic frontier approach]

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  • Wei Dong
  • Tao Wang

Abstract

To promote the integration of the information industry, chain is of great significance for enterprises to improve quality, efficiency cost reduction and high-quality industry development. In this paper, based on the data envelopment analysis method, the efficiency measurement models of series structure, parallel structure and hybrid structure industrial chain are constructed under two different scenarios of central decision-making mechanism and decentralized decision-making mechanism. By quantifying the input and output resources that is in each link of the information industry chain integration process, measuring the input and output efficiency under different industrial chain integration structure; comparing and analyzing the integration efficiency of different regions, different links, discussing the cause of the differences in the integration efficiency of industry chain; thus, providing policy recommendations for the efficiency of industrial chain integration. In addition, taking the actual situation of two industrial parks with the main characteristics of carbon emission in a city of China as an example, the paper analyzes the difference of the integration efficiency of the information industry chain between the two parks. The empirical analysis shows that the information industry chain integration efficiency measurement model based on data envelope analysis theory is feasible and effective. It can not only measure the industry chain efficiency as a whole but also compare and analyze the integration efficiency of enterprises in different links of the industry chain.

Suggested Citation

  • Wei Dong & Tao Wang, 2022. "Research on efficiency measurement of information industry chain integration based on multiple structures and its application in carbon management industrial park [Measuring efficiency in the hotel," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 17, pages 421-429.
    • Handle: RePEc:oup:ijlctc:v:17:y:2022:i::p:421-429.
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    File URL: http://hdl.handle.net/10.1093/ijlct/ctac015
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    References listed on IDEAS

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    1. William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), 2011. "Handbook on Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-1-4419-6151-8, December.
    2. William W. Cooper & Lawrence M. Seiford & Joe Zhu, 2011. "Data Envelopment Analysis: History, Models, and Interpretations," International Series in Operations Research & Management Science, in: William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), Handbook on Data Envelopment Analysis, chapter 0, pages 1-39, Springer.
    3. Joe Zhu, 2014. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Quantitative Models for Performance Evaluation and Benchmarking, edition 3, chapter 1, pages 1-9, Springer.
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    5. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    6. Charnes, A. & Cooper, W. W. & Seiford, L. & Stutz, J., 1982. "A multiplicative model for efficiency analysis," Socio-Economic Planning Sciences, Elsevier, vol. 16(5), pages 223-224.
    7. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
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    Cited by:

    1. Yan, Kun & Gao, Hanbo & Liu, Rui & Lyu, Yizheng & Wan, Mei & Tian, Jinping & Chen, Lyujun, 2024. "Review on low-carbon development in Chinese industrial parks driven by bioeconomy strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).

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