IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i6p5183-d1097631.html
   My bibliography  Save this article

Study on the Evaluation of the Development Efficiency of Smart Mine Construction and the Influencing Factors Based on the US-SBM Model

Author

Listed:
  • Mei Tao

    (College of Mines, Liaoning Technical University, Fuxin 123000, China)

  • Shanshan Lv

    (College of Mines, Liaoning Technical University, Fuxin 123000, China)

  • Shiqian Feng

    (College of Mines, Liaoning Technical University, Fuxin 123000, China)

Abstract

Taking the panel data of 13 provinces (autonomous regions and municipalities directly under the central government) in Shanxi and Xinjiang from 2011 to 2020 as the research object, we establish an evaluation index system for assessing smart mine construction development efficiency combined with the global reference method. The non-desired output super-efficiency slacks-based measure and the kernel density model were used to measure the development efficiency of smart mine construction and spatial structure evolution characteristics. This study explores the internal and external factors affecting the efficiency in various regions using the Tobit regression model. After conducting the analysis, the study obtained four main findings: (1) the development efficiency is influenced by the level of technology, and the overall level is low; (2) there are spatially heterogeneous and agglomerative characteristics, with large differences in regional distribution; (3) personnel is the main factor causing the phenomenon of severe redundancy in the region; and (4) the level of regional economic development, industrial structure, and the degree of government intervention are the main external factors that have a positive impact.

Suggested Citation

  • Mei Tao & Shanshan Lv & Shiqian Feng, 2023. "Study on the Evaluation of the Development Efficiency of Smart Mine Construction and the Influencing Factors Based on the US-SBM Model," Sustainability, MDPI, vol. 15(6), pages 1-17, March.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5183-:d:1097631
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/6/5183/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/6/5183/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hosseinzadeh, Ahmad & Smyth, Russell & Valadkhani, Abbas & Le, Viet, 2016. "Analyzing the efficiency performance of major Australian mining companies using bootstrap data envelopment analysis," Economic Modelling, Elsevier, vol. 57(C), pages 26-35.
    2. Banker, Rajiv D. & Thrall, R. M., 1992. "Estimation of returns to scale using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 62(1), pages 74-84, October.
    3. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    4. Gjalt Huppes & Masanobu Ishikawa, 2005. "A Framework for Quantified Eco‐efficiency Analysis," Journal of Industrial Ecology, Yale University, vol. 9(4), pages 25-41, October.
    5. Kulshreshtha, Mudit & Parikh, Jyoti K., 2002. "Study of efficiency and productivity growth in opencast and underground coal mining in India: a DEA analysis," Energy Economics, Elsevier, vol. 24(5), pages 439-453, September.
    6. Fang, Hong & Wu, Junjie & Zeng, Catherine, 2009. "Comparative study on efficiency performance of listed coal mining companies in China and the US," Energy Policy, Elsevier, vol. 37(12), pages 5140-5148, December.
    7. Pastor, Jesus T. & Lovell, C.A. Knox, 2005. "A global Malmquist productivity index," Economics Letters, Elsevier, vol. 88(2), pages 266-271, August.
    8. Tsolas, Ioannis E., 2011. "Performance assessment of mining operations using nonparametric production analysis: A bootstrapping approach in DEA," Resources Policy, Elsevier, vol. 36(2), pages 159-167, June.
    9. 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.
    10. Charnes, A. & Cooper, W. W. & Rhodes, E., 1979. "Measuring the efficiency of decision-making units," European Journal of Operational Research, Elsevier, vol. 3(4), pages 339-338, July.
    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. Wu, Peng & Wang, Yiqing & Chiu, Yung-ho & Li, Ying & Lin, Tai-Yu, 2019. "Production efficiency and geographical location of Chinese coal enterprises - undesirable EBM DEA," Resources Policy, Elsevier, vol. 64(C).
    2. Ahmad Hosseinzadeh & Russell Smyth & Abbas Valadkhani & Amir Moradi, 2018. "What determines the efficiency of Australian mining companies?," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(1), pages 121-138, January.
    3. Malin Song & Jianlin Wang & Jiajia Zhao & Tomas Baležentis & Zhiyang Shen, 2020. "Production and safety efficiency evaluation in Chinese coal mines: accident deaths as undesirable output," Annals of Operations Research, Springer, vol. 291(1), pages 827-845, August.
    4. Li, Hai-ling & Zhu, Xue-hong & Chen, Jin-yu & Jiang, Fei-tao, 2019. "Environmental regulations, environmental governance efficiency and the green transformation of China's iron and steel enterprises," Ecological Economics, Elsevier, vol. 165(C), pages 1-1.
    5. Biswaranjita Mahapatra & Chandan Bhar & Sandeep Mondal, 2020. "Performance Assessment Based on the Relative Efficiency of Indian Opencast Coal Mines Using Data Envelopment Analysis and Malmquist Productivity Index," Energies, MDPI, vol. 13(18), pages 1-21, September.
    6. Min Wang & Meng Ji & Xiaofen Wu & Kexin Deng & Xiaodong Jing, 2023. "Analysis on Evaluation and Spatial-Temporal Evolution of Port Cluster Eco-Efficiency: Case Study from the Yangtze River Delta in China," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    7. Ruomeng Zhou & Yunsheng Zhang, 2023. "Measurement of Urban Green Total Factor Productivity and Analysis of Its Temporal and Spatial Evolution in China," Sustainability, MDPI, vol. 15(12), pages 1-32, June.
    8. Usman Akbar & József Popp & Hameed Khan & Muhammad Asif Khan & Judit Oláh, 2020. "Energy Efficiency in Transportation along with the Belt and Road Countries," Energies, MDPI, vol. 13(10), pages 1-20, May.
    9. Hosseinzadeh, Ahmad & Smyth, Russell & Valadkhani, Abbas & Le, Viet, 2016. "Analyzing the efficiency performance of major Australian mining companies using bootstrap data envelopment analysis," Economic Modelling, Elsevier, vol. 57(C), pages 26-35.
    10. Yan He & Yung-ho Chiu & Bin Zhang, 2020. "Prevaluating Technical Efficiency Gains From Potential Mergers and Acquisitions in China’s Coal Industry," SAGE Open, , vol. 10(3), pages 21582440209, July.
    11. Hui Zhang & Yingqi Sun & Zhaoying Fan & Zhi Long & Shilong Wan & Zilong Zhang & Xingpeng Chen, 2023. "Analysis of County-Scale Eco-Efficiency and Spatiotemporal Characteristics in China," Land, MDPI, vol. 12(2), pages 1-21, February.
    12. Rafael Benítez & Vicente Coll-Serrano & Vicente J. Bolós, 2021. "deaR-Shiny: An Interactive Web App for Data Envelopment Analysis," Sustainability, MDPI, vol. 13(12), pages 1-19, June.
    13. Geissler, Bernhard & Mew, Michael C. & Weber, Olaf & Steiner, Gerald, 2015. "Efficiency performance of the world's leading corporations in phosphate rock mining," Resources, Conservation & Recycling, Elsevier, vol. 105(PB), pages 246-258.
    14. Sanjeet Singh & Prabhat Ranjan, 2018. "Efficiency analysis of non-homogeneous parallel sub-unit systems for the performance measurement of higher education," Annals of Operations Research, Springer, vol. 269(1), pages 641-666, October.
    15. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    16. Xiang Yan & Yongchun Huang, 2021. "Is there a nonlinear economic threshold effect of financial development on the efficiency of sci‐tech innovation? An empirical test from the Yangtze River Economic Belt," Growth and Change, Wiley Blackwell, vol. 52(3), pages 1387-1409, September.
    17. Zhang, Lina & Gao, Wanting & Chiu, Yung-ho & Pang, Qinghua & Shi, Zhen & Guo, Zhiqin, 2021. "Environmental performance indicators of China's coal mining industry: A bootstrapping Malmquist index analysis," Resources Policy, Elsevier, vol. 71(C).
    18. Wang, Qiang & Jiang, Feng & Li, Rongrong, 2022. "Assessing supply chain greenness from the perspective of embodied renewable energy – A data envelopment analysis using multi-regional input-output analysis," Renewable Energy, Elsevier, vol. 189(C), pages 1292-1305.
    19. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    20. Qin, Quande & Li, Xin & Li, Li & Zhen, Wei & Wei, Yi-Ming, 2017. "Air emissions perspective on energy efficiency: An empirical analysis of China’s coastal areas," Applied Energy, Elsevier, vol. 185(P1), pages 604-614.

    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:15:y:2023:i:6:p:5183-:d:1097631. 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.