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Comparison among U.S. industrial sectors by DEA environmental assessment: Equipped with analytical capability to handle zero or negative in production factors

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  • Sueyoshi, Toshiyuki
  • Yuan, Yan

Abstract

A green image is recently an important component of corporate sustainability in modern business. By extending the two previous works (i.e., Wang et al., 2014; Sueyoshi and Wang, 2014a), this study discusses a new use of Data Envelopment Analysis (DEA) for environmental assessment by incorporating an analytical capability to handle zero and/or negative in a data set. The proposed approach provides us with not only new quantitative assessment on unified (operational and environmental) performance of firms but also information regarding how to invest for eco-technology innovation for abating an amount of their industrial pollutions. According to the previous studies, the energy industry is an attractive investment target if desirable outputs are measured by Return on Assets (ROA) as a short-term concern and an amount of CO2 emission reduction. The selection on a desirable output combination is important in understanding the corporate sustainability of the energy industry because it is the largest emitter among seven industry sectors examined in the previous studies. However, if the ROA is replaced by a corporate value, measured by Tobin's q ratio as a long-term concern, the energy industry is not so attractive because it uses a very large production process so that green investment does not immediately increase the corporate value. An empirical problem of these previous studies is that they have investigated only successful companies with positive ROA or Tobin's q ratios. The analytical feature clearly indicates a methodological drawback of their studies. In contrast, this study pays attention to both successful companies with positive net incomes and unsuccessful companies with negative net incomes, so being able to measure all aspects of their performance in a short-term concern. This study finds that the energy industry exhibits a high level of potential on green investment. However, the energy industry may be not attractive even in the short-term concern (i.e., net income), partly because governmental regulations on their operation and pollution prevention efforts are stricter than the other industrial sectors. This result may be seemingly inconsistent with Wang et al. (2014). Rather, the result indicates that successful energy firms can attain the corporate sustainability by investing eco-technology innovation, but unsuccessful ones cannot attain the sustainability, even in the short-term concern, because they do not have large capital accumulation for eco-technology investment whose importance has been first discussed by Sueyoshi and Goto (2010a). In other words, the eco-technology investment for enhancing a high level of corporate sustainability depends upon an amount of net income generated by each energy firm.

Suggested Citation

  • Sueyoshi, Toshiyuki & Yuan, Yan, 2015. "Comparison among U.S. industrial sectors by DEA environmental assessment: Equipped with analytical capability to handle zero or negative in production factors," Energy Economics, Elsevier, vol. 52(PA), pages 69-86.
  • Handle: RePEc:eee:eneeco:v:52:y:2015:i:pa:p:69-86
    DOI: 10.1016/j.eneco.2015.09.006
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. Małgorzata Janicka & Artur Sajnóg, 2023. "Do environmental and economic performance go hand in hand? An industrial analysis of European Union companies with the non‐parametric data envelopment analysis method," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 30(5), pages 2590-2605, September.
    3. Jie Liu & Chunhui Yuan & Xiaolong Li, 2019. "The Environmental Assessment on Chinese Logistics Enterprises Based on Non-Radial DEA," Energies, MDPI, vol. 12(24), pages 1-18, December.
    4. Sueyoshi, Toshiyuki & Yuan, Yan, 2016. "Returns to damage under undesirable congestion and damages to return under desirable congestion measured by DEA environmental assessment with multiplier restriction: Economic and energy planning for s," Energy Economics, Elsevier, vol. 56(C), pages 288-309.
    5. Lin, Shoufu & Lin, Ruoyun & Sun, Ji & Wang, Fei & Wu, Weixiang, 2021. "Dynamically evaluating technological innovation efficiency of high-tech industry in China: Provincial, regional and industrial perspective," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
    6. Toshiyuki Sueyoshi & Mika Goto, 2019. "DEA Non-Radial Approach for Resource Allocation and Energy Usage to Enhance Corporate Sustainability in Japanese Manufacturing Industries," Energies, MDPI, vol. 12(9), pages 1-22, May.
    7. Mojtaba Ghiyasi & Farhad Taghizadeh-Hesary, 2021. "Environmental Efficiency Analysis for Multi Plants Production Technologies," Sustainability, MDPI, vol. 13(7), pages 1-18, April.
    8. Sueyoshi, Toshiyuki & Goto, Mika & Wang, Derek, 2017. "Malmquist index measurement for sustainability enhancement in Chinese municipalities and provinces," Energy Economics, Elsevier, vol. 67(C), pages 554-571.
    9. Sueyoshi, Toshiyuki & Yuan, Yan, 2017. "Social sustainability measured by intermediate approach for DEA environmental assessment: Chinese regional planning for economic development and pollution prevention," Energy Economics, Elsevier, vol. 66(C), pages 154-166.
    10. Sueyoshi, Toshiyuki & Wang, Derek, 2018. "DEA environmental assessment on US petroleum industry: Non-radial approach with translation invariance in time horizon," Energy Economics, Elsevier, vol. 72(C), pages 276-289.
    11. Wei Wang & Shi Liang & Ruichao Yu & Yumin Su, 2022. "Theoretical Evidence for Green Innovation Driven by Multiple Major Shareholders: Empirical Evidence from Chinese Listed Companies," Sustainability, MDPI, vol. 14(8), pages 1-18, April.
    12. Sueyoshi, Toshiyuki & Goto, Mika, 2016. "Undesirable congestion under natural disposability and desirable congestion under managerial disposability in U.S. electric power industry measured by DEA environmental assessment," Energy Economics, Elsevier, vol. 55(C), pages 173-188.
    13. Andreea Chițimiea & Mihaela Minciu & Andreea-Mariana Manta & Carmen Nadia Ciocoiu & Cristina Veith, 2021. "The Drivers of Green Investment: A Bibliometric and Systematic Review," Sustainability, MDPI, vol. 13(6), pages 1-25, March.
    14. Sueyoshi, Toshiyuki & Goto, Mika, 2017. "Measurement of returns to scale on large photovoltaic power stations in the United States and Germany," Energy Economics, Elsevier, vol. 64(C), pages 306-320.
    15. Sueyoshi, Toshiyuki & Goto, Mika, 2015. "Japanese fuel mix strategy after disaster of Fukushima Daiichi nuclear power plant: Lessons from international comparison among industrial nations measured by DEA environmental assessment in time hori," Energy Economics, Elsevier, vol. 52(PA), pages 87-103.
    16. Sueyoshi, Toshiyuki & Yuan, Yan & Li, Aijun & Wang, Daoping, 2017. "Methodological comparison among radial, non-radial and intermediate approaches for DEA environmental assessment," Energy Economics, Elsevier, vol. 67(C), pages 439-453.
    17. Yang, Xuehui & Zhang, Huirong & Li, Yan, 2022. "High-speed railway, factor flow and enterprise innovation efficiency: An empirical analysis on micro data," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    18. Sueyoshi, Toshiyuki & Wang, Derek, 2017. "Measuring scale efficiency and returns to scale on large commercial rooftop photovoltaic systems in California," Energy Economics, Elsevier, vol. 65(C), pages 389-398.
    19. Sueyoshi, Toshiyuki & Yuan, Yan, 2016. "Marginal Rate of Transformation and Rate of Substitution measured by DEA environmental assessment: Comparison among European and North American nations," Energy Economics, Elsevier, vol. 56(C), pages 270-287.
    20. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    21. Yue Xu & Zebin Wang & Yung-Ho Chiu & Fangrong Ren, 2020. "Research on energy-saving and emissions reduction efficiency in Chinese thermal power companies," Energy & Environment, , vol. 31(5), pages 903-919, August.

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    Keywords

    Environment; Energy; DEA; Investment; Technology innovation; Corporate sustainability;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

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