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Measuring and Improving Eco‐efficiency Using Data Envelopment Analysis

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  • Neus Sanjuan
  • Javier Ribal
  • Gabriela Clemente
  • Ma Loreto Fenollosa

Abstract

The concept of eco‐efficiency can be defined with the “product value/environmental influence” ratio. Different models have been proposed to measure eco‐efficiency. The main difference among them is the weighting system used to aggregate the environmental results. Data envelopment analysis (DEA) permits this aggregation without requiring a subjective judgment about the weights. In this study, we applied a DEA model to Spanish Mahón‐Menorca cheese production to determine the most eco‐efficient production techniques. To this end, 16 scenarios of Mahón‐Menorca cheese production were built regarding technical (degree of automation) and cleaner production criteria. The environmental impacts were assessed by means of life cycle assessment. We carried out an economic assessment by determining the economic value added and the net income for each scenario. The results are referred to as 1 kilogram (kg) cheese ripened over 105 days. Through DEA, an eco‐efficiency ratio between 0 and 1 was obtained. Three scenarios were found to be eco‐efficient, with a high degree of automation (enclosed vat and molding and demolding machines) and accelerated cheese ripening. We used Monte Carlo simulation to carry out a sensitivity analysis to compare the influence of price changes on the eco‐efficiency ratio. The results emphasize the consistency and stability of the eco‐efficient scenarios.

Suggested Citation

  • Neus Sanjuan & Javier Ribal & Gabriela Clemente & Ma Loreto Fenollosa, 2011. "Measuring and Improving Eco‐efficiency Using Data Envelopment Analysis," Journal of Industrial Ecology, Yale University, vol. 15(4), pages 614-628, August.
    • Handle: RePEc:bla:inecol:v:15:y:2011:i:4:p:614-628
    DOI: 10.1111/j.1530-9290.2011.00347.x
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    1. Kiani Mavi, Reza & Saen, Reza Farzipoor & Goh, Mark, 2019. "Joint analysis of eco-efficiency and eco-innovation with common weights in two-stage network DEA: A big data approach," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 553-562.
    2. 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.
    3. Bang, You-Young & Lee, Dae Sung & Lim, Seong-Rin, 2019. "Analysis of corporate CO2 and energy cost efficiency: The role of performance indicators and effective environmental reporting," Energy Policy, Elsevier, vol. 133(C).
    4. Mariantonietta Fiore & Francesco Cont? & Giustina Pellegrini, 2015. "Reducing Food Losses: A (Dis)-Opportunity Cost Model," RIVISTA DI STUDI SULLA SOSTENIBILITA', FrancoAngeli Editore, vol. 2015(1), pages 151-166.
    5. Izhar Hussain Shah & Hung‐Suck Park, 2021. "Chronological change of resource metabolism and decarbonization patterns in Pakistan: Perspectives from a typical developing country," Journal of Industrial Ecology, Yale University, vol. 25(1), pages 144-161, February.
    6. Thies, Christian & Kieckhäfer, Karsten & Spengler, Thomas S. & Sodhi, Manbir S., 2019. "Operations research for sustainability assessment of products: A review," European Journal of Operational Research, Elsevier, vol. 274(1), pages 1-21.
    7. Heidari, Mohammad Davoud & Turner, Ian & Ardestani-Jaafari, Amir & Pelletier, Nathan, 2021. "Operations research for environmental assessment of crop-livestock production systems," Agricultural Systems, Elsevier, vol. 193(C).
    8. Hsing-Fu Kuo & Ko-Wan Tsou, 2015. "Application of Environmental Change Efficiency to the Sustainability of Urban Development at the Neighborhood Level," Sustainability, MDPI, vol. 7(8), pages 1-20, August.
    9. Maria Julia Xavier Belem & Milton Vieira Junior & Giovanni Mummolo & Francesco Facchini, 2021. "An AHP-Based Procedure for Model Selection for Eco-Efficiency Assessment," Sustainability, MDPI, vol. 13(21), pages 1-21, November.
    10. Zon-Yau Lee & Mei-Tai Chu & Yu-Ting Wang & Kuan-Ju Chen, 2020. "Industry Performance Appraisal Using Improved MCDM for Next Generation of Taiwan," Sustainability, MDPI, vol. 12(13), pages 1-18, June.
    11. Molinos-Senante, María & Hernández-Sancho, Francesc & Mocholí-Arce, Manuel & Sala-Garrido, Ramón, 2014. "Economic and environmental performance of wastewater treatment plants: Potential reductions in greenhouse gases emissions," Resource and Energy Economics, Elsevier, vol. 38(C), pages 125-140.

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