IDEAS home Printed from https://ideas.repec.org/a/wly/sustdv/v30y2022i5p817-832.html
   My bibliography  Save this article

How ecoefficient is European food consumption? A frontier‐based multiregional input–output analysis

Author

Listed:
  • Muhammet Enis Bulak
  • Murat Kucukvar

Abstract

This paper presents an integrated approach combining the optimization‐based frontier model with a global multiregional input–output (MRIO) analysis for food consumption in Europe. The weighted and conventional data envelopment analysis models are coupled with production and consumption‐based environmental and economic footprint data obtained from the environmental footprint explorer database. Eco‐efficiency assessment is carried out using multiple undesirable environmental outputs such as carbon emission, total energy consumption, land use, material use, water use, and one desirable economic output, which is the gross value‐added (GVA). This assessment indicates an efficiency level of each economic activity associated with its environmental impacts and policies are made as a result of the efficiency level to propose an equilibrium between economic development and environmental impacts. Finally, a sensitivity analysis of each parameter, variability analysis between weighted and non‐weighted models, and performance improvement projections are presented. Based on the results, four countries become efficient when moving from production‐based accounting (PBA) to consumption‐based accounting (CBA). France, United Kingdom, Italy, and Sweden are efficient countries in both findings. Denmark caused the highest carbon emission from the production point of view. Germany is the largest importer in all environmental categories such as carbon emission, energy usage, material use, land use, and water use. Additionally, the weight‐restricted model indicated a noticeable difference concerning the eco‐efficiency scores under the PBA and CBA approach, where land use and material footprint categories were found to be the most sensitive parameters for eco‐efficiency scores. The authors believe that this integrated approach will aid in decision‐making and help build a composite eco‐efficiency score when comparing the performance of food consumption with multiple environmental and economic metrics.

Suggested Citation

  • Muhammet Enis Bulak & Murat Kucukvar, 2022. "How ecoefficient is European food consumption? A frontier‐based multiregional input–output analysis," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(5), pages 817-832, October.
  • Handle: RePEc:wly:sustdv:v:30:y:2022:i:5:p:817-832
    DOI: 10.1002/sd.2282
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/sd.2282
    Download Restriction: no

    File URL: https://libkey.io/10.1002/sd.2282?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Arnold Tukker & Stefan Giljum & Richard Wood, 2018. "Recent Progress in Assessment of Resource Efficiency and Environmental Impacts Embodied in Trade: An Introduction to this Special Issue," Journal of Industrial Ecology, Yale University, vol. 22(3), pages 489-501, June.
    3. Dariush Khezrimotlagh & Yao Chen, 2018. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 217-234, Springer.
    4. Kortelainen, Mika, 2008. "Dynamic environmental performance analysis: A Malmquist index approach," Ecological Economics, Elsevier, vol. 64(4), pages 701-715, February.
    5. Arnold Tukker & Arjan de Koning & Richard Wood & Troy Hawkins & Stephan Lutter & Jose Acosta & Jose M. Rueda Cantuche & Maaike Bouwmeester & Jan Oosterhaven & Thomas Drosdowski & Jeroen Kuenen, 2013. "Exiopol - Development And Illustrative Analyses Of A Detailed Global Mr Ee Sut/Iot," Economic Systems Research, Taylor & Francis Journals, vol. 25(1), pages 50-70, March.
    6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    7. Christos Papahristodoulou, 1997. "A DEA model to evaluate car efficiency," Applied Economics, Taylor & Francis Journals, vol. 29(11), pages 1493-1508.
    8. Marcel P. Timmer & Erik Dietzenbacher & Bart Los & Robert Stehrer & Gaaitzen J. Vries, 2015. "An Illustrated User Guide to the World Input–Output Database: the Case of Global Automotive Production," Review of International Economics, Wiley Blackwell, vol. 23(3), pages 575-605, August.
    9. M. Lenzen & D. Moran & K. Kanemoto & B. Foran & L. Lobefaro & A. Geschke, 2012. "International trade drives biodiversity threats in developing nations," Nature, Nature, vol. 486(7401), pages 109-112, June.
    10. Arunima Malik & Jun Lan, 2016. "The role of outsourcing in driving global carbon emissions," Economic Systems Research, Taylor & Francis Journals, vol. 28(2), pages 168-182, June.
    11. Peters, Glen P., 2008. "From production-based to consumption-based national emission inventories," Ecological Economics, Elsevier, vol. 65(1), pages 13-23, March.
    12. Liu, C.H. & Lin, Sue J. & Lewis, Charles, 2010. "Evaluation of thermal power plant operational performance in Taiwan by data envelopment analysis," Energy Policy, Elsevier, vol. 38(2), pages 1049-1058, February.
    13. Doyle, JR & Green, RH, 1991. "Comparing products using data envelopment analysis," Omega, Elsevier, vol. 19(6), pages 631-638.
    14. Robbie M. Andrew & Glen P. Peters, 2013. "A Multi-Region Input-Output Table Based On The Global Trade Analysis Project Database (Gtap-Mrio)," Economic Systems Research, Taylor & Francis Journals, vol. 25(1), pages 99-121, March.
    15. Emrouznejad, Ali & Parker, Barnett R. & Tavares, Gabriel, 2008. "Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA," Socio-Economic Planning Sciences, Elsevier, vol. 42(3), pages 151-157, September.
    16. Lenzen, Manfred & Moran, Daniel & Bhaduri, Anik & Kanemoto, Keiichiro & Bekchanov, Maksud & Geschke, Arne & Foran, Barney, 2013. "International trade of scarce water," Ecological Economics, Elsevier, vol. 94(C), pages 78-85.
    17. Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
    18. Egilmez, Gokhan & Kucukvar, Murat & Tatari, Omer & Bhutta, M. Khurrum S., 2014. "Supply chain sustainability assessment of the U.S. food manufacturing sectors: A life cycle-based frontier approach," Resources, Conservation & Recycling, Elsevier, vol. 82(C), pages 8-20.
    19. Chung, Whan-Sam & Tohno, Susumu & Shim, Sang Yul, 2009. "An estimation of energy and GHG emission intensity caused by energy consumption in Korea: An energy IO approach," Applied Energy, Elsevier, vol. 86(10), pages 1902-1914, October.
    20. Kucukvar, Murat & Cansev, Bunyamin & Egilmez, Gokhan & Onat, Nuri C. & Samadi, Hamidreza, 2016. "Energy-climate-manufacturing nexus: New insights from the regional and global supply chains of manufacturing industries," Applied Energy, Elsevier, vol. 184(C), pages 889-904.
    21. Hughes, Andrew & Yaisawarng, Suthathip, 2004. "Sensitivity and dimensionality tests of DEA efficiency scores," European Journal of Operational Research, Elsevier, vol. 154(2), pages 410-422, April.
    22. Wiedmann, Thomas & Wilting, Harry C. & Lenzen, Manfred & Lutter, Stephan & Palm, Viveka, 2011. "Quo Vadis MRIO? Methodological, data and institutional requirements for multi-region input-output analysis," Ecological Economics, Elsevier, vol. 70(11), pages 1937-1945, September.
    23. Chia-Nan Wang & Thanh-Tuan Dang & Ngoc-Ai-Thy Nguyen & Thi-Thu-Hong Le, 2020. "Supporting Better Decision-Making: A Combined Grey Model and Data Envelopment Analysis for Efficiency Evaluation in E-Commerce Marketplaces," Sustainability, MDPI, vol. 12(24), pages 1-24, December.
    24. Wiedmann, Thomas & Lenzen, Manfred & Turner, Karen & Barrett, John, 2007. "Examining the global environmental impact of regional consumption activities -- Part 2: Review of input-output models for the assessment of environmental impacts embodied in trade," Ecological Economics, Elsevier, vol. 61(1), pages 15-26, February.
    25. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    26. Edgar Hertwich, 2011. "The Life Cycle Environmental Impacts Of Consumption," Economic Systems Research, Taylor & Francis Journals, vol. 23(1), pages 27-47.
    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. Jingwen Huo & Peipei Chen & Klaus Hubacek & Heran Zheng & Jing Meng & Dabo Guan, 2022. "Full‐scale, near real‐time multi‐regional input–output table for the global emerging economies (EMERGING)," Journal of Industrial Ecology, Yale University, vol. 26(4), pages 1218-1232, August.
    2. Ninpanit, Panittra & Malik, Arunima & Wakiyama, Takako & Geschke, Arne & Lenzen, Manfred, 2019. "Thailand’s energy-related carbon dioxide emissions from production-based and consumption-based perspectives," Energy Policy, Elsevier, vol. 133(C).
    3. Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
    4. Daraio, Cinzia & Kerstens, Kristiaan & Nepomuceno, Thyago & Sickles, Robin C., 2019. "Empirical Surveys of Frontier Applications: A Meta-Review," Working Papers 19-005, Rice University, Department of Economics.
    5. Eisenmenger, Nina & Wiedenhofer, Dominik & Schaffartzik, Anke & Giljum, Stefan & Bruckner, Martin & Schandl, Heinz & Wiedmann, Thomas O. & Lenzen, Manfred & Tukker, Arnold & Koning, Arjan, 2016. "Consumption-based material flow indicators — Comparing six ways of calculating the Austrian raw material consumption providing six results," Ecological Economics, Elsevier, vol. 128(C), pages 177-186.
    6. Kucukvar, Murat & Haider, Muhammad Ali & Onat, Nuri Cihat, 2017. "Exploring the material footprints of national electricity production scenarios until 2050: The case for Turkey and UK," Resources, Conservation & Recycling, Elsevier, vol. 125(C), pages 251-263.
    7. Eivind Lekve Bjelle & Johannes Többen & Konstantin Stadler & Thomas Kastner & Michaela C. Theurl & Karl-Heinz Erb & Kjartan-Steen Olsen & Kirsten S. Wiebe & Richard Wood, 2020. "Adding country resolution to EXIOBASE: impacts on land use embodied in trade," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 9(1), pages 1-25, December.
    8. Hongli Liu & Xiaoyu Yan & Jinhua Cheng & Jun Zhang & Yan Bu, 2021. "Driving Factors for the Spatiotemporal Heterogeneity in Technical Efficiency of China’s New Energy Industry," Energies, MDPI, vol. 14(14), pages 1-21, July.
    9. Thomas Grebel, 2019. "What a difference carbon leakage correction makes!," Journal of Evolutionary Economics, Springer, vol. 29(3), pages 939-971, July.
    10. Thomas Bournaris & George Vlontzos & Christina Moulogianni, 2019. "Efficiency of Vegetables Produced in Glasshouses: The Impact of Data Envelopment Analysis (DEA) in Land Management Decision Making," Land, MDPI, vol. 8(1), pages 1-11, January.
    11. Vinicius A. Vale & Fernando S. Perobelli & Ariaster B. Chimeli, 2018. "International trade, pollution, and economic structure: evidence on CO2 emissions for the North and the South," Economic Systems Research, Taylor & Francis Journals, vol. 30(1), pages 1-17, January.
    12. Qingyou Yan & Xu Wang & Tomas Baležentis & Dalia Streimikiene, 2018. "Energy–economy–environmental (3E) performance of Chinese regions based on the data envelopment analysis model with mixed assumptions on disposability," Energy & Environment, , vol. 29(5), pages 664-684, August.
    13. Abbas Mardani & Dalia Streimikiene & Tomas Balezentis & Muhamad Zameri Mat Saman & Khalil Md Nor & Seyed Meysam Khoshnava, 2018. "Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends," Energies, MDPI, vol. 11(8), pages 1-21, August.
    14. Meng, Bo & Peters, Glen P. & Wang, Zhi & Li, Meng, 2018. "Tracing CO2 emissions in global value chains," Energy Economics, Elsevier, vol. 73(C), pages 24-42.
    15. Dolter, Brett & Victor, Peter A., 2016. "Casting a long shadow: Demand-based accounting of Canada's greenhouse gas emissions responsibility," Ecological Economics, Elsevier, vol. 127(C), pages 156-164.
    16. Boya Zhang & Shukuan Bai & Yadong Ning & Tao Ding & Yan Zhang, 2020. "Emission Embodied in International Trade and Its Responsibility from the Perspective of Global Value Chain: Progress, Trends, and Challenges," Sustainability, MDPI, vol. 12(8), pages 1-26, April.
    17. Shih-Heng Yu, 2019. "Benchmarking and Performance Evaluation Towards the Sustainable Development of Regions in Taiwan: A Minimum Distance-Based Measure with Undesirable Outputs in Additive DEA," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(3), pages 1323-1348, August.
    18. Natalia Borisovna Lubsanova & Lyudmila Bato-Zhargalovna Maksanova & Zinaida Sergeevna Eremko & Taisiya Borisovna Bardakhanova & Anna Semenovna Mikheeva, 2022. "The Eco-Efficiency of Russian Regions in North Asia: Their Green Direction of Regional Development," Sustainability, MDPI, vol. 14(19), pages 1-19, October.
    19. Makiko Tsukui & Shigemi Kagawa & Yasushi Kondo, 2015. "Measuring the waste footprint of cities in Japan: an interregional waste input–output analysis," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 4(1), pages 1-24, December.
    20. Franco Solís, Alberto & F.T. Avelino, André & Carrascal-Incera, André, 2020. "The evolution of household-induced value chains and their environmental implications," Ecological Economics, Elsevier, vol. 174(C).

    More about this item

    Statistics

    Access and download statistics

    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:wly:sustdv:v:30:y:2022:i:5:p:817-832. 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: Wiley Content Delivery (email available below). General contact details of provider: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1099-1719 .

    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.