IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i7p3870-d527736.html
   My bibliography  Save this article

Sustainability Performance Assessment Using Self-Organizing Maps (SOM) and Classification and Ensembles of Regression Trees (CART)

Author

Listed:
  • Mehrbakhsh Nilashi

    (School of Biomedical Engineering and Health Sciences, Faculty of Engineering, Universiti Teknologi Malaysia, Skudai 81310, Johor, Malaysia)

  • Shahla Asadi

    (Centre of Software Technology and Management, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia)

  • Rabab Ali Abumalloh

    (Computer Department, Community College, Imam Abdulrahman Bin Faisal University, Dammam 34212, Saudi Arabia)

  • Sarminah Samad

    (Department of Business Administration, College of Business and Administration, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia)

  • Fahad Ghabban

    (Faculty of Computer Science and Engineering, Information System Department, Taibah University, Madinah 41411, Saudi Arabia)

  • Eko Supriyanto

    (School of Biomedical Engineering and Health Sciences, Faculty of Engineering, Universiti Teknologi Malaysia, Skudai 81310, Johor, Malaysia)

  • Reem Osman

    (Computer Department, Community College, Imam Abdulrahman Bin Faisal University, Dammam 34212, Saudi Arabia)

Abstract

This study aims to develop a new approach based on machine learning techniques to assess sustainability performance. Two main dimensions of sustainability, ecological sustainability, and human sustainability, were considered in this study. A set of sustainability indicators was used, and the research method in this study was developed using cluster analysis and prediction learning techniques. A Self-Organizing Map (SOM) was applied for data clustering, while Classification and Regression Trees (CART) were applied to assess sustainability performance. The proposed method was evaluated through Sustainability Assessment by Fuzzy Evaluation (SAFE) dataset, which comprises various indicators of sustainability performance in 128 countries. Eight clusters from the data were found through the SOM clustering technique. A prediction model was found in each cluster through the CART technique. In addition, an ensemble of CART was constructed in each cluster of SOM to increase the prediction accuracy of CART. All prediction models were assessed through the adjusted coefficient of determination approach. The results demonstrated that the prediction accuracy values were high in all CART models. The results indicated that the method developed by ensembles of CART and clustering provide higher prediction accuracy than individual CART models. The main advantage of integrating the proposed method is its ability to automate decision rules from big data for prediction models. The method proposed in this study could be implemented as an effective tool for sustainability performance assessment.

Suggested Citation

  • Mehrbakhsh Nilashi & Shahla Asadi & Rabab Ali Abumalloh & Sarminah Samad & Fahad Ghabban & Eko Supriyanto & Reem Osman, 2021. "Sustainability Performance Assessment Using Self-Organizing Maps (SOM) and Classification and Ensembles of Regression Trees (CART)," Sustainability, MDPI, vol. 13(7), pages 1-24, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:7:p:3870-:d:527736
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/7/3870/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/7/3870/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ramin Gharizadeh Beiragh & Reza Alizadeh & Saeid Shafiei Kaleibari & Fausto Cavallaro & Sarfaraz Hashemkhani Zolfani & Romualdas Bausys & Abbas Mardani, 2020. "An integrated Multi-Criteria Decision Making Model for Sustainability Performance Assessment for Insurance Companies," Sustainability, MDPI, vol. 12(3), pages 1, January.
    2. de Olde, Evelien M. & Bokkers, Eddie A.M. & de Boer, Imke J.M., 2017. "The Choice of the Sustainability Assessment Tool Matters: Differences in Thematic Scope and Assessment Results," Ecological Economics, Elsevier, vol. 136(C), pages 77-85.
    3. Ness, Barry & Urbel-Piirsalu, Evelin & Anderberg, Stefan & Olsson, Lennart, 2007. "Categorising tools for sustainability assessment," Ecological Economics, Elsevier, vol. 60(3), pages 498-508, January.
    4. Antipov, Evgeny & Pokryshevskaya, Elena, 2010. "Mass appraisal of residential apartments: An application of Random forest for valuation and a CART-based approach for model diagnostics," MPRA Paper 27645, University Library of Munich, Germany.
    5. Mehrbakhsh Nilashi & Fausto Cavallaro & Abbas Mardani & Edmundas Kazimieras Zavadskas & Sarminah Samad & Othman Ibrahim, 2018. "Measuring Country Sustainability Performance Using Ensembles of Neuro-Fuzzy Technique," Sustainability, MDPI, vol. 10(8), pages 1-20, August.
    6. Ali, Syed Ahtsham & Alharthi, Majed & Hussain, Hafezali Iqbal & Rasul, Farhat & Hanif, Imran & Haider, Jahanzaib & Ullah, Saad & ur Rahman, Saeed & Abbas, Qaiser, 2021. "A clean technological innovation and eco-efficiency enhancement: A multi-index assessment of sustainable economic and environmental management," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    7. Begić, Fajik & Afgan, Naim H., 2007. "Sustainability assessment tool for the decision making in selection of energy system—Bosnian case," Energy, Elsevier, vol. 32(10), pages 1979-1985.
    8. Andriantiatsaholiniaina, Luc A. & Kouikoglou, Vassilis S. & Phillis, Yannis A., 2004. "Evaluating strategies for sustainable development: fuzzy logic reasoning and sensitivity analysis," Ecological Economics, Elsevier, vol. 48(2), pages 149-172, February.
    9. Aiyshwariya Paulvannan Kanmani & Renee Obringer & Benjamin Rachunok & Roshanak Nateghi, 2020. "Assessing Global Environmental Sustainability Via an Unsupervised Clustering Framework," Sustainability, MDPI, vol. 12(2), pages 1-12, January.
    10. Phillis, Yannis A. & Grigoroudis, Evangelos & Kouikoglou, Vassilis S., 2011. "Sustainability ranking and improvement of countries," Ecological Economics, Elsevier, vol. 70(3), pages 542-553, January.
    11. Marko Hakovirta & Navodya Denuwara, 2020. "How COVID-19 Redefines the Concept of Sustainability," Sustainability, MDPI, vol. 12(9), pages 1-4, May.
    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. Mostafa Shaaban & Jürgen Scheffran & Jürgen Böhner & Mohamed S. Elsobki, 2018. "Sustainability Assessment of Electricity Generation Technologies in Egypt Using Multi-Criteria Decision Analysis," Energies, MDPI, vol. 11(5), pages 1-25, May.
    2. Weiwei Li & Pingtao Yi & Danning Zhang, 2018. "Sustainability Evaluation of Cities in Northeastern China Using Dynamic TOPSIS-Entropy Methods," Sustainability, MDPI, vol. 10(12), pages 1-15, December.
    3. Lhermie, Guillaume & Wernli, Didier & Jørgensen, Peter Søgaard & Kenkel, Donald & Lin Lawell, C.-Y. Cynthia & Tauer, Loren William & Gröhn, Yrjo Tapio, 2019. "Tradeoffs between resistance to antimicrobials in public health and their use in agriculture: Moving towards sustainability assessment," Ecological Economics, Elsevier, vol. 166(C), pages 1-1.
    4. Phillis, Yannis A. & Kouikoglou, Vassilis S., 2012. "System-of-Systems hierarchy of biodiversity conservation problems," Ecological Modelling, Elsevier, vol. 235, pages 36-48.
    5. Janmontree, Jettarat & Zadek, Hartmut, 2020. "Development of sustainability performance measurement framework for measuring complex sustainability impacts in the manufacturing industry," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Data Science in Maritime and City Logistics: Data-driven Solutions for Logistics and Sustainability. Proceedings of the Hamburg International Conferen, volume 30, pages 3-31, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    6. Eleonora Bottani & Maria Carmen Gentilotti & Marta Rinaldi, 2017. "A Fuzzy Logic-Based Tool for the Assessment of Corporate Sustainability: A Case Study in the Food Machinery Industry," Sustainability, MDPI, vol. 9(4), pages 1-29, April.
    7. Joseph MacPherson & Carsten Paul & Katharina Helming, 2020. "Linking Ecosystem Services and the SDGs to Farm-Level Assessment Tools and Models," Sustainability, MDPI, vol. 12(16), pages 1-19, August.
    8. Rubio Rodríguez, M.A. & Ruyck, J. De & Díaz, P. Roque & Verma, V.K. & Bram, S., 2011. "An LCA based indicator for evaluation of alternative energy routes," Applied Energy, Elsevier, vol. 88(3), pages 630-635, March.
    9. Pin Li & Jinsuo Zhang, 2019. "Is China’s Energy Supply Sustainable? New Research Model Based on the Exponential Smoothing and GM(1,1) Methods," Energies, MDPI, vol. 12(2), pages 1-30, January.
    10. Figge, Frank & Hahn, Tobias & Barkemeyer, Ralf, 2014. "The If, How and Where of assessing sustainable resource use," Ecological Economics, Elsevier, vol. 105(C), pages 274-283.
    11. Paul, Ananna & Shukla, Nagesh & Trianni, Andrea, 2023. "Modelling supply chain sustainability challenges in the food processing sector amid the COVID-19 outbreak," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    12. L. Hay & A. H. B. Duffy & R. I. Whitfield, 2017. "The S‐Cycle Performance Matrix: Supporting Comprehensive Sustainability Performance Evaluation of Technical Systems," Systems Engineering, John Wiley & Sons, vol. 20(1), pages 45-70, January.
    13. Jean-Marc Douguet & Pierre Failler & Gianluca Ferraro, 2022. "Sustainability Assessment of the Societal Costs of Fishing Activities in a Deliberative Perspective," Sustainability, MDPI, vol. 14(10), pages 1-21, May.
    14. Diana Tuomasjukka & Staffan Berg & Marcus Lindner, 2013. "Managing Sustainability of Fennoscandian Forests and Their Use by Law and/or Agreement: For Whom and Which Purpose?," Sustainability, MDPI, vol. 6(1), pages 1-32, December.
    15. Georgiadou, Maria Christina & Hacking, Theophilus & Guthrie, Peter, 2012. "A conceptual framework for future-proofing the energy performance of buildings," Energy Policy, Elsevier, vol. 47(C), pages 145-155.
    16. Ngoc-Ninh Ho & Truong Lam Do & Dinh-Thao Tran & Trung Thanh Nguyen, 2022. "Indigenous pig production and welfare of ultra-poor ethnic minority households in the Northern mountains of Vietnam," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(1), pages 156-179, January.
    17. Schilling, Markus & Chiang, Lichun, 2011. "The effect of natural resources on a sustainable development policy: The approach of non-sustainable externalities," Energy Policy, Elsevier, vol. 39(2), pages 990-998, February.
    18. Kristoffer B. Birkeland & Allan D. D'Silva & Roland Füss & Are Oust, 2021. "The Predictability of House Prices: "Human Against Machine"," International Real Estate Review, Global Social Science Institute, vol. 24(2), pages 139-183.
    19. Shang, Hua & Jiang, Li & Pan, Xianyou & Pan, Xiongfeng, 2022. "Green technology innovation spillover effect and urban eco-efficiency convergence: Evidence from Chinese cities," Energy Economics, Elsevier, vol. 114(C).
    20. Alexandra Doernberg & Annette Piorr & Ingo Zasada & Dirk Wascher & Ulrich Schmutz, 2022. "Sustainability assessment of short food supply chains (SFSC): developing and testing a rapid assessment tool in one African and three European city regions," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 39(3), pages 885-904, September.

    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:13:y:2021:i:7:p:3870-:d:527736. 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.