IDEAS home Printed from https://ideas.repec.org/a/spr/endesu/v25y2023i5d10.1007_s10668-022-02210-z.html
   My bibliography  Save this article

A hybrid novel approach for evaluation of resiliency and sustainability in construction environment using data envelopment analysis, principal component analysis, and mathematical formulation

Author

Listed:
  • Zahra Mohammadnazari

    (University of Tehran)

  • Amir Aghsami

    (University of Tehran
    K. N. Toosi University of Technology)

  • Masoud Rabbani

    (University of Tehran)

Abstract

This article utilizes balanced score card (BSC) and resilience engineering factors for organizational performance. The methodology involves two stages: in the first stage, we tried to find the efficiency of organization based on previous projects of the organization applying data envelopment analysis (DEA). In order to apply DEA model for organizational assessment, some questionnaires have been spread among managers of the organization. Principal component analysis (PCA) is introduced in the second stage to highlight the shaping factors that influence overall efficiency. Furthermore, a comparison will be made with sensitivity analysis of DEA and PCA results. The results of the comparison highlight the importance of the three categories (BSC, RE, and sustainability) on organizational performance. After identifying the shaping factors and assessing the organization’s situation, artificial neural network (ANN) is applied to help us find the success factor (utility) of future projects and a mathematical formulation is presented which helps the decision makers select the best projects considering organizational situation and values. According to results, resilience engineering factors, including flexibility, management commitment, reporting culture, learning, awareness, preparedness, teamwork, redundancy, self-organization, and fault tolerance, are the most shaping and decisive factors in organization efficiency. The importance of RE over environmental factors and the coverage of data made by RE factors indicate that this construction environment devoted a great deal of attention to RE factors.

Suggested Citation

  • Zahra Mohammadnazari & Amir Aghsami & Masoud Rabbani, 2023. "A hybrid novel approach for evaluation of resiliency and sustainability in construction environment using data envelopment analysis, principal component analysis, and mathematical formulation," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(5), pages 4453-4490, May.
  • Handle: RePEc:spr:endesu:v:25:y:2023:i:5:d:10.1007_s10668-022-02210-z
    DOI: 10.1007/s10668-022-02210-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10668-022-02210-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10668-022-02210-z?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Chiung-Lin & Shang, Kuo-Chung & Lirn, Taih-Cherng & Lai, Kee-Hung & Lun, Y.H. Venus, 2018. "Supply chain resilience, firm performance, and management policies in the liner shipping industry," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 202-219.
    2. Yarveisy, Rioshar & Gao, Chuan & Khan, Faisal, 2020. "A simple yet robust resilience assessment metrics," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    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. Edith Callaghan & John Colton, 2008. "Building sustainable & resilient communities: a balancing of community capital," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 10(6), pages 931-942, December.
    5. Cai, Baoping & Xie, Min & Liu, Yonghong & Liu, Yiliu & Feng, Qiang, 2018. "Availability-based engineering resilience metric and its corresponding evaluation methodology," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 216-224.
    6. Ruiz-Benítez, Rocío & López, Cristina & Real, Juan C., 2018. "The lean and resilient management of the supply chain and its impact on performance," International Journal of Production Economics, Elsevier, vol. 203(C), pages 190-202.
    7. David J. Yu & Michael L. Schoon & Jason K. Hawes & Seungyoon Lee & Jeryang Park & P. Suresh C. Rao & Laura K. Siebeneck & Satish V. Ukkusuri, 2020. "Toward General Principles for Resilience Engineering," Risk Analysis, John Wiley & Sons, vol. 40(8), pages 1509-1537, August.
    8. 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.
    9. Zahra Mohammadnazari & Seyed Farid Ghannadpour, 2021. "Sustainable construction supply chain management with the spotlight of inventory optimization under uncertainty," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(7), pages 10937-10972, July.
    10. Shirali, Gh.A. & Mohammadfam, I. & Ebrahimipour, V., 2013. "A new method for quantitative assessment of resilience engineering by PCA and NT approach: A case study in a process industry," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 88-94.
    11. W D Cook & L Liang & Y Zha & J Zhu, 2009. "A modified super-efficiency DEA model for infeasibility," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(2), pages 276-281, February.
    12. Hu, Benyong & Meng, Chao & Xu, Dong & Son, Young-Jun, 2018. "Supply chain coordination under vendor managed inventory-consignment stocking contracts with wholesale price constraint and fairness," International Journal of Production Economics, Elsevier, vol. 202(C), pages 21-31.
    13. Elbanna, Said, 2016. "Managers' autonomy, strategic control, organizational politics and strategic planning effectiveness: An empirical investigation into missing links in the hotel sector," Tourism Management, Elsevier, vol. 52(C), pages 210-220.
    14. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    15. Rajiv D. Banker & Richard C. Morey, 1986. "Efficiency Analysis for Exogenously Fixed Inputs and Outputs," Operations Research, INFORMS, vol. 34(4), pages 513-521, August.
    16. Aida Rezaei & Amir Aghsami & Masoud Rabbani, 2021. "Supplier selection and order allocation model with disruption and environmental risks in centralized supply chain," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(6), pages 1036-1072, December.
    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. Alexandre Marinho & Simone de Souza Cardoso & Vivian Vicente de Almeida, 2009. "Avaliação da Eficiência Técnica dos Países nos Jogos Olímpicos de Pequim – 2008," Discussion Papers 1394, Instituto de Pesquisa Econômica Aplicada - IPEA.
    2. Karima Kourtit & Peter Nijkamp & Soushi Suzuki, 2023. "Quantitative performance assessment of Asian stellar cities by a DEA cascade system: a capability interpretation," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 70(1), pages 259-286, February.
    3. Zervopoulos, Panagiotis & Emrouznejad, Ali & Sklavos, Sokratis, 2019. "A Bayesian approach for correcting bias of data envelopment analysis estimators," MPRA Paper 91886, University Library of Munich, Germany.
    4. Fernández, David & Pozo, Carlos & Folgado, Rubén & Jiménez, Laureano & Guillén-Gosálbez, Gonzalo, 2018. "Productivity and energy efficiency assessment of existing industrial gases facilities via data envelopment analysis and the Malmquist index," Applied Energy, Elsevier, vol. 212(C), pages 1563-1577.
    5. Cheng, Gang & Zervopoulos, Panagiotis, 2012. "A proxy approach to dealing with the infeasibility problem in super-efficiency data envelopment analysis," MPRA Paper 42064, University Library of Munich, Germany.
    6. Nima Monghasemi & Amir Vadiee & Konstantinos Kyprianidis & Elaheh Jalilzadehazhari, 2023. "Rank-Based Assessment of Grid-Connected Rooftop Solar Panel Deployments Considering Scenarios for a Postponed Installation," Energies, MDPI, vol. 16(21), pages 1-16, October.
    7. Emmanuel Thanassoulis & Maria Da Conceicao & A. Silva Portela, 2002. "School Outcomes: Sharing the Responsibility Between Pupil and School1," Education Economics, Taylor & Francis Journals, vol. 10(2), pages 183-207.
    8. Mahmoudi, Reza & Emrouznejad, Ali & Shetab-Boushehri, Seyyed-Nader & Hejazi, Seyed Reza, 2020. "The origins, development and future directions of data envelopment analysis approach in transportation systems," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    9. Lin, Ruiyue & Liu, Yue, 2019. "Super-efficiency based on the directional distance function in the presence of negative data," Omega, Elsevier, vol. 85(C), pages 26-34.
    10. Bozec, Richard & Dia, Mohamed, 2007. "Board structure and firm technical efficiency: Evidence from Canadian state-owned enterprises," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1734-1750, March.
    11. Baldin, Andrea, 2017. "A DEA approach for selecting a bundle of tickets for performing arts events," Journal of Retailing and Consumer Services, Elsevier, vol. 39(C), pages 190-200.
    12. Guo-Ya Gan & Hsuan-Shih Lee, 2021. "Resolving the infeasibility of the super-efficiency DEA based on DDF," Annals of Operations Research, Springer, vol. 307(1), pages 139-152, December.
    13. Ghasemi, M.-R. & Ignatius, Joshua & Emrouznejad, Ali, 2014. "A bi-objective weighted model for improving the discrimination power in MCDEA," European Journal of Operational Research, Elsevier, vol. 233(3), pages 640-650.
    14. An, Qingxian & Tao, Xiangyang & Chen, Xiaohong, 2023. "Nested frontier-based best practice regulation under asymmetric information in a principal–agent framework," European Journal of Operational Research, Elsevier, vol. 306(1), pages 269-285.
    15. Ya Chen & Yongjun Li & Liang Liang & Huaqing Wu, 2019. "An extension on super slacks-based measure DEA approach," Annals of Operations Research, Springer, vol. 278(1), pages 101-121, July.
    16. Zhu, Joe, 2000. "Multi-factor performance measure model with an application to Fortune 500 companies," European Journal of Operational Research, Elsevier, vol. 123(1), pages 105-124, May.
    17. Ghasemi, Mohammad Reza & Ignatius, Joshua & Rezaee, Babak, 2019. "Improving discriminating power in data envelopment models based on deviation variables framework," European Journal of Operational Research, Elsevier, vol. 278(2), pages 442-447.
    18. Saranga, Haritha, 2009. "The Indian auto component industry - Estimation of operational efficiency and its determinants using DEA," European Journal of Operational Research, Elsevier, vol. 196(2), pages 707-718, July.
    19. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
    20. Chen, Nengcheng & Xu, Lei & Chen, Zeqiang, 2017. "Environmental efficiency analysis of the Yangtze River Economic Zone using super efficiency data envelopment analysis (SEDEA) and tobit models," Energy, Elsevier, vol. 134(C), pages 659-671.

    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:spr:endesu:v:25:y:2023:i:5:d:10.1007_s10668-022-02210-z. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.