Skip to main content
SpringerLink
Log in

A chance-constrained network DEA approach based on enhanced Russell-based directional distance measure to evaluate public sector performance: a case study of OECD countries

  • Original Research
  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

Decision-making quality is a concern for the public sector because its decisions may involve more dimensions than those faced by the private sector. However, past studies on public sector efficiency have ignored the uncertainty of data estimation. This study addresses this shortcoming by proposing a chance-constrained network DEA approach based on an enhanced Russell-based directional distance measure that evaluates public sector performance. The proposed approach uses stochastic inputs and outputs to enhance decision-making quality and capacity in the public sector. The usefulness of this approach is demonstrated through an empirical case of the OECD. Our approach also provides practical suggestions for promoting a green economic transformation and serves as a reference for government policies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Adam, A., Delis, M. D., & Kammas, P. (2013). Fiscal decentralization and public sector efficiency: Evidence from OECD countries. Economics of Governance, 15(1), 17–49. https://doi.org/10.1007/s10101-013-0131-4

    Article  Google Scholar 

  • Afzalinejad, M. (2021). Evaluating radial efficiency considering environmental factors: A generalization of classical DEA. Measurement. https://doi.org/10.1016/j.measurement.2021.109497

    Article  Google Scholar 

  • Arbolino, R., Boffardi, R., Ioppolo, G., Lantz, T., & Rosa, P. (2022). Evaluating industrial sustainability in OECD countries: A cross-country comparison. Journal of Cleaner Production, 331, 129773.

    Article  Google Scholar 

  • Aye, G. C., Gupta, R., & Wanke, P. (2018). Energy efficiency drivers in South Africa: 1965–2014. Energy Efficiency, 11(6), 1465–1482.

    Article  Google Scholar 

  • Chen, P.-C., & Yu, M.-M. (2014). Total factor productivity growth and directions of technical change bias: Evidence from 99 OECD and non-OECD countries. Annals of Operations Research, 214(1), 143–165.

    Article  Google Scholar 

  • Cherchye, L., De Witte, K., Ooghe, E., & Nicaise, I. (2010). Efficiency and equity in private and public education: A nonparametric comparison. European Journal of Operational Research, 202(2), 563–573. https://doi.org/10.1016/j.ejor.2009.06.015

    Article  Google Scholar 

  • Christl, M., Köppl-Turyna, M., & Kucsera, D. (2020). Determinants of public-sector efficiency: decentralization and fiscal rules. Kyklos, 73(2), 253–290.

    Article  Google Scholar 

  • Costa-Campi, M. T., Garcia-Quevedo, J., & Martínez-Ros, E. (2017). What are the determinants of investment in environmental R&D? Energy Policy, 104, 455–465.

    Article  Google Scholar 

  • Galagedera, D. U. A. (2017). Modelling superannuation fund management function as a two-stage process for overall and stage-level performance appraisal. Applied Economics, 50(22), 2439–2458. https://doi.org/10.1080/00036846.2017.1400649

    Article  Google Scholar 

  • Guccio, C., Martorana, M., Mazza, I., Pignataro, G., & Rizzo, I. (2020). An assessment of the performance of Italian public historical archives: Preservation vs utilisation. Journal of Policy Modeling, 42(6), 1270–1286.

    Article  Google Scholar 

  • Gunasekaran, A., Irani, Z., & Papadopoulos, T. (2014). Modelling and analysis of sustainable operations management: Certain investigations for research and applications. Journal of the Operational Research Society, 65(6), 806–823.

    Article  Google Scholar 

  • Izadikhah, M., & Saen, R. F. (2018). Assessing sustainability of supply chains by chance-constrained two-stage DEA model in the presence of undesirable factors. Computers & Operations Research, 100, 343–367.

    Article  Google Scholar 

  • Kava, H., Spanaki, K., Papadopoulos, T., Despoudi, S., Rodriguez-Espindola, O., & Fakhimi, M. (2021). Data analytics diffusion in the UK renewable energy sector: An innovation perspective. Annals of Operations Research. https://doi.org/10.1007/s10479-021-04263-1

    Article  Google Scholar 

  • Kaya Samut, P., & Cafrı, R. (2015). Analysis of the efficiency determinants of health systems in OECD countries by DEA and panel tobit. Social Indicators Research, 129(1), 113–132. https://doi.org/10.1007/s11205-015-1094-3

    Article  Google Scholar 

  • Keskin, B. (2021). An efficiency analysis on social prosperity: OPEC case under network DEA slack-based measure approach. Energy. https://doi.org/10.1016/j.energy.2021.120832

    Article  Google Scholar 

  • Khodadadipour, M., Hadi-Vencheh, A., Behzadi, M. H., & Rostamy-malkhalifeh, M. (2021). Undesirable factors in stochastic DEA cross-efficiency evaluation: An application to thermal power plant energy efficiency. Economic Analysis and Policy, 69, 613–628. https://doi.org/10.1016/j.eap.2021.01.013

    Article  Google Scholar 

  • Kitamori, K., Manders, T., Dellink, R., & Tabeau, A. (2012). OECD environmental outlook to 2050: the consequences of inaction (9264122168). Retrieved from

  • Kuosmanen, T., Zhou, X., & Dai, S. J. W. D. (2020). How much climate policy has cost for OECD countries?, 125, 104681.

  • Land, K. C., Lovell, C. K., & Thore, S. (1993). Chance-constrained data envelopment analysis. Managerial and Decision Economics, 14(6), 541–554.

    Article  Google Scholar 

  • Le, P. T., & Nguyen, H.-O. (2020). Influence of policy, operational and market conditions on seaport efficiency in newly emerging economies: The case of Vietnam. Applied Economics, 52(43), 4698–4710.

    Article  Google Scholar 

  • Lin, F. Y., Lin, S. W., & Lu, W. M. (2018). Sustainability assessment of Taiwan’s semiconductor industry: A new hybrid model using combined analytic hierarchy process and two-stage additive network data envelopment analysis. Sustainability. https://doi.org/10.3390/su10114070

    Article  Google Scholar 

  • Mavi, N. K., & Mavi, R. K. (2019). Energy and environmental efficiency of OECD countries in the context of the circular economy: Common weight analysis for malmquist productivity index. Journal of Environmental Management, 247, 651–661.

    Article  Google Scholar 

  • Moheb-Alizadeh, H., & Handfield, R. (2018). An integrated chance-constrained stochastic model for efficient and sustainable supplier selection and order allocation. International Journal of Production Research, 56(21), 6890–6916. https://doi.org/10.1080/00207543.2017.1413258

    Article  Google Scholar 

  • Mohmmad Nejad, Z., & Ghaffari-Hadigheh, A. (2018). A novel DEA model based on uncertainty theory. Annals of Operations Research, 264(1), 367–389.

    Article  Google Scholar 

  • Mohsin, M., Hanif, I., Taghizadeh-Hesary, F., Abbas, Q., & Iqbal, W. (2021). Nexus between energy efficiency and electricity reforms: A DEA-based way forward for clean power development. Energy Policy. https://doi.org/10.1016/j.enpol.2020.112052

    Article  Google Scholar 

  • Moon, H., & Min, D. (2020). A DEA approach for evaluating the relationship between energy efficiency and financial performance for energy-intensive firms in Korea. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2020.120283

    Article  Google Scholar 

  • Nasseri, S. H., Ebrahimnejad, A., & Gholami, O. (2018). Fuzzy stochastic data envelopment analysis with undesirable outputs and its application to banking industry. International Journal of Fuzzy Systems, 20(2), 534–548.

    Article  Google Scholar 

  • Nicolli, F., & Vona, F. (2019). Energy market liberalization and renewable energy policies in OECD countries. Energy Policy, 128, 853–867.

    Article  Google Scholar 

  • Olesen, O. B., & Petersen, N. C. (2016). Stochastic data envelopment analysis—A review. European Journal of Operational Research, 251(1), 2–21.

    Article  Google Scholar 

  • Oppi, C., Campanale, C., & Cinquini, L. (2022). Ambiguity in public sector performance measurement: A systematic literature review. Journal of Public Budgeting, Accounting & Financial Management, 34(3), 370–390.

    Article  Google Scholar 

  • Ozcan, B., Tzeremes, P. G., & Tzeremes, N. G. J. E. M. (2020). Energy consumption, economic growth and environmental degradation in OECD countries. 84, 203–213.

  • Paramati, S. R., Shahzad, U., & Doğan, B. (2022). The role of environmental technology for energy demand and energy efficiency: Evidence from OECD countries. Renewable and Sustainable Energy Reviews, 153, 111735.

    Article  Google Scholar 

  • Park, S., Ok, C., & Ha, C. (2018). A stochastic simulation-based holistic evaluation approach with DEA for vendor selection. Computers & Operations Research, 100, 368–378.

    Article  Google Scholar 

  • Rietig, K. J. E. P. (2019). The importance of compatible beliefs for effective climate policy integration. 28(2), 228–247.

  • Seiford, L. M., & Zhu, J. (2002). Modeling undesirable factors in efficiency evaluation. European Journal of Operational Research, 142(1), 16–20.

    Article  Google Scholar 

  • Shen, Z., Boussemart, J.-P., & Leleu, H. (2017). Aggregate green productivity growth in OECD’s countries. International Journal of Production Economics, 189, 30–39. https://doi.org/10.1016/j.ijpe.2017.04.007

    Article  Google Scholar 

  • Tavassoli, M., Fathi, A., & Farzipoor Saen, R. (2021). Developing a new super-efficiency DEA model in the presence of both zero data and stochastic data: A case study in the Iranian airline industry. Benchmarking: an International Journal, 28(1), 42–65.

    Article  Google Scholar 

  • Wang, R., Wang, Q., & Yao, S. (2021). Evaluation and difference analysis of regional energy efficiency in China under the carbon neutrality targets: Insights from DEA and Theil models. Journal of Environmental Management, 293, 112958.

    Article  Google Scholar 

  • Wanke, P., Barros, C. P., & Emrouznejad, A. (2016). Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping: A case of Mozambican banks. European Journal of Operational Research, 249(1), 378–389.

    Article  Google Scholar 

  • Yadava, A. K., & Neog, Y. (2022). Public sector performance and efficiency assessment of Indian states. Global Business Review, 23(2), 493–511.

    Article  Google Scholar 

  • Yu, D., & He, X. (2020). A bibliometric study for DEA applied to energy efficiency: Trends and future challenges. Applied Energy. https://doi.org/10.1016/j.apenergy.2020.115048

    Article  Google Scholar 

  • Zakari, A., Khan, I., Tan, D., Alvarado, R., & Dagar, V. (2022). Energy efficiency and sustainable development goals (SDGs). Energy, 239, 122365.

    Article  Google Scholar 

  • Zhang, C., & Chen, P. (2022). Applying the three-stage SBM-DEA model to evaluate energy efficiency and impact factors in RCEP countries. Energy. https://doi.org/10.1016/j.energy.2021.122917

    Article  Google Scholar 

  • Zhao, X., Ma, X., Shang, Y., Yang, Z., & Shahzad, U. (2022). Green economic growth and its inherent driving factors in Chinese cities: Based on the Metafrontier-global-SBM super-efficiency DEA model. Gondwana Research, 106, 315–328.

    Article  Google Scholar 

  • Zhou, X., Xu, Z., Chai, J., Yao, L., Wang, S., & Lev, B. (2019). Efficiency evaluation for banking systems under uncertainty: A multi-period three-stage DEA model. Omega, 85, 68–82.

    Article  Google Scholar 

Download references

Funding

This research was supported by the Ministry of Science and Technology, Taiwan, R.O.C. under Grant No. MOST111-2410-H-606–003 and MOST110-2410-H-034–021-MY3.

Author information

Authors and Affiliations

  1. Department of Financial Management, National Defense University, No. 70, Section 2, Zhongyang North Road, Beitou, Taipei, 112, Taiwan

    Sheng-Wei Lin

  2. Department of International Business Administration, Chinese Culture University, No. 55, Hwa-Kang Road, Shilin District, Taipei, 11114, Taiwan

    Wen-Min Lu

Authors
  1. Sheng-Wei Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wen-Min Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wen-Min Lu.

Ethics declarations

Conflict of interests

The authors declare that they have no conflicts of interest.

Animal and Human participants

This article does not contain any studies involving human participants performed by any of the authors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lin, SW., Lu, WM. A chance-constrained network DEA approach based on enhanced Russell-based directional distance measure to evaluate public sector performance: a case study of OECD countries. Ann Oper Res (2023). https://doi.org/10.1007/s10479-023-05337-y

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10479-023-05337-y

Keywords

Search

Navigation