Relationship between sustainable development indicators and SMEs’ development indicators: Evidence from the EU countries

  • Received February 27, 2024;
    Accepted April 5, 2024;
    Published April 16, 2024
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/ppm.22(2).2024.07
  • Article Info
    Volume 22 2024, Issue #2, pp. 71-92
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This work is licensed under a Creative Commons Attribution 4.0 International License

This study aims to identify whether achieving sustainable development goals influences SMEs’ development and assess its degree. The dataset on SMEs’ development indicators and SDGs 2, 8, 9, 12, and 13 for the panel of EU-27 countries in 2011–2020 was collected using Eurostat and OECD datasets. Breusch and Pagan Lagrangian multiplier test for pooled OLS/panel data random effects and Hausman test for fixed/random effects were utilized. The results were in favor of random effect GLS regression for SDG2 models, SDG9 models, and SDG12-13 (Model 1) and fixed effect GLS regression for SDG8 models and SDG12-13 (Model 2), respectively. Based on bibliometric analyses using VOSViewer 14 and a comprehensive literature review, 19 independent variables have been selected from the “Sustainable development indicators” catalog covering five sustainable development goals; SMEs’ turnover and SMEs’ employees employed are used as the dependent variables to reflect SMEs’ development. The empirical evidence suggests a significant relationship between individual sustainable development and SMEs’ development indicators. It was found that all seven sustainable development indicators of SDG 2 (Zero hunger) and SDG 12 (Responsible consumption and production) have a significant relationship with the indicators of SMEs’ development. Instead, only a part (8 out of 13) of the sustainable development indicators of SDG 8 (Decent work and economic growth), SDG 9 (Industry, innovation and infrastructure), and SDG 13 (Climate action) have a significant relationship with two or one of the SMEs’ development indicators. Therefore, achieving sustainability goals stimulates the development of SMEs itself.

Acknowledgment
This study is supported by the British Academy’s Researchers at Risk Fellowships Program (Award Reference: RaR\100673).

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    • Figure 1. The “Sustainable development – SMEs’ development” network visualization
    • Figure 2. The “Sustainable development goals” keywords network visualization
    • Table 1. The estimated results of GLS FE and RE for the SDG 2, SDG 12-13 indicators, and the SMEs’ development
    • Table 2. The estimated results of GLS FE and RE for the SDG 8, SDG 9 indicators, and the SMEs’ development indicators
    • Table A1. Pearson correlation matrix for SDG2 and SMEs indicators
    • Table A2. Pearson correlation matrix for SDG12-13 and SMEs indicators
    • Table A3. Pearson correlation matrix for SDG8 and SMEs indicators
    • Table A4. VIF values for SDG8 indicators and SMEs’ persons employed as the dependent variable (EmpltmntRt included)
    • Table A5. VIF values for SDG8 indicators and SMEs’ persons employed as the dependent variable (EmpltmntRt excluded)
    • Table A6. VIF values for SDG8 indicators and SMEs’ turnover as the dependent variable (EmpltmntRt included)
    • Table A7. VIF values for SDG8 indicators and SMEs’ turnover as the dependent variable (EmpltmntRt excluded)
    • Table A8. Pearson correlation matrix for SDG9 and SMEs indicators
    • Table A9. VIF values for SDG9 indicators and SMEs’ persons employed as the dependent variable (Patent_Inn included)
    • Table A10. VIF values for SDG9 indicators and SMEs’ persons employed as the dependent variable (Patent_Inn excluded)
    • Table A11. VIF values for SDG9 indicators and SMEs’ turnover as the dependent variable (Patent_Inn included)
    • Table A12. VIF values for SDG9 indicators and SMEs’ turnover as the dependent variable (Patent_Inn excluded)
    • Table B1. Estimated results of Breusch and Pagan Lagrangian multiplier test for random effects for SDG2 and SMEs’ employment
    • Table B2. Estimated results of Breusch and Pagan Lagrangian multiplier test for random effects for SDG2 and SMEs’ turnover
    • Table B3. Estimated results of Breusch and Pagan Lagrangian multiplier test for random effects for SDG12-13 and SMEs’ employment
    • Table B4. Results of Breusch and Pagan Lagrangian multiplier test for random effects for SDG12-13 and SMEs’ turnover
    • Table B5. Results of Breusch and Pagan Lagrangian multiplier test for random effects for SDG8 and SMEs’ employment
    • Table B6. Results of Breusch and Pagan Lagrangian multiplier test for random effects for SDG8 and SMEs’ turnover
    • Table B7. Results of Breusch and Pagan Lagrangian multiplier test for random effects for SDG9 and SMEs’ employment
    • Table B8. Results of Breusch and Pagan Lagrangian multiplier test for random effects for SDG9 and SMEs’ turnover
    • Table C1. Hausman test for SDG2 and SMEs’ employment
    • Table C2. Hausman test for SDG2 and SMEs’ turnover
    • Table C3. Hausman test for SDG12-13 and SMEs’ employment
    • Table C4. Hausman test for SDG12-13 and SMEs’ turnover
    • Table C5. Hausman test for SDG8 and SMEs’ employment
    • Table C6. Hausman test for SDG8 and SMEs’ turnover
    • Table C7. Hausman test for SDG9 and SMEs’ employment
    • Table C8. Hausman test for SDG9 and SMEs’ turnover
    • Conceptualization
      Bohdan Kovalov
    • Data curation
      Bohdan Kovalov
    • Formal Analysis
      Bohdan Kovalov
    • Funding acquisition
      Bohdan Kovalov
    • Investigation
      Bohdan Kovalov
    • Methodology
      Bohdan Kovalov
    • Project administration
      Bohdan Kovalov
    • Resources
      Bohdan Kovalov
    • Software
      Bohdan Kovalov
    • Supervision
      Bohdan Kovalov
    • Validation
      Bohdan Kovalov
    • Visualization
      Bohdan Kovalov
    • Writing – original draft
      Bohdan Kovalov
    • Writing – review & editing
      Bohdan Kovalov