Research Article
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Year 2021, Issue: 37, 58 - 67, 31.12.2021

Selin Ceren Turan Emre Dünder Mehmet Ali Cengiz

https://doi.org/10.53570/jnt.1034246

Abstract

Thanks

İlgili hakem ve editörlerimize, çalışmamıza göstermiş oldukları ilgi ve ayırdıkları zaman için çok teşekkür ederiz.

References

  • E. Marshall, J. Shortle, Using DEA and VEA to evaluate quality of life in the Mid-Atlantic States, Agricultural and Resource Economics Review 34(2) (2005) 185–203.
  • H. C. Siong, M. Z. S. M Hussein, Modeling Urban Quality of Life with Data Envelopment Analysis Methods, Research Result Report, Universiti Teknologi Malaysia, VOT78513, 2008.
  • Y. Yu, Z. Wen, Evaluating China’s Urban Environmental Sustainability with Data Envelopment Analysis, Ecological Economics (69) (2010) 1748–1755.
  • D. Yoshino, A. Fujiwara, J. Zhang, Environmental Efficiency Model Based on Data Envelopment Analysis and Its Application to Environmentally Sustainable Transport Policies, Transportation Research Record 2163(1) (2010) 112–123.
  • Z. Xiaoping, L. Yuanfang, W. Wenjia, Evaluation of Urban Resource and Environmental Efficiency in China Based on The DEA Model, Journal of Resources and Ecology 5(1) (2014) 11–19.
  • T. S. Adebayo, D. Kirikkaleli, I. Adeshola, D. Oluwajana, G. D. Akinsola, O. S. Osemeahon, Coal Consumption and Environmental Sustainability in South Africa: The Role of Financial Development and Globalization, International Journal of Renewable Energy Development 10(3) (2021) 527–536.
  • S. Kihombo, A. I. Vaseer, Z. Ahmed, S. Chen, D. Kirikkaleli, T. S. Adebayo, Is There a Trade-Off Between Financial Globalization, Economic Growth, and Environmental Sustainability? An Advanced panel Analysis, Environmental Science and Pollution Research (2021) 1–11.
  • S. A. R. Khan, P. Ponce, Z. Yu, H. Golpîra, M. Mathew, Environmental Technology and Wastewater Treatment: Strategies to Achieve Environmental Sustainability, Chemosphere 286 (2022) 131532.
  • R. Akbani, S. Kwek, N. Japkowicz, Applying Support Vector Machines to Imbalanced Datasets, Machine Learning: ECML of the series Lecture Notes in Computer Science 3201 (2004) 39–50.
  • H. He, Learning from Imbalanced Data, IEEE Transactions on Knowledge and Data Engineering 21(9) (2009) 1263–1284.
  • A. Charnes, W. W. Cooper, E. Rhodes, Measuring the Efficiency of Decision-Making Units, European Journal of Operations Research 2(6) (1978) 429–444.
  • R. D. Banker, A. Charnes, W. Cooper, Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis, Management Science 30(9) (1984) 1078–1092.
  • T. Coelli, A Guide to DEAP Version 2.1: A Data Envelopment Analysis (Computer) Program, Centre for Efficiency and Productivity Analysis, University of New England, Australia 96(08) (1996) 1–49.
  • R. Fare, S. Grosskopf, Modeling Undesirable Factors in Efficiency Evaluation: Comment, European Journal of Operational Research 157(1) (2004) 242–245.
  • A. Charnes, W. Cooper, A. Y. Lewin, L. M. Seiford, Data Envelopment Analysis Theory, Methodology and Applications, Journal of the Operational Research Society 48(3) (1997) 332–333.
  • W. W. Cooper, L. M. Seiford, K. Tone, Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software, Journal of the Operational Research Society 52(12) (2001) 1408–1409.
  • S. Kotsiantis, D. Kanellopoulos, P. Pintelas, Handling Imbalanced Datasets: A Review, GESTS International Transactions on Computer Science and Engineering 30(1) (2006) 25–36.
  • R. S. Mitchell, J. G. Michalski, T. M. Carbonell, An Artificial Intelligence Approach, Berlin, Germany, Springer, 2013.
  • R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org/
  • P. Bogetoft, L. Otto, Benchmarking with Dea, Sfa, and r (Vol. 157). Springer Science & Business Media, 2010.
  • T. Therneau, B. Atkinson, (2019). rpart: Recursive Partitioning and Regression Trees. R package version 4.1-15. https://CRAN.R-project.org/package=rpart

Efficiency Analysis and Estimation of Factors Affecting the Efficiency with Decision Trees in Imbalanced Data: A Case of Turkey’s Environmental Sustainability

Year 2021, Issue: 37, 58 - 67, 31.12.2021

Selin Ceren Turan Emre Dünder Mehmet Ali Cengiz

https://doi.org/10.53570/jnt.1034246

Abstract

Cities have proliferated and experienced increasing environmental issues in the modern world. The concept of environmental sustainability is one of the main problems to solve. Therefore, it is fundamental to establish statistical methods to measure environmental sustainability. The first aim of this study is to measure the environmental sustainability performance of 42 cities in Turkey by Data Envelopment Analysis. The second aim is to solve the imbalance in the efficiency values obtained using Synthetic Minority Oversampling Technique methods. After all, we expose the multiple relationships between input and output variables and efficiency using the Decision trees classifiers approach. As a result of the analyses, three internal factors were found to influence the environmental efficiency levels: residential sales, population intensity, and the number of completed industrial sites. It has been determined that the number of completed industrial sites and the increase in residential sales distorted environmental efficiency.

Keywords

Classification decision trees DEA environmental sustainability imbalanced data SMOTE

References

  • E. Marshall, J. Shortle, Using DEA and VEA to evaluate quality of life in the Mid-Atlantic States, Agricultural and Resource Economics Review 34(2) (2005) 185–203.
  • H. C. Siong, M. Z. S. M Hussein, Modeling Urban Quality of Life with Data Envelopment Analysis Methods, Research Result Report, Universiti Teknologi Malaysia, VOT78513, 2008.
  • Y. Yu, Z. Wen, Evaluating China’s Urban Environmental Sustainability with Data Envelopment Analysis, Ecological Economics (69) (2010) 1748–1755.
  • D. Yoshino, A. Fujiwara, J. Zhang, Environmental Efficiency Model Based on Data Envelopment Analysis and Its Application to Environmentally Sustainable Transport Policies, Transportation Research Record 2163(1) (2010) 112–123.
  • Z. Xiaoping, L. Yuanfang, W. Wenjia, Evaluation of Urban Resource and Environmental Efficiency in China Based on The DEA Model, Journal of Resources and Ecology 5(1) (2014) 11–19.
  • T. S. Adebayo, D. Kirikkaleli, I. Adeshola, D. Oluwajana, G. D. Akinsola, O. S. Osemeahon, Coal Consumption and Environmental Sustainability in South Africa: The Role of Financial Development and Globalization, International Journal of Renewable Energy Development 10(3) (2021) 527–536.
  • S. Kihombo, A. I. Vaseer, Z. Ahmed, S. Chen, D. Kirikkaleli, T. S. Adebayo, Is There a Trade-Off Between Financial Globalization, Economic Growth, and Environmental Sustainability? An Advanced panel Analysis, Environmental Science and Pollution Research (2021) 1–11.
  • S. A. R. Khan, P. Ponce, Z. Yu, H. Golpîra, M. Mathew, Environmental Technology and Wastewater Treatment: Strategies to Achieve Environmental Sustainability, Chemosphere 286 (2022) 131532.
  • R. Akbani, S. Kwek, N. Japkowicz, Applying Support Vector Machines to Imbalanced Datasets, Machine Learning: ECML of the series Lecture Notes in Computer Science 3201 (2004) 39–50.
  • H. He, Learning from Imbalanced Data, IEEE Transactions on Knowledge and Data Engineering 21(9) (2009) 1263–1284.
  • A. Charnes, W. W. Cooper, E. Rhodes, Measuring the Efficiency of Decision-Making Units, European Journal of Operations Research 2(6) (1978) 429–444.
  • R. D. Banker, A. Charnes, W. Cooper, Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis, Management Science 30(9) (1984) 1078–1092.
  • T. Coelli, A Guide to DEAP Version 2.1: A Data Envelopment Analysis (Computer) Program, Centre for Efficiency and Productivity Analysis, University of New England, Australia 96(08) (1996) 1–49.
  • R. Fare, S. Grosskopf, Modeling Undesirable Factors in Efficiency Evaluation: Comment, European Journal of Operational Research 157(1) (2004) 242–245.
  • A. Charnes, W. Cooper, A. Y. Lewin, L. M. Seiford, Data Envelopment Analysis Theory, Methodology and Applications, Journal of the Operational Research Society 48(3) (1997) 332–333.
  • W. W. Cooper, L. M. Seiford, K. Tone, Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software, Journal of the Operational Research Society 52(12) (2001) 1408–1409.
  • S. Kotsiantis, D. Kanellopoulos, P. Pintelas, Handling Imbalanced Datasets: A Review, GESTS International Transactions on Computer Science and Engineering 30(1) (2006) 25–36.
  • R. S. Mitchell, J. G. Michalski, T. M. Carbonell, An Artificial Intelligence Approach, Berlin, Germany, Springer, 2013.
  • R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org/
  • P. Bogetoft, L. Otto, Benchmarking with Dea, Sfa, and r (Vol. 157). Springer Science & Business Media, 2010.
  • T. Therneau, B. Atkinson, (2019). rpart: Recursive Partitioning and Regression Trees. R package version 4.1-15. https://CRAN.R-project.org/package=rpart
There are 21 citations in total.

Details

Primary Language English
Subjects Applied Mathematics
Journal Section Research Article
Authors

Selin Ceren Turan 0000-0002-0290-5298

Emre Dünder 0000-0003-0230-8968

Mehmet Ali Cengiz 0000-0002-1271-2588

Publication Date December 31, 2021
Submission Date December 8, 2021
Published in Issue Year 2021 Issue: 37

Cite

APA Turan, S. C., Dünder, E., & Cengiz, M. A. (2021). Efficiency Analysis and Estimation of Factors Affecting the Efficiency with Decision Trees in Imbalanced Data: A Case of Turkey’s Environmental Sustainability. Journal of New Theory(37), 58-67. https://doi.org/10.53570/jnt.1034246
AMA Turan SC, Dünder E, Cengiz MA. Efficiency Analysis and Estimation of Factors Affecting the Efficiency with Decision Trees in Imbalanced Data: A Case of Turkey’s Environmental Sustainability. JNT. December 2021;(37):58-67. doi:10.53570/jnt.1034246
Chicago Turan, Selin Ceren, Emre Dünder, and Mehmet Ali Cengiz. “Efficiency Analysis and Estimation of Factors Affecting the Efficiency With Decision Trees in Imbalanced Data: A Case of Turkey’s Environmental Sustainability”. Journal of New Theory, no. 37 (December 2021): 58-67. https://doi.org/10.53570/jnt.1034246.
EndNote Turan SC, Dünder E, Cengiz MA (December 1, 2021) Efficiency Analysis and Estimation of Factors Affecting the Efficiency with Decision Trees in Imbalanced Data: A Case of Turkey’s Environmental Sustainability. Journal of New Theory 37 58–67.
IEEE S. C. Turan, E. Dünder, and M. A. Cengiz, “Efficiency Analysis and Estimation of Factors Affecting the Efficiency with Decision Trees in Imbalanced Data: A Case of Turkey’s Environmental Sustainability”, JNT, no. 37, pp. 58–67, December 2021, doi: 10.53570/jnt.1034246.
ISNAD Turan, Selin Ceren et al. “Efficiency Analysis and Estimation of Factors Affecting the Efficiency With Decision Trees in Imbalanced Data: A Case of Turkey’s Environmental Sustainability”. Journal of New Theory 37 (December 2021), 58-67. https://doi.org/10.53570/jnt.1034246.
JAMA Turan SC, Dünder E, Cengiz MA. Efficiency Analysis and Estimation of Factors Affecting the Efficiency with Decision Trees in Imbalanced Data: A Case of Turkey’s Environmental Sustainability. JNT. 2021;:58–67.
MLA Turan, Selin Ceren et al. “Efficiency Analysis and Estimation of Factors Affecting the Efficiency With Decision Trees in Imbalanced Data: A Case of Turkey’s Environmental Sustainability”. Journal of New Theory, no. 37, 2021, pp. 58-67, doi:10.53570/jnt.1034246.
Vancouver Turan SC, Dünder E, Cengiz MA. Efficiency Analysis and Estimation of Factors Affecting the Efficiency with Decision Trees in Imbalanced Data: A Case of Turkey’s Environmental Sustainability. JNT. 2021(37):58-67.
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