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Bir Performans Değerlendirme Modelinin Kâğıt ve Kâğıt Ürünleri Basım Sektörüne Uygulanması: VZA-AHP Hibrit Algoritması

Year 2024, Volume: 11 Issue: 2, 215 - 238, 01.07.2024
https://doi.org/10.17541/optimum.1417219

Abstract

Kâğıt ve kâğıt ürünleri basım sektörü, gelir elde etmede, istihdam oluşturmada ve ihracatın ve çeşitli endüstrilerin desteklenmesinde önemli bir rol oynamaktadır. Bu sektörde faaliyet gösteren şirketlerin etkinliğinin ölçülmesi iyileştirme için alanların belirlenmesinde ve genel performansın artırılmasında önemlidir. Bu çalışmada, Borsa İstanbul’da işlem gören on iki kâğıt ve kâğıt ürünleri basım şirketinin etkinliğini analiz etmek için iki aşamalı bir VZA (veri zarflama analizi)-AHP (analitik hiyerarşi prosesi) yaklaşımı önerilmektedir. Şirketlerin ikili karşılaştırmasını yapmak için modifiye VZA yöntemi kullanılmıştır. Girdi olarak toplam varlıklar, toplam özkaynaklar ve personel sayısı, çıktı olarak ise hasılat ve net dönem kârı seçilmiştir. AHP yöntemi, VZA aracılığıyla oluşturulan matematiksel modellerin çıktılarını dikkate alarak şirketleri önceliklendirmektedir. Önerilen çerçeve en etkin şirketin belirlenmesine, şirket performansının karşılaştırılmasına ve iyileştirilecek alanların belirlenmesine katkıda bulunarak farklı bir bakış açısı sunmaktadır.

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Application of a Performance Evaluation Model to the Paper and Paper Products Printing Sector: The DEA-AHP Hybrid Algorithm

Year 2024, Volume: 11 Issue: 2, 215 - 238, 01.07.2024
https://doi.org/10.17541/optimum.1417219

Abstract

The paper and paper products printing sector plays a crucial role in generating income, creating employment opportunities, and supporting exports and various industries. Measuring the efficiency of companies operating in this sector is important in identifying areas for improvement and enhancing overall performance. In this study, a two-stage DEA (data envelopment analysis)-AHP (analytic hierarchy process) approach is proposed to analyze the efficiency of twelve paper and paper products printing companies traded on Borsa Istanbul. The modified DEA method is employed to make pairwise comparisons of the companies. Total assets, total equity, and the number of employees are selected as inputs, while revenue and net profit are considered as outputs. The AHP method prioritizes the companies by considering the outputs of the mathematical models constructed via DEA. The proposed framework presents a different view because it contributes to identifying the most efficient company, benchmarking company performance, and determining areas for improvement.

References

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  • Amin, G. R., El-Temtamy, O., & Garas, S. (2022). Audit risk evaluation using data envelopment analysis with ordinal data. Abacus, 58(3), 589–602.
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  • Bhaskar, A. S., & Khan, A. (2022). Comparative analysis of hybrid MCDM methods in material selection for dental applications. Expert Systems with Applications, 209, 1–8.
  • Bhattacharya, A., Sarkar, B., & Mukherjee, S. K. (2005). Integrating AHP with QFD for robot selection under requirement perspective. International Journal of Production Research, 43(17), 3671–3685.
  • Caner, H. I., & Aydin, C. C. (2021). Shipyard site selection by raster calculation method and AHP in GIS environment, İskenderun, Turkey. Marine Policy, 127, 1–17.
  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444.
  • Chen, T. (2002). A comparison of chance-constrained DEA and stochastic frontier analysis: Bank efficiency in Taiwan. Journal of the Operational Research Society, 53(5), 492–500.
  • Debreu, G. (1951). The coefficient of resource utilization. Econometrica, 19(3), 273–292.
  • Demirtaş, M. C., & Orçun, Ç. (2022). Brand value analysis with hirose method: An aplication on paper and paper products, printing and publishing sector. Journal of Academic Projection, 7(2), 101–116.
  • Dos Santos, P. H., Neves, S. M., Sant’Anna, D. O., Oliveira, C. H. de, & Carvalho, H. D. (2019). The analytic hierarchy process supporting decision making for sustainable development: An overview of applications. Journal of Cleaner Production, 212, 119–138.
  • Durak, İ., Arslan, H. M., & Özdemir, Y. (2022). Application of AHP–TOPSIS methods in technopark selection of technology companies: Turkish case. Technology Analysis and Strategic Management, 34(10), 1109–1123.
  • Durão, L. F. C. S., Carvalho, M. M., Takey, S., Cauchick-Miguel, P. A., & Zancul, E. (2018). Internet of Things process selection: AHP selection method. International Journal of Advanced Manufacturing Technology, 99(9–12), 2623–2634.
  • Ersoy, Y. (2021). Performance evaluation in distance education by using data envelopment analysis (DEA) and TOPSIS methods. Arabian Journal for Science and Engineering, 46(2), 1803–1817.
  • Fancello, G., Carta, M., & Serra, P. (2020). Data envelopment analysis for the assessment of road safety in urban road networks: A comparative study using CCR and BCC models. Case Studies on Transport Policy, 8(3), 736–744.
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, Series A (General), 120(3), 253–281.
  • Fukuyama, H., Matousek, R., & Tzeremes, N. G. (2023). Estimating the degree of firms’ input market power via data envelopment analysis: Evidence from the global biotechnology and pharmaceutical industry. European Journal of Operational Research, 305(2), 946–960.
  • Gao, Z., Jiang, Y., He, J., Wu, J., Xu, J., & Christakos, G. (2022). An AHP-based regional COVID-19 vulnerability model and its application in China. Modeling Earth Systems and Environment, 8(2), 2525–2538.
  • Goswami, M., & Ghadge, A. (2020). A supplier performance evaluation framework using single and bi-objective DEA efficiency modelling approach: Individual and cross-efficiency perspective. International Journal of Production Research, 58(10), 3066–3089.
  • Gunasekaran, A., Williams, H. J., & McGaughey, R. E. (2005). Performance measurement and costing system in new enterprise. Technovation, 25(5), 523–533.
  • Haider, S., Danish, M. S., & Sharma, R. (2019). Assessing energy efficiency of Indian paper industry and influencing factors: A slack-based firm-level analysis. Energy Economics, 81, 454–464.
  • Hailu, A. (2003). Pollution abatement and productivity performance of regional Canadian pulp and paper industries. Journal of Forest Economics, 9(1), 5–25.
  • Hamdi, A., Karimi, A., Mehrdoust, F., & Belhaouari, S. B. (2022). Portfolio selection problem using CVaR risk measures equipped with DEA, PSO, and ICA algorithms. Mathematics, 10(15), 1–26.
  • Hseu, J. S., & Shang, J. K. (2005). Productivity changes of pulp and paper industry in OECD countries, 1991-2000: A non-parametric Malmquist approach. Forest Policy and Economics, 7(3), 411–422.
  • Hussain, J., & Bernard, J.-T. (2017). Regional productivity convergence: An analysis of the pulp and paper industries in U.S., Canada, Finland, and Sweden. Journal of Forest Economics, 28, 49–62.
  • Islamoglu, M., & Celik, N. (2015). Financial performance determinants of paper and paper products firms listed in Borsa Istanbul. International Journal of Economics and Finance, 7(4), 233–243.
  • Jomthanachai, S., Wong, W. P., & Lim, C. P. (2021). An application of data envelopment analysis and machine learning approach to risk management. IEEE Access, 9, 85978–85994.
  • Jun, Y., Go, J., & Yeom, C. (2022). Experimental variables assessment for virtual road safety audit using analytic hierarchy process. Journal of Transportation Safety and Security, 14(6), 1002–1021.
  • Kengpol, A., Meethom, W., & Tuominen, M. (2012). The development of a decision support system in multimodal transportation routing within Greater Mekong sub-region countries. International Journal of Production Economics, 140(2), 691–701.
  • Khanduja, R., Tewari, P. C., & Chauhan, R. S. (2009). Performance analysis of screening unit in a paper plant using genetic algorithm. Journal of Industrial and Systems Engineering, 3(2), 140–151.
  • Leccese, F., Salvadori, G., Rocca, M., Buratti, C., & Belloni, E. (2020). A method to assess lighting quality in educational rooms using analytic hierarchy process. Building and Environment, 168, 1–15.
  • Lee, A. H. I., Chen, S. C., & Kang, H. Y. (2020). A decision-making framework for evaluating enterprise resource planning systems in a high-tech industry. Quality Technology and Quantitative Management, 17(3), 319–336.
  • Li, Z., Tang, D., Han, M., & Bethel, B. J. (2018). Comprehensive evaluation of regional sustainable development based on data envelopment analysis. Sustainability, 10(11), 1–18.
  • Liu, J., Gong, Y., Zhu, J., & Titah, R. (2022). Information technology and performance: Integrating data envelopment analysis and configurational approach. Journal of the Operational Research Society, 73(6), 1278–1293.
  • Marović, I., Perić, M., & Hanak, T. (2021). A multi‐criteria decision support concept for selecting the optimal contractor. Applied Sciences, 11(4), 1–18.
  • Moreno, P., & Lozano, S. (2014). A network DEA assessment of team efficiency in the NBA. Annals of Operations Research, 214(1), 99–124.
  • Mourtzis, D., Samothrakis, V., Zogopoulos, V., & Vlachou, E. (2019). Warehouse design and operation using augmented reality technology: A papermaking industry case study. Procedia CIRP, 79, 574–579.
  • Myeong, S., Jung, Y., & Lee, E. (2018). A study on determinant factors in smart city development: An analytic hierarchy process analysis. Sustainability, 10(8), 1–17.
  • Nguyen, P. H., Nguyen, T. L., Nguyen, T. G., Nguyen, D. T., Tran, T. H., Le, H. C., & Phung, H. T. (2022). A cross-country European efficiency measurement of maritime transport: A data envelopment analysis approach. Axioms, 11(5), 1–18.
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There are 78 citations in total.

Details

Primary Language English
Subjects Comparative Economic Systems, Business Administration
Journal Section Articles
Authors

Hilal Singer 0000-0003-0884-2555

Publication Date July 1, 2024
Submission Date January 9, 2024
Acceptance Date February 15, 2024
Published in Issue Year 2024 Volume: 11 Issue: 2

Cite

APA Singer, H. (2024). Application of a Performance Evaluation Model to the Paper and Paper Products Printing Sector: The DEA-AHP Hybrid Algorithm. Optimum Ekonomi Ve Yönetim Bilimleri Dergisi, 11(2), 215-238. https://doi.org/10.17541/optimum.1417219
AMA Singer H. Application of a Performance Evaluation Model to the Paper and Paper Products Printing Sector: The DEA-AHP Hybrid Algorithm. OJEMS. July 2024;11(2):215-238. doi:10.17541/optimum.1417219
Chicago Singer, Hilal. “Application of a Performance Evaluation Model to the Paper and Paper Products Printing Sector: The DEA-AHP Hybrid Algorithm”. Optimum Ekonomi Ve Yönetim Bilimleri Dergisi 11, no. 2 (July 2024): 215-38. https://doi.org/10.17541/optimum.1417219.
EndNote Singer H (July 1, 2024) Application of a Performance Evaluation Model to the Paper and Paper Products Printing Sector: The DEA-AHP Hybrid Algorithm. Optimum Ekonomi ve Yönetim Bilimleri Dergisi 11 2 215–238.
IEEE H. Singer, “Application of a Performance Evaluation Model to the Paper and Paper Products Printing Sector: The DEA-AHP Hybrid Algorithm”, OJEMS, vol. 11, no. 2, pp. 215–238, 2024, doi: 10.17541/optimum.1417219.
ISNAD Singer, Hilal. “Application of a Performance Evaluation Model to the Paper and Paper Products Printing Sector: The DEA-AHP Hybrid Algorithm”. Optimum Ekonomi ve Yönetim Bilimleri Dergisi 11/2 (July 2024), 215-238. https://doi.org/10.17541/optimum.1417219.
JAMA Singer H. Application of a Performance Evaluation Model to the Paper and Paper Products Printing Sector: The DEA-AHP Hybrid Algorithm. OJEMS. 2024;11:215–238.
MLA Singer, Hilal. “Application of a Performance Evaluation Model to the Paper and Paper Products Printing Sector: The DEA-AHP Hybrid Algorithm”. Optimum Ekonomi Ve Yönetim Bilimleri Dergisi, vol. 11, no. 2, 2024, pp. 215-38, doi:10.17541/optimum.1417219.
Vancouver Singer H. Application of a Performance Evaluation Model to the Paper and Paper Products Printing Sector: The DEA-AHP Hybrid Algorithm. OJEMS. 2024;11(2):215-38.

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