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

Yıl 2024, Cilt: 11 Sayı: 2, 215 - 238, 01.07.2024
https://doi.org/10.17541/optimum.1417219

Öz

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.

Kaynakça

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

Yıl 2024, Cilt: 11 Sayı: 2, 215 - 238, 01.07.2024
https://doi.org/10.17541/optimum.1417219

Öz

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.

Kaynakça

  • Ahmadi, J., Toroghi Haghighat, A., Rahmani, A. M., & Ravanmehr, R. (2022). A flexible approach for virtual machine selection in cloud data centers with AHP. Software - Practice and Experience, 52(5), 1216–1241.
  • Akyüz, K. C., Çamur, G., & Yıldırım, İ. (2015). Activity analysis with data envelopment analysis in the furniture and panelboard sectors. Turkish Journal of Forestry, 16(1), 50–59.
  • Al-Refaie, A., Wu, C. W., & Sawalheh, M. (2019). DEA window analysis for assessing efficiency of blistering process in a pharmaceutical industry. Neural Computing and Applications, 31, 3703–371.
  • Alam, T. E., González, A. D., & Raman, S. (2023). Benchmarking of academic departments using data envelopment analysis (DEA). Journal of Applied Research in Higher Education, 15(1), 268–285.
  • Amin, G. R., El-Temtamy, O., & Garas, S. (2022). Audit risk evaluation using data envelopment analysis with ordinal data. Abacus, 58(3), 589–602.
  • Awad, J., & Jung, C. (2022). Extracting the planning elements for sustainable urban regeneration in Dubai with AHP (analytic hierarchy process). Sustainable Cities and Society, 76, 1–13.
  • 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.
  • Omair, M., Noor, S., Tayyab, M., Maqsood, S., Ahmed, W., Sarkar, B., & Habib, M. S. (2021). The selection of the sustainable suppliers by the development of a decision support framework based on analytical hierarchical process and fuzzy inference system. International Journal of Fuzzy Systems, 23(7), 1986–2003.
  • Özşahin, Ş., Singer, H., Temiz, A., & Yildirim, İ. (2019). Selection of softwood species for structural and non-structural timber construction by using the analytic hierarchy process (AHP) and the multiobjective optimization on the basis of ratio analysis (MOORA). Baltic Forestry, 25(2), 281–288.
  • Panchal, S., & Shrivastava, A. K. (2022). Landslide hazard assessment using analytic hierarchy process (AHP): A case study of National Highway 5 in India. Ain Shams Engineering Journal, 13(3), 1–11.
  • Pang, J., Wang, R., Xiao, Q., & Qin, F. (2020). A data-driven condition monitoring of product quality analysis system based on rs and ahp. Tehnicki Vjesnik, 27(2), 382–390.
  • Qi, H., Zhou, Z., Li, N., & Zhang, C. (2022). Construction safety performance evaluation based on data envelopment analysis (DEA) from a hybrid perspective of cross-sectional and longitudinal. Safety Science, 146, 1–14.
  • Ray, S. (2011). Financial performance of paper and paper product companies in India in post-liberalization period: An exploratory study. Research Journal of Finance and Accounting, 2(5), 48–59.
  • Rostamzadeh, R., Akbarian, O., Banaitis, A., & Soltani, Z. (2021). Application of DEA in benchmarking: A systematic literature review from 2003–2020. Technological and Economic Development of Economy, 27(1), 175–222.
  • Rouyendegh, B. D. (2009). DEA-ANP sequential hybrid algorithm for multiple-criteria decision-making process, a long with an application [Unpublished doctoral dissertation]. Gazi University.
  • Rouyendegh, B. D., Oztekin, A., Ekong, J., & Dag, A. (2019). Measuring the efficiency of hospitals: A fully-ranking DEA–FAHP approach. Annals of Operations Research, 278(1–2), 361–378.
  • Şahin, T., Ocak, S., & Top, M. (2019). Analytic hierarchy process for hospital site selection. Health Policy and Technology, 8(1), 42–50.
  • Saaty, T. L. (1980). The analytic hierarchy process: planning, priority setting, resource allocation. Mcgraw-Hill. Şensöğüt, C., Kasap, Y., & Ören, Ö. (2021). Investigation of work accidents in underground and surface coal mining activities of western lignite corporation by data envelopment analysis (DEA). Mining, Metallurgy and Exploration, 38(5), 1973–1983.
  • Senthilkannan, N., & Parameshwaran, R. (2019). Performance analysis and quality improvement using fuzzy MCDM and lean tools in a paper industry. International Journal of Integrated Supply Management, 12(3), 205–229.
  • Shahi, S. K., & Dia, M. (2020). Empirical study of the performance of Ontario’s pulp and paper mills using bootstrap data envelopment analysis. International Journal of Productivity and Quality Management, 31(1), 98–133.
  • Singer, H., & Özşahin, Ş. (2018). Employing an analytic hierarchy process to prioritize factors influencing surface roughness of wood and wood-based materials in the sawing process. Turkish Journal of Agriculture and Forestry, 42(5), 364–371.
  • Singer, H., & Özşahin, Ş. (2023). Applying an interval-valued Pythagorean fuzzy analytic hierarchy process to rank factors influencing wooden outdoor furniture selection. Wood Material Science and Engineering, 18(1), 322–333.
  • Singh, M., Pant, M., Godiyal, R. D., & Kumar Sharma, A. (2020). MCDM approach for selection of raw material in pulp and papermaking industry. Materials and Manufacturing Processes, 35(3), 241–249.
  • Soba, M., & Altıntaş, F. (2019). 2008 Dünya ekonomik krizinin G20 ülkeleri ekonomik performanslarına etkisinin AHP ve VIKOR yöntemleriyle değerlendirilmesi. Optimum Ekonomi ve Yönetim Bilimleri Dergisi, 6(1), 33–52.
  • Soltani, A. A., Oukil, A., Boutaghane, H., Bermad, A., & Boulassel, M. R. (2021). A new methodology for assessing water quality, based on data envelopment analysis: Application to Algerian dams. Ecological Indicators, 121, 1–18.
  • Soltysova, Z., Modrak, V., & Nazarejova, J. (2022). A multi-criteria assessment of manufacturing cell performance using the AHP method. Applied Sciences, 12(2), 1–14.
  • Sueyoshi, T., & Goto, M. (2009). Methodological comparison between DEA (data envelopment analysis) and DEA-DA (discriminant analysis) from the perspective of bankruptcy assessment. European Journal of Operational Research, 199(2), 561–575.
  • Sueyoshi, T., Zhang, R., Qu, J., & Li, A. (2021). New concepts for environment-health measurement by data envelopment analysis and an application in China. Journal of Cleaner Production, 312, 1–14.
  • Sulthonuddin, I., & Herdiansyah, H. (2021). Sustainability of Batik wastewater quality management strategies: Analytical hierarchy process. Applied Water Science, 11(2), 1–12.
  • Toppinen, A., Pätäri, S., Tuppura, A., & Jantunen, A. (2017). The European pulp and paper industry in transition to a bio-economy: A Delphi study. Futures, 88, 1–14.
  • Tsai, W. H., & Lai, S. Y. (2018). Green production planning and control model with ABC under industry 4.0 for the paper industry. Sustainability, 10(8), 1–29.
  • Üçüncü, T., Akyüz, K. C., Akyüz, İ., Bayram, B. Ç., & Ersen, N. (2018). Evaluation of financial performance of paper companies traded at BIST with TOPSIS method. Kastamonu University Journal of Forestry Faculty, 18(1), 92–98.
  • Unver, S., & Ergenc, I. (2021). Safety risk identification and prioritize of forest logging activities using analytic hierarchy process (AHP). Alexandria Engineering Journal, 60(1), 1591–1599.
  • URL-1. (2023). Public Disclosure Platform. https://www.kap.org.tr/en/
  • Wang, C. N., Dang, T. T., Nguyen, N. A. T., & Wang, J. W. (2022). A combined data envelopment analysis (DEA) and grey based multiple criteria decision making (G-MCDM) for solar PV power plants site selection: A case study in Vietnam. Energy Reports, 8, 1124–1142.
  • Wang, X., Ferreira, F. A. F., Tao, M., & Chang, C. T. (2022). A hybrid AHP–FCE–WMCGP approach for internal auditor selection: A generic framework. International Journal of Fuzzy Systems, 24(5), 2229–2249.
  • Wu, Y. C., & Lin, S. W. (2022). Efficiency evaluation of Asia’s cultural tourism using a dynamic DEA approach. Socio-Economic Planning Sciences, 84, 101426.
  • Yang, C. L., Chuang, S. P., & Huang, R. H. (2009). Manufacturing evaluation system based on AHP/ANP approach for wafer fabricating industry. Expert Systems with Applications, 36(8), 11369–11377.
  • Yang, W., & Li, L. (2018). Efficiency evaluation of industrial waste gas control in China: A study based on data envelopment analysis (DEA) model. Journal of Cleaner Production, 179, 1–11.
  • Yen, B. T. H., & Li, J. S. (2022). Route-based performance evaluation for airlines – a metafrontier data envelopment analysis approach. Transportation Research Part E: Logistics and Transportation Review, 162, 1–20.
  • Yu, C., Shi, L., Wang, Y., Chang, Y., & Cheng, B. (2016). The eco-efficiency of pulp and paper industry in China: An assessment based on slacks-based measure and Malmquist–Luenberger index. Journal of Cleaner Production, 127, 511–521.
  • Zemtsov, S., & Kotsemir, M. (2019). An assessment of regional innovation system efficiency in Russia: The application of the DEA approach. Scientometrics, 120(2), 375–404.
  • Zhang, Y., Zhao, Y., Sun, W., & Li, J. (2021). Ocean wave energy converters: Technical principle, device realization, and performance evaluation. Renewable and Sustainable Energy Reviews, 141, 1–20.
Toplam 78 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Karşılaştırmalı Ekonomik Sistemler, İşletme
Bölüm Makaleler
Yazarlar

Hilal Singer 0000-0003-0884-2555

Yayımlanma Tarihi 1 Temmuz 2024
Gönderilme Tarihi 9 Ocak 2024
Kabul Tarihi 15 Şubat 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 11 Sayı: 2

Kaynak Göster

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. OEYBD. Temmuz 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, sy. 2 (Temmuz 2024): 215-38. https://doi.org/10.17541/optimum.1417219.
EndNote Singer H (01 Temmuz 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”, OEYBD, c. 11, sy. 2, ss. 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 (Temmuz 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. OEYBD. 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, c. 11, sy. 2, 2024, ss. 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. OEYBD. 2024;11(2):215-38.

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