SavedAdd your journal

Journals / Journal of Turkish Operations Management / 2024 / Cilt: 8 Sayı: 2

A New Integrated Criteria Weighting Approach for Determining Production Priority in Demand Management

Elif Kılıç Delice(Atatürk Üniversitesi)0000-0002-3051-0496
Elif Akviran(ATATÜRK ÜNİVERSİTESİ)0000-0003-2776-2374
Pages
442–458
Publication Date
2024-12-31
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Therefore, it is thought that this study will contribute to the literature.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In the demand management process; it is tried to balance the customers' needs with the company's supply possibilities.
📊
Key Findings & Data:Correctly determining production priorities is one of the ways to increase customer satisfaction.
💡
Conclusion & Impact:Therefore, it is thought that this study will contribute to the literature.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Production Priority · LBWA · CRITIC

Abstract

In the demand management process; it is tried to balance the customers' needs with the company's supply possibilities. Effective demand management starts with effective stock control and tracking of customer orders and ends with customer satisfaction. Correctly determining production priorities is one of the ways to increase customer satisfaction. In this context, a new approach has been developed to determine the production priority needed in the demand management process. A new integrated approach based on Multi-Criteria Decision Making (MCDM) is proposed to determine production priorities. In the first stage of this three-stage approach, customer alternatives are determined. In the second stage, production priority criteria are determined depending on customer characteristics. In the third stage; with LBWA (Level Based Weight Assessment) and CRITIC (The Criteria Importance Through Intercriteria Correlation) methods, objective and subjective criterion weights are calculated by considering expert opinions and real data. Then, integrated criterion weights are determined with the SOWIA (Subjective and Objective Weight Integrated Approach) method using objective and subjective criterion weights. In the literature; few studies determine production priority using the MCDM method. Additionally, no study has been found in the literature in which quantitative and qualitative methods are used integrated in the ceramic industry. Therefore, it is thought that this study will contribute to the literature.

🔖

Cite This Article

Delice, E. K., Akviran, E. (2024). A New Integrated Criteria Weighting Approach for Determining Production Priority in Demand Management. Journal of Turkish Operations Management, Cilt: 8 Sayı: 2, 442–458. https://doi.org/10.56554/jtom.1410593

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (49)

  1. Adali, E.A., Öztaş, G.Z., Öztaş, T. & Tuş, A. (2022). Assessment of European Cities from a Smartness Perspective: An Integrated Grey MCDM Approach. Sustainable Cities and Society. 84, 104021. https://doi.org/10.1016/j.scs.2022.104021
  2. Ali, T., Sunny, M.R., Aghaloo, K. & Wang, K. (2024). Planning off-grid hybrid energy system using technoeconomic optimization and wins in league theory-based multi-criteria decision-making method in the wetland areas of developing countries. Energy Conversion and Management, 313, 118587. https://doi.org/10.1016/j.enconman.2024.118587
  3. Ayan, B., Abacıoğlu, S. & Basilio, MP. A. (2023). A Comprehensive Review of the Novel Weighting Methods for Multi-Criteria Decision-Making. Information, 14(5), 285. https://doi.org/10.3390/info14050285
  4. Ayçin, E. (2023). Çok Kriterli Karar Problemlerinde LBWA Yöntemi İle Kriterlerin Önem Ağırlıklarının Hesaplanmasına Yönelik Bir Uygulama: LBWA-Solver, İktısadı ve İdarı Bilimlerde Uluslararası Araştırma ve Değerlendirmeler, Serüven Yayınevi, 83-93. https://www.seruvenyayinevi.com/Webkontrol/uploads/Fck/iktisat1aralik2023_2.pdf Ayough, A., Shargh, SB. & Khorshidvand, B. (2023). A new integrated approach based on base-criterion and utility additive methods and its application to supplier selection problem. Expert Systems with Applications, 221, 119740. https://doi.org/10.1016/j.eswa.2023.119740
  5. Ayrım, Y., & Can, G. F. (2017). Risk değerlendirmesinde crıtıc metodu ile sektörlerin karşılaştırması. Journal of Turkish Operations Management, 1(1), 67-78.
  6. Aytekin, A., Korucuk, S., Bedirhanoğlu, Ş.B. & Vladimir, S. (2024) Selecting the ideal sustainable green strategy for logistics companies using a T-spherical fuzzy-based methodology, Engineering Applications of Artificial Intelligence, 127, 107347. https://doi.org/10.1016/j.engappai.2023.107347
  7. Bayram, E. (2022). Talep yönetiminde üretim önceliğinin belirlenmesi için çok kriterli karar verme tabanlı bütünleşik bir yaklaşım (Master’s Thesis). Atatürk Universty, Erzurum. Retrieved from: https://tez.yok.gov.tr/UlusalTezMerkezi/tezDetay.jsp?id=NvNxiLfiIIp4n6IHVihaJA&no=M1kRqLG7j_tLf9e0K ruXjA
  8. Biswas, S. and Pamučar, D. (2020). Facility Location Selection for B-Schools in Indian Context: A Multi-Criteria Group Decision Based Analysis. Axioms, 9 (3): 77. https://doi.org/10.3390/axioms9030077
  9. Biswas, S., Pamučar, D., Božanic, D. & Halder, B. (2022a). A New Spherical Fuzzy LBWA-MULTIMOOSRAL Framework: Application in Evaluation of Leanness of MSMEs in India. Mathematical Problems in Engineering, 1–17. https://doi.org/10.1155/2022/5480848
  10. Biswas, S., Pamučar, D. & Mukhopadhyaya, J.N. (2022b). A Multi-Criteria-Based Analytical Study of the Impact of COVID-19 on ELSS Fund Performance. International Journal of Management and Decision Making, 21, 339– 378. https://doi.org/10.1504/IJMDM.2022.10048438 Božanic, D., Jurišic, D. & Erkic, D. (2020a). LBWA–Z-MAIRCA Model Supporting Decision Making in the Army. Operational Research in Engineering Sciences: Theory and Applications, 3, 87–110. https://doi.org/10.31181/oresta2003087b
  11. Božanić, D., Ranđelović, A., Radovanović & Tešić, M. D. (2020b). A hybrid LBWA- IR-MAIRCA multi-criteria decision-making model for determination of constructive elements of weapons. Facta Universitatis-Series Mechanical Engineering, 18 (3), 399-418. https://doi.org/10.22190/FUME200528033B Çelikyay, S. (2002). Çok amaçlı savaş uçağı seçiminde çok ölçütlü karar verme yöntemlerinin uygulanması (Yüksek Lisans Tezi). Erişim adresi: https://tez.yok.gov.tr/UlusalTezMerkezi/tezSorguSonucYeni.jsp Das, M.C., Sarkar, B. & Ray, S. (2013). On the performance of Indian technical institutions: a combined SOWIAMOORA approach. OPSEARCH, 50(3), 319–333. https://doi.org/10.1007/s12597-012-0116-z
  12. Demir, G. (2020). LBWA Method. Çok Kriterli Karar Verme Problemlerinde Kriter Ağırlıklandırma Yöntemleri, Nobel Yayınevi, Ankara, 137-158.
  13. Diakoulaki, D., Mavrotas, G. & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The CRITIC method. Computers & Operations Research, 22(7), 763-770. https://doi.org/10.1016/0305- 0548(94)00059-H Ecer, F. (2020). Çok Kriterli Karar Verme Geçmişten Günümüze Kapsamlı Bir Yaklaşım. Seçkin Yayıncılık, Ankara. Ecer, F., Pamučar, D., Mardani, A. &Alrasheedi, M. (2021). Assessment of Renewable Energy Resources Using New Interval Rough Number Extension of the Level Based Weight Assessment and Combinative Distance-Based Assessment. Renew Energy, 170, 1156–1177. https://doi.org/10.1016/j.renene.2021.02.004
  14. Erdogan, M. & Ayyildiz, E. (2022). Comparison of hospital service performances under COVID-19 pandemics for pilot regions with low vaccination rates, Expert Systems with Applications, 206, 117773. https://doi.org/10.1016/j.eswa.2022.117773 Farid, H.M.A., Miletic, S.D., Riaz, M., Simic, V. & Pamučar, D. (2024). Prioritization of sustainable approaches for smart waste management of automotive fuel cells of road freight vehicles using the q-rung orthopair fuzzy CRITIC-EDAS method. Information Sciences, 661, 120162. https://doi.org/10.1016/j.ins.2024.120162
  15. Görçün, Ö.F. & Küçükönder, H. (2021). An integrated MCDM approach for evaluating the Ro-Ro marine port selection process: a case study in black sea region, Australian Journal of Maritime & Ocean Affairs, 13(3), 203- 223. https://doi.org/10.1080/18366503.2021.1878872
  16. Gupta, S., Kushwaha, P.S., Badhera, U. & Singh, R.K. (2024). Managing tourism and hospitality industry during pandemic: analysis of challenges and strategies for survival, Benchmarking: An International Journal, early access https://doi.org/10.1108/BIJ-11-2023-0806
  17. Hristov, N., Pamučar, D. & Amine, M. (2021). Application of a D Number Based LBWA Model and an Interval MABAC Model in Selection of an Automatic Cannon for Integration into Combat Vehicles. Defence Science Journal, 71 (1), 34–45. https://doi.org/10.14429/dsj.71.15738
  18. Jakovljevic, V., Zizovic, M., Pamučar, D., Stevic, Ž. & Albijanic, M. (2021). Evaluation of Human Resources in Transportation Companies Using Multi-Criteria Model for Ranking Alternatives by Defining Relations between Ideal and Anti-Ideal Alternative (RADERIA). Mathematics, 9 (9), 976. https://doi.org/10.3390/math9090976
  19. Keskin, Z.B, & Delice E.K., (2023). Determining the effectiveness of countries in combating pandemics: COVID- 19 case. RAIRO Operations Research,57, 2151–2176. https://doi.org/10.1051/ro/2023077 Krishnan, AR. (2024).Research trends in criteria importance through intercriteria correlation (CRITIC) method: a visual analysis of bibliographic data using the Tableau software, Information Discovery And Delivery, early access. https://doi.org/10.1108/idd-02-2024-0030
  20. Korucuk, S., Aytekin, A., Ecer, F., Pamučar, D.S.S. & Karamaşa, Ç. (2022). Assessment of Ideal Smart Network Strategies for Logistics Companies Using an Integrated Picture Fuzzy LBWA–CoCoSo Framework. Management
  21. Decision, 61, 1434–1462. https://doi.org/10.1108/MD-12-2021-1621 Kumari, M., & Kulkarni, M. S. (2019).Single-Measure and Multi-Measure Approach of Predictive Manufacturing Control: A Comparative Study. Computers & Industrial Engineering, 127, 182–195. https://doi.org/10.1016/j.cie.2018.12.018
  22. Li, Y., Su, D.A. & Mardani, A., (2023). Digital twins and blockchain technology in the industrial Internet of Things (IIoT) using an extended decision support system model: Industry 4.0 barriers perspective, Technological Forecasting and Social Change, 195, 122794. https://doi.org/10.1016/j.techfore.2023.122794
  23. Mishra, A. R., Rani, Pratibha Ravi Sundar Prajapati (2021a). Multi-criteria weighted aggregated sum product assessment method for sustainable biomass crop selection problem using single-valued neutrosophic sets, Applied Soft Computing, 113, 108038. https://doi.org/10.1016/j.asoc.2021.108038
  24. Mishra, AR, Rani, P & Saha, A. (2021b). Single-valued neutrosophic similarity measure-based additive ratio assessment framework for optimal site selection of electric vehicle charging station, Internatıonal Journal of Intelligent System, 36 (10), 5573-5604. https://doi.org/10.1002/int.22523
  25. Narayanamoorthy, S., Annapoorani, V., Kang, D., Baleanu, D., Jeon, J., Kureethara, J.V. & Ramya, L. (2020). A novel assessment of bio-medical waste disposal methods using integrating weighting approach and hesitant fuzzy MOOSRA, Journal of Cleaner Production, 275, 122587. https://doi.org/10.1016/j.jclepro.2020.122587
  26. Narayanamoorthy, S., Brainy, J.V., Shalwala, R.A., Alsenani, T.R., Ahmadian, A. & Daekook K., (2023). An enhanced fuzzy decision making approach for the assessment of sustainable energy storage systems. Sustainable Energy, Grids and Networks, 33, 100962. https://doi.org/10.1016/j.segan.2022.100962
  27. Orhan, M. (2013). Karar alma problemlerinde AHP'nin yeri ve kalkınmışlık kriterleriyle Avrupa Birliği üyesi ülkelerin karşılaştırılması (Master’s Thesis). Marmara Universty, İstanbul. Retrieved from: https://tez.yok.gov.tr/UlusalTezMerkezi/tezDetay.jsp?id=T0uALLN8tVzNEGdEm-taSA&no=EXwoGD24- wXNhSjuE-DyWw
  28. Ögel, İ.Y., Ecer, F. & Özgöz, A.A. (2022). Identifying the Leading Retailer-Based Food Waste Causes in Different Perishable Fast-Moving Consumer Goods’ Categories: Application of the F-LBWA Methodology. Environmental Science and Pollution Research, 30, 32656–32672. https: //doi.org/10.1007/s11356-022-24500-9
  29. Pamučar, D., Žižović, M., Marinković, D., Doljanica, D., Jovanović, SV. & Brzaković P. (2020). Development of a Multi-Criteria Model for Sustainable Reorganization of a Healthcare System in an Emergency Situation Caused by the COVID-19 Pandemic. Sustainability, 12(18),7504. https://doi.org/10.3390/su12187504
  30. Pamučar, D., Behzad, M., Božanić, D. & Behzad, M. (2021). Decision making to support sustainable energy policies corresponding to agriculture sector: Case study in Iran’s Caspian Sea coastline. Journal of Cleaner Production, 292, 125302. https://doi.org/10.1016/j.jclepro.2020.125302
  31. Pamučar, D. & Görçün, Ö.F. (2022). Evaluation of the European Container Ports Using a New Hybrid Fuzzy LBWA-CoCoSo’B Techniques. Expert Systems with Applications, 203, 117463. https://doi.org/10.1016/j.eswa.2022.117463
  32. Pamučar, D., Gokasar, I., Torkayesh, A.E., Deveci, M., Martínez, L. & Wu, Q. (2023). Prioritization of Unmanned Aerial Vehicles in Transportation Systems Using the Integrated Stratified Fuzzy Rough Decision-Making Approach with the Hamacher Operator. Information Sciences, 622, 374–404. https://doi.org/10.1016/j.ins.2022.11.143
  33. Peng, X. & Huang, H. (2020). Fuzzy decision making method based on CoCoSo with CRITIC for financial risk evaluation. Technological and Economic Development of Economy, 26 (6),1199-1215. https://doi.org/10.3846/tede.2020.11920
  34. Piasecki, M. & Kostyrko, K. (2020).Development of weighting scheme for indoor air quality model using a multiattribute decision making method. Energies, 13(12),3120. https://doi.org/10.3390/en13123120
  35. Razzaq, A., Riaz, M. & Aslam, M. (2024). Efficient picture fuzzy soft CRITIC-CoCoSo framework for supplier selection under uncertainties in Industry 4.0. AIMS Mathematics, 9(1), 665-701. https://doi.org/10.3934/math.2024035
  36. Shang, C., Saeidi, P. & Goh, C.F. (2022), “Evaluation of circular supply chains barriers in the era of industry 4.0 transition using an extended decision-making approach”, Journal of Enterprise Information Management, Vol. 35 Nos 4/5, pp. 1100-1128.
  37. Sharma,M., Joshi,S. & Govindan,K. (2023). Overcoming barriers to implement digital technologies to achieve sustainable production and consumption in the food sector: A circular economy perspective. Sustainable Production And Consumption, 39, 203-215. https://doi.org/10.1016/j.spc.2023.04.002
  38. Sreekumar, V. & Rajmohan, M. (2019). Supply chain strategy decisions for sustainable development using an integrated multi-criteria decision making approach. Sustainable Development, 27:50–60. https://doi.org/10.1002/sd.1861
  39. Torkayesh, A.E., Pamučar, D., Ecer, F. & Chatterjee, P. (2021a). An Integrated BWM-LBWA-CoCoSo Framework for Evaluation of Healthcare Sectors in Eastern Europe. Socio-Economic Planning Sciences, 78, 101052. https://doi.org/10.1016/j.seps.2021.101052
  40. Torkayesh, A. E. & Torkayesh, S. E., (2021). Evaluation of information and communication technology development in G7 countries: An integrated MCDM approach. Technology in Society, 66, 101670. https://doi.org/10.1016/j.techsoc.2021.101670
  41. Tuş, A., & Aytaç, A., E. (2019). The new combination with CRITIC and WASPAS methods for the time and attendance software selection problem. OPSEARCH, 56, 528–538. https://doi.org/10.1007/s12597-019-00371-6
  42. Uluskan, M., Topuz, D. & Çimen, C. (2020). AHP, bulanık AHP, LBWA VE COPRAS yöntemleri ile tedarikçi değerlendirme: demiryolu sektöründe bir uygulama. Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi, 30(3),412-430. https://doi.org/10.31796/ogummf.1068384
  43. Wang, W., Chen, Y., Wang, Y., Deveci,M., Moslem, S. & Coffman, D. (2024). Unveiling the implementation barriers to the digital transformation in the energy sector using the Fermatean cubic fuzzy method. Applied Energy, 360,122756. https://doi.org/10.1016/j.apenergy.2024.122756
  44. Wei, G., Lei, F., Lin, R., Wang, R., Wei, Y., Wu, J., & Wei, C. (2020). Algorithms for probabilistic uncertain linguistic multiple attribute group decision making based on the GRA and CRITIC method: application to location planning of electric vehicle charging stations. Economic Research-Ekonomska Istraživanja, 33(1), 828–846. https://doi.org/10.1080/1331677X.2020.1734851
  45. Yazdani, M., Pamučar, D., Chatterjee, P. & Torkayesh, A.E. (2022). A Multi-Tier Sustainable Food Supplier Selection Model under Uncertainty. Operations Management Research, 15, 116–145. https://doi.org/10.1007/s12063-021-00186-z
  46. Žižović, M. & Pamučar, D. (2019). New model for determining criteria weights: level-based weight assessment (LBWA) model. Decision Making: Applications in Management and Engineering, 2(2), 1-20. https://doi.org/10.31181/dmame1902102z
  47. Zaher, H., Khalifa, H. A. & Mohamed, S. (2018). On Rough Interval Multi Criteria Decision Making. International Journal of Scientific & Technology Research, 7(3), 44-54. Corpus ID: 116022924
  48. Zeng, S., Gao, L. & Wu, J. (2024). Data literacy evaluation of undergraduate in business majors based on probabilistic linguistic integrated EDAS method. Granular Computing, 9, 27. https://doi.org/10.1007/s41066- 024-00453-x Zhu, L., Lei,G. & Gao, J. (2023). Research
  49. Pamučar, D., Behzad, M., Božanić, D. & Behzad, M. (2021). Decision making to support sustainable energy policies corresponding to agriculture sector: Case study in Iran’s Caspian Sea coastline. Journal of Cleaner Production, 292, 125302. https://doi.org/10.1016/j.jclepro.2020.125302