Zemin Kaplama Ürünlerinin Kalite Boyutlarının Garvin Modeli ve Aralık Değerli Fermatean Bulanık Analitik Hiyerarşi Prosesi Entegrasyonu ile Analizi

Yıl 2023, Cilt: 13 Sayı: 2, 276 - 291, 29.12.2023

Hilal Singer

Öz

Döşemeler, yapılarda katları birbirinden ayıran ve üzerlerinde yürünebilen, beklenebilen ve vakit geçirilebilen yapı elemanlarıdır. Döşemeler değişik etkilere maruz kaldığından beklenen fonksiyonları yerine getirebilmeleri için uygun bir şekilde malzemelerle kaplanması gerekir. Artan ulusal ve uluslararası rekabet ile çeşitli ve değişen tüketici zevkleri nedeniyle, zemin kaplama endüstrisinin ürün kalitesini geliştirmesi önem arz etmektedir. Bu çalışmada, zemin kaplama ürünlerinin kalite boyutları tanımlanmış ve bu boyutlar uzman bilgisine dayalı bir karar verme yaklaşımı ile analiz edilmiştir. Literatürde sıkça kullanılan Garvin modeli çevrecilik, ekonomiklik ve güvenlik boyutları eklenerek sekiz boyuttan on bir boyuta genişletilmiştir. Önerilen on bir kalite boyutu aralık değerli Fermatean bulanık AHP yöntemi ile değerlendirilmiştir. Çalışmanın bulguları, uygunluk, performans ve dayanıklılık boyutlarının rekabetçi kalite açısından oldukça önemli olduğunu göstermiştir. İlaveten, uygulanan yöntemin çıktıları karşılaştırmalı analiz ile güçlendirilmiştir.

Anahtar Kelimeler

Analitik Hiyerarşi Prosesi, Aralık Değerli Fermatean Bulanık küme, Ürün Kalite Boyutları, Zemin Kaplama Endüstrisi

Analyzing the quality dimensions of flooring products with the integration of the Garvin model and the interval-valued Fermatean fuzzy analytical hierarchy process

Öz

Floorings are the construction elements that divide the building into different levels and can be walked, waited, and spent time on them. Since floorings are exposed to different forces, they should be properly covered with materials in order to fulfill their expected functions. Due to the increasing national and international competition and diverse and changing consumer pleasures, it is important for the flooring industry to improve product quality. In this study, the quality dimensions of flooring products are defined, and these dimensions are analyzed by an expert knowledge-based decision-making approach. The Garvin model, which is frequently used in the literature, is expanded from eight dimensions to eleven dimensions by adding environmentalism, economy, and safety dimensions. The proposed eleven quality dimensions are evaluated by the interval-valued Fermatean fuzzy AHP method. The findings of the study demonstrate that conformance, performance, and durability dimensions are highly important in terms of competitive quality. Additionally, the outputs of the applied method are strengthened by the comparative analysis.

Anahtar Kelimeler

Analytic hierarchy process, Interval-valued fermatean fuzzy set, Product quality dimensions, Flooring industry

Kaynakça

• Alkan, N., Kahraman, C. 2023. Prioritization of supply chain digital transformation strategies using multi-expert Fermatean fuzzy analytic hierarchy process. Informatica, 34: 1-33. Doi:10.15388/22-infor493
• Ayyildiz, E. 2022. Fermatean fuzzy step-wise Weight Assessment Ratio Analysis (SWARA) and its application to prioritizing indicators to achieve sustainable development goal-7. Renew. Energy, 193: 136-148. Doi:10.1016/j.renene.2022.05.021
• Bostancioglu, E. 2021. Double skin façade assessment by fuzzy AHP and comparison with AHP. Archit. Eng. Des. Manag., 17: 110-130. Doi:10.1080/17452007.2020.1735292
• Camci, A., Ertürk, ME., Gül, S. 2022. A novel Fermatean fuzzy analytic hierarchy process proposition and its usage for supplier selection problem in industry 4.0 transition. in: H. Garg [ed.], Q-Rung Orthopair Fuzzy Sets. Springer, Singapore, pp. 405-437.
• Celik, E., Akyuz, E. 2018. An interval type-2 fuzzy AHP and TOPSIS methods for decision-making problems in maritime transportation engineering: the case of ship loader. Ocean Eng., 155: 371-381. Doi:10.1016/j.oceaneng.2018.01.039
• Chen, SC., Chang, L., Huang, TH. 2009. Applying six-sigma methodology in the Kano quality model: an example of the stationery industry. Total Qual. Manag. Bus. Excell., 20: 153- 170. Doi:10.1080/14783360802622847
• Çavdar, E., Zerdali, N. 2020. Farklı mamul grupları için kalite boyutları önem değerlendirmesi. İşletme Ekon. ve Yönetim Araştırmaları Derg., 2: 222-233.
• Deliktaş, D., Karagoz, S., Simić, V., Aydin, N. 2023. A stochastic Fermatean fuzzy-based multi-choice conic goal programming approach for sustainable supply chain management in endof-life buildings. J. Clean. Prod., 382: 135305. Doi:10.1016/j. jclepro.2022.135305
• Deveci, M., Varouchakis, E.A., Brito-Parada, P.R., Mishra, A.R., Rani, P., Bolgkoranou, M., Galetakis, M. 2023. Evaluation of risks impeding sustainable mining using Fermatean fuzzy score function based SWARA method. Appl. Soft Comput., 139: 110220. Doi:10.1016/j.asoc.2023.110220
• Díaz, H., Teixeira, AP., Guedes Soares, C. 2022. Application of Monte Carlo and Fuzzy Analytic Hierarchy Processes for ranking floating wind farm locations. Ocean Eng., 245: 1-10. Doi:10.1016/j.oceaneng.2021.110453
• Döngel, N. 2005. Ahşap ve ahşap esaslı döşeme kaplama malzemelerinin (parke) teknik özellikleri. Gazi Üniversitesi, Fen Bilimleri Enstitüsü, Ankara, Türkiye.
• Döngel, N., Küreli, İ., Söğütlü, C. 2008. Kuru sıcaklığın ahşap ve ahşap esaslı döşeme kaplama malzemelerinde parlaklık ve renk değişimine etkisi. Politek. Derg., 11: 255-263.
• Efe, B., Kurt, M. 2018. Bir liman işletmesinde personel seçimi uygulaması. Karaelmas Fen ve Mühendislik Derg., 8: 417-427. Doi:10.7212%2Fzkufbd.v8i2.750
• Farid, HMA., Bouye, M., Riaz, M., Jamil, N. 2023. Fermatean fuzzy CODAS approach with topology and its application to sustainable supplier selection. Symmetry, 15: 433. Doi:10.3390/sym15020433
• Fetanat, A., Tayebi, M., Mofid, H. 2023. Water-energy-carbon nexus and sustainability-oriented prioritization of negative emissions technologies for the oil & gas industry: A decision support system under Fermatean fuzzy environment. Process Saf. Environ. Prot., 179: 462-483. Doi:10.1016/j. psep.2023.09.037
• Garvin, DA. 1984. What does “product quality” really mean? MIT Sloan Manag. Rev., 26: 25-43.
• Ghylin, KM., Green, BD., Drury, CG., Chen, J., Schultz, JL., Uggirala, A., Abraham, JK., Lawson, TA. 2008. Clarifying the dimensions of four concepts of quality. Theor. Issues Ergon. Sci., 9: 73-94. Doi:10.1080/14639220600857639
• Gouda, SK., Awasthy, P., Krishnan, TS., Sreedevi, R. 2019. What does “green quality” really mean? TQM J., 31: 52-69. Doi:10.1108/TQM-06-2018-0080
• Görçün, ÖF., Pamucar, D., Biswas, S. 2023. The blockchain technology selection in the logistics industry using a novel MCDM framework based on Fermatean fuzzy sets and Dombi aggregation. Inf. Sci., 635: 345-374. Doi:10.1016/j. ins.2023.03.113
• Gul, M., Lo, HW., Yucesan, M. 2021. Fermatean fuzzy TOPSIS-based approach for occupational risk assessment in manufacturing. Complex Intell. Syst., 7: 2635-2653. Doi:10.1007/ s40747-021-00417-7
• Hazen, BT., Boone, CA., Wang, Y., Khor, KS. 2017. Perceived quality of remanufactured products: construct and measure development. J. Clean. Prod., 142: 716-726. Doi:10.1016/j. jclepro.2016.05.099
• Hoe, LC., Mansori, S. 2018. The effects of product quality on customer satisfaction and loyalty: evidence from Malaysian engineering industry. Int. J. Ind. Mark., 3: 20. Doi:10.5296/ ijim.v3i1.13959
• Hooshangi, N., Mahdizadeh Gharakhanlou, N., Ghaffari Razin, SR. 2023. Evaluation of potential sites in Iran to localize solar farms using a GIS-based Fermatean Fuzzy TOPSIS. J. Clean. Prod., 384: 135481. Doi:10.1016/j.jclepro.2022.135481
• Ilieva, G., Yankova, T. 2022. Extension of interval-valued Fermatean fuzzy TOPSIS for evaluating and benchmarking COVID-19 vaccines. Mathematics. 10: 1-22. Doi:10.3390/ math10193514
• Jaskulska, J. 2013. Quality of service and product as the main factors influencing customers’ satisfaction in the clothing retailing industry in Ireland - case study of Zara Plc. Dublin Business School, Dublin, İrlanda.
• Karnes, CL., Sridharan, SV., Kanet, JJ. 1995. Measuring quality from the consumer’s perspective: a methodology and its application. Int. J. Prod. Econ., 39: 215-225. Doi:10.1016/0925- 5273(95)00027-L
• Keshavarz-Ghorabaee, M., Amiri, M., Hashemi-Tabatabaei, M., Zavadskas, EK., Kaklauskas, A. 2020. A new decision-making approach based on fermatean fuzzy sets and waspas for green construction supplier evaluation. Mathematics, 8: 1-24. Doi:10.3390/math8122202
• Kianpour, K., Jusoh, A., Asghari, M. 2014. Environmentally friendly as a new dimension of product quality. Int. J. Qual. Reliab. Manag., 31: 547-565. Doi:10.1108/IJQRM-06-2012-0079
• Kim, Y., Chung, ES. 2013. Fuzzy VIKOR approach for assessing the vulnerability of the water supply to climate change and variability in South Korea. Appl. Math. Model., 37: 9419- 9430. Doi:10.1016/j.apm.2013.04.040
• Kirişci, M., Demir, I., Şimşek, N. 2022. Fermatean fuzzy ELECTRE multi-criteria group decision-making and most suitable biomedical material selection. Artif. Intell. Med., 127: 1-23. Doi:10.1016/j.artmed.2022.102278
• Kumar, L., Ibne Hossain, NU., Fazio, SA., Awasthi, A., Jaradat, R., Babski-Reeves, K. 2021. A data driven decision model for assessing the enablers of quality dimensions: context of industry 4.0. CIRP J. Manuf. Sci. Technol., 35: 896-910. Doi:10.1016/j.cirpj.2021.10.003
• Luczak, T., Burch, R., Smith, B., Chander, H., Carruth, D., Lamberth, J., Crane, C., Bollwinkel, D., Burgos, B. 2022. Using human factors engineering and Garvin’s product quality to develop a basketball shoe taxonomy. Proc. Inst. Mech. Eng. Part P J. Sport. Eng. Technol., 236: 60-69. Doi:10.1177/1754337120965421
• Mishra, AR., Liu, P., Rani, P. 2022a. COPRAS method based on interval-valued hesitant Fermatean fuzzy sets and its application in selecting desalination technology. Appl. Soft Comput., 119: 1-17. Doi:10.1016/j.asoc.2022.108570
• Mishra, AR., Rani, P., Pandey, K. 2022b. Fermatean fuzzy CRITIC-EDAS approach for the selection of sustainable third-party reverse logistics providers using improved generalized score function. J. Ambient Intell. Humaniz. Comput., 13: 295-311. Doi:10.1007/s12652-021-02902-w
• Özveri, O., Kabak, M. 2018. İşletmelerin ürün kalitesi etkinliğinin analiz edilmesi için bulanık veri zarflama analizi yönteminin kullanılması. Anadolu Üniversitesi Sos. Bilim. Derg., 18: 145-158.
• Rani, P., Mishra, AR. 2022. Interval-valued fermatean fuzzy sets with multi-criteria weighted aggregated sum product assessment-based decision analysis framework. Neural Comput. Appl., 34: 8051-8067. Doi:10.1007/s00521-021-06782-1
• Rani, P., Mishra, AR., Deveci, M., Antucheviciene, J. 2022. New complex proportional assessment approach using Einstein aggregation operators and improved score function for interval-valued Fermatean fuzzy sets. Comput. Ind. Eng., 169: 1-20. Doi:10.1016/j.cie.2022.108165
• Rao, CN., Sujatha, M. 2023. A consensus-based Fermatean fuzzy WASPAS methodology for selection of healthcare waste treatment technology selection. Decis. Mak. Appl. Manag. Eng., 6: 600-619. Doi:10.31181/dmame622023621
• Saha, A., Pamucar, D., Gorcun, OF., Raj Mishra, A. 2023. Warehouse site selection for the automotive industry using a fermatean fuzzy-based decision-making approach. Expert Syst. Appl., 211: 118497. Doi:10.1016/j.eswa.2022.118497
• Saaty, TL. 1977. A scaling method for priorities in hierarchical structures. J. Math. Psychol., 15: 234-281. Doi:10.1016/0022- 2496(77)90033-5 Sebastianelli, R., Tamimi, N. 2002. How product quality dimensions relate to defining quality. Int. J. Qual. Reliab. Manag., 19: 442-453. Doi:10.1108/02656710210421599
• Seker, S., Kahraman, C. 2021. Socio-economic evaluation model for sustainable solar PV panels using a novel integrated MCDM methodology: a case in Turkey. Socioecon. Plann. Sci., 77: 1-14. Doi:10.1016/j.seps.2020.100998
• Sergi, D., Sari, IU., Senapati, T. 2022. Extension of capital budgeting techniques using interval-valued Fermatean fuzzy sets. J. Intell. Fuzzy Syst., 42: 365-376. Doi:10.3233/JIFS-219196
• Sharma, MG., Kumar, G. 2016. Prioritizing quality of product and service dimensions with respect to a product-service system in the public transport sector. Qual. Manag. J., 23: 23-36. Doi:10.1080/10686967.2016.11918487
• Simic, V., Ebadi Torkayesh, A., Ijadi Maghsoodi, A. 2023. Locating a disinfection facility for hazardous healthcare waste in the COVID-19 era: a novel approach based on Fermatean fuzzy ITARA-MARCOS and random forest recursive feature elimination algorithm. Ann. Oper. Res., 328: 1105-1150. Doi:10.1007/s10479-022-04822-0
• Simić, V., Ivanović, I., Đorić, V., Torkayesh, AE. 2022. Adapting urban transport planning to the COVID-19 pandemic: an integrated Fermatean fuzzy model. Sustain. Cities Soc., 79: 1-26. Doi:10.1016/j.scs.2022.103669
• Sinclair, SA., Hansen, BG., Fern, EF. 1993. Industrial forest product quality: an empirical test of Garvin’s eight quality dimensions. Wood Fiber Sci., 25: 66-76.
• Singer, H., Özşahin, Ş. 2023. Applying an interval-valued Pythagorean fuzzy analytic hierarchy process to rank factors influencing wooden outdoor furniture selection. Wood Mater. Sci. Eng., 18: 322-333. Doi:10.1080/17480272.2021.2025427
• 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 J. Agric. For., 42: 364-371. Doi:10.3906/tar-1801-138
• Sousa, R., Voss, CA. 2002. Quality management re-visited: a reflective review and agenda for future research. J. Oper. Manag., 20: 91-109. Doi:10.1016/S0272-6963(01)00088-2
• Şengül, D., Çağil, G. 2020. Bulanık swara ve bulanık analitik hiyerarşi prosesi yöntemi ile iş değerlemesi. Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Derg., 11, 965-976. Doi:10.24012/dumf.715363
• Tripathi, AK., Agrawal, S., Gupta, RD. 2022. Comparison of GIS-based AHP and fuzzy AHP methods for hospital site selection: a case study for Prayagraj City, India. GeoJournal, 87: 3507-3528. Doi:10.1007/s10708-021-10445-y
• Verma, R., Chandra, S. 2021. Interval-valued intuitionistic fuzzy-analytic hierarchy process for evaluating the impact of security attributes in fog based Internet of Things paradigm. Comput. Commun., 175: 35-46. Doi:10.1016/j.comcom.2021.04.019
• Wudhikarn, R., Chakpitak, N., Neubert, G. 2015a. An analytic network process approach for the election of green marketable products. Benchmarking, 22: 994-1018. Doi:10.1108/BIJ-10- 2012-0069
• Wudhikarn, R., Chakpitak, N., Neubert, G. 2015b. Use of an analytic network process and monte carlo analysis in new product formula selection decisions. Asia-Pacific J. Oper. Res., 32: 1-28. Doi:10.1142/S0217595915500074
• Yang, S., Pan, Y., Zeng, S. 2022. Decision making framework based Fermatean fuzzy integrated weighted distance and TOPSIS for green low-carbon port evaluation. Eng. Appl. Artif. Intell., 114: 1-8. Doi:10.1016/j.engappai.2022.105048
• Zadeh, LA. 1965. Fuzzy sets. Inf. Control, 8: 338-353. Zavadskas, EK., Turskis, Z., Stević, Ž., Mardani, A. 2020. Modelling procedure for the selection of steel pipe supplier by applying the fuzzy ahp method. Oper. Res. Eng. Sci. Theory Appl., 3: 39-53. Doi:10.31181/oresta2003034z
• Zeng, S., Gu, J., Peng, X. 2023. Low-carbon cities comprehensive evaluation method based on Fermatean fuzzy hybrid distance measure and TOPSIS. Artif. Intell. Rev. 56: 8591-8607. Doi:10.1007/s10462-022-10387-y
• Zeng, S., Pan, Y., Jin, H. 2022. Online teaching quality evaluation of business statistics course utilizing Fermatean fuzzy analytical hierarchy process with aggregation operator. Systems, 10: 1-25. Doi:10.3390/systems10030063