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Sanayi Yatırımlarında Karar Destek Sistemleri: BOCR-FAHP Hibrit Modeli ile Sürdürülebilir Tekstil Fabrikası Yer Seçimi

Yıl 2026, Cilt: 27 Sayı: 1, 1 - 23, 26.01.2026

Damla Çevik Aka

https://doi.org/10.37880/cumuiibf.1681988

Öz

Bu çalışma, ihracat kapasitesi son dönemde artış gösteren tekstil sektöründeki bir firmanın yeni tesis yatırımı kararını sürdürülebilirlik perspektifinden ele almayı amaçlamaktadır. Karar verme süreci, çevresel boyutlar ve uzun vadeli sorumluluklar dikkate alınarak yapılandırılmıştır. Bu doğrultuda, tesis yeri seçimi gibi çok boyutlu karar problemlerine bütüncül bir yaklaşım sunan Fayda, Fırsat, Maliyet ve Risk (BOCR) modeli kullanılmıştır. Söz konusu model, yatırım kararlarını etkileyen çok yönlü faktörlerin dengeli bir şekilde değerlendirilmesini mümkün kılmaktadır. Örnek olaydaki üretici firma, Marmara Bölgesi’nde yer alan Tekirdağ, Kırklareli, Sakarya ve Kocaeli illerinden birinde yeni bir tesis kurmayı planlamaktadır. Yer seçimi kapsamında belirlenen 20 kriterin, firmanın beş üst düzey yöneticisi tarafından değerlendirilmesi ve bu doğrultuda en uygun alternatifin belirlenmesi hedeflenmiştir. Çalışmada, karar verme sürecine sistematik bir yaklaşım getirmek amacıyla BOCR-FAHP tabanlı bir model önerilmektedir. Sürdürülebilirlik odaklı kriterlerin geleneksel kriterlerle birlikte ele alınması, literatüre önemli katkılar sağlayacaktır. Ayrıca, gerçek işletme problemleri üzerinden yapılan analizlerle, bu çalışmanın stratejik karar alma süreçlerinde karar vericilere yol gösterici olması beklenmektedir. Elde edilen bulgular, sürdürülebilir bir tekstil fabrikası yeri seçiminde en kritik kriterin pazar erişilebilirliği olduğunu; bunu, bölgenin ulaşım ve lojistik altyapısı ile lojistik maliyetlerinin izlediğini ortaya koymuştur. Yapılan değerlendirmeler sonucunda, 10 üzerinden 8,03 puanla Tekirdağ ili, yeni tesis için en uygun lokasyon olarak belirlenmiştir.

Anahtar Kelimeler

BOCR Karar Destek Sistemi Fabrika Yeri Tekstil Endüstrisi Yer Seçimi Kararı

Etik Beyan

Bu çalışma Kırklareli Üniversitesi Rektörlüğü Bilimsel Araştırmalar ve Yayın Etiği Kurulu tarafından , E-35523585-199-155080 sayı numarası ile 18.03.2025 tarihinde etik kurul izni almıştır.

Kaynakça

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  • Altan, E., & Isik, Z. (2024). Digital twins in lean construction: A neutrosophic AHP–BOCR analysis approach. Engineering, Construction and Architectural Management, 31(12), 5029-5056. https://doi.org/10.1108/ECAM-11-2022-1115
  • Amelia, T., & Mohamed, R. (2024). Reprocolla: Requirements prioritisation model with collaboration perspectives based on cost-value approach. Journal of Information and Communication Technology, 23(2), 211-252. https://doi.org/10.32890/jict2024.23.2.3
  • Aslani, B., Rabiee, M., Jabbari, M., & Delen, D. (2024). Retracted Artİcle: An optimization framework for the sustainable healthcare facility location problem using a hierarchical conflict resolution approach. Annals of Operations Research, 337(Suppl 1), 31-32. https://doi.org/10.1007/s10479-023-05429-9
  • Bait, S., Lauria, S. M., & Schiraldi, M. M. (2021). Multi-criteria decision-making model for supporting manufacturing settlements location in Africa after COVID-19. International Journal of Engineering Business Management, 13, 18479790211023348. https://doi.org/10.1177/18479790211023348
  • Bait, S., Lauria, S. M., & Schiraldi, M. M. (2022). A risk-based hybrid multi-criteria approach to support managers in the industrial location selection in developing countries: A case study of textile sector in Africa. Journal of Cleaner Production, 335, 130325. https://doi.org/10.1016/j.jclepro.2021.130325
  • Bajpai, A., Kaul, A., Darbari, J.D., & Jha, P.C. (2020). A fuzzy MCDM model for facility location evaluation based on quality of life. Soft Comput Probl Solving 1:687–697. https://doi.org/10.1007/978-981-15-0035-0_56
  • Balbontin, C., & Hensher, D. A. (2019). Firm-specific and location-specific drivers of business location and relocation decisions. Transport Reviews, 39(5), 569-588. https://doi.org/10.1080/01441647.2018.1559254
  • Chithambaranathan, P., Rajkumar, A., Prithiviraj, D., & Palpandi, M. (2022). A multi criteria decision based approach for facility location selection with flexible criteria weights. Mater Today: Proc 62, 1215–1217. https://doi.org/10.1016/j.matpr.2022.04.467
  • Choi, G. (2022). Determinants of target location selection for acquirers in the manufacturing sector: Pollution intensity, policy enforcement, and civic environmentalism. Journal of Business Research, 146, 308-324. https://doi.org/10.1016/j.jbusres.2022.03.074
  • Gergin, R. E., Peker, I., Baki, B., Tuzkaya, U. R., & Tanyas, M. (2023). Oilseed warehouse location selection with an integrated approach: A case of Turkey. Kybernetes, 52(9), 3667-3705. https://doi.org/10.1108/K-10-2021-1072
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  • Jain, N. K., Kothari, T., & Kumar, V. (2016). Location choice research: Proposing new agenda. Management International Review, 56, 303-324. https://doi.org/10.1007/s11575-015-0271-6
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DECISION SUPPORT SYSTEMS IN INDUSTRIAL INVESTMENTS: SUSTAINABLE TEXTILE FACTORY LOCATION SELECTION VIA THE BOCR-AHP HYBRID MODEL

Yıl 2026, Cilt: 27 Sayı: 1, 1 - 23, 26.01.2026

Damla Çevik Aka

https://doi.org/10.37880/cumuiibf.1681988

Öz

This study aims to examine the investment decision of a textile company, which has recently increased its export capacity, from a sustainability perspective. The decision-making process considers both environmental factors and long-term responsibilities. In this context, the benefit, opportunity, cost, and risk (BOCR) model, which offers a holistic approach to complex decision-making problems such as facility location selection, is employed. This model enables a balanced evaluation of the multifaceted factors influencing investment decisions. The case manufacturing company plans to establish a new facility in one of the following provinces in the Marmara Region: Tekirdag, Kırklareli, Sakarya, or Kocaeli. Within the scope of the location selection process, 20 criteria were identified and evaluated by five senior executives of the company, with the aim of determining the most suitable alternative. Accordingly, this study proposes a BOCR-FAHP-based decision-making model to introduce a systematic approach to the evaluation process. The integration of sustainability-oriented criteria with conventional criteria is expected to make a significant contribution to the literature. Furthermore, by focusing on real-world business problems, this study is anticipated to serve as a practical guide for decision makers in strategic selection processes. The findings reveal that, in the context of selecting a sustainable textile factory location, market accessibility is the most critical criterion, followed by the region’s transportation and logistics infrastructure and logistics costs. As a result of the evaluations, Tekirdag was identified as the most suitable location for the new facility, with a score of 8.03 out of 10.

Anahtar Kelimeler

BOCR Decision Support System Factory Location Textile Industry Location Selection Decision.

Etik Beyan

This study was approved by the Kırklareli University Rectorate Scientific Research and Publication Ethics Committee with the number E-35523585-199-155080 on 18.03.2025.

Kaynakça

  • Abdel-Basset, M., Gamal, A., Chakrabortty, R. K., & Ryan, M. (2021). A new hybrid multi-criteria decision-making approach for location selection of sustainable offshore wind energy stations: A case study. Journal of Cleaner Production, 280, 124462. https://doi.org/10.1016/j.jclepro.2020.124462
  • Ali, A. M., Abdel-Basset, M., Abouhawwash, M., Gharib, M., & Mohamed, M. (2024). N-type-2-ARAS: An efficient hybrid multi-criteria optimization approach for end-of-life vehicle’s recycling facility location: A sustainable approach. Expert Systems with Applications, 250, 123873. https://doi.org/10.1016/j.eswa.2024.123873
  • Altan, E., & Isik, Z. (2024). Digital twins in lean construction: A neutrosophic AHP–BOCR analysis approach. Engineering, Construction and Architectural Management, 31(12), 5029-5056. https://doi.org/10.1108/ECAM-11-2022-1115
  • Amelia, T., & Mohamed, R. (2024). Reprocolla: Requirements prioritisation model with collaboration perspectives based on cost-value approach. Journal of Information and Communication Technology, 23(2), 211-252. https://doi.org/10.32890/jict2024.23.2.3
  • Aslani, B., Rabiee, M., Jabbari, M., & Delen, D. (2024). Retracted Artİcle: An optimization framework for the sustainable healthcare facility location problem using a hierarchical conflict resolution approach. Annals of Operations Research, 337(Suppl 1), 31-32. https://doi.org/10.1007/s10479-023-05429-9
  • Bait, S., Lauria, S. M., & Schiraldi, M. M. (2021). Multi-criteria decision-making model for supporting manufacturing settlements location in Africa after COVID-19. International Journal of Engineering Business Management, 13, 18479790211023348. https://doi.org/10.1177/18479790211023348
  • Bait, S., Lauria, S. M., & Schiraldi, M. M. (2022). A risk-based hybrid multi-criteria approach to support managers in the industrial location selection in developing countries: A case study of textile sector in Africa. Journal of Cleaner Production, 335, 130325. https://doi.org/10.1016/j.jclepro.2021.130325
  • Bajpai, A., Kaul, A., Darbari, J.D., & Jha, P.C. (2020). A fuzzy MCDM model for facility location evaluation based on quality of life. Soft Comput Probl Solving 1:687–697. https://doi.org/10.1007/978-981-15-0035-0_56
  • Balbontin, C., & Hensher, D. A. (2019). Firm-specific and location-specific drivers of business location and relocation decisions. Transport Reviews, 39(5), 569-588. https://doi.org/10.1080/01441647.2018.1559254
  • Chithambaranathan, P., Rajkumar, A., Prithiviraj, D., & Palpandi, M. (2022). A multi criteria decision based approach for facility location selection with flexible criteria weights. Mater Today: Proc 62, 1215–1217. https://doi.org/10.1016/j.matpr.2022.04.467
  • Choi, G. (2022). Determinants of target location selection for acquirers in the manufacturing sector: Pollution intensity, policy enforcement, and civic environmentalism. Journal of Business Research, 146, 308-324. https://doi.org/10.1016/j.jbusres.2022.03.074
  • Gergin, R. E., Peker, I., Baki, B., Tuzkaya, U. R., & Tanyas, M. (2023). Oilseed warehouse location selection with an integrated approach: A case of Turkey. Kybernetes, 52(9), 3667-3705. https://doi.org/10.1108/K-10-2021-1072
  • https://www.undp.org/sites/g/files/zskgke326/files/migration/tr/Sektorel_Yol_Haritalari_Turkiyede_Tekstil_Sektoru-re2.pdf. (The Access Date: 20.03.2025)
  • https://tim.org.tr/files/downloads/Strateji_Raporlari/ihracat_2024_raporu.pdf (The Access Date: 01.03.2025)
  • He, Z., & Romanos, M. (2016). Spatial agglomeration and location determinants: Evidence from the US communications equipment manufacturing industry. Urban Studies, 53(10), 2154-2174. https://doi.org/10.1177/0042098015586698
  • Huang, S. W., Liou, J. J., Tang, W., & Tzeng, G. H. (2020). Location selection of a manufacturing facility from the perspective of supply chain sustainability. Symmetry, 12(9), 1418. https://doi.org/10.3390/sym12091418
  • Jain, N. K., Kothari, T., & Kumar, V. (2016). Location choice research: Proposing new agenda. Management International Review, 56, 303-324. https://doi.org/10.1007/s11575-015-0271-6
  • Janssen, M., & Van Der Voort, H. (2016). Adaptive governance: Towards a stable, accountable and responsive government. Government Information Quarterly, 33(1), 1-5. https://doi.org/10.1016/j.giq.2016.02.003
  • Jia, F., Yin, S., Chen, L., & Chen, X. (2020). The circular economy in the textile and apparel industry: A systematic literature review. Journal of Cleaner Production, 259, 120728. https://doi.org/10.1016/j.jclepro.2020.120728
  • Kamal, M. A., Hasanat Shah, S., Jing, W., & Hasnat, H. (2020). Does the quality of institutions in host countries affect the location choice of Chinese OFDI: Evidence from Asia and Africa. Emerging Markets Finance and Trade, 56(1), 208-227. https://doi.org/10.1080/1540496X.2019.1610876
  • Kim, J., and Yang, M. (2023). Hydrogen production methods: Benefits, opportunities, costs, and risks. In Hydrogen Economy: Processes, Supply Chain, Life Cycle Analysis and Energy Transition for Sustainability. Edited by Antonio Scipioni, Alessandro Manzardo and Jingzheng Ren. Cambridge: Academic Press, 573–94. https://doi.org/10.1016/B978-0-323-99514-6.00018-2
  • Lee, A. (2009). A fuzzy AHP evaluation model for buyer–supplier relationships with the consideration of benefits, opportunities, costs and risks. Int. Journal of Production Research, 47, 4255-4280. https://doi.org/10.1080/00207540801908084
  • Liu, W. K. (2015). Using FDM and DEMATEL approaches to evaluate the location selection of investment. International Journal of Information and Education Technology, 5(10), 732. https://doi.org/10.7763/IJIET.2015.V5.602
  • Marinković, S., Nikolić, I., & Rakićević, J. (2018). Selecting location for a new business unit in ICT industry. Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, 36(2), 801-825. https://doi.org/10.18045/zbefri.2018.2.801
  • Medjoudj, R., Iberraken, F., & Aissani, D. (2016). Combining AHP method with BOCR merits to analyze the outcomes of business electricity sustainability. In Applications and Theory of Analytic Hierarchy Process-Decision Making for Strategic Decisions. IntechOpen. https://doi.org/10.5772/64042
  • Mittal, R., & Obaid, A. (2023). Sustainable warehouse location selection in humanitarian supply chain: Multi-criteria decision-making approach. International Journal of Mathematical, Engineering & Management Sciences, 8(2). https://doi.org/10.33889/IJMEMS.2023.8.2.019
  • Mousavi, S. M., Tavakkoli-Moghaddam, R., Heydar, M., & Ebrahimnejad, S. (2013). Multi-criteria decision making for plant location selection: An integrated Delphi–AHP–PROMETHEE methodology. Arabian Journal for Science and Engineering, 38, 1255-1268. https://doi.org/10.1007/s13369-012-0361-8
  • Nacar, E.N., & Erdebilli, B. (2021). Tesis yeri seçimine yeni bir bakış: Katmanlı çok kriterli karar verme yöntemi. Verimlilik Dergisi 4, 103–117. https://doi.org/10.51551/verimlilik.832480
  • Neves-Silva, R., & Camarinha-Matos, L. M. (2022). Simulation-based decision support system for energy efficiency in buildings retrofitting. Sustainability, 14(19), 12216. https://doi.org/10.3390/su141912216
  • Nghiem, T. B. H., & Chu, T. C. (2024). A total distance ranking approach to fuzzy AHP-based MCDM method for selecting sustainable manufacturing facility location. Journal of Intelligent & Fuzzy Systems, 46(2), 3085-3115. https://doi.org/10.3233/JIFS-223962
  • Onden, I., & Eldemir, F. (2015). GIS and f-AHP integration for locating a new textile manufacturing facility, Fibres & Textiles in Eastern Europe, 5, 113, 18–22. https://doi.org/10.5604/12303666.1161751
  • Organ, A., & Tekin, B. (2017). Şehir hastanesi kuruluş yerı seçimi için gri ilişkisel analiz yaklaşımı: Denizli ili örneği. Adnan Menderes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 4(3), 256-278. https://doi.org/10.30803/adusobed.336967
  • Ozkurt, P. (2024). A MCDM approach to the facility location selection problem of sustainable solid waste management. Present Environment & Sustainable Development, 18(2). https://doi.org/10.47743/pesd2024182006
  • Pekkaya, M., & Bucak, U. (2018). Çok kriterli karar verme yöntemleriyle bölgesel liman kuruluş yeri seçimi: Batı Karadeniz’de bir uygulama. Uluslararası İktisadi ve İdari İncelemeler Dergisi, 253-268. https://doi.org/10.18092/ulikidince.353653
  • Rahman, M. S., Ali, M. I., Hossain, U., & Mondal, T. K. (2018). Facility location selection for plastic manufacturing industry in Bangladesh by using AHP method. International Journal of Research in Industrial Engineering, 7(3), 307-319.
  • Ray, A., De, A., & Dan, P. K. (2015). Facility location selection using complete and partial ranking MCDM methods. International Journal of Industrial and Systems Engineering, 19(2), 262-276. https://doi.org/10.1504/IJISE.2015.067251
  • Saaty, T. L. (2002). Decision making with the analytic hierarchy process. Scientia Iranica, 9(3), 215–229.
  • Saaty, T. L., & Ozdemir, M. (2003). Negative priorities in the analytic hierarchy process. Mathematical and computer modelling, 37(9-10), 1063-1075. https://doi.org/10.1016/S0895-7177(03)00118-3
  • Saaty, T.R. (2004). Fundamentals of the analytic network process—multiple networks with benefits, costs, opportunities and risks, Journal of Systems Science and Systems Engineering, 13, 348-379. https://doi.org/10.1007/s11518-006-0171-1
  • Sanjari-Parizi, M., Sazvar, Z., Nayeri, S., & Mehralizade, R. (2024). Novel decision-making methods for the sustainable warehouse location selection problem considering the value alteration boundaries and accumulation of alternatives. Clean Technologies and Environmental Policy, 26(9), 2977-3002. https://doi.org/10.1007/s10098-024-02759-5
  • Sharma, P., Singh Ghatorha, K., Kang, A. S., Cepova, L., Kumar, A., & Phanden, R. K. (2024). Strategic insights in manufacturing site selection: a multi-method approach using factor rating, analytic hierarchy process, and best worst method. Frontiers in Mechanical Engineering, 10, 1392543. https://doi.org/10.3389/fmech.2024.1392543
  • Shuyan, L., & Fabuš, M. (2019). Study on the spatial distribution of China's outward foreign direct investment in EU and its influencing factors. Entrepreneurship and Sustainability Issues, 6(3), 1280. https://doi.org/10.9770/jesi.2019.6.3(16)
  • Silva, M. G., Przybysz, A. L., & Piekarski, C. M. (2022). Location as a key factor for waste to energy plants. Journal of Cleaner Production, 379, 134386. https://doi.org/10.1016/j.jclepro.2022.134386
  • Singh, R.K., Chaudhary, N., & Saxena, N. (2018). Selection of warehouse location for a global supply vhain: A case study. IIMB Management Review, 30(4), 343-356. https://doi.org/10.1016/j.iimb.2018.08.009
  • Sobczyk, E. J., Galica, D., Kopacz, M., & Sobczyk, W. (2022). Selecting the optimal exploitation option using a digital deposit model and the AHP. Resources Policy, 78, 102952. https://doi.org/10.1016/j.resourpol.2022.102952
  • Suman, N.H., Sarfaraj, N., Cyhon, F.A., & Fahim, R.I. (2021) Facility location selection for the furniture industry of Bangladesh: Comparative AHP and FAHP analysis. International Journal Eng. Bus Manag. 13, 1–15. https://doi.org/10.1177/18479790211030851
  • Terme, B., Cicek, İ., & Kiraz, A. (2022). Entegre bulanık AHP ve bulanık VIKOR yöntemleriyle tesis yeri seçimi. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi 37(2), 383–398. https://doi.org/10.21605/cukurovaumfd.1146098
  • Topaloglu, F. (2024). Development of a new hybrid method for multi-criteria decision making (MCDM) approach: A case study for facility location selection. Operational Research, 24(4), 60. https://doi.org/10.1007/s12351-024-00871-4
  • Torkayesh, A. E., & Simic, V. (2022). Stratified hybrid decision model with constrained attributes: Recycling facility location for urban healthcare plastic waste. Sustainable Cities and Society, 77, 103543. https://doi.org/10.1016/j.scs.2021.103543
  • Ulutas, A., & Karakuş, C. (2021). Location selection for a textile manufacturing facility with GIS based on hybrid MCDM approach. Industria Textila, 72(2). https://doi.org/10.35530/IT.072.02.1736
  • Yap, H.Y., & Nixon, J. D. (2015). A multi-criteria analysis of options for energy recovery from municipal solid waste in India and the UK. Waste Management, 46, 265-277. https://doi.org/10.1016/j.wasman.2015.08.002
  • Wang, K. J., Lestari, Y. D., & Tran, V. N. B. (2017). Location selection of high-tech manufacturing firms by a fuzzy analytic network process: a case study of Taiwan high-tech industry. International Journal of Fuzzy Systems, 19(5), 1560-1584. https://doi.org/10.1007/s40815-016-0264-z
  • Wang, X., Zhang, C., & Zhang, Z. (2019). Pollution haven or porter? The impact of environmental regulation on location choices of pollution-intensive firms in China. Journal of Environmental Management, 248, 109248. https://doi.org/10.1016/j.jenvman.2019.07.019
  • Wang, X., Lin, R., Ye, W., & Ma, Z. (2023). Are expensive expressways in China attractive to businesses? Evidence from the location selections of manufacturing enterprises. Transportation Research Record, 2677(5), 567-578. https://doi.org/10.1177/03611981221133384
  • Wijnmalen, J. D. (2007). Analysis of benefits, opportunities, costs, and risks (BOCR) with the AHP–ANP: A critical validation. Mathematical and Computer Modelling 7–8: 892–905. https://doi.org/10.1016/j.mcm.2007.03.020
  • Wyrwa, J. (2019). Analysis of determinants of the inflow of foreign direct investment to Poland. Part I–theoretical considerations. Management, 23(2). https://doi.org/10.2478/manment-2019-0029
Toplam 56 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İşletme
Bölüm Araştırma Makalesi
Yazarlar

Damla Çevik Aka 0000-0001-9622-273X

Gönderilme Tarihi 22 Nisan 2025
Kabul Tarihi 12 Kasım 2025
Yayımlanma Tarihi 26 Ocak 2026
Yayımlandığı Sayı Yıl 2026 Cilt: 27 Sayı: 1

Kaynak Göster

APA Çevik Aka, D. (2026). DECISION SUPPORT SYSTEMS IN INDUSTRIAL INVESTMENTS: SUSTAINABLE TEXTILE FACTORY LOCATION SELECTION VIA THE BOCR-AHP HYBRID MODEL. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, 27(1), 1-23. https://doi.org/10.37880/cumuiibf.1681988

Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi Creative Commons Atıf-GayriTicari 4.0 Uluslararası Lisansı (CC BY NC) ile lisanslanmıştır.