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Prioritization of Industrial Symbiosis Enablers Using a Hesitant Fuzzy SWARA Approach

Yıl 2025, Cilt: 13 Sayı: 2, 200 - 228

Sinan Çıkmak

https://doi.org/10.22139/jobs.1671070

Öz

Industrial symbiosis (IS), a crucial tool for reducing industrial waste, preventing pollution, and enhancing resource efficiency, is emerging as one of the sustainable approaches. IS is a network structure in which independent industrial enterprises cooperate and use the waste or by-products of one as raw material for the other. This synergistic network structure can help companies reduce costs, boost efficiency, and lessen negative environmental impacts. However, successful IS implementation relies on key enabling factors facilitating collaboration and ensuring mutual benefits among participants. This study focuses on Türkiye, where the development of IS networks holds significant potential due to its industrial diversity and growing emphasis on sustainability. It aims to rank the critical enabling factors in fostering these networks. To achieve this aim, Stepwise Weight Assessment Ratio Analysis (SWARA), a subjective multi-criteria decision-making (MCDM) technique that systematically evaluates and ranks criteria based on expert judgments, was employed. This approach was integrated with hesitant fuzzy sets to account for uncertainty and hesitation in expert opinions, ensuring a more robust assessment of the enabling factors. In the present study, a comprehensive literature review and expert opinions were employed to identify 23 sub-enablers falling under five main dimensions. The hesitant fuzzy SWARA method was then applied to calculate their importance weights. The results of the study indicate that the five most critical sub-enablers are, in descending order of importance: "reduction of raw material costs," "interest and support from top management," "reduction of waste disposal costs," "geographical proximity," and "openness to new business ideas."

Anahtar Kelimeler

Industrial Symbiosis Enablers Hesitant Fuzzy Sets SWARA

Kaynakça

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Yıl 2025, Cilt: 13 Sayı: 2, 200 - 228

Sinan Çıkmak

https://doi.org/10.22139/jobs.1671070

Öz

Kaynakça

  • Agarwal, S., Kant, R., & Shankar, R. (2020). Evaluating solutions to overcome humanitarian supply chain management barriers: A hybrid fuzzy SWARA–Fuzzy WASPAS approach. International Journal of Disaster Risk Reduction, 51, 101838.
  • Agudo, F. L., Bezerra, B. S., Paes, L. A. B., & Júnior, J. A. G. (2022). Proposal of an assessment tool to diagnose industrial symbiosis readiness. Sustainable Production and Consumption, 30, 916–929.
  • Alakaş, H. M., Gür, Ş., Özcan, E., & Eren, T. (2020). Ranking of sustainability criteria for industrial symbiosis applications based on ANP. Journal of Environmental Engineering and Landscape Management, 28(4), 192–201.
  • Alimardani, M., Hashemkhani Zolfani, S., Aghdaie, M. H., & Tamošaitienė, J. (2013). A novel hybrid SWARA and VIKOR methodology for supplier selection in an agile environment. Technological and Economic Development of Economy, 19(3), 533–548.
  • Alkaya, E. (2021). Türkiye’de endüstriyel simbiyoz: Mevcut durum raporu. İzmir Development Agency. https://endustriyelsimbiyoz.ikvp.izka.org.tr/wp-content/uploads/2022/05/EK-6.-Endustriyel-Simbiyoz-Mevcut-Durum-Raporu_public.pdf
  • Behera, S. K., Kim, J. H., Lee, S. Y., Suh, S., & Park, H. S. (2012). Evolution of ‘designed’ industrial symbiosis networks in the Ulsan Eco-industrial Park: ‘Research and development into business’ as the enabling framework. Journal of Cleaner Production, 29, 103–112.
  • Boons, F., Chertow, M., Park, J., Spekkink, W., & Shi, H. (2017). Industrial symbiosis dynamics and the problem of equivalence: Proposal for a comparative framework. Journal of Industrial Ecology, 21(4), 938–952.
  • Cerceau, J., Mat, N., Junqua, G., Lin, L., Laforest, V., & Gonzalez, C. (2014). Implementing industrial ecology in port cities: International overview of case studies and cross-case analysis. Journal of Cleaner Production, 74, 1–16.
  • Çevre, Şehircilik ve İklim Değişikliği Bakanlığı. (2023). Endüstriyel Simbiyoz Kılavuzu. https://www.akillisehirler.gov.tr/wp-content/uploads/2024/09/Endustriyel-Simbiyoz-Kilavuzu.pdf
  • Chanas, S. (2001). On the interval approximation of a fuzzy number. Fuzzy Sets and Systems, 122(2), 353–356.
  • Chertow, M. R. (2000). Industrial symbiosis: Literature and taxonomy. Annual Review of Energy and the Environment, 25(1), 313–337.
  • Chertow, M. R. (2007). Uncovering industrial symbiosis. Journal of Industrial Ecology, 11(1), 11–30.
  • Chertow, M. R., Ashton, W. S., & Espinosa, J. C. (2008). Industrial symbiosis in Puerto Rico: Environmentally related agglomeration economies. Regional Studies, 42(10), 1299–1312.
  • Chrysikopoulos, S. K., Chountalas, P. T., Georgakellos, D. A., & Lagodimos, A. G. (2024). Modeling critical success factors for industrial symbiosis. Eng, 5(4), 2902–2919.
  • Corder, G. D., Golev, A., Fyfe, J., & King, S. (2014). The status of industrial ecology in Australia: Barriers and enablers. Resources, 3(2), 340–361.
  • Demircioğlu, E. N., & Ever, D. (2020). Döngüsel ekonomiye geçişte endüstriyel simbiyozun maliyetler üzerine etkisi. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 29(3), 461–473.
  • Dolgen, D., & Alpaslan, M. N. (2020). Eco-industrial parks: Experiences from Turkey. Global Journal of Ecology, 5(1), 30–32.
  • Domenech, T., Bleischwitz, R., Doranova, A., Panayotopoulos, D., & Roman, L. (2019). Mapping industrial symbiosis development in Europe: Typologies of networks, characteristics, performance and contribution to the circular economy. Resources, Conservation and Recycling, 141, 76–98.
  • Durusoy, Ö. T. (2021). Endüstriyel simbiyoz (ortak yaşam): Çevresel bir yaklaşım. Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 26(2), 563–590.
  • Erdal, H. (2022). Tereddütlü bulanık dilsel terimler tabanlı SWARA yönetimi ile zararlı/olumsuz liderlik türlerinin karşılaştırmalı nicel analizi. In L. Sürücü (Ed.), Liderliğin Karanlık Yüzü (pp. 205–231). Ankara: Orion Akademi.
  • Erol, I., Peker, I., Ar, I. M., & Searcy, C. (2023). Examining the role of urban-industrial symbiosis in the circular economy: An approach based on N-Force field theory of change and N-ISM-Micmac. Operations Management Research, 16(4), 2125–2147.
  • Farhadinia, B., & Herrera-Viedma, E. (2019). Multiple criteria group decision making method based on extended hesitant fuzzy sets with unknown weight information. Applied Soft Computing, 78, 310–323.
  • Ghenai, C., Albawab, M., & Bettayeb, M. (2020). Sustainability indicators for renewable energy systems using multi-criteria decision-making model and extended SWARA/ARAS hybrid method. Renewable Energy, 146, 580–589.
  • Ghorabaee, M. K., Amiri, M., Zavadskas, E. K., & Antucheviciene, J. (2018). A new hybrid fuzzy MCDM approach for evaluation of construction equipment with sustainability considerations. Archives of Civil and Mechanical Engineering, 18, 32–49.
  • Ghorui, N., Ghosh, A., Mondal, S. P., Bajuri, M. Y., Ahmadian, A., Salahshour, S., & Ferrara, M. (2021). Identification of dominant risk factor involved in spread of COVID-19 using hesitant fuzzy MCDM methodology. Results in Physics, 21, 103811.
  • Gibbs, D. (2003). Trust and networking in inter-firm relations: The case of eco-industrial development. Local Economy, 18(3), 222–236.
  • Giurco, D., Bossilkov, A., Patterson, J., & Kazaglis, A. (2011). Developing industrial water reuse synergies in Port Melbourne: Cost effectiveness, barriers and opportunities. Journal of Cleaner Production, 19(8), 867–876.
  • Gök Kısa, A. C., & Ayçin, E. (2019). OECD ülkelerinin lojistik performanslarının SWARA tabanlı EDAS yöntemi ile değerlendirilmesi. Çankırı Karatekin Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 9(1), 301–325.
  • Harfeldt-Berg, L., & Harfeldt-Berg, M. (2023). Connecting organizational context to environmental sustainability initiatives and industrial symbiosis: Empirical results and case analysis. Sustainable Production and Consumption, 40, 210–219.
  • Harfeldt-Berg, L., Broberg, S., & Ericsson, K. (2022). The importance of individual actor characteristics and contextual aspects for promoting industrial symbiosis networks. Sustainability, 14(9), 4927.
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  • Jensen, P. D. (2016). The role of geospatial industrial diversity in the facilitation of regional industrial symbiosis. Resources, Conservation and Recycling, 107, 92–103.
  • Jensen, P. D., Basson, L., Hellawell, E. E., Bailey, M. R., & Leach, M. (2011). Quantifying ‘geographic proximity’: Experiences from the United Kingdom's national industrial symbiosis programme. Resources, Conservation and Recycling, 55(7), 703–712.
  • Ji, Y., Liu, Z., Wu, J., He, Y., & Xu, H. (2020). Which factors promote or inhibit enterprises’ participation in industrial symbiosis? An analytical approach and a case study in China. Journal of Cleaner Production, 244, 118600.
  • Kang, D., Jaisankar, R., Murugesan, V., Suvitha, K., Narayanamoorthy, S., Omar, A. H., ... & Ahmadian, A. (2023). A novel MCDM approach to selecting a biodegradable dynamic plastic product: A probabilistic hesitant fuzzy set-based COPRAS method. Journal of Environmental Management, 340, 117967.
  • Kayapınar Kaya, S., & Erginel, N. (2020). Futuristic airport: A sustainable airport design by integrating hesitant fuzzy SWARA and hesitant fuzzy sustainable quality function deployment. Journal of Cleaner Production, 275, 123880.
  • Keršuliene, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243–258.
  • Khan, Z. A., Chowdhury, S. R., Mitra, B., Mozumder, M. S., Elhaj, A. I., Salami, B. A., ... & Rahman, S. M. (2023). Analysis of industrial symbiosis case studies and its potential in Saudi Arabia. Journal of Cleaner Production, 385, 135536.
  • Lambert, A. J. D., & Boons, F. A. (2022). Eco-industrial parks: Stimulating sustainable development in mixed industrial parks. Technovation, 22(8), 471–484.
  • Lasthein, M. K., Lingås, D. B., & Johansen, L. M. (2021). Guide for industrial symbiosis facilitators. Kalundborg Symbiosis. http://www.symbiosis.dk/wp-content/uploads/2021/03/Guide-for-IS-facilitators_online2.pdf
  • Lawal, M., Alwi, S. R. W., Manan, Z. A., & Ho, W. S. (2021). Industrial symbiosis tools—A review. Journal of Cleaner Production, 280, 124327.
  • Leigh, M., & Li, X. (2015). Industrial ecology, industrial symbiosis and supply chain environmental sustainability: A case study of a large UK distributor. Journal of Cleaner Production, 106, 632–643.
  • Liu, H., & Rodríguez, R. M. (2014). A fuzzy envelope for hesitant fuzzy linguistic term set and its application to multicriteria decision making. Information Sciences, 258, 220–238.
  • Liu, P., & Zhang, X. (2020). A new hesitant fuzzy linguistic approach for multiple attribute decision making based on Dempster–Shafer evidence theory. Applied Soft Computing, 86, 105897.
  • Lombardi, D. R., & Laybourn, P. (2012). Redefining industrial symbiosis: Crossing academic–practitioner boundaries. Journal of Industrial Ecology, 16(1), 28–37.
  • Madsen, J. K., Boisen, N., Nielsen, L. U., & Tackmann, L. H. (2015). Industrial symbiosis exchanges: Developing a guideline to companies. Waste and Biomass Valorization, 6, 855–864.
  • Mardani, A., Saraji, M. K., Mishra, A. R., & Rani, P. (2020). A novel extended approach under hesitant fuzzy sets to design a framework for assessing the key challenges of digital health interventions adoption during the COVID-19 outbreak. Applied Soft Computing, 96, 106613.
  • Martin, M., & Harris, S. (2018). Prospecting the sustainability implications of an emerging industrial symbiosis network. Resources, Conservation and Recycling, 138, 246–256.
  • Mirata, M. (2004). Experiences from early stages of a national industrial symbiosis programme in the UK: Determinants and coordination challenges. Journal of Cleaner Production, 12(8–10), 967–983.
  • Mishra, A. R., Rani, P., Pardasani, K. R., & Mardani, A. (2019). A novel hesitant fuzzy WASPAS method for assessment of green supplier problem based on exponential information measures. Journal of Cleaner Production, 238, 117901.
  • Mortensen, L., & Kørnøv, L. (2019). Critical factors for industrial symbiosis emergence process. Journal of Cleaner Production, 212, 56–69.
  • Moser, S., & Rodin, V. (2021). The “industrial symbiosis”: Information asymmetries are the main challenge for industrial symbiosis – Evidence from four Austrian testbeds with a focus on heat exchange. Elektrotechnik & Informationstechnik, 138(4–5), 264–268.
  • Müyeseroğlu, A., Onaygil, S., & Acuner, E. (2024). Importance of industrial symbiosis strategies on energy efficiency improvement in organized industrial zones: Konya OIZ case. Konya Journal of Engineering Sciences, 12(4), 838–864.
  • Neves, A., Godina, R., Azevedo, S. G., & Matias, J. C. (2020). A comprehensive review of industrial symbiosis. Journal of Cleaner Production, 247, 119113.
  • Neves, A., Godina, R., Azevedo, S. G., Pimentel, C., & Matias, J. C. O. (2019). The potential of industrial symbiosis: Case analysis and main drivers and barriers to its implementation. Sustainability, 11(24), Article 7095.
  • Ohnishi, S., Dong, H., Geng, Y., Fujii, M., & Fujita, T. (2017). A comprehensive evaluation on industrial and urban symbiosis by combining MFA, carbon footprint, and emergy methods—Case of Kawasaki, Japan. Ecological Indicators, 73, 513–524.
  • Özkan, A., Günkaya, Z., Özdemir, A., & Banar, M. (2018). Sanayide temiz üretim ve döngüsel ekonomiye geçişte endüstriyel simbiyoz yaklaşımı: Bir değerlendirme. Anadolu University Journal of Science and Technology B-Theoretical Sciences, 6(1), 84–97.
  • Ramírez-Rodríguez, L. C., Ormazabal, M., & Jaca, C. (2024). Mapping sustainability assessment methods through the industrial symbiosis life cycle for a circular economy. Sustainable Production and Consumption, 50, 253–267.
  • Ren, R., Liao, H., Al-Barakati, A., & Cavallaro, F. (2019). Electric vehicle charging station site selection by an integrated hesitant fuzzy SWARA-WASPAS method. Transformations in Business & Economics, 18(2).
  • Ruiz-Puente, C., & Jato-Espino, D. (2020). Systemic analysis of the contributions of co-located industrial symbiosis to achieve sustainable development in an industrial park in Northern Spain. Sustainability, 12(14), 5802.
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  • Sequeira, M., Adlemo, A., & Hilletofth, P. (2023). A hybrid fuzzy-AHP-TOPSIS model for evaluation of manufacturing relocation decisions. Operations Management Research, 16(1), 164–191.
  • Sindhwani, R., Singh, P. L., Behl, A., Afridi, M. S., Sammanit, D., & Tiwari, A. K. (2022). Modeling the critical success factors of implementing net zero emission (NZE) and promoting resilience and social value creation. Technological Forecasting and Social Change, 181, 121759.
  • Sonel, E., Gür, Ş., & Eren, T. (2022). Analysis of factors affecting industrial symbiosis collaboration. Environmental Science and Pollution Research, 29(6), 8479–8486.
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  • Taqi, H. M. M., Meem, E. J., Bhattacharjee, P., Salman, S., Ali, S. M., & Sankaranarayanan, B. (2022). What are the challenges that make the journey towards industrial symbiosis complicated? Journal of Cleaner Production, 370, 133384.
  • Torra, V. (2010). Hesitant fuzzy sets. International Journal of Intelligent Systems, 25(6), 529–539.
  • Tseng, M. L., & Bui, T. D. (2017). Identifying eco-innovation in industrial symbiosis under linguistic preferences: A novel hierarchical approach. Journal of Cleaner Production, 140, 1376–1389.
  • TÜİK (Turkish Statistical Institute). (2023). The results of address-based population registration system, 2023. Ankara. https://data.tuik.gov.tr/Bulten/Index?p=The-Results-of-Address-Based-Population-Registration-System-2023-49684&dil=2
  • Ulutaş, A., Karakuş, C. B., & Topal, A. (2020). Location selection for logistics center with fuzzy SWARA and CoCoSo methods. Journal of Intelligent & Fuzzy Systems, 38(4), 4693–4709.
  • Velenturf, A. P. (2016). Promoting industrial symbiosis: Empirical observations of low-carbon innovations in the Humber region, UK. Journal of Cleaner Production, 128, 116–130.
  • Xia, M., & Xu, Z. (2011). Hesitant fuzzy information aggregation in decision making. International Journal of Approximate Reasoning, 52(3), 395–407.
  • Yang, T., Liu, C., Côté, R. P., Ye, J., & Liu, W. (2022). Evaluating the barriers to industrial symbiosis using a group AHP-TOPSIS model. Sustainability, 14(11), Article 6815.
  • Yazıcı, E., Alakaş, H. M., & Eren, T. (2023). Prioritizing of sectors for establishing a sustainable industrial symbiosis network with Pythagorean fuzzy AHP-Pythagorean fuzzy TOPSIS method: A case of industrial park in Ankara. Environmental Science and Pollution Research, 30(31), 77875–77889.
  • Yazıcı, E., Alakaş, H. M., & Eren, T. (2024). Selection of waste receiving companies for sustainable industrial symbiosis network: An application a case in Ankara for foundry industry waste. Neural Computing and Applications, 36, 13009–13026.
  • Yeşilkaya, M., Daş, G. S., & Türker, A. K. (2020). A multi-objective multi-period mathematical model for an industrial symbiosis network based on the forest products industry. Computers & Industrial Engineering, 150, 106883.
  • Yuan, Z., & Shi, L. (2009). Improving enterprise competitive advantage with industrial symbiosis: Case study of a smeltery in China. Journal of Cleaner Production, 17(14), 1295–1302.
  • Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353.
Toplam 86 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İşletme
Bölüm Araştırma Makalesi
Yazarlar

Sinan Çıkmak 0000-0002-4704-3409

Erken Görünüm Tarihi 2 Temmuz 2025
Yayımlanma Tarihi
Gönderilme Tarihi 7 Nisan 2025
Kabul Tarihi 14 Mayıs 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 13 Sayı: 2

Kaynak Göster

APA Çıkmak, S. (2025). Prioritization of Industrial Symbiosis Enablers Using a Hesitant Fuzzy SWARA Approach. İşletme Bilimi Dergisi, 13(2), 200-228. https://doi.org/10.22139/jobs.1671070
AMA Çıkmak S. Prioritization of Industrial Symbiosis Enablers Using a Hesitant Fuzzy SWARA Approach. About the Journal. Temmuz 2025;13(2):200-228. doi:10.22139/jobs.1671070
Chicago Çıkmak, Sinan. “Prioritization of Industrial Symbiosis Enablers Using a Hesitant Fuzzy SWARA Approach”. İşletme Bilimi Dergisi 13, sy. 2 (Temmuz 2025): 200-228. https://doi.org/10.22139/jobs.1671070.
EndNote Çıkmak S (01 Temmuz 2025) Prioritization of Industrial Symbiosis Enablers Using a Hesitant Fuzzy SWARA Approach. İşletme Bilimi Dergisi 13 2 200–228.
IEEE S. Çıkmak, “Prioritization of Industrial Symbiosis Enablers Using a Hesitant Fuzzy SWARA Approach”, About the Journal, c. 13, sy. 2, ss. 200–228, 2025, doi: 10.22139/jobs.1671070.
ISNAD Çıkmak, Sinan. “Prioritization of Industrial Symbiosis Enablers Using a Hesitant Fuzzy SWARA Approach”. İşletme Bilimi Dergisi 13/2 (Temmuz 2025), 200-228. https://doi.org/10.22139/jobs.1671070.
JAMA Çıkmak S. Prioritization of Industrial Symbiosis Enablers Using a Hesitant Fuzzy SWARA Approach. About the Journal. 2025;13:200–228.
MLA Çıkmak, Sinan. “Prioritization of Industrial Symbiosis Enablers Using a Hesitant Fuzzy SWARA Approach”. İşletme Bilimi Dergisi, c. 13, sy. 2, 2025, ss. 200-28, doi:10.22139/jobs.1671070.
Vancouver Çıkmak S. Prioritization of Industrial Symbiosis Enablers Using a Hesitant Fuzzy SWARA Approach. About the Journal. 2025;13(2):200-28.

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