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Circular economy and fuzzy set theory: a bibliometric and systematic review based on Industry 4.0 technologies perspective

    Xunjie Gou Affiliation
    ; Xinru Xu Affiliation
    ; Zeshui Xu Affiliation
    ; Marinko Skare Affiliation

Abstract

The Circular Economy (CE) is receiving more attention, especially in Industry 4.0 (I4.0). In the face of several ambiguous and uncertain information, fuzzy techniques based on Fuzzy Set Theory (FST) are essential for developing CE strategies. This paper uses bibliometric methods to analyze the characteristics of the authors, nations/regions, institutions of the literature of FST and CE, and the collaborations relations between them, and then summarize the literature on fuzzy techniques in the CE and identify the specific role that FST can play in each stage of CE, its primary effects on the CE’s pre-preparation stage, design and production stage, and recycling and reuse stage. Meanwhile, the paper explores the advantages of I4.0 technologies for CE and analyzes the research on the role of fuzzy techniques based on FST for CE and I4.0 technologies. Last but not least, this paper is concluded by summarizing the knowledge gained from the bibliometric and content analyses of the literature and suggesting further research directions of investigation. This research will draw attention to FST’s contribution and encourage its advancement in CE and I4.0 technologies.

Keyword : circular economy, fuzzy set theory, Industry 4.0, I4.0 technology, Internet of Things

How to Cite
Gou, X., Xu, X., Xu, Z., & Skare, M. (2024). Circular economy and fuzzy set theory: a bibliometric and systematic review based on Industry 4.0 technologies perspective. Technological and Economic Development of Economy, 30(2), 489–526. https://doi.org/10.3846/tede.2024.20286
Published in Issue
May 9, 2024
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References

Abdul-Hamid, A. Q., Ali, M. H., Tseng, M. L., Lan, S. L., & Kumar, M. (2020). Impeding challenges on industry 4.0 in circular economy: Palm oil industry in Malaysia. Computers & Operations Research, 123, Article 105052. https://doi.org/10.1016/j.cor.2020.105052

Agarwal, S., Tyagi, M., & Garg, R. K. (2023). The conception of circular economy obstacles in the context of supply chain: A case of rubber industry. International Journal of Productivity and Performance Management, 72(4), 1111–1153. https://doi.org/10.1108/IJPPM-12-2020-0686

Agarwal, S., Tyagi, M., & Garg, R. K. (2022). Framework development and evaluation of Industry 4.0 technological aspects towards improving the circular economy-based supply chain. Industrial Robot-the International Journal of Robotics Research and Application, 49(3), 555–581. https://doi.org/10.1108/IR-10-2021-0246

Agrawal, R., Wankhede, V. A., Kumar, A., Upadhyay, A., & Garza-Reyes, J. A. (2022). Nexus of circular economy and sustainable business performance in the era of digitalization. International Journal of Productivity and Performance Management, 71(3), 748–774. https://doi.org/10.1108/IJPPM-12-2020-0676

Ahmed, A. A., Nazzal, M. A., Darras, B. M., & Deiab, I. M. (2022). A comprehensive multi-level circular economy assessment framework. Sustainable Production and Consumption, 32, 700–717. https://doi.org/10.1016/j.spc.2022.05.025

Akbari, M., & Hopkins, J. L. (2022). Digital technologies as enablers of supply chain sustainability in an emerging economy. Operations Management Research, 15, 689–710. https://doi.org/10.1007/s12063-021-00226-8

Akram, S. V., Malik, P. K., Singh, R., Gehlot, A., Juyal, A., Ghafoor, K. Z., & Shrestha, S. (2022). Implementation of digitalized technologies for fashion Industry 4.0: Opportunities and challenges. Scientific Programming, 2022, Article 7523246. https://doi.org/10.1155/2022/7523246

Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An r-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007

Alam, T. M., Shaukat, K., Khelifi, A., Khan, W. A., Raza, H. M. E., Idrees, M., Luo, S., & Hameed, I. A. (2022). Disease diagnosis system using IoT empowered with fuzzy inference system. Cmc-Computers Materials & Continua, 70(3), 5305–5319. https://doi.org/10.32604/cmc.2022.020344

Alavi, B., Tavana, M., & Mina, H. (2021). A dynamic decision support system for sustainable supplier selection in circular economy. Sustainable Production and Consumption, 27, 905–920. https://doi.org/10.1016/j.spc.2021.02.015

Alcayaga, A., Wiener, M., & Hansen, E. G. (2019). Towards a framework of smart-circular systems: An integrative literature review. Journal of Cleaner Production, 221, 622–634. https://doi.org/10.1016/j.jclepro.2019.02.085

Alhawari, O., Awan, U., Bhutta, M. K. S., & ulku, M. A. (2021). Insights from circular economy literature: A review of extant definitions and unravelling paths to future research. Sustainability, 13(2), Article 859. https://doi.org/10.3390/su13020859

Ali, Y., Jokhio, D. H., Dojki, A. A., Rehman, O. U., Khan, F., & Salman, A. (2022). Adoption of circular economy for food waste management in the context of a developing country. Waste Management & Research, 40(6), 676–684. https://doi.org/10.1177/0734242X211038198

Alimardani, M., Hashemkhani Zolfani, S., Aghdaie, M. H., & Tamosaitiene, 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. https://doi.org/10.3846/20294913.2013.814606

Antikainen, M., Uusitalo, T., & Kivikytö-Reponen, P. (2018). Digitalisation as an enabler of circular economy. Procedia CIRP, 73, 45–49. https://doi.org/10.1016/j.procir.2018.04.027

Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87–96. https://doi.org/10.1016/S0165-0114(86)80034-3

Awan, U., Sroufe, R., & Shahbaz, M. (2021). Industry 4.0 and the circular economy: A literature review and recommendations for future research. Business Strategy and the Environment, 30(4), 2038–2060. https://doi.org/10.1002/bse.2731

Bag, S., & Pretorius, J. H. C. (2022). Relationships between industry 4.0, sustainable manufacturing and circular economy: Proposal of a research framework. International Journal of Organizational Analysis, 30(4), 864–898. https://doi.org/10.1108/IJOA-04-2020-2120

Belhadi, A., Kamble, S., Gunasekaran, A., & Mani, V. (2021). Analyzing the mediating role of organizational ambidexterity and digital business transformation on industry 4.0 capabilities and sustainable supply chain performance. Supply Chain Management-an International Journal, 27(6), 696–711. https://doi.org/10.1108/SCM-04-2021-0152

Bhalaji, R. K. A., Bathrinath, S., Ponnambalam, S. G., & Saravanasankar, S. (2019). A fuzzy decision-making trial and evaluation laboratory approach to analyse risk factors related to environmental health and safety aspects in the healthcare industry. Sadhana-Academy Proceedings in Engineering Sciences, 44, Article 55. https://doi.org/10.1007/s12046-018-1050-4

Bijos, J. C. B. F., Zanta, V. M., Morato, J., Queiroz, L. M., & Oliveira-Esquerre, K. P. S. R. (2022). Improving circularity in municipal solid waste management through machine learning in Latin America and the Caribbean. Sustainable Chemistry and Pharmacy, 28, Article 100740. https://doi.org/10.1016/j.scp.2022.100740

Blanco-Mesa, F., Merigo, J. M., & Gil-Lafuente, A. M. (2017). Fuzzy decision making: A bibliometric-based review. Journal of Intelligent & Fuzzy Systems, 32(3), 2033–2050. https://doi.org/10.3233/JIFS-161640

Bui, T. D., Tsai, F. M., Tseng, M. L., Wu, K. J., & Chiu, A. S. F. (2020). Effective municipal solid waste management capability under uncertainty in vietnam: Utilizing economic efficiency and technology to foster social mobilization and environmental integrity. Journal of Cleaner Production, 259, Article 120981. https://doi.org/10.1016/j.jclepro.2020.120981

Burmaoglu, S., Gungor, D. O., Kirbac, A., & Saritas, O. (2022). Future research avenues at the nexus of circular economy and digitalization. International Journal of Productivity and Performance Management, 72(8), 2247–2269. https://doi.org/10.1108/IJPPM-01-2021-0026

Cao, Y., Qu, Y., & Guo, L. (2022). Identifying critical eco-innovation practices in circular supply chain management: Evidence from the textile and clothing industry. International Journal of Logistics-Research and Applications, 26(11), 1462–1483. https://doi.org/10.1080/13675567.2022.2076817

Cetin, S., De Wolf, C., & Bocken, N. (2021). Circular digital built environment: An emerging framework. Sustainability, 13(11), Article 6348. https://doi.org/10.3390/su13116348

Chai, J., & Ngai, E. W. T. (2020). Decision-making techniques in supplier selection: Recent accomplishments and what lies ahead. Expert Systems with Applications, 140, Article 112903. https://doi.org/10.1016/j.eswa.2019.112903

Chauhan, C., Parida, V., & Dhir, A. (2022a). Linking circular economy and digitalisation technologies: A systematic literature review of past achievements and future promises. Technological Forecasting and Social Change, 177, Article 121508. https://doi.org/10.1016/j.techfore.2022.121508

Chauhan, A., Sharma, N. K., Tayal, S., Kumar, V., & Kumar, M. (2022b). A sustainable production model for waste management with uncertain scrap and recycled material. Journal of Material Cycles and Waste Management, 24(5), 1797–1817. https://doi.org/10.1007/s10163-022-01435-4

Cheah, C. G., Chia, W. Y., Lai, S. F., Chew, K. W., Chia, S. R., & Show, P. L. (2022). Innovation designs of industry 4.0 based solid waste management: Machinery and digital circular economy. Environmental Research, 213, Article 113619. https://doi.org/10.1016/j.envres.2022.113619

Chen, Z. S., Zhang, X., Govindan, K., Wang, X. J., & Chin, K. S. (2021a). Third-party reverse logistics provider selection: A computational semantic analysis-based multi-perspective multi-attribute decision-making approach. Expert Systems with Applications, 166, Article 114051. https://doi.org/10.1016/j.eswa.2020.114051

Chen, L., Duan, D., Mishra, A. R., & Alrasheedi, M. (2022). Sustainable third-party reverse logistics provider selection to promote circular economy using new uncertain interval-valued intuitionistic fuzzy-projection model. Journal of Enterprise Information Management, 35(4/5), 955–987. https://doi.org/10.1108/JEIM-02-2021-0066

Chen, W.-K., Nalluri, V., Hung, H.-C., Chang, M.-C., & Lin, C.-T. (2021b). Apply DEMATEL to analyzing key barriers to implementing the circular economy: An application for the textile sector. Applied Sciences-Basel, 11(8), Article 3335. https://doi.org/10.3390/app11083335

Chen, Z., Ming, X., Zhang, X., Yin, D., & Sun, Z. (2019). A rough-fuzzy DEMATEL-ANP method for evaluating sustainable value requirement of product service system. Journal of Cleaner Production, 228, 485–508. https://doi.org/10.1016/j.jclepro.2019.04.145

Cui, Y., Liu, W., Rani, P., & Alrasheedi, M. (2021). Internet of Things (IoT) adoption barriers for the circular economy using Pythagorean fuzzy SWARA-CoCoSo decision-making approach in the manufacturing sector. Technological Forecasting and Social Change, 171, Article 120951. https://doi.org/10.1016/j.techfore.2021.120951

D’Amico, G., Arbolino, R., Shi, L., Yigitcanlar, T., & Ioppolo, G. (2022). Digitalisation driven urban metabolism circularity: A review and analysis of circular city initiatives. Land Use Policy, 112, Article 105819. https://doi.org/10.1016/j.landusepol.2021.105819

Dey, P. K., Malesios, C., Chowdhury, S., Saha, K., Budhwar, P., & De, D. (2022). Adoption of circular economy practices in small and medium-sized enterprises: Evidence from Europe. International Journal of Production Economics, 248, Article 108496. https://doi.org/10.1016/j.ijpe.2022.108496

Dehshiri, S. J. H., Amiri, M., Olfat, L., & Pishvaee, M. S. (2022). Multi-objective closed-loop supply chain network design: A novel robust stochastic, possibilistic, and flexible approach. Expert Systems with Applications, 206, Article 117807. https://doi.org/10.1016/j.eswa.2022.117807

Dolatabad, A. H., Mahdiraji, H. A., Babgohari, A. Z., Garza-Reyes, J. A., & Ai, A. (2022). Analyzing the key performance indicators of circular supply chains by hybrid fuzzy cognitive mapping and fuzzy dematel: Evidence from healthcare sector. Environment Development and Sustainability. https://doi.org/10.1007/s10668-022-02535-9

Dwivedi, A., & Paul, S. K. (2022). A framework for digital supply chains in the era of circular economy: Implications on environmental sustainability. Business Strategy and the Environment, 31(4), 1249–1274. https://doi.org/10.1002/bse.2953

Ecer, F., & Torkayesh, A. E. (2022). A stratified fuzzy decision-making approach for sustainable circular supplier selection. IEEE Transactions on Engineering Management, 71, 1130–1144. https://doi.org/10.1109/TEM.2022.3151491

Enyoghasi, C., & Badurdeen, F. (2021). Industry 4.0 for sustainable manufacturing: Opportunities at the product, process, and system levels. Resources Conservation and Recycling, 166, Article 105362. https://doi.org/10.1016/j.resconrec.2020.105362

Erol, I., Ar, I. M., Peker, I., & Searcy, C. (2022). Alleviating the impact of the barriers to circular economy adoption through blockchain: An investigation using an integrated MCDM-based QFD with hesitant fuzzy linguistic term sets. Computers & Industrial Engineering, 165, Article 107962. https://doi.org/10.1016/j.cie.2022.107962

Erol, I., Peker, I., Ar, I. M., Turan, I., & Searcy, C. (2021). Towards a circular economy: Investigating the critical success factors for a blockchain-based solar photovoltaic energy ecosystem in Turkey. Energy for Sustainable Development, 65, 130–143. https://doi.org/10.1016/j.esd.2021.10.004

Farooque, M., Zhang, A., & Liu, Y. P. (2019). Barriers to circular food supply chains in China. Supply Chain Management-an International Journal, 24(5), 677–696. https://doi.org/10.1108/SCM-10-2018-0345

Firoiu, D., Ionescu, G. H., Pirvu, R., Badircea, R., & Patrichi, I. C. (2022). Achievement of the sustainable development goals (sdg) in portugal and forecast of key indicators until 2030. Technological and Economic Development of Economy, 28(6), 1649–1683. https://doi.org/10.3846/tede.2022.17645

Fu, Y.-K., & Liao, C.-N. (2023). A hybrid evaluation approach using fuzzy topsis and msgp for catering food reverse logistics provider selection in airline industry. International Journal of Shipping and Transport Logistics, 16(1–2), 1–18. https://doi.org/10.1504/IJSTL.2023.128547

Fraga-Lamas, P., Lopes, S. I., & Fernandez-Carames, T. M. (2021). Green IoT and edge AI as key technological enablers for a sustainable digital transition towards a smart circular economy: An Industry 5.0 use case. Sensors, 21(17), Article 5745. https://doi.org/10.3390/s21175745

Gebhardt, M., Spieske, A., & Birkel, H. (2022). The future of the circular economy and its effect on supply chain dependencies: Empirical evidence from a Delphi study. Transportation Research Part E-Logistics and Transportation Review, 157, Article 102570. https://doi.org/10.1016/j.tre.2021.102570

Gedam, V. V., Raut, R. D., Jabbour, A. B. L. d. S., Tanksale, A. N., & Narkhede, B. E. (2021). Circular economy practices in a developing economy: Barriers to be defeated. Journal of Cleaner Production, 311, Article 127670. https://doi.org/10.1016/j.jclepro.2021.127670

Genovese, A., Acquaye, A. A., Figueroa, A., & Koh, S. C. L. (2017). Sustainable supply chain management and the transition towards a circular economy: Evidence and some applications. Omega-International Journal of Management Science, 66, 344–357. https://doi.org/10.1016/j.omega.2015.05.015

Geissdoerfer, M., Savaget, P., Bocken, N. M. P., & Hultink, E. J. (2017). The circular economy a new sustainability paradigm? Journal of Cleaner Production, 143, 757–768. https://doi.org/10.1016/j.jclepro.2016.12.048

Gholami, H., Hashemi, A., Lee, J. K. Y., Abdul-Nour, G., & Salameh, A. A. (2022). Scrutinizing state-of-the-art i4.0 technologies toward sustainable products development under fuzzy environment. Journal of Cleaner Production, 377, Article 134327. https://doi.org/10.1016/j.jclepro.2022.134327

Gholami, H., Jamil, N., Zakuan, N., Saman, M. Z. M., Sharif, S., Awang, S. R., & Sulaiman, Z. (2019). Social value stream mapping (socio-vsm): Methodology to societal sustainability visualization and assessment in the manufacturing system. IEEE Access, 7, 131638–131648. https://doi.org/10.1109/ACCESS.2019.2940957

Ghobakhloo, M. (2020). Industry 4.0, digitization, and opportunities for sustainability. Journal of Cleaner Production, 252, Article 119869. https://doi.org/10.1016/j.jclepro.2019.119869

Gil-Lamata, M., & Pilar Latorre-Martinez, M. (2022). The circular economy and sustainability: A systematic literature review. Cuadernos De Gestion, 22(1), 129–142. https://doi.org/10.5295/cdg.211492mg

Gou, X. J., Liao, H. C., Xu, Z. S., & Herrera, F. (2017). Double hierarchy hesitant fuzzy linguistic term set and MULTIMOORA method: A case of study to evaluate the implementation status of haze controlling measures. Information Fusion, 38, 22–34. https://doi.org/10.1016/j.inffus.2017.02.008

Gou, X. J., Liao, H. C., Xu, Z. S., & Herrera, F. (2021a). Probabilistic double hierarchy linguistic term set and its use in designing an improved VIKOR method: The application in smart healthcare. Journal of the Operational Research Society, 72(12), 2611–2630. https://doi.org/10.1080/01605682.2020.1806741

Gou, X. J., Xu, X. R., Deng, F. M., Zhou, W., & Herrera-Viedma, E. (2023). Medical health resources allocation evaluation in public health emergencies by an improved ORESTE method with linguistic preference orderings. Fuzzy Optimization and Decision Making. https://doi.org/10.1007/s10700-023-09409-3

Gou, X. J., Xu, Z. S., Liao, H. C., & Herrera, F. (2021b). Consensus model handling minority opinions and noncooperative behaviors in large-scale group decision-making under double hierarchy linguistic preference relations. IEEE Transactions on Cybernetics, 51(1), 283–296. https://doi.org/10.1109/TCYB.2020.2985069

Govindan, K., & Hasanagic, M. (2018). A systematic review on drivers, barriers, and practices towards circular economy: A supply chain perspective. International Journal of Production Research, 56(1–2), 278–311. https://doi.org/10.1080/00207543.2017.1402141

Govindan, K., Nasr, A. K., Karimi, F., & Mina, H. (2022). Circular economy adoption barriers: An extended fuzzy best-worst method using fuzzy DEMATEL and Supermatrix structure. Business Strategy and the Environment, 31(4), 1566–1586. https://doi.org/10.1002/bse.2970

Goyal, S., Luthra, S., & Garg, D. (2022). Shifting systematically towards sustainable consumption and production: A solution framework to overcome the impacts of Covid-19. International Journal of Information Technology & Decision Making, 21(03), 933–968. https://doi.org/10.1142/S0219622022500043

Hassan, M. S., Ali, Y., Petrillo, A., & De Felice, F. (2023). Risk assessment of circular economy practices in construction industry of Pakistan. Science of the Total Environment, 868, Article 161418. https://doi.org/10.1016/j.scitotenv.2023.161418

Hu, Y., Al-Barakati, A., & Rani, P. (2022). Investigating the internet-of-things (iot) risks for supply chain management using q-rung orthopair fuzzy-swara-aras framework. Technological and Economic Development of Economy. https://doi.org/10.3846/tede.2022.16583

Ingemarsdotter, E., Jamsin, E., & Balkenende, R. (2020). Opportunities and challenges in IoT-enabled circular business model implementation – A case study. Resources Conservation and Recycling, 162, Article 105047. https://doi.org/10.1016/j.resconrec.2020.105047

Jun, X., & Soc, I. C. (2009). Model of cluster green supply chain performance evaluation based on circular economy. In The 2nd International Conference on Intelligent Computation Technology and Automation, Changsha, Peoples R China. IEEE. https://doi.org/10.1109/ICICTA.2009.692

Kannan, D. (2018). Role of multiple stakeholders and the critical success factor theory for the sustainable supplier selection process. International Journal of Production Economics, 195, 391–418. https://doi.org/10.1016/j.ijpe.2017.02.020

Kannan, D., Mina, H., Nosrati-Abarghooee, S., & Khosrojerdi, G. (2020). Sustainable circular supplier selection: A novel hybrid approach. Science of the Total Environment, 722, Article 137936. https://doi.org/10.1016/j.scitotenv.2020.137936

Karuppiah, K., Sankaranarayanan, B., Ali, S. M., Jabbour, C. J. C., & Bhalaji, R. K. A. (2021). Inhibitors to circular economy practices in the leather industry using an integrated approach: Implications for sustainable development goals in emerging economies. Sustainable Production and Consumption, 27, 1554–1568. https://doi.org/10.1016/j.spc.2021.03.015

Karuppiah, K., Sankaranarayanan, B., D’Adamo, I., & Ali, S. M. (2022). Evaluation of key factors for industry 4.0 technologies adoption in small and medium enterprises (SMEs): An emerging economy context. Journal of Asia Business Studies, 17(2), 347–370. https://doi.org/10.1108/JABS-05-2021-0202

Kartsonakis, S., Grigoroudis, E., & Neofytou, M. (2017). Supplier selection and evaluation using multicriteria decision analysis. In A. Theodoridis, A. Ragkos, & M. Salampasis (Eds.), Innovative Approaches and Applications for Sustainable Rural Development. HAICTA 2017 (pp. 187–204). Springer. https://doi.org/10.1007/978-3-030-02312-6_11

Kaya, I., Colak, M., & Terzi, F. (2019). A comprehensive review of fuzzy multi criteria decision making methodologies for energy policy making. Energy Strategy Reviews, 24, 207–228. https://doi.org/10.1016/j.esr.2019.03.003

Kayikci, Y., Gozacan-Chase, N., Rejeb, A., & Mathiyazhagan, K. (2022). Critical success factors for implementing blockchain-based circular supply chain. Business Strategy and the Environment, 31(7), 3595–3615. https://doi.org/10.1002/bse.3110

Kazancoglu, Y., Ozkan-Ozen, Y. D., Mangla, S. K., & Ram, M. (2022). Risk assessment for sustainability in e-waste recycling in circular economy. Clean Technologies and Environmental Policy, 24(4), 1145–1157. https://doi.org/10.1007/s10098-020-01901-3

Kazancoglu, Y., Ozkan-Ozen, Y. D., Sagnak, M., Kazancoglu, I., & Dora, M. (2021a). Framework for a sustainable supply chain to overcome risks in transition to a circular economy through Industry 4.0. Production Planning & Control, 34(10), 902–917. https://doi.org/10.1080/09537287.2021.1980910

Kazancoglu, Y., Sagnak, M., Mangla, S. K., Sezer, M. D., & Pala, M. O. (2021b). A fuzzy based hybrid decision framework to circularity in dairy supply chains through big data solutions. Technological Forecasting and Social Change, 170, Article 120927. https://doi.org/10.1016/j.techfore.2021.120927

Kerin, M., & Pham Duc, T. (2020). Smart remanufacturing: a review and research framework. Journal of Manufacturing Technology Management, 31(6), 1205–1235. https://doi.org/10.1108/JMTM-06-2019-0205

Keshavarz Ghorabaee, M., Amiri, M., Olfat, L., & Khatami Firouzabadi, S. M. A. (2017). Designing a multi-product multi-period supply chain network with reverse logistics and multiple objectives under uncertainty. Technological and Economic Development of Economy, 23(3), 520–548. https://doi.org/10.3846/20294913.2017.1312630

Khan, F., & Ali, Y. (2022). A facilitating framework for a developing country to adopt smart waste management in the context of circular economy. Environmental Science and Pollution Research, 29(18), 26336–26351. https://doi.org/10.1007/s11356-021-17573-5

Khan, S. A. R., Yu, Z., Sarwat, S., Godil, D. I., Amin, S., & Shujaat, S. (2022). The role of block chain technology in circular economy practices to improve organisational performance. International Journal of Logistics-Research and Applications, 25(4–5), 605–622. https://doi.org/10.1080/13675567.2021.1872512

Kharola, S., Ram, M., Goyal, N., Mangla, S. K., Nautiyal, O. P., Rawat, A., Kazancoglu, Y., & Pant, D. (2022). Barriers to organic waste management in a circular economy. Journal of Cleaner Production, 362, Article 132282. https://doi.org/10.1016/j.jclepro.2022.132282

Kirchherr, J., Reike, D., & Hekkert, M. (2017). Conceptualizing the circular economy: An analysis of 114 definitions. Resources Conservation and Recycling, 127, 221–232. https://doi.org/10.1016/j.resconrec.2017.09.005

Kouhizadeh, M., Zhu, Q., & Sarkis, J. (2020). Blockchain and the circular economy: Potential tensions and critical reflections from practice. Production Planning & Control, 31(11–12), 950–966. https://doi.org/10.1080/09537287.2019.1695925

Korhonen, J., Honkasalo, A., & Seppala, J. (2018). Circular economy: The concept and its limitations. Ecological Economics, 143, 37–46. https://doi.org/10.1016/j.ecolecon.2017.06.041

Kovacic, D., & Bogataj, M. (2017). Net present value evaluation of energy production and consumption in repeated reverse logistics. Technological and Economic Development of Economy, 23(6), 877–894. https://doi.org/10.3846/20294913.2015.1065455

Krstic, M., Agnusdei, G. P., Miglietta, P. P., & Tadic, S. (2022). Evaluation of the smart reverse logistics development scenarios using a novel MCDM model. Cleaner Environmental Systems, 7, Article 100099. https://doi.org/10.1016/j.cesys.2022.100099

Krishankumar, R., Amritha, P. P., & Ravichandran, K. S. (2022). An integrated fuzzy decision model for prioritization of barriers affecting sustainability adoption within supply chains under unknown weight context. Operations Management Research, 5, 1010–1027. https://doi.org/10.1007/s12063-022-00322-3

Kunz, N., Mayers, K., & Van Wassenhove, L. N. (2018). Stakeholder views on extended producer responsibility and the circular economy. California Management Review, 60(3), 45–70. https://doi.org/10.1177/0008125617752694

Kuo, T. C., Laksanawimol, P., Aylesworth, L., Foster, S. J., & Vincent, A. C. J. (2018). Changes in the trade of bycatch species corresponding to CITES regulations: the case of dried seahorse trade in Thailand. Biodiversity and Conservation, 27(13), 3447–3468. https://doi.org/10.1007/s10531-018-1610-2

Kusi-Sarpong, S., Gupta, H., Khan, S. A., Chiappetta Jabbour, C. J., Rehman, S. T., & Kusi-Sarpong, H. (2021). Sustainable supplier selection based on industry 4.0 initiatives within the context of circular economy implementation in supply chain operations. Production Planning & Control, 34(10), 999–1019. https://doi.org/10.1080/09537287.2021.1980906

Lahane, S., & Kant, R. (2021). A hybrid Pythagorean fuzzy AHP – CoCoSo framework to rank the performance outcomes of circular supply chain due to adoption of its enablers. Waste Management, 130, 48–60. https://doi.org/10.1016/j.wasman.2021.05.013

Lahti, T., Wincent, J., & Parida, V. (2018). A definition and theoretical review of the circular economy, value creation, and sustainable business models: Where are we now and where should research move in the future? Sustainability, 10(8), Article 2799. https://doi.org/10.3390/su10082799

Liang, W. Z., Zhao, G. Y., & Hong, C. S. (2018). Performance assessment of circular economy for phosphorus chemical firms based on vikor-qualiflex method. Journal of Cleaner Production, 196: 1365-1378. https://doi.org/10.1016/j.jclepro.2018.06.147

Liu, L., & Mishra, A. R. (2022). Enabling technologies challenges of green Internet of things (iot) towards sustainable development in the era of industry 4.0. Technological and Economic Development of Economy. https://doi.org/10.3846/tede.2022.16520

Liu, P., Zhu, B., & Wang, P. (2021a). A weighting model based on best-worst method and its application for environmental performance evaluation. Applied Soft Computing, 103, Article 107168. https://doi.org/10.1016/j.asoc.2021.107168

Liu, Y. P., Wood, L. C., Venkatesh, V. G., Zhang, A. B., & Farooque, M. (2021b). Barriers to sustainable food consumption and production in China: A fuzzy dematel analysis from a circular economy perspective. Sustainable Production and Consumption, 28, 1114–1129. https://doi.org/10.1016/j.spc.2021.07.028

Lopes de Sousa Jabbour, A. B., Chiappetta Jabbour, C. J., Godinho Filho, M., & Roubaud, D. (2018). Industry 4.0 and the circular economy: A proposed research agenda and original roadmap for sustainable operations. Annals of Operations Research, 270(1–2), 273–286. https://doi.org/10.1007/s10479-018-2772-8

Lu, J., Zhang, S., Wu, J., & Wei, Y. (2021). Copras method for multiple attribute group decision making under picture fuzzy environment and their application to green supplier selection. Technological and Economic Development of Economy, 27(2), 369–385. https://doi.org/10.3846/tede.2021.14211

Luo, C., Ju, Y., Gonzalez, E. D. R. S., Dong, P., & Wang, A. (2020). The waste-to-energy incineration plant site selection based on hesitant fuzzy linguistic Best-Worst method ANP and double parameters TOPSIS approach: A case study in China. Energy, 211, Article 118564. https://doi.org/10.1016/j.energy.2020.118564

Luthra, S., Sharma, M., Kumar, A., Joshi, S., Collins, E., & Mangla, S. (2022). Overcoming barriers to cross-sector collaboration in circular supply chain management: a multi-method approach. Transportation Research Part E-Logistics and Transportation Review, 157, Article 102582. https://doi.org/10.1016/j.tre.2021.102582

Mahpour, A. (2018). Prioritizing barriers to adopt circular economy in construction and demolition waste management. Resources Conservation and Recycling, 134, 216–227. https://doi.org/10.1016/j.resconrec.2018.01.026

Mangla, S. K., Luthra, S., Mishra, N., Singh, A., Rana, N. P., Dora, M., & Dwivedi, Y. (2018). Barriers to effective circular supply chain management in a developing country context. Production Planning & Control, 29(6), 551–569. https://doi.org/10.1080/09537287.2018.1449265

Mastrocinque, E., Javier Ramirez, F., Honrubia-Escribano, A., & Pham, D. T. (2022). Industry 4.0 enabling sustainable supply chain development in the renewable energy sector: A multi-criteria intelligent approach. Technological Forecasting and Social Change, 182, Article 121813. https://doi.org/10.1016/j.techfore.2022.121813

Millar, N., McLaughlin, E., & Borger, T. (2019). The circular economy: Swings and roundabouts? Ecological Economics, 158, 11–19. https://doi.org/10.1016/j.ecolecon.2018.12.012

Min, Z., Sawang, S., & Kivits, R. A. (2021). Proposing circular economy ecosystem for Chinese SMEs: A systematic review. International Journal of Environmental Research and Public Health, 18(5), Article 2395. https://doi.org/10.3390/ijerph18052395

Mirzynska, A., Kosch, O., Schieg, M., Suhajda, K., & Szarucki, M. (2021). Exploring concomitant concepts in the discussion on the circular economy: a bibliometric analysis of web of science, scopus and twitter. Technological and Economic Development of Economy, 27(6), 1539–1562. https://doi.org/10.3846/tede.2021.15801

Mohammadian, A., Dahooie, J. H., Qorbani, A. R., Zavadskas, E. K., & Turskis, Z. (2021). A new multi-attribute decision-making framework for policy-makers by using interval-valued triangular fuzzy numbers. Informatica, 32(3), 583–618. https://doi.org/10.15388/21-INFOR448

Modgil, S., Gupta, S., Sivarajah, U., & Bhushan, B. (2021). Big data-enabled large-scale group decision making for circular economy: An emerging market context. Technological Forecasting and Social Change, 166, Article 120607. https://doi.org/10.1016/j.techfore.2021.120607

Mukherjee, S., Nagariya, R., Baral, M. M., Patel, B. S., Chittipaka, V., Rao, K. S., & Rao, U. V. A. (2022). Blockchain-based circular economy for achieving environmental sustainability in the Indian electronic MSMEs. Management of Environmental Quality, 34(4), 997–1017. https://doi.org/10.1108/MEQ-03-2022-0045

Nag, U., Sharma, S. K., & Padhi, S. S. (2022). Evaluating value requirement for industrial product-service system in circular economy for wind power-based renewable energy firms. Journal of Cleaner Production, 340, Article 130689. https://doi.org/10.1016/j.jclepro.2022.130689

Nara, E. O. B., da Costa, M. B., Baierle, I. C., Schaefer, J. L., Benitez, G. B., do Santos, L., & Benitez, L. B. (2021). Expected impact of industry 4.0 technologies on sustainable development: A study in the context of Brazil’s plastic industry. Sustainable Production and Consumption, 25, 102–122. https://doi.org/10.1016/j.spc.2020.07.018

Nikseresht, A., Hajipour, B., Pishva, N., & Mohammadi, H. A. (2022). Using artificial intelligence to make sustainable development decisions considering VUCA: a systematic literature review and bibliometric analysis. Environmental Science and Pollution Research, 29(28), 42509–42538. https://doi.org/10.1007/s11356-022-19863-y

Omerali, M., & Kaya, T. (2020). Should firms investigating in TOT domain buy or implement in their Industry 4.0 initiatives? An application of Type-2 Fuzzy COPRAS. Journal of Intelligent & Fuzzy Systems, 39(5), 6539–6552. https://doi.org/10.3233/jifs-189117

Ozkan-Ozen, Y. D., Kazancoglu, Y., & Mangla, S. K. (2020). Synchronized barriers for circular supply chains in industry 3.5/industry 4.0 transition for sustainable resource management. Resources Conservation and Recycling, 161, Article 104986. https://doi.org/10.1016/j.resconrec.2020.104986

Pan, X., Wong, C. W. Y., & Li, C. (2022). Circular economy practices in the waste electrical and electronic equipment (WEEE) industry: A systematic review and future research agendas. Journal of Cleaner Production, 365, Article 132671. https://doi.org/10.1016/j.jclepro.2022.132671

Pappas, N., Caputo, A., Pellegrini, M. M., Marzi, G., & Michopoulou, E. (2021). The complexity of decision-making processes and IoT adoption in accommodation SMEs. Journal of Business Research, 131, 573–583. https://doi.org/10.1016/j.jbusres.2021.01.010

Percin, S. (2022). Evaluating the circular economy-based big data analytics capabilities of circular agri-food supply chains: The context of Turkey. Environmental Science and Pollution Research, 29, 83220–83233. https://doi.org/10.1007/s11356-022-21680-2

Percin, S. (2023). Identifying barriers to big data analytics adoption in circular agri-food supply chains: A case study in turkey. Environmental Science and Pollution Research, 30, 52304–52320. https://doi.org/10.1007/s11356-023-26091-5

Persis, D. J., Venkatesh, V. G., Sreedharan, V. R., Shi, Y. Y., & Sankaranarayanan, B. (2021). Modelling and analysing the impact of Circular Economy; Internet of Things and ethical business practices in the VUCA world: Evidence from the food processing industry. Journal of Cleaner Production, 301, Article 126871. https://doi.org/10.1016/j.jclepro.2021.126871

Peng, X., Krishankumar, R., & Ravichandran, K. S. (2021). A novel interval-valued fuzzy soft decision-making method based on cocoso and critic for intelligent healthcare management evaluation. Soft Computing, 25(6), 4213–4241. https://doi.org/10.1007/s00500-020-05437-y

Priyadarshini, J., Singh, R. K., Mishra, R., & Kamal, M. M. (2022). Adoption of additive manufacturing for sustainable operations in the era of circular economy: Self-assessment framework with case illustration. Computers & Industrial Engineering, 171, Article 108514. https://doi.org/10.1016/j.cie.2022.108514

Raut, R. D., Mangla, S. K., Narwane, V. S., Gardas, B. B., Priyadarshinee, P., & Narkhede, B. E. (2019). Linking big data analytics and operational sustainability practices for sustainable business management. Journal of Cleaner Production, 224, 10–24. https://doi.org/10.1016/j.jclepro.2019.03.181

Rehman, O. U., Ali, Y., & Sabir, M. (2022). Risk assessment and mitigation for electric power sectors: A developing country’s perspective. International Journal of Critical Infrastructure Protection, 36, Article 100507. https://doi.org/10.1016/j.ijcip.2021.100507

Rejeb, A., Rejeb, K., Keogh, J. G., & Zailani, S. (2022). Barriers to blockchain adoption in the circular economy: a fuzzy Delphi and Best-Worst approach. Sustainability, 14(6), Article 3611. https://doi.org/10.3390/su14063611

Ren, X. S. (2009). Evaluation on the enterprise performance based on the circular economy [Conference presentation]. International Conference on Management of Technology, Taiyuan, Peoples R China.

Rosa, P., Sassanelli, C., Urbinati, A., Chiaroni, D., & Terzi, S. (2020). Assessing relations between circular economy and Industry 4.0: a systematic literature review. International Journal of Production Research, 58(6), 1662–1687. https://doi.org/10.1080/00207543.2019.1680896

Rusch, M., Schoeggl, J.-P., & Baumgartner, R. J. (2022). Application of digital technologies for sustainable product management in a circular economy: A review. Business Strategy and the Environment. https://doi.org/10.1002/bse.3099

Rymaszewska, A., Helo, P., & Gunasekaran, A. (2017). IoT powered servitization of manufacturing – an exploratory case study. International Journal of Production Economics, 192, 92–105. https://doi.org/10.1016/j.ijpe.2017.02.016

Sassanelli, C., Rosa, P., Rocca, R., & Terzi, S. (2019). Circular economy performance assessment methods: A systematic literature review. Journal of Cleaner Production, 229, 440–453. https://doi.org/10.1016/j.jclepro.2019.05.019

Sadhukhan, J., Martinez-Hernandez, E., Murphy, R. J., Ng, D. K. S., Hassim, M. H., Ng, K. S., Kin, W. Y., Jaye, I. F. M., Hang, M., & Andiappan, V. (2018). Role of bioenergy, biorefinery and bioeconomy in sustainable development: Strategic pathways for malaysia. Renewable & Sustainable Energy Reviews, 81, 1966–1987. https://doi.org/10.1016/j.rser.2017.06.007

Sharma, M., Joshi, S., Prasad, M., & Bartwal, S. (2023). Overcoming barriers to circular economy implementation in the oil & gas industry: Environmental and social implications. Journal of Cleaner Production, 391, Article 136133. https://doi.org/10.1016/j.jclepro.2023.136133

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, 35(4/5), 1100–1128. https://doi.org/10.1108/JEIM-09-2021-0396

Shen, K.-w., Li, L., & Wang, J.-Q. (2020). Circular economy model for recycling waste resources under government participation: A case study in industrial waste water circulation in China. Technological and Economic Development of Economy, 26(1), 21–47. https://doi.org/10.3846/tede.2019.11249

Shen, K.-w., & Wang, J.-q. (2018). Z-vikor method based on a new comprehensive weighted distance measure of Z-number and its application. IEEE Transactions on Fuzzy Systems, 26(6), 3232–3245. https://doi.org/10.1109/TFUZZ.2018.2816581

Simsek, E., Demirel, Y. E., Ozturk, E., & Kitis, M. (2022). Use of multi-criteria decision models for optimization of selecting the most appropriate best available techniques in cleaner production applications: A case study in a textile industry. Journal of Cleaner Production, 335, Article 130311. https://doi.org/10.1016/j.jclepro.2021.130311

Sun, X., & Wang, X. (2022). Modeling and analyzing the impact of the Internet of Things-based Industry 4.0 on circular economy practices for sustainable development: Evidence from the food processing industry of China. Frontiers in Psychology, 13, Article 866361. https://doi.org/10.3389/fpsyg.2022.866361

Sun, Z., Ma, Z., Ma, M., Cai, W., Xiang, X., Zhang, S., Chen, M., & Chen, L. (2022). Carbon peak and carbon neutrality in the building sector: A bibliometric review. Buildings, 12(2), Article 128. https://doi.org/10.3390/buildings12020128

Tamasiga, P., Miri, T., Onyeaka, H., & Hart, A. (2022). Food waste and Circular Economy: Challenges and opportunities. Sustainability, 14(16), Article 9896. https://doi.org/10.3390/su14169896

Tan, J., Tan, F. J., & Ramakrishna, S. (2022). Transitioning to a Circular Economy: A systematic review of its drivers and barriers. Sustainability, 14(3), Article 1757. https://doi.org/10.3390/su14031757

Tang, M., & Liao, H. (2021). Multi-attribute large-scale group decision making with data mining and subgroup leaders: An application to the development of the circular economy. Technological Forecasting and Social Change, 167, Article 120719. https://doi.org/10.1016/j.techfore.2021.120719

Tanveer, M., Khan, S. A. R., Umar, M., Yu, Z., Sajid, M. J., & Haq, I. U. (2022). Waste management and green technology: Future trends in circular economy leading towards environmental sustainability. Environmental Science and Pollution Research International, 29, 80161–80178. https://doi.org/10.1007/s11356-022-23238-8

Thavi, R. R., Narwane, V. S., Jhaveri, R. H., & Raut, R. D. (2021). To determine the critical factors for the adoption of cloud computing in the educational sector in developing countries – a fuzzy DEMATEL approach. Kybernetes, 51(11), 3340–3365. https://doi.org/10.1108/K-12-2020-0864

Theeraworawit, M., Suriyankietkaew, S., & Hallinger, P. (2022). Sustainable supply chain management in a Circular Economy: A bibliometric review. Sustainability, 14(15), Article 9304. https://doi.org/10.3390/su14159304

Toker, K., & Gorener, A. (2023). Evaluation of circular economy business models for SMEs using spherical fuzzy TOPSIS: An application from a developing countries’ perspective. Environment Development and Sustainability, 25, 1700–1741. https://doi.org/10.1007/s10668-022-02119-7

Torra, V. (2010). Hesitant fuzzy sets. International Journal of Intelligent Systems, 25(6), 529–539. https://doi.org/10.1002/int.20418

Torgul, B., & Paksoy, T. (2022). Multi-level competitive closed loop supply chain network design. Journal of Polytechnic-Politeknik Dergisi. https://doi.org/10.2339/politeknik.1005387

Tsai, F. M., Bui, T. D., Tseng, M. L., Lim, M. K., & Hu, J. Y. (2020). Municipal solid waste management in a circular economy: A data-driven bibliometric analysis. Journal of Cleaner Production, 275, Article 124132. https://doi.org/10.1016/j.jclepro.2020.124132

Tseng, M.-L., Ha, H. M., Wu, K.-J., & Xue, B. (2022a). Healthcare industry circular supply chain collaboration in vietnam: Vision and learning influences on connection in a circular supply chain and circularity business model. International Journal of Logistics-Research and Applications, 25(4–5), 743–768. https://doi.org/10.1080/13675567.2021.1923671

Tseng, M. L., Bui, T. D., Lim, M. K., & Lewi, S. (2021a). A cause and effect model for digital sustainable supply chain competitiveness under uncertainties: Enhancing digital platform. Sustainability, 13(18), Article 10150. https://doi.org/10.3390/su131810150

Tseng, M. L., Ha, H. M., Tran, T. P. T., Bui, T. D., Chen, C. C., & Lin, C. W. (2022b). Building a data-driven circular supply chain hierarchical structure: Resource recovery implementation drives circular business strategy. Business Strategy and the Environment, 31(5), 2082–2106. https://doi.org/10.1002/bse.3009

Tseng, M.-L., Tran, T. P. T., Ha, H. M., Bui, T.-D., & Lim, M. K. (2021b). Sustainable industrial and operation engineering trends and challenges Toward Industry 4.0: a data driven analysis. Journal of Industrial and Production Engineering, 38(8), 581–598. https://doi.org/10.1080/21681015.2021.1950227

Tseng, M.-L., Thi Phuong Thuy, T., Wu, K.-J., Xue, B., & Chen, X. (2021c). Causality seafood processing circular supply chain capabilities in qualitative data analytics. Industrial Management & Data Systems, 121(12), 2760–2784. https://doi.org/10.1108/IMDS-06-2021-0357

Tsolakis, N., Niedenzu, D., Simonetto, M., Dora, M., & Kumar, M. (2021). Supply network design to address United Nations Sustainable Development Goals: A case study of blockchain implementation in Thai fish industry. Journal of Business Research, 131, 495–519. https://doi.org/10.1016/j.jbusres.2020.08.003

Urbinati, A., Chiaroni, D., & Chiesa, V. (2017). Towards a new taxonomy of circular economy business models. Journal of Cleaner Production, 168, 487–498. https://doi.org/10.1016/j.jclepro.2017.09.047

van Eck, N. J., & Waltman, L. (2010). Software survey: Vosviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3

Vatansever, K., Akarsu, H., & Kazancoglu, Y. (2021). Evaluation of transition barriers to circular economy: A case from the tourism industry. International Journal of Mathematical Engineering and Management Sciences, 6(3), 824–846. https://doi.org/10.33889/IJMEMS.2021.6.3.049

Wan, X., Teng, Z., Zhang, Z., Liu, X., & Du, Z. (2023). Equity financing risk assessment based on plts-er approach in marine ranching from the ecological and circular economy perspectives. Annals of Operations Research. https://doi.org/10.1007/s10479-023-05222-8

Wang, H., Zhang, F., & Ullah, K. (2022). Waste clothing recycling channel selection using a COCOSO-D method based on sine trigonometric interaction operational laws with pythagorean fuzzy information. Energies, 15(6), Article 2010. https://doi.org/10.3390/en15062010

Wang, Q., Lu, S., Yuan, X., Zuo, J., Zhang, J., & Hong, J. (2017). The index system for project selection in ecological industrial park: A China study. Ecological Indicators, 77, 267–275. https://doi.org/10.1016/j.ecolind.2017.01.032

Wang, S., Lei, L., & Xing, L. (2021). Urban circular economy performance evaluation: A novel fully fuzzy data envelopment analysis with large datasets. Journal of Cleaner Production, 324, Article 129214. https://doi.org/10.1016/j.jclepro.2021.129214

Wang, Y.-L., & Liao, C.-N. (2023). Assessment of sustainable reverse logistic provider using the fuzzy topsis and MSGP framework in food industry. Sustainability, 15(5), Article 4305. https://doi.org/10.3390/su15054305

Weglarz, A., & Gilewski, P. (2021). Risk analysis in the environmental impact assessment of building construction innovations. Archives of Civil Engineering, 67(4), 433–450. https://doi.org/10.24425/ace.2021.138510

Wei, G., Wei, C., & Guo, Y. (2021). EDAS method for probabilistic linguistic multiple attribute group decision making and their application to green supplier selection. Soft Computing, 25, 9045–9053. https://doi.org/10.1007/s00500-021-05842-x

Xu, X., Gou, X., Zhang, W., Zhao, Y., & Xu, Z. (2023). A bibliometric analysis of carbon neutrality: Research hotspots and future directions. Heliyon, 9(8), Article e18763. https://doi.org/10.1016/j.heliyon.2023.e18763

Xin, L., Lang, S., & Mishra, A. R. (2022). Evaluate the challenges of sustainable supply chain 4.0 implementation under the circular economy concept using new decision making approach. Operations Management Research, 15, 773–792. https://doi.org/10.1007/s12063-021-00243-7

Yadav, H., Soni, U., & Kumar, G. (2021). Analysing challenges to smart waste management for a sustainable circular economy in developing countries: a fuzzy DEMATEL study. Smart and Sustainable Built Environment. https://doi.org/10.1108/SASBE-06-2021-0097

Yadav, G., Luthra, S., Huisingh, D., Mangla, S. K., Narkhede, B. E., & Liu, Y. (2020). Development of a lean manufacturing framework to enhance its adoption within manufacturing companies in developing economies. Journal of Cleaner Production, 245, Article 118726. https://doi.org/10.1016/j.jclepro.2019.118726

Yang, Z. K., & Li, J. (2010). Assessment of green supply chain risk based on circular economy. In Proceedings –2010 IEEE 17th International Conference on Industrial Engineering and Engineering Management, IE and EM2010. IEEE. https://doi.org/10.1109/ICIEEM.2010.5645996

Yıldızbaşı, A., Öztürk, C., Yılmaz, İ., & Arıöz, Y. (2022). Key challenges of lithium-ion battery recycling process in circular economy environment: Pythagorean fuzzy ahp approach. Lecture Notes in Networks and Systems, 308, 561–568. https://doi.org/10.1007/978-3-030-85577-2_66

Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X

Zadeh, L. A. (1975). Concept of a linguistic variable and its application to approximate reasoning-1. Information Sciences, 8(3), 199–249. https://doi.org/10.1016/0020-0255(75)90036-5

Zhang, A., Venkatesh, V. G., Liu, Y., Wan, M., Qu, T., & Huisingh, D. (2019). Barriers to smart waste management for a circular economy in china. Journal of Cleaner Production, 240(10), Article 118198. https://doi.org/10.1016/j.jclepro.2019.118198

Zhang, A., Venkatesh, V. G., Wang, J. X., Mani, V., Wan, M., & Qu, T. (2021a). Drivers of industry 4.0-enabled smart waste management in supply chain operations: a circular economy perspective in china. Production Planning & Control, 34(10), 870–886. https://doi.org/10.1080/09537287.2021.1980909

Zhang, X., Li, Z., & Wang, Y. (2020). A review of the criteria and methods of reverse logistics supplier selection. Processes, 8(6), Article 705. https://doi.org/10.3390/pr8060705

Zhang, Y., Ge, L., Xiao, L., Zhang, M., & Liu, S. (2021b). A bibliometric review of information systems research from 1975–2018: Setting an agenda for is research. Journal of Global Information Management, 29(6), Article 287631. https://doi.org/10.4018/JGIM.287631

Zhao, H. R., Zhao, H. R., & Guo, S. (2017). Evaluating the comprehensive benefit of eco-industrial parks by employing multi-criteria decision making approach for circular economy. Journal of Cleaner Production, 142, 2262–2276. https://doi.org/10.1016/j.jclepro.2016.11.041

Zhao, L., Zhao, S., & Gao, S. (2012). Based on fuzzy math method to evaluate of reverse logistics of waste automobiles [Conference presentation]. 3rd International Conference on Manufacturing Science and Engineering (ICMSE 2012), Xiamen, Peoples R China.

Zheng, F. Y. (2010). Comprehensive evaluation on the total performance of modern logistics enterprises based on circular-economy [Conference presentation]. International Conference on Management Sci and Engineering, SW Univ Nationalities, Chengdu, Peoples R China.

Zhou, Z. (2012). Research on green degree evaluation of reverse logistics system based on fuzzy comprehensive evaluation method [Conference presentation]. 1st International Conference on Energy and Environmental Protection (ICEEP 2012), Hohhot, Peoples R China.