Sustainable Supplier Selection Using Fuzzy AHP (AHP-F) and Fuzzy ARAS (ARAS-F) Techniques for Fertilizer Supply in the Agricultural Supply Chain
DOI:
https://doi.org/10.24925/turjaf.v12i8.1269-1280.6568Anahtar Kelimeler:
Agricultural Marketing- Supplier Selection- Fuzzy AHP- Fuzzy ARAS- MCDMÖzet
Implementing the right strategies in the agricultural supply chain in the supply of seeds, pesticides, fertilizer, energy, fuel and agricultural mechanization tools and equipment has a great role in increasing agricultural productivity. The main purpose of the study is to rank and evaluate alternatives in choosing a sustainable fertilizer supplier in the agricultural supply chain by using AHP-F and ARAS-F techniques. In an environment of uncertainty and complex supply chain structure, multi-criteria decision making (MCDM) methods are widely used to solve supplier selection problems. In this study, the importance levels and weights of the criteria in the selection of sustainable fertilizer suppliers were measured by the AHP-F method. The criteria that are important for fertilizer supplier selection were evaluated by taking expert opinions, the uncertain and uncertain opinions of the decision makers were modeled with the AHP-F approach and the weights of the criteria were determined. Among the criteria, resource consumption (FSC05) has the highest weight. Then, alternative rankings were obtained with the ARAS-F method. Fertilizer supplier alternatives in the agricultural supply chain were ranked with the ARAS-F method, using the criterion weights found with AHP-F. In the ranking of alternatives, alternative fertilizer supplier FS03 ranked first with the highest value. This study provides a resource for businesses and other stakeholders to make decisions regarding sustainable fertilizer supplier selection.
Referanslar
Abdel-Baset, M., Chang, V., Gamal, A., & Smarandache, F. (2019a). An integrated neutrosophic ANP and VIKOR method for achieving sustainable supplier selection: A case study in importing field. Computers in Industry, 106, 94-110. https://doi.org/10.1016/j.compind.2018.12.017
Abdel-Basset, M., Manogaran, G., Gamal, A., & Smarandache, F. (2018). A hybrid approach of neutrosophic sets and DEMATEL method for developing supplier selection criteria. Design Automation for Embedded Systems, 22, 257-278. https://doi.org/10.1007/s10617-018-9203-6
Abdel-Basset, M., Saleh, M., Gamal, A., & Smarandache, F. (2019b). An approach of TOPSIS technique for developing supplier selection with group decision making under type-2 neutrosophic number. Applied Soft Computing, 77, 438-452. https://doi.org/10.1016/j.asoc.2019.01.035
Ahmadi, H. B., Kusi-Sarpong, S., & Rezaei, J. (2017). Assessing the social sustainability of supply chains using Best Worst Method. Resources, Conservation and Recycling, 126, 99-106. https://doi.org/10.1016/j.resconrec.2017.07.020
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
Ali, H., Zhang, J., Liu, S., & Shoaib, M. (2023). An integrated decision-making approach for global supplier selection and order allocation to create an environment-friendly supply chain. Kybernetes, 52(8), 2649-2671. https://doi.org/10.1108/K-10-2021-1046
Atlı, H. F. (2024). Safety of agricultural machinery and tractor maintenance planning with fuzzy logic and MCDM for agricultural productivity. International Journal of Agriculture Environment and Food Sciences, 8(1), 25-43. https://doi.org/10.31015/jaefs.2024.1.4
Awasthi, A., Govindan, K., & Gold, S. (2018). Multi-tier sustainable global supplier selection using a fuzzy AHP-VIKOR based approach. International Journal of Production Economics, 195, 106-117. https://doi.org/10.1016/j.ijpe.2017.10.013
Ayaz, M., Ammad-Uddin, M., Sharif, Z., Mansour, A., & Aggoune, E. H. M. (2019). Internet-of-Things (IoT)-based smart agriculture: Toward making the fields talk. IEEE access, 7, 129551-129583. https://doi.org/10.1109/ACCESS.2019.2932609
Badi, I., & Pamucar, D. (2020). Supplier selection for steelmaking company by using combined Grey-MARCOS methods. Decision Making: Applications in Management and Engineering, 3(2), 37-48. https://doi.org/10.31181/dmame2003037b
Bag, S., & Rahman, M. S. (2023). The role of capabilities in shaping sustainable supply chain flexibility and enhancing circular economy-target performance: an empirical study. Supply Chain Management: An International Journal, 28(1), 162-178. https://doi.org/10.1108/SCM-05-2021-0246
Bag, S., Telukdarie, A., Pretorius, J. C., & Gupta, S. (2021). Industry 4.0 and supply chain sustainability: framework and future research directions. Benchmarking: An International Journal, 28(5), 1410-1450. https://doi.org/10.1108/BIJ-03-2018-0056
Bakır, M., & Atalık, Ö. (2021). Application of fuzzy AHP and fuzzy MARCOS approach for the evaluation of e-service quality in the airline industry. Decision Making: Applications in Management and Engineering, 4(1), 127-152. https://doi.org/10.31181/dmame2104127b
Baltrunaite, A., Giorgiantonio, C., Mocetti, S., & Orlando, T. (2021). Discretion and supplier selection in public procurement. The Journal of Law, Economics, and Organization, 37(1), 134-166. https://doi.org/10.1093/jleo/ewaa009
Banaeian, N., Mobli, H., Fahimnia, B., Nielsen, I. E., & Omid, M. (2018). Green supplier selection using fuzzy group decision making methods: A case study from the agri-food industry. Computers & Operations Research, 89, 337-347. https://doi.org/10.1016/j.cor.2016.02.015
Bayraç, N. H., & Doğan, E. (2016). Türkiye'de iklim değişikliğinin tarım sektörü üzerine etkileri. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 11(1), 23-48.
Buckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy sets and systems, 17(3), 233-247.
Cavalcante, I. M., Frazzon, E. M., Forcellini, F. A., & Ivanov, D. (2019). A supervised machine learning approach to data-driven simulation of resilient supplier selection in digital manufacturing. International Journal of Information Management, 49, 86-97. https://doi.org/10.1016/j.ijinfomgt.2019.03.004
Chatterjee, N., & Bose, G. (2013). Selection of vendors for wind farm under fuzzy MCDM environment. International Journal of Industrial Engineering Computations, 4(4), 535-546. http://dx.doi.org/10.5267/j.ijiec.2013.06.002
Chakraborty, S., Chattopadhyay, R., & Chakraborty, S. (2020). An integrated D-MARCOS method for supplier selection in an iron and steel industry. Decision Making: Applications in Management and Engineering, 3(2), 49-69. https://doi.org/10.31181/dmame2003049c
Chang, D. Y. (1996). Applications of the extent analysis method on fuzzy AHP. European journal of operational research, 95(3), 649-655. https://doi.org/10.1016/0377-2217(95)00300-2
Chen, C. H. (2020). A novel multi-criteria decision-making model for building material supplier selection based on entropy-AHP weighted TOPSIS. Entropy, 22(2), 259. https://doi.org/10.3390/e22020259
Chen, L., Zhao, X., Tang, O., Price, L., Zhang, S., & Zhu, W. (2017). Supply chain collaboration for sustainability: A literature review and future research agenda. International Journal of Production Economics, 194, 73-87. https://doi.org/10.1016/j.ijpe.2017.04.005
Chen, Z., Ming, X., Zhou, T., & Chang, Y. (2020). Sustainable supplier selection for smart supply chain considering internal and external uncertainty: An integrated rough-fuzzy approach. Applied Soft Computing, 87, 106004. https://doi.org/10.1016/j.asoc.2019.106004
Çalık, A. (2021). A novel Pythagorean fuzzy AHP and fuzzy TOPSIS methodology for green supplier selection in the Industry 4.0 era. Soft Computing, 25(3), 2253-2265. https://doi.org/10.1007/s00500-020-05294-9
Dahooie, J. H., Zavadskas, E. K., Abolhasani, M., Vanaki, A., & Turskis, Z. (2018). A novel approach for evaluation of projects using an interval–valued fuzzy additive ratio assessment (ARAS) method: a case study of oil and gas well drilling projects. Symmetry, 10(2), 45. https://doi.org/10.3390/sym10020045
Đalić, I., Stević, Ž., Karamasa, C., & Puška, A. (2020). A novel integrated fuzzy PIPRECIA–interval rough SAW model: Green supplier selection. Decision Making: Applications in Management and Engineering, 3(1), 126-145. https://doi.org/10.31181/dmame2003114d
Deng, H. (1999). Multicriteria analysis with fuzzy pairwise comparison. International journal of approximate reasoning, 21(3), 215-231. https://doi.org/10.1016/S0888-613X(99)00025-0
Doğan, Z., Arslan, S., & Berkman, A. (2015). Türkiye’de tarim sektörünün iktisadi gelişimi ve sorunlari: tarihsel bir bakiş. Niğde Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 8(1), 29-41.
Durmić, E., Stević, Ž., Chatterjee, P., Vasiljević, M., & Tomašević, M. (2020). Sustainable supplier selection using combined FUCOM–Rough SAW model. Reports in mechanical engineering, 1(1), 34-43. https://doi.org/10.31181/rme200101034c
Dweiri, F., Kumar, S., Khan, S. A., & Jain, V. (2016). Designing an integrated AHP based decision support system for supplier selection in automotive industry. Expert Systems with Applications, 62, 273-283. https://doi.org/10.1016/j.eswa.2016.06.030
Ecer, F., & Pamucar, D. (2020). Sustainable supplier selection: A novel integrated fuzzy best worst method (F-BWM) and fuzzy CoCoSo with Bonferroni (CoCoSo’B) multi-criteria model. Journal of cleaner production, 266, 121981. https://doi.org/10.1016/j.jclepro.2020.121981
Emrouznejad, A., & Marra, M. (2017). The state of the art development of AHP (1979–2017): A literature review with a social network analysis. International journal of production research, 55(22), 6653-6675. https://doi.org/10.1080/00207543.2017.1334976
Esmaeilian, B., Sarkis, J., Lewis, K., & Behdad, S. (2020). Blockchain for the future of sustainable supply chain management in Industry 4.0. Resources, Conservation and Recycling, 163, 105064. https://doi.org/10.1016/j.resconrec.2020.105064
Fallahpour, A., Wong, K. Y., Rajoo, S., Fathollahi-Fard, A. M., Antucheviciene, J., & Nayeri, S. (2021). An integrated approach for a sustainable supplier selection based on Industry 4.0 concept. Environmental science and pollution research, 1-19. https://doi.org/10.1007/s11356-021-17445-y
Fu, Y. K., Wu, C. J., & Liao, C. N. (2021). Selection of in-flight duty-free product suppliers using a combination fuzzy AHP, fuzzy ARAS, and MSGP methods. Mathematical Problems in Engineering, 2021, 1-13. https://doi.org/10.1155/2021/8545379
Gao, H., Ju, Y., Gonzalez, E. D. S., & Zhang, W. (2020). Green supplier selection in electronics manufacturing: An approach based on consensus decision making. Journal of Cleaner Production, 245, 118781. https://doi.org/10.1016/j.jclepro.2019.118781
Geissdoerfer, M., Morioka, S. N., de Carvalho, M. M., & Evans, S. (2018). Business models and supply chains for the circular economy. Journal of cleaner production, 190, 712-721. https://doi.org/10.1016/j.jclepro.2018.04.159
Genovese, A., Acquaye, A. A., Figueroa, A., & Koh, S. L. (2017). Sustainable supply chain management and the transition towards a circular economy: Evidence and some applications. Omega, 66, 344-357. https://doi.org/10.1016/j.omega.2015.05.015
Ghadikolaei, A. S., & Esbouei, S. K. (2014). Integrating FAHP and Fuzzy ARAS for evaluating financial performance. Bol. Soc. Paran. Mat, 32(3), 163-174. https://doi.org/10.5269/bspm.v32i2.21378
Ghadikolaei, A. S., Khalili Esbouei, S., & Antucheviciene, J. (2014). Applying fuzzy MCDM for financial performance evaluation of Iranian companies. Technological and Economic Development of Economy, 20(2), 274-291. https://doi.org/10.3846/20294913.2014.913274
Ghorabaee, M. K., Zavadskas, E. K., Amiri, M., & Turskis, Z. (2016). Extended EDAS method for fuzzy multi-criteria decision-making: an application to supplier selection. International journal of computers communications & control, 11(3), 358-371.
Giannakis, M., & Papadopoulos, T. (2016). Supply chain sustainability: A risk management approach. International Journal of Production Economics, 171, 455-470. https://doi.org/10.1016/j.ijpe.2015.06.032
Giri, B. C., Molla, M. U., & Biswas, P. (2022). Pythagorean fuzzy DEMATEL method for supplier selection in sustainable supply chain management. Expert Systems with Applications, 193, 116396. https://doi.org/10.1016/j.eswa.2021.116396
Govindan, K., Khodaverdi, R., & Jafarian, A. (2013). A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach. Journal of Cleaner production, 47, 345-354. https://doi.org/10.1016/j.jclepro.2012.04.014
Govindan, K., Mina, H., Esmaeili, A., & Gholami-Zanjani, S. M. (2020). An integrated hybrid approach for circular supplier selection and closed loop supply chain network design under uncertainty. Journal of Cleaner Production, 242, 118317. https://doi.org/10.1016/j.jclepro.2019.118317
Govindan, K., Rajendran, S., Sarkis, J., & Murugesan, P. (2015a). Multi criteria decision making approaches for green supplier evaluation and selection: a literature review. Journal of cleaner production, 98, 66-83. https://doi.org/10.1016/j.jclepro.2013.06.046
Govindan, K., Soleimani, H., & Kannan, D. (2015b). Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future. European journal of operational research, 240(3), 603-626. https://doi.org/10.1016/j.ejor.2014.07.012
Gupta, H., & Barua, M. K. (2017). Supplier selection among SMEs on the basis of their green innovation ability using BWM and fuzzy TOPSIS. Journal of Cleaner Production, 152, 242-258. https://doi.org/10.1016/j.jclepro.2017.03.125
Hamdan, S., & Cheaitou, A. (2017). Supplier selection and order allocation with green criteria: An MCDM and multi-objective optimization approach. Computers & Operations Research, 81, 282-304. https://doi.org/10.1016/j.cor.2016.11.005
Harwood, R. R. (2020). A history of sustainable agriculture. In Sustainable agricultural systems (pp. 3-19). CRC Press.
Hashemi, S. H., Karimi, A., & Tavana, M. (2015). An integrated green supplier selection approach with analytic network process and improved Grey relational analysis. International Journal of Production Economics, 159, 178-191. https://doi.org/10.1016/j.ijpe.2014.09.027
He, X., Deng, H., & Hwang, H. M. (2019). The current application of nanotechnology in food and agriculture. Journal of food and drug analysis, 27(1), 1-21. https://doi.org/10.1016/j.jfda.2018.12.002
Hendiani, S., Mahmoudi, A., & Liao, H. (2020). A multi-stage multi-criteria hierarchical decision-making approach for sustainable supplier selection. Applied Soft Computing, 94, 106456. https://doi.org/10.1016/j.asoc.2020.106456
Iordache, M., Schitea, D., Deveci, M., Akyurt, İ. Z., & Iordache, I. (2019). An integrated ARAS and interval type-2 hesitant fuzzy sets method for underground site selection: Seasonal hydrogen storage in salt caverns. Journal of Petroleum Science and Engineering, 175, 1088-1098. https://doi.org/10.1016/j.petrol.2019.01.051
Ivanov, D. (2022). Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic. Annals of operations research, 319(1), 1411-1431. https://doi.org/10.1007/s10479-020-03640-6
Jain, N., & Singh, A. R. (2020). Sustainable supplier selection under must-be criteria through Fuzzy inference system. Journal of Cleaner Production, 248, 119275. https://doi.org/10.1016/j.jclepro.2019.119275
Jain, V., Sangaiah, A. K., Sakhuja, S., Thoduka, N., & Aggarwal, R. (2018). Supplier selection using fuzzy AHP and TOPSIS: a case study in the Indian automotive industry. Neural computing and applications, 29, 555-564. https://doi.org/10.1007/s00521-016-2533-z
Javad, M. O. M., Darvishi, M., & Javad, A. O. M. (2020). Green supplier selection for the steel industry using BWM and fuzzy TOPSIS: A case study of Khouzestan steel company. Sustainable Futures, 2, 100012. https://doi.org/10.1016/j.sftr.2020.100012
Joshi, S., Singh, R. K., & Sharma, M. (2023). Sustainable agri-food supply chain practices: Few empirical evidences from a developing economy. Global Business Review, 24(3), 451-474. https://doi.org/10.1177/0972150920907014
Junior, F. R. L., Osiro, L., & Carpinetti, L. C. R. (2014). A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection. Applied soft computing, 21, 194-209. https://doi.org/10.1016/j.asoc.2014.03.014
Kamble, S. S., Gunasekaran, A., Subramanian, N., Ghadge, A., Belhadi, A., & Venkatesh, M. (2023). Blockchain technology’s impact on supply chain integration and sustainable supply chain performance: Evidence from the automotive industry. Annals of Operations Research, 327(1), 575-600. https://doi.org/10.1007/s10479-021-04129-6
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., de Sousa Jabbour, A. B. L., & Jabbour, C. J. C. (2014). Selecting green suppliers based on GSCM practices: Using fuzzy TOPSIS applied to a Brazilian electronics company. European Journal of operational research, 233(2), 432-447. https://doi.org/10.1016/j.ejor.2013.07.023
Kannan, D., Mina, H., Nosrati-Abarghooee, S., & Khosrojerdi, G. (2020). Sustainable circular supplier selection: A novel hybrid approach. Science of the Total Environment, 722, 137936. https://doi.org/10.1016/j.scitotenv.2020.137936
Kansara, S., Modgil, S., & Kumar, R. (2023). Structural transformation of fuzzy analytical hierarchy process: a relevant case for Covid-19. Operations Management Research, 16(1), 450-465. https://doi.org/10.1007/s12063-022-00270-y
Karmaker, C. L., Ahmed, T., Ahmed, S., Ali, S. M., Moktadir, M. A., & Kabir, G. (2021). Improving supply chain sustainability in the context of COVID-19 pandemic in an emerging economy: Exploring drivers using an integrated model. Sustainable production and consumption, 26, 411-427. https://doi.org/10.1016/j.spc.2020.09.019
Kaur, H., & Singh, S. P. (2021). Multi-stage hybrid model for supplier selection and order allocation considering disruption risks and disruptive technologies. International Journal of Production Economics, 231, 107830. https://doi.org/10.1016/j.ijpe.2020.107830
Keršulienė, V., & Turskis, Z. (2011). Integrated fuzzy multiple criteria decision making model for architect selection. Technological and economic development of economy, 17(4), 645-666. https://doi.org/10.3846/20294913.2011.635718
Keršulienė, V., & Turskis, Z. (2014a). An integrated multi-criteria group decision making process: selection of the chief accountant. Procedia-Social and Behavioral Sciences, 110, 897-904. https://doi.org/10.1016/j.sbspro.2013.12.935
Keršulienė, V., & Turskis, Z. (2014b). A hybrid linguistic fuzzy multiple criteria group selection of a chief accounting officer. Journal of Business Economics and Management, 15(2), 232-252. https://doi.org/10.3846/16111699.2014.903201
Khan, S. A. R., Yu, Z., Golpira, H., Sharif, A., & Mardani, A. (2021). A state-of-the-art review and meta-analysis on sustainable supply chain management: Future research directions. Journal of Cleaner Production, 278, 123357. https://doi.org/10.1016/j.jclepro.2020.123357
Koberg, E., & Longoni, A. (2019). A systematic review of sustainable supply chain management in global supply chains. Journal of cleaner production, 207, 1084-1098. https://doi.org/10.1016/j.jclepro.2018.10.033
Kouhizadeh, M., Saberi, S., & Sarkis, J. (2021). Blockchain technology and the sustainable supply chain: Theoretically exploring adoption barriers. International journal of production economics, 231, 107831. https://doi.org/10.1016/j.ijpe.2020.107831
Kubler, S., Robert, J., Derigent, W., Voisin, A., & Le Traon, Y. (2016). A state-of the-art survey & testbed of fuzzy AHP (FAHP) applications. Expert systems with applications, 65, 398-422. https://doi.org/10.1016/j.eswa.2016.08.064
Kumari, R., & Mishra, A. R. (2020). Multi-criteria COPRAS method based on parametric measures for intuitionistic fuzzy sets: application of green supplier selection. Iranian journal of science and technology, Transactions of Electrical Engineering, 44(4), 1645-1662. https://doi.org/10.1007/s40998-020-00312-w
Kusi-Sarpong, S., Gupta, H., Khan, S. A., Chiappetta Jabbour, C. J., Rehman, S. T., & Kusi-Sarpong, H. (2023). 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
Lee, H. L. (2002). Aligning supply chain strategies with product uncertainties. California management review, 44(3), 105-119. https://doi.org/10.2307/41166135
Lei, F., Wei, G., Gao, H., Wu, J., & Wei, C. (2020). TOPSIS method for developing supplier selection with probabilistic linguistic information. International Journal of Fuzzy Systems, 22, 749-759. https://doi.org/10.1007/s40815-019-00797-6
Liang, W., Zhao, G., & Luo, S. (2021). Sustainability evaluation for phosphorus mines using a hybrid multi-criteria decision making method. Environment, Development and Sustainability, 23, 12411-12433. https://doi.org/10.1007/s10668-020-01175-1
Liu, Y., Eckert, C. M., & Earl, C. (2020). A review of fuzzy AHP methods for decision-making with subjective judgements. Expert Systems with Applications, 161, 113738. https://doi.org/10.1016/j.eswa.2020.113738
Liu, Y., Ma, X., Shu, L., Hancke, G. P., & Abu-Mahfouz, A. M. (2020). From Industry 4.0 to Agriculture 4.0: Current status, enabling technologies, and research challenges. IEEE Transactions on Industrial Informatics, 17(6), 4322-4334. https://doi.org/10.1109/TII.2020.3003910
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
Luthra, S., Govindan, K., Kannan, D., Mangla, S. K., & Garg, C. P. (2017). An integrated framework for sustainable supplier selection and evaluation in supply chains. Journal of cleaner production, 140, 1686-1698. https://doi.org/10.1016/j.jclepro.2016.09.078
Luthra, S., & Mangla, S. K. (2018). Evaluating challenges to Industry 4.0 initiatives for supply chain sustainability in emerging economies. Process Safety and Environmental Protection, 117, 168-179. https://doi.org/10.1016/j.psep.2018.04.018
Mahmoudi, A., Deng, X., Javed, S. A., & Zhang, N. (2021). Sustainable supplier selection in megaprojects: grey ordinal priority approach. Business Strategy and the Environment, 30(1), 318-339. https://doi.org/10.1002/bse.2623
Manavalan, E., & Jayakrishna, K. (2019). A review of Internet of Things (IoT) embedded sustainable supply chain for industry 4.0 requirements. Computers & industrial engineering, 127, 925-953. https://doi.org/10.1016/j.cie.2018.11.030
Mavi, R. K. (2015). Green supplier selection: a fuzzy AHP and fuzzy ARAS approach. International Journal of Services and Operations Management, 22(2), 165-188. https://doi.org/10.1504/IJSOM.2015.071528
Memari, A., Dargi, A., Jokar, M. R. A., Ahmad, R., & Rahim, A. R. A. (2019). Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method. Journal of manufacturing systems, 50, 9-24. https://doi.org/10.1016/j.jmsy.2018.11.002
Meredith, J. R., & Shafer, S. M. (2023). Operations and supply chain management for MBAs. John Wiley & Sons.
Mina, H., Kannan, D., Gholami-Zanjani, S. M., & Biuki, M. (2021). Transition towards circular supplier selection in petrochemical industry: A hybrid approach to achieve sustainable development goals. Journal of Cleaner Production, 286, 125273. https://doi.org/10.1016/j.jclepro.2020.125273
Misra, N. N., Dixit, Y., Al-Mallahi, A., Bhullar, M. S., Upadhyay, R., & Martynenko, A. (2020). IoT, big data, and artificial intelligence in agriculture and food industry. IEEE Internet of things Journal, 9(9), 6305-6324. https://doi.org/10.1109/JIOT.2020.2998584
Myers, J. H., & Alpert, M. I. (1968). Determinant buying attitudes: meaning and measurement. Journal of Marketing, 32(4_part_1), 13-20. https://doi.org/10.1177/002224296803200404
Nasr, A. K., Tavana, M., Alavi, B., & Mina, H. (2021). A novel fuzzy multi-objective circular supplier selection and order allocation model for sustainable closed-loop supply chains. Journal of Cleaner production, 287, 124994. https://doi.org/10.1016/j.jclepro.2020.124994
Nguyen, H. T., Md Dawal, S. Z., Nukman, Y., Aoyama, H., & Case, K. (2015). An integrated approach of fuzzy linguistic preference based AHP and fuzzy COPRAS for machine tool evaluation. PloS one, 10(9), e0133599. https://doi.org/10.1371/journal.pone.0133599
Nguyen, H. T., Md Dawal, S. Z., Nukman, Y., P. Rifai, A., & Aoyama, H. (2016). An integrated MCDM model for conveyor equipment evaluation and selection in an FMC based on a fuzzy AHP and fuzzy ARAS in the presence of vagueness. PloS one, 11(4), e0153222. https://doi.org/10.1371/journal.pone.0153222
Ömürbek, N., & Tunca, Z. (2013). Analitik hiyerarşi süreci ve analitik ağ süreci yöntemlerinde grup kararı verilmesi aşamasına ilişkin bir örnek uygulama. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 18(3), 47-70.
Paksoy, T., Çalik, A., Kumpf, A., & Weber, G. W. (2019). A new model for lean and green closed-loop supply chain optimization. Lean and Green Supply Chain Management: Optimization Models and Algorithms, 39-73. https://doi.org/10.1007/978- 3-319-97511-5_2
Pamucar, D., Torkayesh, A. E., & Biswas, S. (2023). Supplier selection in healthcare supply chain management during the COVID-19 pandemic: a novel fuzzy rough decision-making approach. Annals of Operations Research, 328(1), 977-1019. https://doi.org/10.1007/s10479-022-04529-2
Prakash, C., & Barua, M. K. (2016). A combined MCDM approach for evaluation and selection of third-party reverse logistics partner for Indian electronics industry. Sustainable Production and Consumption, 7, 66-78. https://doi.org/10.1016/j.spc.2016.04.001
Ponomarov, S. Y., & Holcomb, M. C. (2009). Understanding the concept of supply chain resilience. The international journal of logistics management, 20(1), 124-143. https://doi.org/10.1108/09574090910954873
Puri, V., Nayyar, A., & Raja, L. (2017). Agriculture drones: A modern breakthrough in precision agriculture. Journal of Statistics and Management Systems, 20(4), 507-518. https://doi.org/10.1080/09720510.2017.1395171
Qin, J., Liu, X., & Pedrycz, W. (2017). An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment. European Journal of Operational Research, 258(2), 626-638. https://doi.org/10.1016/j.ejor.2016.09.059
Rajeev, A., Pati, R. K., Padhi, S. S., & Govindan, K. (2017). Evolution of sustainability in supply chain management: A literature review. Journal of cleaner production, 162, 299-314. https://doi.org/10.1016/j.jclepro.2017.05.026
Razavi Toosi, S. L., & Samani, J. M. V. (2016). Evaluating water management strategies in watersheds by new hybrid Fuzzy Analytical Network Process (FANP) methods. Journal of Hydrology, 534, 364-376. https://doi.org/10.1016/j.jhydrol.2016.01.006
Rezaei, J., Nispeling, T., Sarkis, J., & Tavasszy, L. (2016). A supplier selection life cycle approach integrating traditional and environmental criteria using the best worst method. Journal of cleaner production, 135, 577-588. https://doi.org/10.1016/j.jclepro.2016.06.125
Rouyendegh, B. D., Yildizbasi, A., & Üstünyer, P. (2020). Intuitionistic fuzzy TOPSIS method for green supplier selection problem. Soft Computing, 24, 2215-2228. https://doi.org/10.1007/s00500-019-04054-8
Saaty, T. L. (1977). Modeling unstructured decision-making-AHP. In International Conference on Mathematical Modeling.
Saaty, T. L. (1982). The analytic hierarchy process: A new approach to deal with fuzziness in architecture. Architectural Science Review, 25(3), 64-69. https://doi.org/10.1080/00038628.1982.9696499
Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International journal of production research, 57(7), 2117-2135. https://doi.org/10.1080/00207543.2018.1533261
Saputro, T. E., Figueira, G., & Almada-Lobo, B. (2023). Hybrid MCDM and simulation-optimization for strategic supplier selection. Expert Systems with Applications, 219, 119624. https://doi.org/10.1016/j.eswa.2023.119624
Sarkis, J. (2020). Supply chain sustainability: learning from the COVID-19 pandemic. International Journal of Operations & Production Management, 41(1), 63-73. https://doi.org/10.1108/IJOPM-08-2020-0568
Sathyan, R., Parthiban, P., Dhanalakshmi, R., & Sachin, M. S. (2023). An integrated Fuzzy MCDM approach for modelling and prioritising the enablers of responsiveness in automotive supply chain using Fuzzy DEMATEL, Fuzzy AHP and Fuzzy TOPSIS. Soft Computing, 27(1), 257-277. https://doi.org/10.1007/s00500-022-07591-x
Saurabh, S., & Dey, K. (2021). Blockchain technology adoption, architecture, and sustainable agri-food supply chains. Journal of Cleaner Production, 284, 124731. https://doi.org/10.1016/j.jclepro.2020.124731
Schramm, V. B., Cabral, L. P. B., & Schramm, F. (2020). Approaches for supporting sustainable supplier selection-A literature review. Journal of cleaner production, 273, 123089. https://doi.org/10.1016/j.jclepro.2020.123089
Seuring, S. (2013). A review of modeling approaches for sustainable supply chain management. Decision support systems, 54(4), 1513-1520. https://doi.org/10.1016/j.dss.2012.05.053
Seuring, S., Sarkis, J., Müller, M., & Rao, P. (2008). Sustainability and supply chain management–an introduction to the special issue. Journal of cleaner production, 16(15), 1545-1551. https://doi.org/10.1016/j.jclepro.2008.02.002
Shafiee, M. (2015). A fuzzy analytic network process model to mitigate the risks associated with offshore wind farms. Expert Systems with Applications, 42(4), 2143-2152. https://doi.org/10.1016/j.eswa.2014.10.019
Shang, Z., Yang, X., Barnes, D., & Wu, C. (2022). Supplier selection in sustainable supply chains: Using the integrated BWM, fuzzy Shannon entropy, and fuzzy MULTIMOORA methods. Expert Systems with Applications, 195, 116567. https://doi.org/10.1016/j.eswa.2022.116567
Singh, V., Kumar, V., & Singh, V. B. (2023). A hybrid novel fuzzy AHP-Topsis technique for selecting parameter-influencing testing in software development. Decision Analytics Journal, 6, 100159. https://doi.org/10.1016/j.dajour.2022.100159
Soberi, M. S. F., & Ahmad, R. (2016). Application of fuzzy AHP for setup reduction in manufacturing industry. J. Eng. Res. Educ, 8, 73-84.
Stević, Ž., Pamučar, D., Puška, A., & Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS). Computers & industrial engineering, 140, 106231. https://doi.org/10.1016/j.cie.2019.106231
Tirkolaee, E. B., Mardani, A., Dashtian, Z., Soltani, M., & Weber, G. W. (2020). A novel hybrid method using fuzzy decision making and multi-objective programming for sustainable-reliable supplier selection in two-echelon supply chain design. Journal of cleaner production, 250, 119517. https://doi.org/10.1016/j.jclepro.2019.119517
Tong, L. Z., Wang, J., & Pu, Z. (2022). Sustainable supplier selection for SMEs based on an extended PROMETHEE Ⅱ approach. Journal of Cleaner Production, 330, 129830. https://doi.org/10.1016/j.jclepro.2021.129830
Turskis, Z., Goranin, N., Nurusheva, A., & Boranbayev, S. (2019). A fuzzy WASPAS-based approach to determine critical information infrastructures of EU sustainable development. Sustainability, 11(2), 424. https://doi.org/10.3390/su11020424
Turskis, Z., Urbonas, K., & Daniūnas, A. (2019). A hybrid fuzzy group multi-criteria assessment of structural solutions of the symmetric frame alternatives. Symmetry, 11(2), 261. https://doi.org/10.3390/sym11020261
Turskis, Z., Zavadskas, E. K., Antucheviciene, J., & Kosareva, N. (2015). A hybrid model based on fuzzy AHP and fuzzy WASPAS for construction site selection. International Journal of Computers communications & control, 10(6), 113-128.
Van Huis, A. (2020). Insects as food and feed, a new emerging agricultural sector: a review. Journal of Insects as Food and Feed, 6(1), 27-44. https://doi.org/10.3920/JIFF2019.0017
Wang, C. N., & Van Thanh, N. (2022). Fuzzy MCDM for Improving the Performance of Agricultural Supply Chain. Computers, Materials & Continua, 73(2). http://dx.doi.org/10.32604/cmc.2022.030209
Wang Chen, H. M., Chou, S. Y., Luu, Q. D., & Yu, T. H. K. (2016). A fuzzy MCDM approach for green supplier selection from the economic and environmental aspects. Mathematical Problems in Engineering, 2016. https://doi.org/10.1155/2016/8097386
Wang, C. N., Nguyen, N. A. T., Dang, T. T., & Lu, C. M. (2021). A compromised decision-making approach to third-party logistics selection in sustainable supply chain using fuzzy AHP and fuzzy VIKOR methods. Mathematics, 9(8), 886. https://doi.org/10.3390/math9080886
Wu, Q., Zhou, L., Chen, Y., & Chen, H. (2019). An integrated approach to green supplier selection based on the interval type-2 fuzzy best-worst and extended VIKOR methods. Information Sciences, 502, 394-417. https://doi.org/10.1016/j.ins.2019.06.049
Yazdani, M., Chatterjee, P., Zavadskas, E. K., & Zolfani, S. H. (2017). Integrated QFD-MCDM framework for green supplier selection. Journal of Cleaner Production, 142, 3728-3740. https://doi.org/10.1016/j.jclepro.2016.10.095
Yazdani, M., Torkayesh, A. E., Stević, Ž., Chatterjee, P., Ahari, S. A., & Hernandez, V. D. (2021). An interval valued neutrosophic decision-making structure for sustainable supplier selection. Expert Systems with Applications, 183, 115354. https://doi.org/10.1016/j.eswa.2021.115354
Yu, C., Shao, Y., Wang, K., & Zhang, L. (2019). A group decision making sustainable supplier selection approach using extended TOPSIS under interval-valued Pythagorean fuzzy environment. Expert Systems with Applications, 121, 1-17. https://doi.org/10.1016/j.eswa.2018.12.010
Zadeh, L. A. (1965). Information and control. Fuzzy sets, 8(3), 338-353.
Zadeh, L. A. (1975). Fuzzy logic and approximate reasoning. Synthese, 30(3), 407-428.
Zadeh, L. A. (2015). Fuzzy logic—a personal perspective. Fuzzy sets and systems, 281, 4-20.
Zamani, M., Rabbani, A., Yazdani-Chamzini, A., & Turskis, Z. (2014). An integrated model for extending brand based on fuzzy ARAS and ANP methods. Journal of Business Economics and Management, 15(3), 403-423. https://doi.org/10.3846/16111699.2014.923929
Zambon, I., Cecchini, M., Egidi, G., Saporito, M. G., & Colantoni, A. (2019). Revolution 4.0: Industry vs. agriculture in a future development for SMEs. Processes, 7(1), 36. https://doi.org/10.3390/pr7010036
Zavadskas, E. K., & Turskis, Z. (2010). A new additive ratio assessment (ARAS) method in multicriteria decision‐making. Technological and economic development of economy, 16(2), 159-172. https://doi.org/10.3846/tede.2010.10
Zavadskas, E. K., Turskis, Z., & Bagočius, V. (2015). Multi-criteria selection of a deep-water port in the Eastern Baltic Sea. Applied Soft Computing, 26, 180-192. https://doi.org/10.1016/j.asoc.2014.09.019
Zimmer, K., Fröhling, M., & Schultmann, F. (2016). Sustainable supplier management–a review of models supporting sustainable supplier selection, monitoring and development. International journal of production research, 54(5), 1412-1442. https://doi.org/10.1080/00207543.2015.1079340
Zin, N. A., & Badaluddin, N. A. (2020). Biological functions of Trichoderma spp. for agriculture applications. Annals of Agricultural Sciences, 65(2), 168-178. https://doi.org/10.1016/j.aoas.2020.09.003
İndir
Yayınlanmış
Nasıl Atıf Yapılır
Sayı
Bölüm
Lisans
Bu çalışma Creative Commons Attribution-NonCommercial 4.0 International License ile lisanslanmıştır.