Supplier selection using Fuzzy DEA credibility constrained and relative closeness index: A case of Indonesian manufacturing industry

References

• Abel, E., Ríos, C., C, J., Paton, N. W., Keane, J. A., & Fernandes, A. A. A. (2020). Targeted evidence collection for uncertain supplier selection. Expert Systems with Applications, 159, 159. https://doi.org/10.1016/j.eswa.2020.113583
   Web of Science ®Google Scholar
• Aydin, S., & Kahraman, C. (2010). Multiattribute supplier selection using fuzzy analytic hierarchy process. International Journal of Computational Intelligence Systems, 3(5), 553–24. https://doi.org/10.1080/18756891.2010.9727722
   Web of Science ®Google Scholar
• Azadi, M., Jafarian, M., Saen R, F., & Mirhedayatian, S. M. (2015). A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context. Computers & Operations Research, 54, 274–285. https://doi.org/10.1016/j.cor.2014.03.002
   Web of Science ®Google Scholar
• Bai, C., & Sarkis, J. (2010). Integrating sustainability into supplier selection with grey system and rough set methodologies. International Journal of Production Economics, 124(1), 252–264. https://doi.org/10.1016/j.ijpe.2009.11.023
   Web of Science ®Google Scholar
• Baskaran, V., Nachiappan, S., & Rahman, S. (2012). Indian textile suppliers’ sustainability evaluation using the grey approach. International Journal of Production Economics, 135, 647–658. https://doi.org/10.1016/j.ijpe.2011.06.012
   Web of Science ®Google Scholar
• Berghäll, E., & Nisar, T. (2016). Innovation, competition and technical efficiency. Cogent Business & Management, 3(1), 1199522. https://doi.org/10.1080/23311975.2016.1199522
   Google Scholar
• Bulgurcu, B., & Nakiboglu, G. (2018). An extent analysis of 3PL provider selection criteria: A case on Turkey cement sector. Cogent Business & Management, 5(1), 1469183. https://doi.org/10.1080/23311975.2018.1469183
   Web of Science ®Google Scholar
• Chen, C.-T., Lin, C.-T., & Huang, S.-F. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management. International Journal of Production Economics, 102(2), 289–301. https://doi.org/10.1016/j.ijpe.2005.03.009
   Web of Science ®Google Scholar
• Chen, K.-L., Yeh, C.-C., & Huang, J.-C. (2014). Supplier selection using a hybrid model for 3c industry. Journal of Business Economics and Management, 15(4), 631–645. https://doi.org/10.3846/16111699.2013.807870
   Web of Science ®Google Scholar
• Chin-Nung, L. (2012). Applying fuzzy-MSGP approach for supplier evaluation and selection in food industry. African Journal of Agricultural Research, 7(5). https://doi.org/10.5897/AJARX11.088
   Google Scholar
• Cook, W. D., Tone, K., & Zhu, J. (2014). Data envelopment analysis: Prior to choosing a model. Omega, 44, 1–4. https://doi.org/10.1016/j.omega.2013.09.004
   Web of Science ®Google Scholar
• Cooper, W. W., Seiford, L. M. & J, Z. H. U., Cooper, W. W., Seiford, L. M., Zhu, J. (2011). Handbook on data envelopment analysis. Springer US. https://doi.org/10.1007/978-1-4419-6151-8
   Google Scholar
• Dargi, A., Anjomshoae, A., Galankashi, M. R., Memari, A., & Tap, M. B. M. (2014). Supplier selection: A fuzzy-ANP approach. Procedia Computer Science, 31, 691–700. https://doi.org/10.1016/j.procs.2014.05.317
   Google Scholar
• Dobos, I., & Vörösmarty, G. (2014). Green supplier selection and evaluation using DEA-type composite indicators. International Journal of Production Economics, 157, 273–278. https://doi.org/10.1016/j.ijpe.2014.09.026
   Web of Science ®Google Scholar
• Duong, N. H., Ha, Q.-A., & Tan, A. W. K. (2021). The links between supply chain risk management practices, supply chain integration and supply chain performance in Southern Vietnam: A moderation effect of supply chain social sustainability. Cogent Business & Management, 8(1), 1999556. https://doi.org/10.1080/23311975.2021.1999556
   Web of Science ®Google Scholar
• Eftekhari, N., Yazdani, A., Razmyan, S., & Shamohammadi, A. (2020). Data envelopment analysis based procedure for selection and ranking of ground motion prediction equations. Soil Dynamics and Earthquake Engineering, 137, 106303. https://doi.org/10.1016/j.soildyn.2020.106303
   Web of Science ®Google Scholar
• Fei, L., Deng, Y., & Hu, Y. (2018). DS-VIKOR: A new multi-criteria decision-making method for supplier selection. International Journal of Fuzzy Systems, 21(1), 157–175. https://doi.org/10.1007/s40815-018-0543-y
   Web of Science ®Google Scholar
• Gordon, S. R. (2008). Supplier evaluation and performance excellence: A guide to meaningful metrics and successful results. J. Ross Publishing.
   Google Scholar
• Hanaysha, J. (2016). Testing the effects of employee empowerment, teamwork, and employee training on employee productivity in higher education sector. International Journal of Learning and Development, 6(1), 164–178. https://doi.org/10.5296/ijld.v6i1.9200
   Google Scholar
• Hoseini, A. R., Ghannadpour, S. F., & Ghamari, R. (2020). Sustainable supplier selection by a new possibilistic hierarchical model in the context of Z-information. Journal of Ambient Intelligence and Humanized Computing, 11(11), 4827–4853. https://doi.org/10.1007/s12652-020-01751-3
   Web of Science ®Google Scholar
• Jauhar, S. K., & Pant, M. (2017). Integrating DEA with DE and MODE for sustainable supplier selection. Journal of Computational Science, 21, 299–306. https://doi.org/10.1016/j.jocs.2017.02.011
   Web of Science ®Google Scholar
• Kannan, V. R., & Tan, K. C. (2002). Supplier selection and assessment: Their impact on business performance. The Journal of Supply Chain Management, 38(4), 11–21. https://doi.org/10.1111/j.1745-493X.2002.tb00139.x
   Google Scholar
• Kara, K., & Çetinkaya, A. S. L. I. (2022). Determination of Financial Performance Efficiency with Data Envelopment Analysis: Evidence from Borsa İstanbul (BIST) Transportation and Storage Sector. Journal of Emerging Economies and Policy (Online), 7(2).
   Google Scholar
• Karsak, E. E., & Dursun, M. (2014). An integrated supplier selection methodology incorporating QFD and DEA with imprecise data. Expert Systems with Applications, 41(16), 6995–7004. https://doi.org/10.1016/j.eswa.2014.06.020
   Web of Science ®Google Scholar
• Kilincci, O., & Onal, S. A. (2011). Fuzzy AHP approach for supplier selection in a washing machine company. Expert Systems with Applications, 38(8), 9656–9664. https://doi.org/10.1016/j.eswa.2011.01.159
   Web of Science ®Google Scholar
• Kim, S., Warinsiriruk, E., & Joy-A-Ka, S. (2019). Estimation of welding machine flexibility by using Data Envelopment Analysis (DEA) with Relative Closeness (RC). Proceedings of the 2019 4th Technology Innovation Management and Engineering Science International Conference (TIMES-iCON), Bangkok, Thailand (pp. 1–5). IEEE.
   Google Scholar
• Konings, M., Bak, M., Hanssen, M., Van, O. J., & Krabbendam, L. (2006). Validity and reliability of the CAPE: A self-report instrument for the measurement of psychotic experiences in the general population. Acta Psychiatrica Scandinavica, 114, 55–61. https://doi.org/10.1111/j.1600-0447.2005.00741.x
   PubMed Web of Science ®Google Scholar
• LI, X., & B, L. I. U. (2006). A sufficient and necessary condition for credibility measures. International Journal of Uncertainty, 14(5), 527–535. https://doi.org/10.1142/S0218488506004175
   Google Scholar
• LI, X. M., LU, H. W., LI, J., DU, P., XU, M., & HE, L. (2015). A modified fuzzy credibility constrained programming approach for agricultural water resources management—A case study in Urumqi, China. Agricultural Water Management, 156, 79–89. https://doi.org/10.1016/j.agwat.2015.03.005
   Web of Science ®Google Scholar
• LIN, S.-W., & LU, W.-M. (2023). A chance-constrained network DEA approach based on enhanced Russell-based directional distance measure to evaluate public sector performance: A case study of OECD countries. Annals of Operations Research. https://doi.org/10.1007/s10479-023-05337-y
   Web of Science ®Google Scholar
• Masudin, I., Aprilia, G. D., Nugraha, A., & Restuputri, D. P. (2021). Impact of E-procurement adoption on company performance: Evidence from Indonesian manufacturing industry. Logistics, 5(1), 16. https://doi.org/10.3390/logistics5010016
   Google Scholar
• Masudin, I., LAU, E., Safitri, N. T., Restuputri, D. P., Handayani, D. I., & Tan, A. W. K. (2021). The impact of the traceability of the information systems on humanitarian logistics performance: Case study of Indonesian relief logistics services. Cogent Business & Management, 8(1), 1906052. https://doi.org/10.1080/23311975.2021.1906052
   Web of Science ®Google Scholar
• Masudin, I., Ramadhani, A., & Restuputri, D. P. (2021). Traceability system model of Indonesian food cold-chain industry: A Covid-19 pandemic perspective. Cleaner Engineering and Technology, 4, 100238. https://doi.org/10.1016/j.clet.2021.100238
   Google Scholar
• Masudin, I., Safitri, N. T., Restuputri, D. P., Wardana, R. W., Amallynda, I., & Tan, A. W. K. (2020). The effect of humanitarian logistics service quality to customer loyalty using Kansei engineering: Evidence from Indonesian logistics service providers. Cogent Business & Management, 7(1), 1826718. https://doi.org/10.1080/23311975.2020.1826718
   Web of Science ®Google Scholar
• Meng, M., & Liu, Y. (2007). Fuzzy data envelopment analysis with credibility constraints. Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), Fuzhou, China (Vol. 1, pp. 149–153). IEEE.
   Google Scholar
• Meng, M., Yuan, G., & Huang, J. (2011). Satisficing data envelopment analysis model with credibility constraints. Proceedings of the 2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), Shanghai, China (Vol. 2, pp. 703–707). IEEE.
   Google Scholar
• Mirmousa, S., & Dehnavi, H. D. (2016). Development of criteria of selecting the supplier by using the fuzzy DEMATEL method. Procedia - Social & Behavioral Sciences, 230, 281–289. https://doi.org/10.1016/j.sbspro.2016.09.036
   Google Scholar
• Mohammadnazari, Z., Mousapour Mamoudan, M., Alipour-Vaezi, M., Aghsami, A., Jolai, F., & Yazdani, M. (2022). Prioritizing post-disaster reconstruction projects using an integrated multi-criteria decision-making approach: A case study. Buildings, 12(2), 136. https://doi.org/10.3390/buildings12020136
   Web of Science ®Google Scholar
• Molamohamadi, Z., Ismail, N., Leman, Z., & Zulkifli, N. (2013). Supplier selection in a sustainable supply chain. Journal of Advanced Management Science, 278–281. https://doi.org/10.12720/joams.1.3.278-281
   Google Scholar
• Mousavi-Nasab, S. H., & Sotoudeh-Anvari, A. (2017). A comprehensive MCDM-based approach using TOPSIS, COPRAS and DEA as an auxiliary tool for material selection problems. Materials & Design, 121, 237–253. https://doi.org/10.1016/j.matdes.2017.02.041
   Web of Science ®Google Scholar
• Peixoto, M. G. M., Musetti, M. A., & Mendonça, M. C. A. D. (2020). Performance management in hospital organizations from the perspective of principal component analysis and data envelopment analysis: The case of federal university hospitals in Brazil. Computers & Industrial Engineering, 150, 106873. https://doi.org/10.1016/j.cie.2020.106873
   Web of Science ®Google Scholar
• Raith, A., Ehrgott, M., Fauzi, F., Lin, K.-M., Macann, A., Rouse, P., & Simpson, J. J. E. J. O. O. R. (2021). Integrating data envelopment analysis into radiotherapy treatment planning for head and neck cancer patients. European Journal of Operational Research, 296(1), 289–303. https://doi.org/10.1016/j.ejor.2021.04.007
   Web of Science ®Google Scholar
• Rajesh, G., & Malliga, P. (2013). Supplier selection based on AHP QFD methodology. Procedia Engineering, 64, 1283–1292. https://doi.org/10.1016/j.proeng.2013.09.209
   Google Scholar
• Rashidi, K., & Cullinane, K. (2019). A comparison of fuzzy DEA and fuzzy TOPSIS in sustainable supplier selection: Implications for sourcing strategy. Expert Systems with Applications, 121, 266–281. https://doi.org/10.1016/j.eswa.2018.12.025
   Web of Science ®Google Scholar
• Sevkli, M. (2009). An application of the fuzzy ELECTRE method for supplier selection. International Journal of Production Research, 48(12), 3393–3405. https://doi.org/10.1080/00207540902814355
   Web of Science ®Google Scholar
• Soner Kara, S. (2011). Supplier selection with an integrated methodology in unknown environment. Expert Systems with Applications, 38(3), 2133–2139. https://doi.org/10.1016/j.eswa.2010.07.154
   Web of Science ®Google Scholar
• Souza, D. E., Zice S, R., & Chaoyang, L. J. I. M. S. (2000). Supply chain dynamics and optimization. Integrated Manufacturing Systems, 11(5), 348–364. https://doi.org/10.1108/09576060010335627
   Google Scholar
• Stainer, A., Ghobadian, A., Liu, J., & Kiss, T. (2016). Vendor assessment: A computerised approach. International Journal of Computer Applications in Technology, 9(2–3), 106–113. https://doi.org/10.1504/IJCAT.1996.062302
   Google Scholar
• Tavassoli, M., Saen, R. F., & Zanjirani, D. M. (2020). Assessing sustainability of suppliers: A novel stochastic-fuzzy DEA model. Sustainable Production and Consumption, 21, 78–91. https://doi.org/10.1016/j.spc.2019.11.001
   Web of Science ®Google Scholar
• Toloo, M., & Nalchigar, S. (2011). A new DEA method for supplier selection in presence of both cardinal and ordinal data. Expert Systems with Applications, 38(12), 14726–14731. https://doi.org/10.1016/j.eswa.2011.05.008
   Web of Science ®Google Scholar
• Trafialek, J. (2019). The role of suppliers of raw materials in ensuring food safety. Global Journal of Nutrition & Food Science, 1(4). https://doi.org/10.33552/GJNFS.2019.01.000517
   Google Scholar
• Wang, J., Wang, J.-Q., Zhang, H.-Y., & Chen, X.-H. (2016). Multi-criteria group decision-making approach based on 2-tuple linguistic aggregation operators with multi-hesitant fuzzy linguistic information. International Journal of Fuzzy Systems, 18(1), 81–97. https://doi.org/10.1007/s40815-015-0050-3
   Web of Science ®Google Scholar
• Wang, Y.-M., & Y, L. (2006). DEA efficiency assessment using ideal and anti-ideal decision making units. Applied Mathematics and Computation, 173(2), 902–915. https://doi.org/10.1016/j.amc.2005.04.023
   Web of Science ®Google Scholar
• Wardana, R. W., Masudin, I., Restuputri, D. P., Nugraha, A., & Zhou, Z. (2021). A novel decision-making method using fuzzy DEA credibility constrained and RC index. Cogent Engineering, 8(1), 1917328. https://doi.org/10.1080/23311916.2021.1917328
   Web of Science ®Google Scholar
• Wardana, R. W., Masudin, I., Restuputri, D. P., & Tan, Y. Y. (2020). A novel group decision-making method by P-robust fuzzy DEA credibility constraint for welding process selection. Cogent Engineering, 7(1), 1728057. https://doi.org/10.1080/23311916.2020.1728057
   Web of Science ®Google Scholar
• Wen, T.-C., Chang, K.-H., & Lai, H.-H. (2020). Integrating the 2-tuple linguistic representation and soft set to solve supplier selection problems with incomplete information. Engineering Applications of Artificial Intelligence, 87, 103248. https://doi.org/10.1016/j.engappai.2019.103248
   Web of Science ®Google Scholar
• Wen, M., LI, H. J. J. O. C., & Mathematics, A. (2009). Fuzzy data envelopment analysis (DEA): Model and ranking method. Journal of Computational and Applied Mathematics, 223(2), 872–878. https://doi.org/10.1016/j.cam.2008.03.003
   Web of Science ®Google Scholar
• Wu, D. (2009). Supplier selection: A hybrid model using DEA, decision tree and neural network. Expert Systems with Applications, 36(5), 9105–9112. https://doi.org/10.1016/j.eswa.2008.12.039
   Web of Science ®Google Scholar
• Zaim, S., Sevkli, M., & Tarim, M. (2003). Fuzzy analytic hierarchy based approach for supplier selection. Journal of Euromarketing, 12(3–4), 147–176. https://doi.org/10.1300/J037v12n03_09
   Google Scholar
• Zhang, C., & P, G. (2017). A generalized fuzzy credibility-constrained linear fractional programming approach for optimal irrigation water allocation under uncertainty. Journal of Hydrology, 553, 735–749. https://doi.org/10.1016/j.jhydrol.2017.08.008
   Web of Science ®Google Scholar
• Zhou, X., Pedrycz, W., Kuang, Y., & Zhang, Z. (2016). Type-2 fuzzy multi-objective DEA model: An application to sustainable supplier evaluation. Applied Soft Computing, 46, 424–440. https://doi.org/10.1016/j.asoc.2016.04.038
   Web of Science ®Google Scholar