141 106
Full Length Article
American Journal of Business and Operations Research
Volume 7 , Issue 2, PP: 41-55 , 2022 | Cite this article as | XML | Html |PDF


Multi-Criteria Decision-Making Approach based on Neutrosophic Sets for Evaluating Sustainable Supplier Selection in the Industrial 4.0

Authors Names :   Mahmoud Ismail   1 *     Mahmoud Ibrahiem   2  

1  Affiliation :  Faculty of Computers and Informatics, Zagazig University, Sharqiyah, Egypt

    Email :  mahsabe@yahoo.com

2  Affiliation :  Faculty of Computers and Informatics, Zagazig University, Sharqiyah, Egypt

    Email :  mahmoudabosba@gmail.com

Doi   :   https://doi.org/10.54216/AJBOR.070204

Received: March 09, 2022 Accepted: August 28, 2022

Abstract :

Sustainability in supply chain management can be achieved by integrating its applications with Industry 4.0 platforms.  Considering the Sustainability and Industry 4.0 criteria for supplier selection, this research creates a new integrated model to improve the performance of the applicatios.  The choice of suppliers is evaluated using a two-stage neutrosophic sets and the EDAS method.  The first step of this research is to define all of the terms associated with Industry 4.0 and Sustainability.  The neutrosophic EDAS determines the relative relevance of each criterion.  The neutrosophic VIKOR method is used to rank the suppliers.  The suppliers' performance in meeting the sustainability and Industry 4.0 standards is then nominated in a two-stage neutrosophic sets.  A case study of a textile firm is offered to illustrate the usefulness of our integrated approach.  The effectiveness of the suggested integrated method is then evaluated via a series of sensitivity assessments.  Of the things we learned was that it's best to build a decision-making framework that uses Industry 4.0 and sustainability criteria to assess suppliers individually rather than in a relative fashion in a hazy setting.

Keywords :

Decision Support; Industry 4.0; Sustainability; Supplier Selection; MCDM; Entropy; VIKOR; Neutrosophic; EDAS

References :

[1] C.-T. Chiang, T.-C. Kou, and T.-L. Koo, “A systematic literature review of the IT-based supply chain

management system: Towards a sustainable supply chain management model,” Sustainability, vol. 13, no. 5, p. 2547,


[2] Z. Yu, M. Waqas, M. Tabish, M. Tanveer, I. U. Haq, and S. A. R. Khan, “Sustainable supply chain

management and green technologies: a bibliometric review of literature,” Environmental Science and Pollution

Research, pp. 1–17, 2022.

[3] S. Seuring, S. Aman, B. D. Hettiarachchi, F. A. de Lima, L. Schilling, and J. I. Sudusinghe, “Reflecting on

theory development in sustainable supply chain management,” Cleaner Logistics and Supply Chain, vol. 3, p. 100016,


[4] M. Matthess, S. Kunkel, B. Xue, and G. Beier, “Supplier sustainability assessment in the age of Industry 4.0–

Insights from the electronics industry,” Cleaner Logistics and Supply Chain, vol. 4, p. 100038, 2022.

[5] A. Jayant, A. K. Chandan, and S. Singh, “Sustainable supplier selection for battery manufacturing industry:

A MOORA and WASPAS Based Approach,” in Journal of Physics: Conference Series, 2019, vol. 1240, no. 1, p.


[6] G. Chaouni Benabdellah, K. Bennis, A. Chaouni Benabdellah, and K. Zekhnini, “Resilient Sustainable

Supplier Selection Criteria Assessment for Economics Enhancement in Industry 4.0 Context,” in IFIP International

Conference on Product Lifecycle Management, 2021, pp. 194–208.

[7] A. Fallahpour, K. Y. Wong, S. Rajoo, A. M. Fathollahi-Fard, J. Antucheviciene, and S. Nayeri, “An

integrated approach for a sustainable supplier selection based on Industry 4.0 concept,” Environmental science and

pollution research, pp. 1–19, 2021.

[8] S. Kusi-Sarpong, H. Gupta, S. A. Khan, C. J. Chiappetta Jabbour, S. T. Rehman, and H. Kusi-Sarpong,

“Sustainable supplier selection based on industry 4.0 initiatives within the context of circular economy

implementation in supply chain operations,” Production Planning & Control, pp. 1–21, 2021.

[9] J. Fitzgerald and E. Quasney, “Using autonomous robots to drive supply chain innovation,” Deloitte

Perspectives, vol. 1, p. 12, 2017.

[10] A. . Awwad, M.; Kulkarni, P.; Bapna, R.; Marathe, “Big data analytics in supply chain: a literature review.,”

in In Proceedings of the international conference on industrial engineering and operations management, 2018, pp.


[11] Y. Zhan, L. Chung, M. K. Lim, F. Ye, A. Kumar, and K. H. Tan, “The impact of sustainability on supplier

selection: A behavioural study,” International Journal of Production Economics, vol. 236, p. 108118, 2021.

[12] I. O. Raji, E. Shevtshenko, T. Rossi, and F. Strozzi, “Industry 4.0 technologies as enablers of lean and agile

supply chain strategies: an exploratory investigation,” The International Journal of Logistics Management, 2021.

[13] G. Büyüközkan and F. Göçer, “Digital Supply Chain: Literature review and a proposed framework for future

research,” Computers in Industry, vol. 97, pp. 157–177, 2018.

[14] M. Moufaddal, A. Benghabrit, and I. Bouhaddou, “Industry 4.0: A roadmap to digital Supply Chains,” in

2019 1st International Conference on Smart Systems and Data Science (ICSSD), 2019, pp. 1–9.

[15] M. M. Hasan, D. Jiang, A. M. M. S. Ullah, and M. Noor-E-Alam, “Resilient supplier selection in logistics

4.0 with heterogeneous information,” Expert Systems with Applications, vol. 139, p. 112799, 2020.

[16] N. Jain, A. R. Singh, and R. K. Upadhyay, “Sustainable supplier selection under attractive criteria through

FIS and integrated fuzzy MCDM techniques,” International Journal of Sustainable Engineering, vol. 13, no. 6, pp.

441–462, 2020.

[17] N. A. Nabeeh, M. Abdel-Basset, and G. Soliman, “A model for evaluating green credit rating and its impact

on sustainability performance,” Journal of Cleaner Production, vol. 280, p. 124299, 2021.

[18] N. Zhang, W. Su, C. Zhang, and S. Zeng, “Evaluation and selection model of community group purchase

platform based on WEPLPA-CPT-EDAS method,” Computers & Industrial Engineering, p. 108573, 2022.

[19] F. Lei, G. Wei, W. Shen, and Y. Guo, “PDHL-EDAS method for multiple attribute group decision making

and its application to 3D printer selection,” Technological and Economic Development of Economy, vol. 28, no. 1, pp.

179–200, 2022.

[20] A. R. Mishra, S.-M. Chen, and P. Rani, “Multiattribute decision making based on Fermatean hesitant fuzzy

sets and modified VIKOR method,” Information Sciences, vol. 607, pp. 1532–1549, 2022.

[21] D. Abdul, J. Wenqi, and A. Tanveer, “Prioritization of renewable energy source for electricity generation

through AHP-VIKOR integrated methodology,” Renewable Energy, vol. 184, pp. 1018–1032, 2022.

[22] P. Sathiyamoorthi and H. S. Kim, “High-entropy alloys with heterogeneous microstructure: processing and

mechanical properties,” Progress in Materials Science, vol. 123, p. 100709, 2022.

[23] Y. Zhang, D. Wang, and S. Wang, “High‐Entropy Alloys for Electrocatalysis: Design, Characterization, and

Applications,” Small, vol. 18, no. 7, p. 2104339, 2022.

[24] A. M. Fathollahi-Fard, L. Woodward, and O. Akhrif, “Sustainable distributed permutation flow-shop

scheduling model based on a triple bottom line concept,” Journal of Industrial Information Integration, vol. 24, p.

100233, 2021.

[25] N. Ghadami et al., “Implementation of solar energy in smart cities using an integration of artificial neural

network, photovoltaic system and classical Delphi methods,” Sustainable Cities and Society, vol. 74, p. 103149, 2021.

[26] M. Schöll, “Three Essays on Sustainable Supply Chain Management–Towards Sustainable Supplier

Selection and Sustainable Sourcing,” 2017.

[27] R. Lueg and R. Radlach, “Managing sustainable development with management control systems: A literature

review,” European Management Journal, vol. 34, no. 2, pp. 158–171, 2016.

[28] B. L. Golden, E. A. Wasil, and P. T. Harker, “The analytic hierarchy process,” Applications and Studies,

Berlin, Heidelberg, vol. 2, 1989.

[29] C.-L. Hwang, Y.-J. Lai, and T.-Y. Liu, “A new approach for multiple objective decision making,”

Computers & operations research, vol. 20, no. 8, pp. 889–899, 1993.

[30] K. Shahroudi and S. M. S. Tonekaboni, “Application of TOPSIS method to supplier selection in Iran auto

supply chain,” Journal of Global Strategic Management, vol. 6, no. 2, pp. 123–131, 2012.

[31] R. Şahin and M. Yiğider, “A Multi-criteria neutrosophic group decision making metod based TOPSIS for

supplier selection,” arXiv preprint arXiv:1412.5077, 2014.

[32] J. Gan, S. Zhong, S. Liu, and D. Yang, “Resilient supplier selection based on fuzzy BWM and GMo-

RTOPSIS under supply chain environment,” Discrete Dynamics in Nature and Society, vol. 2019, 2019.

[33] M. Abdel-Basset, A. Gamal, R. K. Chakrabortty, and M. J. Ryan, “Evaluation of sustainable hydrogen

production options using an advanced hybrid MCDM approach: A case study,” International Journal of Hydrogen

Energy, vol. 46, no. 5, pp. 4567–4591, 2021.

[34] M. Abdel-Basset, A. Gamal, N. Moustafa, A. Abdel-Monem, and N. El-Saber, “A Security-by-Design

Decision-Making Model for Risk Management in Autonomous Vehicles,” IEEE Access, 2021.

Cite this Article as :
Mahmoud Ismail , Mahmoud Ibrahiem, Multi-Criteria Decision-Making Approach based on Neutrosophic Sets for Evaluating Sustainable Supplier Selection in the Industrial 4.0, American Journal of Business and Operations Research, Vol. 7 , No. 2 , (2022) : 41-55 (Doi   :  https://doi.org/10.54216/AJBOR.070204)