A Bibliometric Analysis of Material Selection Using MCDM Methods: Trends and Insights

Sushil Kumar Sahoo; Bibhuti Bhusan Choudhury; Prasant Ranjan Dhal

doi:10.31181/smeor11202417

Authors

Sushil Kumar Sahoo Department of Mechanical Engineering, Indira Gandhi Institute of Technology (BPUT, Rourkela), Sarang, Dhenkanal, Odisha, India Author https://orcid.org/0000-0002-8551-7353
Bibhuti Bhusan Choudhury Department of Mechanical Engineering, Indira Gandhi Institute of Technology (BPUT, Rourkela), Sarang, Dhenkanal, Odisha, India Author https://orcid.org/0000-0002-2990-3911
Prasant Ranjan Dhal Department of Mechanical Engineering, Indira Gandhi Institute of Technology (BPUT, Rourkela), Sarang, Dhenkanal, Odisha, India Author https://orcid.org/0000-0002-7402-2187

DOI:

https://doi.org/10.31181/smeor11202417

Keywords:

Bibliometric Analysis, MCDM, Material selection, VOSviewer, Science Mapping

Abstract

The selection of appropriate materials is a critical decision-making process in engineering, impacting both performance and sustainability. Multi-Criteria Decision-Making (MCDM) methods have become increasingly popular for navigating the complex trade-offs involved in material selection. This study presents a comprehensive bibliometric analysis of research on material selection using MCDM methods, covering publications from 2010 to 2024. Using tools like VOSviewer 1.6.20, this analysis identifies key trends, influential authors, prominent institutions, and geographic distribution of research contributions. The findings reveal a significant growth in publications, particularly after 2010, reflecting the expanding recognition of MCDM’s importance in material selection processes. Notable contributors, including key researchers and leading institutions, have shaped the field through high-impact studies. The geographic analysis highlights a strong concentration of research in regions such as Asia and Europe, underscoring their leadership in advancing MCDM methodologies. This paper provides valuable insights into the evolution of material selection research using MCDM, offering a foundation for future studies and applications in engineering and beyond.

Downloads

Download data is not yet available.

References

Emovon, I., & Oghenenyerovwho, O. S. (2020). Application of MCDM method in material selection for optimal design: A review. Results in Materials, 7, 100115. https://doi.org/10.1016/j.rinma.2020.100115

Calderón, A., Torres-Rivas, A., Fernández, A. I., & Boer, D. (2024). Simulation tools to assist material choice. In Materials Selection for Sustainability in the Built Environment (pp. 267-297). Woodhead Publishing. https://doi.org/10.1016/B978-0-323-95122-7.00013-7

Sahoo, S. K., & Choudhury, B. B. (2023). Evaluating Material Alternatives for low cost Robotic Wheelchair Chassis: A Combined CRITIC, EDAS, and COPRAS Framework. Jordan Journal of Mechanical & Industrial Engineering, 17(4). https://doi.org/10.59038/jjmie/170419

Nagaraju, S. B., Priya, H. C., Girijappa, Y. G. T., & Puttegowda, M. (2023). Lightweight and sustainable materials for aerospace applications. In Lightweight and Sustainable Composite Materials (pp. 157-178). Woodhead Publishing. https://doi.org/10.1016/B978-0-323-95189-0.00007-X

Kökçam, A. H., Erden, C., Demir, A. S., & Kurnaz, T. F. (2024). Bibliometric analysis of artificial intelligence techniques for predicting soil liquefaction: insights and MCDM evaluation. Natural Hazards, 1-29. https://doi.org/10.1007/s11069-024-06630-0

Srivastava, S., Tripathi, A., & Arora, N. (2024). Multi-criteria decision making (MCDM) in diverse domains of education: a comprehensive bibliometric analysis for research directions. International Journal of System Assurance Engineering and Management, 1-18. https://doi.org/10.1007/s13198-024-02332-9

Demir, G., Chatterjee, P., & Pamucar, D. (2024). Sensitivity analysis in multi-criteria decision making: A state-of-the-art research perspective using bibliometric analysis. Expert Systems with Applications, 237, 121660. https://doi.org/10.1016/j.eswa.2023.121660

Rocha, C. M. M., Benitez, A. S., & Buelvas, D. A. (2024). Review and Bibliographic Analysis of Metaheuristic Methods in Multicriteria Decision‐Making: A 45‐Year Perspective Across International, Latin American, and Colombian Contexts. Journal of Applied Mathematics, 2024(1), 5577682. https://doi.org/10.1155/2024/5577682

Nirmal, D. D., Nageswara Reddy, K., & Singh, S. K. (2024). Application of fuzzy methods in green and sustainable supply chains: critical insights from a systematic review and bibliometric analysis. Benchmarking: An International Journal, 31(5), 1700-1748. https://doi.org/10.1108/BIJ-09-2022-0563

Khulud, K., Masudin, I., Zulfikarijah, F., Restuputri, D. P., & Haris, A. (2023). Sustainable Supplier Selection through Multi-Criteria Decision Making (MCDM) Approach: A Bibliometric Analysis. Logistics, 7(4), 96. https://doi.org/10.3390/logistics7040096

Vatankhah, S., Darvishmotevali, M., Rahimi, R., Jamali, S. M., & Ale Ebrahim, N. (2023). MCDM in travel and tourism research since 1997: A bibliometric approach. International Journal of Contemporary Hospitality Management. http://dx.doi.org/10.2139/ssrn.4324990

Sahin, S. N. A. (2023). A Systematic Overview of Decision-Making on Public Transport Systems Using Bibliometric Analysis on Vosviewer. Transport and Telecommunication Journal, 24(4), 459-470. DOI 10.2478/ttj-2023-0036

Delcea, C., Domenteanu, A., Ioanăș, C., Vargas, V. M., & Ciucu-Durnoi, A. N. (2023). Quantifying Neutrosophic Research: A Bibliometric Study. Axioms, 12(12), 1083. https://doi.org/10.3390/axioms12121083

Raza, S. A., Govindaluri, S. M., & Bhutta, M. K. (2023). Research themes in machine learning applications in supply chain management using bibliometric analysis tools. Benchmarking: An International Journal, 30(3), 834-867. https://doi.org/10.1108/BIJ-12-2021-0755

Pereira, V., & Bamel, U. (2023). Charting the managerial and theoretical evolutionary path of AHP using thematic and systematic review: a decadal (2012–2021) study. Annals of Operations Research, 326(2), 635-651. https://doi.org/10.1007/s10479-022-04540-7

Calleo, Y., & Pilla, F. (2023). Delphi-based future scenarios: a bibliometric analysis of climate change case studies. Futures, 149, 103143. https://doi.org/10.1016/j.futures.2023.103143

Ayan, B., & Abacıoğlu, S. (2022). Bibliometric analysis of the MCDM methods in the last decade: WASPAS, MABAC, EDAS, CODAS, COCOSO, and MARCOS. International Journal of Business and Economic Studies, 4(2), 65-85. https://doi.org/10.54821/uiecd.1183443

Girardi, R., Galdino, J. F., Pellanda, P. C., Junior, J. A. F., & dos Santos, M. (2022). Bibliometric study on multi-criteria decision-making methods applied to life cycle management of defense systems. Procedia Computer Science, 214, 236-247. https://doi.org/10.1016/j.procs.2022.11.171

Costa, I. P. D. A., Costa, A. P. D. A., Sanseverino, A. M., Gomes, C. F. S., & Santos, M. D. (2022). Bibliometric studies on multi-criteria decision analysis (MCDA) methods applied in military problems. Pesquisa Operacional, 42, e249414. https://doi.org/10.1590/0101-7438.2022.042.00249414

Dai, Z., Xu, S., Wu, X., Hu, R., Li, H., He, H., & Liao, X. (2022). Knowledge mapping of multicriteria decision analysis in healthcare: a bibliometric analysis. Frontiers in Public Health, 10, 895552. https://doi.org/10.3389/fpubh.2022.895552

Castelló-Sirvent, F., Meneses-Eraso, C., Alonso-Gómez, J., & Peris-Ortiz, M. (2022). Three decades of fuzzy AHP: A bibliometric analysis. Axioms, 11(10), 525. https://doi.org/10.3390/axioms11100525

Barcellos‐Paula, L., de La Vega, I., & Gil‐Lafuente, A. M. (2022). Bibliometric review of research on decision models in uncertainty, 1990–2020. International Journal of Intelligent Systems, 37(10), 7300-7333. https://doi.org/10.1002/int.22882

McAllister, J. T., Lennertz, L., & Atencio Mojica, Z. (2022). Mapping a discipline: a guide to using VOSviewer for bibliometric and visual analysis. Science & Technology Libraries, 41(3), 319-348. https://doi.org/10.1080/0194262X.2021.1991547

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

Basílio, M. P., Pereira, V., Costa, H. G., Santos, M., & Ghosh, A. (2022). A systematic review of the applications of multi-criteria decision aid methods (1977–2022). Electronics, 11(11), 1720. https://doi.org/10.3390/electronics11111720

Fagundes, M. V. C., Teles, E. O., de Melo, S. A. V., & Freires, F. G. M. (2020). Decision-making models and support systems for supply chain risk: literature mapping and future research agenda. European Research on Management and Business Economics, 26(2), 63-70. https://doi.org/10.1016/j.iedeen.2020.02.001

Wang, X., Xu, Z., & Qin, Y. (2022). Structure, trend and prospect of operational research: a scientific analysis for publications from 1952 to 2020 included in Web of Science database. Fuzzy Optimization and Decision Making, 21(4), 649-672. https://doi.org/10.1007/s10700-021-09380-x

Amirkhani, M., Martek, I., & Luther, M. B. (2021). Mapping research trends in residential construction retrofitting: A scientometric literature review. Energies, 14(19), 6106. https://doi.org/10.3390/en14196106

Sahoo, S. K., Choudhury, B. B., & Dhal, P. R. (2024). Exploring the Role of Robotics in Maritime Technology: Innovations, Challenges, and Future Prospects. Spectrum of Mechanical Engineering and Operational Research, 1(1), 159-176. https://doi.org/10.31181/smeor11202414

Qiu, J. P., Dong, K., & Yu, H. Q. (2014). Comparative study on structure and correlation among author co-occurrence networks in bibliometrics. Scientometrics, 101, 1345-1360. https://doi.org/10.1007/s11192-014-1315-6

Smolinsky, L., & Lercher, A. J. (2020). Co-author weighting in bibliometric methodology and subfields of a scientific discipline. Journal of Data and Information Science, 5(3), 84-96. https://doi.org/10.2478/jdis-2020-0021

Ülker, P., Ülker, M., & Karamustafa, K. (2023). Bibliometric analysis of bibliometric studies in the field of tourism and hospitality. Journal of Hospitality and Tourism Insights, 6(2), 797-818. https://doi.org/10.1108/JHTI-10-2021-0291

Zupic, I., & Čater, T. (2015). Bibliometric methods in management and organization. Organizational research methods, 18(3), 429-472. https://doi.org/10.1177/1094428114562629

Sahoo, S. K., Goswami, S. S., Sarkar, S., & Mitra, S. (2023). A review of digital transformation and industry 4.0 in supply chain management for small and medium-sized enterprises. Spectrum of Engineering and Management Sciences, 1(1), 58-72. https://doi.org/10.31181/sems1120237j

Bindu, N., Sankar, C. P., & Kumar, K. S. (2019). Research collaboration and knowledge sharing in e-governance: Temporal analysis of co-author network. Transforming Government: People, Process and Policy, 13(1), 2-33. https://doi.org/10.1108/TG-03-2018-0022

Derviş, H. (2019). Bibliometric analysis using bibliometrix an R package. Journal of scientometric research, 8(3), 156-160. DOI: 10.5530/jscires.8.3.32

Al-Gerafi, M. A., Goswami, S. S., Sahoo, S. K., Kumar, R., Simic, V., Bacanin, N., & Lasisi, A. (2024). Promoting inclusivity in education amid the post-COVID-19 challenges: An interval-valued fuzzy model for pedagogy method selection. The International Journal of Management Education, 22(3), 101018. https://doi.org/10.1016/j.ijme.2024.101018

Shah, S. H. H., Lei, S., Ali, M., Doronin, D., & Hussain, S. T. (2020). Prosumption: bibliometric analysis using HistCite and VOSviewer. Kybernetes, 49(3), 1020-1045. https://doi.org/10.1108/K-12-2018-0696

Sahoo, S. K., & Goswami, S. S. (2024). Green supplier selection using MCDM: A comprehensive review of recent studies. Spectrum of Engineering and Management Sciences, 2(1), 1-16. https://doi.org/10.31181/sems1120241a

Martins, J., Gonçalves, R., & Branco, F. (2022). A bibliometric analysis and visualization of e-learning adoption using VOSviewer. Universal Access in the Information Society, 1-15. https://doi.org/10.1007/s10209-022-00953-0

Jia, C., & Mustafa, H. (2022). A bibliometric analysis and review of nudge research using VOSviewer. Behavioral Sciences, 13(1), 19. https://doi.org/10.3390/bs13010019