Current Science

Open Access Open Access  Restricted Access Subscription Access

A Bibliometric Analysis of Research on Multiple Criteria Decision Making


Affiliations
1 School of Information, Zhejiang University of Finance and Economics, Hangzhou, Zhejiang 310 018, China
 

In this study, publications in the multiple criteria decision making (MCDM) field during 1977–2016 were analysed using bibliometric analysis. The statistical analysis of influential publications, journals, countries/territories and authors was first conducted. The developing trends of authors’ collaborative structure and research topics were then analysed based on four different periods. The results indicated that more number of publications and authors contributed to MCDM research in the last ten years, and that the collaboration among authors has increased. The comprehensive and scientific analysis of MCDM should help researchers conduct studies in related fields.

Keywords

Bibliometrics, Multiple Criteria Decision Making, Multiple Attribute Decision Making, Social Network Analysis, VOSviewer.
User
Notifications
Font Size

  • Zavadskas, E. K., Turskis, Z. and Kildienė, S., State of art surveys of overviews on MCDM/MADM methods. Technol. Econ. Dev. Eco., 2014, 20, 165–179.

  • Bernroider, E. and Stix, V., A method using weight restrictions in data envelopment analysis for ranking and validity issues in decision making. Comput. Oper. Res., 2007, 34, 2637–2647.

  • Liao, H. C., Xu, Z. S. and Zeng, X. J., Hesitant fuzzy linguistic VIKOR method and its application in qualitative multiple criteria decision making. IEEE Trans. Fuzzy. Syst., 2015, 23, 1343–1355.

  • Zadeh, L. A., Fuzzy sets. Inf. Control, 1965, 8, 338–353.

  • Zadeh, L. A., The concept of a linguistic variable and its application to approximate reasoning, part I. Inf. Sci., 1975, 8, 199–249.

  • Atanassov, K. T., Intuitionistic fuzzy sets. Fuzzy Sets Syst., 1986, 20, 87–96.

  • Xu, Z. S., Intuitionistic fuzzy aggregation operator. IEEE Trans. Fuzzy Syst., 2007, 15, 1179–1187.

  • Xu, Z. S. and Xia, M. M., Distance and similarity measures for hesitant fuzzy sets. Inf. Sci., 2011, 181, 2128–2138.

  • Yu, D. J., Intuitionistic fuzzy information aggregation under confidence levels. Appl. Soft Comput., 2014, 19, 147–160.

  • Xu, Z. S., Yager, R. R., Some geometric aggregation operators based on intuitionistic fuzzy sets. Int. J. Gen. Syst., 2006, 35, 417–433.

  • Liao, H. C. and Xu, Z. S., Intuitionistic fuzzy hybrid weighted aggregation operators. Int. J. Int. Syst., 2014, 29, 971–993.

  • Yu, D. J., Zhang, W. Y. and Huang, G., Dual hesitant fuzzy aggregation operators. Technol. Econ. Dev. Econ., 2016, 22, 194–209.

  • Liang, D. C., Xu, Z. S. and Liu, D., Three-way decisions with intuitionistic fuzzy decision-theoretic rough sets based on point operators. Inf. Sci., 2017, 375, 183–201.

  • Liang, D. C., Xu, Z. S. and Liu, D., Three-way decisions based on decision-theoretic rough sets with dual hesitant fuzzy information. Inf. Sci., 2017, 396, 127–143.

  • Zhou, W. and Xu, Z. S., Asymmetric hesitant fuzzy sigmoid preference relations in the analytic hierarchy process. Inf. Sci., 2016, 358, 191–207.

  • Zeng, S. Z., Merigo, J. M. and Palacios-Marques, D., Intuitionistic fuzzy induced ordered weighted averaging distance operator and its application to decision making. J. Intell. Fuzzy Syst., 2017, 32, 11–22.

  • Wang, H. and Xu, Z. S., Admissible orders of typical hesitant fuzzy elements and their application in ordered information fusion in multi-criteria decision making. Inform. Fusion, 2016, 29, 98–104.

  • Zhou, W. and Xu, Z. S., Generalized asymmetric linguistic term set and its application to qualitative decision making involving risk appetites. Eur. J. Oper. Res., 2016, 254, 610–621.

  • Yu, D. J., Hesitant fuzzy multi-criteria decision making methods based on Heronian mean. Technol. Econ. Dev. Econ., 2017, 23, 296–315.

  • Xu, Z. S., A method based on linguistic aggregation operators for group decision making with linguistic preference relations. Inf. Sci., 2004, 166, 19–30.

  • Yu, D. J., Group decision making based on generalized intuitionistic fuzzy prioritized geometric operator. Int. J. Intell. Syst., 2012, 27, 635–661.

  • Zeng, S. Z., Palacios-Marques, D. and Zhu, F. C., A new model for interactive group decision making with intuitionistic fuzzy preference relations. Informatica, 2016, 27, 911–928.

  • Yu, D. J., Zhang, W. Y. and Xu, Y. J., Group decision making under hesitant fuzzy environment with application to personnel evaluation. Knowl.-Based Syst., 2013, 52, 1–10.

  • Xu, Z. S., Uncertain linguistic aggregation operators based approach to multiple attribute group decision making under uncertain linguistic environment. Inf. Sci., 2004, 168, 171–184.

  • Xu, Y., Merigo, J. M. and Wang, H., Linguistic power aggregation operators and their application to multiple attribute group decision making. Appl. Math. Model., 2012, 36, 5427–5444.

  • Wang, H. and Xu, Z. S., Multi groups decision making using intuitionistic-valued hesitant fuzzy information. Int. J. Innov. Comput. Intell. Fuzzy Syst., 2016, 9, 468–482.

  • Pritchard, A., Statistical bibliography or bibliometrics. J. Doc., 1969, 25, 348–349.

  • Elango, B. and Ho, Y. S., A bibliometric analysis of highly cited papers from India in Science Citation Index Expanded. Curr. Sci., 2017, 112, 1653–1658.

  • Merigo, J. M., Gil-Lafuente, A. M. and Yager, R. R., An overview of fuzzy research with bibliometric indicators. Appl. Soft Comput., 2015, 27, 420–433.

  • Yu, H., Zhi, Z., Zhang, C. and Yang, H., Research on literature involving zirconia-based on Pubmed database: a bibliometric analysis. Curr. Sci., 2017, 112, 1134–1137.

  • Small, H., Co-citation in the scientific literature: a new measure of the relationship between two documents. J. Am. Soc. Inf. Sci., 1973, 24, 265–269.

  • Callon, M., Courtial, J. P., Turner, W. A. and Bauin, S., From translations to problematic networks: an introduction to co-word analysis. Soc. Sci. Inf., 1983, 22, 191–235.

  • Yu, D. J., A scientometrics review on aggregation operator research. Scientometrics, 2015, 105, 115–133.

  • Zhang, L. and Feng, Y., Bibliometrics and visualization analysis of artificial blood vessel research. Curr. Sci., 2014, 106, 816–822.

  • Yu, D. J. and Shi, S. S., Researching the development of Atanassov intuitionistic fuzzy set: using a citation network analysis. Appl. Soft Comput., 2015, 32, 189–198.

  • Van Eck, N. J. and Waltman, L., Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 2010, 84, 523–538.

  • Van Eck, N. J. and Waltman, L., Visualizing bibliometric networks. In Springer International Publishing, Measuring Scholarly Impact, 2014, pp. 285–320.

  • Opricovic, S. and Tzeng, G. H., Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. Eur. J. Oper. Res., 2004, 156, 445–455.

  • Herrera, F. and Herrera-Viedma, E., Linguistic decision analysis: steps for solving decision problems under linguistic information. Fuzzy Sets Syst., 2000, 115, 67–82.

  • Vaidya, O. S. and Kumar, S., Analytic hierarchy process: an overview of applications. Eur. J. Oper. Res., 2006, 169, 1–29.

  • Shih, H. S., Shyur, H. J. and Lee, E. S., An extension of TOPSIS for group decision making. Math. Comput. Model, 2007, 45, 801–813.

  • Wang, Y. M. and Elhag, T. M. S., Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment. Exp. Syst. Appl., 2006, 31, 309–319.

  • Wang, T. C. and Chang, T. H., Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment. Exp. Syst. Appl., 2007, 33, 870–880.

  • Chan, F. T. S. and Kumar, N., Global supplier development considering risk factors using fuzzy extended AHP-based approach. Omega, 2007, 35, 417–431.

  • Lee, J. W. and Kim, S. H., Using analytic network process and goal programming for interdependent information system project selection. Comput. Oper. Res., 2000, 27, 367–382.

  • Pohekar, S. D. and Ramachandran, M., Application of multi-criteria decision making to sustainable energy planning – a review. Renew. Sust. Energ. Rev., 2004, 8, 365–381.

  • Wang, J. J., Jing, Y. Y., Zhang, C. F. and Zhao, J. H., Review on multi-criteria decision analysis aid in sustainable energy decision-making. Renew. Sust. Energ. Rev., 2009, 13, 2263–2278.

  • Ho, W., Xu, X. and Dey, P. K., Multi-criteria decision making approaches for supplier evaluation and selection: a literature review. Eur. J. Oper. Res., 2010, 202, 16–24.

  • Walle Wallenius, J., Dyer, J. S., Fishburn, P. C., Steuer, R. E., Zionts, S. and Deb, K., Multiple criteria decision making, multiattribute utility theory: recent accomplishments and what lies ahead. Manage. Sci., 2008, 54, 1336–1349.

  • Carlsson, C. and Fullér, R., Fuzzy multiple criteria decision making: recent developments. Fuzzy Sets Syst., 1996, 78, 139–153.


Abstract Views: 381

PDF Views: 141




  • A Bibliometric Analysis of Research on Multiple Criteria Decision Making

Abstract Views: 381  |  PDF Views: 141

Authors

Dejian Yu
School of Information, Zhejiang University of Finance and Economics, Hangzhou, Zhejiang 310 018, China
Wanru Wang
School of Information, Zhejiang University of Finance and Economics, Hangzhou, Zhejiang 310 018, China
Wenyu Zhang
School of Information, Zhejiang University of Finance and Economics, Hangzhou, Zhejiang 310 018, China
Shuai Zhang
School of Information, Zhejiang University of Finance and Economics, Hangzhou, Zhejiang 310 018, China

Abstract


In this study, publications in the multiple criteria decision making (MCDM) field during 1977–2016 were analysed using bibliometric analysis. The statistical analysis of influential publications, journals, countries/territories and authors was first conducted. The developing trends of authors’ collaborative structure and research topics were then analysed based on four different periods. The results indicated that more number of publications and authors contributed to MCDM research in the last ten years, and that the collaboration among authors has increased. The comprehensive and scientific analysis of MCDM should help researchers conduct studies in related fields.

Keywords


Bibliometrics, Multiple Criteria Decision Making, Multiple Attribute Decision Making, Social Network Analysis, VOSviewer.

References





DOI: https://doi.org/10.18520/cs%2Fv114%2Fi04%2F747-758