The group decision-making (GDM) is a process of aggregating the preference information of each decision maker in a group into a collective opinion under certain decision criteria. When a decision is made by decision makers (DMs), the group decision or group opinion is a result of the integration of the individual opinions by a mathematical aggregation. An important thing in the integration of the individual opinions is which DMs’ opinions should be of importance in the aggregation process. The group opinion is heavily influenced by the level of expertise of the DMs. In real-life group decision making (GDM) problems, preference relations given by decision makers (DMs) are often heterogeneous because of their expertise and different decision habits. The expertise level of the DMs can be estimated using the ‘the ability to differentiate consistently’, a ratio between discrimination and inconsistency. Each expert has different expertise in different criteria and has his/her limited capacity in constructing of pairwise comparison preference relations. In this paper, we focus on a method to assess expertise-based ranking of experts in GDM with multiple criteria and different preference representation formats. The combination of expertise as ‘the ability to differentiate consistently’ and the consistency of various types of preference relations is discussed, when experts give their judgements for alternatives in various types of preference relations, such as multiplicative preference relations (MPRs), utility values, preference orderings, even incomplete FPRs or MPRs, including FPRs under certain criterion. Then, since the experts have the limited capacity in constructing of pairwise comparison preference relations in GDM with multiple criteria, we propose a expertise-based ranking method using the adjacent pairwise comparison technique in order to reduce the number of judgements. Finally, expertise-based ranking of experts is applied to aggregate the individual opinions into a group opinion by developing into experts’ importance weights in GDM. Numerical analyses show that proposed method is simple than the previous methods and can fill up some gaps in GDM.
| Published in | American Journal of Engineering and Technology Management (Volume 10, Issue 5) |
| DOI | 10.11648/j.ajetm.20251005.11 |
| Page(s) | 69-83 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2025. Published by Science Publishing Group |
Group Decision Making, Ranking, Heterogeneous Preference Relations, Expertise
| [1] | D. J. Weiss, J. Shanteau, Empirical assessment of expertise, Hum. Factors 45(1) (2003) 104–116. |
| [2] | J. Shanteau, D. J. Weiss, R. P. Thomas, J. C. Pounds, Performance-based assessment of expertise: how to decide if someone is an expert or not?, Eur. J. Oper. Res. 136(2) (2002) 253-263. |
| [3] | E. Herowati, U. Ciptomulyono, J. Parung, Suparno, Expertise-based ranking of experts: An assessment level approach, Fuzzy Sets Syst. 315 (2017) 44-56. |
| [4] | V. Malhotra, M. D. Lee, A. Khurana, Domain experts influence decision quality: towards a robust method for their identification, J. Pet. Sci. Eng. 57(1–2) (2007) 181–194. |
| [5] | Michael D. Lee, Mark Steyvers, M. d. Young, B. Miller, Inferring expertise in knowledge and prediction ranking tasks, Top. Cogn. Sci. 4(1) (2012) 151–163. |
| [6] | F. Chiclana, E. Herrera-Viedma, F. Herrera, S. Alonso, Some induced ordered weighted averaging operators and their use for solving group decision making problems based on fuzzy preference relations, Eur. J. Oper. Res. 182(1) (2007) 383–399. |
| [7] | E. Herrera-Viedma, F. Chiclana, F. Herrera, S. Alonso, Group decision-making model with incomplete fuzzy preference relations based on additive consistency, IEEE Trans. Syst. Man Cybern. B 37(1) (2007) 176–189. |
| [8] | E. Herrera-Viedma, F. Herrera, F. Chiclana, M. Luque, Some issues on consistency of fuzzy preference relations, Eur. J. Oper. Res. 154(1) (2004) 98–109. |
| [9] | S. Alonso, F. Chiclana, F. Herrera, E. Herrera-Viedma, J. Alcal’a-Fdez, C. Porcel, A consistency-based procedure to estimate missing pairwise preference values, Int. J. Intell. Syst. 23(2) (2008) 155–175. |
| [10] | S. Alonso, F. J. Cabrerizo, F. Chiclana, F. Herrera, E. Herrera-Viedma, Group decision making with incomplete fuzzy linguistic preference relations, Int. J. Intell. Syst. 24(2) (2009) 201–222. |
| [11] | G. Zhang, Y. Dong, Y. Xu, Linear optimization modeling of consistency issues in group decision making based on fuzzy preference relations, Expert Syst. Appl. 39(3) (2012) 2415–2420. |
| [12] | G. Kou, Y. Peng, X. R Chao, E. Herrera-Viedma, F. E. Alsaadi, A geometrical method for consensus building in GDM with incomplete heterogeneous preference information, Appl. Soft Comput. 105 (2021). |
| [13] | E. Herowati, U. Ciptomulyono, J. Parung, Suparno, Expertise-based experts importance weights in adverse judgment, J. Eng. Appl. Sci. 9(9) (2014). |
| [14] | F. Chiclana, F. Herrera, E. Herrera-Viedma, Integrating three representation models in fuzzy multipurpose decision making based on fuzzy preference relations, Fuzzy Sets Syst. 97(1) (1998) 33–48. |
| [15] | L. Mikhailov, Deriving priorities from fuzzy pairwise comparison judgements, Fuzzy Sets Syst. 134 (2003) 365–385. |
| [16] | A. Khalid, I. Beg, Incomplete interval valued fuzzy preference relations, Inform. Sci. 348 (2016) 15–24. |
| [17] | S. P. Wan, D. F. Li, Fuzzy LINMAP approach to heterogeneous MADM considering comparisons of alternatives with hesitation degrees, Omega 41 (2013) 925–940. |
| [18] | Y. J. Xu, R. Patnayakuni, H. M. Wang, A method based on mean deviation for weight determination from fuzzy preference relations and multiplicative preference relations, Int. J. Inform. Technol. Decis. Mak. 11 (2012) 627–641. |
| [19] | Z. S. Xu, X. Q. Cai, S. S. Liu, Nonlinear programming model integrating different preference formats, IEEE Trans. Syst. Man Cybern. A 41 (2011) 169–177. |
| [20] | E. Herrera-Viedma, F. Herrera, F. Chiclana, A consensus model for multiperson decision-making with different preference formats, IEEE Trans. Syst. Man, Cybern. A 32 (2002) 394–402. |
| [21] | P. Xie, J. Wu, H. Du, The relative importance of competition to contagion: evidence from the digital currency market, Financial Innov. 5(1) (2019) 41. |
| [22] | F. Y. Meng, X. Chen, An approach to incomplete multiplicative preference relations and its application in GDM, Inform. Sci. 309 (2015) 119–137. |
| [23] | G. Kou, D. Ergu, C. S. Lin, Y. Chen, Pairwise comparison matrix in multiple criteria decision making, Technol. Econ. Dev. Econ. 22 (2016) 738–765. |
| [24] | T. L. Saaty, The Analytic Hierarchy Process, McGraw-Hill, New York, USA, 1980. |
| [25] | F. Herrera, E. Herrera-Viedma, F. Chiclana, Multiperson decision-making based on multiplicative preference relations, European J. Oper. Res. 129 (2001) 372–385. |
| [26] | A. O. Efe, Utility representation of an incomplete preference relation. J. Econ Theory, 104 (2002) 429-449. |
| [27] | F. Herrera et al, A consensus model for group decision making with incomplete fuzzy preference relations. IEEE Trans. Syst. 15(5) (2007) 863–877. |
| [28] | A. Shemshadi, H. Shirazi, M. Toreihi, M. J. Tarokh, A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting. Expert Syst. Appl. 38 (2011) 12160–12167. |
| [29] | Z. Mahdi, S. Ferenc, Multicriteria Analysis: Application to water and environment management. Springer, Verlag Berlin Heidelberg, 2011. |
| [30] | D. Cheng, Z. Zhou, F. Cheng, J. Wang, Deriving heterogeneous experts weights from incomplete linguistic preference relations based on uninorm consistency, Knowl. Based Syst. 150 (2018) 150–165. |
| [31] | C. Li, R. M. Rodríguez, L. Martínez, Y. C. Dong, F. Herrera, Consistency of hesitant fuzzy linguistic preference relations: An interval consistency index, Inform. Sci. 432 (2018) 347–361. |
| [32] | Senapati T, Yager RR, Fermatean fuzzy sets. J Amb Intell Hum Comput 11(2) (2020) 663–674. |
| [33] | R. Wang, Y. L. Li, A novel approach for group decision-making from intuitionistic fuzzy preference relations and intuitionistic multiplicative preference relations. Inform. 9(55) (2018); |
| [34] | H. M. Li, Y. C. Cao, L. M. Su, Q. Xia, An interval Pythagorean fuzzy multi-criteria decision making method based on similarity measures and connection numbers. Inform. 10(80) (2019); |
APA Style
Sim, S., Kim, S. (2025). Expertise-Based Ranking of Experts in Multicriteria Group Decision Making with Different Preference Representation Formats. American Journal of Engineering and Technology Management, 10(5), 69-83. https://doi.org/10.11648/j.ajetm.20251005.11
ACS Style
Sim, S.; Kim, S. Expertise-Based Ranking of Experts in Multicriteria Group Decision Making with Different Preference Representation Formats. Am. J. Eng. Technol. Manag. 2025, 10(5), 69-83. doi: 10.11648/j.ajetm.20251005.11
@article{10.11648/j.ajetm.20251005.11,
author = {SongHo Sim and SinHyok Kim},
title = {Expertise-Based Ranking of Experts in Multicriteria Group Decision Making with Different Preference Representation Formats
},
journal = {American Journal of Engineering and Technology Management},
volume = {10},
number = {5},
pages = {69-83},
doi = {10.11648/j.ajetm.20251005.11},
url = {https://doi.org/10.11648/j.ajetm.20251005.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajetm.20251005.11},
abstract = {The group decision-making (GDM) is a process of aggregating the preference information of each decision maker in a group into a collective opinion under certain decision criteria. When a decision is made by decision makers (DMs), the group decision or group opinion is a result of the integration of the individual opinions by a mathematical aggregation. An important thing in the integration of the individual opinions is which DMs’ opinions should be of importance in the aggregation process. The group opinion is heavily influenced by the level of expertise of the DMs. In real-life group decision making (GDM) problems, preference relations given by decision makers (DMs) are often heterogeneous because of their expertise and different decision habits. The expertise level of the DMs can be estimated using the ‘the ability to differentiate consistently’, a ratio between discrimination and inconsistency. Each expert has different expertise in different criteria and has his/her limited capacity in constructing of pairwise comparison preference relations. In this paper, we focus on a method to assess expertise-based ranking of experts in GDM with multiple criteria and different preference representation formats. The combination of expertise as ‘the ability to differentiate consistently’ and the consistency of various types of preference relations is discussed, when experts give their judgements for alternatives in various types of preference relations, such as multiplicative preference relations (MPRs), utility values, preference orderings, even incomplete FPRs or MPRs, including FPRs under certain criterion. Then, since the experts have the limited capacity in constructing of pairwise comparison preference relations in GDM with multiple criteria, we propose a expertise-based ranking method using the adjacent pairwise comparison technique in order to reduce the number of judgements. Finally, expertise-based ranking of experts is applied to aggregate the individual opinions into a group opinion by developing into experts’ importance weights in GDM. Numerical analyses show that proposed method is simple than the previous methods and can fill up some gaps in GDM.
},
year = {2025}
}
TY - JOUR T1 - Expertise-Based Ranking of Experts in Multicriteria Group Decision Making with Different Preference Representation Formats AU - SongHo Sim AU - SinHyok Kim Y1 - 2025/10/31 PY - 2025 N1 - https://doi.org/10.11648/j.ajetm.20251005.11 DO - 10.11648/j.ajetm.20251005.11 T2 - American Journal of Engineering and Technology Management JF - American Journal of Engineering and Technology Management JO - American Journal of Engineering and Technology Management SP - 69 EP - 83 PB - Science Publishing Group SN - 2575-1441 UR - https://doi.org/10.11648/j.ajetm.20251005.11 AB - The group decision-making (GDM) is a process of aggregating the preference information of each decision maker in a group into a collective opinion under certain decision criteria. When a decision is made by decision makers (DMs), the group decision or group opinion is a result of the integration of the individual opinions by a mathematical aggregation. An important thing in the integration of the individual opinions is which DMs’ opinions should be of importance in the aggregation process. The group opinion is heavily influenced by the level of expertise of the DMs. In real-life group decision making (GDM) problems, preference relations given by decision makers (DMs) are often heterogeneous because of their expertise and different decision habits. The expertise level of the DMs can be estimated using the ‘the ability to differentiate consistently’, a ratio between discrimination and inconsistency. Each expert has different expertise in different criteria and has his/her limited capacity in constructing of pairwise comparison preference relations. In this paper, we focus on a method to assess expertise-based ranking of experts in GDM with multiple criteria and different preference representation formats. The combination of expertise as ‘the ability to differentiate consistently’ and the consistency of various types of preference relations is discussed, when experts give their judgements for alternatives in various types of preference relations, such as multiplicative preference relations (MPRs), utility values, preference orderings, even incomplete FPRs or MPRs, including FPRs under certain criterion. Then, since the experts have the limited capacity in constructing of pairwise comparison preference relations in GDM with multiple criteria, we propose a expertise-based ranking method using the adjacent pairwise comparison technique in order to reduce the number of judgements. Finally, expertise-based ranking of experts is applied to aggregate the individual opinions into a group opinion by developing into experts’ importance weights in GDM. Numerical analyses show that proposed method is simple than the previous methods and can fill up some gaps in GDM. VL - 10 IS - 5 ER -