Two-phase pairwise comparison-based model for the ranking prediction of global innovation capability

doi:10.23919/JSEE.2025.000018

Journal of Systems Engineering and Electronics ›› 2026, Vol. 37 ›› Issue (2): 504-520.doi: 10.23919/JSEE.2025.000018

• SYSTEMS ENGINEERING • Previous Articles

Two-phase pairwise comparison-based model for the ranking prediction of global innovation capability

Ruijing CUI(), Jianbin SUN(), Kewei YANG()

College of Systems Engineering, National University of Defense Technology, Changsha 410073, China

Received:2022-10-13 Online:2026-04-18 Published:2026-04-30
Contact: Jianbin SUN E-mail:cuiruijing@nudt.edu.cn;sunjianbin@nudt.edu.cn;kayyang27@nudt.edu.cn
About author:
CUI Ruijing was born in 1996. He received his B.E. degree in system engineering, M.E. degree in management science and engineering from National University of Defense Technology, Changsha, China, in 2019 and 2021, respectively. He is currently pursuing his Ph.D. degree in management science and engineering at National University of Defense Technology. His research interests focus on causal inference, complex systems, and systems engineering. E-mail: cuiruijing@nudt.edu.cn

SUN Jianbin was born in 1989. He received his B.E. degree in management engineering, M.E. and Ph.D. degrees in management science and engineering from National University of Defense Technology, Changsha, China, in 2012, 2014 and 2018, respectively. He is currently an associate professor of management science and engineering at National University of Defense Technology. His research interests focus on system-of-systems engineering management and decision analysis under uncertainty. E-mail: sunjianbin@nudt.edu.cn

YANG Kewei was born in 1977. He received his B.S. degree in systems engineering and Ph.D. degree in management science and engineering from National University of Defense Technology, Changsha, China, in 1999 and 2004, respectively. He is currently a professor of management science and engineering, and the director of the System of Systems Engineering Laboratory. His research interests focus on intelligent agent simulation, defense acquisition, and system of systems requirement modeling. E-mail: kayyang27@nudt.edu.cn
Supported by:
This work was supported by the National Natural Science Foundation of China (71901212;72071206), and the Science and Technology Innovation Program of Hunan Province (2020RC4046).

Abstract

Abstract:

To predict the ranking of the country’s innovation capability in the world in real-time, this study designs a two-phased prediction model based on the pairwise comparison. Data from the global innovation index (GII) reports are employed in this study. Countries with different income levels have shown different development inertias, the two-phased prediction model is thus proposed. In the first phase, the GII data from the previous year are applied to predict the ranking of innovation capability for high-income countries. In the second phase, more years of historical data are adopted to predict the innovation ranking for other countries. The global innovation rankings for all countries and economies are thus obtained. Experiments have proved that the model requires only a few indicators to get accurate results. The model provides real-time decision support for decision-makers to formulate innovative development policies.

Key words: global innovation index (GII), pairwise comparison, ranking prediction, two-phased model

Ruijing CUI, Jianbin SUN, Kewei YANG. Two-phase pairwise comparison-based model for the ranking prediction of global innovation capability[J]. Journal of Systems Engineering and Electronics, 2026, 37(2): 504-520.

Figures/Tables 13

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Table 2

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Table 3

Table 4

Table 5

Original rankings and predicted rankings in 2020"

Economy	Orank	Prank	D	Economy	Drank	Prank	D
Switzerland	1	1	0	Iran (Islamic Republic of)	67	61	6
Sweden	2	2	0	Colombia	68	68	0
United States of America	3	3	0	Uruguay	69	69	0
United Kingdom (the)	4	4	0	Qatar	70	70	0
Netherlands (the)	5	4	1	Brunei Darussalam	71	65	6
Denmark	6	6	0	Jamaica	72	73	−1
Finland	7	7	0	Panama	73	78	−5
Singapore	8	8	0	Bosnia and Herzegovina	74	75	−1
Germany	9	9	0	Morocco	75	80	−5
Republic of Korea (the)	10	10	0	Peru	76	72	4
Hong Kong, China	11	12	−1	Kazakhstan	77	82	−5
France	12	16	−4	Kuwait	78	70	8
Israel	13	13	0	Bahrain	79	79	0
China	14	15	−1	Argentina	80	74	6
Ireland	15	11	4	Jordan	81	86	−5
Japan	16	14	2	Azerbaijan	82	83	−1
Canada	17	17	0	Albania	83	77	6
Luxembourg	18	19	−1	Oman	84	84	0
Austria	19	21	−2	Indonesia	85	87	−2
Norway	20	20	0	Kenya	86	84	2
Iceland	21	23	−2	Lebanon	87	88	−1
Belgium	22	22	0	United Republic of Tanzania (the)	88	88	0
Australia	23	18	5	Botswana	89	85	4
Czech Republic (the)	24	26	−2	Dominican Republic (the)	90	90	0
Estonia	25	25	0	Rwanda	91	89	2
New Zealand	26	24	2	El Salvador	92	106	−14
Malta	27	31	−4	Uzbekistan	93	93	0
Italy	28	27	1	Kyrgyzstan	94	100	−6
Cyprus	29	32	−3	Nepal	95	95	0
Spain	30	28	2	Egypt	96	98	−2
Portugal	31	31	0	Paraguay	97	91	6
Slovenia	32	30	2	Trinidad and Tobago	98	98	0
Malaysia	33	35	−2	Ecuador	99	97	2
United Arab Emirates	34	34	0	Cabo Verde	100	96	4
Hungary	35	34	1	Sri Lanka	101	93	8
Latvia	36	33	3	Senegal	102	102	0
Bulgaria	37	40	−3	Honduras	103	107	−4
Poland	38	39	−1	Namibia	104	104	0
Slovakia	39	39	0	Bolivia (Plurinational State of)	105	110	−5
Lithuania	40	36	4	Guatemala	106	104	2
Croatia	41	43	−2	Pakistan	107	107	0
Viet Nam	42	42	0	Ghana	108	116	−8
Greece	43	41	2	Tajikistan	109	109	0
Thailand	44	44	0	Cambodia	110	95	15
Ukraine	45	45	0	Malawi	111	127	−16
Romania	46	46	0	Côte d’Ivoire	112	111	1
Russian Federation	47	51	−4	Lao People’s Democratic Republic (the)	113	112	1
India	48	52	−4	Uganda	114	114	0
Montenegro	49	47	2	Madagascar	115	114	1
Philippines	50	50	0	Bangladesh	116	118	−2
Turkey	51	49	2	Nigeria	117	130	−13
Mauritius	52	45	7	Burkina Faso	118	120	−2
Serbia	53	53	0	Cameroon	119	115	4
Chile	54	48	6	Zimbabwe	120	120	0
Mexico	55	55	0	Algeria	121	113	8
Costa Rica	56	56	0	Zambia	122	122	0
North Macedonia	57	58	−1	Mali	123	122	1
Mongolia	58	54	4	Mozambique	124	125	−1
Republic of Moldova	59	59	0	Togo	125	125	0
South Africa	60	60	0	Benin	126	119	7
Armenia	61	64	−3	Ethiopia	127	121	6
Brazil	62	67	−5	Niger (the)	128	128	0
Georgia	63	57	6	Myanmar	129	126	3
Belarus	64	71	−7	Guinea	130	129	1
Tunisia	65	76	−11	Yemen	131	131	0
Saudi Arabia	66	66	0	−	−	−	−

Table 5

Fig 8

References 28

1	EDQUIST C Systems of innovation perspectives and challenges. African Journal of Science, Technology, Innovation and Development, 2010, 2 (3): 14- 45.
2	SOHN S Y, KIM D H, JEON S Y Re-evaluation of global innovation index based on a structural equation model. Technology Analysis & Strategic Management, 2016, 28 (4): 492- 505.
3	CORNELL UNIVERSITY, INSEAD, WIPO. The global innovation index 2020: who will finance innovation? Geneva: World Intellectual Property Organization, 2020.
4	CRESPO N F Global innovation index: moving beyond the absolute value of ranking with a fuzzy-set analysis. Journal of Business Research, 2016, 69 (11): 5265- 5271. doi: 10.1016/j.jbusres.2016.04.123
5	WANG X, WANG Z J, JIANG Z Y. Configurational differences of national innovation capability: a fuzzy-set qualitative comparative analysis approach. Technology Analysis and Strategic Management, 2020, 33(6): 599−611.
6	YU H K, HUARNG K H, HUANG D H Causal complexity analysis of the global innovation index. Journal of Business Research, 2021, 137 (2): 39- 45.
7	HAMIDI S, BERRADO A. Segmentation of innovation determinants: case of the global innovation index. Proc. of the 12th International Conference on Intelligent Systems: Theories and Applications, 2018. DOI: 10.1145/3289402.3289548.
8	OVESHNIKOVA L, LEBEDINSKAYA O, TIMOFEEV A, et al. Studying the sector of the Russian high tech innovations on the basis of the global innovation index INSEAD. Cham: Springer International Publishing, 2017.
9	LASOVA V, KUZNETSOVA T, ROUD V. Drivers and limitations of Russia’s development based on the evidence provided by the global innovation index. Voprosy Economiki, 2017, 8: 24−41.
10	AL-SUDAIRI M, BAKRY S H Knowledge issues in the global innovation index: assessment of the state of saudi arabia versus countries with distinct development. Innovation Management, 2014, 16, 176- 183.
11	OMER M, ELAMIN M, NASR A, et al. Modeling, visualization, and analysis of african innovation performance. https://arxiv.org/abs/2008.07882.
12	ERSOZ F, AVRUPA T K The status of turkey in light of the indicators of EU innovation (eis). Journal of Istanbul Technical University, 2009, 6 (1): 3- 16.
13	TEZCAN N Comparative analysis of EU countries and Turkey in terms of innovation performance. Research Journal of Business & Management, 2015, 2 (2): 204- 219.
14	USMAN K, LIU Z Y Innovation index framework to measure the innovation capacity and efficiency of SAARC countries. European Journal of Social Sciences, 2015, 46 (3): 325- 338.
15	PENCE I, KALKAN A, CESMELI M S, et al Estimation of the country ranking scores on the global innovation index 2016 using the artificial neural network method. International Journal of Innovation & Technology Management, 2018, 16 (4): 1940007.
16	CUI R J, SUN J B, LI Y, et al. Data-driven approach with artificial neural network for global innovation index re-evaluation. Proc. of the 6th International Conference on Big Data and Information Analytics, 2020: 88−93.
17	LIU T Y. Learning to rank for information retrieval. Hanover: Now Foundations and Trends, 2009.
18	SPEARMAN C The proof and measurement of association between two things. International Journal of Epidemiology, 2010, 39 (5): 1137- 1150. doi: 10.1093/ije/dyq191
19	CORNELL UNIVERSITY, INSEAD, WIPO. The global innovation index 2019: creating healthy lives-the future of medical innovation. Geneva: World Intellectual Property Organization, 2019.
20	BUHLMANN P Missforest-non-parametric missing value imputation for mixed-type data. Bioinformatics, 2012, 28 (1): 112- 118. doi: 10.1093/bioinformatics/btr597
21	HERBRICH R, OBERMAYER K, GRAEPEL T Large margin rank boundaries for ordinal regression. Advances in Neural Information Processing Systems, 2000, 8, 115- 132.
22	JOACHIMS T. Optimizing search engines using clickthrough data. Proc. of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002: 133−142.
23	YI N, YI G X, HU L, et al Influencing factor analysis of interception probability and classification-regression neural network based estimation. Journal of Systems Engineering and Electronics, 2023, 34 (4): 992- 1006.
24	BURGES C, SHAKED T, RENSHAW E, et al. Learning to rank using gradient descent. Proc. of the 22nd International Conference on Machine Learning, 2005: 89−96.
25	CORNELL UNIVERSITY, INSEAD, WIPO. The global innovation index 2017: innovation feeding the world. Geneva: World Intellectual Property Organization, 2017.
26	CORNELL UNIVERSITY, INSEAD, WIPO. The global innovation index 2018: energizing the World with Innovation. Geneva: World Intellectual Property Organization, 2018.
27	CORNELL UNIVERSITY, INSEAD, WIPO. Global innovation index 2021: tracking innovation through the COVID-19 crisis. Geneva: World Intellectual Property Organization, 2021.
28	FREEMAN C. Technology, policy, and economic performance: lessons from japan. New York: Pinter Publishers, 1987.

Input	Notation
Historical data in the GII report	${O_1}$
Sample data to be ranked	${O_2}$

Output	Notation
Accuracy of validation sets	−
Ranking prediction result	−
Binary classifier model	−
Spearman correlation coefficient between the ranking and the original ranking	$\rho $

Reference	$m$	Method	$\rho $
[16]	14	mF-ANN	0.979
This study	14	KNN	0.986
		RF	0.985
		SVM	0.983
		DT	0.983
		GNB	0.965
		RankNet	0.948

Reference		Training data	Testing data	Method	$\rho $
[2]		2013	2013	SEM	0.965
Subsection 3.3 of this study		2019	2020	Pairwise comparison	0.987
Two-phased model	1st phase	2019	2020(H)	Pairwise comparison	0.994
Two-phased model	2nd phase	2017, 2018, and 2019	2020(!H)	Pairwise comparison	0.994

Two-phase pairwise comparison-based model for the ranking prediction of global innovation capability

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