Please wait a minute...
Chin. Phys. B, 2022, Vol. 31(6): 068903    DOI: 10.1088/1674-1056/ac5614
Special Issue: SPECIAL TOPIC— Interdisciplinary physics: Complex network dynamics and emerging technologies
SPECIAL TOPIC—Interdisciplinary physics: Complex network dynamics and emerging technologies Prev   Next  

Advantage of populous countries in the trends of innovation efficiency

Dan-Dan Hu(胡淡淡)1,2, Xue-Jin Fang(方学进)1,2, and Xiao-Pu Han(韩筱璞)1,2,†
1 Alibaba Research Center for Complexity Sciences, Hangzhou Normal University, Hangzhou 311121, China;
2 Institute of Information Economy and Alibaba Business School, Hangzhou Normal University, Hangzhou 311121, China
Abstract  A flurry of studies indicates that population size has a positive effect on innovation, however, cross-country empirical evidence remains sparse. In this paper, we add to the literature by investigating the relationship between population size and innovation efficiency at the country level through constructing three relative indexes based on the datasets of patent applications and Research and Development (R&D) investment. Different from previous studies based on absolute innovation indicators, the relative indexes can reflect the core innovation efficiency of economies by excluding the impact from the difference of economic development level, with a view putting all economies into a comparable standard framework. For all of the three relative indexes, their long-term trends show significant correlations with population size, and the economy with a larger population usually has better and stable performance on the trends of innovation efficiency. In addition, we find that there is a critical population size, over which the economy would be more likely to have a spontaneous improvement on innovation efficiency. This study provides direct evidence in supporting the population size advantage on the trends of innovation efficiency at the economy level and provides new insight to understand the rapid development of innovation in a few populous countries.
Keywords:  innovation efficiency      population size      the relative indexes  
Received:  20 July 2021      Revised:  22 January 2022      Accepted manuscript online:  17 February 2022
PACS:  89.65.Gh (Economics; econophysics, financial markets, business and management)  
  89.75.-k (Complex systems)  
  89.65.-s (Social and economic systems)  
Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 62073112 and 61673151) and the Zhejiang Provincial Natural Science Foundation of China (Grant No. LGF18F030007).
Corresponding Authors:  Xiao-Pu Han     E-mail:  xp@hznu.edu.cn

Cite this article: 

Dan-Dan Hu(胡淡淡), Xue-Jin Fang(方学进), and Xiao-Pu Han(韩筱璞) Advantage of populous countries in the trends of innovation efficiency 2022 Chin. Phys. B 31 068903

[1] Romer P M 1986 J. Polit. Econ. 94 1002
[2] Lucas Jr R E 1988 J. Monet. Econ. 22 3
[3] Grossman G M and Helpman E 1994 J. Econ. Perspect. 8 23
[4] Zhou X X, Cai Z M, Tan K H, Zhang L L, Du J T and Song M L 2021 Technol. Forecast. Soc. Change 167 120671
[5] Ribeiro L C, Ruiz R M, Albuquerque E M and Bernardes A T 2006 Int. J. Mod. Phys. C 17 247
[6] Wang S B, Zhao J L and Yu J N 2019 Int. J. Mod. Phys. C 30 1950012
[7] Grossman G M and Helpman E 1991 Innovation and Growth in the Global Economy (MIT Press)
[8] Romer P M 1990 J. Polit. Econ. 98 S71
[9] Bettencourt L M, Lobo J, Helbing D, Kühnert C and West G B 2007 Proc. Natl. Acad. Sci. U. S. A. 104 7301
[10] Boserup E 1981 Population and Technological Change: A Study of Long Term Trends (Chicago: University of Chicago Press) p. 255
[11] Galor O and Weil D N 2000 Am. Econ. Rev. 90 806
[12] Kremer M 1993 Q. J. Econ. 108 681
[13] Gomez-Lievano A, Patterson-Lomba O and Hausmann R 2017 Nat. Hum. Behav. 1 0012
[14] Liang J 2018 Demographics of Innovation:Why Demographics is a Key to the Innovation Race (John Wiley and Sons) p. 71
[15] Li R Q, Lu L Y, Cui T Y, Gu W W, Ma S D, Xu G and Stanley H E 2021 IEEE Access 9 48052
[16] Balland P A, Jara-Figueroa C, Petralia S G, Steijn M P A, Rigby D L and Hidalgo C A 2020 Nat. Hum. Behav. 4 248
[17] Hong I, Frank M R, Rahwan I, Jung W S and Youn H 2020 Sci. Adv. 6 eaba4934
[18] Shearmur R 2012 Cities 29 S9
[19] Bettencourt L M A, Lobo J, Strumsky D and West G B 2010 PloS One 5 e13541
[20] Pan W, Ghoshal G, Krumme C, Cebrian M and Pentland A 2013 Nat. Commun. 4 1961
[21] Lobo J, Bettencourt L M A, Strumsky D and West G B 2013 PloS One 8 e58407
[22] Gao J, Zhang Y C and Zhou T 2019 Phys. Rep. 817 1
[23] Li R, Dong L, Zhang J, Wang X R, Wang W X, Di Z and Stanley H E 2017 Nat. Commun. 8 1841
[24] Howitt P 1999 J. Polit. Econ. 107 715
[25] Wen Y 2015 FRB St. Louis Working Paper
[26] Acemoglu D and Linn J 2004 Q. J. Econ. 119 1049
[27] Gancia G, Müller A and Zilibotti F 2013 Advances in Economics and Econometrics: Tenth World Congress (Cambridge: Cambridge University Press)
[28] Beerli A, Weiss F J, Zilibotti F and Zweimüller J 2020 Chin. Econ. Rev. 60 101157
[29] Solow R M 1957 Rev. Econ. Stat. 39 312
[30] Gao J and Jefferson G H 2007 Asia Pac. Bus. Rev. 13 357
[31] Desmet K and Parente S L 2010 Int. Rev. Econ. 51 319
[32] Deane P M 1979 The First Industrial Revoluation (Cambridge University Press)
[33] Wang S, Fan J, Zhao D T and Wang S Y 2016 Technol. Anal. Strateg. Manag. 28 396
[34] Lee H Y and Park Y T 2005 Asian J. Technol. Innov. 13 207
[35] Guan J and Zuo K 2014 Scientometrics 100 541
[36] Hsu Y 2011 Afr. J. Bus. Manag. 5 1378
[37] Guede-Cid R, Rodas-Alfaya L, Leguey-Galán S and Cid-Cid A I 2021 J. Open Innov. 7 62
[38] Kontolaimou A, Giotopoulos I and Tsakanikas A 2016 Econ. Model. 52 477
[39] Liu X L and White S 2001 Res. Policy 30 1091
[40] Sharma S and Thomas V 2008 Scientometrics 76 483
[41] Aw B Y, Roberts M J and Xu D Y 2011 Amer. Econ. Rev. 101 1312
[42] Fang X J, Cui J Y, Hu D D and Han X P 2020 Acta Phys. Sin. 69 088905 (in Chinese)
[43] Keuschnigg M, Mutgan S and Hedström P 2019 Sci. Adv. 5 eaav0042
[44] Wang W, Du W B, Li W H, Tong L and Wang J E 2021 Chin. Phys. B 30 018901
[45] Hu J W, Gao S, Yan J W, Lou P and Yin Y 2020 Chin. Phys. B 29 088901
[46] Bai J H and Li J 2011 Innovation 13 142
[47] Wang E C and Huang W C 2007 Res. Policy 36 260
[1] Information flow between stock markets: A Koopman decomposition approach
Semba Sherehe, Huiyun Wan(万慧云), Changgui Gu(顾长贵), and Huijie Yang(杨会杰). Chin. Phys. B, 2022, 31(1): 018902.
[2] Modeling the dynamics of firms' technological impact
Shuqi Xu(徐舒琪), Manuel Sebastian Mariani, and Linyuan Lü(吕琳媛). Chin. Phys. B, 2021, 30(12): 120517.
[3] Pyramid scheme in stock market: A kind of financial market simulation
Yong Shi(石勇), Bo Li(李博), and Guang-Le Du(杜光乐). Chin. Phys. B, 2021, 30(9): 098901.
[4] Network correlation between investor's herding behavior and overconfidence behavior
Mao Zhang(张昴), Yi-Ming Wang(王一鸣). Chin. Phys. B, 2020, 29(4): 048901.
[5] Theoretical analyses of stock correlations affected by subprime crisis and total assets: Network properties and corresponding physical mechanisms
Shi-Zhao Zhu(朱世钊), Yu-Qing Wang(王玉青), Bing-Hong Wang(汪秉宏). Chin. Phys. B, 2019, 28(10): 108901.
[6] Pyramid scheme model for consumption rebate frauds
Yong Shi(石勇), Bo Li(李博), Wen Long(龙文). Chin. Phys. B, 2019, 28(7): 078901.
[7] Spatial memory enhances the evacuation efficiency of virtual pedestrians under poor visibility condition
Yi Ma(马毅), Eric Wai Ming Lee(李伟民), Meng Shi(施朦), Richard Kwok Kit Yuen(袁国杰). Chin. Phys. B, 2018, 27(3): 038901.
[8] Pedestrians' behavior in emergency evacuation: Modeling and simulation
Lei Wang(汪蕾), Jie-Hui Zheng(郑杰慧), Xiao-Shuang Zhang(张晓爽), Jian-Lin Zhang(张建林), Qiu-Zhen Wang(王求真), Qian Zhang(张茜). Chin. Phys. B, 2016, 25(11): 118901.
[9] Asymmetric and symmetric meta-correlations in financial markets
Xiaohui Li(李晓辉), Xiangying Shen(沈翔瀛), Jiping Huang(黄吉平). Chin. Phys. B, 2016, 25(10): 108903.
[10] Cross-correlation matrix analysis of Chinese and American bank stocks in subprime crisis
Zhu Shi-Zhao, Li Xin-Li, Nie Sen, Zhang Wen-Qing, Yu Gao-Feng, Han Xiao-Pu, Wang Bing-Hong. Chin. Phys. B, 2015, 24(5): 058903.
[11] Statistics of extreme events in Chinese stock markets
Wu Gan-Hua, Qiu Lu, Mutua Stephen, Li Xin-Li, Yang Yue, Yang Hui-Jie, Jiang Yan. Chin. Phys. B, 2014, 23(12): 128901.
[12] Statistical physics of human beings in games:Controlled experiments
Liang Yuan, Huang Ji-Ping. Chin. Phys. B, 2014, 23(7): 078902.
[13] A mini-review on econophysics:Comparative study of Chinese and western financial markets
Zheng Bo, Jiang Xiong-Fei, Ni Peng-Yun. Chin. Phys. B, 2014, 23(7): 078903.
[14] Chaotic dynamic behavior analysis and control for a financial risk system
Zhang Xiao-Dan, Liu Xiang-Dong, Zheng Yuan, Liu Cheng. Chin. Phys. B, 2013, 22(3): 030509.
[15] Multidimensional subdiffusion model: Arbitrage-free market
Li Guo-Hua, Zhang Hong, Luo Mao-Kang. Chin. Phys. B, 2012, 21(12): 128901.
No Suggested Reading articles found!