Stability of scientific big data sharing mechanism based on two-way principal-agent

Wang Zhang; Jingkun Zhang; Wang Zhang; Jingkun Zhang

doi:10.3934/math.2023955

AIMS Mathematics

2023, Volume 8, Issue 8: 18762-18779. doi: 10.3934/math.2023955

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Stability of scientific big data sharing mechanism based on two-way principal-agent

Wang Zhang ^{1
,
,},
Jingkun Zhang ²

1.
School of Economics and Management, Northwest University, Xi'an 710127, China
2.
School of Accounting, XiJing University, Xi'an 710123, China

Received: 18 February 2023 Revised: 08 May 2023 Accepted: 22 May 2023 Published: 02 June 2023
MSC : 20C25, 20C35

In the era of big data, facing the data-intensive scientific paradigm shift and the explosion of scientific big data, there is an urgent need for alliance cooperation between heterogeneous research groups to actively open and share scientific big data to support China's economic development, technological innovation and national security. Therefore, the study of scientific big data sharing mechanism has very important practical significance. We think science big data sharing is an ecosystem that is constantly evolving to higher-order ecological evolution. Based on the dual perspectives of psychological contract and contractual contract, the scientific big data sharing strategy evolution mechanism and sharing strategy incentive mechanism are explored.The research finds that the cooperation of scientific research groups is bound by psychological contract and contractual contract; stochastic evolutionary game has stronger explanatory power for sharing strategy evolution, complementarity is positive indicator, random interference and moral risk are negative indicators; two-way principal agent can describe Alliance members are mutually entrusted, and the shared strategy incentive contract consists of fixed wages and incentive wages, which are proportional to risk.
- scientific big data,
- sharing strategy evolution,
- sharing strategy incentives,
- stochastic evolutionary game,
- two-way principal agent
Citation: Wang Zhang, Jingkun Zhang. Stability of scientific big data sharing mechanism based on two-way principal-agent[J]. AIMS Mathematics, 2023, 8(8): 18762-18779. doi: 10.3934/math.2023955

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Abstract

In the era of big data, facing the data-intensive scientific paradigm shift and the explosion of scientific big data, there is an urgent need for alliance cooperation between heterogeneous research groups to actively open and share scientific big data to support China's economic development, technological innovation and national security. Therefore, the study of scientific big data sharing mechanism has very important practical significance. We think science big data sharing is an ecosystem that is constantly evolving to higher-order ecological evolution. Based on the dual perspectives of psychological contract and contractual contract, the scientific big data sharing strategy evolution mechanism and sharing strategy incentive mechanism are explored.The research finds that the cooperation of scientific research groups is bound by psychological contract and contractual contract; stochastic evolutionary game has stronger explanatory power for sharing strategy evolution, complementarity is positive indicator, random interference and moral risk are negative indicators; two-way principal agent can describe Alliance members are mutually entrusted, and the shared strategy incentive contract consists of fixed wages and incentive wages, which are proportional to risk.

References

[1]	R. Kitchin, Big data, new epistemologies and paradigm shift, Big Data Soc., 1 (2014), 1–12.
[2]	H. Guo, L. Wang, C. Fang, D. Liang, Scientific big data and digital earth, Chinese Sci. Bull., 59 (2014), 5066–5073. https://doi.org/10.1007/s11434-014-0645-3 doi: 10.1007/s11434-014-0645-3
[3]	C. L. Borgman, The conundrum of sharing research data, New Technol. Library Inf. Ser., 5 (2013), 1–20. https://doi.org/10.11925/infotech.1003-3513.2013.05.01 doi: 10.11925/infotech.1003-3513.2013.05.01
[4]	Z. Yang, Y. Shi, Y. Li, Analysis of intellectual property cooperation behavior and its simulation under two types of scenarios using evolutionary game theory, Comput. Ind. Eng., 125 (2018), 739–750. https://doi.org/10.1016/j.cie.2018.02.040 doi: 10.1016/j.cie.2018.02.040
[5]	J. Zuo, Y. Chen, The analysis on sharing mode of scientific data in the environment of big data, J. Intell., 32 (2013), 151–154. https://doi.org/10.1007/978-3-319-50627-2 doi: 10.1007/978-3-319-50627-2
[6]	D. S. Sayogo, T. A. Pardo, Exploring the determinants of scientific data sharing: understanding the motivation to publish research data, Gov. Inform. Q., 30 (2013), 519–531. https://doi.org/10.1016/j.giq.2012.06.011 doi: 10.1016/j.giq.2012.06.011
[7]	C. Li, L. Zhang, Scientific big data opening and sharing: models and mechanisms, Inf. Stud.: Theory Pract., 40 (2017), 45–51.
[8]	D. L. Nazareth, J. Choi, A system dynamics model for information security management, Inf. Manage., 52 (2015), 123–134. https://doi.org/10.1016/j.im.2014.10.009 doi: 10.1016/j.im.2014.10.009
[9]	Y. Du, R. Zhang, M. Li, Research on a security mechanism for cloud computing based on virtualization, Telecommun. Syst., 53 (2013), 19–24. https://doi.org/10.1007/s11235-013-9672-7 doi: 10.1007/s11235-013-9672-7
[10]	Y. Kim, M. Adler, Social scientists' data sharing behaviors: investigating the roles of individual motivations, institutional pressures, and data repositories, Int. J. Inf. Manag., 35 (2015), 408–418. https://doi.org/10.1016/j.ijinfomgt.2015.04.007 doi: 10.1016/j.ijinfomgt.2015.04.007
[11]	M. Janssen, Y. Charalabidis, A. Zuiderwijk, Benefits, adoption barriers and myths of open data and open government, Inf. Syst. Manag., 29 (2012), 258–268. https://doi.org/10.1080/10580530.2012.716740 doi: 10.1080/10580530.2012.716740
[12]	B. V. Loenen, H. J. Onsrud, Geographic data for academic research: assessing access policies, Cartogr. Geogr. Inf. Sci., 31 (2004), 3–17. https://doi.org/10.1559/152304004773112730 doi: 10.1559/152304004773112730
[13]	C. Peng, X. Song, H. Jiang, Q. Zhu, H. Chen, J. M. Chen, et al., Towards a paradigm for open and free sharing of scientific data on global change science in China, Ecosyst. Health Sustain., 2 (2016), 23–45. https://doi.org/10.1002/ehs2.1225 doi: 10.1002/ehs2.1225
[14]	X. Gao, W. Zhong, S. Mei, Stochastic evolutionary game dynamics and their selection mechanisms, Comput. Econ., 41 (2013), 233–247. https://doi.org/10.1007/s10614-012-9320-4 doi: 10.1007/s10614-012-9320-4
[15]	S. Dai, G. Nie, N. Xiao, The study of the two-way principal-agent model based on asymmetric information, Wireless Pers. Commun., 102 (2018), 629–639. https://doi.org/10.1007/s11277-017-5071-9 doi: 10.1007/s11277-017-5071-9
[16]	Y. Wei, G. Liu, Analysis of research data management and sharing policy in foreign universities based on data lifecycle, J. Intell., 5 (2017), 153–158.
[17]	D. Hingu, K. S. M. Rao, A. J. Shaiju, Evolutionary stability of polymorphic population states in continuous games, Dyn. Games Appl., 8 (2016), 141–156. https://doi.org/10.1007/s13235-016-0207-1 doi: 10.1007/s13235-016-0207-1
[18]	A. Erwin, P. Alex, On the stability of evolutionary dynamics in games with incomplete information, Math. Soc. Sci., 58 (2009), 310–321.
[19]	Y. Xu, B. Hu, R. Qian, Analysis on stability of strategic alliances based on stochastic evolutionary game including simulations, Syst. Eng.-Theory Pract., 31 (2011), 920–926.
[20]	J. M. Huang, H. W. Zhang, A method for selecting defense strategies based on stochastic evolutionary game model, Acta Electron. Sinica, 46 (2018), 2222–2228. https://doi.org/10.3969/j.issn.0372-2112.2018.09.025 doi: 10.3969/j.issn.0372-2112.2018.09.025
[21]	S. Hu, C. Huang, Stochastic differential equation, Beijing: Science Press, 5 (2008), 66–70.
[22]	H. Sun, X. Wang, Y. Xue, Stochastic evolutionary game model for unexpected incidents involving mass participation based on different scenarios, Operat. Res. Manage. Sci., 25 (2016), 23–29.
[23]	B. Holmastrom, P. Milgrom, Aggregation and linearity in the provision of intertemporal incentives, Econometrica, 55 (1987), 303–328.
[24]	W. Zhang, Game theory and information economics, Shanghai: People's Publishing House, 5 (2012), 242–262.
[25]	Y. Ren, F. Zhu, P. K. Sharma, T. Wang, J. Wang, O. Alifarraj, et al., Data query mechanism based on hash computing power of blockchain in internet of things, Sensors, 20 (2020), 207–229. https://doi.org/10.3390/s20010207 doi: 10.3390/s20010207
[26]	Y. Ren, F. Zhu, J. Wang, P. K. Sharma, U. Ghosh, Novel vote scheme for decision-making feedback based on blockchain in internet of vehicles, IEEE Trans. Intell. Transp. Syst., 23 (2022), 1639–1648. https://doi.org/10.1109/TITS.2021.3100103 doi: 10.1109/TITS.2021.3100103

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