Skip to main content
Log in

Organization incentive driven by modeling of the co-opetition behavior in agent-based complex network

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

Different from a interaction model of traditional organizational incentive and individual behaviors, the research incorporates the concept of “cognitive bias” into a decision making model of employees’ co-opetition behaviors under organizational reform of joint-stock commercial banks based on theories of social dynamics, and establishes a model of employees’ co-opetition behaviors under different organizational incentives as well as variation characteristics of employees’ co-opetition behaviors. Research results show that in organizational change of commercial banks, incentive measures and communication modes shall be treated in differential manners according to specific stages, so that balanced distribution of resources and effect maximization can be achieved. At the initial stage of reform, strengthening of core employee management shall be emphasized and its diffusion effects shall be utilized positively. In this way, progress of organizational reform can be promoted from the microscopic layer.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Deffuant G, Neau D, Amblard F et al (2000) Mixing beliefs among interacting agents. Adv Complex Syst 3(01n04):87–98

    Article  Google Scholar 

  • Dellermann D, Ebel P, Söllner M et al. (2019) Hybrid intelligence. Bus Inf Syst Eng 61(5):637–643

    Article  Google Scholar 

  • Fisher L (2009) The perfect swarm: the science of complexity in everyday life. Basic Books, New York

    Google Scholar 

  • Galam S (2016) Stubbornness as an unfortunate key to win a public debate: an illustration from sociophysics. Mind Soc 15(1):117–130

    Article  Google Scholar 

  • Haag M, Lagunoff R (2007) On the size and structure of group cooperation. J Econ Theory 135(1):68–89

    Article  MathSciNet  MATH  Google Scholar 

  • Hegselmann R, Krause U (2002) Opinion dynamics and bounded confidence models, analysis, and simulation. J Artif Soc Soc Simul 5(3):1–2

    Google Scholar 

  • Huang C, Hu B, Jiang G et al (2016) Modeling of agent-based complex network under cyber-violence. Phys A 458:399–411

    Article  Google Scholar 

  • Jiang F, Zhao X, Bai Q (2019) Simulation and stability analysis of conflict events between employees and organization based on the social network. Concurr Comput Pract Exp 2018:e5097

    Google Scholar 

  • Jin H, Yang Z et al (2013) Exploring how organizational incentives and organizational culture affect knowledge sharing based on modified SIT. Stud Sci Sci 11:1697–1707

    Google Scholar 

  • Kahneman D (2002) Maps of bounded rationality: a perspective on intuitive judgment and choice. Nobel Prize Lect 8:351–401

    Google Scholar 

  • Kahneman D, Tversky A (2013) Prospect theory: an analysis of decision under risk. In: MacLean LC, Ziemba WT (eds) Handbook of the fundamentals of financial decision making: part I. World Scientific, Singapore, pp 99–127

    Chapter  Google Scholar 

  • Kreidler WJ (2005) Creative conflict resolution: more than 200 activities for keeping peace in the classroom. Good Year Books, Culver City

    Google Scholar 

  • Kurmyshev E, Juárez HA, González-Silva RA (2011) Dynamics of bounded confidence opinion in heterogeneous social networks: concord against partial antagonism. Phys A 390(16):2945–2955

    Article  Google Scholar 

  • Lee D, Van den Steen E (2010) Managing know-how. Manag Sci 56(2):270–285

    Article  Google Scholar 

  • Liu X (2017) Evolution and simulation analysis of co-opetition behavior of E-business internet platform based on evolutionary game theory. Cluster Comput. https://doi.org/10.1007/s10586-017-1265-x

    Article  Google Scholar 

  • Lv S, Yang R, Huang C (2017) Contusion and recovery of individual cognition based on catastrophe theory: a computational model. Neurocomputing 220:210–220

    Article  Google Scholar 

  • Lv Z, Hu B, Lv H (2019) Infrastructure monitoring and operation for smart cities based on IoT system. IEEE Transact Ind Inform. https://doi.org/10.1109/TII.2019.2913535

    Article  Google Scholar 

  • Mian M, Jaffry W (2019) Modeling of individual differences in driver behavior. J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-019-01313-2

    Article  Google Scholar 

  • Paris S, Donikian S (2009) Activity-driven populace: a cognitive approach to crowd simulation. IEEE Comput Gr Appl 29(4):34–43

    Article  Google Scholar 

  • Tan L, Hu M, Lin H (2015) Agent-based simulation of building evacuation: combining human behavior with predictable spatial accessibility in a fire emergency. Inf Sci 295:53–66

    Article  MathSciNet  Google Scholar 

  • Wei G, Lean Y et al (2007) A study on incentive factors of team cooperation based on synergy effect. Syst Eng Theory Pract 01:1–9

    Article  Google Scholar 

  • Xu B, Liu R, Liu W (2014) Individual bias and organizational objectivity: an agent-based simulation. J Artif Soc Soc Simul 17(2):1–2

    Article  MathSciNet  Google Scholar 

  • Zhang Y, Leezer J (2010) Simulating human-like decisions in a memory-based agent model. Comput Math Organ Theory 16(4):373–399

    Article  Google Scholar 

  • Zhao X, Hu B (2016) Qualitative simulation on staff counterproductive work behaviors based on stochastic catastrophe theory. J Manag Sci China 02:13–30

    Google Scholar 

  • Zhong H, Li X, Lobell D et al (2018) Hierarchical modeling of seed variety yields and decision making for future planting plans. Environ Syst Decis 38(4):458–470

    Article  Google Scholar 

  • Zhu G, Huang C, Hu B et al (2016) Autonomy in individual behavior under multimedia information. Multimed Tools Appl 75(22):14433–14449

    Article  Google Scholar 

  • Zollman K (2011) Computer simulation and emergent reliability in science. J Artif Soc Soc Simul 14(4):15

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

This research is supported by projects of China Postdoctoral Science Foundation (No. 2018M643213) and National Social Science Foundation of China (No. 17CTQ030).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiaomeng Ma.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lv, S., Ma, X. & Yang, R. Organization incentive driven by modeling of the co-opetition behavior in agent-based complex network. J Ambient Intell Human Comput 11, 3305–3313 (2020). https://doi.org/10.1007/s12652-019-01517-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-019-01517-6

Keywords

Navigation