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Enterprise management heterogeneity and enterprise investment behavior based on intelligent scheduling system

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Abstract

The heterogeneity of enterprise management will have a certain impact on enterprise investment. In order to explore the strength of this correlation, this paper builds an intelligent system that can be used for enterprise analysis with the support of machine learning technology, uses embedded algorithms to improve the traditional algorithm structure, and combines machine learning to optimize and analyze data processing. Moreover, this paper combines the heterogeneity of enterprise management and the actual needs of enterprise management, the current financial market investment status to analyze the system's functional structure, and combine the actual needs to construct the overall system architecture. In addition, this paper adopts algorithm analysis to the system process, analyzes the system logic layer structure, and builds the overall system structure framework. Finally, this paper designs an experiment to analyze the performance of the system constructed in this paper. From the experimental research, it can be seen that the system constructed in this paper basically meets the expected requirements.

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References

  1. Castellano R, Cerqueti R, Rotundo G (2020) Exploring the financial risk of a temperature index: a fractional integrated approach. Ann Oper Res 284(1):225–242

    Article  MathSciNet  Google Scholar 

  2. Chan EY (2015) Physically-attractive males increase men’s financial risk-taking. Evol Hum Behav 36(5):407–413

    Article  Google Scholar 

  3. Cohn A, Engelmann J, Fehr E et al (2015) Evidence for countercyclical risk aversion: an experiment with financial professionals. Am Econ Rev 105(2):860–885

    Article  Google Scholar 

  4. Cole ES, Walker D, Mora A et al (2014) Identifying hospitals that may be at most financial risk from Medicaid disproportionate-share hospital payment cuts. Health Aff 33(11):2025–2033

    Article  Google Scholar 

  5. Cooper WW, Kingyens AT, Paradi JC (2014) Two-stage financial risk tolerance assessment using data envelopment analysis. Eur J Oper Res 233(1):273–280

    Article  MathSciNet  Google Scholar 

  6. Cueva C, Roberts RE, Spencer T et al (2015) Cortisol and testosterone increase financial risk taking and may destabilize markets. Sci Rep 5(1):1–16

    Article  Google Scholar 

  7. Fichtner J, Heemskerk EM, Garcia-Bernardo J (2017) Hidden power of the big three? Passive index funds, re-concentration of corporate ownership, and new financial risk. Bus Polit 19(2):298–326

    Article  Google Scholar 

  8. Shang H, Lu D, Zhou Q (2021) Early warning of enterprise finance risk of big data mining in internet of things based on fuzzy association rules. Neural Comput Appl 33:3901–3909

    Article  Google Scholar 

  9. Lee CJ, Andrade EB (2015) Fear, excitement, and financial risk-taking. Cogn Emot 29(1):178–187

    Article  Google Scholar 

  10. Linarelli J (2017) Luck, justice and systemic financial risk. J Appl Philos 34(3):331–352

    Article  Google Scholar 

  11. Lockwood E (2015) Predicting the unpredictable: value-at-risk, performativity, and the politics of financial uncertainty. Rev Int Polit Econ 22(4):719–756

    Article  Google Scholar 

  12. Lucarelli C, Uberti P, Brighetti G (2015) Misclassifications in financial risk tolerance. J Risk Res 18(4):467–482

    Article  Google Scholar 

  13. Magendans J, Gutteling JM, Zebel S (2017) Psychological determinants of financial buffer saving: the influence of financial risk tolerance and regulatory focus. J Risk Res 20(8):1076–1093

    Article  Google Scholar 

  14. Montford W, Goldsmith RE (2016) How gender and financial self-efficacy influence investment risk taking. Int J Consum Stud 40(1):101–106

    Article  Google Scholar 

  15. Rodríguez-Aguilar R, Marmolejo-Saucedo JA, Tavera-Martínez S (2018) Financial risk of increasing the follow-up period of breast cancer treatment currently covered by the Social Protection System in Health in Mexico. Cost Eff Resour Alloc 16(1):1–11

    Article  Google Scholar 

  16. Scharding TK (2015) Imprudence and immorality: a Kantian approach to the ethics of financial risk. Bus Ethics Q 25(2):243–265

    Article  Google Scholar 

  17. Sosnovska O, Zhytar M (2018) Financial architecture as the base of the financial safety of the enterprise. Baltic J Econ Stud 4(4):334–340

    Article  Google Scholar 

  18. Su J, Furman E (2017) A form of multivariate Pareto distribution with applications to financial risk measurement. ASTIN Bull J IAA 47(1):331–357

    Article  MathSciNet  Google Scholar 

  19. Tanimura T, Jaramillo E, Weil D et al (2014) Financial burden for tuberculosis patients in low-and middle-income countries: a systematic review. Eur Respir J 43(6):1763–1775

    Article  Google Scholar 

  20. Thomä J, Chenet H (2017) Transition risks and market failure: a theoretical discourse on why financial models and economic agents may misprice risk related to the transition to a low-carbon economy. J Sustain Financ Invest 7(1):82–98

    Article  Google Scholar 

  21. Wang GWY, Woo SH, Mileski J (2014) The relative efficiency and financial risk assessment of shipping companies. Marit Policy Manag 41(7):651–666

    Article  Google Scholar 

  22. Wanjohi SM, Wanjohi JG, Ndambiri JM (2017) The effect of financial risk management on the financial performance of commercial banks in Kenya. Int J Financ Bank Res 3(5):70–81

    Article  Google Scholar 

  23. West T, Worthington AC (2014) Macroeconomic conditions and Australian financial risk attitudes, 2001–2010. J Fam Econ Issues 35(2):263–277

    Article  Google Scholar 

  24. Zalik A (2015) Resource sterilization: reserve replacement, financial risk, and environmental review in Canada’s tar sands. Environ Plan A 47(12):2446–2464

    Article  Google Scholar 

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Acknowledgements

This work was supported by Doctoral Thesis Innovation Fund of Northwestern Polytechnical University (Key Project) (Grant No.: 06120-G2020KY04204).

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  1. School of Management, Northwestern Polytechnical University, Xi’an, 710129, Shanxi, China

    Jingjuan Wang & Weili Xia

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  1. Jingjuan Wang
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  2. Weili Xia
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Correspondence to Jingjuan Wang.

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Wang, J., Xia, W. Enterprise management heterogeneity and enterprise investment behavior based on intelligent scheduling system. Neural Comput & Applic 34, 12491–12504 (2022). https://doi.org/10.1007/s00521-021-06463-z

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  • DOI: https://doi.org/10.1007/s00521-021-06463-z

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