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Marketing Strategy of Private Enterprises Based on Bayesian Dynamic Panel Model of Machine Learning Algorithms

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  • Siyu Sun

    (Zhejiang College, Shanghai University of Finance and Economics, China)

  • Juan Long

    (Chongqing City Vocational College, China)

Abstract

Machine learning algorithms have attracted widespread attention in both industry and academia. This article mainly studies the marketing strategy decision-making of private listed enterprises based on Bayesian panel data model. By constructing a Bayesian static panel data model and a Bayesian dynamic panel data model, an empirical analysis was conducted on the debt financing decisions of private enterprises from two aspects: external financial environment and internal governance. The experimental results show that the MC error and standard deviation of parameter estimation for Bayesian static panel data model and Bayesian dynamic panel data model are both very small. This method contains more information, increases observation data and degrees of freedom. This article provides important theoretical guidance for the coordinated development of private listed enterprises and state-owned enterprises. It is conducive to promoting the coordinated development of the entire national economy.

Suggested Citation

  • Siyu Sun & Juan Long, 2024. "Marketing Strategy of Private Enterprises Based on Bayesian Dynamic Panel Model of Machine Learning Algorithms," International Journal of Information Technology and Web Engineering (IJITWE), IGI Global, vol. 19(1), pages 1-19, January.
    • Handle: RePEc:igg:jitwe0:v:19:y:2024:i:1:p:1-19
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    References listed on IDEAS

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    1. Grażyna Iwanowicz-Palus & Mariola Mróz & Krystyna Kowalczuk & Beata Szlendak & Agnieszka Bień & Mateusz Cybulski, 2022. "Nurses Coping with Stressful Situations—A Cross-Sectional Study," IJERPH, MDPI, vol. 19(17), pages 1-11, September.
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