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A Bayesian Networks Approach To Modeling Financial Risks Of E-Logistics Investments

Author

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  • CHIEN-WEN SHEN

    (Department of Business Administration, National Central University, No. 300, Jhongda Rd., Jhongli City, 32001, Taiwan)

Abstract

To evaluate whether the investments of e-logistics systems may increase financial risks, models of Bayesian networks are constructed in this study with the mechanism of structural learning and parameter learning. Empirical findings from the transport and logistics sectors suggest that the e-logistics investments generally do not increase the financial risks of companies except the implementation of computer aided picking systems and radio frequency identification. Meanwhile, only the investment of enterprise resource planning can reduce the financial risks and enhance the profitability at the same time. Generally speaking, most advanced e-logistics investments do not yield financial advantages for the transport and logistics companies from the perspective of Bayesian inference. Empirical study based on the proposed models also demonstrates the practicability of Bayesian models.

Suggested Citation

  • Chien-Wen Shen, 2009. "A Bayesian Networks Approach To Modeling Financial Risks Of E-Logistics Investments," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 8(04), pages 711-726.
    • Handle: RePEc:wsi:ijitdm:v:08:y:2009:i:04:n:s0219622009003594
    DOI: 10.1142/S0219622009003594
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    Cited by:

    1. Брагинский О.Б.* & Татевосян Г.М.** & Седова С.В.***, 2019. "Управление Программами Развития (На Примере Химического Комплекса)," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 55(3), pages 74-85, июль.

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