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A computational analysis of capital chain rupture in e-commerce enterprise

Author

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  • Yi Song

    (Huazhong University of Science and Technology)

  • Bin Hu

    (Huazhong University of Science and Technology)

  • Zhihan Lv

    (Qingdao University)

Abstract

E-commerce has rapidly developed in China. Despite a large number of emerging e-commerce enterprises, many of them withdraw from the market because of capital chain rupture. To expand the market share, enterprises usually reduce the price of a product or gain positive public opinion to enhance their influence on the market. However, improper methods may lead to capital chain rupture and disrupt the development of the enterprise. This thesis views one kind of product from e-commerce enterprise studies on the influence of promotional methods and stocking strategies on internal indexes such as cash flow and investor trust, as well as external indexes such as loyalty. The study then analyzes how these indexes affect the capital chain rupture of enterprises and determine the intrinsic mechanism underlying the promotional methods and stocking strategy. This study uses the multi-agent model and system dynamics to simulate the influence of internal and external indexes on a capital chain. The result is expected to provide suggestions for e-commerce enterprises.

Suggested Citation

  • Yi Song & Bin Hu & Zhihan Lv, 2018. "A computational analysis of capital chain rupture in e-commerce enterprise," Electronic Commerce Research, Springer, vol. 18(2), pages 257-276, June.
    • Handle: RePEc:spr:elcore:v:18:y:2018:i:2:d:10.1007_s10660-017-9278-3
    DOI: 10.1007/s10660-017-9278-3
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    1. Michael R. Baye & John Morgan, 2009. "Brand and Price Advertising in Online Markets," Management Science, INFORMS, vol. 55(7), pages 1139-1151, July.
    2. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    3. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    4. Xuanming Su & Fuqiang Zhang, 2008. "Strategic Customer Behavior, Commitment, and Supply Chain Performance," Management Science, INFORMS, vol. 54(10), pages 1759-1773, October.
    5. Stigler, George J., 2011. "Economics of Information," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 5, pages 35-49.
    6. Xuanming Su, 2007. "Intertemporal Pricing with Strategic Customer Behavior," Management Science, INFORMS, vol. 53(5), pages 726-741, May.
    7. Erica Plambeck & Qiong Wang, 2009. "Effects of E-Waste Regulation on New Product Introduction," Management Science, INFORMS, vol. 55(3), pages 333-347, March.
    8. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    9. Xinxin Li & Bin Gu & Hongju Liu, 2013. "Price Dispersion and Loss-Leader Pricing: Evidence from the Online Book Industry," Management Science, INFORMS, vol. 59(6), pages 1290-1308, June.
    10. Jeffrey S. Stonebraker, 2013. "Product-Generation Transition Decision Making for Bayer's Hemophilia Drugs: Global Capacity Expansion Under Uncertainty with Supply-Demand Imbalances," Operations Research, INFORMS, vol. 61(5), pages 1119-1133, October.
    11. Dou, Wenyu & Ghose, Sanjoy, 2006. "A dynamic nonlinear model of online retail competition using Cusp Catastrophe Theory," Journal of Business Research, Elsevier, vol. 59(7), pages 838-848, July.
    12. James D. Dana, Jr. & Nicholas C. Petruzzi, 2001. "Note: The Newsvendor Model with Endogenous Demand," Management Science, INFORMS, vol. 47(11), pages 1488-1497, November.
    13. Noah Gans, 2002. "Customer Loyalty and Supplier Quality Competition," Management Science, INFORMS, vol. 48(2), pages 207-221, February.
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