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E-business system investment for fresh agricultural food industry in China

Author

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  • Ziping Wang

    (Morgan State University)

  • Dong-Qing Yao

    (Towson University)

  • Xiaohang Yue

    (University of Wisconsin-Milwaukee)

Abstract

A fresh agricultural food online exchange system is gradually becoming an emerging e-business model in China. However, how and when to make an investment in this new business model is risky due to the unique characteristics of fresh agricultural food. In this paper, from a third party decision maker’s perspective, we propose an evolutionary discounted cash flow model to investigate the optimum time point for investment. Based on the assumptions of base demand, the derived e-demand occurring on the pendent e-business system can be characterized by non-stationary stochastic processes. Then our new model can further be innovatively analyzed by considering the dynamic scheme of the cash flow and its evolution. The analytical results suggest the optimal investment time point depends upon the consumers’ switch rate from the physical store to e-store and on the urbanization rate. A Monte Carlo simulation is further presented to compare the effects of multiple uncertainties embedded into the system. Our uncertainty analysis reveals that when government financial support fluctuates greatly, the optimal investment time could be either in the very beginning or in the end. This optimal time strategy also holds for the random demand factor after the coefficient variation of the demand reaches a certain threshold.

Suggested Citation

  • Ziping Wang & Dong-Qing Yao & Xiaohang Yue, 2017. "E-business system investment for fresh agricultural food industry in China," Annals of Operations Research, Springer, vol. 257(1), pages 379-394, October.
    • Handle: RePEc:spr:annopr:v:257:y:2017:i:1:d:10.1007_s10479-015-1830-8
    DOI: 10.1007/s10479-015-1830-8
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    References listed on IDEAS

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    Cited by:

    1. Yael Perlman & Yaacov Ozinci & Sara Westrich, 2022. "Pricing decisions in a dual supply chain of organic and conventional agricultural products," Annals of Operations Research, Springer, vol. 314(2), pages 601-616, July.
    2. Lin, Feng & Jia, Tao & Wu, Feng & Yang, Zhen, 2019. "Impacts of two-stage deterioration on an integrated inventory model under trade credit and variable capacity utilization," European Journal of Operational Research, Elsevier, vol. 272(1), pages 219-234.
    3. Liu, Molin & Dan, Bin & Zhang, Shuguang & Ma, Songxuan, 2021. "Information sharing in an E-tailing supply chain for fresh produce with freshness-keeping effort and value-added service," European Journal of Operational Research, Elsevier, vol. 290(2), pages 572-584.
    4. Jingci Xie & Jianjian Liu & Xin Huo & Qingchun Meng & Mengyu Chu, 2021. "Fresh Food Dual-Channel Supply Chain Considering Consumers’ Low-Carbon and Freshness Preferences," Sustainability, MDPI, vol. 13(11), pages 1-29, June.
    5. Chen Wei & Sobhan Asian & Gurdal Ertek & Zhi-Hua Hu, 2020. "Location-based pricing and channel selection in a supply chain: a case study from the food retail industry," Annals of Operations Research, Springer, vol. 291(1), pages 959-984, August.

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