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Application of the grey Lotka–Volterra model to forecast the diffusion and competition analysis of the TV and smartphone industries

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  • Wang, Hsi-Tse
  • Wang, Ta-Chung

Abstract

To achieve competitive advantages, companies need to embrace changes and evolve strategies for coping with challenges when time and data are limited. This study applies grey forecast theory with the Lotka–Volterra competition model to explore the dynamic competition between smart TVs and flat panel TVs, as well as Android and iOS smartphone operating systems (OS). The results show the growing strength of smart TVs and the Android OS is superior to other competing products. With respect to the interactive relationship between products, the two aforementioned products represent the competition relationship of predators and prey: flat panel TVs and iOS are playing the role of prey, while smart TVs and Android are the predators. After comparing forecast accuracy among the model proposed in this study, the grey forecasting model GM(1,1), and Lotka–Volterra model, we found the proposed model has the best accuracy. Companies can use the proposed model to develop a strategic plan feasible enough to secure a sustainable competitive advantage.

Suggested Citation

  • Wang, Hsi-Tse & Wang, Ta-Chung, 2016. "Application of the grey Lotka–Volterra model to forecast the diffusion and competition analysis of the TV and smartphone industries," Technological Forecasting and Social Change, Elsevier, vol. 106(C), pages 37-44.
    • Handle: RePEc:eee:tefoso:v:106:y:2016:i:c:p:37-44
    DOI: 10.1016/j.techfore.2016.02.008
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    Citations

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    Cited by:

    1. Gatabazi, P. & Mba, J.C. & Pindza, E. & Labuschagne, C., 2019. "Grey Lotka–Volterra models with application to cryptocurrencies adoption," Chaos, Solitons & Fractals, Elsevier, vol. 122(C), pages 47-57.
    2. Szalkowski, Gabriel Andy & Mikalef, Patrick, 2023. "Understanding digital platform evolution using compartmental models," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    3. Gatabazi, P. & Mba, J.C. & Pindza, E., 2019. "Modeling cryptocurrencies transaction counts using variable-order Fractional Grey Lotka-Volterra dynamical system," Chaos, Solitons & Fractals, Elsevier, vol. 127(C), pages 283-290.
    4. Yang, Chunyu & Huang, Jue & Lin, Zhibin & Zhang, Danxia & Zhu, Ying & Xu, Xinghua & Chen, Mei, 2018. "Evaluating the symbiosis status of tourist towns: The case of Guizhou Province, China," Annals of Tourism Research, Elsevier, vol. 72(C), pages 109-125.
    5. Chul-Yong Lee & Sung-Yoon Huh, 2017. "Technology Forecasting Using a Diffusion Model Incorporating Replacement Purchases," Sustainability, MDPI, vol. 9(6), pages 1-14, June.
    6. Dingxuan Huang & Claudio O. Delang & Yongjiao Wu & Shuliang Li, 2021. "An Improved Lotka–Volterra Model Using Quantum Game Theory," Mathematics, MDPI, vol. 9(18), pages 1-17, September.

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