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Predicting Global Internet Growth Using Augmented Diffusion, Fuzzy Regression And Neural Network Models

Author

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  • KALLOL BAGCHI

    (Department of IDS, College of Business, The University of Texas at El Paso, El Paso, TX 79968-0544, USA)

  • SOMNATH MUKHOPADHYAY

    (Department of IDS, College of Business, The University of Texas at El Paso, El Paso, TX 79968-0544, USA)

Abstract

Quantitative models explaining and forecasting the growth of new technology like the Internet in global business operation appear infrequently in the literature. This paper introduces two artificial intelligence (AI) models such as the neural network and fuzzy regression along with an augmented diffusion model to study and predict the Internet growth in several OECD nations. First, a linear version of an augmented diffusion model is designed. An augmented diffusion model is constructed by including an economic indicator, gross domestic product per capita, into the model. In the next step, two soft AI models are calibrated from the augmented diffusion model. Performance measures of predictions from these models on new samples show that these soft models provide improved forecast accuracy over the augmented diffusion model. The results confirm the major contribution of this research in predicting global Internet growth.

Suggested Citation

  • Kallol Bagchi & Somnath Mukhopadhyay, 2006. "Predicting Global Internet Growth Using Augmented Diffusion, Fuzzy Regression And Neural Network Models," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 155-171.
    • Handle: RePEc:wsi:ijitdm:v:05:y:2006:i:01:n:s0219622006001861
    DOI: 10.1142/S0219622006001861
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    Cited by:

    1. Robin Gubela & Artem Bequé & Stefan Lessmann & Fabian Gebert, 2019. "Conversion Uplift in E-Commerce: A Systematic Benchmark of Modeling Strategies," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(03), pages 747-791, May.
    2. Yi Xiao & Shouyang Wang & Ming Xiao & Jin Xiao & Yi Hu, 2017. "The Analysis for the Cargo Volume with Hybrid Discrete Wavelet Modeling," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 851-863, May.
    3. Gubela, Robin & Bequé, Artem & Gebert, Fabian & Lessmann, Stefan, 2018. "Conversion uplift in e-commerce: A systematic benchmark of modeling strategies," IRTG 1792 Discussion Papers 2018-062, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

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