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<p>This research delves into the modeling of high technological product diffusion, considering uncertain marketing environments and dynamic market potential. We propose the novel diffusion models that incorporates a gamma distribution to represent marketing uncertainties realistically. The parameter estimation is performed using MATLAB’s optimization and machine learning tools, employing the non-linear least-square technique. Our results reveal that the proposed models demonstrate exceptional fitting performance, accurately capturing the adoption dynamics of Room Air Conditioner and Cloth Dryer. Moreover, models outperform benchmark model in forecasting future sales, evidenced by lower MAE and MAPE values. This substantiates the superior predictive capabilities of our proposed model, offering valuable insights for strategic decision-making and resource allocation in dynamic market environments.</p>

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Forecasting high-tech product diffusion with dynamic market potential and uncertain marketing environments

  • 期刊论文

  • 发表日期：

    2025年8月18日

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  • Shiva,
  • Neetu Gupta,
  • Anu G. Aggarwal

摘要

This research delves into the modeling of high technological product diffusion, considering uncertain marketing environments and dynamic market potential. We propose the novel diffusion models that incorporates a gamma distribution to represent marketing uncertainties realistically. The parameter estimation is performed using MATLAB’s optimization and machine learning tools, employing the non-linear least-square technique. Our results reveal that the proposed models demonstrate exceptional fitting performance, accurately capturing the adoption dynamics of Room Air Conditioner and Cloth Dryer. Moreover, models outperform benchmark model in forecasting future sales, evidenced by lower MAE and MAPE values. This substantiates the superior predictive capabilities of our proposed model, offering valuable insights for strategic decision-making and resource allocation in dynamic market environments.