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The effect of service rollout on demand forecasting: The application of modified Bass model to the step growing markets

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  • Velickovic, Stevan
  • Radojicic, Valentina
  • Bakmaz, Bojan

Abstract

The purpose of this research is to develop a new forecasting model for gradual development of telecommunications network infrastructure. If technical support service is not provided in the whole territory, then the service cannot be simultaneously offered to the market. Therefore, the adoption process is performing in steps, following the systematic process of the infrastructure development. We propose the step growing market model with variable market potential, based on the fundamental Bass diffusion model. This model uses market segmentation and the simulation of various market scenarios in order to indicate effective service rollout. Demand forecasting is required in order to dimensioning of required network resources. Moreover, this model offers the insight into the operator's compromises regarding decisions in the network investment. The resulting plan is a network deployment strategy that defines temporal sequence of network layouts. Thus, the upgrade plan indicates which investments are indispensible at each point of time.

Suggested Citation

  • Velickovic, Stevan & Radojicic, Valentina & Bakmaz, Bojan, 2016. "The effect of service rollout on demand forecasting: The application of modified Bass model to the step growing markets," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 130-140.
    • Handle: RePEc:eee:tefoso:v:107:y:2016:i:c:p:130-140
    DOI: 10.1016/j.techfore.2016.03.018
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    Cited by:

    1. Edward Oughton, 2018. "Towards 5G: scenario-based assessment of the future supply and demand for mobile telecommunications infrastructure," Working Papers 2017/04 (revised), Cambridge Judge Business School, University of Cambridge.
    2. Szalkowski, Gabriel Andy & Mikalef, Patrick, 2023. "Understanding digital platform evolution using compartmental models," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    3. Singhal, Shakshi & Anand, Adarsh & Singh, Ompal, 2020. "Studying dynamic market size-based adoption modeling & product diffusion under stochastic environment," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    4. Pannhorst, Matthias & Dost, Florian, 2019. "Marketing innovations to old-age consumers: A dynamic Bass model for different life stages," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 315-327.
    5. Han, Zhongya & Tang, Zhongjun & He, Bo, 2022. "Improved Bass model for predicting the popularity of product information posted on microblogs," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    6. Edward Oughton, 2017. "Towards 5G: scenario-based assessment of the future supply and demand for mobile telecommunications infrastructure," Working Papers 2017/04, Cambridge Judge Business School, University of Cambridge.

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