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Integrated Model of Demand for Telephone Services in Terms of Microeconometrics

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  • Kaczmarczyk Paweł

    (The State University of Applied Sciences in Płock, Faculty of Economics and Information Technology, Department of Economics, Nowe Trzepowo 55, 09-402 Płock, Poland)

Abstract

The paper presents the results of the testing effectiveness of the integrated model in the short-term forecasting of demand for telephone services in 24-hour cycles. The linear regression model with dichotomous (binary) independent variables was integrated with the feed forward neural network. The regression model was used as a filter of modelled variability of the demand. The neural network was used to model residual variability. The research shows that the integrated model has a higher possibility of approximation and prediction in comparison to the non-integrated linear regression model. The research study was based on data provided by the selected telecommunications network operator. The range of empirical material consisted of hourly counted seconds of outgoing calls and generated by network subscribers in various analytical sections.

Suggested Citation

  • Kaczmarczyk Paweł, 2016. "Integrated Model of Demand for Telephone Services in Terms of Microeconometrics," Folia Oeconomica Stetinensia, Sciendo, vol. 16(2), pages 72-83, December.
    • Handle: RePEc:vrs:foeste:v:16:y:2016:i:2:p:72-83:n:6
    DOI: 10.1515/foli-2016-0026
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    Cited by:

    1. Kaczmarczyk Paweł, 2018. "Neural Network Application to Support Regression Model in Forecasting Single-Sectional Demand for Telecommunications Services," Folia Oeconomica Stetinensia, Sciendo, vol. 18(2), pages 159-177, December.

    More about this item

    Keywords

    Decision Support System; linear regression; feed forward neural network; forecasting;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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