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Understanding the Predictive Relationship Between Wireless Network Experience and Customer Churn

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  • Michael Dienhart
  • Qu Yanzhen

Abstract

Wireless networks have transformed society, and their evolving capabilities support numerous economic and social goals. Continued investments in wireless technologies and network coverage by mobile network operators (MNOs) depends on their achieving a favorable return on investment. Retaining existing customers by reducing churn is the most financially efficient means to improve economic returns, however the causes of customer churn are not fully understood due to the lack of studies on the relationship between wireless network quality and customer churn. This quantitative study leveraged existing secondary data from one MNO containing nine network quality factors, which formed three network quality constructs in the model, measured in 646 counties for one month in combination with a partial least squares structural equation modeling methodology to evaluate the predictive value of the network quality factors on customer churn. The study further assessed the degree to which the predictive value varies based on the population density of each county. The surprising findings suggest that network quality does not predict a meaningful amount of customer churn (p

Suggested Citation

  • Michael Dienhart & Qu Yanzhen, 2025. "Understanding the Predictive Relationship Between Wireless Network Experience and Customer Churn," European Journal of Electrical Engineering and Computer Science, European Open Science, vol. 9(2), pages 20-27, March.
    • Handle: RePEc:epw:ejece0:v:9:y:2025:i:2:id:19696
    DOI: 10.24018/ejece.2025.9.2.696
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