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An Exploratory Analysis of Price Sensitivity in Mobile Data Usage in Kisumu County: A Qualitative Analysis
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1708700 Vol 8 · Issue 11 Download Paper

An Exploratory Analysis of Price Sensitivity in Mobile Data Usage in Kisumu County: A Qualitative Analysis

Nyauchi Vincent Otieno Dr. Yasin Ghabon Kuso

Subject area: Arts, Social Sciences and Humanities  ·  Area of research: Price Sensitivity in Mobile Data Usage

Abstract

This journal paper explores the dynamics of price sensitivity in mobile data usage in Kisumu County using an exploratory, qualitative approach. The study aims to understand consumer behavioral patterns in response to mobile data pricing in a low to middle-income urban Kenyan context. Theoretical frameworks such as the Law of Demand, Price Elasticity of Demand, and Engel?s Law are applied to guide the analysis. Data was sourced secondarily from institutional reports, academic literature, and online consumer feedback. Thematic analysis, supported by NVivo-style qualitative coding, was employed to extract behavioral patterns from the collected data. Findings suggest a high degree of price sensitivity among lower-income groups, heavy use of promotional bundles, and dynamic provider-switching behavior, all reflecting elasticity in consumer behavior. The paper concludes with recommendations for mobile service providers and policymakers to design inclusive and competitive pricing structures. This study offers a foundation for further mixed-methods research in digital service consumption.

References

[1] Aker, J.C., & Mbiti, I.M. (2010). Mobile phones and economic development in Africa. Journal of Economic Perspectives, 24(3), 207–232.

[2] Chabossou, A., et al. (2009). Demand for mobile services in Africa. Information Economics and Policy, 21(4), 250–261.

[3] Communications Authority of Kenya. (2022). Quarterly Sector Statistics Report Q3 2022/2023. Nairobi: CAK.

[4] Communications Authority of Kenya. (2023). Annual Report 2022/2023. Nairobi: CAK.

[5] Marshall, A. (1920). Principles of Economics. London: Macmillan.

[6] Odhiambo, L. (2021). Mobile data pricing and consumer behavior in Kenya. Kenya Journal of Economics and Policy, 5(1), 41–55.

[7] Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–292.

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How to cite this paper

Nyauchi Vincent Otieno, Dr. Yasin Ghabon Kuso "An Exploratory Analysis of Price Sensitivity in Mobile Data Usage in Kisumu County: A Qualitative Analysis" Iconic Research And Engineering Journals Volume 8 Issue 11 2025 Page 1957-1964
Nyauchi Vincent Otieno, Dr. Yasin Ghabon Kuso "An Exploratory Analysis of Price Sensitivity in Mobile Data Usage in Kisumu County: A Qualitative Analysis" Iconic Research And Engineering Journals, vol. 8, no. 11, May. 2025
Nyauchi Vincent Otieno, Dr. Yasin Ghabon Kuso (2025). An Exploratory Analysis of Price Sensitivity in Mobile Data Usage in Kisumu County: A Qualitative Analysis. Iconic Research And Engineering Journals, 8(11).
Nyauchi Vincent Otieno, Dr. Yasin Ghabon Kuso "An Exploratory Analysis of Price Sensitivity in Mobile Data Usage in Kisumu County: A Qualitative Analysis" Iconic Research And Engineering Journals, vol. 8, no. 11, May. 2025.
@article{1708700,
      author = {Nyauchi Vincent Otieno, Dr. Yasin Ghabon Kuso},
      title = {An Exploratory Analysis of Price Sensitivity in Mobile Data Usage in Kisumu County: A Qualitative Analysis},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {8},
      number = {11},
      pages = {1957-1964},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1708700.pdf},
      abstract = {This journal paper explores the dynamics of price sensitivity in mobile data usage in Kisumu County using an exploratory, qualitative approach. The study aims to understand consumer behavioral patterns in response to mobile data pricing in a low to middle-income urban Kenyan context. Theoretical frameworks such as the Law of Demand, Price Elasticity of Demand, and Engel?s Law are applied to guide the analysis. Data was sourced secondarily from institutional reports, academic literature, and online consumer feedback. Thematic analysis, supported by NVivo-style qualitative coding, was employed to extract behavioral patterns from the collected data. Findings suggest a high degree of price sensitivity among lower-income groups, heavy use of promotional bundles, and dynamic provider-switching behavior, all reflecting elasticity in consumer behavior. The paper concludes with recommendations for mobile service providers and policymakers to design inclusive and competitive pricing structures. This study offers a foundation for further mixed-methods research in digital service consumption.},
      month = {May},
  }