Modelling and forecasting mobile money customer transaction volumes in rural and semi-urban Malawi: An autoregressive integrated moving average spatial decomposition

Mobile money technologies in Malawi have revolutionised banking and monetary transactions across geographical barriers. Prospects of profit have drawn mobile money agents to invest in the business but find it is more profitable when substantial customers subscribe to the cash-in and cash-out facilities of mobile money. Despite the initial success, several challenges have emerged, including regulatory hurdles, network reliability issues, and the need for increased financial literacy among users. The volumes of transactions in the rural areas are observably lower compared to urban areas. This study uses Bvumbwe township in Malawi to model and forecast the discrepancy of mobile money transactions in rural and semi-urban Malawi. The study uses ARIMA modelling to understand the temporal manifestation of mobile money subscription in these localities. Using ARMA (1,1) models decomposed for the semi-urban and rural area, the study finds that the semi-urban area has a disproportionately higher and lasting volume of mobile money transactions compared to the rural area. The study also finds that mobile money transactions are more susceptible to long-lasting effects of external shocks in the rural area compared to the urban area. Intuitively, the day-to-day relationship in the transactions is also stronger in the rural area. These findings highlight the need for tailored policy interventions to enhance mobile money adoption and utilization in different geographical contexts.

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Publication Details

Journal
Scientific African
Published
2024-10-17
DOI
https://doi.org/10.1016/j.sciaf.2024.e02430
Citations
1
Primary Topic
Human Mobility and Location-Based Analysis
Type
article
Field-Weighted Citation Impact
0.68
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article

Modelling and forecasting mobile money customer transaction volumes in rural and semi-urban Malawi: An autoregressive integrated moving average spatial decomposition

Winford H. Masanjala, Collins Duke Namakhwa, Wisdom Richard Mgomezulu, Betchani H. M. Tchereni et al.
1 citations
Scientific African
Human Mobility and Location-Based Analysis
0.68
article

Modelling and forecasting mobile money customer transaction volumes in rural and semi-urban Malawi: An autoregressive integrated moving average spatial decomposition

Winford H. Masanjala, Collins Duke Namakhwa, Wisdom Richard Mgomezulu, Betchani H. M. Tchereni, Danny Namakhwa, Steven Limbanazo Kuchande
article en
1 citations

Abstract

Mobile money technologies in Malawi have revolutionised banking and monetary transactions across geographical barriers. Prospects of profit have drawn mobile money agents to invest in the business but find it is more profitable when substantial customers subscribe to the cash-in and cash-out facilities of mobile money. Despite the initial success, several challenges have emerged, including regulatory hurdles, network reliability issues, and the need for increased financial literacy among users. The volumes of transactions in the rural areas are observably lower compared to urban areas. This study uses Bvumbwe township in Malawi to model and forecast the discrepancy of mobile money transactions in rural and semi-urban Malawi. The study uses ARIMA modelling to understand the temporal manifestation of mobile money subscription in these localities. Using ARMA (1,1) models decomposed for the semi-urban and rural area, the study finds that the semi-urban area has a disproportionately higher and lasting volume of mobile money transactions compared to the rural area. The study also finds that mobile money transactions are more susceptible to long-lasting effects of external shocks in the rural area compared to the urban area. Intuitively, the day-to-day relationship in the transactions is also stronger in the rural area. These findings highlight the need for tailored policy interventions to enhance mobile money adoption and utilization in different geographical contexts.

Scientific AfricanVol. 26
University of Malawi (MW), Malawi University of Science and Technology (MW), Malawi Government (MW)
Sustainable cities and communities
Openalex Percentile: Top 21%
Human Mobility and Location-Based Analysis
0.68
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