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Determinants of mobile Internet adoption by Malian consumers
This article aims to determine the factors that may explain the adoption of mobile internet in Mali. For this, we used the Logit binary model. This model was estimated by the maximum likelihood method. The data used come from the survey conducted in 2020 by the Research Group in Solidarity and Industrial Economy (GRESI). The results from the econometric estimate show that the adoption of mobile Internet in Mali is explained by age, gender, marital status, professional status, income, price and level of computer training. The results suggest the implementation by the sector regulator of measures allowing greater competition in the Malian mobile Internet market.(original abstract)
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Determinants of mobile Internet adoption by Malian consumers
This article aims to determine the factors that may explain the adoption of mobile internet in Mali. For this, we used the Logit binary model. This model was estimated by the maximum likelihood method. The data used come from the survey conducted in 2020 by the Research Group in Solidarity and Industrial Economy (GRESI). The results from the econometric estimate show that the adoption of mobile Internet in Mali is explained by age, gender, marital status, professional status, income, price and level of computer training. The results suggest the implementation by the sector regulator of measures allowing greater competition in the Malian mobile Internet market.(original abstract)