This article was written by Mango, J., Duncan G, W., Kiiru, N., Chao, H,. Olango, J,. Amolo, A,. Nekesa, L,. and Chizi, M from DDD's research team.
The DSO project’s research team recruited participants in rural, peri-urban and urban areas of Vihiga, Kisumu, Nairobi, Mombasa and Kilifi. The sample was designed to achieve a statistically valid, location representative sample of individuals aged between 18 and 35 years who purchased or received their first smartphone within the last six months, and reported an average daily income of 5USD or below.
The target sample size for the survey was 150 in total for the five sites but we targeted 60 respondents in each site in case
- Recruited respondents dropout of study either voluntary or move out of study area
- Recruited respondents do not meet the project’s requirements ( average daily income of 5USD or below and less than 6 months smartphone ownership).
The recruitment process started by introducing the project to the county commissioners1 in each location. The county administrations were supportive of DSO since it was geared towards the people they are also trying to empower by offering free training on how to use digital platforms in order to learn about income generating activities, of which can assist them to be self employed. This involves providing free accessible information through print media and also in the county website, this is achievable by providing free internet services within the county headquarters.
In Kisumu, the project was introduced in the chief “baraza” the local administration meeting. In other areas, village elders introduced the project to traders in marketplaces who were then able to recommend potential respondents. Surprisingly, this process required a month to complete because few people (students, SME traders, casual laborers,) own smartphones in Vihiga, Kisumu and Kilifi, contrary to Nairobi and Mombasa where there are many early adopters. As of 2016, only 16% percent of Kenyan adults have a smartphone and just 18% accessed Internet in the past 4 weeks2.
During recruitment, a questionnaire was used to capture topics on age, gender, educational background, duration of phone ownership, income generating activities and, most importantly, willingness to participate in the study by staying in the area for one year. The questionnaire was recorded electronically during face-to-face interviews in English, using a translator where local languages were preferred (usually Kiswahili).
We learned that there is need for outlets that are selling the smartphones need to explain to the customers who are purchasing the smartphone the full aspects of the phone. This can also be incorporated in the interventions of project to train respondents on different operating systems of a smartphone, the advantages and disadvantages of each.
Most interestingly, respondents showed a lack of knowledge about their phone's operating system consistently across all sites. With that in mind, our researchers checked each prospective respondent’s smartphone to confirm that they were running some variant of Android. Some prospective respondents were not aware of the different operating systems for smart phones, and were surprised to learned about the variety. Most only knew of smartphones by their iconic touch screens and thought one system underpinned all of them. Others believed they owned an Android smartphone, but, on confirmation, researchers were able to observe that their phones were running a different operating system. As most respondents were surprised to learn that we have what we called operating system that varies across phone.
Picture by Duncan Washington-->
Kisumu had more respondents recruited in the 25-30 age bracket compared to other sites. Within the age 18-24 bracket there is no significant difference across the study sites. In general very few people above the 31–35 age group are first-time smartphone users who earn less than 5USD per day, because perhaps, simply due to their age, they may have owned their own smartphone in the past.
There is no significant difference in gender of the respondents recruited at each site.
Kisumu, Nairobi, Mombasa and Vihiga have more respondents who have completed secondary level education as compared to Kilifi. In Kilifi there is no significance difference in educational level of the recruited respondents.
Kisumu had the highest number of respondents with casual employment as the main income source. With respect to Regular employment1, Mombasa and Kilifi had the highest number of recruited respondents, while Nairobi, Kisumu and Vihiga had significantly lower numbers. For Self-Employment there was no significant difference between sites—the numbers were almost equal.
A county commissioner is an official appointed by the President of the Republic Kenya to represent government at the county level. ↩
Central Bank of Kenya, Kenya National Bureau of Statistics & FSD Kenya. (2016). The 2016 FinAccess Household Survey on financial inclusion. Nairobi, Kenya: FSD Kenya. ↩
Regular employment in this context refers to a job that someone is sure of getting an income after a specific period. ↩