A review article on the impact and challenges of mobile phone usage on agricultural production in Africa

Figures & data

Figure 1. Describes the PRISMA process for selecting appropriate papers.

Table 1. Distribution of catfish farmers according to sources of information

Information source	Users		Non-users
	Freq	%	Freq	%
Television	98	81.7	22	18.3
Radio	95	79.2	25	20.8
Billboard	31	25.8	89	74.1
Newspaper	66	55.0	54	45.0
Contact groups	94	78.3	26	21.7
Extension agents	79	65.8	41	34.2
Internet	82	68.3	38	31.7

Figure 2. The average digital skill of people by sector across the five countries in 2019 in Africa.

Source: International Finance Corporation (IFC), 2021.

Table 2. The estimated adoption rate of digital skills in the agricultural sector across five countries

Country	2019 (%)	2030 (forecasted) (%)
Cote d’Ivoire	5–10%	20–25%
Kenya	15–10%	35–40%
Mozambique	0–5%	10–15%
Nigeria	5–10%	25–30%
Rwanda	5–10%	25–30%

Source: International Finance Corporation (IFC), 2021.

Table 3. Connections and networks in Africa, 2018

Description	Percentage per 100 population
Fixed broadband connections	0.4
Covered by a mobile cellular network	88.9
Covered by a 3G network of better	73.1
Covered by LTE or WiMAX network	33.8

Source: (Corrigan, 2020).

Table 4. Internet usage in some African countries, 2017

Country	Percentage
Tunisia	64.2%
Gabon	62.0%
Morocco	61.8%
Cabo Verde	57.2%
South Africa	56.2%
Senegal	46.0%
Nigeria	42.0%
Kenya	17.8%
Central African Republic	4.3%
Guinea-Bissau	3.9%
Burundi	2.7%
Somalia	2.0%
Eritrea	1.3%

Source: (Corrigan, 2020).

Table

No.	Author	Scope	Country	Method	Study Approach	Topic	Time and Scope	Title
1	Chikuni and Kilima (2019)	Post Production	Malawi	Quantitative and Qualitative Analysis	Yes	Yes	Yes	Smallholder farmers’ market participation and mobile phone-based market information services in Lilongwe, Malawi
2	Alant and Bakare (2021)	Pre-production	South Africa	Descriptive and Inferential Statistics	Yes	Yes	Yes	A case study of the relationship between smallholder farmers’ ICT literacy levels and demographic data w.r.t. their use and adoption of ICT for weather forecasting
3	Courtois and Subervie (2015)	Post-Production	Sub-Saharan Africa	Choice Experiment and Descriptive Analysis	Yes	Yes	Yes	Farmer Bargaining Power and Market Information Services
4	Daum et al. (2021)	Pre-Production	Nigeria	Quantitative and Qualitative Analysis	Yes	Yes	Yes	Uber for tractors? Opportunities and challenges of digital tools for tractor hire in India and Nigeria
5	Emeana et al. (2020)	Pre and Post Production	Africa	Descriptive Analysis	Yes	Yes	Yes	The Revolution of Mobile Phone-Enabled Services for Agricultural Development (m-Agri Services) in Africa: The Challenges for Sustainability
6	Freeman and Qin (2020)	Pre-Production	Uganda	Quantitative Analysis (Logit model	Yes	Yes	Yes	The Role of Information and Interaction Processes in the Adoption of Agriculture Inputs in Uganda
7	Graham et al. (2012)	Pre-production	Kenya	Quantitative and Descriptive Analysis	Yes	Yes	Yes	Mobile phone communication in effective human-elephant conflict management in Laikipia County, Kenya
8	Henriksson et al. (2021)	Pre-Production	Malawi	Quantitative and Qualitative Analysis	Yes	Yes	Yes	Understanding gender differences in availability, accessibility and use of climate information among smallholder farmers in Malawi
9	Krone et al. (2016)	Post-Production	Kenya	Quantitative and Descriptive Analysis	Yes	Yes	Yes	The use of modern information and communication technologies in smallholder agriculture: Examples from Kenya and Tanzania
10	Mapiye et al. (2020)	Pre-Post Production	South Africa	Quantitative Analysis (Logit model)	Yes	Yes	Yes	Management information sources and communication strategies for commercially oriented smallholder beef cattle producers in Limpopo province, South Africa
11	Ngarava et al., (2019)	Post-Production	South Africa	Quantitative Analysis (Logit model)	Yes	Yes	Yes	Market Awareness and Participation for Cattle Farmers in the Kaonafatso ya Dikgomo (KyD) Scheme in KwaZulu-Natal Province, South Africa
12	Nakato et al. (2016)	Pre-Production	Uganda	Quantitative and Descriptive Analysis	Yes	Yes	Yes	Building agricultural networks of farmers and scientists via mobile phones: case study of banana disease surveillance in Uganda
13	Oyinbo et al. (2020)	Pre-production	Nigeria	Quantitative Analysis (Logit model)	Yes	Yes	Yes	Design of Digital Agricultural Extension Tools: Perspectives from Extension Agents in Nigeria
14	Muvhuringi et al. (2021)	Pre and Post Production	Zimbabwe	Quantitative (Descriptive analysis)	Yes	Yes	Yes	The impact of COVID-19 on agricultural extension and food supply in Zimbabwe
15	Karanasios & Slavova (2019).	Pre and Post Production	Ghana	Qualitative Analysis	Yes	Yes	Yes	How do development actors do ICT for development? A strategy-as-practice perspective on emerging practices in Ghanaian agriculture
16	Parlasca et al. (2020)	Post Production	Kenya	Quantitative Analysis (Regression)	Yes	Yes	Yes	Can mobile phones improve nutrition among pastoral communities? Panel data evidence from Northern Kenya
17	McCampbell et al. (2018)	Pre-Production	The Great Lakes Region and Rwanda	Descriptive Analysis	Yes	Yes	Yes	Xanthomonas Wilt of Banana (BXW) in Central Africa: Opportunities, challenges, and pathways for citizen science and ICT-based control and prevention strategies
18	Baumüller (2015)	Post-Production	Kenya	Quantitative and Qualitative Analysis	Yes	Yes	Yes	Assessing the Role of Mobile Phones in Offering Price Information and Market Linkages: The Case of M-Farm in Kenya.
19	Abdul‐Rahaman and Abdulai (2022)	Pre-Production	Ghana	Quantitative Analysis (Regression)	Yes	Yes	Yes	Mobile money adoption, input use, and farm output among smallholder rice farmers in Ghana
20	Birner et al. (2021)	Pre and Post Production	Global	Descriptive Analysis	Yes	Yes	Yes	Who drives the digital revolution in agriculture? A review of supply‐side trends, players and challenges.
21	Obayelu et al. (2021)	Pre and Post Production	Nigeria	Quantitative and Qualitative Analysis	Yes	Yes	Yes	Assessment of the Immediate and Potential Long-Term Effects of COVID-19 Outbreak on Socioeconomics, Agriculture, Security of Food and Dietary Intake in Nigeria.
22	Furuholt and Matotay (2011)	Post Production	Tanzania	Quantitative (Descriptive analysis)	Yes	Yes	Yes	The Developmental Contribution From Mobile Phones Across the Agricultural Value Chain in Rural Africa.
23	Baumüller (2012)	Post Production	Global including Africa	Qualitative Analysis	Yes	Yes	Yes	Facilitating Agricultural Technology Adoption Among the Poor: The Role of Service Delivery Through Mobile Phones
24	Bankole Dr and Mimbi (2017).	Post Production	Africa	Quantitative Analysis (Regression)	Yes	Yes	Yes	ICT infrastructure and it’s impact on national development: a research direction for Africa.
25	Willy et al. (2020).	Pre-Production	Africa	Descriptive Analysis	Yes	Yes	Yes	COVID-19 Pandemic in Africa: Impacts on agriculture and emerging policy responses for adaptation and resilience building.
26	Corrigan (2020).	Post-Production	Africa	Quantitative and Qualitative Analysis	Yes	Yes	Yes	Africa’s ICT Infrastructure: Its Present and Prospects

Corrigan, T. (2020). Africa’s ICT infrastructure: Its present and prospects.

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