# Information and Communication Technologies and Agricultural Production: New Evidence from Africa
## 1 Introduction  
Africa lags significantly behind the global north in terms of the use of ICT and other digital technologies in business activities, including agriculture, owing to the substantial financial investment and expertise required for providing digital technological services. While a large number of people now are hooked to the internet, fixed telephone, and mobile phones in most developed countries compared to a couple of decades ago, the use of digital technologies, however, is relatively less pronounced in Africa, particularly in agriculture [1]. Estimates by [PERSON] et al. [1], for example, indicate that only 13% of smallholder farmers in sub-Saharan Africa have access to various digital technologies. Indeed, internet penetration rate in sub-Saharan African countries has remained low. In sub-Saharan Africa, the internet penetration (individuals using the internet) was 16% in 2015 and rose to 29% of the population as of 2020 [2]. There is an uneven adoption of information and communication technologies by scale and geography within Africa. For instance, mobile money services dominate (85%) in Kenya, with presence among more than half (55%) of the population in Ghana, less than half (45%) in Tanzania, and relatively low (8%) in South Africa and Nigeria (4%) [1]. As of 2021, there were 515 million mobile services subscribers in sub-Saharan Africa, representing about 46 percent of the population [3]. Recent estimates show that 40% of the adult population is connected to mobile internet, whereas 44% of individuals live in areas with mobile network coverage, but they do not use mobile internet services [3]. Notwithstanding the uneven coverage, a positive effect has been established between mobile money services and financial inclusion, welfare, and other development outcomes in sub-Saharan Africa (SSA) [4; 5; 6; 7]. Meanwhile, significant advances in the use of technology in agriculture in developed economies have occurred in the last two-three decades, culminating in the birth of what is termed \"precision agriculture\", which involves machine software and sensors as well as more contemporary agricultural technologies, such as drones, robots, and farm management software. This development has occasioned the emergence of terminologies such as digital farming [8], smart farming [9; 10], agriculture 4.0 [11; 12], and Farming 4.0 [13; 14]. Technological advances have led to substantial improvements and scaling up of innovations driven by terminologies such as the internet of things (IoT), cloud, artificial intelligence (AI), gene editing, and big data in consolidating the fourth agricultural revolution [15; 16]. Agriculture 4.0 involves the adoption of digital technologies in managing agricultural production and processes [17; 18] in monitoring production variables of interest [19] contingent on the scientific dataset [12; 20; 21; 22]. The data shape and guide food crop cultivation and animal rearing up to processing [23; 24], reducing production costs and minimizing wastage by only using essential inputs [25; 26]. [PERSON] et al. [27] argued that digital technologies promote sustainable agriculture. Agriculture 4.0 includes the use of information and communication technologies (including big data, IoT--internet of things, GPS--geographical positioning systems) on farmers' farms to improve efficiency and productivity [12; 15; 28; 29]. Agriculture 4.0 steps in to effectively address the uncertainties in the agricultural value chain [12; 30]. More recently, the exigencies of the COVID-19 pandemic have made more apparent the critical role of ICT in agricultural development and, hence, the need to ramp up use of ICT in agricultural production in SSA and reap the potential benefits thereof. The existing literature suggests that ICT facilitate information sharing including agricultural extension and advisory services in emerging and developed economies, helping to reduce information asymmetries and transaction costs [31; 32; 33].