Examining e-Adoption of Agricultural Systems by Farmers in Central Nigeria

Examining e-Adoption of Agricultural Systems by Farmers in Central Nigeria

Kenneth David Strang (SUNY, Plattsburgh, USA), Narasimha Rao Vajjhala (American University of Nigeria, Yola, Nigeria) and Nankyer Sarah Bitrus (American University of Nigeria, Yola, Nigeria)
Copyright: © 2019 |Pages: 10
DOI: 10.4018/IJEA.2019070103

Abstract

In this study the authors examined what factors impacted the agricultural information system (AIS) electronic software adoption by rural farmers in central Nigeria. They collected a moderately large sample of responses from rural farmers and examined the generally accepted factors that were found in the literature. The authors applied nonparametric Spearman as well as canonical correlation along with discriminant analysis and developed a statistically significant classification model which used only three independent factors to predict AIS e-adoption. The results should generalize to other rural farm decision makers in Nigeria and the paper should be of interest to other researchers in this field.
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Introduction

Central Nigeria and other emerging countries are struggling with agriculture production to the extent that many citizens live in poverty (Fountas, Carli, Sørensen, Tsiropoulos, Cavalaris, Vatsanidou, & Tisseyre, 2015). Agriculture production in African countries once met 89% of the resident needs during the 1960s but this has dropped to 75% and continues to decrease (Thiendou, 1993). This drop in self-sufficiency was caused by political, economic, environmental issues as well as lack of technology adoption by comparison to competitors in other developing countries (Pinet & Papajorgji, 2014). An important problem is farmers are not adopting agricultural information systems (AIS) to help with crop planning (Aker, 2011), which is the problem we examine in this study.

According to Kim et al. (2015), an Agricultural Information System (AIS) is an information system that can among general agricultural data related to crops as well as their varieties, farm inputs, cultivation practices as well as farm activities. A Farm Management Information System (FMIS) can be considered to be a form of AIS which primarily deals with the collection, storage, and processing of data necessary to complete the operational functions in a farm (Kim et al., 2015).

Information systems and technology were initially used in the area of agriculture primarily for data storage and tasks, including financial accounting and bookkeeping. AIS and farm management information systems have evolved from simple recordkeeping into the adoption of complex information systems (Fountas et al., 2015). The adoption of technology was limited in the early days and the usage rate was low as well. However, with technological advancements, especially over the last decade, information systems have been used for a wide range of tasks, including the usage of tiny sensor nodes to advanced AIS and FMIS. The technological advancements were also coupled with a reduction in the cost of technology as well as increased awareness among farmers about the advantages of the use of technology. The development of AIS, as well as FMIS, has opened up possibilities for improved farm output. North and West European countries are considered to be data-integrated and have successfully integrated these technologies. However, there is limited research, especially in developing countries in Asia and Africa about the factors that contribute to the adoption and use of these technologies.

Agriculture contributes significantly to economic activity and employment in developing countries, especially in Africa. For instance, in Tanzania, the agriculture sector employs more than 70% of the total population (Tumbo et al., 2018). The agricultural sector in African countries is facing challenges, including political, economic, and geographical. For instance, climate change has affected the agricultural sector in African countries causing low productivity in agriculture. Such challenges can partly be addressed by the use of advanced technology to help in climate change prediction and adaption.

However, the information systems adoption and usage rate are rather low in African countries. The existing research in this area has identified some of the factors, including the limited number of agricultural extension workers, low levels of interactivity in the media, such as radio and television, as well as lack of awareness among the farmers. However, there is limited research exploring the influence of various demographic factors on the adoption and use of agricultural information systems. Considering that there are significant cultural differences between African countries as compared to European and Asian countries, exploring the role of demographic factors would contribute to understanding the issues influencing the adoption and use of AIS. Hence, investigating the role of various factors, especially, demographic factors might offer deeper insights into this problem.

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