2019•International Journal of E-AdoptionOpen access

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

Kenneth David Strang, Narasimha Rao Vajjhala, Nankyer Sarah Bitrus

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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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What this paper is about

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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Available 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.

Key concepts: Agriculture, Sample (material), Agricultural science, Rural development, Socioeconomics, Linear discriminant analysis, Rural area, Geography

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