Analysis of Rural Households’ Mobile Phone Utilization Decision for Rural Innovation Services in Gomma Woreda, Southwest Ethiopia

Berhanu Daniso


Mobile phones have already started functioning as more than just communications devices. It can promote innovation services for rural farmers. However, there are factors affecting mobile phone utilization for rural innovation services. The aim of this study was to analyze rural households’ mobile phone utilization decision for rural innovation services in Gomma woreda, Southwest Ethiopia. Cross-sectional survey design was used for this study. Structured interview schedule, focus group discussion, key informant interview and personal observations were used as a method of data collection tools for this study. Multi-stage sampling technique was used for this study and data were collected by using both primary and secondary source of data from 188 sample household heads. Descriptive statistics including frequency and percentage and multivariate probit regression model were used for analyzing the data. The multivariate probit model was estimated jointly for marketing, agricultural, health and other mobile services. Wald test (χ2 (56) = 158.12, p = 0.000) and the likelihood ratio test LR (χ2 (6) = 30.4755, Prob>χ2 = 0.000) is significant at the 1% level. The result revealed that education level, distance, frequency of extension contact, network problem and off/non-farm income were found to be significantly affecting rural farmers’ mobile phone utilization decisions for rural innovation services. The correlation between using mobile for marketing and health service; marketing and other mobile services; and extension and other mobile service are negative and statistically significant. This indicates there was a competitive relationship of using mobile for marketing and health services, marketing and other mobile services and extension and other mobile service respectively. Therefore, rural mobile phone utilization for innovation services needed to be supported by stakeholders to solve the problems of mobile phone utilization in rural areas.

Keywords: Rural Innovation, Rural household, Mobile phone, Multivariate probit model, Utilization

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