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Barham, J. and Chitemi, C, "Collective action initiatives to improve marketing performance. Lessons from farmer groups in Tanzania," CGIAR systematic program on collective action and property rights. Working Paper No. 74, 2008.

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Article

Influence of Collective Action Participation on Technical Efficiency among Smallholder Producers: A Case of Banana Farmers in Kisii and Nyamira, Kenya

1Department of Agricultural Economics, Egerton University, Nakuru, Kenya

2Tegemeo Institute of Agricultural Policy and Development, Nairobi, Kenya


Journal of Food Security. 2020, Vol. 8 No. 3, 105-116
DOI: 10.12691/jfs-8-3-4
Copyright © 2020 Science and Education Publishing

Cite this paper:
Wilfred Omondi, Hillary Bett, Timothy Njagi. Influence of Collective Action Participation on Technical Efficiency among Smallholder Producers: A Case of Banana Farmers in Kisii and Nyamira, Kenya. Journal of Food Security. 2020; 8(3):105-116. doi: 10.12691/jfs-8-3-4.

Correspondence to: Wilfred  Omondi, Department of Agricultural Economics, Egerton University, Nakuru, Kenya. Email: wuodajeli@gmail.com

Abstract

The main aim of the paper is to analyse the influence of collective action participation defined as group participation on technical efficiency among smallholder banana producers in Kisii and Nyamira Counties, Kenya. Using stochastic frontier approach, the study evaluated how farmers in collective action differ from non-collective action participants in terms of technical efficiency levels of banana production as well as the factors responsible for inefficiencies among farmers. Logistic regression model is also used to determine the characteristics of group participation among the smallholder producers. The findings were based on cross-sectional data with a sample size of 260 smallholder banana producing households obtained through a multi-stage sampling technique. From the results obtained from logistic regression, salaried occupation had a significant adverse effect on group participation, while age, gender, education level, informal occupation, mobile phone ownership and access to extension advice had a significant positive impact. Besides, the stochastic production frontier model estimates showed that group members were more technically efficient than non-members at the 1% significance level. Field size, use of manure and inorganic fertilizer had a significant positive effect on productivity levels with high returns to scale exhibited among non-group members. Inefficiency levels were significantly affected by the age, gender and occupation of the household head. In conclusion, collective action helps farmers to address various production needs, thus making them more technically efficient.

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