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A network data envelopment analysis (NDEA) model of post-harvest handling: the case of Kenya’s rice processing industry

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Abstract

Food security is a global challenge. With rising world population and demand for food being compounded by resource and arable land constraints, raising the efficiency of food production and use has become increasingly important. While much of the research on food security is focused on farm efficiency and productivity, most neglect post-harvest (PH) handling which is critical in determining the availability of food. In this study, we employ the network Data Envelopment Analysis (DEA) model to evaluate the PH efficiency of milling, using data from Kenya’s rice processing industry. The results show lower efficiency scores when using a network DEA model, which reflects its greater discriminatory power when compared to the standard DEA approach. The study also quantified sources of productive efficiency using a fractional regression model and identified storage space and distance to market as having an impact on drying efficiency; while experience, age of mill, servicing and energy type influenced milling efficiency. The results suggest that policy makers should focus on investing in drying technologies and storage facilities to improve drying efficiency. To improve milling efficiency, policy recommendations include enhancing millers’ access to better technologies, investing in reliable sources of energy and providing PH handling workshops to reduce PH losses.

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Notes

  1. For studies that use the Malmquist productivity index at industry level, see Lee (2013).

  2. Paddy here refers to unhulled rice grain, which is threshed but unmilled rice grain.

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Acknowledgements

The authors acknowledge financial support for data collection involved in this research from Australian Awards Africa. The views expressed in the article, however, are solely of the authors and do not necessarily reflect the views of the supporting agency.

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Authors and Affiliations

  1. Department of Agriculture and Resource Economics, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya

    Eucabeth Majiwa

  2. School of Economics and Finance, Queensland University of Technology, Brisbane, QLD, Australia

    Boon L. Lee & Clevo Wilson

  3. Graduate School of Fisheries Science and Environmental Studies, Nagasaki University, Nagasaki, Japan

    Hidemichi Fujii

  4. Faculty of Economics, Kyushu University, 6-19-1 Hakozaki, Higashi-ku, Fukuoka, 812-8581, Japan

    Hidemichi Fujii

  5. Urban Institute and Engineering, Kyushu University, Fukuoka, Japan

    Shunsuke Managi

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  1. Eucabeth Majiwa
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Correspondence to Boon L. Lee.

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Majiwa, E., Lee, B.L., Wilson, C. et al. A network data envelopment analysis (NDEA) model of post-harvest handling: the case of Kenya’s rice processing industry. Food Sec. 10, 631–648 (2018). https://doi.org/10.1007/s12571-018-0809-0

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