Characterization of the levels of cassava commercialization among smallholder farmers in Kenya: A multinomial regression approach

Abstract

Cassava commercialization is a concept that has been used by many development practitioners because of its possible strategic role in transforming livelihoods of smallholder farmers in subSaharan Africa, including Siaya and Kilifi Counties in Kenya. This concept can easily be implemented when the levels of commercialization is known. However, empirical evidence reveals little information on the levels of cassava commercialization amongst smallholder farmers in these counties. Thus effective policy interventions on cassava commercialization for these farmers are difficult to implement, since there is no proper understanding of their levels of cassava commercialization. Therefore the main objective of this paper was to characterize levels of cassava commercialization among smallholder farmers. Factors influencing cassava commercialization were also evaluated. The data was collected from 381 farm households in Siaya and Kilifi Counties (Kenya).This data was used to calculate the Household Commercialization Index (HCI) and Value Addition Indices (VAI) which were then integrated to form the Commercialization Index (CI). This integrated index formed the basis for categorizing the levels of commercialization. A multinomial regression model was used to evaluate factors that affect levels of commercialization. The results obtained revealed that majority of smallholder farmers' operate at low and medium categories with very few of them at high level. Distance to the market, cassava acreage, schooling years, gender and marketing costs were the key determinants of the levels of commercialization. In order to promote high level commercialization, the study recommends developing policies that enhance formal education among farmers, optimal usage of land and minimization of transportation costs through infrastructural development.

Factors influencing the level of commercialization among smallholder cassava farmers in Taita-Taveta and Kilifi Counties, Kenya

“…Hence, as the household size increases, smallholder cassava farmers are more likely to participate in lower categories of commercialization levels. This result is similar to that of Florence et al (2017) who found out that, in Kilifi county households with larger number of people were likely to participate at lower categories of commercialization level because larger households exerted pressure on the limited resources available in the homestead including farm produce. Similarly, Agwu et al (2013) found out that, an increase in the household size reduces the probability of farmers' orientation towards market commercialization due to its effect on increased domestic consumption needs.…”

“…This is because, an increase in distance to the market increases transport and production costs and therefore reducing gains from cassava farming hence discoursing cassava marketing. This result corresponds with that of Florence et al (2017), Muhammad-Lawal et al (2014, Agwu et al (2013) and Martey et al (2012) who found a negative relationship between distance to the market and commercialization, whereby Florence et al (2017) concluded that it was due to increase in transport and transaction costs.…”

“…Israel Glenn (1992) and Singh and Masuku (2014) outline four different procedures of determining a sample size. This study reached a sample size of 250 cassava farming households by imitating other related studies that include Florence et al (2017), Kehinde and John (2015), Martey et al (2012) and Musah et al (2014).…”

“…Area under cassava is a proxy for the quantity of cassava produced. As the area increases, the quantity produced is more likely to increase proportionately and consequently, the quantity available for marketing (Florence et al, 2017). According to the results in Tables 2 and 4, the area under cassava has a positive and significant influence on the level of commercialization.…”

“…The HCI ranges from zero to one and it measures how a farmer is market oriented. Different studies including Abera (2009), Florence et al (2017), Muricho et al (2015), Musah et al (2014), Martey et al (2012), and Omiti et al (2009) have used the HCI to categorize different farmers into different commercialization levels. The general assumption is that, the closer to one the index is, the greater the farmer is market oriented and therefore a higher market participation.…”