Location and uptake: integrated household and GIS analysis of technology adoption and land use, with application to smallholder dairy farms in Kenya

Abstract

CIS-derived measures of location and space have increasingly been used in models of land use and ecology. However, they have made few inroads into the literature on technology adoption in developing countries, which continues to rely mainly on survey-derived information. Location, with all its dimensions of market access, demographics and agro-climate, nevertheless remains key to understanding potential for technology use. The measures of location typically used in the adoption literature, such as locational dummy variables that proxy a range of locational factors, now appear relatively crude given the increased availability of more explicit GIs-derived measures. This paper attempts to demonstrate the usefulness of integrating CIS-measures into analysis of technology uptake, for better differentiating and understanding locational effects. A set of GIs-derived measures of market access and agro-climate are included in a standard household model of technology uptake, applied to smallholder dairy farms in Kenya, using a sample of 3330 geo-referenced farm households. The three technologies examined are keeping of dairy cattle, planting of specialised fodder, and use of concentrate feed. Logit estimations are conducted that significantly differentiate effects of individual household characteristics from those related to location. The predicted values of the locational variables are then used to make spatial predictions of technology potential. Comparisons are made with estimations based only on survey data, which demonstrate that while overall explanatory power may not improve with CIS-derived variables, the latter yield more practical interpretations, which is further demonstrated through predictions of technology uptake change with a shift in infrastructure policy. Although requiring large geo-referenced data sets and high resolution GIS layers, the methodology demonstrates the potential to better unravel the multiple effects of location on farmer decisions on technology and land use.

Adoption of dairy farming technologies by small farm holders: practices and constraints

“…About 46.1% farmers were small land holding and 35.6% were medium (< 1 ha) and there had insignificant association between land size and adoption of dairy. The finding is contrary to the study of Staal et al (2002), which found a positive correlation between these two qualitative variables. Only 15 percent farmer's main source of income was dairy farming, 14 percent farmers received credit and 11 percent farmers received extension services (Table 1).…”

Farm intensification and drivers of technology adoption in mixed dairy-crop systems in Santa Cruz, Bolivia

“…In this case, farmer i adopts a certain technology if the derived benef its B i are higher that a certain threshold T (Staal et al, 2002):…”

“…These technologies could be clearly identified with a pathway of dairy intensification. The explanatory variables were selected based on previous studies on factors influencing technology adoption and development pathways (Nicholson et al, 1999;Staal et al, 2002, Baltenweck et al, 2003Pender, 2004). These variables included: distance of farm to the nearest populated area as indicator of location and access to markets; level of education of farmer and age of farmer representing characteristics of the household head in relation to management capacity; size of farm land and herd size because it was considered that technological development could be scale dependent; level of technical assistance because it was considered that information and advise can facilitate technology adoption; and finally family income considering that economic position of the household influences the possibility of technological investments.…”

“…Among the different factors found in the literature, the most frequently considered are: education and behavioural characteristics of the farmer (Nicholson et al, 1999;Baerenklau, 2005); information sources and presence of programmes and organizations for transference (Pender, 2004;Adegbola and Gardebroek, 2007); and access to financial and input/output markets (Nicholson et al, 1999;Baltenweck et al, 2003), which is closely related to farm location (Staal et al, 2002).…”

Identifying Investment Opportunities for Ruminant Livestock Feeding in Developing Countries

“…The legumes were promoted because of their biological characteristics without taking account of the bio-physical and socio-economic factors that limited their adoption (Sumberg, 2002). Recent methods for analyzing smallholder systems and applying the innovation systems approach largely overcome these deficiencies and planted forage technologies can be targeted more effectively (Staal et al, 2002;Ouma et al, 2007;Tesfaye Lemma Tefera et al, 2010). See also for example fodder innovation research -Chapter 11.…”