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Sciknow Publications Ltd. JAERD 2014, 2(3):110-122 Journal of Agriculture Economics and Rural Development DOI: 10.12966/jaerd.08.06.2014 ©Attribution 3.0 Unported (CC BY 3.0)
Marketing Proclivity, Constraints and Opportunities in the
Sorghum Based Stockfeed Value Chain in Lusitu, Zambia
Lighton Dube1,*
, Joseph P. Musara2, Joyce Bediako
2, Vincent T. Munyati
3
1Faculty of Commerce and Law, Zimbabwe Open University, National Office, P.O Box MP 111, Mt Pleasant, Harare, Zimbabwe 2Faculty of Agriculture and Natural Resources, Africa University, P. O Box 1320, Mutare, Zimbabwe 3Department of Agricultural Economics, Education and Extension, Bindura University of Science Education, P. Bag 1020, Bindura, Zim-babwe.
*Corresponding author (Email: dubelig@gmail.com)
Abstract - This study unpacks marketing proclivity, constraints and opportunities that exist for farmers in the sorghum based
stockfeed value chain (VC) in Lusitu, Zambia. The objectives were to examine factors that influence the farmer’s decision to
market their produce and to analyse the marketing constraints and opportunities faced by farmers in the sorghum based stockfeed
VC. The study used a combination of data collection mechanisms including questionnaires, semi structured interviews and focus
group discussions. Friedman ranking test was used to determine marketing constraints and opportunities. Logit regression
modelling determined the factors that influence the farmer’s proclivity to market produce. The major marketing constraints were
identified as inefficient extension services and unreliable product markets. Of the 10 variables that had been hypothesised to have
an influence on sorghum grain marketing decision, 6 had the expected significant (p<0.05) influence. Inefficient marketing
systems were viewed as a major drawback to the functioning of the sorghum based stockfeed value chain in the study area.
Farmers noted labour shortages as the least constraint in marketing produce. Stakeholders need to develop, strengthen and par-
ticipate in low cost input supply systems. This will enable smallholder sorghum farmers to increase productivity and enhance
their chances of marketing the grain. Sorghum producers recommended and advocated for the establishment of producer asso-
ciations so that they can market produce with one voice thus strengthening their bargaining power.
Keywords - Marketing, Proclivity, Sorghum, Stockfeed, Value Chain
1. Background
Sorghum makes up about 20 % of the total cereal production
in Southern Africa and approximately 25 % in Africa. World
Bank (2008) stated that the top producers of sorghum in
Southern Africa are Botswana and Namibia. A significant
number of Southern African countries also produce sorghum
in the communal areas especially for subsistence. The pro-
duction of sorghum in Zambia dates back to many centuries
into the pre-colonial era. As reported by Hamukwala et al.,
(2010), sorghum production is mainly done in the country’s
Northern, Western, North-Western and Southern Provinces.
They further stated that yield levels for sorghum in these areas
have been as low as on average 0.55MT/ha (compared to
potential yields of 5 to 6MT/ha) for the past two to three
decades.
As highlighted in Figure1, between 1990 and 2008 sorg-
hum yields were reported by Hamukwala et al., (2010) to
have reached peak in 1993 at 0.76MT/ha and the lowest level
of 0.05MT/ha recorded in 2001. During the same period,
millet yield averaged 0.65MT/ha. Maize was however re-
ported to have averaged significantly higher at 1.52 MT/ha.
Sorghum and millet farmers experience a spectrum of
challenges ranging from limited access to input markets to
inadequate institutional support in their localities. The low
sorghum and millet yields have been mainly attributed to
farmers’ adherence to farm saved seed as the main source for
the next planting season. With a seed system that is not effi-
cient, the whole VC is affected since primary production is the
starting point of the chain. Zambia has experienced low rates
of sorghum seed replacements with minimal research and
development having taken place in the seed system.
Reports by World Bank (2008) point towards govern-
ments’ reluctance to embrace sorghum and millet as signifi-
cant cereal crops in their food security strategic plans. It is
reported that the improved NARS/SMIP varieties have in-
creased yields by up to 20 % as compared to conventional
varieties in the areas they have been taken up including Lusitu
and Siavonga in Zambia. There is also potential for further
gains if improved crop management methods are used. Their
early maturity characteristic of up to one month earlier than
conventional varieties significantly reduces risk of
drought-induced crop failure. Despite all the positives for the
Journal of Agriculture Economics and Rural Development (2014) 110-122 111
grain, uptake of the improved varieties still remains low even
in the semi-arid areas of Zambia. This has led to low aggre-
gate sorghum grain output and in the process compromising
the food security in these areas which have little economic
potential.
Figure 1. Sorghum, Millet and Maize Yields from 1990 to 2008 in Zambia
Source: Hamukwala et al., (2010)
(FARA, 2012; Hamukwala et al., 2010) also noted that the
other challenge is that once preferred crops in the drought
prone zones of Zambia such as cassava, sorghum and millet
were suddenly not being produced and consumed at their peak
levels. They reported that these trends have been mainly due
to the preferential treatment rendered to maize by the gov-
ernment through guaranteed pricing, input provision (FISP)
and provision of market infrastructure. The government has
however recently scrapped the fuel subsidy as it reorients its
maize support policy. The prevalence of policy skewness has
been said to have led to inappropriate enterprise choice. As
farmers attempted to benefit from the government support,
they ended up producing maize even in areas where sorghum
was more appropriate. A report by Chimai (2011) highlighted
that at the peak of government intervention in maize markets,
the crop accounted for just below 70 % of the total area
cropped in Zambia. In this policy environment, sorghum
production is now mainly done by a few resource constrained
smallholder farmers who lack the support, commercial
orientation and cannot produce enough for sale. This, coupled
with long distances to markets, high transportation costs and
high transaction costs act as barriers to entry for farmers and
investors leading to inefficient domestic sorghum markets.
Marketing of produce has therefore largely remained rudi-
mentary with very little, if any real gains from such transac-
tions.
Apparently in Zambia, considerable efforts have been
made to develop effective sorghum production and marketing
systems among smallholder farmers. However, according to
FARA (2012), adoption of sorghum production practices and
marketing is however still relatively low and so are the vo-
lumes of the grain being produced and traded. (Chimai, 2011;
Hamukwala et al., 2010) concurred when they observed that
in Zambia the low adoption of this potential food security
stabilizer was being affected by a number of socio-economic
and socio-cultural factors. These, they said include lack of
adequate support services, erratic and variable performance of
the production and marketing techniques. According to
Thomlow (2007), operations in agriculture such as planting
and weeding have relatively high labour demands and in most
cases smallholder farmers find themselves unable to cope
with these peaks. He further presented that in most small
holder farming communities, most farmers find themselves
with 2-3 labour people per household while at the same time
draught power remains a challenge. This compels farmers to
consider alternative ways of managing their labour, draught
power and financial resources. Production of government
supported crops such as maize come in as a more lucrative
alternative since some of the variable costs of production are
catered for by the government through input subsidy pro-
grams.
Technical efficiency is a major challenge for small farm-
ing communities in Southern Africa. Chimai (2011) reported
that the current efficiency levels in small farming communi-
ties of Zambia therefore present opportunities for sorghum
production and marketing improvement initiatives. The study
further reported that there is potential to double resources
productivity and income levels for farmers through technol-
ogy adoption and improved management practices. Hamuk-
wala et al., (2010) also concurred that without the right ma-
Yield trends (1990-2008)
0.00
0.50
1.00
1.50
2.00
2.50
3.00
2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990
Year
Metr
ic t
on
s/H
a
Maize
Sorghum
Millet
112 Journal of Agriculture Economics and Rural Development (2014) 110-122
cro-economic environment including favorable incentives
and effective extension services, resource constrained farmers
can hardly benefit from sorghum production and marketing
innovation platforms. This is so even in areas of low, erratic
rainfall and relatively high temperatures where the crop has
great potential to do well.
2. Research Problem
Marketing challenges have compromised the expansion po-
tential of agricultural systems especially for smallholder
farmers (UNIDO, 2009). The emergence of small grains as an
option out of household food security in marginalized farming
communities has been welcome and much research has been
done regarding the support structures on the production facet
of the VC. However there are still silent gaps in literature
regarding the challenges experienced by these farmers as they
attempt to embrace these small grains as safety nets for their
livelihoods in Zambia (FARA, 2012; Chimai, 2011; Ha-
mukwala et al., 2010). There is therefore need to analyze the
marketing challenges and opportunities for effective inter-
vention and grease the sorghum based stockfeed VC.
3. Research Questions
This study seeks to answer the following research questions in
the research area:
1) What are the determinants of farmers’ proclivity to
market sorghum grain?
2) What are the marketing challenges and opportunities
faced by farmers in the sorghum-stockfeed VC?
3) What strategies can be put in place to scale up mar-
keting initiatives in the sorghum-stockfeed VC?
3.1. Factors Affecting Adoption of Innovative Agricultural
Technologies
A number of social, economic and institutional factors have a
bearing on whether a farmer will take up an innovative
technology or not. These are presented in this section based on
empirical evidence by (Namara et al., 2007; Thomlow, 2007;
Feder and Zilberman, 2006; Baudron, 2001; Neil and Lee,
2001; Rogers, 1995) from previous studies on agricultural
innovation adoption. These factors are the once hypothesized
to have an influence on proclivity to market sorghum grain
(viewed as an innovation in this study) by farmers in Lusitu.
3.1.1. Proportion of non-farm income (PCNFINC)
Sorghum production is perceived as a practice for the poor
(World Bank, 2008). Studies have shown that on average,
well-to-do farmers (as depicted by the proportion of off-farm
income) are less likely to participate in “low level” technol-
ogy adoption such as sorghum production and marketing.
This is reported by Thomlow (2007) in his study on conser-
vation agriculture in Zimbabwe to be due to their social status
which forbids them from being associated with technologies
viewed to be of low status. As these farmers’ access to income
from off farm and non-farm sources increases, the likelihood
of participation has however been observed to increase but up
to some point (Namara et al., 2007). At higher levels of
off-farm and non-farm income, the farmers are less likely to
participate in for example sorghum marketing because they
have enough to finance their household needs and still remain
with enough for contingencies. This shows the importance of
cash as leverage in the initial adoption decision by farmers.
USAID (2010) concur with this and reports that in Tanzania
sorghum is mainly consumed directly in households and in the
brewing of traditional beers for rituals. The largest consumers
of sorghum are in rural areas and these are amongst low in-
come groups in most communities.
3.1.2. Duration in agricultural practice (DNSGM)
Duration in agricultural activities has been observed to sig-
nificantly influence the farmers’ decision to participate in an
innovative activity in the hope of increasing productivity and
incomes. Feder et al., (2006) argued that this is constructed in
the social dynamics of the communities under review where
in most cases there is dependency on agriculture for survival.
The duration in agriculture can also be taken to reflect the
extent to which the farmer is experienced.
3.1.3. Age of farmer (AGE)
Farmer’s age has been reported to have a negative influence
on the chances of innovation adoption. The negative sign for
the age variable in econometric models could be understood
from the commonly observed negative correlation between
the age and adoption decision for most innovations in dy-
namic economic environments (Namara et al., 2007; Rogers,
1995). Younger farmers tend to be more willing to adopt new
practices than their older counterparts. This idea is supported
by Rukuni, Tawonezvi, Eicher, Munyuki-Hungwe and Ma-
tondi (2006) who argued that being older creates a conserva-
tive feeling among farmers and hence resistance to change
especially in smallholder farming communities of Zimbabwe.
In his study, Baudron (2001) however observed that chances
of participation in technology adoption increased with age
because youths have little appreciation on the importance of
agricultural activities in most rural set ups and will take mar-
ginal effort to expand these activities. This variable therefore
has to be understood and analysed in the specific context and
characteristics of the study area in terms of development
prospects where there might exist untapped markets and
economic activities.
3.1.4. Education level (EDUC)
Education level as measured by the number of years in
schooling by household head has been significantly observed
to influence farmers’ inclination to participate on an innova-
tion platform (Neil et al., 2001). With more years in schooling
the probability of participation tends to decrease. Possible
explanations to this have been presented in literature as being
Journal of Agriculture Economics and Rural Development (2014) 110-122 113
that educated people tend to shun agriculture for white color
jobs and hence have alternative income sources. Some edu-
cated individuals are more concerned with time value of
money and will prefer projects with quick returns and prof-
itable like retailing in groceries and textiles. However, these
results differ from Thomlow (2007) who asserted that educa-
tion influences households’ ability to process information and
causes farmers to have better access to, understand and in-
terpret information regarding the potential benefits of the
innovation.
3.1.5. Land size (LNDSZ)
The effect of land size on adoption chances has been reported
to be positive. Studies have pointed towards the trend that
farmers with large arable land size have the opportunity to
spare some sections to try out new practices at less risk.
Hardaker, Huirne, Anderson and Lien (2004) argued that
large land size also implies that farmers can diversify into
other crops and reduce the inherent risk that is in agricultural
production. Despsch (2004) supported this by stating that the
size of the land is important because the transactional costs
are largely fixed costs that are spread across more potential
output on large farms. There are also observable indications
that increased participation in sorghum marketing is a func-
tion of land productivity (FARA, 2012).
3.1.6. Dependency Ratio (DPR)
Dependency ratio is the proportion of family members whose ages are less than 14 or more than 65.
14 65
Number of family members whose ages are less than or more thanDPR
Total number of family members (1)
This variable has been introduced into most of the models
explaining agricultural production innovation adoption as a
surrogate for household size to indicate the status of labor
availability in the household (Namara et al., 2007). The va-
riable has had a positive effect on the probability of adoption
decision. Researchers have reported that the higher the effec-
tive labour available the more likely the household is to par-
ticipate since chances of labour shortages during peak times
are low and this enhances the chances of favourable yields
(Rogers, 1995). However, Thomlow (2007) in his study of
conservation technologies reported that this variable does not
significantly influence the outputs since some of the tech-
nologies are labour extensive.
3.1.7. Gender (GNDR)
The sex of the household head has been reported in literature
to influence the adoption decision making. Coulibaly (2011)
reported that male farmers had higher chances of diversifying
to other crops in the event of low cotton prices as opposed to
women. This is because of the land tenure systems in most
African countries which favours male farmers. Rukuni et al.,
(2006) alluded to this when they noted that male farmers in
communal Zimbabwe are the dominant decision makers when
it comes to what to produce, how to produce, how much to
market and whether to market or not. (Kilima, Mbiha, Er-
baugh and Larson, 2010; Namara et al., 2007; Feder et al.,
2006) reported similar observations in their various studies on
innovation adoption in countries including Tanzania and
India.
3.1.8. Household size (HSZE)
This gives an indication of the demands for food and cash in
the household. Even though Thomlow (2007) argues that this
factor does not greatly influence the decision by farmers to
adopt conservation farming innovations. The main reason
may be that the systems do not require much labour as other
traditional farming technologies. However, Baudron (2001)
reported that in semi- arid Zambia, the larger the family, the
more the chances of adopting higher yielding conservation
innovation. This is so since there would be need to produce
enough for household consumption and market surplus for
other household expenses such as medical bills and contin-
gencies. This was alluded to by Despsch (2004) in his study of
no-till adoption innovations.
3.1.9. Average weighted price (AWTPRC)
Hardaker et al., (2004) stated that price is an important indi-
cator of market efficiency. This variable also serves the pur-
pose of sending signals in the market regarding which mar-
keting option to choose. Tefera et al., (2012) reported that in
semi-arid environments of Mali, farmers have overtime
shunned the production of sorghum regardless of the cereal’s
economic importance and its role as a major component of the
Malians’ diet. This has been reported to be driven by the
sensitivity of the farmers’ selection of crops to the relative
market prices and government intervention in markets for
these crops. This was seconded by Rukuni et al., (2006) who
also concur and reported that crop prices have influenced crop
enterprise choice in most communal areas of Zimbabwe. Most
of these farmers have shifted to cash crops which have higher
producer prices such as cotton and tobacco. However recent
reports in Zimbabwe’s communal sector point towards re-
duced hectares under cotton since the price has decline in the
past three seasons (2009-2012).
3.1.10. Frequency of extension visits (EXTN)
Extension services strengthen the farmer’s understanding of
agricultural developments in the production and marketing
spheres (Rukuni et al., 2006). This gives the farmer the right
information regarding appropriate farming and marketing
strategies in their localities. As observed in India, enhanced
contact with farmers means that the communication provides
a feedback loop where problems of farmers were aired and
addressed appropriately (Namara et al., 2007).
114 Journal of Agriculture Economics and Rural Development (2014) 110-122
3.2. Who Should Be On The Sorghum Marketing Promo-
tion Innovation Platform?
The promotion and support for crop production, processing
and marketing is applicable to all crops including annual
crops, horticultural crops and tradable crops. This is a holistic
approach to farming and includes seed development and
supply, integrated diseases and pest management techniques
and support services provision. In Southern Africa, there is
reported room (Rukuni et al., 2006) for further innovation
adoption opportunities especially if the farmers are educated
and information on innovation use and benefits provided in
the right forms. This calls for the need to bring on board
various stakeholders including farmers, farmer organizations,
government and its agents, NGOs, processors and the private
sector. Namara et al., (2007) reported that these actors will
have to be involved in various aspects in their domains to
influence the adoption of innovations as evidenced in their
study on microirrigation kits adoption in India. In Botswana
and Namibia sorghum seed development improvements have
been made at several levels to increase farm productivity.
This was done through collaboration of actors in the seed
systems. It has also been reported (FARA, 2012; Chimai,
2011) that sorghum production in Zambia has now been in-
cluded in the GRZ SFP Programme and is slowly widely
recognized country wide as a viable concept towards sus-
tainable agriculture.
There are a number of aspects required when introducing
farmers to the sorghum platform. Literature of innovation
adoption (FARA, 2012; Thomlow, 2007; Feder et al., 2006;
Despsch, 2004; Baudron, 2001) has shown that the entry point
is the exposure of farmers to different crop production sys-
tems and potential marketing options. FARA (2012) reported
that farmers and other chain actors appreciate the benefits of
an innovation when they are directly involved in the imple-
mentation process. This may be through participatory activity
and on-farm demonstrations to show the benefits and practi-
cality of new techniques such as the use of a newly introduced
sorghum variety for enhanced yields and returns. Tefera et al.,
(2012) however reported that the experience of INTSORMIL
PIs in the West African Sahel pointed towards the ineffec-
tiveness of the on-farm demonstration approach to catalyzing
adoption of cereal technologies. They said this is mainly
because of the differences that exist in the production and
marketing conditions and the extent of poverty in these fragile
and challenging environments.
Farmers are said to have a tendency to quickly adopt if
they notice successes of adopted innovations in their own
localities such as villages or wards. If farmers learn how the
production and marketing of sorghum in their arid conditions
can solve some of their problems they are more likely willing
to adopt the innovations.
FARA (2012) reported that extension workers or NGOs
involved need to describe the benefits and principles of the
practices (such as sorghum production and marketing). A
blended approach therefore needs to be embraced. This calls
for development agents to get to and make use of the farmer’s
farming environment as test sites and/or using lead farmers.
Such an approach allows observers (potential adopters) and
innovation users to relate the new practices with their pre-
vious experiences. Neil et al., (2001) reported that even if an
organization may target specific groups in the community,
such as vulnerable (including HIV/AIDS affected) house-
holds, it is important that the technology is introduced to
every farmer and other VC representatives in the introductory
stages.
FARA (2012) agreed with this in their report and argued
that if some social groups are excluded at this early stage, it
may hold back adoption by the wider community at later
stages. They further observed that another adoption catalyst
will be to train the farmers and processors in the practical use
of new innovations and technologies. Implementing innova-
tions with chain actors involve more than simply training but,
a change in attitude has to take place regarding what they
believe to be the correct way of resource allocation in their
domains. This has been observed for farmers, extension pro-
viders, researchers and policy makers (Baudron, 2001). These
strategies, they said, need to be combined with flexible
funding mechanisms and incentives, particularly during the
transition period. In Zambia the current key principles of
sorghum production and marketing have been reported to
challenge and conflict the government supported way Zam-
bians have farmed for many decades (Hamukwala, 2010).
Since in Zambia’s smallholder communities, existing institu-
tional structures need to be involved in overall sorghum
production, processing and marketing extension programmes,
it becomes a challenge to break the cycle of dependency on
the government for subsidies they were used to while pro-
ducing government supported crops such as maize. Chimai
(2011) argued that price stability is another integral part of
innovation adoption decision.
Cereal crop prices tend to be volatile (and collapsing in
most cases) across harvests especially in above normal yield
years and in below normal yield years. This, he suggested is
mainly attributed to pronounced public intervention that
characterises grain markets. It then becomes imperative to
integrate introduction of a new innovation related to cereals
with an all inclusive marketing plan.
FARA and its partner organizations advocates for the
scaling up of sorghum production and marketing in Zambia.
This is reportedly intended to drive increased farm produc-
tivity and profitability whilst preserving the environment for
future generations. FARA (2012) reported that they are
driving towards the self sustaining stages in the development
and use of sorghum varieties for improvements in land
productivity, reduced farming costs and environmental bene-
fits. There is need for a holistic approach to these integrated
activities which have to be done by a number of actors along a
viable commodity VC in a collaborative manner.
3.2.1. Description of Study Area
The Southern region of Zambia accounts for the highest
sorghum production (FARA, 2012). The areas include Sia-
Journal of Agriculture Economics and Rural Development (2014) 110-122 115
vonga, Lusitu, Sinazongwe, Chongwe, Luangwa, Petaukwe,
and Mambwe. These farming communities have an unfa-
vourable climate and provide little opportunities for economic
development. However agricultural practices in crops such as
sorghum, millet, maize and some livestock rearing in goats
and cattle are done in the areas where water sources are li-
mited. There is also isolated production of the crop in areas
such as Milenga, Masaiti and Seshoke. Figure 2 shows the
major sorghum producing areas in Zambia.
Figure 2. Major Sorghum Producing Areas in Zambia
Source: FARA (2012)
3.2.2. Research Design
Most methodologies in VCA (Hamukwala et al., 2010; Sa-
nogo, 2010; UNIDO, 2009; World Bank, 2008; Kaplinsky et
al., 2002) are premised on an understanding of the product
market since most chains are anchored on these markets as
their driving force. The study borrowed from the guiding
philosophy of these methodologies. The study adopted both
qualitative and quantitative approaches.
3.2.3. Sampling and Sample Size
The sampling frame consists of farmers including those who
are marketing or not marketing sorghum grain during the
DONATA/IPTA implementation period in Lusitu. The frame
also included handling agents, stock feed companies and other
actors involved in sorghum business such as wholesalers and
retailers of sorghum-stockfeed. The study used a multistage
sampling procedure. Initially purposive sampling was used to
identify the major sorghum producing areas in Zambia. Due
to time and financial resources limitations, the study could not
be done in all the areas. Chirundu District was selected con-
veniently. Lusitu was then selected from the district since it is
a DONATA/IPTA project area where the farmers have prac-
ticed sorghum production and marketing for a relatively long
time. Simple random sampling using the random number
generation technique was used to select 65 farmers for inter-
viewing. Babie (1998) stated that this selection criterion
creates equal chances of selection for each farmer into the
sample in the study area. Though the researcher was not
worried about the sample size per se, the sample size of 65
was used. This will be both for statistical analysis reasons as
well as the fact that larger samples include a greater percen-
tage of the population for the study purposes and hence yield
better results than smaller samples. There is also an inverse
relationship that exists between the standard error and the
sample size which favours larger samples (Woodridge, 2003).
Five agents, five wholesalers and fifteen retailers were se-
lected using the snowball technique. Two sorghum based
stockfeed processors were purposively selected.
3.2.4. Data Types and Collection Procedures
This study made use of both primary and secondary data
sources. Existing data from the DONATA/IPTA program
records, individual farmers, traders, processers, wholesalers
and retailers were used. Primary data were generated using
questionnaires which were personally administered to farmers,
traders, processors, wholesalers, retailers and consumers. This
was augmented with follow-up visits to discuss the responses
and explore opinions through Focus Group Discussions and
observations. Interviews were also held with the DONA-
TA/IPTA program representatives and other identified chain
stakeholders such as ZARI and MAL representatives. The
researcher was cautious of being too rigid and following
strictly the basic theory of VCs which suggests that linkages
are simple when in actual fact, the real world presents more
complex relationships. This called for making of arbitrary
116 Journal of Agriculture Economics and Rural Development (2014) 110-122
decisions especially at the identification of VC actors. Ethical
considerations were also taken into account. Respondents
were assured of aspects such as the confidentiality of the
information divulged to the researcher, their anonymity and
security from any form of harm. Data were captured in The
Statistical Package for Social Science (SPSS) and Microsoft
Excel computer programs for summarizing and analysis.
3.2.5. Analytical Procedures and Tools
Both qualitative and quantitative approaches were used in the
study. Researchers have tended to combine these two ap-
proaches so as to benefit from both depth and breadth of the
approaches in social research. This multi-method approach
has yielded better results as evidenced by improved efficiency
in most agricultural markets in terms of pricing and produc-
tion. The study adopted this approach to data analysis. The
analytical tools used were based on empirical studies in lite-
rature and the appropriateness of the tool to this study.
3.2.6. Logit Regression Model
Generally the term adoption refers to various processes and
stages as one uses an innovation (Rogers, 1995; Neil, et al.,
2001). However in the context of this study adoption is de-
fined to mean participation in any sorghum grain product
market during the duration of the DONATA/IPTA project
years. This definition created a binary dependent variable
since any farmer would either be an adopter or non adopter.
The specification of the logit model (derived from the logistic
regression function) allowed for the assessment of the de-
terminants of the marketing decision (Greene, 2000; Maddala,
1993) to embark on sorghum farming. The likelihood of ob-
serving the dependant variable (iP ) was tested as a function
of variables which include age, training and gender of
household head. Therefore:
expPr 1
1 expi i
ZP Y
Z
(2)
The natural log transformation of (2) results in (3):
0ln
1i i
ni
iii
P
P
(3)
,0
n
i i i ii
Z (4)
Where:
iP is the probability that the i
th farmer is a sorghum
marketer (Yi = 1)
0 is the intercept
i ’s are the slope parameters, and
i ’s are the independent variables.
The marginal effect for the model is given as:
exp 1.
1 exp 1 exp
ij
j
zP
X z z
(5)
In this model, the dependant variable, iZ in (4) is the
natural logarithm of the probability that a particular choice (in
this case the choice is adoption of the sorghum marketing
practice) would be made (Ramanathan, 2002). The logit
model implies diminishing magnitude of the partial effects for
the independent variables. The coefficients give the signs of
the partial effects of each of the independent variables on the
adoption probability (Woodridge, 2003). The dummy va-
riables included in this model were defined to distinguish
between two groups. In this study the coefficient estimates are
the ceteris paribus difference between the two groups such as
male and female sorghum marketing farmers.
3.3. Description of the Factors Affecting Proclivity to
Market Sorghum Grain by Farmers
The most common variables used in modelling innovation
adoption processes are human-capital variables (such as level
of education, age), attributes of the innovation, biophysical
and socio-economic variables, tenure system, resource en-
dowment, risk and uncertainty, social capital, and so-
cial-psychological factors (Namara et al., 2007; Feder et al.,
2006; Rogers 1995). In the present case, the variables hy-
pothesized to influence sorghum marketing adoption deci-
sions are summarized in Table 1.
Table 1. Description of Sorghum Marketing Proclivity Variables
Variable Description Units Expected Effect
Age (AGE) Age of household head Year -
Household size (HSZE) Number of family members Number +
Land size (LNDSZ) Size of arable land holding Hectare +
Education level (EDUC) Years of schooling by household head Number +
Dependency ratio (DPR) Proportion of dependant household members Percent +
Nonfarm income (PNFINC) Proportion of off farm income Percent -
Duration (DNSGM) Period farmer has been producing sorghum Years +
Extension (EXTN) Number of extension visits per week Number +
Gender (GNDR) Whether a farmer is female (0) or male (1) Dummy +/-
Price (AWTPRC) Average weighted price Currency +
Journal of Agriculture Economics and Rural Development (2014) 110-122 117
The variables were selected based on literature reviews of
the determinants of agricultural innovations including market
choices, conservation farming and new seed varieties mar-
keting (Hamukwala, 2010; Thomlow, 2007; Despsch, 2004;
Benites, 2003; Baudron, 2001; Neil et al., 2001), the technical
attributes of the sorghum marketing systems prevalent in the
study area and own understanding of the socioeconomic set-
ting of the study area.
The logit model was then operationalized as:
0 1 2 3 4 5 6 7iZ AGE HSZE LNDSZ EDUC DDPR PN NSGMFINC
8 9 10EXTN GEN A CDR WTPR (6)
3.4. Friedman Test
To rank the major constraints faced by the farmers in small-
holder sorghum producing communities of Lusitu, Friedman
test for ranking was used since it provides a mean rank for the
variables depending on the responses given by the farmers
basing on a predetermined scale. In this study the scale ranged
from 1=“extremely severe” to 5=“not a serious problem”.
4. Results and Discussion
4.1. Determinants of Farmers’ Proclivity to Participate in
Sorghum Marketing
The results of logit regression analysis are shown in Table 2.
This is a combined analysis of variables hypothesized to have
an effect on marketing adoption decision by sorghum farmers
in Lusitu. Analysing the variables in isolation could not have
provided the realistic interaction that takes place among the
variable in reality.
The adoption of sorghum marketing strategies was meas-
ured as to whether or not the farmer markets or does not
market sorghum grain during the duration of the DONA-
TA/IPTA project. This definition was reached at after realis-
ing that not all farmers who have produced sorghum in many
years have marketed their produce. A number have resorted to
using the grain for household consumption and other cere-
monial traditional events. It is of paramount importance to
take note that the dependent variable in the model (Zi) is not
participation in any sorghum grain market per se but the
probability of participation (Woodridge, 2003; Greene, 2000;
Maddala, 1983). This means that the coefficients against each
of the hypothesised independent variables represent the
change in the probability of participation given a unit change
in the corresponding independent variable. Most of the va-
riables that were captured in the model as shown in Table 2
had the expected signs as hypothesised in Table 1.
Table 2. The Relationship between Marketing Decision and Independent Variables
Variable Mean ± SE Coefficient Sig
CONSTANT -659.235 0.191
AGE 46.7 ± 1.416 -0.199 0.009**
HSZE 8.4 ± 0.434 -9.288 0.092
LNDSZ 3.1 ± 0.119 -21.794 0.005**
EDUC 7.95 ± 0.317 4.918 0.043**
DEPR 30.9 ± 1.951 -0.906 0.917
PNFINC 54.17 ± 1.046 14.320 0.039**
DNSGM 11.05 ± 1.308 1.218 0.027**
EXTN 1.03 ± 0.142 19.623 0.021**
GNDR 2.26 ± 0.271 -30.902 0.897
AWTPRC 1.51 ± 0.987 70.722 0.993
χ2 (df) 83.201(10)**
Percentage of correct predictions 60
Note: ** Significant at 0.05 (5 %)
Of the ten variables included in the regression model, six
had significant (p<0.05) effect on the sorghum grain mar-
keting decision by the farmer. These are proportion of off
farm income (PNFINC); duration in sorghum production
(DNSGM); farmer’s age (AGE); Education level (EDUC);
Land size (LNDSZ) and frequency of extension visits
(EXTN). However, dependency ratio (DPR); gender (GNDR);
household size (HSZE) and average weighted price
118 Journal of Agriculture Economics and Rural Development (2014) 110-122
(AWTPRC) had insignificant effect on marketing decision.
On average, well-to-do farmers who have a significant
share of household income contributed from nonfarm income
(PNFINC) are less likely to participate in the marketing of
sorghum grain. In the study, access to off farm and non-farm
income had the expected negative sign. This is in agreement
with (Musara, Chimvuramahwe, and Borerwe, 2012) who
observed in a conservation farming study in Madziva, Zim-
babwe that as farmers’ access to income from off farm and
non-farm sources increases, the likelihood of participation in
a new innovation platform initially increases but only up to
some point. In the context of this study, it shows the impor-
tance of cash from outside the farm as leverage especially in
the initial market participation decision of farmers since the
risk of failure is high. However, at higher levels of off-farm
and non-farm income, the farmers are less likely to participate
in the marketing of sorghum because they have adequate
finances for household needs and farming activities while
retaining reserves for contingencies. The essence of market-
ing agricultural produce is to generate incomes for various
purposes in the home such as payment of school fees, medical
bills, purchases of food, investments and savings. The major
nonfarm activities carried out by farmers in the study area
include fruit gathering, pensions and remittances.
In the context of the study, most farmers had on average
11 years producing sorghum. As per aprior expectations,
duration in agricultural activities (DNSGM) significantly
(p<0.05) influences the farmers’ decision to participate in
innovative farming and marketing practices. This is rooted in
the dependency of most communal communities on agricul-
ture as a livelihood strategy (Rukuni et al., 2006). The
chances of marketing adoption are higher for farmers with
more years of sorghum production experience as indicated by
the positive coefficient of 1.218. This may be due to the fact
that experience in production creates the ability of the farmer
to obtain, process and use information relevant to other op-
tions of commercialising sorghum production. In essence the
experience has the tendency of generating confidence among
the farmers leading to higher proclivity to venturing in mar-
keting of produce as a source of income.
Farmer’s age (AGE) had the expected negative sign and
significant (p<0.05) influence on the chances of farmers par-
ticipating in sorghum marketing. The negative sign for the age
variable could be understood from the commonly observed
negative correlation between the age of decision makers and
adoption decision for most technologies especially in eco-
nomically fragile environments. Observations are that
younger farmers have a higher proclivity (odds) towards new
practises in production and marketing as compared to their
older counterparts. A study conducted by (Namara et al., 2007)
in India highlighted that with increase in age, farmers tend to
shun new micro-irrigation farming practices for less de-
manding cropping systems since these have low transactional
costs. Additionally, older farmers are in most cases risk averse
and are unwilling to take up innovative options such as par-
ticipating in new markets. This they argue is an attempt to
avoid risk associated with these untested strategies. This idea
is supported by Neil et al., (2001) in their study of cover crops
in Northern Honduras who argued, that being older creates a
conservative feeling among farmers and hence resistance to
change. In his study, (Thomlow, 2007) however observed that
chances of participation in conservation farming increased
with age because youths have little appreciation on the im-
portance of agricultural activities in most rural set ups and
will take marginal effort to expand these activities.
Frequency of extension visits (EXTN) had the expected
positive effect on the likelihood (log odds) of participation.
This means that the more farmers are exposed to extension
services, the more likely they are to participate in markets.
The role of extension is to capacitate the farmer with the
requisite skill and knowledge on sustainable production and
marketing practices (Rukuni et al., 2006). This is achieved by
availing up to date information on market prices and the
benefits of commercial agriculture through embracing agri-
culture as a business as opposed to subsistence mindsets
which most communal farmers have. In their study in Tan-
zania, Kilima et al., (2010) also alluded to the role of agri-
cultural training in influencing agricultural technologies
adoption.
Education level (EDUC) as measured by the number of
years of schooling by household head significantly (p<0.05)
influence farmers’ participation in sorghum markets. How-
ever with more years in schooling the probability of partici-
pation tends to decrease.
A possible explanation to this is that educated people tend
to shun agriculture for white color jobs in Lusitu and sur-
rounding areas (including Siavonga and Lusaka). Some
households are more concerned with time value of money and
will prefer projects with quick return and profitable like
broiler production. However, these results differ from find-
ings by (Rogers, 1995; Schrader, 2009) who asserted that
education influences household to process information and
causes farmers to have better access to understanding and
interpretation of information. These traits are important in
marketing decision since this involves accessing and
processing marketing information.
Land size (LNDSZ) significantly, influenced farmer par-
ticipation in sorghum marketing. A possible explanation to
this could be that farmers with large arable land size have the
opportunity to spare some sections to try out new practices
such as contracting farming at less risk. Baudron, (2001)
supported this in a study of conservation farming practices in
Zambia by stating that the size of the land is important be-
cause the transactional costs are largely fixed cost that are
spread across more potential output on large farms. There are
also observable indications that increased participation in
conservation farming is a function of land productivity.
Olukosi and Echado (2006) alluded that large land size also
implies that farmers can diversify into other crops and reduce
the inherent risk that is in agricultural production.
Dependency ratio (DPR) which is the proportion of family
members whose ages are less than 14 or more than 65 was
Journal of Agriculture Economics and Rural Development (2014) 110-122 119
introduced into the model as a surrogate for household size.
This variable is an indicator of the status of labor availability
in the household. The variable had a positive and insignificant
(p>0.05) effect on the market participation decision. The
higher the effective labour available the more likely the
household is to participate since chances of labour shortages
during peak times are low. This enhances the chances of
favourable yields which can be used for household consump-
tion.
The sex of the household head (GNDR) has an insignifi-
cant (p>0.05) bearing on the chances of deciding to partici-
pate in sorghum grain marketing. Even though women do
much of the farming, the marketing decisions are made by the
males in the home.
In the study, results show that young farmers regardless of
gender have higher odds (chances) of participating in sorg-
hum grain markets. This contradicts with Coulibaly (2011)’s
findings in a cotton study in Mali where female headed
households had more challenges in diversifying to other crops
in the wake of cotton price drops as compared to males.
Household size (HSZE) has no significant (p>0.05) im-
pact on the farmer’s chances of participating in any sorghum
grain market. As opposed to agricultural production studies
were household size would imply more labour available,
marketing of produce does not necessarily follow the same
trends. The processes do not require much labour and as such
the size of the household does not affect the decision. How-
ever, Njuki, Kaaria, Sanginga, Kaganzi and Magombo (un-
dated) presented a case for larger households requiring more
market linkages since the incomes generated from these ac-
tivities will be used for the higher demands for finances in the
home such as school fees, medical expenses and food.
Interestingly, average weighted price (AWTPRC) had the
expected positive but insignificant (p>0.05) effect on the
marketing participation decision by farmers in Lusitu. The
price is an indicator of the efficient functioning of markets
and as such is expected to significantly affect the decisions by
farmers as to whether they should participate in a given
market. Higher producer price usually imply higher revenues
and gross margins (Erickson et al., 2002) which are favoura-
ble to farmers. In semi-arid environments of Mali, Tefera et
al., (2012) reported that farmers have overtime shunned the
production of sorghum regardless of the cereal’s economic
importance and its role as a major component of the Malians’
diet. This has been reported to be driven by the sensitivity of
the farmers’ selection of crops to the relative market prices
and government intervention in markets for these crops.
However, Reardon et al., (2007) argued that even though
producer prices are important determinants of market choice,
this variable has been overshadowed by aspects of health and
safety of products.
4.2. Challenges and Opportunities Faced By Farmers in
Sorghum Marketing
There are a number of identified issues which limit the po-
tential of farmers to effectively market their sorghum grain.
These are presented in this section.
4.3. Marketing Challenges Faced By Farmers
The results from Friedman rank test and the associated test
statistic are as presented in Table 3. Unreliable product mar-
kets and poor extension systems were highly ranked as the
extremely severe challenge by farmers while labour shortages
were the least problematic challenge.
Table 3. The ranking of marketing challenges and associated test statistic
Challenge Mean Rank Rank of challenge
Poor extension services delivery 5.34 1
Unreliable product market 5.25 2
Inefficient finance services 4.99 3
Costly inputs 4.83 4
Costly transport 4.47 5
Low producer prices 4.43 6
Late delivery of inputs 4.21 7
Unavailability of inputs 3.99 8
Labour shortages during critical stages 3.48 9
N 65
Test Statistics (a)
N Chi-square df Asymp sig
65 38.622 7 0.000
a Friedman Test
In this section marketing was presented in its broader
perspective to include both input and product markets.
a) Before production: Farmers cited the late delivery of
quality input supply as a major challenge to effective
production. Production factors such as fertilizers and
pesticides are expensive while quality seed of different
120 Journal of Agriculture Economics and Rural Development (2014) 110-122
sorghum varieties are relatively available but have not
been multiplied and distributed to farmers at the right
time and quantity for early planting. Farmers mainly
depend on seed from the previous season and since
2009, FARA has also been providing seed to selected
farmers in the DONATA/IPTA project. Both these
mechanisms have been unreliable and farmers ended
up planting the crop late. As a result the crop has suf-
fered from mid season dry spells culminating in low
yields. Faced with low yields, farmers are left with no
option but to reserve the little yield for household
consumption. Rural finance is also an integral part of
sorghum production, just like any other crop enterprise
(Rukuni et al., 2006). The absence of financing me-
chanisms in the study area imply that farmers have to
rely on savings, loans from friends and relatives and
cash from non-farm activities such as selling milk to
finance agricultural activities. The unreliability of
these strategies greatly compromise timely acquisition
of inputs.
b) During production: In Lusitu, extension service deli-
very is inefficient with almost no contact between ex-
tension officers and farmers. This implies that sorg-
hum production has remained rudimentary and unin-
formed. Market and marketing information are ingre-
dients to effective marketing decision making by far-
mers (Hardaker et al., 2004; Kaganzi, undated). In the
study area agriculture practises are still poor and the
land used is not always the most suitable for sorghum.
Hamukwala et al., (2010) also concur that without the
right macro-economic environment including favora-
ble incentives and effective extension services, re-
source constrained farmers can hardly benefit from
sorghum production and marketing innovation plat-
forms. This is so even in areas of low, erratic rainfall
and relatively high temperatures where the crop has
great potential to do well. Observations also showed
that the uptake of water and soil conservation farming
strategies is still very low as farmers are continuing
with practices that lead to land degradation.
c) Post production: In Lusitu, handling agents hig-
hlighted that storage of the grain is difficult, and stor-
ing facilities are not the most appropriate or missing in
some cases. This has led to significant losses along the
chain as some grain deteriorates during storage.
Sorghum producers in the study area are too small,
producing an average of 0.81MT/ha on an average area
of 0.6ha per household. The farmers have weak nego-
tiating capacities since they rarely receive any training
on farm management principles such as marketing in
competitive environments. Industrial Restructuring
Project (2000) observed that if logistics are compli-
cated and difficult with traders and middleman con-
trolling the market, then the market becomes ineffi-
cient. This is the case in the study area where there are
no sorghum farmers’ associations to dialogue with
buyers on pricing. The tiny size of the sorghum market
in Southern Zambia means millers have to import
sorghum from other regions where productivity has
been reported by Chimai (2011) to be high. Problems
are encountered in supplying adequate volumes to
markets. This is compounded by the purchasing power
of Zambians which represents the main limitation for
market penetration, expansion and growth.
4.4. Opportunities and Suggested Marketing Solutions
Farmers were interviewed on how they suggest the marketing
problems they currently face may be redressed. Their res-
ponses are presented in Table 4.
Table 4. Farmer Suggested Marketing Solutions
Suggested marketing solutions Responses (%) Rank of solution
Integration with markets 100 1
Increase extension officer to farmer ratio 99 2
Government subsidy in sorghum 93 3
Training on marketing strategies 89 4
Form farmer associations to negotiate prices 65 5
Strengthen cooperatives to provide finance and transport 48 6
Penetrate more rewarding markets 44 7
N 65
Farmers agreed on a number of possible intervention
mechanisms including vertical and horizontal integration in
current markets. This is in line with a report by DFID (2008)
which argued that market linkages are an integral part of
market development. These linkages provide useful informa-
tion, inputs and feedback mechanisms on the needs of market
Journal of Agriculture Economics and Rural Development (2014) 110-122 121
participants. De Klerk (2007) concurred that this enhances
market efficiency since the barriers to entry and exit are re-
duced. However generally farmers did not appreciate the need
to penetrate more rewarding markets or strengthen the coop-
eratives as potential options out of the marketing challenges.
This conflicts with the findings of Esterhuizen et al., (2007)
who argued that partnerships are drivers which smoothens the
wheel of marketing. This variation in opinion may be due to
the fact that sorghum farmers in the study area have been
members of cooperatives for a long time and they do not see
these as a way out of issues such as low market prices of high
transport costs. Financial Times Business (2012) reported that
it is important to train farmers on up to date marketing strat-
egies if they are to actively participate in value chains. The
need for training was also echoed by sorghum farmers in
Lusitu as a potential option to improved market access. In
relation to this, respondents also suggested the need for ex-
tension contact to be improved. They appreciated the role of
extension in information generation and dissemination as
alluded to by in studies (Hancock, undated; Louw, 2007).
More frequent visits by extension officers will keep the far-
mers updated on latest market developments such as seasonal
price variations, existing potential partnerships and new
markets.
Farmers also suggested that they could benefit greatly
from government subsidy programs on sorghum as is the
current case with maize. They stated that this program can
include inputs such as seed and fertilizer as well as support in
the output market in terms of subsidized transport and guar-
anteed prices for their produce. This is in line with Rukuni et
al., (2006) who presented a case for government's expenditure
decisions as having important implications for small holder
agriculture in Zimbabwe. They reported that subsidy pro-
grams in the 1980s increased yields in especially cotton. This
resulted in small holder farmers being the major contributors
(with around 70 %) towards the national cotton output.
Webber (2010) in his report on enhancing the competi-
tiveness of African agriculture agreed that the role of the
government in agricultural markets is to support the under
resourced stakeholders financial and by providing linkage
networks to markets. However, Stamm (2004) contradicts
these views when he reports that fiscal policy changes
prompting adjustments in government spending can trigger
expansion of the government deficit. He added that fears of
inflationary deficit spending must be carefully balanced
against the positive effects government spending can have on
national income and employment growth.
5. Summary and Conclusions
In the study area, results show that farmers who market
sorghum grain constitute almost two thirds of the farming
population. Most non marketers have not been trained in farm
management principles while 80 % of the farmers who have
received training are non marketers. This shows that the farm
management training offered to sorghum farmers has some
influence on the decision to market the produce.
At 5 % level of significance, proportion of off farm in-
come (PNFINC); duration in sorghum production (DNSGM);
farmer’s age (AGE); Education level (EDUC); Land size
(LNDSZ) and frequency of extension visits (EXTN) have a
significant impact on the decision to participate in sorghum
grain markets. However, dependency ratio (DPR); gender
(GNDR); household size (HSZE) and average weighted price
(AWTPRC) have no significant effect on marketing decision.
Sixty percent of the variables in the model had the expected
effect on the proclivity to market sorghum grain.
Unreliable product markets and poor extension delivery
systems were highly ranked as the extremely severe challenge
by farmers while labour shortages were the least problematic
challenge. Farmers highlighted a number of possible inter-
vention mechanisms including vertical and horizontal inte-
gration in current markets. However generally farmers did not
value the need to penetrate more rewarding markets or
strengthen the cooperatives as potential options out of the
marketing challenges. The need for training was also echoed
by sorghum farmers in Lusitu as a potential option to im-
proved market access. Farmers also suggested that they could
benefit greatly from government subsidy programs on sorg-
hum as is the current case with maize. They stated that this
program can include inputs such as seed and fertilizer as well
as support in the output market in terms of subsidized trans-
port and guaranteed prices for their produce.
Recommendations
Basing on the study findings, the following policy recom-
mendations are made:
To aid sorghum farmers in smallholder arid areas, further
research on the economic as well as social sustainability of
marketing the crop as well as operationalising the sorghum
based stockfeed VC might also be done to encourage the
adoption process after the potential gains would have been
highlighted.
The private sector, NGOs and the government may assist
smallholder sorghum farmers with marketing information
databases in their localities. The smallholder sector may still
realize its potential as the base for food security in the country
as well as reducing the poverty in communal areas.
Acknowledgements
This study was made possible by the generous sponsorship
from the Forum for Agricultural Research in Africa (FARA)
and support from Zambia Agriculture Research Institute
(ZARI).
122 Journal of Agriculture Economics and Rural Development (2014) 110-122
References
Babie, E. (1998). The Practice Of Social Research, 8th Edition, Belmont:
Wadsworth
Baudron, F. (2001). Challenges for the Adoption of Conservation Farming by Small holders in Semi Arid Zambia. CIRAD, Harare. Zimbabwe
Barnes, J. (2000). Domestic Market Pressures Facing the South African
Automotive Components Industry. Research Report No. 33, School of Development Studies, University of Natal, Durban
Best, J. W., & Khan, J. V. (1995). Research in Education. 7th Edition. Prentice
Hall, New Delhi Chimai, B. C. (2011). Determinants of Technical Efficiency in Smallholder
Sorghum Farming in Zambia. MSc Thesis. Department of Agricultural,
Environmental, and Development Economics. Ohio State University, Columbus, Ohio.
Coulibaly, J. Y. (2011). Diversification or Cotton Recovery in the Malian
Cotton Zone: Effects on Households and Women. PhD Dissertation. Department of Agricultural Economics. Purdue University, West La-
fayette, Indiana.
Despsch, R. (2004). Critical Steps To No-Till Adoption. Paper Presented at the Conference on Conservation Farming, Ukraine, November 18 – 23
Erickson, S. P., Akridge, J. T., Barnard, F. L., & Downey, D. D. (2002).
Agribusiness Management. McGraw Hill Companies, New York. FARA (Forum for Agricultural Research in Africa). 2012. Making Things
Happen: Stories From The Field-Series 1. FARA. Accra. Ghana.
Feder, G., & Zilberman, J. D. (2006). Adoption of Agricultural Innovations in Developing Countries. A Survey on Economic Development and
Cultural Changes. American Journal of Agricultural Economics. 33, 255-298
Greene, W. H. (2000). Econometric Analyses. Macmillan Publishers, New
York Hamukwala, P., Tembo, G., Erbaugh , J. M., & Larson, D. W. (2010).
Sorghum and Pearl Millet Improved Seed Value Chains in Zambia:
Challenges And Opportunities For Small Holder Farmers. Hancock, J. D. (undated). Enhancing The Utilization And Marketability Of
Sorghum And Pearl Millet Through Improvement In Grain Quality,
Processing, Procedures, And Technology Transfer To The Poultry Industry. Project KSU 102. INTSORMIL
Hardaker, J. B., Huirne, R. B. M., Anderson, J. R., & Lien, G. (2004). Coping
with Risk in Agriculture. 2nd Edition. CABI Publishing. Hart, W. S. (1998). Doing A Literature Review: Realizing The Social Science
Research Imagination. SAGE Publications Ltd. London.
Hellin, J., & Meijer, M. (2006). Guidelines for Value Chain Analysis. No-vember 2006
Kaplinsky, R., & Morris, M. (2002). A Handbook for Value Chain Research.
Prepared For IDRC Kilima, F. T. M., Mbiha, M. R., Erbaugh, J. M., & Larson, D. W. (2010).
Adoption of Improved Agricultural Technologies by Smallholder
Maize and Sorghum Farmers in Tanzania. African Journal of Agri-cultural Economics and Economic Development (JAED), 7, 25-54.
Maddala, G. S. (1983). Limited Dependant and Quantitative Variables in
Econometrics. Cambridge University Press. United Kingdom. Musara, J. P., Chimvuramahwe, J., & Borerwe, R. (2012). Adoption and
Efficiency of Selected Conservation Farming Technologies in Madziva
Communal Area, Zimbabwe: A Transcendental Production Function Approach. Bulletin of Environment, Pharmacology & Life Sciences
Volume 1, Issue 4: 27 – 38
Namara, R. E., Nagar R. K., & Upadhyay, B. (2007). Economics, Adoption Determinants, and Impacts of Micro-Irrigation Technologies: Empiri-
cal Results from India. Irrig Sci (2007) 25, 283–297
Neil, S. P., Lee, D. R. (2001). Explaining The Adoption And Disadoption Of
Sustainable Agriculture: The Case Of Cover Crops In Northern Hon-
duras. Economic Development And Cultural Change 49(4), 793-812.
Ramanathan, R. (2002). Introductory Econometrics With Application. Fifth Edition. South Western Publishers. Ohio.
Reardon, T., & Timmer, C. P. (2007). Transformation Of Markets For
Agricultural Output In Developing Countries Since 1950: How Has Thinking Changed? Handbook Of Agricultural Economics, Volume 3.
Reardon, T., Timmer, P., & Berdegue, J. (2004). The Rapid Rise of Super-markets in Developing Countries: Induced Organisational, Institutional,
and Technological Change. Agrofood Systems 1: 168-183.
Rogers, E. M. (1995). Diffusion of Innovations. Fourth Edition. The Free Press. New York.
Rukuni, M., Tawonezvi, P., Eicher, C., Munyuki-Hungwe, M., & Matondi, P.
(2006). Zimbabwe’s Agricultural Revolution Revisited, University of Zimbabwe Publications, Harare.
Sanogo, I. (2010). Market Analysis Tool - How To Conduct A Food Com-
modity Value Chain Analysis? World Food Programme and VAM food security analysis
Thomlow, S. (2007). Assessment of Sustainable Adoption of Conservation
Farming in Zimbabwe. UNIDO (2009). Agro-Value Chain Analysis and Development. The UNIDO
Approach: A Staff Working Paper. Vienna
USAID (2009). Global Food Security Response: West Africa Value Chain Analysis Protocol. MicroREPORT No. 153, February
USAID (2009) Staple Foods Value Chain Analysis: Country Report – Ma-
lawi. November 2009 Woodridge, J. M. (2003). Introductory Econometrics: A Modern Approach.
Thomson South Western. Ohio.
World Bank. (2008). Quantitative Value Chains for Key Crops in Malawi