Marketing Proclivity, Constraints and Opportunities in the Sorghum Based Stockfeed Value Chain in...

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: [email protected])

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

mailto:[email protected]

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


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).


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-


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


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 +


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


(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


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


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


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).


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

Marketing Proclivity, Constraints and Opportunities in the Sorghum Based Stockfeed Value Chain in...

Documents

Transcript of Marketing Proclivity, Constraints and Opportunities in the Sorghum Based Stockfeed Value Chain in...