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African Journal of Agricultural Marketing ISSN 2375-1061 Vol. 4 (2), pp. 001-009, February, 2016. Available online at 
www.internationalscholarsjournals.org © International Scholars Journals 

 

Author(s)                                           Author(s) retain the copyright of this article. 
 
 

 

Full Length Research Paper 

 

An analysis of institutional and technical factors 
influencing agricultural marketing amongst smallholder 
farmers in the Kat River Valley, Eastern Cape Province, 

South Africa 
 

B. Jari1* and G. C. G. Fraser2
 

 
1
Department of Agricultural Economics and Extension, University of Fort Hare, Alice 5700, Eastern Cape, South Africa. 

2
Department of Economics and Economic History, Rhodes University, South Africa. 

 
Accepted 12 November, 2015 

 
Smallholder farmers in the Kat River Valley do not use output markets effectively due to a number of factors. 
The technical and institutional factors that demoralise them from marketing are identified in this paper. It is 
asserted that an explicit analysis in the relationship between technology, institutions and markets may be 
useful in developing livelihood improving programs. Therefore, by identifying such factors, the paper seeks 
to find out ways of improving market participation among the smallholders, hence, livelihood development. 
The multinomial regression model was used to investigate the factors that influence marketing choices 
among smallholder and emerging farmers in the area under study. Empirical results show that market 
information, expertise on grades and standards, contractual agreements, social capital, market infrastructure, 
group participation and tradition significantly influence household marketing behaviour. 
 
Key words: Smallholder farmers, market participation, institutional and technical factors, multinomial logistic 

regression model. 

 
INTRODUCTION 

 
In the age of trade liberalization and globalisation, the 
world markets are increasingly being integrated. This 
implies that farmers in the developing world are ever 
more linked to consumers and corporations of the rich 
nations. Consequently, local farmers are facing 
increasing market competition, not only in international 
markets, but in local markets as well. In an effort to 
withstand the market pressures, agricultural markets are 
now transforming to a vertically coordinated structure 
(Reardon and Barrett, 2000). Also, both the private and 
public sectors have made some adjustments in agri-
cultural markets, in order to survive competition resulting 
from market changes.  

The South African agricultural sector was deregulated 

in 1997, with the aim of creating an open and market-  
 
 
 
*Corresponding author. E-mail: beejaery@yahoo.com. Tel: 
+27738599594. 

 
 
 
 
oriented environment for boosting the sector. Based on 
the Agricultural Products Act of 1996, government inter-
vention in agricultural marketing through the use of 
control boards was ceased. This change resulted in 
smallholder farmers and other formerly deprived farmers 
in output markets being included in agricultural marketing 
(Meyer et al., 2002). Although the policy is now oriented 
in favour of smallholder farmers, they still have to com-
pete for markets with the already developed commercial 
sector. For this reason, their survival in the markets is still 
at stake. In output markets, smallholder farmers often 
faced with difficulties in enforcing contracts and meeting 
stringent food safety norms, lack skills, are located in 
remote areas and mostly rely on middlemen. They are 
also served by poor physical infrastructures and weak 
institutions in markets (Kherallah and Kirsten, 2001; 
Makhura, 2001). Understanding such challenges among 
smallholder farmers is important in identifying areas that 
need focus and direction for improvement. In the light of 
these challenges, suggestions can be made on how to 

file:///C:\Users\user\Documents\REPUBLICATION\AGRICULTURAL%20SCIENCES\AppData\Local\Temp\www.internationalscholarsjournals.org


 
 
 

 

improve smallholder farmers’ 3 participation in output 
markets  

The main objective of this study is to identify and 
assess the technical and institutional factors influencing 
agricultural market participation behaviour amongst 
smallholder farmers in the Kat River Valley of the Eastern 
Cape Province in South Africa. The study focuses on the 
factors that compel smallholder farmers to make certain 
marketing decisions. Thus, it considers factors that guide 
farmers in deciding whether to sell produce or not. It 
further looks at the factors that influence the choice of 
marketing channels when selling produce. 

 

CONSTRAINTS TO AGRICULTURAL OUTPUT 

MARKETS 
 
Markets are important because they act as a mechanism 
for exchange. They are particularly important to the poor, 
because their involvement in the use of markets results in 
co-ordination and allocation of resources, goods and 
services. In other words, markets are very important in 
reducing poverty and improving livelihoods of house-
holds. It follows that market participation is important 
amongst smallholder farmers because households derive 
benefits such as income and open opportunities for rural 
employment (Dorward et al., 2003; Machethe, 2004). In 
addition, marketing activities such as processing, trans-
portation and selling can provide employment for those 
willing to exit the farming sector. At the national level, 
Lyster (1990) identified that market participation is impor-

tant both for sustainable agriculture and economic growth and 

for the alleviation of poverty and inequality. Unfor-tunately, 
smallholder farmers face difficulties in accessing markets, as a 

result, markets fail from effectively performing their duty. It is 
central to this paper to identify barriers that hinder markets 

from serving the interests of smallholder farmers, giving 
special attention to institutional and technical factors. 
 

In South Africa, less developed rural economies and 
smallholder farmers find it difficult to participate in 
commercial markets due to a range of technical and insti-
tutional constraints. Factors such as poor infrastructure, 
lack of market transport, dearth of market information, 
insufficient expertise on grades and standards, inability to 
have contractual agreements and poor organisational 
support have led to the inefficient use of markets, hence, 
commercialisation bottlenecks. 

 

Institutional aspects in smallholder agricultural 

markets 
 

Institutions are defined by North (1990) as rules of the 
game that facilitate coordination or govern relationships 
between individuals or groups. North (1990) divided 
institutions into formal and informal institutions. Institu-
tional aspects and their role in marketing and economic 
development revolve around transaction costs, market 

 
 
 
 

 

information flows and the institutional environment. It is 
affirmed that smallholder farmers in developed rural eco-
nomies lack adequate market information and contractual 
arrangements, lack lobbies in the legal environment and 
are not easily receptive to changes (Delgado, 1999; 
Kherallah and Kirsten, 2001). These factors result in high 
transaction costs, hence difficulties in formal market 
participation. This line of argument is substantiated by 
Makhura (2001) who explained that when smallholder 
farmers are faced with high transaction costs, they will 
either stop participation in marketing or resort to other 
means of marketing such as spot markets. The use of 
spot markets may not be as rewarding to the farmers as 
formal markets are, mainly due to traders’ opportunistic 
behaviour. In addition, spot markets are becoming less 
popular in the liberalised environment. To sum up, owing 
to institutional aspects, smallholder farmers face 
difficulties in accessing formal markets. This calls for 
institutional development among this group of farmers. 
 

 

Technical aspects in smallholder agricultural markets 

 

Technical changes in marketing can be viewed as those 
transformations that allow goods to be available on the 
market at lower costs and diversification of markets. 
Technical changes are usually influenced by the 
organization, and regulation and advances in technology, 
but technical changes are closely linked to technological 
development. In agricultural production and marketing, 
smallholder farmers are still lagging in the use of 
improved technology (Carre` and Drouot, 2002). 
Machethe (2004) pointed out that most small producers in 
South Africa lack appropriate transportation facilities and 
road infrastructure, communication links and storage 
infrastructure. Further, smallholder farmers have limited 
ability to add value to their produce. Lack of such facilities 
usually constrains farmers’ supply response to any 
incentives in both agricultural production and marketing 
(Dorward et al., 2003). Moreover, poor roads and poor 
telecommunication networks results in high transaction 
cost (Fenwick and Lyne, 1999). Sometimes these costs 
are too high for farmers and traders to get any meaning-
ful benefits from their trading activities, thus discouraging 
farmers from marketing activities. For this reason, 
institutional development has to be accompanied by 
technological changes, in order to sustain market 
participation among smallholder farmers. 
 

 
METHODOLOGY 
 
This section reviews the research methods used in collecting and 
analyzing data from smallholder farmers in the Kat River Valley. 
The section is intended to show how the study was conducted using 
research tools. It starts by describing the study area, and then it 
explains the sampling technique and the sample size from which 
data was collected. The methods of data analysis and model 
specifications follow, outlining the model for data processing, and 



 
 
 

 
giving reasons why the model has been chosen. 

 

Study area 
 
Kat River Valley is located in the Eastern Cape Province, the 
second largest of the nine provinces in South Africa (Ngqangweni, 
2000). It is situated northeast of Grahamstown, in the foothills of the 
Winterberg and the Amatole Mountains (Magni, 1999). The Kat 
River Valley forms part of the Nkonkobe Local Municipality, which 
falls, under Amatole District Municipality. Before the change of 
government in 1994, the upper part of the Kat River Valley was part 
of the Ciskei homeland – one of several black racial reserves 
created during the apartheid era. The Kat River Valley is approxi-

mately 80 km in length and 1700 km
2
 in area (Motteux, 2001). Its 

catchment includes the areas of Seymour, Balfour, Fort Beaufort 
and other smaller rural communities.  

Kat River Valley’s altitude increases from approximately 600 to 
1600 m at the top of the escarpment (Shackleton and Shackleton, 
2006). Its climate can be described as mild (Magni, 1999) . Rainfall 
is unevenly distributed within the area. It ranges between 400 and 
1200 mm, where the least rainfall is received at the confluence with 
the Great Fish River and the highest, in the mountainous northern 
region of the catchment (Magni, 1999). The rainfall is relatively high 
in the mountainous region, but much of the area in the catchment 
can be regarded as sub-humid to semi-arid. Kat River Valley 
receives both summer and winter rainfall. Approximately 75% of the 
mean annual precipitation is received between October/November 
and February/March, where the highest rainfall figures are recorded 
in March. The temperatures range from moderately hot summers to 
cool moderate winters (Motteux, 2001).  

Population in the Kat River Valley is composed of different races, 
and the racial composition is the result of history and apar-theid. 
The Upper and Middle parts of the Kat River Valley belong mainly 
to black Xhosa speakers and coloured Afrikaans speakers, whereas 
the Lower part belong mainly to white English speakers. Of the total 
population in the area, approximately 94.28% are black Xhosa 
people, 4.12% coloured and 0.76% white (Motteux, 2001).  

Kat River Valley is characterised by a variety of land uses, 
ranging from export-oriented citrus farming, commercially oriented 
rangeland stock farming to small-scale vegetable and crop 
production and stock farming (McMaster, 2002). Commercial 
farmers are mainly located in the Middle and Lower Kat, whereas 
smallholders and emerging farmers mostly practise agriculture in 
the Upper catchment (Nel, 1998). Vegetable gardening is an 
important occupation amongst smallholder farmers in the area. 
Most of these vegetables are grown on fertile plots lying adjacent to 
rivers and streams. For watering the vegetables, some farmers 
practise sprinkler irrigation, whereas the farmers who lack irrigation 
infrastructure practise hand irrigation (Farolfi and Rowntree, 2005). 
The soil, on which most cultivation occurs in the valley, is alluvium, 
which is suitable for agriculture. Smit (2003) explained that even 
though the soil is suitable for agriculture, phosphorous and 
potassium deficiencies have been identified in the alluvial soil 
profiles of the Kat River basin.  

There is a corresponding change in vegetation from Eastern 
Thorn Bushveld dominated by Acacia karroo in the valley, to a more 
succulent thicket in the south. The Acacia bush is the predominant 
vegetation type at the valley bottom owing to lower rainfalls. This 
vegetation type is capable of supporting livestock, explaining animal 
farming in the area. Acacia bush is also suitable for game farming, 
even though the area has not yet gained tourism importance from 
the four game reserves in the area (Motteux, 2001). Apart from 
different farming types, lack of sufficient rainfall remains a limiting 
factor to agricultural development in the catchment. In addition to 
rainfall problems, environmental problems in the Kat River Valley 
include over-fertilization, litter, water-pollution, erosion and river 
siltation, reduced tree and grass cover and increasing sediment 

  
  

 
 

 
output (Smit, 2003). 

 

Sample and sampling techniques employed in the study 
 
Data was collected from a sample of smallholder farmers who are 
producing a marketable surplus in the Kat River Valley. Farmers 
were stratified according to farming types: cattle and vegetable 
farmers. Eighty six farmers were randomly selected for the survey, 
where 43 each were cattle and vegetable farmers. The sampling 
frame from where the farmers were selected was obtained from 
extension officers. A questionnaire was then administered to the 
sampled household heads through face-to-face interviews. In the 
absence of the head, the spouse or any family member who is 
directly involved in the farming activities and management was 
interviewed. 

 

Methods of data analysis 
 
Statistical Package for Social Scientists (SPSS version 15.0) was 
used to run the data collected from smallholder farmers. To analyze 
relevant data, descriptive statistics were used together with the 
multinomial logistic regression model. The main descriptive 
indicators that were employed were frequency and mean values.  

The multinomial logistic regression model was used to test the 
institutional and technical factors that influence households from using 
greater depth marketing methods which have the potential of 
increasing their incomes. Multinomial logistic regression can be 
used to predict a dependent variable, on the basis of continuous 
and/or categorical independent variables, where the dependent 
variable takes more than two forms (Hill et al., 2001). Logistic 
regression does not assume a linear relationship between the 
dependent variable and independent variables, but requires that the 
independent variables be linearly related to the logit of the 
dependent variable (Gujarati, 1992). However, Pundo and Fraser 
(2006) explained that the model allows for the interpretation of the 
logit weights for the variables in the same way as in linear 
regression. 

The smallholder farmers under study are faced with three 
choices; formal-, informal- and non-market participation. It is 
assumed that these decisions are made on the basis of the option 
which maximizes their utility, subject to institutional and technical 
constraints. 
 
As such, the utility maximizing function can be given as: 
 
Max U = U (Ck, Rfk, Rik; Hu) (1) 
 
Where; Max U denotes the maximum utility that can be attained 
from agricultural production 
Ck represents the consumption of produced goods by the 
household 
Rfk represents revenue gained from formal market participation 
Rik represents revenue gained from informal market participation 
Hu represents a set of institutional and technical factors shifting the  
utility function 
 
From the utility maximizing function, it can be seen that households 
make decisions to produce, consume and market, subject to 
institutional and technical factors. Therefore, if the costs that are 
associated with using a particular channel are greater than the 
benefits, households will be discouraged from using it, shifting to 
the option that maximizes their utility. In the utility function, the 
amount of good k that is consumed or sold does not have to exceed 
the amount that is produced. However, it is difficult to measure 
utility directly; therefore, it is assumed that households make 
participation choices depending on the option that maximize their 



 
 
 

 
Table 1. Description of variables used in the model.  

 
 Variable Label Variable name Coding of variable Expected relationship 

 MKTINFO Access to market information 1 if access, otherwise 0 + 

 GRDS Expertise on grades and standards 1 if yes, otherwise 0 + 

 EXT Access to extension contact 1 if yes, otherwise 0 + 

 ORGMEM Member of an organisation 1 if member, otherwise 0 + 

 FMNGTYP Type of farming 1 if arable, 0 if livestock +/- 

 RDINFR Road infrastructure 1 if good, 0 if poor + 

 TRANS Market transport 1 if have own transport, otherwise 0 + 

 ADDVAL Ability to add value 1 if yes, otherwise 0 + 

 MKTINFR Market infrastructure 1 if good, otherwise 0 + 

 STOR Storage facilities 1 if good, otherwise 0 + 

 CONTRCT Availability of contractual agreements 1 if yes, otherwise 0 + 

 SOCIALK Availability of extensive Social capital 1 if yes, otherwise 0 + 

 PART Groups or individual participation 1 if group, 0 if individual + 
 TRAD Guided by tradition and beliefs 1 if yes, otherwise 0 _ 

 

 
utility. Thus, decisions to participate in either formal or informal mar-
kets or even not participating, signify the direction which maximizes 
utility. With the given assumption, multinomial regression was used 
to relate the decisions to participate in formal and informal markets 
or not participating and the factors that influence these choices.  

A typical logistic regression model which was used is of the form: 
 
Logit (Pi) = ln (Pi / 1 – Pi) =  +  1X1 + …+  nXn (2) 
 
Where; ln (Pi / 1 – Pi) = logit for market participation choices 
Pi = not participating in markets 
1-Pi = participating in markets 
X represents covariates 
 
In the model, market participation choice represents the dependent 
variable where non-market participation has been set as the 
baseline group. Market participation choice describes the decision 
to market or not, and the variety of marketing methods (either 
formal or informal channels) used by households to market 
agricultural output. It follows that Pi represents the probability of not 
participating in produce marketing and (1 – Pi) represents either 
informal or formal market participation. In other words, the model 
was used to assess the odds of: informal market participation vs. 
not participating; and formal market participation versus not 
participating. 

 

Model specifications 
 
By fitting explanatory variables into the logistic regression model, 

the model is presented as: 
 
ln (Pi / 1 – Pi) =  
B0  B1 MKTINFO  B2 GRDS  B3 EXT  B4 ORGMEM  
 B5 FMNGTYP  B6 RDINFR  B7 TRANS  B8 ADDVAL
 B9 MKTINFR  B10 STOR  B11 CONTRCT  B12 SOCIALK
 B13 PART  B14 TRAD  Et

 
The description of the explanatory variables, and their expected 
relationships to the dependent variable are presented on Table 1. 

The variable (MKTINFO) which reflects access to market 

information was measured by the household’s ability to get market 

 

 
information in time and the ability to interpret it correctly. In order to 
capture this variable closely, households were interviewed on the 
communication networks that are accessible to them. Access to 
information has been set as a dummy variable, where a household 
with access to information takes the value of one and a household 
that has no access to information takes a value of zero. Access to 
information was expected to influence market participation posi-
tively; implying that households with access to information are more 
likely to participate in marketing, making use of formal markets. 
Another variable that is closely linked to information availability is 
access to extension services (EXT) such as access to farming 
advice and knowledge through extension officers. This variable was 
also allocated dummy values where households with access to 
extension services took the value of one and zero if otherwise.  

Expertise on grades and standards (GRDS) was recorded in 
order to investigate whether it influences marketing participation 
choices or not. Households were asked if they were aware of 
market grades and standards, and whether there were problems 
meeting such standards. The households with knowledge on 
grades and standards, and had no problems meeting them were set 
to have expertise on grades and standards. Such households took 
the value of one and those households with no expertise on grades 
and standards were equated to zero. Households with expertise on 
grades and standards are expected to make use of formal markets 
than those without, thus an expected positive relation. 

Collective action is measured by two main variables in this study; 
organizational support services (ORGMEM), and group or individual 
participation (PART). Respondents were asked whether they 
belonged to an organization or not and whether they sold output in 
groups or individually, the responses were allocated dummy values. 
Both variables are anticipated to impact positively on market 
participation choice among the smallholder farmers.  

The types of farming (FMNGTYP) have been divided into either 
arable or livestock farming, where the former takes a value of one 
and the latter takes the value of zero. This variable was included 
into the model in order to capture the differences in the nature of 
produce from different farming types. Thus, in some types of 
farming, formal market penetration may be easier than in the other 
types. For instance, Matungul et al. (2002) pointed out that formal 
livestock markets are readily accessible to both commercial and 
small-scale livestock farmers in South Africa, owing to public 
investment in sales yards. The variable can take either a positive or 
a negative value. 

Ownership of market transport (TRANS), specifically vehicles, 



 
 
 

 
was used to measure the availability of produce transportation 
facilities by households. Moreover, the availability of transportation 
facilities helps reduce long market distance constraint, offering 
greater depth in marketing choices. In cases where households 
owned a vehicle, the variable took the value of one, and zero if the 
household did not own any form of vehicle. This variable is 
expected to have a positive influence on the market participation 
choices.  

The availability of good road and market infrastructures are 
expected to exert a positive influence on market participation. Road 
infrastructure (RDINFR) is measured by the adequacy of the road 
networks that are accessible to households and their conditions. 
Market infrastructure (MKTINFR) is measured by the availability of 
infrastructure, such as marketing stalls and their conditions. Dummy 
values are used to define the variables, where in both cases, one 
indicates good condition and zero indicates either unavailability or 
poor condition.  

In this study, social capital (SOCIALK) refers to personal social 
networks that encourage market participation. It is through these 
networks that trust is developed, which, in turn, encourages 
cooperation and regular exchanges. Also, information and produc-
tion resources can be transmitted through these networks. In order 
to capture this variable, respondents were asked about how they 
relate with their customers and whether any were regular custo-
mers. The availability of an extensive social capital structure is 
expected to impact positively on the dependent variable.  

The availability of contractual agreements (CONTRCT) ensures 
the availability of a guaranteed market for the farmers, thus pro-
moting market participation and including the smallholder farmers in 
mainstream agriculture. In other words, the existence of a 
guaranteed market reduces the costs that are associated with 
searching for potential buyers, thereby encouraging participation in 
formal markets. This variable is expected to have a positive 
relationship with the dependent variable  

The ability to add value to agricultural produce is captured by the 
variable (ADDVAL). Dummy values are used to define the variable 
where those households who add value to their produce, take the 
value of one and those who do not, zero. It is hypothesized that the 
ability to add value exerts a positive impact on market participation.  

The variable storage facilities (STOR), is closely related to value 
adding. Good storage facilities reduce loss of produce and urgency 
of produce selling, and maintain the physical state of produce. 
Thus, households with good storage facilities are more likely to 
participate in formal markets, hence a positive relationship.  

Traditions and beliefs are part of informal institutions that can 
influence marketing choices. In the model, the dummy variable 
(TRAD) which refers to guidance from tradition and beliefs is used 
to determine effects of tradition and beliefs on marketing. House-
holds were asked on the extent to which tradition plays a role in 
their agricultural activities. They were also asked if they were open 
to new farming and marketing methods offered by non-family 
members. The variable was allocated dummy values where house-
holds with strong traditional guidance took the value of one and 
zero if otherwise. The variable is expected to take a negative value. 

 

EMPIRICAL RESULTS 
 
Descriptive results 
 
The descriptive results for the demographic characte-
ristics show that from all the interviewed respondents, 
there were a larger proportion of male respondents (58%) 
as opposed to females. However, there were greater pro-
portions of females (63%) in vegetable farming, but in 
cattle, there were greater proportions of males. A large 

  
  

 
 

 

number of females in vegetable farming can be explained 
by day-to-day vegetable supervision by females where 
men move to cities/town in search of jobs. The majority 
(72%) of the smallholder farmers in the Kat River Valley 
are above 49 years of age. The educational level among 
the sampled farmers is generally low, where 18% of the 
household heads never attended school and 39% went 
up to primary level. Household size ranges from a mini-
mum of two people to a maximum of 18, with a mean of 
7.1 in each household. According to Randela (2005), a 
larger household size has a negative effect in produce 
marketing because the household needs to supply 
household consumption before it decides to sell. Evi-
dence from the research confirms this line of argument 
because larger households in this research sold less 
produce as compared to smaller households.  

Household incomes of the respondents are received 
from five main sources; farming, wages, pensions, social 
grants, and other small household business activities. Of 
importance, is the fact that in the absence of pension and 
social grants, 74 % of the households view farming as 
their main source of income. When selling produce, 
households had different reasons for choosing the mar-
keting channels they use. A summary of the main market 
outlets used by smallholder farmers are presented in 
Table 2.  

As shown in Table 2, more vegetable and cattle far-
mers make use of informal markets than formal markets. 
In an effort to find the reasons why the sampled farmers 
preferred the markets they use, they were interviewed on 
the prevailing marketing problems they faced during 
selling and those that constrained them from mano-
euvring into more rewarding marketing arrangements. 
The most frequently mentioned marketing challenges are 
shown in Table 3.  

Farmers were asked to clarify on the challenges that 
are listed on Table 3. For example, farmers were asked 
what they meant by market information. The most men-
tioned answers were related to information on prevailing 
prices, type of goods required in the markets and alter-
native markets. Farmers explained that the information 
which they had access to was unreliable because they 
usually got them from either other people in the village 
who are involved in selling or from the rural traders. They 
pointed out that they rarely trusted such information but, 
they had no option because those are the only sources 
accessible to them. Alternatively, the farmers explained 
that they would just take chances and go to the market 
place without any information and charge the same price 
as other people selling at that selling point.  

Taking a closer look at the marketing challenges that 
were cited by households, they can all be resolved 
through technological and institutional innovations. For 
instance, low prices for produce can be related to poor 
produce quality, inability to reach other markets, being 
uninformed on what is required in the markets and 
abundance of the same produce in the markets. Poor 



 
 
 

 
Table 2. Main market outlets used by sampled households.  

 
Type of farming Main market outlets (%) Market type  

 
 

Vegetables (n = 43) 
 
 
 
 

 

Cattle (n = 43) 

  
Farm gate (46.5) Informal  
Fort Beaufort (32.5) Formal & Informal  
Around the village (14.0) Informal  
Roadside (7.0) Informal 

 
Private sales (39) Informal  
Speculators (26) Informal  
Auctions (23) Formal  
Abattoirs (9) Formal  
Butcheries (3) Formal  
 

 

Table 3. Marketing challenges among sampled households.  
 

 Marketing challenges Households affected (%) 

 1. Lack of capital 80 

 2. Bad roads 79 

 3. Low prices for produce 67 

 4. No reliable markets 65 

 5. No market information 64 

 6. Lack transport /high transportation costs 59 

 7. No exposure to other markets 53 

 8. Lack of storage facilities 51 

 9. High competition 46 

 10. No convenient place to sell from 38 

 11. No transparency in marketing channels 18 
 

 

produce quality can be resolved by availability of infor-
mation on grades and standards and an improvement in 
technology for storage and transportation. Farmers may 
be able to reach other markets if they participate in 
groups because they share information and broaden 
social capital within the groups. In addition, when farmers 
market in groups, they eliminate competition and may 
diversify into producing other crops, thereby reducing 
market pressure. 

 

Multinomial logistic regression results 
 
The results for the model are presented in Table 4. The 
table shows the estimated coefficients ( values), stan-
dard error, significance values and odds ratios of 
variables in the model. According to Gujarati (1992), the 
coefficient values measures the expected change in the 
logit for a unit change in the corresponding independent 
variable, other independent variables being equal. The 
sign of the coefficient shows the direction of influence of 
the variable on the logit. It follows that a positive value 
indicates an increase in the likelihood that a household 
will change to the alternative option from the baseline 
group (Gujarati, 1992; Pundo and Fraser, 2006). There- 

 

 

fore, in this study, a positive value implies an increase in 
the likelihood of changing from not participating in 
marketing to either informal or formal market participation 
choice.  

As indicated in Table 4, some predictor variables 
influence market participation choices significantly. Of the 
14 independent variables used in the model, five and six 
variables in informal and formal market choices respect-
tively, are statistically significant at the 5% significance 
level. In some cases, the signs of the estimated 
coefficients are consistent with the a priori expectations 
whereas in some they are contrary to expectations. 

 

Estimation of significant variables in the model 
 
Access to market information has a positive sign for both 
formal and informal market choices, which is consistent 
with the a priori expectations. The significance values of 

0.011 for the informal market choice and 0.006 for the 
formal market choice imply that there is enough evidence 
to support that an increase in the availability of market 
information results in an increase in both informal and 
formal market participation. The larger values in odds 
ratios show that households are most likely to increase 



  
 
 

 
Table 4. Multinomial logistic results for informal and formal market choices as compared to non-marketing choice.  
 
  Informal market choice   Formal market choice  

Variable Coefficient Std. Error Significance Odds ratio Coefficient Std. Error Significance Odds ratio 

MKTINFO 2.686 1.050 0.011* 14.673 4.217 1.385 0.006* 67.83 

GRADES -1.623 0.905 0.073 0.197 3.830 0.848 0.016* 46.06 

EXT 0.606 0.868 0.485 1.833 1.166 2.942 0.282 3.209 

ORGMEM 0.788 0.786 0.316 2.199 1.324 1.384 0.330 3.758 

FMNGTYP -0.248 0.754 0.742 0.780 -1.164 1.854 0.530 0.312 

RDINFR 0.862 0.841 0.305 2.368 2.992 2.171 0.168 19.92 

SOCIAILK 0.222 0.948 0.050* 1.248 1.180 2.863 0.031* 3.254 

ADDVAL 1.352 1.079 0.210 3.865 0.392 0.218 0.860 1.479 

MKTINFR 2.557 1.030 0.013* 12.897 -0.687 0.026 0.735 0.503 

STOR 0.584 0.777 0.453 1.793 0.259 1.873 0.890 1.296 

CONTRCT 0.844 0.755 0.263 2.326 2.803 1.912 0.047* 16.49 

TRANS 0.843 0.774 0.276 2.323 0.449 1.644 0.785 1.567 

PART 1.899 0.854 0.026* 6.679 1.997 1.418 0.039* 7.367 

TRAD 2.477 1.441 0.031* 11.905 -2.144 2.296 0.007* 0.117 

INTERCEPT -4.934 2.860 0.048 _ -17.069 4.466 0.044 _ 

 

  Goodness-of-fit  

 Chi-Square df Significance 

Pearson 111.372 168 0.050* 

Deviance 84.301 168 0.988 
 
N = 86; * Statistically significant at 5% significance level. 
 

 

participation in both informal and formal markets with the 
availability of market information. As shown by the 
coefficients, the increase in formal marketing, resulting 
from market information availability is about twice the 
increase in informal marketing.  

Expertise on grades and standards is significant for the 
formal market choice with a significance value of 0.016. A 
positive sign on its coefficient indicates that an 
improvement in expertise on grades and standards 
results in an increase in the formal market participation 
choice by households. When households acquire exper-
tise in grades and standards, they prefer selling their 
produce in the more paying formal markets, in order to 
cover costs associated with acquiring the expertise 
(Reardon and Barrett, 2000).  

A positive and significant (0.047) relationship was found 
between formal market participation and the availability of 
contractual agreements. The relationship implies that 
households tend to increase in formal market 
participation with the availability of contractual agree-
ments. The value of the odds ratio (16.49) supports the 
higher probability of the variable influence on the formal 
market choice.  

The variable existence of extensive social capital is 
significant for both informal (0.050) and formal (0.031) 
market choices. The positive relationship in both formal 

and informal market participation choices explains that an 
increase in social capital results in households shifting 

 
 

 

from non-participation to formal and informal market 
participation. The odds ratios for both formal and informal 
market choices suggest a higher probability of shifting to 
formal and informal marketing with an increase in social 
capital. Therefore, it can be concluded that social net-
works are important in produce marketing, regardless of 
the choice of market being used.  

It was expected that the availability of good market 
infrastructure could have a positive influence on alterna-
tive market participation choices, away from not partici-
pating in marketing. However, the a priori expectations 
hold true for the informal market choice only. There is 
sufficient evidence (significance value of 0.013) to 
support that the availability of good market infrastructure 
is likely to encourage households to market their produce 
through informal channels. Unlike formal channels where 
market infrastructure is not important for farmers, as they 
supply their produce in bulk once harvested to the higher 
level of the marketing channel (Takavarasha and Jayne, 
2004).  

The results shown in Table 4, for group participation 
are consistent with the a priori expectations. For both 

formal and informal market choices, there is enough evi-
dence to support that when households market their pro-
duce in groups, there is a higher chance of participating 
in either formal or informal markets. Thus, group partici-
pation encourages market penetration among small-
holder farmers who find it difficult individually to gain 



 
 
 

 

market access 

A positive and significant (0.031) relationship was found 
between informal marketing and guidance from traditions 
and beliefs. The positive relationship between the 
variables may be possibly explained by traditional 
wisdom and skills passed on in families and creation of 
marketing links through traditions and beliefs. For 
instance, some households may prefer to sell their 
produce (especially in cattle marketing) to people they 
are familiar with. On the other hand there is a negative 
and significant (0.007) relationship between formal 
marketing and guidance from traditions and beliefs. The 
explanation to this relationship may be that the marketing 
environment is ever changing (Kherallah and Kirsten, 
2001); therefore, if farmers are to be part of the formal 
markets, they have to be receptive to changes. 

 

CONCLUSIONS AND RECOMMENDATIONS 
 
This paper has attempted to identify factors influencing 
market participation choices among smallholder farmers 
in the Kat River Valley. Evidence from the research sup-
ports literature that pointed out that, smallholder farmers 
usually use informal markets in selling their produce. 
Furthermore, there are some challenges in the market 
environment that discourage these farmers from using 
formal markets. The statistically significant variables, at 
5% level are access to market information, expertise on 
grades and standards, availability of contractual agree-
ments, existence of extensive social capital, availability of 
good market infrastructure, group participation and 
reliance on tradition.  

The results of this study suggest several ways in which 
smallholder farmers can actively market their produce. 
The findings suggest that an adjustment in each one of 
the significant variables can significantly influence the 
probability of market participation. That is, technological 
growth and institutional developments that affect such 
variables can help farmers improve participation and 
encourage formal market participation. Firstly, it has to be 
accepted that smallholder farmers cannot individually 
compete against commercial farmers in markets. Also, it 
is difficult for them to get contractual agreements indivi-
dually, owing to a small marketable output. Therefore, 
beneficial institutional innovations can be in the form of 
co-operatives and group marketing arrangements. It is 
true that past experiences for co-operatives and other 
farmer group arrangements had their own challenges 
(Kherallah and Kirsten, 2001). However, it is worth noting 
that farmer group arrangements that are based on trust 
and commitment may be successful. This brings out the 
suggestion that when choosing group members, farmers 
working towards the same goal should be grouped 
together. In addition, rules and roles within the group 
ought to be specified from the beginning. Also, farmers 
have to be encouraged to develop trust and mutual 
respect for their fellow members. 

 
 
 
 

 

With the farmer groups, social capital is likely to be 
broadened and farmers can now be linked to other mar-
ket chain actors. For instance, smallholder farmers in a 
co-operative or farmers marketing in a group can be con-
sidered for contract production. Once they get contractual 
agreements, an entrepreneurial culture can be 
developed, where they produce for marketing, rather than 
trying to market what they have produced. Again, it is 
critical to develop trust between the farmers and the 
contractors, even though it should be supported by legal 
compliance. Farmers can gain trust by delivering the 
required produce and contractors can develop trust by 
having confidence in the producers. Such an environment 
encourages marketing and is advantageous to both 
parties (Masuku et al., 2003).  

The government can support the smallholder farmers 
through technical innovations. These may be in the form 
of investments in public facilities such as improved roads, 
telecommunications and market places. Smallholder 
farmers still have to play a role in order to ensure that 
these facilities are provided for them. They have to form 
an association and choose a lobby that has to represent 
them. 

 
REFERENCES 
 
Carre` M, Drouot D (2002). Nature of technological change. 

http://www.crest.fr/doctravail/document/2002-56.pdf. Accessed: 18-
04-07. 

Delgado C (1999). Sources of Growth in Smallholder Agriculture in sub-
Saharan Africa: The Role of Vertical Integration of Smallholders with 
Processors and Marketers of High-value Added Items. Agrekon, 
38:165-189.  

Dorward A, Poole N, Morrison J, Kydd J, Urey I (2003). Markets, 
institutions and Technology: Missing Links in Livelihoods Analysis. 
Dev. Policy Rev. 21(3): 319-332. 

Farolfi S, Rowntree K (2005). Negotiation and game theory for water 
management in the Kat Basin, South Africa: Development of a 
Cooperative game theory Model and a comparison with a role-playing 
game results derived of a negotiation approach. 
http://www.ceepa.co.za/docs/Desole.pdf. Accessed: 19-07-07.  

Fenwick LJ, Lyne MC (1999). The relative importance of liquidity and 
other constraints inhibiting the growth of small-scale farming in 
KwaZulu-Natal. Dev. S. Afr. 16(1): 141-155. 

Gujarati D (1992). Essentials of Econometrics. MacGraw–Hill, New 
York. 

Hill RC, Griffiths WE, Judge GG (2001). Econometrics (2
nd

  edition). 
John Wiley & Sons, New York.  

Kherallah M, Kirsten J (2001). The New Institutional Economics: 
Applications for agricultural policy research in developing countries. 
Markets and Structural Studies Division, Discussion paper NO. 41, 
Int. Food Policy Res. Institute Washington, D.C.  

Lyster DM (1990). Agricultural marketing in KwaZulu: a farm-household 
perspective. Unpublished MSc Agric thesis, University of Natal, 
Pietermaritzburg. 

Machethe CL (2004). Agriculture and poverty in South Africa: can  
agriculture reduce poverty? http://cfapp1-docs-
public.undp.org/eo/evaldocs1/sfcle/eodoc 357114047.pdf. Accessed: 
09-04-07. 

Magni P (1999). Physical Description of the Kat River Valley, 
Geography Department, Rhodes University, Grahamstown.  

Makhura MT (2001). Overcoming transaction costs barriers to market 
participation of smallholder farmers in the Northern Province of South 
Africa. PhD thesis, University of Pretoria, Pretoria. 

Masuku MB, Kirsten JF, van Rooyen CJ, Perret S (2003). Contractual 



 
 
 

 
relationships between small-holder sugarcane growers and millers in 
the sugar industry supply chain in Swaziland. Agrekon 42(3): 183-
199. 

Matungul PM, Ortmann GF, Lyne MC (2002). Marketing methods and 
income generation amongst small-scale farmers in two communal 
areas of KwaZulu-Natal, South Africa. Paper presented at the 13th 
Int. Farm Management Congress, Wageningen, Netherlands.  

McMaster A (2002). GIS in participatory catchment management: a 
case study in the Kat River Valley, Eastern Cape, S. Africa, 
Unpublished MSc thesis, Rhodes University, Grahamstown. 

Meyer N, Fenyes T, Louw D (2002). The impact of market reform and 
land reform on regional trade and food security in the South African 
grain market. Working paper, Pretoria. 

Motteux N (2001). The Development and Co-ordination of Catchment 
Fora through the empowerment of Rural Communities, Catchment 
Research Group. WRC Report K5/1014. Water Res. Commission, 
Pretoria.  

Nel EL (1998). An evaluation of community driven economic 
development, land tenure and sustainable environmental 
development in the Kat River Valley, Report to the Programme for 
Human Needs, Resources and the Environ. HSRC Publishers, 
Pretoria.  

North D (1990). Institutions, institutional change and economic 
performance, Cambridge University Press, Cambridge.  

Ngqangweni SS (2000). Promoting Income and Employment Growth in 
the Rural economy of the Eastern Cape through Smallholder 
Agriculture. Unpublished PhD thesis, University of Pretoria, Pretoria. 

Pundo MO, Fraser GCG (2006). Multinomial logit analysis of household 

cooking fuel choice in rural Kenya: The case of Kisumu district. 

Agrekon 45(1): 24-37. 

  
  

 
 

 
Randela R (2005). Integration of emerging cotton farmers into the 

commercial agricultural economy. Unpublished PhD thesis, University 
of the Free State, Bloemfontein. 

Reardon T, Barrett C (2000). Agro-industrialization, globalization, and 
international development: An overview of issues, patterns, and 
determinants. J. Agric. Econ. 23(3): 195 -205. 

Shackleton CM, Shackleton SE (2006). Household wealth status and 
natural resource use in the Kat River Valley, South Africa. J. Trop. 
For. Prod., 8(1): 45-65. 

Smit T (2003). Catchment Management Forums in the Eastern Cape  
Province of South Africa. 
http://campus.ru.ac.za/download.php?actionarg=986. Accessed: 27- 
07-07.  

Takavarasha T, Jayne TS (2004). Toward improved maize marketing 
and trade policies to promote household food security in Southern 
Africa.  
http://www.aec.msu.edu/maizemarket/JayneTakavarashaSummary.p 
df. Accessed: 18-07-08. 

Wynne AT, Lyne MC (2003). Rural economic growth linkages and small 
scale poultry production: A survey of poultry producers in KwaZulu-
Natal. Paper presented at the 41st Annual Conference of the Agric. 

Econ. Association of S. Africa (AEASA), Pretoria. 


