Agri-food Value Chain
1
Agri-food Value Chain Development and
Market Information Systems in the Caribbean
Ardon Iton
Caribbean Agricultural Research and Development Institute
e-mail: aiton@cardi.org
Abstract
Recent years have seen increased discussion of the role of Market Information Systems (MIS) and
Value Chains (VC) in economic development, especially in developing countries. This research
attempts to identify how many farmers in Trinidad have used the Trinidad and Tobago National
Agricultural Market Information System (NAMIS) and what are some of the key differences between
users and non-users of NAMIS from a farmers’ perspective. Using data collected from a survey
conducted in 2010, the following criteria were used to develop and test several hypotheses to identify
those factors that contribute to use or non-use of NAMIS – size of farm, decision making
responsibility, educational level, gender and age.
Recently, several other CARICOM countries have expressed an interest in adopting NAMIS or
versions of it for use in their countries. It is hoped that by identifying some of the differences between
users and non-users of NAMIS, better MIS can be developed in the region and a stronger link can be
made between MIS and Value Chain Development (VCD) to help Caribbean farmers participate in
high value agri-food value chains and make the transition to market oriented agriculture.
Keywords: Value chain development, Market information systems, NAMIS, Information dissemination,
Caribbean farmers.
Introduction
With the escalation of personal computers
and other information and communication
technologies (ICTs) in the region in the last
decade Market Information Systems (MIS)
were thought to be a sure way of
addressing many of the issues confronting
stakeholders in the agri-food value chain.
MIS
were
expected
to
generate
improvements in market efficiency. For
small farmers and agribusiness operators
in developing countries some development
specialists saw MIS as a panacea for small
farmer problems, citing such things as:


Providing
farmers
with
proper
production incentives
Expanding market opportunities for
small farmers

Increasing small farmers’ bargaining
power
In essence, by removing information
asymmetries and reducing transaction
costs small farmers would have greater
opportunities to sell their produce and
labor – participate in high value agri-food
chains.
However, value chain development is
almost impossible if a near-total sharing of
information does not exist among all
elements of the chain. Information can be
considered the glue that holds the value
chain members together in harmony. As
Verdouw et. al. (2010) states “Information
systems are vital enablers of dynamic
demand driven supply chains”. The
information requirements and use by the
stakeholders in the value chain will differ,
Agri-food Value Chain
but information must be shared for the
synchronization of processes and the
maximization of chain performance. MIS
are seen as one source of providing the
numerous chain actors with useful
information.
From a farmer’s perspective access to
timely, relevant and accurate information is
critical for meaningful discussions with
downstream and upstream members of the
chain. But how many of our farmers
access and use the information provided
by our MIS? Further, how many of our MIS
reach our small producers in remote
areas? Parikh et. al. 2007, provides a
useful overview of some of the problems
faced by small farmers and access to MIS.
The reasons for non-use of MIS by farmers
can be quite varied, and include - age, low
levels of literacy, access to the mode of
information dissemination (internet), lack of
knowledge of using information in decision
making etc.
The purpose of this study is to find out
how many farmers in Trinidad have used
The Trinidad and Tobago National
Agricultural Market Information System
(NAMIS) and what are some of the key
differences between users and non-users.
That is, what are some of the factors
contributing to or hindering the use of
NAMIS. It is hoped that based on the
findings of this study increased use can be
made of NAMIS by farmers as they strive
to participate in agri-food value chains.
Also, other CARICOM countries will be
better positioned to analyze the pros and
cons of duplicating NAMIS in their
countries as they attempt to facilitate agrifood value chain development by
establishing MIS.
The rest of this paper proceeds as
follows: the second section provides a brief
description of NAMIS as it was conceived.
Section three outlines the methodology
utilized in the study. The analysis of the
primary data and a presentation of the
results follow this. In section five some
conclusions are drawn and a few
2
suggestions made for improving the use of
MIS as a means of building stronger value
chains.
Overview of NAMIS
The National Agricultural Marketing and
Development Corporation (NAMDEVCO)
manages the Market Information System of
Trinidad and Tobago titled National
Agricultural Market Information System
(NAMIS) which was launched in January
2007. The vision of NAMIS was stated
then as “To use NAMIS as the tool to
provide reliable Information and Market
Intelligence, on a real time basis, to all
stakeholders by accurately gathering and
organizing data using modern methods
and techniques to accurately reflect the
production status; cost of inputs; sale of
produce
at
the
primary/secondary
wholesale and retail markets for Sea and
Agri-Food products.”
The objectives of NAMIS can be succinctly
stated as follows:
(1) To provide the fresh produce sector
and relevant policymakers in T&T with
reliable, timely and independent
information.
(2) To
improve
agribusiness
development, in particular to the
development
of
non-traditional
agricultural exports (NTAEs).
(3) To help meet foreign demand for fresh
produce and seafood, which is
growing rapidly in the developed
markets of Europe and North America.
(4) To provide domestic and international
prices, freight costs and supply and
demand statistics, plus market access
information for the main target
markets, crop production issues and a
contacts database.
(5) Align all agricultural departments of
NAMDEVCO to help provide all
stakeholders with accurate and timely
information as well as to improve the
Agri-food Value Chain
corporation’s overall polices
department processes.
3
and
The list of beneficiaries envisaged was:

Farmers

Exporters

Supermarkets

Fishermen

Agro processors

Hotels and Restaurants

Caterers

Policy
Makers,
Planners
and
Researchers

General public
The primary research undertaken in this
study focused on the farmers.
How would NAMIS provide information to
stakeholders on a timely basis? The
following methods were identified:











Green Vine – a monthly newsletter
Email
Telephone
Fax
Website
Directly through staff
Interactive Online Access
Kiosk
Expanded Green Vine
E-market
Linked to other Agri-Information
Systems
Table 1 provides a categorisation of the
information dissemination methods as
listed above. As can be observed from this
table ICTs were the preferred means
envisaged of getting information to users.
However, one must ask how many of our
ageing farming population really uses the
computer as an information source for
farming decisions? As is pointed out in
“Impact of Public Market Information
Systems (PIMS) on Farmers Food
Marketing Decisions: Case of Benin,” by
Chogou et. al. 2009, access to information
through farmers’ own social networks
might be more influential in decision
making than PIMS. In table 1 person to
person and print media were not the
preferred means of dissemination – 9%
and 18% respectively. ICTs were the
preferred
means
of
information
dissemination – 73%. But as Irick M. L.
2008, points out “In order for an
information system to have a positive
impact on individual performance, 1) the
information technology must be utilized,
and 2) there must be a good fit with the
tasks the technology supports”.
Methodology
Data was collected by means of
questionnaires from a random sample of
farmers on a face to face basis and the
data analyzed using SPSS. A total of 514
farmers responded to the questionnaire. All
questions were not answered by the 514
farmers.
The following criteria were used to identify
differences between users and non-users
of NAMIS:





Size of farm
Decision making responsibility
Educational level
Gender
Age
The hypotheses developed are as follows:
Size of farm operation
HO: The use of NAMIS by farmers does not
depend on the size of farm operation
HA: The use of NAMIS by farmers depends
on the size of farm operation
Decision maker
Agri-food Value Chain
HO: The use of NAMIS by farmers does not
depend on them being the main decision
maker for their operations
HA: The use of NAMIS by farmers depends
on them being the main decision maker of
their operations
4
A t-test for equality of means (2-tailed)
produced a p-value of 0.000. As the pvalue is lower than 0.05 we reject the null
hypothesis. The size of the farmer’s
operation does appear to influence the use
of NAMIS.
Decision maker
Educational level of farmer
HO: The use of NAMIS by farmers does not
depend on their educational level
HA: The use of NAMIS by farmers depends
on their educational level
Gender
HO: The use of NAMIS by farmers does not
depend on their gender
HA: The use of NAMIS by farmers depends
on their gender
Age of farmer
HO: The use of NAMIS by farmers does not
depend on their age
HA: The use of NAMIS by farmers depends
on their age
Results
Five hundred and fourteen farmers were
interviewed of which 87.5% were males.
88.7% of the farmers considered
themselves the main decision maker for
the farm operation, and 44% of the
respondents had used NAMIS.
Size of farm operation:
A total of 502 farmers indicated the size of
their farming operations
A total of 501 farmers responded to this
question.
Table 3 illustrates the
contingency table on which the Fisher’s
Exact Test was performed. The Fisher’s
Exact Test was used in preference to the
Pearson’s Chi-square because this is a
2x2 contingency table. A p-value of 0.040
was obtained, so the null hypothesis was
rejected. The data suggests that being the
main decision maker appears to be more
likely to use NAMIS.
Educational level
A total of 500 farmers indicated their
educational level as is illustrated in table 4.
For purposes of performing the Pearson’s
Chi-square test the no formal educational
level was deleted. A p-value of 0.00 was
obtained, so the null hypothesis was
rejected. The data suggests that the
educational level of the farmer appears to
have an influence on the use of NAMIS.
Those with a higher level of education are
more likely to use NAMIS.
Gender
A total of 502 farmers indicated their
gender, of which 405 were males. The
Fisher’s Exact Test was used and a pvalue of 0.883 was obtained, so the null
hypothesis was not rejected. The data
suggests that gender did not appear to
have an influence on the use of NAMIS.
Age of farmer
A total of 512 farmers responded and table
6 illustrates the number of farmers in the
Agri-food Value Chain
various age groups for both users and nonusers of NAMIS. The Pearson Chi-square
test was used and a p-value of 0.117 was
obtained, so the null hypothesis was not
rejected. The data suggests that age did
not appear to have an influence on the use
of NAMIS.
Table 7 illustrates the means by which
farmers received their NAMIS information.
As is observed in this table the top three
sources were the Green Vine, Newspaper
and NAMDEVCO staff in descending
order. It is worthy to note that the print
media far exceeded the ICTs as a means
of obtaining information by the farmers.
Fax was not used by any of the farmers.
This reinforces the issue of “tasktechnology fit and information systems
effectiveness”, Irick, M.L. 2008.
5
information by print media is expected to
be more expensive than more modern
means, such as, mobile phones and
websites, however if our information
consumers have not embraced these
modern means the effectiveness of MIS
will be seriously jeopradized.
Demonstrating the benefits of the use
of information in decision making in the
agribusiness sector is necessary if MIS are
to contribute to improved performance of
the sector. Further, if the benefits of agrifood value chain management are to be
derived in the region, then a stronger link
has to be made between MIS and value
chain development in the effort to make
the transition to a market oriented
agricultural sector.
References
Conclusion and Suggestions
Some general conclusions can be drawn
with respect to NAMIS. The above analysis
suggests that the information system is not
widely utilized by farmers – less than 50%.
Of those who have used the system the
majority received their information by print
media – Green Vine and newspaper. It
might be possible to increase the use of
NAMIS by re-examining the information
dissemination methods, since most
farmers do not appear to use the more
modern ICTs dissemination methods.
Educational level, decision making
responsibility and farm size based on this
study influences the use of NAMIS. Age
and gender did not have an influence on
the use of NAMIS. The use of NAMIS and
by extension other MIS in the region might
be increased by improving the educational
level of our farmers as is suggested from
the findings of this study.
As other Caribbean countries attempt
to adopt NAMIS or versions of it I will
recommend that a cost benefit analysis is
undertaken, especially of the various
means of disseminating information.
Generally,
dissemination
of
market
Chogou, P.L., P. Lebailly, A. Adegbidi, and
E. Gandonou. 2009. “Impact of Public
Market Information System (PMIS) on
Farmers Food Marketing Decisions:
Case of Benin”. Paper delivered at 111
EAAE-IAAE Seminar ‘Small Farms:
decline or persistence’ University of
Kent, Canterbury, UK, 26 – 29 June
2009.
Irick, M. L. 2008. “Task-Technology Fit and
Information Systems Effectiveness”,
Journal of Knowledge Management
Practice 9(3).
Khalil, J. and C. Kenny. 2008. “The next
decade of ICT development: access,
applications, and the forces of
convergence.”
Information
Technologies
and
International
Development 4(3): 1 – 6.
Parikh, T. S., N. Patel, and Y.
Schwartzman. 2007, “A Survey of
Information Systems Reaching Small
Producers in Global Agricultural Value
Chains.” In Proceedings of IEEE
Conference
on
Information
and
Communication
Technologies
for
Development (ICTD) 2007, 334 – 344.
Agri-food Value Chain
Verdouw, C. N., A.J.M. Beulens, J.H.
Trienekens and S. Wolfert. 2010.
“Business Process Modelling in
Demand-Driven
Agri-Food
Supply
Chains.” Proceedings of the 4th
International European Forum on
6
System Dynamics and Innovation in
Food Networks. Organized by the
International Center for Food Chain
and Network Research, University of
Bonn, Germany.
Agri-food Value Chain
7
Table 1: Information dissemination method by group
Information dissemination method
Person to person
Percent
9
18
Print media
ICTs
73
Table 2:Farm size and use or non-use of NAMIS
Used NAMIS
221
9.01
Farmers
Mean farm size (acres)
Did not use NAMIS
281
5.21
Table 3:Decision maker of farm and use or non-use of NAMIS
Main decision maker (yes)
Main decision maker (no)
Used NAMIS
207
13
Did not use NAMIS
249
32
Table 4:Educational level of farmer and use or non-use of NAMIS
No formal educational level
Primary school started
Primary school completed
Secondary school started
Secondary school completed
Tertiary level education
Used NAMIS
0
10
48
36
88
15
Did not use NAMIS
2
51
105
50
53
12
Table 5: Decision maker of farm and use or non-use of NAMIS
Males
Females
Used NAMIS
199
24
Did not use NAMIS
251
28
Table 6: Age of farmer and use or non-use of NAMIS
Under 25 years
25 to 34 years
35 to 44 years
45 to 54 years
55 to 64 years
Over 65 years
Used NAMIS
9
36
75
71
24
9
Did not use NAMIS
8
48
71
96
52
13
Agri-food Value Chain
8
Table 7: Percent of respondents receiving information from the various NAMIS
Information source
Percent of respondents
68
Green Vine
Newspaper (market watch)
NAMDEVCO’s staff
Telephone
Website
Kiosk
Email
Fax
58
57
13
12
10
1
0
NB: There were 225 respondents
sources