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IMAGES project – Final report – version 1
1.1 Results of simulations on the study zones
1.1.1 Conversion to organic Farming in Allier (France)
1.1.1.1 Generation of the farming population and social networks
The farming population of Allier was generated through the method described in the previous chapter. The phase
2 interviews gave us very partial results about the social networks. Clearly, the sample is not representative of
the population we want to model.
However, the model is in this case particularly schematic because, as seen in the study of the general model, the
distribution of neighbourhood links depends much on the spatial distribution of the farms. The procedure of
localisation of the farms for Allier gives only a very rough idea of this spatial distribution.
Therefore, the distribution of neighbourhood links is very approximate in this model.
The professional links are related to the distance of each farm to the nearest city, or market centre. The rationale
is that the professional organisations, meetings and so on happen in these cities and structure the professional
links between farmers.
Finally a very small number of random links was chosen (0.1 ) on average.
Figure 5.23 gives an example of generated network.
Figure 5.23 : Example of generated social network in Allier. The blue lines represent social links. The
majority of the links correspond to geographic neighbourhood, but some links going through large
parts of the département can also be seen. These are the random links.
1.1.1.2 Evaluation of the personal impact
We studied mainly the financial impact of the conversion (see Huet and Deffuant 2001 for the details). The
evaluation of the financial impact of the conversion to organic farming is a very delicate problem because of the
lack of references and the high variability of this impact with the quality of the land, and other parameters on
which we do not have information. We developed a simplified model of this financial impact based on the
following steps :
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IMAGES project – Final report – version 1

definition of a simplified model of the financial impact for the period of conversion and after conversion.
This model is limited by the available variables in RICA data. It takes as input the characteristics of the
farm, the specifications of the measure (level of subsidies), and involves several parameters ruling the
decrease of yields, the prices of organic products…
 definition of possible ranges of values of variation for the parameters. These values come from the literature
about organic farming. The combination of all these values of parameters gives a large set of possible
models.
 Selection of a set of models by elimination of the models which are not compatible with the available
references. The selection is related to the effect of the load of the farm and by the study of the effect on a
farm which particularly close to the typical organic farms.
The final selection of models gives a range of possible values for the lower and upper impact. This calculation is
used to defined the personal calculation from the farmer, and the result of the technico-economic study.
Four periods are considered for the impact calculation :
 Period 1 : no subsidy for the conversion,
 Period 2 : First ceiling of the subsidy (30 000 F per year per equivalent full time work in the farm, limited to
two workers)
 Period 3 : second ceiling of the subsidy (60 000 F per year per equivalent full time work in the farm, limited
to two workers)
 Period 4 : no ceiling.
3000
Number of farms
2500
2000
period 1
period 2
1500
period 3
period 4
1000
500
-0
,8
0
-0
,7
2
-0
,6
5
-0
,5
7
-0
,4
9
-0
,4
2
-0
,3
4
-0
,2
6
-0
,1
9
-0
,1
1
-0
,0
3
0,
04
0,
12
0,
20
0,
27
0
Financial impact (percentage of the farm benefit)
Figure 5.24 : the histogram of financial impacts in the farming population of Allier for the four
periods. The results are negative for a majority of the population, but they are improved by the
introduction of the subsidies.
Number of farms for which the financial
impact is positive
2000
30
25
20
15
10
5
0
1500
nb farms
Percentage of the farms for which the
financial impact is positive
1000
500
period 1
0
period 1 period 2 period 3 period 4
period 2
% of total population
2
period 3
period 4
% of the prototypes
IMAGES project – Final report – version 1
Figure 5.25 : Number and percentages of farms for which the financial impact is positive (taking into account
the uncertainty). We note that the evolution of the subsidies has a very significant impact. On the right, we note
that the percentage of prototypes is lower than the percentage of farms. It means that the considered prototypes
represent more farms than the average.
1.1.1.3 Initialisation of the social impact
The initialisation of the social impact is based on the analysis of the interviews results, and also on various
sources of other data.. In particular, we used a study made in 1991, in which the farmers were asked about their
priorities for the five next years. We noted that 10% of the farmers envisaged to convert a part of their
productions to organic. On the other hand, 13% had the project to intensify their production.
Considering also the strong set of values which are related to organic farming, with ethical aspects, a distribution
including very convinced people (extremists) on both sides seems appropriate. We test a number of extremists of
about 10%.
The values of the mean value of the social opinion and its standard deviation were constrained by the following
reasons :
the values of –0.2 or +0.2 correspond to extreme positions, because when they are added with the financial
evaluation in the aggregated function, it means that the agent is ready to pay or to loose 20% of his benefit
because of his social convictions.
The mean of the social opinion about organic farming is very probably negative at the beginning of the
simulation (1992). The majority of the farmers consider organic farming as marginal practises.
1.1.1.4 Modelling the institutional process
The study of the institutional process and of the messages of the press showed that one can distinguish three
main periods which are described in the presentation of the measure in chapter 3. In the model, we made the
following simplifications :
we considered that the main institution in charge of the promotion sent only information about the financial
interest of the conversion, and the technical risks or problems. Practically this means that in the model the
institution sends only information messages, and no “social” messages. The information messages are boolean
values which express that the farmer has enough knowledge to make a personal calculation of the impact, and if
he is aware of the current subsidies.
We modelled the global trend in the society which gives more importance to the environment, and also to the
quality of the agricultural products by a global source of messages which touches at random all the farmers with
the same frequency, and delivers a positive social message. Table ?? shows the number of articles about organic
farming which we found in the local papers. The counting includes some reference to national papers, but is not
exhaustive.
Years
Number of messages
1992-1993
8
1994
21
1995
38
1996
50
1997
92
From 1998
Almost daily messages
Table 5.11 : number of message in the local press.
We considered four periods in the model, and the farmer receive (on average) the following number of messages
each year :
 from 1.03.1993 : 2 messages per year,
 from 1.06.1995 : 12 messages per year,
 from 1.01.1997 : 45 messages per year,
 from 12.06.1998 : 75 messages per year.
The study of the messages during the period led us to propose the following set of messages from the society :
 from 14.10.1994 : mean broadcast opinion 0.1 uncertainty 0.08 (organic farming is a quality label),
 from 14.06.1996 : mean broadcast opinion 0.15 uncertainty 0.1 (BSE crisis push people to be interest to this
label which assure of food tracability),
 from 19.12.1997 : mean broadcast opinion 0.2 uncertainty 0.1 (the French Prime Minister invites farmers to
convert),
 from 12.06.1998 : 0.25 uncertainty 0.1 (a national politic to support organic farming is implemented).
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IMAGES project – Final report – version 1
1.1.1.5 Parameter exploration
A first parameter exploration focused on the initial value for the mean social opinion and the corresponding
standard deviation, without the messages from the society. We extract from this first exploration the values
which led to low numbers of adoption, because the addition of the positive messages from the society tend to
increase this number.
Description of the parameter
value
Reflection time for adoption
1 week
Interest threshold
0.05
Average number of neighbourhood links
4
Average number of random links
0.1
Average number of professional links
0.2
Frequency of neighbourhood interactions
0.1 times per
day
Frequency of professional interactions
Once a month
Frequency of interaction in random links
Twice a year
Frequency of message meeting with the institution (when the farmer is in
Once a year
the network of the institution)
Frequency of messages from society
See above
Mean value of the society message
See above
Uncertainty of the society message
See above
Percentage of extremists
13%
Uncertainty of the extremists
0.01
Table 5.12: fixed parameters in the exploration of the model applied to Organic farming in Allier.
Description of the parameter
Information transmission rate
Mean of the initial mean social impact distribution
Standard deviation of the mean social impact distribution
Uncertainty of extremist
Uncertainty on the social opinion
Communication noise
Discussion diffusion
Uncertainty percentage for personal economical impact calculation
Values
0.1, 0.2
-0.15, -0.1, -0.05
0.1, 0.2, 0.3
0.01, 0.05
0.1, 0.2
0.01, 0.02, 0.03
0.2, 0.25, 0.3, 0.4
10, 20
Table 5.13 : varying parameters in the exploration of the Organic farming in Allier model
1.1.1.6 Results
Figure 5.26 shows the diversity of the results which can be obtained within the range of chosen parameters
(considering the number of adopters on 31.12.1999). The actual number of adopters being 111, be particularly
focus on parameter stets corresponding to the bottom left part of the curve.
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IMAGES project – Final report – version 1
Mean and standard deviation of adopter's number for different parameters
900
850
800
750
700
650
600
550
500
450
400
350
300
250
200
150
100
50
0
-50
-100
-150
-200
mean of mean opinion -0.05
mean of mean opinion -0.1
mean of mean opinion -0.15
intensity of social influ 0.4
intensity of social influ 0.3
Communication Noise stand 0.03
Communication Noise stand 0.02
Communication Noise stand 0.01
Information transmission 0.2
Information transmission 0.1
Decreasing discussion dif 0.4
Decreasing discussion dif 0.3
Decreasing discussion dif 0.25
Decreasing discussion dif 0.2
Uncertainty percentage fo 20.0
Uncertainty percentage fo 10.0
standard deviation (for n 0.3
standard deviation (for n 0.2
standard deviation (for n 0.1
Uncertainty of extremist 0.05
Uncertainty of extremist 0.01
Uncertainty of the rest o 0.2
Uncertainty of the rest o 0.1
Average of adopters
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IMAGES project – Final report – version 1
We consider the parameter sets leading to average values between 90 and 138 adopters on 31-12-1999.
300
280
Mean and standard deviation of adopter's number on 31.12.1999
for the interesting parameters
263268
260
240
230
220
205
number of farmers
200
188
180
174 175
160
157
140
117 119 122
120
100
90
129
138
100
80
60
40
46
46
46
47
20
0
- 20
- 40
intensity of social influ 0.4
intensity of social influ 0.3
Information transmission 0.2
Information transmission 0.1
mean of mean opinion -0.1
mean of mean opinion -0.15
Uncertainty of the rest o 0.2
Uncertainty of the rest o 0.1
Average of adopters
Figure 5.26 : Zoom on the simulations which are close to the actual number of adopters on 31-121999.
This selection leads us to consider 7 configurations of parameters are compatible with the data about the
adoption. These configurations are represented in table ??.
Information
transmission
probability
(omega)
Social
influence
A
0.1
0.3
B
0.1
C
0.2
D
Mean of mean Standard
Uncertainty of Number of
opinions
deviation of
the rest of the Adopters
mean opinions population
(average over
20
simulations)
Standard
deviation on
the number of
adopters (%)
-0.15
0.1
0.2
87,8
14,55
0.3
-0.1
0.1
0.2
114,3
15,89
0.3
-0.15
0.1
0.2
143,4
15,09
0.1
0.3
-0.1
0.1
0.2
100,4
11,37
E
0.2
0.4
-0.1
0.1
0.1
119
31,64
F
0.1
0.4
-0.1
0.1
0.2
121,8
12,05
G
0.1
0.3
-0.1
0.1
0.1
129,4
32,79
Table 5.14 : the values which are the most compatible with the data of adoption (111 adopters on
31.12.1999).
We now study these 7 cases.
We identified two social dynamics :
 A and C with an mean initial social opinion of – 0,15
 B, D, E, F, G with a mean initial social opinion of – 0,10
For both of them the majority shifts toward more negative values. However, the shift is more important for
dynamics A..
For both these dynamics, a group of positive extremists appears (later for dynamics A). In both cases, the
positive extremists have a mean opinion at 0.33. As an example, figures 5.27 and 5.28 give more details on the
evolution of the social opinion of the farmers and the evolution of the number of farmers in the different interest
phases.
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IMAGES project – Final report – version 1
0
50
100
150
200
250
300
350
Evolution of social opinion (A)
6000
number of farmers
5000
4000
3000
2000
1000
0,45
0,33
0,22
0,10
-0,02
-0,13
-0,25
-0,37
-0,48
0
opinion
Figure 5.27 : Evolution of the distribution of social opinions in the case of parameter values A.
not interested/100
120
number of farmers
100
80
uncertain/10
Evolution of the number of farmers in each phase (A)
interested
allier bio
visited
adopters
adopt data
60
40
20
no
vm 93
ar
s94
ju
il94
no
vm 94
ar
s95
ju
il9
no 5
vm 95
ar
s96
ju
il9
no 6
vm 96
ar
s97
ju
il97
no
vm 97
ar
s98
ju
il98
no
vm 98
ar
s99
ju
il99
0
Figure 5.28 : evolution of the number of farmers in the different phases.
1.1.1.7 Concluding remarks about the application of the model on organic farming
conversion in Allier
The presented results are very preliminary. A more systematic exploration of the parameter space is necessary.
In particular, the shift toward negative values of the majority of farmers is a counter intuitive result. It is likely
that other parts of the parameter space are compatible with the constraints of the data, without this average
worsening of the social opinion about organic farming.
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IMAGES project – Final report – version 1
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