Discussion Papers 1988.
Spatial Organization and Regional Development 123-147. p.
1 23
Gyorgy ENYEDI
SPATIAL DIFFUSION OF INNOVATIONS IN HUNGARIAN
AGRICULTURE
Introduction
The Epatial diffusion of innovations has
been an important issue in geographic research
since Hagerstrand published his famous book on
"Innovationsforloppet" 35 years ago. This research
approach put the time/space relationship into a
new prospective. The theoretical background of this
approach was enlarged in recent decades, by Hager-
strand himself, by his school in Lund, and by a
group of North American geographers. Now, geography
textbooks refer to time geography, describing the
general model, how an innovation is generated in a
center, and how it is diffused spatially from this
center towards the receiving, less developed areas
until the point of saturation.
This approach did not have great influence
on the geographers of East Central Europe. We can
quote only R. Domanski of Poland and K. Ivanicka
of Czechoslovakia, who applied innovation diffusion
theory in their empirical research.
The method and approach gained new importance
when, since the late 1970s, "an innovation oriented
regional policy" has been formulated. There was an
urgent need to replace the earlier growth oriented
regional policy by a new one emphasizing structural
and qualitative changes. Substantial changes in the
world economy occurred in the last decade, and these
changes forced the re-evaluation of traditional

Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
124
regional policy.
This "traditional" approach classified the
different regions according to their capacity of
growth: local natural resources, manpower, trans-
port-connections, etc. New regional policies dis-
tinguished the different regions according to their
capacity of emanating, transferring, and absorbing
innovations; hence, their
+ D potential, sectoral
structure size of enterprises, labor qualification,
type of settlement network, etc. came into the
forefront.
This paper analyses  the  territorial diffusion
of one of the most important agricultural innova-
tions: production systems. Hungarian agriculture
proved to be most innovative - perhaps the only
really innovative - sector of the Hungarian econony.
There is an adequate data base for analyzing the
territorial diffusion of production systems. The
production systems themselves represent a complex
organizational-technological innovation and have
been dispersed on the whole area of the country
/75 % of the country's area is utilized by agri-
culture/.
We were looking  for answers to the following
questions;
- is it possible to describe the life cycle
of innovations?
- can we distinguish centers and  receiving
areas of innovation?
- can we recognize territorial regularities
in the diffusion of innovation?
- based upon the above aspects, can we
forecast future territorial paths of innovation?

Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
1 25
Production Systems
Production systems represent an industrial-
type method of agriculture, when all the details
of production of a given plant or that of animal
products are accurately elaborated: e.g., the time
of sowing, the quality of seed, the quantity of
seed to be sown per hectare, the type and quantity
of fertilizers, the time of fertilizing, all the
types of machinery, etc. The production systems
are worked out either by agricultural schools,
leading farms, or big agribusiness enterprises /e.
g., by food processing and marketing chains/. The
owner of the system offers the application of the
system as a service to individual farms. The-system
manager adapts the system to the local ecological
conditions; it will supply the farmer with the
necessary technology, quality seeds, etc. and will
guarantee a minimum yield. Farmers pay a fee for
the expertise and services.
The production system idea was worked out
first in the U. S. It was applied for the first time
in Hungary some 20 years ago, and it started to be
propagated in the country between 1969 and 1971.
Broiler chicken and corn, then wheat production
were incorporated first into production systems;
later, all the important plants /including fruit
and vines/ and animal products had their production
systems elaborated and introduced. The scientific
accuracy of the production systems has cortributed
largely to the spectacular yield take-off of Hunga-
rian agriculture. The yields of the most important
products doubled during the last 15 years.
In Hungary, the innovation centers remained
almost entirely within agriculture. Some leading

Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
126
state farms or cooperative farms took the initiative
for working out and propagating production systems.
In certain cases - e.g., sugar beet and hemp - the
processing industry also took part in managing
production systems.
Within a few years, most of the Hungarian
large scale farms joined to one or several produc-
tion systems. Farm managers expected different
types of advantages from membership in production
systems: higher yield, easier access to quality
seeds, and especially to Western technology im-
ported for hard currency. The curve of the life
cycle of single production systems showed a regular
pattern: after a strong take-off period, a slowly
advancing growth, then saturation and even a slight
decline. The decline was explained by the worsening
economic conditions for agriculture, when the
charges for membership proved to be too heavy a
burden for poor cooperatives. The profitability
of agricultural activity diminished significantly
during the last five years because of the growing
taxes and the rapidly rising prices of industrial
goods used in agriculture.
On the other hand, the original task of pro-
duction system managers, i.e., the introduction of
the new technology, was practically achieved. We
do not intend to discuss here what type of future
might be forecasted for the production systems.
Anyway, their life cycles are long enough for
analyzing their regularities.
During fifteen years, the production systems
became general in Hungarian agriculture. In 1985,
there were 64 industrial *pe production systems
in our agriculture: 20 of them were dealing with

Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
127
crops; 22-22 of them organized the production of
animal products and that of truck gardening and
fruit and vine growing. Eighty-nine percent of
wheat production, 91 % of corn production, and
96 % of sugar beet output are produced using
production systems. Two thirds of vine and 60
percent of apple output also come from production
systems. As for livestock raising, 71 percent of
dairy cows, 89 percent of pigs, and 99 percent of
egg laying hens belong to production systems /Data
of the collective, large scale farming sector/.
There were 8 production systems that had more than
200 member farms; large scale cooperative or state
farms participate only in the production systems.
There are 1,300 large scale farms in the whole
country; they dealt with basic products /wheat,
corn, beef/. The majority of the production systems
have 10-15 member farms. There is a real competition
among production system managers for recruting - and
keeping - members. The relation between the manager
farms and the member farms has been based on mutual
economic interests; there was not any administrative
or government intervention into the territorial or-
ganization of the production systems. Consequently,
their territorial diffusion was guided spontaneously
by economic judgements and by the dissemination of
information about the systems.
In sum, the spatial distribution of produc-
tion systems fits to the concept of the territorial
diffusion of innovations.
Data Base
Our research covered the area and activity of
3 systems and 4 crops /Table 1/.
Here we present a
summary of the research of two corn production sys-
tems.

Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
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Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
129
The two systems are: Industrial Corn Production
System /IKR/, with its headquarters in Babolna
/Babolna Agricultural Combine, a state farm/; and
the industrial Corn Production Association /KITE/,
organized by the "Red Star" Producers'Cooperative
in Nadudvar. The first center is located in North-
western Hungary; the latter one on the Great Plain,
near the city of Debrecen. These are the largest
production systems of the country; IKR had 260 and
KITE had 348 member farms in 1981. In the beginning,
the two distant systems had separate areas, but
later competition developed between them.
Corn is the most important crop in Hungary,
occupying 1/4 of the total cropland. During the
1970s, corn enjoyed a good economic position, thus
innovative farms turned easily towards the corn pro-
duction systems. We analyzed the spatial distribu-
tion of the corn production systems year by year
between 1971 and 1981.
The Analysis
/a/ The development of both production sys-
tems show three distinct periods /Fig. 1/. The first
period, the take-off, was characterized by a very
rapid growth of the number of member farms. The
take-off period started earlier in the case of IKR
/Babolna Agricultural Combine was the pioneer of
the deep technological-organizational changes in
Hungarian agriculture/. The take-off period ended
in both cases around 1975. The second period /1975-
1980/ was the phase of levelling, when the exten-
sion of the systems continued in much slower pace
than earlier. This period was different in the two
systems: it was more explicit in the case of the

•
•
▪
Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
130
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Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
131
IKR; but KITE enjoyed a second, smaller take-off
period /after 1977/1 KITE was still able to en-
large their clientee. Due to its more successful
and more aggressive business policy, it succeeded
in seizing some of the former IKR members. On the
other hand, corn areas expanded mainly on the most
fertile chernozem zones of the Great Plain, where
the KITE headquarters is located. TKR had to
withdraw from Northern Hungary, where it tried to
introduce corn production systansamong relatively
poor farms. Due to the modest ecological potential,
corn yields in Northern Hungary were not large
enough to support the raise in production costs.
Changes in the territory cultivated in pro-
duction systems were more differentiated. Figures
2 and  3  show the changes in the size of corn area
in the two  systems,  by counties.
In the IKR /Fig. 2/, the take-off period is
clear in every county. The system is present in all
19 counties of Hungary. IKR started its activity in
the late 1960s in  4  Western Hungarian counties, but
it penetrated in some counties as late as 1974. In
1977,  there was a sharp drop in corn area in almost
all the counties. This decline was explained by the
sudden worsening of the economic conditions of the
crop. Following the second oil price explosion, the
prices of energy, gasoline, and fertilizer jumped,
but corn prices remained unchanged. The farms re-
sponded to this situation by drastically reducing the
area activated with corn. The government was forced
to rise the corn price and expansion of the corn
area started again - but not everywhere, and not on
the same rhythm. In some counties, the saturation
became clear already in  1979.  Anyway, there was not

Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
132
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Area involved in the IKR system by
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Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
133
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FIGURE 3
Area Involved in the KITE system by counties

Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
134
a single county that was able to reach the maximum
level of the take-off period untill 1981. Corn
areas were becoming more and more concentrated in
the ecologically most advantageous counties.
The KITE system was organized later, so the
take-off period was postponed somewhat. The member
farms are less dispersed in the country than in the
case of IKR:  5  counties /all of them in Western
Hungary/ contain no member farm. The  1977  drop in
corn area was slighter than in the IKR area, fol-
lowed by an explicit new take-off, and, again, by a
new slight drop in 1980. In the three leading
counties - Bekes, Hajdu-Bihar and Szolnok - which
have contiguous area and where we can find the
three most fetile loess ridges of the country, the
take-off continues in full speed. A few of the
counties already showed a certain levelling in the
corn area, but, as a whole, the system was far
from saturation in  1981.
/b/ The next question was: whether there was
any spatial continuity in the expansion of the sys-
tems. Evidently, there was not a clear geographical
continuity, since IKR and KITE tried to advertize
their services in the whole country and so the infor-
mation was not passed from neighbour to neighbour,
as in the classical Hagerstrand model.
Nevertheless, there are distinct geographical
groups that became "core areas" of the system. Geog-
raphical proximity helped to establish relations
between agricultural enterprises; the ecological
conditions were similar, too. In the IKR system
/Fig.  4/,
the take-off started in Komarom and East
of Gy5r-Sopron Counties, close to the Babolna
headquarters. The next contiguous areas of the take-

Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
13 6
off were: Vas and West of Gy6r-Sopron Counties;
South Eastern Plain /Bekes and Csongrad Counties/;
Fejer County and the Szerencs Loess Ridge /in Bor-
sod-Abauj-Zemplen County/. The last wave of expan-
sion created zones in Somogy and Baranya Counties.
New farms that joined the system during and after
the late 1970s were dispersed geographically. The
importance of the geographical connectivity is also
shown while we analyze the core areas of the systems
/Figures 5 and 6/ in a more detailed way.
We can conclude our time/space analysis as
follows:
/1/ one can describe the life cycle of the
systems by a regular curve. The IKR system has al-
ready reached its saturation; the KITE has more
dynamism. The saturation does not mean that the sys-
tems will be ended, though: they make efforts to
keep their positions and they introduce ever newer
production systems and diversify their activities.
The earlier successful corn production system pro-
vides a reference for other crops. Rural settle...,
ments, where the headquarters of production sys-
tems were located, became innovation centers at the
national and in some cases, international scale.
They exported production systems - mostly for corn
and poultry - to several countries. This fact had
a great impact on the functional diversification
and on the overall development of the given rural
communities.
/2/ There were regularities in the geogra-
phical expansion of the systems. The take-off
started in a spatially concentrated manner; later,
a few local centers were formed that conveyed the
innovations received from the production systems'

Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
• t
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FIGURE 5 Member farms within the KITE core area
by their year of joining the system
FIGURE 6 Member farms within the IKR core area
by their year of joining the system

Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
138
centers towards the neighbouring villages.
The Models
After analyzing the empirical data, and
concluding the above mentioned main tendencies,
we tried to describe the general relations of the
spatial diffusion of production systems in forms
of models. /Mathematical modelling was carried out
by Dr. J. Rechnitzer./
/1/ The saturation of the systems - the
"snowball" model
The snowball model explains the intensity
of the propagation and the level of the saturation
in the case of a process developing in time ard in
space. The model applies a logistic estimation of
a function for defining the size of growth. The
model was elaborated at the county level.
The model predicts the saturation level /in
hectares/ of the systems by counties. Comparing the
saturation level and the actual size of corn area,
we can estimate the further expansion of the pro-
duction system in a given county. The life curve
of the production system is different from county
to county. In sum, the model proved the saturation
of the IKR system. KITE still has some potential
for further expansion, but - because of its rapid
growth - it is nearing rapidly the upper limit of
its expansion.
/2/ The role of distance in the diffusion
of production systems - the center of
gravity analysis
The center of gravity method is used mainly
in population geography. One analyses the general

•
Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
1 3 9
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Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
trend of population location within a giveL area
by determining the movement of the center of gray-
ity for the whole country and on county levels as
well. In the calculations, we weighted the geog-
raphical coordinations of each member farm by the
corn area of the given farm. The calculation was
made year by year between  1971  and  1981.
In the take-off period, the center of grav-
ity of the IKR system was close to the center of
the production system, in KomArom County. We can
distinguish three phases in the movement of the
center of gravity. Between  1971  and  1974,  the cen-
ter of gravity "crossed" the Danube and it moved
to Pest County as a consequence of the intensive
expansion of the system in the Great Plain. In the
period of levelling /1974-1980/, the movement ex-
hibited different directions, but the center did
get somewhat closer to Transdanubia. In 1980-1981,
the center of gravity moved to the NE, which showed
the saturation of Transdanubia and the slow advance-
ment in the Great Plain.
In the case of the KITE system, the movement
of the center of gravity has been less exaggerated.
In the take-off period, the center of gravity moved
Westward, as the production system penetrated Trans-
danubia. Later, the movement slowed down, and the
center of gravity remained within the same region.
Concerning the movement of centres of grav-
ity on the county level, we get a similar picture:
the IKR system has had a more intensive territorial
movement within the counties, with South-South-East
as the main direction  /Table 2/.

Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
Table 2
The direction of movement of the center
-
ofravintheIKR
system by counties,
1971-1981
1. Szolnok
1. Komarom
2. Heves
2. Fejer
3. Bekes
3. Szabolcs-Szat-
mar
1. Vas
1. Veszpr4m
2. Somogy
2. NogrAd
3. Bacs-Kiskun
3. Hajdu-Bihar
4. Baranya
5. CsongrAd
6. Borsod-Abauj-
-Zemplen
7. Pest
8. Gy5r-Sopron
9. Tolna
The order of counties expresses the intensity of
the movements /from low to high/.
The movement of the KITE-system has been
less intensive. In several counties, the movement
was so insignificant that the location of the cen-
ter of gravity remained practically unchanged. In
most cases, the direction of the movement has been
N-NE /Table 3/.

Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
142
Table  3
The direction of movement of the center
of gravity in the KITE-system /1973-1981/;
by counties
1.  Szolnok
1.  Baranya
2.  Bekes
2.  Hajdu-Bihar
3.  Heves
3.  Bacs-Kiskun
4.  CsongrAd
5.  Fejer
1. Borsod-Abauj-
1.  NogrAd
-Zemplen
2.  Pest
2.  Szabolcs-SzatmAr
3.  Somogy
It is interesting to note that the direc-
tion of movement of the two systems has been inden-
tical in six counties, especially in the case of NW
movement. We can suppose the existence of an inten-
sive competition for the good corn areas in these
counties.
/3/ Groups of member-farms; cluster analysis
In the third level of modelling, we tried
to classify the member farms according to their spa-
tial peculiarities /from the point of view of the
propagation of the corn production systems/. The
following variables were used by farms:
1. the location of the farms /their geog-
raphical coordinates/;

Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
143
2. the year of entering /or re-entering/
into the system;
3. the size of the corn area /including
changes in size/.
We used the well known cluster analysis method for
grouping the member farms. We carried out cluster
analysis separately for the two systems.
We summarize here the result of the analysis
in the case of the IKR. We grouped the 260 member
farms of the production system into 7 groups
/clusters/.
In the first cluster, we found only 2 farms:
--
the Babolna Agricultural Combine and the Agard Ag-
ricultural Combine. Their corn area has shown a
steady growth: these two leading state farms played
a decisive role in the propagation of the produc-
tion system. Babolna originated the innovation, but
Agard was developed later into the position of co-
center of the innovation.
In the second cluster /15 farms/ we find the
local centers of the innovation. These farms joined
the production system between 1972 and 1974, and
they had large /1,500-4,000 hectares/ corn areas.
These local centers - which conveyed the innovation
into their surrounding regions - are dispersed in
the country /in 10 countries/.
In the third cluster /22 farms/ are the
member farms of the first take-off period. They
joined the system in an early period with large
corn areas. But these farms have not been stable
elements of the system: they have reduced continu-
ously their areas or at least there were sudden
drops in area.

Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
144
The seventh cluster /55 farms/ also contains
the farms of the first wave but they represent the
stable elements of the system, with a ccrn area of
1,000-2,000 hectares. The changes in their territo-
ry have been insignificant.
There are again only 2 farms in the fourth
cluster. They are close to the third cluster. They
joined the system in the first take-off period with
large corn area, which fell to half its size during
the period under investigation.
The fifth and sixth clusters /32 and 32
-----
farms/ represent the second wave of the propaga-
tion of the system. The farms joined the system in
1977 and 1978. The fifth cluster's farms weresiallein
their territory /800-1,000 hectares/, remaining un-
changed or extendirg slightly. In the sixth cluster,
the farms remained marginal from the point of view
of the system. Their corn area /500-800 hectares/
was at a minimum level, since about 800 hectares
of corn area are needed for the fully efficient
utilization of the complex technology chain of the
production system. Some of them quit the system and
re-entered later. They will be the first to leave
the system in case of unfavourable conditions.
Conclusion
We can conclude the results of our analysis
as follows:
1. We proved that there are spatial regulari-
ties in the diffusion of innovation /i.e., the corn
production system/. We were able to distinguish in-
novation centers and member farms that were ready
to absorb innovations to variable extents.

Enyedi, György: Spatial Diffusion of Innovations in Hungarian Agriculture. Ed.: Orosz Éva, Pécs:
Centre for Regional Studies, Discussion Papers 1988. Spatial Organization and Regional Development 123-147. p.
145
2. We were able to describe the life cycle
of innovation, and to distinguish the phases of
take-off, levelling, and saturation. The life cycle
curve was disturbed by the strong drop of the corn
area in 1977, which was a consequence of the drastic
worsening of the profitability of corn production.
We can expect a regular curve of the life cycle in
the case of continuously favourable conditions for
the propagation of innovation. The modelling of the
life cycle makes it possible to forecast the time
of saturation and the places of the possible further
expansion of the system.
3. We defined the main geographical direc..
tions in the propagatior of the system, i.e., the
role of distance in the diffusion of innovation.
4. We distinguished different groups of the
member farms according to their location, the ex-
tent of their corn area, and to their relation to
the production system.
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