MARKETING CHARACTERISTICS OF
THE HUNGARIAN SMEs WORKING IN
THE FOOD PROCESSING INDUSTRY
Zsolt Polereczki, György Kövér, Tibor
Bareith, Zoltán Szakály
Kaposvár University, Faculty of Economic Sciences,
Marketing and Trade Department
International Symposium on Business and
Social Sciences
Toshi Center Hotel, Tokyo, Japan
March 15-17, 2013
The structure of the presentation
• Antecedents of the
research
• Aims of the research
• Methodology
• Main results
• Consequences
Antecedents
the
Is
it possible toofset
upresearch
a branch related
model relating to SMEs?
•
Basic idea based on the models explaining the consumers’
behaviour
Consumers’
behaviour
General models
Product group
related models
Market
orientation
e.g.: EngelBlackwell-Miniard
(1987); Howard,
Sheth (1969)
Desphande, Farley, Webster
(1993); Kohli, Jaworsky
(1990); Ruekert (1992);
Kohli, Jaworsky (1990);
Narver, Slater (1990);
Shapiro (1988)
e.g.: Shepherd, R.
(1990); Pilgrim, F.
J. (1957); Grunert,
Brunso, Bisp (1993)
Verhees, Meulenberg
(2004)
Aims of the research
Model
creation
3rd step
International expansion of
the research
2nd step
In 2010 we investigated 250 agricultural and
food industrial SMEs with internationally used
standard questions – external and internal
factors, market orientation, market efficiency
1st step
Nationwide survey carried out in 2009 with
100 dairy and meat industrial SMEs - general
entrepreneurial practice and opinion about
marketing
1.
2.
Testing MARKOR and MKTOR among food processing SMEs:
Can the three-three
factors in theManagerial
two scalesfocus
be considered one
Cultural focus
dimension?
MKTOR
Slater discriminating
MARKOR - Kohli,
Does each
factor- Narver,
have enough
ability, that is do we
Jaworsky
(1990)
have the right to(1990)
separate the variables
constituting
the factors
into three-three factors?
Customer orientation
Intelligence generation
Competitor orientation
Intelligence dissemination
Interfunctional
Responsiveness
coordination
Methodology
• The composition of the sample
Number
employees
of
Composition
Head
%
0-9 people
136
71,2
10-49 people
42
21,9
50-300 people
13
6,9
Total
191
100
The data were analyzed with the
structural equation modelling (SEM)
method – Amos 7 (SPSS)
Results
• Acceptable one-dimensional models
Nomination of factor
Number of
variables in the
original model
Number
of kept
variables
Chi2
Degree
of
freedom
p
6
4
9
10,430
4,790
37,049
7
2
26
0,166
0,930
0,074
8
5
4
5
3,542
-
2
0
0,170
-
4
4
0,248
1
0,618
MARKOR
Intelligence generation
Intelligence dissemination
Responsiveness
10
8
14
MKTOR
Consumer orientation
Competitor orientation
Interfunctional coordination
• Summary of the discriminating ability
investigation between the factor pairs
Factor pairs
Degree of
freedom
p
35,649
3
8,88E-08
141,02
1
1,59E-32
66,98
1
2,74E-16
Chi2
MARKOR
Intelligence generation
Intelligence dissemination
Intelligence generation
Responsiveness
Intelligence dissemination
Responsiveness
The original model
can partly be used
MKTOR
Consumer orientation
3,67E-20
in
the case
of SMEs84,592
working1 in the
food
Interfunctional
coordination
industry.
• MARKOR scale, Intelligence generation factor
– The food industrial SMEs collect secondary information through
basically informal channels - enterprises consider this little information
satisfactory, they are highly convinced that they react to real
consumer demands (Responsiveness factor).
• MARKOR scale, Intelligence dissemination factor
– One of the weakest elements of market orientation is the effective
information flow.
• MKTOR scale, Customer orientation factor
– Enterprises already feel commitment to customer orientation,
however, it does not appeal in real activities.
Consequences and implications
• It is possible to decrease the onedimensional variables in a way that the
refusal of the one-factor model cannot be
justified in case of 5 of the examined six
factors.
The original model can not be used in
the case of SMEs working in the food
industry.
Is it possible to set up a branch related
model relating to SMEs?
Yes! But new variables should be inserted in the
model to increase its explanation ability.
THANK YOU FOR YOUR
ATTENTION!
polereczki.zsolt@ke.hu