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, JapanMarch 15-17, 2013

The structure of the presentation

• Antecedents of the research

• Aims of the research

• Methodology

• Main results

• Consequences

Antecedents of the research

• Basic idea based on the models explaining the consumers’ behaviour

General models

Consumers’ behaviour

e.g.: Engel-Blackwell-Miniard (1987); Howard,

Sheth (1969)

Product group related models

e.g.: Shepherd, R. (1990); Pilgrim, F. J.

(1957); Grunert, Brunso, Bisp (1993)

Market orientation

Verhees, Meulenberg (2004)

Desphande, Farley, Webster (1993); Kohli, Jaworsky (1990); Ruekert (1992); Kohli, Jaworsky (1990); Narver, Slater (1990);

Shapiro (1988)

Is it possible to set up a branch Is it possible to set up a branch related model relating to SMEs?related model relating to SMEs?

Aims of the research

Cultural focus Managerial focus

MKTOR - Narver,

Slater (1990)

MARKOR - Kohli,

Jaworsky (1990)

Customer orientation Intelligence generation

Competitor orientation Intelligence

dissemination

Interfunctional

coordination

Responsiveness

Testing MARKOR and MKTOR among food processing Testing MARKOR and MKTOR among food processing SMEs:SMEs:

1.1. Can the three-three factors in the two scales be Can the three-three factors in the two scales be considered one dimension? considered one dimension?

2.2. Does each factor have enough discriminating ability, that Does each factor have enough discriminating ability, that is do we have the right to separate the variables is do we have the right to separate the variables constituting the factors into three-three factors? constituting the factors into three-three factors?

Methodology

• The composition of the sample

Number of

employees

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 The data were analyzed with the structural equation modelling (SEM) structural equation modelling (SEM)

method – Amos 7 (SPSS)method – Amos 7 (SPSS)

Results

• Acceptable one-dimensional models

Nomination of factor

Number of variables in the original

model

Number of kept

variablesChi2

Degree of

freedom

p

MARKOR

Intelligence generation 10 6 10,430 7 0,166Intelligence dissemination

8 4 4,790 2 0,930

Responsiveness 14 9 37,049 26 0,074

MKTOR

Consumer orientation 8 4 3,542 2 0,170Competitor orientation 5 5 - 0 -Interfunctional coordination 4 4 0,248 1 0,618

• Summary of the discriminating ability investigation between the factor pairs

Factor pairs Chi2 Degree of freedom

p

MARKORIntelligence generationIntelligence dissemination

35,649 3 8,88E-08

Intelligence generationResponsiveness

141,02 1 1,59E-32

Intelligence dissemination Responsiveness

66,98 1 2,74E-16

MKTOR Consumer orientation Interfunctional coordination

84,592 1 3,67E-20

The original model can The original model can partly partly be be used inused in the the case of SMEs working in case of SMEs working in

the food industry. the food 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 one-dimensional 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 The original model can not be used inin the the case of SMEs working in the case of SMEs working in the

food industry. food industry.

Next step: look for variables that

Next step: look for variables that

describe more efficient

describe more efficientlyly the characteristics

the characteristics

of the SMEs in this branch.

of the SMEs in this branch.

Is it possible to set up a branch Is it possible to set up a branch relarelatted model ed model relating to relating to SMEs?SMEs?

Yes! But new variables should be inserted in Yes! But new variables should be inserted in the model to increase its explanation ability. the model to increase its explanation ability.

THANK YOU FOR YOUR ATTENTION!

polereczki.zsolt@ke.hu