Baltic Journal of Economic Studies
93
Vol. 4, No. 2, 2018
Corresponding author:
1 Department of Management and Economics of Water Transport, State University of Infrastructure and Technology.
E-mail: karpo_2004@ukr.net
2 Department of Management and Economics of Water Transport, State University of Infrastructure and Technology.
E-mail: Palyvoda_olena@ukr.net
3 Department of Finance, National University of Trade and Economics.
E-mail: e95bond@gmail.com
DOI: https://doi.org/10.30525/2256-0742/2018-4-2-93-98
SIMULATION MODELLING OF STRATEGIC DEVELOPMENT
OF TRANSPORT AND LOGISTICS CLUSTERS IN UKRAINE
Оksana Karpenko1, Olena Palyvoda2
State University of Infrastructure and Technology, Ukraine
Olena Bondarenko3
National University of Trade and Economics, Ukraine
Abstract. The aim. The article is devoted to the development of methodological approaches to the strategic
management of the development of transport and logistics clusters, which take into account opportunities and
barriers, especially the domestic economic environment, as well as the specifics of certain types of economic
activity. Methods. The economic and mathematical model is substantiated using the Savage criterion, which gives
an opportunity to choose the optimal strategy of transport and logistics cluster development in the domestic
conditions of management taking into account the different expectations of business entities. Methods similar
to the Wald, Bayesian and Savage criteria were used for choosing optimal strategies in decision making theory
and optimization problems of the following types were solved: when the distribution of states of the environment
is unknown and assumed to be the most unfavourable; when it is known empirical expected distribution of
environmental conditions and that is the average expected performance level for each indicator’s group; when
it is known expected division of the priorities of the decision-making entity that is the average expected level
of financial (organizational, etc.) support for a certain group of indicators. Results. Four types of “clean” cluster
development strategies are identified and described, which can be used in various combinations by transport and
logistics companies. The economic and mathematical model of the transport and logistics cluster performance is
presented, which allows implementing a large number of combinations of types of cluster development strategy
by taking economic, environmental, social and innovative measures, affecting different groups of performance
indicators. The influence of all possible variants of the binary and ternary combination of different types of
transport and logistics cluster development strategies on the cluster performance is considered. It is established
that the greatest influence on the transport and logistics cluster performance is exerted by the combination of
economic and innovative types of strategy. Practical significance. Given the interest of entrepreneurs in cluster
forms of organization and the strengthening of cooperation with EU countries, present development promotes
scientific approaches to modelling cluster development strategies in the economy of Ukraine. Relevance/originality.
The developed simulation model increases the likelihood of implementing the most optimal combination of “clean”
development strategies, contributes to a more accurate prediction of cluster development and as a methodological
approach can be applied to various types of economic activity.
Key words: transport and logistics cluster, simulation modelling, strategic development of transport and logistics
cluster, cluster performance, logistics, transport.
JEL Classification: D85, O18
1. Introduction
The need to ensure competitive advantages of the
national economy in the global economy motivates to
search for organizational and managerial methods and
forms that could, under the conditions of permanent
economic and technological changes, contribute to the
successful adaptation and development of economic
actors. The formation and operation of regional clusters
is a kind of answer to this task, because, as the world
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Vol. 4, No. 2, 2018
practice shows, they represent peculiar growth points
that accelerate and strengthen the innovative orientation
of the economy, lay the foundations of competitiveness
and investment attractiveness. Regional clusters also act
as an instrument that forms a particularly favourable
environment for the development of small and
medium-sized business and promotes the generation of
synergetic and multiplicative effects that have a positive
influence on the development of the economy, raising
the level and quality of life of the population, both in
individual regions and in the country as a whole.
In Ukraine, there is a strong interest in the idea
of economic development based on clusters, both
among government officials and in the scientific and
business environment. This is evidenced by the formal
declaration of about two dozen clusters in various
types of economic activity in Ukraine. But it should
be noted that the overwhelming majority of initiated
clusters has merely declarative nature and does not
provide for the real economic cooperation. However,
given the interest of entrepreneurs and scientists in
a cluster form of entrepreneurship and taking into
account the increased cooperation with EU countries,
there is an urgent need to develop scientific approaches
to analysing and modelling strategies for the cluster
formation and development in the economy of Ukraine,
forecasting the consequences of their operation in the
domestic economic space, assessing the integral cluster
performance.
The research of the problems of cluster network
operation is quite active and careful taking place in
western and domestic economic science during the
last decades. At present, the questions of the nature,
types, goals, tasks, stages of formation, and mechanisms
of interaction between enterprises in clusters, as
well as directions and forms of the state support are
comprehensively considered in the works of such
researchers, as M. Porter, M. Castells, M. Enright,
O. Solvell, G. Lindqvist, Ch. Ketels, M. Voinarenko,
V. Tarasenko and others.
Despite the existence of significant scientific research
results in the field of cluster development, the research
and formulation of the peculiarities of cluster operation
in certain types of economic activity, in particular
transport and logistics, remains relevant. There is also
a practical interest in the formulation and selection of
the optimal cluster development strategies that take into
account the opportunities and barriers, first of all, of the
domestic economic environment.
Taking the above into consideration, the objective of
the presented research is to develop an economic and
mathematical model using the Wald, Bayesian, and
Savage criteria, and on its basis to analyse the influence
of the binary and ternary combination of different
types of transport and logistics cluster development
strategies on the expected cluster performance, with
the subsequent selection of the optimal strategy for
cluster development under the domestic conditions
of management.
2. Types of probable “clear” strategies for the
development of transport and logistics clusters
The study of the practice of European clusters’
operation shows that the main types of performance
that can be generated by the cluster cooperation are:
economic, social, environmental, and innovative. In
previous works, we implemented the modelling of
cluster efficiency in abovementioned directions and
calculated their integral indicators on the basis of groups
of indicators (Fig. 1) (Karpenko, Palyvoda, Bondar,
2018).
However, in order to ensure the efficiency of cluster
performance, the necessary condition is the forecasting
and selection of cluster development strategies that
are optimal in the domestic business environment. To
accomplish this task, we identified and studied four
types of possible “pure” strategies for the development
of transport and logistics clusters (TLC):
1) the strategy for the economic development of
TLC, which is associated with changes in production,
organizational and managerial activities of transport
and logistics enterprises (TLE), aimed at increasing
profit and profitability of transport and logistics
enterprises, increasing competitiveness, making
the best use of available resources, improving the
quality of transport and logistics services, increasing
the share and developing new market segments,
attracting investments, improving the management
system, the widest implementation of information and
communication technologies, etc.
2) the strategy for the environmental development
of TLC, which is aimed at the implementation of
environmental and economic interests by reducing
harmful emissions into the environment through
the use of cleaner modes of transport, reducing the
influence of transport on the environment through
the introduction of innovative technologies, achieving
compliance of vehicles with the requirements of
international environmental standards, raising
the level of environmental consciousness of the
population;
3) the strategy for the social development of TLC,
which is aimed at achieving general welfare and
collective security on the basis of mutual responsibility,
transparency, ethical behaviour, observance of legal
norms, observance of international norms, protection of
human rights, increasing the number of jobs, improving
working conditions, ensuring an uninterrupted
improvement of the educational and professional
level of workers, adequate wages, availability of social
benefits;
4) the strategy for the innovative development of TLC,
which provides for the efficient development and
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Vol. 4, No. 2, 2018
implementation of managerial, logistics and transport
innovations based on strategic marketing, research
and development works, modern information and
communication technologies, available scientific and
technical and intellectual potential of the enterprise,
use of the channels of technology and knowledge
transfer, development of intellectual needs of the staff,
stimulation of creative approach to the tasks performed,
constant knowledge development by the staff in the
process of professional activity.
2. Modelling the efficiency of the cluster
functioning at different expectations
In order to determine the dynamics of the groups of
indicators of the TLC performance (Fig. 1), recurrence
relations were given:
ft(xij)=g(dij1)xij+g(dij2)g(dij1)xij+g(dij3)g(dij2)g(dij1)xij, (1)
where g(dijt) is the function of the expected value
of the growth factor of the indicator xij for the year t,
which is a linear function in the case when the factor is
an indicator with a positive ingredient and inverse for
a factor with a negative ingredient. The results of the
previous modelling of the dynamics of integral indicators
of the transport and logistics cluster performance are
presented in Table 1.
Table 1
Integral indicators of the expected transport
and logistics cluster performance by group indicators
Integral indicator of
the TLC performance
Years of the TLC operation
t=0 t=1 t=2 t=3
Economic
performance
0,2935 0,2976 0,3203 0,3591
Environmental
performance
0,1848 0,1865 0,1929 0,2068
Innovative
performance
0,2826 0,2920 0,3128 0,3470
Social performance 0,2391 0,2423 0,2253 0,2696
Source: developed by the authors
The implementation of the above formulas is shown
for the case g(x+)=x+ and g(x–)=1/x–. Based on the data
presented in Table 1, we have modelled the evaluation
matrix of performance. In the model example, let us
assume that all xij acquire single values. Consequently,
this allows us to get the evaluation function with a
positive ingredient of this type (formula 2):
Indicators of the economic performance
– increase in revenues from the provision of services;
– increase in workforce productivity;
– increase in capital investments;
– reduction of expenses from the provision of services;
– increase in profitability (ratio of total revenues to total expenses).
Indicators of the environmental performance
– reduction of emissions to the environment due to the use of environmentally friendly modes of transport;
– reducing the impact of transport on the environment through the introduction of innovative technologies;
– increasing compliance of vehicles with the requirements of international environmental standards (environmental
safety of transport);
– reduction of payments for taxes and fees (environmental tax);
– reduction of fines for the violation of environmental legislation.
Indicators of the innovative performance
– return on assets;
– formation of new channels of technology transfer;
– increase in the number of developed and/or implemented information and management innovations;
– increase in the number of developed and/or implemented logistics innovations;
– increase in the number of developed and/or implemented transport innovations.
Indicators of the social performance
– creating additional jobs;
– improvement of working conditions;
– increase in the number and quality of social communications;
–growth of the wage level of employees;
– advanced training of employees, growth of social status and opportunities for self-realization.
Fig. 1. Indicators of cluster performance
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96
Vol. 4, No. 2, 2018
F+ =
0 0665 0 0718 0 0790
0 0554 0 0610 0 0701
0 0652 0 0717 0 0816
0
, , ,
, , ,
, , ,
,, , ,
, , ,
, , ,
,
0439 0 0453 0 0477
0 0665 0 0705 0 0762
0 0555 0 0584 0 0649
0 05443 0 0555 0 0584
0 0333 0 0349 0 0374
0 0217 0 0220 0 0231
0 0652 0
, ,
, , ,
, , ,
, ,, ,
, , ,
, , ,
, ,
0672 0 0712
0 0549 0 0571 0 0605
0 0439 0 0452 0 0475
0 0217 0 02222 0 0233
0 0565 0 0610 0 0671
0 0652 0 0678 0 0719
0 0239 0 0268 0
,
, , ,
, , ,
, , ,,
, , ,
, , ,
, , ,
0308
0 0717 0 0825 0 0990
0 0659 0 0692 0 0761
0 0652 0 0665 0 06992
(2)
After the “convolution” operation taking into account
weighting factors, an evaluation matrix for the groups of
indicators was obtained:
F fij= =
0 297613 0 186544 0 242283
0 320350 0 192898 0 252709
0 35
, , ,
, , ,
, 99053 0 206828 0 269639
0 297613 0 186544 0 242283
, ,
, , ,
�. (3)
For the study of the obtained evaluation matrix,
approaches similar to the Wald, Bayesian, and Savage
criteria of selecting optimal strategies in the decision-
making theory (Vitlinskyi, Velikoivanenko, 2004) were
used, that is, the optimization problems of the following
types were solved:
1. Optimization provided that the distribution of
states of the environment is unknown and assumed
antagonistic (the most unfavourable) for the subject of
decision-making:
z=V→max, (4)
j
ij i
i
i
min i max
f w
w
w w w
=
=
∑
∑
≥
=
≤ ≤ ≤
1
4
1
20
1
0
V ,
,
,
(5)
Where wi is the relative share of available resources
for the TLC development, which is directed to the
implementation of the i-th strategy, wmin and wmax are
respectively the least and most expected values, which
in practice should be determined by expert evaluation,
fij are the elements of the matrix F, V is the integral
indicator of the TLC performance.
On converting the model to an equivalent form:
g t
V
min
i
i= = →
=
∑
1
4 1 , (6)
j
ij i
i
i
min i max
f t
t
w
V
t t t
=
∑ ≥
=
≤ ≤ ≤
1
4
1
0
,
,
,
(7)
The result was obtained: w1=0,2847,w2=0,2293,
w3=0,2563, w4=0,2297, V=0,2834. Consequently,
according to the Wald criterion, in order to ensure
the transport and logistics cluster performance in the
amount of 28.34%, it is expedient to allocate 28.47%
of the available resources to the implementation of
the strategy of economic development, 22.93% –
environmental development, 25.63% – social
development, 22.97% – innovative development of
TLC.
2. Optimization, provided that the empirical expected
distribution of states of the environment is known, in our
case, it is the average expected level of performance for
each group of indicators. Let us denote this distribution
by λ=(λ1;λ2;λ3;λ4), 0≤ λ1 ≤1, ∑4i=1 λi=1. In this case, the
Bayesian criterion was applied and the following model
is obtained:
z V max= → , (8)
j
i ij i
i
i
min i max
f w
w
w w w
=
=
∑
∑
≥
=
≤ ≤ ≤
1
4
1
20
1
0
λ V ,
,
,
(9)
In practice, it is expedient to use a model of this type
after a certain period of time after the start of cluster
operation; in this case, it is possible to estimate the value
of λ=(λ1;λ2;λ3;λ4) empirically.
3. Optimization, provided that the expected
division of priorities of the decision-maker is known,
in our case, it is the average expected level of financial
(organizational, etc.) support for a certain group
of indicators. This distribution was denoted by:
µ µ µ µ µ µ µ= ( ) ≤ ≤ =
=
∑1 2 3 4
1
4
0 1 1; ; ; , ,� � � � �i
i
i and the following
model is obtained:
z
w
V
min V max
i
i i= → →
=
∑
1
4 µ
, � � � � , (10)
j
ij i i
i
i i
min i max
f w
w
w w w
=
=
∑
∑
≥
=
≤ ≤ ≤
1
4
1
20
1
0
µ
µ
V ,
,
,
(11)
1. Economic and environmental development of
TLC. In this case, the following values are assumed:
Baltic Journal of Economic Studies
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Vol. 4, No. 2, 2018
µ µ µ µ µ µ3 4 1 2 1 20 0 0 1= = > > + =, , , .� � � � � � We also
considered the values of weighting factors as variables.
After the implementation of the model, we obtained
the following result: w w w w V1 2 3 40 6802 0 3198 0 0 0 2621= = = = =, , , , , , , .� � � � � � � � � �
w w w w V1 2 3 40 6802 0 3198 0 0 0 2621= = = = =, , , , , , , .� � � � � � � � � �
2. Economic and social development of TLC. In this
case, the following values are assumed: µ µ µ µ µ µ2 4 1 3 1 30 0 0 1= = > > + =, , , .� � � � � �
µ µ µ µ µ µ2 4 1 3 1 30 0 0 1= = > > + =, , , .� � � � � � After the implementation
of the model, we obtained the following result:
w w w w V1 2 3 40 6599 0 0 3401 0 0 2788= = = = =, , , , , , , .� � � � � � � � � �
3. Economic and innovative development of TLC. In
this case, the following values are assumed: µ µ µ µ µ µ2 3 1 4 1 40 0 0 1= = > > + =, , , .� � � � � �
µ µ µ µ µ µ2 3 1 4 1 40 0 0 1= = > > + =, , , .� � � � � � After the implementation
of the model, we obtained the following result:
w w w w V1 2 3 40 6394 0 0 0 3606 0 2957= = = = =, , , , , , , .� � � � � � � � � �
4. Social and environmental development of TLC. In
this case, the following values are assumed: µ µ µ µ µ µ1 4 2 3 2 30 0 0 1= = > > + =, , , .� � � � � �
µ µ µ µ µ µ1 4 2 3 2 30 0 0 1= = > > + =, , , .� � � � � � After the implementation
of the model, we obtained the following result:
w w w w V1 2 3 40 0 2768 0 7232 0 0 2269= = = = =, , , , , , , .� � � � � � � � � �
5. Social and innovative development of TLC. In this
case, the following values are assumed: µ µ µ µ µ µ1 3 2 4 2 40 0 0 1= = > > + =, , , .� � � � � �
µ µ µ µ µ µ1 3 2 4 2 40 0 0 1= = > > + =, , , .� � � � � � After the implementation
of the model, we obtained the following result:
w w w w V1 2 3 40 0 3156 0 0 6844 0 2587= = = = =, , , , , , , .� � � � � � � � � �
6. Innovative and environmental development of TLC.
In this case, the following values are assumed: µ µ µ µ µ µ1 2 3 4 3 40 0 0 1= = > > + =, , , .� � � � � �
µ µ µ µ µ µ1 2 3 4 3 40 0 0 1= = > > + =, , , .� � � � � � After the implementation
of the model, we obtained the following result:
w w w w V1 2 3 40 0 0 4358 0 5642 0 2753= = = = =, , , , , , , .� � � � � � � � � �
The results of the study of influence of the binary
combination of strategy types on the transport and
logistics cluster performance are presented in Table 2.
As a result of the comparison of influence of
the binary combination of different types of TLC
development strategies, it has been discovered that
the combination of economic and innovative types of
strategy has the greatest influence on the transport and
logistics cluster performance, which allows ensuring the
expected integral performance in the amount of 29.57%
after three years of the TLC operation. The results of
the study of the influence of the ternary combination
of different types of TLC development strategies on
the transport and logistics cluster performance are
presented in Table 3.
The comparison of influence of the ternary
combination of different types of TLC development
strategies has shown that the combination of social,
Table 2
Results of the study of the influence of the binary combination of different types of cluster development strategies
on the cluster performance
Variants of the binary combination
of different types of TLC
development strategies
Relative indicator
of the TLC
performance, V
Relative frequency, wi
W1,
economic
performance
indicators
W2,
environmental
performance
indicators
W3,
social
performance
indicators
W4,
innovative
performance
indicators
Economic and innovative 0,2957 0,6394 0 0 0,3606
Economic and social 0,2788 0,6599 0 0,3401 0
Innovative and environmental 0,2753 0 0 0,4358 0,5642
Economic and environmental 0,2621 0,6802 0,3198 0 0
Social and innovative 0,2587 0 0,3156 0 0,6844
Social and environmental 0,2269 0 0,2768 0,7232 0
Note: developed by the authors
Table 3
Results of the study of the influence of the ternary combination of different types of TLC development strategies
on the TLC performance
Types of TLC
development strategy
Relative indicator
of the TLC
performance, V
Relative frequency, wi
W1,
economic
performance
indicators
W2,
environmental
performance
indicators
W3,
social
performance
indicators
W4,
innovative
performance
indicators
Social and innovative and
environmental
0,2732 0 0,3333 0,3333 0,3333
Economic and innovative and
environmental
0,2605 0,3643 0,3178 0 0,3178
Economic and social and
environmental
0,2475 0,3964 0,3010 0 0,3026
Economic and social and innovative 0,2455 0,4010 0 0,2993 0,2997
Note: developed by the authors
Baltic Journal of Economic Studies
98
Vol. 4, No. 2, 2018
innovative, and environmental types of strategy has the
greatest influence on the transport and logistics cluster
performance, which allows ensuring the expected
integral performance in the amount of 27.32% after
three years of the TLC operation.
On the basis of the developed economic and
mathematical model, the influence of the binary
and ternary combination of different types of TLC
development strategies on the expected integral
performance of transport and logistics cluster is
determined (Fig. 2).
4. Conclusion
As a result of the comparison of influence of the
binary and ternary combination of different types of
TLC development strategies, it has been discovered that
the combination of economic and innovative types of
strategy has the greatest influence on the transport and
logistics cluster performance, which allows ensuring the
expected integral performance in the amount of 29.57%
after the first three years of operation of the formed
transport and logistics cluster.
0,2957
0,2788
0,2753
0,2732
0,2621
0,2605
0,2587
0,2475
0,2455
0,2269
0 0,05 0,1 0,15 0,2 0,25 0,3 0,35
Economic and innovative
Economic and social
Innovative and environmental
Social and innovative and environmental
Economic and environmental
Economic and innovative and environmental
Social and innovative
Economic and social and environmental
Economic and social and innovative
Social and environmental
Expected performance factor
C
om
bi
na
tio
n
of
ty
pe
s
of
T
L
C
d
ev
el
op
m
en
t
st
ra
te
gi
es
Fig. 2. Results of comparison of the influence of the binary and ternary combination of different types of TLC
development strategies
Note: developed by the authors
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