Simulation modelling of marinas and heuristic optimisation of
business in relation to investments in sports objects
Ph.D. Ante Muniti¢,
M.Sc. Eli Maru8ié¢,
M.Sc. Josko Dvornik,
M.Sc. Merica Sliskovié
University of Split
Maritime Faculty Split
Zrinsko-Frankopanska 38, 21000 Split, Croatia
phone: 385 21 380 762, fax 385 21 380 759
E-mail: amunitic@pfst.hr
emarusic@pfst.hr
josko@pfst.hr
merica@pfst.hr
Abstract
System dynamics simulation modelling of marinas in relation to investments in
sports objects will enable rise of the quality of the total offer and competitive forces of
the observed system, and at the end growing satisfaction of tourists. The system of
marinas (LNT) has all the characteristics of a complex organisation and business
system, for which dynamic modelling efficient methods of simulation techniques have to
be used. One of the relatively recent, and particularly exposed and practically proved
scientific methods is system dynamics simulation modelling which was developed by the
Professor Forrester in the famous world scientific centre of the development of
management science - The Sloan School of Management (MIT).
This model is developed for the practical training of marine management
students. In this paper, the business system of marinas (LNT) will be determined
through a global model of integral nautical and tourist service (from berthing service as
a basic service to all other additional services). The subsystem of investments in new
capacities, like sports and additional capacities will be determined by exogenous
variable VINK- value of investments in new capacities.
Key words: system dynamics, simulation modelling, business system of marinas,
investments in sports objects, competitive advantages, nautical and tourist market,
sports and recreation market.
1. System dynamics quality simulation models of a business system (LNT)
The subsystem of investment in sports objects of a business system of a nautical
and tourist port must have the characteristics of intelligent behaviour, which implies the
following characteristics of managing behaviour: "If the capacity of LNT is full and if
in the last several years the income per guest has not increased, it is necessary, in the
next mid-term period, to invest in new facilities which will improve the quality of the
total services of LNT. In this case it is planned to build at least 4 outdoor and two
indoor tennis courts, one beach volleyball court and one swimming pool of 50m’,
including facilities like dressing rooms, sauna, showers, massage and medical
assistance, etc.). In case there is a decline of interest in the main LNT services, berthing,
then it is necessary to stop the construction of new capacities. This implies that the
started objects will be finished, while the others will be built after the demand increases
again. Also, if the state of the transfer account of LNT is not positive or there are not
sufficient means to cover the investment, it is necessary to ensure the mid-term and long
term loans in order to complete the investment."
In order to determine the global system dynamics simulation model of LNT, it is
necessary to determine the following relevant subsystems: subsystem of berthing
capacity (the main nautical and tourist service); subsystem of servicing vessels;
subsystem of capacities of additional services (trade and catering); information
subsystem; subsystem of the state of finances in the transfer account; subsystem of
credits for performed services; subsystem of debts; subsystem of income; subsystem of
marketing and sales; subsystem of long term and short term loans; subsystem of
engagement of total capacities; subsystem of the new sport capacities and their
facilities.
Simulation of LNT begins on the first day of April of the observed business year
(TIME=120 days). The first season finishes at the beginning of October of the same
year (TIME=300 days). The next period of off-season business begins in October of the
same year (TIME=300 days) and lasts to the beginning of the new season (TIME=485
days). The new tourist season begins on the 485" day (TIME=485 day) and lasts to
October of the next business year (TIME=665 days). New off-season business begins on
the 665" day and ends on the 850" day (TIME=850 days).
Investing into new capacities begins on the 380" day (TIME=380) and lasts on average
180 days, which means that it ends on the 560" day of business, and the first positive
effects of the investment (variable KPNI), or increase of the total income (UP), total
operating costs (UTP), generator of the vessel arrivals (GDP) and average realised
revenues per vessel per day (POPPD) stars in time TIME=406 days.
1.1. Mental and verbal simulation model of LNT business system
In accordance with system dynamics simulation quality methodology, it is
possible to present the mental and verbal model of LNT in the following way:
"If the variable generator of the vessel arrival GDP increases, the number of vessel
registration a day BPPD will also increase, which shows a positive (+) cause-
consequence link CCL", i.e., as abbreviated:
GDP(+)>(+)BPPD
«lf the number of vessel registration a day BPPD increases, the total number of
registered vessels UBPP will also increase, which shows a positive (+)cause-
consequence link CCL», i.e., as abbreviated:
BPPD(+)> (+)UBPP
"If the total number of registered vessels UBPP increases, the number of vessel
checkouts a day BOPD will also increase, which shows a positive (+) CCL.", ie., as
abbreviated:
UBPP(+)> (+)BOPD
"If the number of vessel checkouts a day BOPD increases, the total number of registered
vessels UBPP will decrease, which shows a negative (-) CCL", i.e., as abbreviated:
BOPD(+)> (-)UBPP
"If the average staying time of vessels PVZP increases, then the number of vessel
checkouts a day BOPD decreases, which shows a negative (-) CCL", ie., as
abbreviated:
PVZP(+)>(-)BOPD
(-) FBL1: The variables UBPP and BOPD create the so called negative (-) feedback
loop or self-governing (-) KPD1", i.e., as abbreviated:
UBPP(+)>(+)BOPD(+)>(-)UBPP
"If the number of vessel checkouts a day BOPD increases, the total value of the issued
invoices UVIR will also increase, which shows a positive (+) cause-consequence link
CCL", i.e., as abbreviated:
BOPD(+)>(+)UVIR
"If the average time of stay of vessels PVZP increases, the number of vessel checkouts a
day BOPD will be decreased, which shows a negative (-) CCL, i.e., as abbreviated:
PVZP(+)>(-)BOPD
"If the average realised revenue per vessel per day POPPD increases, the value of the
issued invoices a day VIRD will also increase, which shows a positive (+) FBL, i.e., as
abbreviated:
POPPD(+)>(+)VIRD
"If the value of the issued invoices a day VIRD increases, the total value of the issued
invoices UVIR will also increase, which shows a positive (+) cause-consequence link
CCL", i.e., as abbreviated:
VIRD(+)>(4)UVIR
"If the total value of the issued invoices UVIR increases, the value of the collected debts
a day VNPD will also increase, which shows a positive (+) cause-consequence link
CCL".
UVIR(+)>(+)VNPD
"If the average time of collecting debts PVNP increases, the value of collected debts a
day VNPD will decrease, which shows a negative (-) cause-consequence link CCL".
PVNP(+)>(-)VNPD
"If the value of collected debts a day VNPD increases, the total value of issued invoices
UVIR will decrease, which shows the negative (-) CCL."
VNPD(+)>(-)UVIR
(-) FBL2: The variables VNPD and UVIR create the so called negative (-) feedback
loop, or self-governing (-) FBL2",
UVIR(4)> VNPD(+)9(-JUVIR
"If the value of collected debts a day VNPD increases, then the total realised revenues a
day UOPD will also increase, which shows a positive (+) cause-consequence link
CCL".
VNPD(+)>(+)UOPD
"If the total realised revenues a day UOPD increase, the INCOME will also increase,
which shows a positive (+) cause-consequence link CCL".
UOPD(+)>(+)INCOME
"If the value of collected debts a day VNPD increases, the value of paid assets to the
transfer account a day VUSZRD will also increase which shows a positive (+) cause-
consequence link CCL".
VNPD(+)>(+)VUSZDR
"If the value of paid assets to transfer account a day VUSZRD increases, the state of
the total assets in the transfer account SUSZR, will also increase, which shows a
positive (+)cause-consequence link CCL".
VUSZRD(+)>(+)SUSZR
"If the state of the total assets in the transfer account SUSZR, increases, then the value
of the disbursements from the transfer account a day VISZRD will also increase, which
shows a positive (+) cause-consequence link CCL".
SUSZR(+)>(4)VISZRD
"If the value of disbursements from the transfer account a day VISZRD increases, then
the state of the total assets in the transfer account SUSZR will decrease, which shows a
negative (-)cause-consequence link CCL".
VISZRD(+)>(-)SUSZRD
(-) KPD3: The variables SUSZR and VISZRD create the so called negative (-) feedback
loop, or self-governing (-) FBL3".
SUSZRD(+)> VISZRD(+)>(-)SUSZRD
"If the number of registered vessels a day BPPD increases, then the total operating
costs UTP will also increase, which shows a positive (+)cause-consequence link CCL".
BPPD(+)>(+)UTP
"If the variable average costs per vessel per day PTPD increases, then the total
operating costs UTP will also increase, which shows a positive (+)cause-consequence
link CCL".
BPPD(+)>(+)UTP
"If the total operating costs UTP increase, then the value of the liabilities a day
VDOPD will also increase, which shows a positive (+) cause-consequence link CCL".
UTP(4)>(4)VDOPD
"If the value of liabilities a day VDOPD increases, then the INCOME will decrease,
which shows a negative (-) cause-consequence link CCL".
VDOPD(+)>(-)INCOME
"If the value of liabilities a day VDOPD increases, then the value of the total debts
VUD will also increase, which shows a positive (+) cause-consequence link CCL".
VDOPD(+)3(4)VUD
"If the value of the total debts VUD increases, then the value of debt settlement a day
VIOPD will also increase, which shows a positive (+) cause-consequence link CCL".
VUD(+)>(+)VIOPD
"If the average time of debt settlement PVIOP increases, then the value of debt
settlement a day VIOPD will decrease, which shows a negative (-) cause-consequence
link CCL".
PVIOP(+)(-)VIOPD
"If the value of debt settlement a day VIOPD increases, the value of total debts VUD
will decrease, which shows a negative (-) cause-consequence link CCL".
VIOPD(+)>(-)VUD
(-) KPD4: The variables VUD and VIOPD create the so called negative (-) feedback
loop, or self-governing FBL4".
VUD(+)> VIOPD(+)>(-)VUD
"If the value of debt settlement a day VIOPD increases, the value of paid assets from the
transfer account a day VISZRD will also increase, which shows a positive (+) cause-
consequence link CCL".
VIOPD(+)>(+)VISZRD
"If the value of the investment in new capacities VINK increases, then the value of paid
assets from the transfer account a day VISZRD will also increase:
R VISZRD.KL=VIOPD.KL+VINK.KL
where:
VISZDR - the value of paid assets from the transfer account a day;
VIOPD -— the value of debt settlement a day BIOP — the rate of debt settlement
VINK - the value of investment into new capacities
The value of investment into new capacities — VINK will be determined:
R VINK.KL=DELAY3(PULSE(500000, 1,366, 1000)+PULSE(100,1,380,1000)+*
PULSE(1000000,1,390,1000),180)
where
DELAY3 is the name of MACRO function DYNAMO programme package and it is the
exponential delay of III class of investment (investment into new capacities) which
average construction period is 180 days.
Remark: The first item of the equation VINK.KL (500,000 EUR) denotes the total
investment of the marina during the construction period of 180 days (its own financial
means and bank loan as the outer finances); the other item of the equation denotes the
possible investment in total of 2 million US$ of the foreign partner investors, and it will
not have a negative effect (increase of costs) to financial state of the transfer account,
but the new investor will ensure the return on investment by an agreed share in the
profit. The investment effect will reflect for the first time in the realisation of the
increased revenues in the following season.
Positive effects of the investment will reflect in the variable KPNI coefficient of the
increase of new investments:
A KPNLK=TABHL(KPNIT, VINK.KL,500,2500,500)
T KPNIT=1,1.2,1.5,1.8,1.9
The variable KPNI denotes an increase of revenues in the future period (after
completing the investment and the beginning of work of the completed new capacities).
The symbol KPNIT denotes the tabular amplitudes of a relative factor of increase of
new investments to the growth of total revenues, costs, average costs per vessel and the
generator of vessel arriving.
The state of the total assets in the transfer account — SUSZR, will be determined:
L SUSZR.K=SUSZR.J+DT(VUSZRD.JK-VISZRD.JK),
where
VUSZRD - the value of the paid assets to the transfer account a day
VISZRD — the value of the paid assets from the transfer account a day
Remark: If the state of the total assets in the transfer account is higher than zero, then
the marina is solvent, and if it is zero or less than zero, then it is financially insolvent
and in order to be capable to pay its liabilities it has to ensure cash assets on the basis of
loans (mid-term or short term loans).
1.2. Structural model of the LNT business system
In accordance to the completed mental and verbal simulation model of investing
into sports and other objects in the LNT business system, it is possible to determine the
system dynamics simulation model of LNT:
POPPD
average realised
revenue per
vessel a day
vessel arial ~“UBPP
generator total number of registered
vIRD
the value of
vessels
() FBL1
BOPD issued invoices
BPPD a: a day
susie af vesea checkouts a day
registrations a day
average time of
vuszRD + the stay of the
value of paid vessels +
assets to the uvIR
total value of issued
transfer account a t 4
invoices a day
day ure
total operating
costs =_—
average costs
SUSZR + per vessel a day
total assets on the +
transfer account a ‘DOPD
the value of labilties a
day
NPD +
() FBL3 the value of
collected debts a q_—
d
the wee :. total 2h
viszRD liabilities
the value of the paid NOB:
assets from a transfer Need
accounta day average age tne of
+ ©) FBL4 ape aaay collecting debts
viopD
¢) FBL2
the value of paid INCOME ¥ 4.
liabilities a day
~ Pviop
average time of
paid liabilities
Figure 1. Structural model of the LNT business system
2. Conclusions
On the basis of the system dynamics research of the performance of the complex
business system LNT, with the aid of a fast digital computer on which the performance
simulation was done, it is possible to bring forward a number of relevant conclusions:
1. A direct application of system dynamics simulation complex models in the field of
scientific research of performance of nonlinear management systems has full
rationalization, because it ensures to the model constructor an extremely suitable
software medium which may be determined as intelligent models of the second
generation, if the first generation refers to present expert systems.
2. System dynamics and its efficiency of intelligent modelling of a business system
may be considered as a logic order of development of intelligent systems in the
field of applying research of dynamics of cybernetic business systems.
3. System dynamics uses special methodology and special software packages, the
most outstanding being: DY NAMO; Powersim, Stella, Vensim, and Think.
4. System dynamics is especially convenient for the study of performance dynamics
of business systems in which a great number of non-linear retroactive circles
operate, or for systems where at operating the system the use of manager’s
intuition alone fails.
5. A special importance and quality of applying system dynamics in education,
training, designing and exploitation of complex business management systems
may be considered in acquiring new knowledge which classic management
methods cannot offer.
On the basis of the above presentation, the authors of this paper recommend the
implementation of system dynamics methodology tool into all fields of human activities
with the aim of understanding various complex systems, in which the experiment cannot
be performed in real life without jeopardizing their existence, growth and development.
The possible scientific contribution of this paper is primarily in authorised determining
of general multiple simulation models which allow for acquiring new knowledge about
dynamic performance of real nautical and tourist business systems, but also sports
organisation systems. Also, in order to follow successfully the development of modern
sports industry, the students of kinesiology need knowledge and skills in various areas,
especially economy, management and marketing. By using the proposed tools and
system dynamics simulation methodology, the students will acquire knew knowledge
about performance dynamics of complex organisation systems in the field of tourism,
sports and recreation.
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