40 2016, XIX, 3
Ekonomie
40 DOI: 10.15240/ ul/001/2016-3-004
In oduc ion
In bo h classical economics (Adam Smi h, Da id
Rica do) and neoclassical economics (e.g. John
Hicks, Léon Wal as, William S anley Je ons,
Geo ge S igle , Ca l Menge , John Ba es Cla k),
he e a e h ee p ima y ac o s o p oduc ion:
land, labo , capi al. Land means a esou ce
c ea ing an addi ional u ili y and is no only
a na u al esou ce o be ound abo e o below
he soil. The e canno be a dis ega d o he
decision making p ocess conce ning loca ion
and in es men . The p oblem is mani es no
only in he indi idual solo in es men bu also
in he po olio dispe sion o in es men in an
en i e egion.
The a icle ocuses on he a gumen s
suppo ing he hesis (implica ion): he decision
ule c ea es he decision space and his space
(mean as an occasion o manoeu e) i
e alua ed, p o ides he u ili y. Disc epancies in
he assessmen o de elopmen oppo uni ies
in a egional o u ban a ea a e well-known
ma e s o discussion and ha e se ious
long e m economic consequences. Le us
conside he abo e s a emen as a goal-se ing
endea ou . The s a emen o mula es he
speci i c and measu able in en ions, and he
in en o he au ho s is o que y whe he goals
a e a ainable, ealis ic and ime-bound. Mo e
gene ally i desc ibe a si ua ion ca ying he
implica ion
Economic decision Rule c ea e Economic
decision Space e alua e Economic decision
U ili y (1)
o adjus ed o elimina e he edundan wo ds
Rule c ea e Space e alua e U ili y (1a)
I will no be amiss o look b ie l y o
he causes o gaps in heo y and/o in any
applica ion o ac ual p ac ice. The ac ual gaps
may be pe cei ed in: a) a good e alua ion o
solo in es men and b) he unsa is ac o ily
calcula ed impac o in es men in an a ea
( egion). The e alua ion me hodology su e s
om a) he absence o p obabilis ic causali y,
b) weak espec o he dynamics in ime,
c) dis ega d o he in l uence o decision-making
ules, and d) ma ginaliza ion o he e ec o
ex e nali ies ( he dynamic o chain e ec s in
he a ea, and he economic impac o loca ion
add essed in sub-sec ion 2.2).
Mo i a ion: The main eason o w i ing his
a icle was he i ndings isualized in Fig. 1. The
di e en ia ed de elopmen is p esen ed o
Cen al and Eas e n Eu ope. The i ndings and
da a illus a e an exis ing si ua ion elabo a ed
by he Wo ld Bank. The a icle sea ches o
ese es in loca ing in es men s and any
po en ial o inc ease p oduc i i y o he egion
(A is, Cu an, & Sensie , 2010).
Implemen a ion: The de elopmen o ci ies
can be e i cien , bu i happens no always by
design. Fixa ion on he dis an a ge o ision
has mos ly a highe p io i y han dynamics and
o ien a ion in he p ocess o achie ing long-
e m goals. The inspi a ions behind, o a he
some indica o s o , he gene al p oblem is
add essed by (Mandelb o , 1991) and o he
au ho s and an ex ensi e o e iew is p esen ed
by (Wol am, 2002).
Applica ion: An economic de elopmen
including de elopmen o se lemen s, indus ies,
egions, e c. depends on he p esence o he
necessa y in as uc u e as a condi ion o
in es men ; bu i is no a su i cien condi ion.
Acco ding o adical changes sough in
he EU (Eu opean Commission, 2013), he
ollowing mus happen: g ea e accessibili y and
eadiness o in eg a ion o da a om he h ee
p incipal sou ces (public, p i a e and socie al)
aking ma e s beyond he Di ec i e 2013/37/EU.
LONG-TERM INFRASTRUCTURE
INVESTMENT: A NEW APPROACH TO THE
ECONOMICS OF LOCATION
Pe Dlask, Václa Be an
EM_3_2016.indd 40EM_3_2016.indd 40 8.9.2016 14:11:018.9.2016 14:11:01
41
3, XIX, 2016
Economics
41
1. Li e a u e – Synopsis
and Commen s
Some au ho s sum up he p oblem men ioned
in (Eu opean Commission, 2013) om di e en
angles, and alk abou he issue in e ms o
dynamics, isks, unce ain ies, dimensions
(1D, 2D,…, e c.). The ques ion o dynamics
in he economy was made e iden al eady
in (Fo es e , Indus ial Dynamics, 1961)
and also la e (1969) in U ban Dynamics
(Fo es e , 1969). Compa ison and e alua ion
o consequences in ime is he main sou ce
o he disc epancy in any gi en si ua ion. The
heo y o economics and managemen (E&M)
cu en ly add esses he desi e o u he
de elopmen in a ious ways. We ha e o
men ion a leas Econophysics, and he ela ed
conce ns add essed by (Gallega i, Keen, Lux, &
O me od, 2006) o sus ainable de elopmen in
(S e n, 2006). The main p oblems o di i cul ies
a e ound in he ollowing: dynamics o ime,
a ea s uc u e, causal in e ac ion o he ac ion,
ac ion isk, unce ain y, p udence, e hical
s anda ds, e c. In es men s and he ac i e
p ocess o in es ing a e widely ecognized
as a ool o economic de elopmen (A is,
Cu an, & Sensie , 2010), (Be an & Dlask,
2005; 2011). The ques ion poses enqui y
a ound he espec i e condi ions o necessi y
and su i ciency o any economic de elopmen .
The a icle expe imen s wi h he hypo hesis
ha ins ead o demanding gene ic models,
he decision-making ules should c ea e
he backbone s uc u e o mos economic
and manage ial p oblems, see o example
(Mi so a, Shus e , & Wang, 2011), (Pa ke ,
2007), (P une i, Muzy, & Innocen i, 2014) and
(S anilo & Ba y, 2011). I is necessa y o poin
ou he limi a ions o any new solu ions.
Limi 1: A lo o di e en ypes o knowledge
and in o ma ion may o e shadow a hope ul
endea o , o example in (Malecki, 2012),
ega ding ac i i ies abou an u ban e o i ing
in (Dixon, Eames, Hun , & Lannon, 2014).
Mi o & Sil e s desc ibe his po en ial o
o e shadowing as P obabilis ic causali y
in (Mi o & Sil e s, 2013). The idea o he
„mul i- i be “ p obabilis ic causali y is inspi ing.
The p obabilis ic concep ion o causali y is
an impo an and in e es ing p oblem. I is
no ewo hy ha in mos o he gene ic models
he use s gene ally deal only wi h a segmen o
he in l uencing pa ame e s. Such an app oach
does no espec he pa ame e ola ili y o
decision making (DM). Le us gi e a b ie
example in explana ion.
Fo in es men aims in (S imson, S ough,
& B ian, 2006) s a es i is possible o cons uc
a causali y ma ix (Mi o & Sil e s, 2013),
and he ac i i ies In as uc u e and No -
In as uc u e play he ole o he ini ia ing
condi ion while In es men and No -In es men
play he ole o a esponding ac i i y. The ma ix
is p esen ed in Tab.1.
The causal in e ac ions aij in he ma ix
in Tab. 1 shows possible ou comes o he
implica ion In as uc u eIn es men . Ano he
app oach p esen s p ocess/p oduc and
quali a i e/quan i a i e aspec s as p esen ed
in (Lenne & Robe , 2010). I is undeniable
ha he in as uc u e plays he ole o
a necessa y condi ion and he in es men he
condi ion o su i ciency. The ou come a11 in
Tab. 1 is commonly conside ed as app op ia e
o ac ion pe mission. Howe e he decision
make dese es mo e sensi i e and speci i c
in o ma ion abou opic “clima e”: as a12, a21, a22.
Mos decision-making me hods (Ne p esen
In es men Condi ions (e i ciency)
In es men e i cien In es men ine i cien
Explo ing o
De elopmen
P econdi ions
In as ac u e
exis s (+)
a11: E i cien ou come
exis s + a12: Nega i e ou come -
In as ac u e
does no exis (-) a21: Nega i e ou come - a22: Posi i e ou come +
Sou ce: own based on (Mi o & Sil e s, 2013)
Tab. 1: Regional de elopmen and in es men as a causal in e ac ion (in an a ea ω)
EM_3_2016.indd 41EM_3_2016.indd 41 8.9.2016 14:11:018.9.2016 14:11:01
42 2016, XIX, 3
Ekonomie
42
alue NPV, In e nal a e o e u n IRR, Pay-back
pe iod and o he s) a e based on a de e minis ic
causal nexus, which has only a limi ed alidi y
in he eal wo ld.
Limi 2: The endency o ackle only one single
si ua ion a11 has in many si ua ions a limi ed
alidi y as well. The egional de elopmen (RD,
se lemen s, ci ies, egions) is subjec o some
kind o causali ies in 3D space wi h he segmen ed
a eas X, Y, Z and hei bene i s o e i ciency and
u ili y as hei ou h axis. The wo ding o he
dimension is aken om ISO 16739:2013 whe e
he e is p esen ed an ex ension o 4D-image
( ime) and 5D-image (cos s).
The analysis o a landscape and i s ex u e,
along wi h spa ial analyses a e he disciplines
ha open mo e insigh s in o he beha io o
egions (Tao, Tang, & S obl, 2012). Many
au ho s a e looking o an answe in simula ion
and in a spa ial s uc u es model as suppo ing
asks.
Limi 3: De elopmen is a dynamic p ocess
in ime (A is, Cu an, & Sensie , 2010), (Be an
& Dlask, 2005; 2007; 2011), and in ac uali y an
u ban o in es men a angemen akes place
in space. The ele ance o he opic u ban
de elopmen and cellula me hodology and i s
apid eme gence in he las 15 yea s is e iden
om he da a shown in da abase ISI. The
published i ems abou “u ban de elopmen and
cellula me hodology” (pe yea ) inc eases om
nea ly ze o be o e yea 2000 o mo e han 700
in 2013/2014.
Socie y and indeed almos e e y indi idual
o ci izen equi es ha he u ban a angemen ,
he egional in as uc u e and i s economy can
p o ide high bene i s in ime and space.
Limi 4: Dys unc ional p ac ice is oo ed
in de ec i e heo y. Decision ules a e
unde es ima ed in managemen p ac ice.
A ule shows he way – di ec ion – o he
cons uc ion o oads, ailways, wa e ways,
public buildings, esiden ial buildings, and hei
a chi ec u al a angemen ; ules exp ess he
use o a public o p i a e space – and his has
been so o cen u ies. They we e de eloped by
means o a consensus in he ules o DM o he
c ea ion o he a angemen o a whole space
de elopmen , as well as he economic and
cul u al backg ound o i ( he echnical-economic
memo y o he gi en space). A o maliza ion o
DM ules dec eases app ehension ega ding
Fig. 1: Economic ac i i y (GDP/km2) in Cen al Eu ope – an une en opog aphy
Sou ce: Wo ld Bank GIS Labo a o y
EM_3_2016.indd 42EM_3_2016.indd 42 8.9.2016 14:11:018.9.2016 14:11:01
43
3, XIX, 2016
Economics
43
con l ic s be ween playe s and in 3D is exp essed
in he ime, space and economy o he decision
p oposals. The p esence o playe s in he igh
ime a he igh place is desi able. P ope
unc ioning is o be ensu ed, o hose who
belie e in he au ho ship o an in isible hand
(Smi h, 2013), h ough he implemen a ion o
sel - egula ion. On he o he hand, he e exis s
a cul u e o decision ules and hei e l ec ion
on he planning: - e i o ial, -spa ial and o he
dimensions (Syko a, Balchin, & Bull, 1999).
The simula ion o a long- e m de elopmen
has a p edominan ly sophis ica ed suppo in
p o essional simula ion p oduc s. Me onamica
is one o hem, which has buil -in alloca ion
algo i hms, ha calcula e he ansi ion o cells
( om one land use o ano he ) on he basis o
sophis ica ed ules (accessibili y, zoning,...)
(S anilo & Ba y, 2011) o (Webe , 1929).
The pu pose o ien ed so wa e is in he
main sophis ica ed and based on complica ed
gene ic o mulas. This pape ies o pa e he
way o a ule o ien ed app oach, based on he
gene ally a ailable so wa e o applica ions
di ec ly c ea ed by he use .
Ra ionale/app oach o p oblem s udy:
in es men loca ion
The DM ules o m he economic ba ie s and
ames, as well as he cha ac e o he egional
and u ban o echnical decisions space (Be an
& Dlask, 2005), (Ba y, 2005), and (Webe ,
1929). The decision ules c ea e as well as
es ablish p obably one o he la ges long- e m
egula ions in a socie y aken as a whole. We
unde s and he las sen ence as a s a emen
ha c ea es bene i s o a long- e m concep ion.
Paymen o he economic de i ciencies which
esul om he long- e m undamen als, ac s
o he whole li e ime pe iod o cons uc ion
wo ks; o example, a acing o oads, s ee s,
ailways, channels, housing s uc u es e c.
The gi en concep s, ac s and hei limi s a e
mos ly isible h ough cen u ies; see Fig. 2.
The main subjec o in e es o his pape is
a DM mechanism and i s impac on he egional
economy. The p oblem is sol ed om ano he
pe spec i e – op imiza ion in gene al, see in
(Fo , Ple ný, Š eco á, & Vacík, 2013).
A de elopmen is limi ed no only by he
li e cycle (LC) o cons uc ion subs ances,
bu also by a long li e cycle (LLC) o layou s,
in as uc u e e c. Among LLC cons uc ion
objec s a e he anspo in as uc u e,
Fig. 2:
The LLC g ow h o se lemen
in he las cen u ies; (1764-68),
(1836-1852), (1837)
Sou ce: A chi es o Town Nepomuk
EM_3_2016.indd 43EM_3_2016.indd 43 8.9.2016 14:11:028.9.2016 14:11:02
44 2016, XIX, 3
Ekonomie
44
enginee ing in as uc u e, wa e dis ibu ion
sys em and he usage o adjoining unc ional
a eas. This a icle aims o de e mine he
po en ial bene i s – hus he u ili y – o he use
o he e i o y (a ea) ω.
2. Me hodology: Simula ion Model
and Vi ual Complexi y
The c i e ion o an economic de elopmen
has o in ol e measu ing he achie ed u ili y in
e ms o ela ion (1) and is desc ibed in de ail
in chap e 2. Decision ules. The e alua ion
needs an agg ega e p ospec (p ognosis) o
he u ili y based on pas in es men s in e ms o
su i ciency. The success o in es men se s ou
a dema ca ion line o knowledge, in as uc u e,
indus ial p oduc ion, i nal consump ion and
housing, a b oade iew being gi en by
(Dambo ský, Wokoun, & K ejčo á, 2013).
On he one side, in e e ence in he gene al
cycle
Consume  In es men 
De elopmen Consume (2)
as a basic dependence is exp essed in a ious
o ms in classical mac oeconomics; i binds
he in es men I wi h he change in p oduc ion
ou pu Y in ime, w i en as
I = dY/d (2a)
whe e 0≤ ≤1, and shows he e ec i eness o
he p oposed in es men , dY/d is change o
p oduc ion ou pu o ime uni .
On he o he side, (2) o (2a) doesn’
sol e he p oblem o he e i o ial dis ibu ion
and he impac o decision-making ules. The
choice and he sui abili y o he in es men
loca ion is b ough in o play p edominan ly
only h ough easibili y s udies. He e we
speak abou he pa ial Isolo in es men and
isola ed mic o-decisions. The u he desc ibed
simula ion explains he po en ial bene i s o
he complexes: egions, a eas. The s udy ies
o explain, he ex en o which (as % o u ili y)
he i nal e ec migh imp o e he e i ciency o
in es men .
The au ho s o he pape a gue ha he DM
ules implemen ed o m he pa e n o he u u e
de elopmen . A DM ule di ec s he de elopmen
o in as uc u e, buildings and hei po en ial
economic des ina ions. The ag icul u al pa e n
o he a ea in Fig. 3 is changed o a mo e
economically in ensi e exploi a ion. Decision
ules o ches a e he e alua ion. Mo e abou
decision ules is p esen ed in subsec ion o
chap e 2.2 and in o mulas (10), (11).
2.1 E alua ion o Economic Po en ial −
he In es men Tools and Indica o s
The egional de elopmen is ecognized in he
s a ing posi ion mos ly as an ag icul u al land
wi hou ini ial in es men . Such an example
p esen s a u ili y, p ea anged in Fig. 2 and in
segmen s ωij (see Fig. 3) weigh ed only wi h
he wea he ola ili y and he ha es incomes.
We assume he loca ion as a po en ial
own expansion a ea, amed in Fig. 2. The
p oceeds o u ili ies uij in he pa ial ag icul u al
segmen s a y be ween 1 and 5% o yields pe
yea .
La e , he ini ial in es men (a ime = 1)
in he cen al loca ed segmen is w i en as
I =1(10,10) = 1 and will ac as an ini ial sp eading
elemen o he de elopmen . The in es men in
a egion (a ea) is i xed in ime and localiza ion,
I (i,j). The cumula ed yields (u ili y) o a pe iod
 s a ,…, ac ual,…, ho izon is gi en as a agg ega ion
(sum) o ma ices U (ω) =
 

σ࢛௧(࣓)
௧ ௔௖௧௨௔௟
௧ ௦௧௔௥௧ ,
whe e ω is he ange o a ea (le us say
o example, he e i o ial unc ions, he
adminis a i e de i ni ion e c.), and is an ac ual
obse e ‘s ime posi ion. The single elemen ωij
con ains he alue o simula ed u ili y uij o one
pe iod. The segmen loca ions a e speci i ed wi h
i = 1, 2, …, m and j = 1, 2, …, n. To compa e he
di e en ime s ages, a numbe o indica o s a e
a ailable (e.g. di e ence, dis ance, di e gence,
e c.).
The di e ence o he s ages and -1 is
gi en in gene al as a ma ix o u ili y di e ences;
indica ed changes o ∆ , gi en as a dispa i y
ma ix o he ac ual and pas s a e
∆u (ω) = u (ω) – u -1(ω) (3)
whe e da a o ma ices u (ω), = 1, 2,…, ac ual
is he con i med eali y o = s a ,… ac ual is an
accep ed simula ion on he basis o ela ions
(10) and (11), isualized in Fig. 3, Fig. A1 o
Fig. 7. An example o ∆u (ω), = 1, 2,… is gi en
in Fig. 8. The ma ices ∆u (ω) ob ained in (3) a e
signi i can as an indica ion o he a ac i eness
o he po en ial ( +1) in es men .
The p edic ion o u ili y changes ∆u +1(ω),
∆u +2(ω),… (whe e is in e p e ed as ac ual) can
be de i ed by simula ions, expe judgmen s,
EM_3_2016.indd 44EM_3_2016.indd 44 8.9.2016 14:11:028.9.2016 14:11:02

45
3, XIX, 2016
Economics
45
s a is ical analysis. The ma ices ∆u( +x)(ω) allow
calcula ion o u he de elopmen s a es as
U +1(ω) = u (ω) + ∆u +1(ω), (4)
U +2(ω) = U +1(ω) + ∆u +2(ω), e c. (5)
whe e he ma ix U (ω) is he sum o u ili ies o
pe iod  s a , +1, o e en le us say a p ognosis
ou look om a las obse e s a e
ac ual as
a s a ing poin o he p ognosis. The ma ix
u1(ω) illus a es as ac ual he “no h-wes ” co ne
o Fig. 7 and ma ix ∆u +1(ω) illus a es he
“no h-wes ” co ne o Fig. 8.
The ma ix U (ω) mul iplied by a ec o o ow
ele ancies ( o example in e ms o he u ban,
economic, social in es men and de elopmen )
w  = [w1
 , w2
 ,…,wk
 ,…,wn
 ] whe e 0 wk
 1 and
∑k=1
n
wk
 = 1 and by a ec o o column ele ancies
w| [w1
|, w2
|,…, wl
|,…,wn
| ]T, whe e 0 wl
| 1 and
∑l=1
m
w
l
| = 1 iden i i es he main de elopmen
ends. The ma ices in (6) and (7) se e
as de elopmen (change) indica o s o he
s a es , w i en as ow (1n) ma ices U (ω)
o columns ( ead o example as a cumula ed
p o i le o wes -eas de elopmen )
U
 (ω) = w  U (ω) (6)
and as columns ma ix (n1) o ows ( ead
o example as a p o i le o no h-sou h
de elopmen )
U
|(ω) = U (ω) w| (7)
whe e w  is he ow ma ix o u ili y ele ancies
o columns o ma ix U (ω),
U
 (ω) is he u ili y ow ma ix o sums o
ime phases = 1, 2, …, ac ual; le us say he
wes -eas u ili y p o i les o a ea ω up o he
ac ual ime ho izon, example gi en in Fig. 4b,
w| is column ma ix o u ili y ele ancies o
ows j = 1,…, m o ma ix U (ω),
U
|(ω) is he u ili y column ma ix o weigh ed
sums; in ou example he no h-sou h u ili y
p o i le o a ea ω up o ac ual, example Fig. 4a.
The indica o o o al yield o he in es iga ed
a ea ω can be gi en e.g. as ma ix
U
o(ω) = w  U (ω) w| (8)
Mo e examples used la e in his a icle a e
p esen ed in Tab. 2.
The long- e m economic p o i le is gi en by
he simula ion se ies U (ω) and in es men I
placemen o all whe e end is he used
economic ho izon h. The u ili y o in es men
(Be an & Dlask, 2007) is no only a ques ion
o he e ec i eness o sales, demand o o e s,
bu also a ques ion o he simula ion inpu s as
a) loca ion,
b) he ange o in es men ,
c) economic li e cycle o in es men ,
d) eliabili y ( isk) o economic ac i i ies in
loca ion,
e) po en ial g ow h ac o in loca ion, e c.
The abo e men ioned poin s should be
in e p e ed wi h espec o he p obabilis ic
causali y in (Mi o & Sil e s, 2013), men ioned
in he Tab. 1 o ou chap e In oduc ion. The
u ili ies o an a ea ω is no only a sequence o
cumula ed u ili y ma ices u1(ω), u2(ω), … bu
also he sophis ica ed calcula ion p ocess o
he pa ial combina o y pa ame e s a) o e),
implemen ed in a ime sequence o simula ions
( o be ead as delays o u u e expec a ions)
U(I,ω)= Sim [u1(I, ω), u2(I, ω),…. ,
…. , uh(I, ω)] o = 1, …, h (9)
whe e U(I, ω) is a ime sequence o ma ices o
u ili ies o he a ea ω, speci i ed by in es men
condi ions I in uni o m pe iods = 1, …, h,
I is he in es men condi ioned by a),… ,e),
e c.,
u (I, ω) is he u ili y simula ion o he ime
pe iod .
The economic po en ial es ablishes he base
o he compa ison o a ian s and p e e ences
o di e en in es men s a egies. The long e m
e ec is a signi i can DM indica o .
The compa ison o a ian s may ha e
a a ied cons uc ion o indica o s. The
mos a o dable a e indica o s p esen ed in
ela ionship (3), (6) and (7).
2.2 Decision Making Rules
The DM c i e ia a e mos ly he ules o g ow h,
p o iding a u ili y ha oscilla es wi h espec o
he limi ing local condi ions, such as:
a) e enues, which a e pa ially uns able and
con o ming o he ex e nal condi ions (supply,
demand, in l uence o ex e nali ies ou side he
e i o y o in e es , ene gy p ices, ecological
egula ion, ax egula ions, cha ges e c.),
b) e ec o in es men ime delay, i say he
in es men e enues a e delayed o a ew
yea s,
EM_3_2016.indd 45EM_3_2016.indd 45 8.9.2016 14:11:038.9.2016 14:11:03
46 2016, XIX, 3
Ekonomie
46
c) e ec o e enue expands om an a ea
elemen ij o Moo neighbo hood elemen s
(eigh ), su ounding he calcula ed cell:
pic og am as ۞, labeled la e as M,
d) o al e ec o e longe ime is dependen
on bo h ini ial in es men , and he le el o
andomness o he e ec s,
e) all e ec s (u ili y) a e cumula ed,
) he decision making ule, applied o he ime
pe iod , in l uences a ea  in ime pe iod
+1.
The au ho s o he pape a gue ha he
DM ules implemen ed, o m he pa e n o
he u u e de elopmen . A DM- ule di ec s
he de elopmen o in as uc u e and hei
po en ial economics. The ag icul u al pa e n
o he a ea in Fig. 3 is changed o a mo e
economically in ensi e exploi a ion. Decision
ules o ches a e he e alua ion.
The e alua ions enable a managemen
decision abou possible: a) s a e, b) changes,
c) accele a ion, d) ola ili y, e c. The example
in Fig. 3 and in subsec ion chap e 2.3 p esen s
he e alua ion o a localiza ion o he s uc u al
in es men s. The o hcoming pe iods (yea s)
a e e alua ed ( ead ha able p ocesso
elemen s x a e e alua ed) by a decision ule
gi en o ins ance as
IF (segmen x shows in p e ious ime
pe iod g ow h, ha i is highe han he
gi en limi )
(10)
hen yes  inc ease in he ac ual
ime pe iod by α %;
no  IF( he su ounding o
segmen M was g owing
in he p e ious pe iod)
hen yes  andom inc ease
by a high (op imis ic)
assessmen ;
no  low andom
inc ease assessmen )).
The ela ion (10) can be w i en in he o m
close o he able p ocesso en y as
IF (u -1(x) ≥ I • index o equi ed g ow h
hen u (x)=u -1(x) • index o equi ed
g ow h • R1 (11)
o else IF (su ounding u -1(x
M)≥I)
hen u -1(x
M) • R2;
o else u -1(x
M) • R3)
whe e R is he andom-numbe gene a o
wi h equi ed p obabili y densi y dis ibu ions
R1, R2, R3,
I is ini ial in es men implemen ed in o a ea,
x is pa icula elemen x o a ea ,
Fig. 3: Ag icul u al a ea, andom condi ioned u ili y simula ions: esul ing u ili y ange
is min 79.8 o max 82.7 uni s
Sou ce: own
EM_3_2016.indd 46EM_3_2016.indd 46 8.9.2016 14:11:038.9.2016 14:11:03
47
3, XIX, 2016
Economics
47
x
M is Moo e neighbo hood o he elemen
x; su ounded by 8 elemen s,
index o g ow h is calcula ed as eα whe e α
is an expec ed g ow h ac o .
To simpli y in e p e a ion, we assume ha
he in as uc u e is s a ing on ag icul u al
land (wi hou e i aliza ion, land eclama ion,
en i onmen al es o a ion, e c.). Any in es men
c ea es he e ec s in , acco ding o he ules,
men ioned be o e in a) o e); he e ec s a e
dispe sed and calcula ed acco ding o (10) and
(11).
2.3 Me a-Analysis
The desc ibed app oach can be in e p e ed and
gene alized o a la ge ange o de elopmen
si ua ions, and he p ecision and accu acy o
he calcula ion can be imp o ed i a dense
g id is used. Mo e ealis ic in o ma ion may
inc ease he de ec ed in e p e a ion e ec s.
Fo he p o ec ion o p ope y igh s in he
mos p ac ical examples, we use u he o ou
illus a ion a me ada a simula ion, based on he
his o ical locali y speci i ed in Fig. 2.
2.4 Loca ion o In es men –
Compa ison
The loca ion o in es men I in a ea ω is an
impo an economic s ep ha c ea es a u ili y
u (ωij) o he pa icula in es men in pe iod .
A easibili y s udy o an indi idual solo in es men ,
wi hou espec o he sp ead ( ead as impac )
on he ω, does no enable desc ip ion o he long
e m u ili y e ec s. Mo e abou he e alua ion
and localiza ion o an a ea is w i en in (Zang,
2012; Žižka, 2010). The ca ego y includes
he loca ion indica o s, quo ien s, shi -sha e
analysis, he Gini coe i cien o localiza ion, he
Ellison, Glaese agglome a ion index e c. The
economic impac o he loca ion will be isible
i we change he in es men loca ion; he ini ial
in es men loca ions a e in cen e “A” and hen
in he si e bounda y “B”, and in he sou h-eas
co ne o he a ea desc ibed as “C”, see Fig. 3.
Expe imen al esul s as he sum o u ili ies is
w i en as U (ω), and a e p esen ed in Tab. 2.
The simula ed sum o u ili ies U (ω) o
loca ion o I in ω-a eas A, B, C o he in ended
in es men in Fig. 2, illus a e he expec ed
bene i s. The anges o min and max di e s.
The di e ences be ween he max and he min
u ili y U =10(ω) a e high. In p ac ical applica ions
he echnical condi ions a e sophis ica ed, and
he si ua ion speaks e en mo e s ongly o he
use o he ad anced quan i i ca ion me hods.
These o e he applica ion o he op imiza ion
echniques in (Fo , Ple ný, Š eco á, & Vacík,
2013) which “…aims o speci y he p oblem
o op imiza ion o de elopmen o a p ojec
po olio unde isk (op imal alloca ion o sca ce
esou ces)”. In Appendix he e is a isualized
si ua ion wi h some limi s o g ow h. The
es ic ions c ea e in es men limi s ( i e ,
ansi - oad, eco-co ido , pa ks, and o es ) and
change he po en ial sp ead o de elopmen ,
see Appendix Fig. A1. Fo simplici y, he
op imiza ion was no applied. Howe e , he
simula ions o he u ili y pa ame e s a e he
necessa y basis o o mula ion o he objec i es
and op imiza ion unc ion.
Ac ually:
1. he e i o y de elopmen is caused by
andom a ia ions o ma ke condi ions in
a de e mined egion,
Loca ion I = 1 o a eas A, B, C min Sum
U =10 (ω)
max Sum
U =10 (ω)
Expec ed
U =10 (ω)Dispe sion σ
Cen e (10, 10) A 178.38 420.19 322.70 48.96
Eas e n bounda y (10, 19) B 207.08 426.85 306.47 44.38
Sou h Eas co ne (19, 19) C 185.10 375.12 298.03 40.90
A ea u ili y o ag icul u e D 112.61 354.98 253.18 47.89
Sou ce: own
No e: 1. Dispe sion is gi en as s anda d de ia ion
D
d
V
=ඥܧ[(ܺെ
P
)ଶ
మ], ܧ[ܺ]=
P
2. See ela ions o (Tab. 2). in (Fig. 3).
Tab. 2: Simula ion esul s: In es men I = 1 loca ed in A, o B, and C; expec ed e ec i e-
ness α = 1.05 p o ides U (ω) ≥ I wi h ola ili y 10%; o U (ω) ≤ I is ola ili y 5%
EM_3_2016.indd 47EM_3_2016.indd 47 8.9.2016 14:11:038.9.2016 14:11:03
48 2016, XIX, 3
Ekonomie
48
2. om he middle e m iew, de elopmen
in a e i o y is in l uenced by all he
u baniza ion phases om he pas ,
3. he highes de elopmen in a e i o y
(Fig. A1) doesn’ ha e o appea only in he
ini ial segmen , chosen o he in es men
(see dispe sion e ec in Fig. 4a, b),
4. shi in he segmen s wi h he highes
cus om (u ili y) e ec in he a ea change
he p opo ion acco ding o he ime o
in l uence.
The esul s and p ope ies o a eal u ban
simula ion can be desc ibed in he o m
o analysis and pa icula simula ions o
= 1, = 2, …, and can p o ide answe s o he
ques ions:
a) o wha ex en is i a ional o assume ha
he e i o ial de elopmen is unique?
b) o wha ex en is he i nal ini ia ing e ec o
he s a ing in es men unique?
c) wha a e he c i e ia expedien o
in es men in he u banized dis ic ?
Each e i o y is a singula en i y. Ques ions
in his ca ego y can be answe ed only by
a simula ion. Appendix in e p e s in Fig. A1 he
simula ed bene i s in he a ea wi h es ic ions
(limi s), and he in as uc u e in es men s
a e placed and s a om he Sou h-Eas
co ne . The simula ed a ea includes limi s,
such as a small wa e l ow o a oad. Bo h
limi s ep esen obs acles o addi ional
in es men equi emen s, b idges, and auxilia y
communica ions. The de elopmen p o i les a e
isible in Fig. 4a, and 4b as cumula i e alues
in U

=1,...,10 (ω) and U|
=1,...,10 (ω). The app oach
allows an economic compa ison o changes,
encou aging he c ea ion o new designa ed
componen s and hei limi s.
2.5 E alua ion o In es men Loca ion –
Dispe sion Model
The de elopmen a ea has i s cumula i e u ili y
U (ω) p o i le. The simula ion opens ou o be e
insigh in o po en ials o u u e de elopmen .
The economic c i e ion o Payback Pe iod
is a sho e m indica o ( o each a ecoup o
he capi al expended in an in es men , o o
each he b eak-e en poin ). In he simula ion
example as p esen ed in Fig. 4a, b he ime
uni is 5 o 10 yea s and he dimension o he
ime ho izon is abou 50 o 100 yea s. The
e alua ion is based on exp ession (6) and
(7). We assume ha he calcula ion has o be
ealized o e e y single e i o y segmen ωij.
A comme cially ocused managemen aims o
he sho - e m e ec s and paybacks. In mos
cases he use o such s a egies is p ac iced
due o he lack o in o ma ion abou he
dynamics in ime and he isk o in es men .
A mo e sophis ica ed economic unde s anding
(DM) has o espec he eali y o a long- e m
economy and he isk in ol ed in he long li e
cycle o a subs an i e in es men . The ans e
om he ex ensi ely used a eas, o example
ag icul u e seen in Fig. 3, and a e i aliza ion
owa ds he in ensi ely used ones (se ices,
indus y, housing, seen Fig. A1 cons i u e he
po en ial o egional managemen . Comme cial
in es o s end o espec in hei de elopmen
p ojec s a ela i ely sho ime ho izon (ea ly
epaymen o c edi ). A public adminis a ion
should look o e ec i eness in he ull li e-
cycle as max ULC(ω). The calcula ion ool is
app op ia e o such p oblems in simula ion.
Fig. 4a, b shows he bene i s o each
pa icula in es men loca ion and he impac on
he su ounding a ea. Vola ili y in he g ow h o
indi idual a ea segmen s is caused by na u al
elie condi ions ( i e , oad, b idges, o es ,
exis ing esiden ial de elopmen , e c.), see
Appendix Fig. A1.
The schema ic agg ega ed de elopmen ,
espec ing es ic ion on he de elopmen is
gi en in Tab. 3. In Fig. 5 he e is p esen ed
a simula ion o in es men loca ed in he cen e
o ω. The di e ences in da a a e illus a ed in
Fig. 4a and Fig. 4b, and a e e y cau iona y.
The ansac ion cos s o an ad-hoc in es men
loca ion a e o e he li e-cycle e y high
and indica e he p ice o missed economic
oppo uni ies. Fig. 6 implemen s Tab. 3 da a
in o a g aphic sequence. The p o ound
consequences o a w ong localiza ion o an
ini ial in es men a e isible a he end o he li e
cycle. They ex end in ou simula ion o many
imes he alue o he ini ial in es men .
3. Resea ch Resul s
The simula ion o an RD a ea in ol es a numbe
o si ua ions along wi h a mo e indi idual iew
connec ed wi h he pa icula p ojec , as is
men ioned abo e. An in e es ing global iew
exis s. The o al and pa ial de elopmen
e enues o disposable e i o y segmen s ωij
we e men ioned in subchap e 2.1 wi h he
exp essions gi en in (3), (4), and (5).
The indica ion o main s eams o u ili y is
indica ed by u
−(ω) and u
|
(ω) in exp essions
EM_3_2016.indd 48EM_3_2016.indd 48 8.9.2016 14:11:048.9.2016 14:11:04
55
3, XIX, 2016
Economics
55
Appendix: Figu es A1 and A2
Fig. A1: Simula ion U =10(ω) o amed a ea in Fig. 2, Ini ial In es men s a s om sou h
eas co ne (19,19). Res ic ions: eas e ical is i e , sou h ho izon al is oad.
Sou ce: own
Fig. A2: Published i ems and ci a ions ( om 1995 o Janua y 2014) o opic chain: u ban
de elopmen and cellula me hodology
Sou ce: own based on Da abase ISI
EM_3_2016.indd 55EM_3_2016.indd 55 8.9.2016 14:11:068.9.2016 14:11:06

56 2016, XIX, 3
Ekonomika
56 2016, XIX, 3
Abs ac
LONG-TERM INFRASTRUCTURE INVESTMENT: A NEW APPROACH
TO THE ECONOMICS OF LOCATION
Pe Dlask, Václa Be an
Con empo a y mode n de elopmen o a egion (RD) is associa ed wi h some concep ion o
economic ola ili y and echnological knowledge. The RD is igge ed by he exis ence o an
in as uc u e as a h eshold. Only hen can we expec he long- e m economic and egional e ec s.
F om he long- e m iew, he de elopmen o mos egions is also associa ed wi h a su p ising
di e si y. The easons o g ow h o s agna ion a e e y o en indis inc , and in some cases hey a e
e en uniden i i able.
Exis ing de elopmen is a ma e ialized oo p in o ea lie economic ac i i ies and he e is
mo e abou ha , o example, in Quali y o li e in ci ies, (Eu opean Commission, 2013). We should
unde s and he economics o RD as an accoun ; an accoun o ei he poo o success ul egional
managemen . In o he wo ds, egional economics and managemen (E&M) is a i s causal oo s
a p oo o he igh o w ong decision ules and hei implemen a ion. This a icle a gues ha he
s a e o municipali ies and o egions is only pa ly a hos age o he egional in es men economy
and ha a non-negligible way o success is pa ed by decision making p ocesses especially h ough
he use o ce ain decision c i e ia.
The pape aims o demons a e ha :
a) an elemen a y decision ule de e mines he decision space de e mining bo h ime and
concei able ac ions, ( iming o inno a ions, use and unc ions o a eas, implemen a ion o
pa icula in es men s, localiza ion o esea ch di ec ions, ma ke expansion, e c.);
b) dispe sion e ec s a e a ound and ou side he p ima y in es men ha gene a es he g ow h;
c) he bu nou e ec o he ini ial in es men exis s and begins o ac a e a ce ain ime pe iod;
d) i xing he ime o he ini ial in es men bu nou is iden i i able and can be calcula ed.
Poin c) and d) ep esen igge s o any need o new in es men s, usually called inno a ion,
mode niza ion, econs uc ion e c.
Key Wo ds: De elopmen , u ili y, simula ion, in as uc u e, e alua ion, me amodel.
JEL Classi i ca ion: C63, C81, O18, R58.
DOI: 10.15240/ ul/001/2016-3-004
EM_3_2016.indd 56EM_3_2016.indd 56 8.9.2016 14:11:068.9.2016 14:11:06