Long-term infrastructure investment: a new approach to the economics of location
Abstract
Contemporary modern development of a region (RD) is associated with some conception of economic volatility and technological knowledge. The RD is triggered by the existence of an infrastructure as a threshold. Only then can we expect the long-term economic and regional effects. From the long-term view, the development of most regions is also associated with a surprising diversity. The reasons for growth or stagnation are very often indistinct, and in some cases they are even unidentifiable.Existing development is a materialized foot print of earlier economic activities and there is more about that, for example, in Quality of life in cities, (European Commission, 2013). We should understand the economics of RD as an account; an account of either poor or successful regional management. In other words, regional economics and management (E&M) is at its causal roots a proof of the right or wrong decision rules and their implementation. This article argues that the state of municipalities and of regions is only partly a hostage of the regional investment economy and that a non-negligible way to success is paved by decision making processes especially through the use of certain decision criteria.The paper aims to demonstrate that:a) an elementary decision rule determines the decision space determining both time and conceivable actions, (timing of innovations, use and functions of areas, implementation of particular investments, localization of research directions, market expansion, etc.);b) dispersion effects are around and outside the primary investment that generates the growth;c) the burnout effect of the initial investment exists and begins to act after a certain time period; d) fixing the time of the initial investment burnout is identifiable and can be calculated.Point c) and d) represent triggers for any need of new investments, usually called innovation, modernization, reconstruction etc.
Full text
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
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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 eIn 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)
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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
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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
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44 2016, XIX, 3
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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
௧ ௦௧௧ ,
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,
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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 (1n) 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 (n1) 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,
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46 2016, XIX, 3
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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
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3, XIX, 2016
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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%
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48 2016, XIX, 3
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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
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55
3, XIX, 2016
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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
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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
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