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Empirical analysis of Hungarian firms according to venture capital investment criteria

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Empirical analysis of Hungarian firms according to venture capital investment criteria

Author: Futó, Judit Edit
Year: 2016
Source: https://dea.lib.unideb.hu/bitstreams/3447ab7d-2bd3-42ca-a524-4f41207970d1/download
Timisoa a Jou nal o Economics and Business | ISSN: 2286-0991 | www. jeb. o
Yea 2016 | Volume 9 | Issue 1 | Pages: 16–32
EMPIRICAL ANALYSIS OF HUNGARIAN FIRMS
ACCORDING TO VENTURE CAPITAL INVESTMENT CRITERIA
Judi Edi FUTÓ1
DOI: 10.1515/ jeb-2016-0002
O e he pas decade he en u e capi al indus y has
become mo e and mo e p ominen , no jus on a global
le el, bu in Hunga y, oo. Thanks o he JEREMIE P og am a
la ge numbe o new en u e capi al i ms a e loca ed in ou
coun y, and he e o e an in es men wa e has s a ed. The
aim o he pape is o so mic o- and small sized
en e p ises in e ms o how app op ia e is a en u e capi al
inancing. The main opic o he pape ela es o he
selec ion o i ms o en u e capi al in es men ; he e o e,
in he i s pa o he s udy we b ie ly summa ize a gene al
en u e capi al in es men p ocess, highligh ing bo h he
selec ion p ocess and he c i e ia used o selec ion. Then
we p opose 3 indexes ( us wo hiness index, openness
index, in es men index), which we ha e c ea ed o help
en u e capi alis s o decide whe he he a ge ed
en e p ises a e app op ia e o hem, o no . In he main
pa o he pape we p o ide a classi ica ion o mic o- and
small sized Hunga ian i ms based on my own su ey, and
we analyze wha kind o ela ionship exis s be ween he
p oposed indexes and he ype o he classi ied i ms. The
esul o he classi ica ion is ha we iden i y ou main i m
ypes and, based on s a is ical es s, i can be said ha
he e is no signi ican ela ionship be ween he
us wo hiness index and he clus e s, bu ha he e a e
be ween he wo o he indexes and he clus e s.
Keywo ds:
en u e capi al, ins i u ional in es o s, i ms, selec ion c i e ia, clus e analysis.
JEL Classi ica ion:
G24, G23, M1.
1 PhD s uden , Uni e si y o Deb ecen, Facul y o Economics and Business, Hunga y.
DOI: 10.1515/ jeb-2016-0002
Fu ó, E. J. (2016).
Empi ical analysis o Hunga ian i ms acco ding o en u e capi al in es men c i e ia
Timisoa a Jou nal o Economics and Business | ISSN: 2286-0991 | www. jeb. o
Yea 2016 | Volume 9 | Issue 1 | Pages: 16 – 32
17
1. In oduc ion
O e he pas decade he en u e capi al indus y has become mo e and mo e p ominen ,
no jus on a global le el bu in Hunga y, oo. Ne e heless, eno mous a ia ions emain in
he size and success o en u e capi al ma ke s a ound he wo ld. (Cumming, Schmid &
Walz 2010)
Ven u e capi al has had a p ominen ole in he Hunga ian economy o e he pas 5-6 yea s,
al hough i made i s i s appea ance in he egime change o 1989 (Ka sai, 2006). Mos
en u e capi al unds we e o eign, because he app op ia e legal and economic
en i onmen did no hen exis in Hunga y. The i s ele an law came in o o ce in 1998,
bu his did no encou age in es o s (Banyá & Csáki, 2006); since hen, con inuous
imp o emen s ha e been made. The pa h o Hunga ian VC de elopmen has been a ec ed
by a numbe o ac o s, such as he unde de eloped inancial sys em, he quali y o
en e p ises, cul u e, ins i u ions, his o y and public engagemen (Ka sai, 2012).
In a Cen al and Eas e n Eu opean con ex he Hunga ian en u e capi al indus y was
ou s anding be ween 2004 and 2008, bu as a esul o he inancial c isis i encoun e ed
se ious p oblems. A e 2007, when he inancial c isis occu ed, he Hunga ian en u e
capi al indus y s a ed o slow down. The easons o he decline we e, on he demand
side, he in ensi ying compe i ion o en u e capi al unds be ween en ep eneu s. Since
he inancial c isis, i has been ha d o ge loans om banks, and he e o e he owne s o
companies ha e s a ed o look o al e na i e sou ces o unds, such as en u e capi al. On
he o he hand, he sou ces o en u e capi al also dec eased because he VC unds held
back on eleasing unds in o de o s abilise hei own po olios, and so he ounde s o VC
unds also a ec ed he c isis because o he educ ion o he amoun o unds managed
(Ka sai, 2013).
The impac o he inancial c isis can be obse ed in he dec ease in he sha e o he
p i a e equi y segmen . Howe e , he classic en u e capi al segmen has now s a ed o
inc ease, due o he JEREMIE P og am. (MNB, 2015) The abo e men ioned p oblem, i.e. he
lack o capi al, has been sol ed hanks o he Eu opean Union and he Hunga ian
go e nmen . Toge he hey c ea ed he JEREMIE P og amme, which o e s 45 billion HUF
(a ound 150 million eu os) o 8 VC unds. The goal o he new 8 VC unds is o inance he
inno a i e, mic o- and small-size en e p ises ha p e iously disappea ed beyond he
ho izons o bo h in es o s and he go e nmen (Ka sai, 2013).
All o his sounds encou aging, bu he ques ions emains as o whe he he e a e su icien
en e p ises o he igh quali y o be inanced by en u e capi al unds. Many in he
business communi y ha e w i en abou his p oblem, highligh ing he ole o he g owing
DOI: 10.1515/ jeb-2016-0002
Fu ó, E. J. (2016).
Empi ical analysis o Hunga ian i ms acco ding o en u e capi al in es men c i e ia
Timisoa a Jou nal o Economics and Business | ISSN: 2286-0991 | www. jeb. o
Yea 2016 | Volume 9 | Issue 1 | Pages: 16 – 32
18
alloca ed capi al bu exp essing scep icism abou whe he VC unds can ind he igh
po olio companies. Acco ding o in es o s, a mis aken classi ica ion o Hunga ian
en e p ises is caused by incompe en managemen and he lack o sales ac i i y. The
consequences o he si ua ion desc ibed abo e a e ha , on he one hand, any business -
e en hose less sui able - can ge access o capi al, and, on he o he hand, he in es men
pe iod is ex ended wi h he JEREMIE unds (MNB, 2015).
In he in oduc ion we ga e a e y b ie e iew o he Hunga ian en u e capi al indus y as
a basis o his s udy. Due o he cu en si ua ion in Hunga y, i is impo an o unde s and
he main cha ac e is ics o Hunga ian en e p ises, in o de o know whe he hey mee he
expec a ions o en u e capi al unds. The pu pose o he s udy is o p o ide a classi ica ion
o mic o- and small sized Hunga ian i ms, based on my own su ey and o analyze wha
kind o ela ionship exis s be ween he p oposed indexes and he ypes o he classi ied
i ms.
Fi s ly, we gi e a gene al o e iew o he selec ion phase o he en u e capi al in es men
p ocess, because his heo e ical backg ound will be used o he analysis o he su ey.
Secondly, o a deepe unde s anding we b ie ly desc ibe 3 indexes, which we c ea ed o
help en u e capi alis s o easily decide whe he he a ge ed en e p ises a e app op ia e
o hem, o no . In he las pa o he pape we p esen and discuss he empi ical esul s o
clus e analysis and we inish wi h a conclusion.
2. Li e a u e Re iew
A e he in oduc ion, whe e we b ie ly cha ac e ize he Hunga ian en u e capi al indus y,
le us con inue he li e a u e e iew o he main opic o he pape .
The pu pose o his sec ion is o desc ibe he usual p ocess o deal-making in a en u e
capi al i m and a ew o he decision making cha ac e is ics o he deal. Mo e impo an
he e is he kind o c i e ia used by en u e capi alis s o e alua e new en u e p oposals.
Based on Kollmann and Kucke z (2009); Macmillan, Siegel, and Na asimha (1985);
Tyebjee and B uno (1984); Hall and Ho e (1993); Khanin, Baum, Mah o, and Helle (2008);
F ied and His ich (1994) we gi e a lis o he gene al c i e ia ha en u e capi alis s use o
e alua e po en ial in es men s. These c i e ia a e, o example, he en ep eneu 's
pe sonali y, abili y, expe ience; he cha ac e is ics o he business; he cha ac e o he
p oduc / se ice; he business model; compe i ion and ma ke g ow h; and o cou se he
inancial sys em de elopmen le el. The c i e ia o he anking o each in es o is di e en ,
bu uni o m ag eemen can be obse ed in his ega d ha he mos impo an aspec o
he in es o is he en ep eneu skills, ai ness and expe ience. These a e e y subjec i e
ac o s, bu en u e capi alis s always co-ope a e wi h someone in whom hey see he
DOI: 10.1515/ jeb-2016-0002
Fu ó, E. J. (2016).
Empi ical analysis o Hunga ian i ms acco ding o en u e capi al in es men c i e ia
Timisoa a Jou nal o Economics and Business | ISSN: 2286-0991 | www. jeb. o
Yea 2016 | Volume 9 | Issue 1 | Pages: 16 – 32
19
p ope sympa hy. In addi ion, ano he impo an c i e ia is he possibili y o he exi because
wi hou a good exi he en u e capi alis canno aise new und in he nex e m.
The en u e capi al in es men p ocess consis s o 5 s eps. These a e deal o igina ion, deal
sc eening, deal e alua ion, deal s uc u ing and pos -in es men ac i i y (Tyebjee & B uno,
1984). The heo y o selec ion is well de eloped in inance; i will no be e iewed he e.
Howe e , we emphasise he sc eening and e alua ion phases, whe e he en u e capi alis s
o hei eam seek o subjec i ely assess he po en ial en e p ises on a mul idimensional
se o c i e ia. Tyebjee and B uno (1984) ind 5 dimensions, namely, ma ke a ac i eness,
p oduc di e en ia ion, manage ial capabili ies, en i onmen al h ea esis ance, and cash-
ou po en ial. F om hese dimensions i is necessa y o highligh he en u e’s abili y o
manage hem e ec i ely, he quali y o he managemen eam, and he p oduc ’s
compe i i e ad an ages and uniqueness.
O he au ho s (Kollmann & Kucke z (2009); Macmillan e al. (1985); Hall and Ho e
(1993); Khanin e al. (2008); F ied and His ich (1994)) ha e also w i en abou his opic.
The di e ences in hei app oach conce n he ype o esea ch me hods used, he sample,
and how hey ca ego ize he c i e ia. Mos o hem de ine he ollowing c i e ia: en u e
capi al i m/ und equi emen s, he cha ac e is ics o he en ep eneu , he na u e o he
p oposed business, and he economic en i onmen o he p oposed indus y o coun y.
Zacha akis and Meye (1998) c i icize he abo e men ioned s udies because he majo i y o
pas esea ch elies on pos hoc me hodologies o unde s and he decision p ocess and
c i e ia. Zacha akis and Meye (1998) use policy cap u ing and a eal- ime me hod common
in cogni i e psychology. Thei indings sugges ha en u e capi alis s a e no good a
in ospec ing abou hei own decision p ocesses because, as mo e in o ma ion becomes
a ailable, insigh diminishes.
In o de o collec he igh a iables o he clus e analysis we ha e o know wha he mos
use ul c i e ia in he en u e sc eening p ocess a e. The e o e, we highligh h ee aspec s
which a e used du ing he analysis. We hink ha he mos impo an a e he
en ep eneu ’s eliabili y and openness; he inancial me hods o and he cha ac e o he
p oduc /se ice.
In he nex sec ion we in oduce ou own sample and he a iables and desc ibe he 3
indexes we ha e c ea ed o analysis.
DOI: 10.1515/ jeb-2016-0002
Fu ó, E. J. (2016).
Empi ical analysis o Hunga ian i ms acco ding o en u e capi al in es men c i e ia
Timisoa a Jou nal o Economics and Business | ISSN: 2286-0991 | www. jeb. o
Yea 2016 | Volume 9 | Issue 1 | Pages: 16 – 32
20
3. Da a and me hodology
In his sec ion we in oduce he sample, he a iables and he indexes. We use a
ep esen a i e su ey which was p o ided by he HÉTFA Resea ch Ins i u e, which consis s
o 300 Hunga ian mic o- and small-size en e p ises. The su ey was made a 2011 sp ing.
The en e p ises in he su ey we e in ol ed in he indus ial, ading and se ice sec o s,
ope a ing in se en di e en egions o Hunga y. The business owne s we e in e iewed. The
pu poses o he su ey we e o unde s and how mic o- and small-size en e p ises ope a e
on an e e yday basis, and wha hei de elopmen plans a e. (Su ey, 2011)
As ega ds he analysis, we conside i p oblema ic ha we only use his pa icula ly su ey
and i s da a; howe e , we we e no in ol ed in he edi ing o he su ey. We added ex a
in o ma ion o he da abase, such as sales, o al asse s, and owne ship s uc u e. In
Table 1 we lis all he a iables we use o he analysis. Table 1 con ains basic s a is ical
in o ma ion, such as he mean, s d. de ia ion, minimum and maximum alue o all
a iables. Some o he a iables a e dummies, bu he e a e o he s which a e measu ed in
scales. In hese cases we s anda dize hese o ge nominal a iables whose alue is
be ween 0-1. Fo example, we no e ha he maximum alue o he sales a iable is
2,900,000,000 HUF; we hen di ide he amoun o each company’s sales by ha maximum
alue. We apply he same me hod o he yea s o ope a ion, en ep eneu s’ yea s o
ac i i y, he age o he in e iewees, he income le el o he in e iewees, sales, o al
asse s, he us wo hiness index, he in es men index, and he openness index.
A e in oducing he da abase we summa ise he s uc u e o he indexes we men ioned
ea lie , because we will use hem la e on. In Fu ó – Szobonya (2012) we c ea ed 3 indexes
which migh be aken in o accoun as selec ion c i e ia o en u e capi alis s. The i s is
he us wo hiness index, which gi es in o ma ion abou he eliabili y o he manage . The
second index is he openness index; his measu es how en e p ises ag ee o ake en u e
capi al in es men which in ol es hei own company. The hi d index is he in es men
index, which cha ac e izes he company’s in es men objec i es.
The c ea ion o he p oposed indexes s a ed om he ques ions o he su ey gi en o us.
The su ey consis ed o 86 ques ions, despi e he di icul ies, which men ioned ea lie , 16
ques ions could be selec ed o build he indexes. Thus, we began o in oduce he c ea ion
o he p oposed indexes. We ecei ed some help o he selec ion o app op ia e ques ions
om Pe e Szobonya, who has aken pa in se e al en u e capi al nego ia ion as an
in e media y pa y, he e o e he has some knowledge abou he habi s o and expec a ions
o he en u e capi alis . Du ing o ming he index alues we used Mic oso O ice Excel.

DOI: 10.1515/ jeb-2016-0002
Fu ó, E. J. (2016).
Empi ical analysis o Hunga ian i ms acco ding o en u e capi al in es men c i e ia
Timisoa a Jou nal o Economics and Business | ISSN: 2286-0991 | www. jeb. o
Yea 2016 | Volume 9 | Issue 1 | Pages: 16 – 32
21
Table 1. Desc ip i e s a is ics o he a iables
Minimum Maximum Mean S d.
De ia ion
Numbe
o
esponden s
Budapes
0.0000
1.0000
0.3367
0.4734
101
Deb ecen
0.0000
1.0000
0.1633
0.3703
49
Dunauj a os
0.0000
1.0000
0.0833
0.2768
25
Miskolc
0.0000
1.0000
0.1233
0.3294
37
Szeged
0.0000
1.0000
0.1200
0.3255
36
Szeksza d
0.0000
1.0000
0.0567
0.2316
17
Zalaege szeg
0.0000
1.0000
0.1167
0.3216
35
mic o-size en e p ise
0.0000
1.0000
0.4767
0.5003
143
small-size en e p ise
0.0000
1.0000
0.5233
0.5003
157
indus ial company
0.0000
1.0000
0.2933
0.4561
88
ading company
0.0000
1.0000
0.3167
0.4660
95
se ice company
0.0000
1.0000
0.3900
0.4886
117
he in e iewee is he owne
0.0000
1.0000
0.8288
0.3774
242
he in e iewee is no he owne
0.0000
1.0000
0.1712
0.3774
50
he owne is an ac i e wo ke
0.0000
1.0000
0.9267
0.2611
278
he owne is no an ac i e wo ke
0.0000
1.0000
0.0733
0.2611
22
oca ional educa ion
0.0000
1.0000
0.0367
0.1883
11
educa ed o high school le el
0.0000
1.0000
0.3233
0.4685
97
g adua e
0.0000
1.0000
0.6400
0.4808
192
ma ied
0.0000
1.0000
0.8712
0.3356
257
unma ied
0.0000
1.0000
0.1288
0.3356
38
eligious
0.0000
1.0000
0.6056
0.4896
172
non- eligious
0.0000
1.0000
0.3944
0.4896
112
has child en
0.0000
1.0000
0.9033
0.2960
271
has no child en
0.0000
1.0000
0.0967
0.2960
29
male
0.0000
1.0000
0.7200
0.4497
216
emale
0.0000
1.0000
0.2800
0.4497
84
membe o a business o ganiza ion
0.0000
1.0000
0.6133
0.4878
184
no a membe o a business o ganiza ion
0.0000
1.0000
0.3867
0.4878
116
poo
0.0000
1.0000
0.0517
0.2219
15
a e age income
0.0000
1.0000
0.8379
0.3692
243
ich
0.0000
1.0000
0.1103
0.3139
32
he owne s is Hunga ian
0.0000
1.0000
0.9800
0.1402
294
he owne is o eign
0.0000
1.0000
0.0200
0.1402
6
ope a ion yea s_s anda dized
0.0800
0.9200
0.5286
0.2566
en ep eneu s yea s_s anda dized
0.0476
1.0000
0.6988
0.2984
age o he in e iewee_s anda dized
0.2500
0.9750
0.6500
0.1300
income le el o he in e iewee_s anda dized
0.0000
1.0000
0.5633
0.1711
sales_s anda dized
0.0001
0.9861
0.0688
0.1191
o al asse s_s anda dized
0.0001
0.9892
0.0589
0.1176
Sou ce
: Au ho s’ calcula ions
DOI: 10.1515/ jeb-2016-0002
Fu ó, E. J. (2016).
Empi ical analysis o Hunga ian i ms acco ding o en u e capi al in es men c i e ia
Timisoa a Jou nal o Economics and Business | ISSN: 2286-0991 | www. jeb. o
Yea 2016 | Volume 9 | Issue 1 | Pages: 16 – 32
22
The us wo hiness index consis s o 4 ques ions and each e e s o how he owne -
manage conside s ce ain i egula i ies o be accep able, such as ax aud o kickbacks.
The u hs o s a emen s a e ma ked om 1 o 10 scale. A alue o 1 means "ne e
allowed", while 10 is "always pe missible". The inal alue o he index is a weigh ed a e age
o he 4 answe s o ha , so he alue o he us wo hiness index a e be ween [1-10]. I he
alue o he index is 1, hen we say ha he owne o he company is eliable, and highe
alue om 1 means he owne is un eliable.
Connec ed o he openness index, 10 ques ions we e conside ed app op ia e o e alua e
he openness, so he e a e ypes o ques ions we pu as "I could no bea ha he company
alls in o he hands o ano he , no e en i I ge good p ice o i " o "I could no bea o an
ex e nal inancial in es o as a co-owne in e e e in he managemen o he company" o
" o he company's g ow h use o en u e capi al is concei able". The openness index is
composed o 10 di e en ques ions, which we e needed o scale i s ly, and hen he
answe s we e classi ied so ha hey s eng hen o weaken o neu alize he openness
index. I he answe o a ques ion s eng hened he openness index we gi e a 1, i i
weakened -1 and 0 i neu al. Then we summa ized he alue o he answe s o he
ques ions ha a e weigh ed equally in he index. The possibili y o a ia ion in he openness
index mo es in qui e a wide ange. The mos ideal case, he maximum index alue is 8 and
he minimum is -7.
Finally, he in es men index is ela ed o he company's u u e in es men plans and
inancing issues. In he case o he in es men index, h ee ca ego ies we e dis inguished
du ing he o ming: "absolu ely inapp op ia e", "medium" and " highly ele an ”. The
"absolu ely inapp op ia e" ca ego y is ele an o a company ha does no plan o expand o
in es by en u e capi al. The "medium" a ing is gi en o companies ha plan o esea ch
and de elopmen and / o new se ices, new p oduc in oduc ion and / o expansion o
equipmen , bu in he i s ound do no in end o inance hese plans by in ol emen o an
ex e nal in es o . Those companies which plan o he abo e lis ed in es men s and
inanced by ex e nal in es o s a e in he "highly ele an " ca ego y. In la e i would be
di icul o ca y ou an analysis wi h g oup names, hus we simply added alues o each
g oups, bu i is i ele an wha he numbe o he alue is. The highly ele an g oup
ecei ed 1, he medium go 2, and absolu ely inapp op ia e g oup go 3.
Fo he bes in es men oppo uni y; he e o e, you mus sea ch o he ollowing c i e ia:
he us wo hiness index should be 1, he openness index should be posi i e and he
in es men index should be 1.
In he s udy (Fu ó – Szobonya 2012) we made a eg ession analysis in SPSS o ind ou
which a iables he success o a en u e capi al in es men depends on. The explana o y
DOI: 10.1515/ jeb-2016-0002
Fu ó, E. J. (2016).
Empi ical analysis o Hunga ian i ms acco ding o en u e capi al in es men c i e ia
Timisoa a Jou nal o Economics and Business | ISSN: 2286-0991 | www. jeb. o
Yea 2016 | Volume 9 | Issue 1 | Pages: 16 – 32
23
powe o eg ession models was no conside ed app op ia e, and hus I do no wish o
p esen he esul s he e again; consequen ly, we con inue wi h he clus e analysis.
The pu pose o he clus e ing is o iden i y di e en g oups in o de o cha ac e ize he
ypical company which could mee he equi emen s o en u e capi alis s. Fi s ly, we o m
he clus e s; hen we b ie ly summa ize he bes - i ing ai s. A e his, we conduc a
ela ionship analysis wi h he explana o y a iables, he missing a iables and he 3
indexes. Fo all hese we make a K-mean clus e analysis in he SPSS p og am.
The p ocess o he analysis in ol es all he a iables a ailable o me selec ed o he
clus e ing; we es ed how hey con ibu e o clus e o ma ion. We s a wi h he
s anda diza ion o he explana o y a iables and emo e he a ypical cases (ou lie s) which
would dis o he clus e ing. The dend og am can p o ide a s a ing poin o de e mine he
numbe o clus e s. In his case, we ha e a sample wi h 300 elemen s; i is ha d o ead he
exac numbe o clus e s om he dend og am, bu he conclusion is ha he co ec
numbe o clus e s is 4 o 5. We ca y ou some andom K-mean clus e ing in a ious
clus e cases, and hen we choose 4 as he numbe o he clus e . In making he decision i
is impo an ha he e is a good dis ance be ween he clus e cen es, so ha hey will be
in e p e ed accu a ely. I 6 o 8 clus e s a e o med, he expec ed esul s will be los om
he analysis.
To ind he inal explana o y a iables we need o use One-way ANOVA, which p o ides a
s a is ical es o whe he o no he means o se e al g oups a e equal, and he e o e
gene alizes he - es o mo e han wo g oups. As a s a ing poin we use all he a iables o
o m 4 clus e s, and we analyse he ANOVA able (in Table 2) o ind he bes a iables which
con ibu e signi ican ly o clus e o ma ion and hose which can be dis ega ded.
We ha e o conside hose a iables which ha e a signi ican le el o ze o and also hose
be ween 1 and 5 pe cen , such as he s uc u e o he owne ship, he income le el o he
in e iewed, and o al asse s. Comple ely insigni ican a iables include ma ied, eligious, he
en ep eneu s’ age, and he age o he in e iewee. The signi ica ion le el o he yea s o
ope a ion a iable is abo e 5 pe cen , bu in he desc ip i e able i can be seen ha he
missing alidi y is he highes he e, and he e o e we lose one hi d o my sample du ing he
clus e ing. To ind he bes clus e s we omi a ew explana o y a iables such as he ma ied,
eligious, child en, male, poo and a e age income a iables, he en ep eneu s’ age, and he
age o he in e iewee.
DOI: 10.1515/ jeb-2016-0002
Fu ó, E. J. (2016).
Empi ical analysis o Hunga ian i ms acco ding o en u e capi al in es men c i e ia
Timisoa a Jou nal o Economics and Business | ISSN: 2286-0991 | www. jeb. o
Yea 2016 | Volume 9 | Issue 1 | Pages: 16 – 32
24
Table 2. ANOVA ou pu o he explana o y a iables
F
Sig.
Budapes
72.04664
0.00000
Deb ecen
2.51597
0.05941
Dunauj a os
2.40790
0.06830
Miskolc
5.74449
0.00086
Szeged
7.19590
0.00013
Szeksza d
4.85193
0.00278
mic o-size en e p ise
6.22926
0.00046
indus ial company
93.07387
0.00000
ading company
7.80426
0.00006
he in e iewee is he owne
4.87335
0.00271
he owne is an ac i e wo ke
5.20694
0.00174
educa ed o high school le el
608.08470
0.00000
g adua e
1061.17825
0.00000
ma ied
0.73782
0.53060
eligious
0.46087
0.70992
has child en
1.05956
0.36735
male
1.53146
0.20750
membe o a business o ganiza ion
9.51449
0.00001
poo
1.62141
0.18557
a e age income
1.23437
0.29831
he owne s is Hunga ian
4.54388
0.00417
ope a ion yea s_s anda dized
2.32203
0.07629
en ep eneu s yea s_s anda dized
0.65810
0.57874
age o he in e iewee_s anda dized
0.62937
0.59683
income le el o he in e iewee_s anda dized
3.29161
0.02163
sales_s anda dized
4.18256
0.00671
o al asse s_s anda dized
3.32937
0.02059
Sou ce
: Au ho s’ calcula ions
4. Empi ical Resul s
To explain he clus e s we use he ou pu o he inal clus e cen es and he ANOVA ou pu ,
which can be ound in Table 3 and Table 4.
Based on he geog aphic a iables, 4 clus e s a e o med. Two ou o he ou a e mixed g oups,
which means he en e p ises ope a e in any pa o he coun y. In he hi d clus e he e a e
only Budapes based en e p ises, and in he ou h clus e he e a e only en e p ises in u al
a eas. Fo his eason we ha e named he hi d clus e Budapes -only businesses, while he
DOI: 10.1515/ jeb-2016-0002
Fu ó, E. J. (2016).
Empi ical analysis o Hunga ian i ms acco ding o en u e capi al in es men c i e ia
Timisoa a Jou nal o Economics and Business | ISSN: 2286-0991 | www. jeb. o
Yea 2016 | Volume 9 | Issue 1 | Pages: 16 – 32
31
We ha e modi ied he me hodology used in hei app oach, and we ha e p o ided a
classi ica ion o hese mic o- and small-size i ms based on his su ey. Ou inding is 4
main ypes o i ms. Two ou o he ou a e mixed g oups, which means ha he en e p ises
ope a e in any pa o he coun y. In he hi d clus e he e a e only Budapes based
en e p ises and in he ou h clus e he e a e only en e p ises in u al a eas. Based on he
accoun ing in o ma ion, he hi d clus e includes he la ges companies which can be ound
in he sample, while he second clus e con ains he smalles i ms. Ano he impo an
di e ence is ha he majo i y o businesses who ha e o eign owne s a e in he hi d
clus e . Howe e , he e is no g ea di e ence be ween he clus e s in e ms o he yea s o
ope a ion and he indus ial sec o . Acco ding o he so ing we could say ha he hi d
clus e ‘s companies ha e go he bes ea u es by which may be accep able o en u e
capi alis du ing he selec ion p ocess. Because hese i ms ope a e in Budapes his gi es
hem a compe i i e ad an age. Budapes is he capi al ci y in Hunga y, he e o e he
economic en i onmen is mo e inspi ing so he companies ha e mo e chance o g ow as e .
Subsequen ly, we analyzed wha kind o ela ionship exis s be ween he p oposed indexes
and he ype o i m classi ied, because his could help o unde s and which i ms could be
po en ial a ge s o en u e capi al in es men . The pu pose o he analysis is o disco e
which ype o company could be app op ia e o en u e capi alis s based on he p oposed
indexes. Based on s a is ical es s, i can be es ablished ha he e is no signi ican
ela ionship be ween he us wo hiness index and he clus e s, bu ha he e is be ween
he wo o he indexes and he clus e s. We conclude ha - based on he openness index
and in es men index - en u e capi alis s need o ocus on en e p ises which ope a e in
Budapes , i.e. hose co esponding o he cha ac e is ics o he hi d clus e . Fu he mo e, i
can be said ha only wo companies ou o 300 a e accep able acco ding o he 3 p oposed
indexes c i e ia. These wo i ms belong o he hi d clus e so his also con i ms ha
Budapes as capi al ci y has good e ec on he companies li e.
Ou esea ch wo k does no end he e, because a ollow-up is necessa y in o de o
de e mine how success ul a en u e capi al selec ion made wi h he help o he p oposed
indexes is, and so in he u u e ou esea ch wo k will con inue on his pa h. We plan o
con ac wi h Hunga ian en u e capi al i ms o o e ou indexes o hem o y i du ing a
eal in es men p ocess. Beside his we wan o emake/calcula e he p oposed indexes o
hose companies, who won en u e capi al om Je emie’s en u e capi al i ms. The e o e
we wan o see wha kind o index alues ha e hey eached, and could we classi y hem o
ou 4 g oups.

DOI: 10.1515/ jeb-2016-0002
Fu ó, E. J. (2016).
Empi ical analysis o Hunga ian i ms acco ding o en u e capi al in es men c i e ia
Timisoa a Jou nal o Economics and Business | ISSN: 2286-0991 | www. jeb. o
Yea 2016 | Volume 9 | Issue 1 | Pages: 16 – 32
32
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