146 2017, XX, 2
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DOI: 10.15240/ ul/001/2017-2-011
In oduc ion
This pape analyzes on he pe cep ions
o in e ne i nancial epo ing (he eina e
e e ed o as IFR) in Malaysia. While in e ne
i nancial epo ing is as and a ac i e
becoming he s anda d in de eloped coun ies,
bu , ew o p e ious s udies ha e ocused on
his phenomenon in de eloping coun ies. In
ecen yea s in e ne usage ha e inc eased
o dissemina ion o co po a e in o ma ion and
is seen as a globaliza ion p ocess (Mo adi e
al., 2011; Gallego-Al a ez, 2011; Valen ine i &
Rea, 2012). In addi ion, he sys em o economic
digi alized (Shi i e al., 2013). Thus, disclosu e
o i nancial epo ing ep esen s con inuing
imp o emen o e adi ional me hods such as
pape based in e ms o supplying imely da a,
lowe cos and speed in ob aining in o ma ion
abou co po a ions (Ojah & Moko eli, 2012;
And ikopoulos e al., 2013). Mo eo e , pape -
based annual epo s a e less use ul now in
e ms o imeliness and eliabili y as he wo ld is
highly elian on in o ma ion and communica ion
echnologies (E edge e al., 2002). In e ne
connec ion has se e al di ec ions in na u e and
e y apid in ansmission and o e s inc eased
accessibili y o i nancial and non- i nancial
in o ma ion (Bollen e al., 2008; Sanchez e al.,
2011). Many companies a ound he wo ld a e
mo i a ed o p ac ice IFR o mee use s’ needs
o mo e imely in o ma ion (Amin & Mohamed,
2016).
Acco ding o cu en IFR li e a u e, e olu ion
o IFR is he signi i can opic in s udies. The IFR
esea ch e olu ion can classi i ed in he a ious
desc ip i e esea ches, hemes, dimensions o
IFR, associa ion esea ches and classi i ca ion o
IFR. In addi ion; he s udy on IFR can ca ego ies
in di e en ypes such as; desc ip i e s udy some
coun ies, s udy by schola s and explana o y
s udy. (Ali Khan, 2010). Fu he mo e; s udies
on IFR can be ca ego ized based on i s
and second gene a ion (Al-H ayba , 2011).
Al hough; p e ious s udies ha e emphasized
on IFR esea ches in las wo decades, ew o
p e ious pape s ha e ocused and desc ip he
ela ionship be ween a i udes and p e e ences
o co po a e annual epo use and co po a e
beha iou pa icula ly in de eloping coun ies
such as Malaysia. As well, he success o
elec onic go e nmen policy in Malaysia has
inc eased he numbe o companies ha u ilize
in e ne i nancial epo ing in bo h he public and
p i a e sec o s (Abdul Aziz e al., 2011). This is
because companies had ealized he bene i s
associa ed wi h IFR (Poon e al., 2003). Fi ms
which a e adop ing he in e ne o accoun ing
and i nancial in o ma ion p esen a ion may see
addi ional bene i s o e addi ional cos s by
p o iding i nancial epo s h ough a websi e
(Khan, 2006). In addi ion, he de elopmen o
in o ma ion echnology makes a e olu ion in
achie e in o ma ion ou side o a ound he wo ld
(Shi i e al., 2013). Acco ding o Ali Khan e
al. (2013), con en dimension is an impo an
ac o o in l uence he e ec i eness o IFR
as he i ems o IFR will help o de e mine he
impo ance and use ulness o IFR in Malaysia.
Also, he e a e se e al mo i a ions in engaging
IFR in Malaysia which a e an inc ease in
he anspa ency o dissemina ing company
in o ma ion, inc eased use o he in e ne
in e ms o p omo ion and he c ea ion o
a good b and name as well as he p ac ise o
good co po a e go e nance (Kiew & Salleh,
2011). The e a e no guidelines p esc ibing he
in o ma ion on co po a e websi es (Ali Khan &
Ismail, 2011a). Ye , he e a e s ill no manda o y
guidelines and equi emen o IFR disclosu e
in Malaysia (Hani a & Ab. Rashid, 2005).
The e o e, he aim o his s udy o examine he
EMPIRICAL RESEARCH OF USERS’
OPINIONS ON SELECTED ASPECTS
IN INTERNET FINANCIAL REPORTING
Mohd Noo Azli Ali Khan, Noo Azizi Ismail, Abbas Ma dani,
Edmundas Kazimie as Za adskas, A u as Kaklauskas
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pe cep ions o co po a e annual epo use s
owa ds selec ed aspec s o IFR in Malaysia.
The emainde o his a icle is o ganized
as ollows. A e iew o ele an li e a u e a e
p o ided in he nex sec ion. Sec ion wo
discusses he esea ch design, ollowed by
esea ch i ndings. Nex sec ion desc ibes web
usage and web con en analy ics. A summa y,
conclusion and sugges ions o u u e esea ch
a e p esen ed in he i nal sec ion.
1. In e ne Financial Repo ing and
Web Analy ics – Re iew o he
Li e a u e
IFR is an in e es ing, a ac i e and apid
g owing s udy i eld (Oyele e e al., 2003; Xiao
e al., 2005; Ali Khan, 2010; And ikopoulos
e al., 2013). Acco ding o S oel e al. (2012),
mos companies ha e s a ed o adop IFR
wi h he ad ance o in o ma ion echnology.
Al hough IFR a e wide issues o s udy, he
implemen a ion is di e en ac oss coun ies
in e ms o echnological de elopmen , and
he endency o use he in e ne o i nancial
epo ing pu poses and signi i can ly in l uenced
by he accoun ing sys em in each coun y (Alali
& Rome o, 2012). Ojah and Moko eli (2012)
s a ed ha poli ical en i onmen is one o he
ac o s which ha e con ibu ed o co po a e
adop ion o IFR. Resea che also p o ided
examples om s udies which indica ed ha
i e Eas Asia coun ies including Hong Kong,
Malaysia, Thailand, Singapo e and China which
lack complemen a y en i onmen in as uc u e
has no success ully adop ed IFR o e all. In
addi ion, IFR also p omo es anspa ency
abou in o ma ion disclosu e which enhances
manage ial decisions and he cong uency o
s akeholde s in he decision making p ocess
(Kel on & Penning on, 2012; Ojah & Moko eli,
2012).
Lyme (1999) indica ed ha , he e a e some
bene i s o he he in e ne o i nancial epo ing
such as l exibili y,speed, i s cheapness and
dynamism, On he o he hand, in e ne has
become e ec i e by p omo ing he use o
hype links and sea ch engines (Ojah & Mako eli,
2012). F om an in es o ’s pe spec i e, Kel on
and Penning on (2012) s a ed ha IFR is
ano he way o accessing in o ma ion which will
in l uence hei decision making p ocess based
on he in o ma ion disclosed. In addi ion, IFR
no only con ain he i nancial epo ing as pape
based epo s. I also epo s cu en si ua ions
in a o ma which enhances accessibili y and
l exibili y owa d use s (Ojah & Moko eli, 2012).
Bene i in e ms o cos associa ed wi h
he l exibili y p o ided by hype link make
IFR mo e in e ac i e and mo e use iendly
(Kel on & Penning on, 2012). O he han ha ,
he in oduc ion o a new echnology like IFR
equi es expe ise. Thus, he implemen a ion,
compliance and he quali y o he o e all
i nancial epo ing disclosu e may be less
e ec i e due o he lack o expe ise (S oel e
al., 2012; Shi i e al., 2013).
In he ecen yea s he impo an o IFR
issues ha e con i med in he li e a u e. Mo adi
e al. (2011) s a ed ha IFR is a new, signi i can
and in e es ing a ea o u u e s udies and
has become a ocus o u gen in es iga ion
a in e na ional le el (Al-H ayba , 2011).
The esul s o his eme ging s eam o IFR
esea ch sugges ha companies a e s ill in
he e y p elimina y s ages o in eg a ing hese
echnologies in o hei o e all communica ion
s a egy (Bow in, 2015). The le el o IFR o
Bu sa Malaysia lis ed companies s a ed om
48.27 pe cen o 78.16 pe cen wi h a min o
65.10 (Ali Khan, 2011a). Fu he mo e, he le el
o IFR among he public lis ed companies in
Bu sa Malaysia s a ed om 56.43 pe cen o
87.14 pe cen (Ali Khan, 2015). The disclosu e
i ems in he IFR disclosu e index checklis a e
based on he pe spec i e o use s o co po a e
annual epo (Ali Khan, 2016). Con en
analysis is used o p o ide on IFR p ac ices by
280 publicly aded i ms. Based on he Ali Khan
(2016), he le el o IFR o Bu sa Malaysia lis ed
companies s a ed om 56.55 pe cen o 86.21
pe cen .
Also, we analyze Web analy ics (Web usage
and Web con en analy ics) o disco e i nancial
and non- i nancial usage and con en pa e ns
om company websi es and o he sou ces o
Wo ld da a. Web usage analy ics has allowed
company c ea es be e buye ela ionship and
o do pe sonalized ma ke ing. Fo example, we
can used Open Web Analy ics (OWA). OWA
is an open sou ce web analy ics so wa e ha
anyone can use ha so wa e o ack and
analyse how people use you websi es and
applica ions.
Web Con en Mining ocuses on he aw
in o ma ion a ailable in Web pages. Sou ce
da a mainly consis s o ex ual da a in Web
pages. Many Web Con en mining sys ems
o he disco e ing company e enue ela ions
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om news (Ma e al., 2009), p edic ing company
(Tho leuch e e al., 2012), i m analysis (Cecchini
e al., 2010), opinion mining (Mo eo e al., 2012;
He e al., 2015; Ra i e al., 2015; Mos a a, 2013),
p edic abili y o i nancial (Nassi oussi e al.,
2014) and s ock (Schumake & Chen, 2009;
G o h & Mun e mann, 2011; Pa anjape-Vodi el
& Deshpande, 2013; Zhang e al., 2011; Fo uny
e al., 2014; Schumake e al., 2012) ma ke s,
compe i o analysis (Ma e al., 2011) ha e been
de eloped wo ldwide. The ollowing is a sho
desc ip ion o some o he Web Con en Mining
sys ems o disco e i nancial and non- i nancial
usage and con en pa e ns om company
websi es and o he sou ces o Wo ld da a.
Cecchini e al. (2010) o examine o
company ca as ophic i nancial e en s ha e
used i nancial ex . Cecchini e al. (2010) ound
ha aud (81.97%) and bank up cy (83.87%)
wi h he in eg a ed da a, ep esen ing ha
he ex o he managemen discussion and
analysis sec ions complemen s he quan i a i e
i nancial in o ma ion. Mos a a (2013) showed
he signi i can o some social ne wo ks such
as Facebook and Twi e ha been impo an
in ma ke ing i ms, public i ms and some
o he ex mining co po a ions. Mos a a (2013)
o assess he consume s‘ sen imen owa ds
u ilized he andom sample o 3516 wee s o
amus b ands like T-mobile, DHL, IBM, KLM
and Nokia.
Nassi oussi e al. (2014) e iew he ela ed
wo ks ha a e abou ma ke p edic ion based
on online- ex -mining and p oduce a pic u e
o he gene ic componen s ha hey all
ha e. Schumake and Chen (2009) examine
a quan i a i e s ock p edic ion sys em based
on i nancial news. Schumake and Chen (2009)
seek o con ibu e o he A izona Financial Tex
Sys em (AZFinTex ) by compa ing AZFinTex ’s
p edic ions agains exis ing quan i a i e unds
and human s ock p icing expe s.
Zhang e al. (2011) desc ibe ea ly wo k
ying o p edic s ock ma ke indica o s such
as Dow Jones, NASDAQ and S&P 500 by
analyzing Twi e pos s. Zhang e al. (2011)
measu ed collec i e hope and ea on each
day and analyzed he co ela ion be ween
hese indices and he s ock ma ke indica o s.
Zhang e al. (2011) ound ha emo ional wee
pe cen age signi i can ly nega i ely co ela ed
wi h Dow Jones, NASDAQ and S&P 500, bu
displayed signi i can posi i e co ela ion o VIX.
Fo uny e al. (2014) discuss how o gain insigh
in o ex -mining-based s ock p ice p edic ion
models in o de o e alua e, alida e and e i ne
he models.
2. Resea ch Design
The main goal o his pape o examines he
pe cep ions o co po a e annual epo use s
owa d in he se e al pe spec i es o IFR. To
da e, ew o p e ious pape s ha e been he
examine pe cep ions and a i udes o use s
o co po a e annual epo and compa e
hem o selec ed aspec s o IFR p o ided by
co po a ions in Malaysia. As a as we awa e,
his is among he i s s udy o e alua e and
compa e he selec ed aspec s o IFR o a ious
use -g oups in Malaysia.
Fo his objec i e we ha e collec ed equi e
da a h ough means o su ey ques ionnai e.
Responden s o his pape we e a co po a e
annual epo use . Mohd Isa (2006) s a ed
ha pe spec i es o annual epo use s
(academicians, business owne s, g adua es,
sha e b oke and o he public use s) a e
amilia wi h i nancial in o ma ion, accoun ing
in o ma ion and ha e knowledge o using he
in o ma ion in he co po a e annual epo . In
addi ion; academics a e selec ed o he p oxy
g oup o he co po a e annual epo use s
in ou pape because hey a e conside ed
o be esponsible o sys em o accoun ing
educa ion (Misheka y & Saudaga an, 2005).
Fu he mo e; audi o s a e selec ed because
hey using he i nancial in o ma ion, i nancial
epo ing and accoun ing in o ma ion o
i nalized he pe o mance o company. Mohd
Isa (2006) indica ed ha ; s uden s belie ed can
be as g oup o co po a e annual epo use s
because o hei academic specializa ion and
backg ound. Bank o i ce s a e ep esen a i es
o a ma ke economy (Mi sheka y &
Saudaga an, 2005). Mo eo e ; manage s we e
selec ed as ano he g oup because hey a e
conside s being esponsible o daily decision
making which in l uence on business p ocess.
(Ba sky & Ca anach, 2011; Moghadam e al.,
2013). The esponden s we e asked o indica e
hei opinions on a i e-poin Like scale
anging om 1 = no impo an a all o 5 = e y
impo an .
The na u e o his pape is explo a o y which
can conduc ed o examine he pe cep ion
o he p elimina y esponden s. We sen
ques ionnai e o he esponden s and a le e
o in oduce o s udy objec i e, con i den iali y
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o he esponden , a s amped add essed
en elope and a ailabili y o su ey esul upon
eques . Ques ionnai e o his s udy is used
o collec hei ideas on di e en IFR aspec s
including; ad an ages, disad an ages, ac o s
and bene i s. Fo examine he impo an o
IFR i ems he pe cep ion su ey o use -g oup
was conduc ed. Tab. 1 shows he esponden s
ques ionnai e which pooled opinions on he
le el o impo ance o each disclosu e i em in
he lis o con en and p esen a ion dimension.
308 ques ionnai es ou o 490 sen we e
e u ned (62.86 pe cen ).
The ques ionnai e o his s udy was
including wo sec ions. The i s sec ion was
ela ed o esponden s’ in o ma ion including
educa ion le el and majo , sex and age. The
second pa consis s o esponden s’ pe cep ion
owa ds ad an ages, disad an ages, ac o s
and bene i s o IFR.
To p o ide he s udy issues in he second
pa o he ques ionnai e, we employed he es
o K uskal-Wallis o he selec ed aspec s o IFR.
The K uskal-Wallis and Mann-Wi hney U es s
we e chosen as being app opia e o es ing he
hypo hesis in sec ion pa o he ques ionnai e
(simila wi h Mi sheka y & Saudaga an, 2005).
Mi sheka y and Saudaga an (2005) s a ed ha
o showing he weigh s o each g oup we e
simila , de e mine i he weigh ings o each g oup
we e simila , Mann-Wi hney U and K uskal-
Wallis es ha e used o es ing hypo hesis. Fo
examine he indi idual in o ma ion i ems such
ques ionnai e which gi e he decision making
pa ies like a s anda d se ing boa d, egula o
and p o essional schola s, a be e insigh
in o ag eemen and desi abili y o di e ence
ha would be be ween use s g oups and
in o each g oup (Mi sheka y & Saudaga an,
2005). The e o e, a K uskal-Wallis es was
used on second pa o he ques ionai e o
es he signi i can di e ences among he
use s o each in o ma ion i em. Fu he mo e,
a Mann-Wi hney U es was ca ied ou o i nd
di e ences be ween use -g oups (Mi sheka y &
Saudaga an, 2005).
3. Resea ch Findings
Acco ding o i ndings o Tab. 2, he pe cen ages
o 308 esponden s, 129 (41.9%) esponden s
we e male and emale we e 179 (58.1%)
esponden s. In e ms o academic quali i ca ion
140 esponden s had he diploma holde s,
deg ee we e 108 esponden s, mas e and
PhD we e 51 and nine espec i ely. 173 o
ou esponden s had 30 yea s, 34 o ou
esponden s we e be ween ages 41 o 50,
89 o esponden s had age be ween 31 o 40
yea s old, and 12 esponden s we e 51 abo e
yea s old. In e ms o academic specializa ion,
majo o 200 esponden s we e accoun ing,
33 esponden s we e i nance, 26 including
accoun ing and i nance, and 36 esponden s
we e business adminis a ion, nine o
esponden s we e in economic majo and ou
esponden s ocused on in es men . In e ms o
o ganiza ion posi ion, 106 o ou esponden s
we e manage s, academics esponden s we e
34, uni e si y s uden s we e 74, 54 wo k as
bank o i ce s (17.5%) and i nally 40 wo k as
audi o (13.0%).
In o de o de e mine he bene i s ha
may acc ue o companies which disclose hei
annual epo s o he public h ough in e ne ,
esponden s asked nine i ems o demons a ed
No. Use G oup Respond
1 Manage 106 ou o 150 = 67%
2 Academic 34 ou o 50 = 68%
3 Bank o i ce 54 ou o 110 = 49%
4 S uden 74 ou o 80 = 93%
5 Audi o 40 ou o 100 = 40%
To al 308 Malaysian esponden s
Sou ce: own esea ch on pe cep ions o In e ne Financial Repo ing
Tab. 1: Dis ibu ion o esponden s
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ag eemen s‘ le el o each i em shown. Tab. 3
ep esen ed; o e all he use s de e mined an
a e age use ulness mean abo e 3.5 o each
o nine i ems which shows all he i ems a e
signi i can and ele an .
Fu he mo e, a ac o eign in es o was
i s choice ollowed by p omo e company
wide o he public, a ac local in es o s,
p o ide wide co e age, a ac po en ial
cus ome s, enhance manage ial e i ciency
and discha ge accoun abili y a e signi i can a
one pe cen , while no i em was signi i can a
i e pe cen . Usually, by disclosing an annual
epo h ough in e ne all use s can access and
analyze he i nancial epo o ha company,
so i he company i nancial epo has a good
backg ound i will a ac o eign in es o s and
he possibili y o inc eased u u e p o i .
Findings o K uskal Wallis es demons a ed
ha ; he e a e di e ences in he use g oups’
pe cep ion abou whe he he appea ance o an
annual epo h ough in e ne would imp o e
he i nancial pe o mance o he company.
The es o Mann Whi ney indica ed ha he
pe cep ion on p epa ed is di e en om he
use pe cep ion. They di e ed based on he
p epa ed pe cep ion du ing p epa a ion o he
annual epo . Use s can ac ually use o he
annual epo s om o he companies as a guide
line o p epa e hei own annual epo ha hey
can hen imp o e and measu e. Subsequen ly,
unlike use pe cep ion hey only use annual
epo o analyze he da a wi hou making
co ec ions o adjus men s so i does no impac
hei pe cep ion ega ding whe he o no i will
imp o e i nancial pe o mance.
Demog aphic I em F equency Pe cen age
(%)
Gende Male 129 41.9
Female 179 58.1
Age < 30 yea s 173 56.2
31-40 yea s 89 28.9
41-50 yea s 34 11.0
51-60 yea s 12 3.9
Academic quali i ca ion Diploma 140 45.5
Deg ee / P o essional 108 35.1
Mas e 51 16.6
PhD 9 2.9
Majo ing Accoun ing 200 64.9
Finance 33 10.7
Accoun ing & Finance 26 8.4
In es men 4 1.3
Economic 9 2.9
Business Adminis a ion 36 11.7
Posi ion in o ganiza ion Academic esponden s 34 11
Uni e si y S uden s 74 24.0
Manage 106 34.4
Bank O i ce 54 17.5
Audi o 40 13.0
Sou ce: own esea ch on pe cep ions o In e ne Financial Repo ing
Tab. 2: P o i le o esponden
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Finally, p omo e anspa ency di e ed om
he p epa e s and use s on he dimension
conce ning bene i o he company. Rega ding
use pe cep ion company disclosu e o hei
annual epo o he public h ough in e ne
is he bes ac ion o allow use s a easie
me hod o analyze he company pe o mance
because o hei anspa ency. Consequen ly,
om p epa e s’ pe cep ion, p omo ion o
anspa ency o he public would inc ease he
secu i y p oblem ega ding he sa e y o hei
annual epo in u u e.
The s udy sough opinions om he
esponden s on he pe cep ion when disclose
annual epo h ough in e ne based on
bene i o use s. The lis o i ems namely
inc ease e i ciency and imeliness in achie ing
inexpensi ely, in o ma ion ega ding i nancial,
makes in es men decision p ocess as e ,
helps use s in he decision making p ocess
and easie , p o ides accessibili y o he use s,
p o ides ano he medium o disclosu e and
in o ma ion o company. The i ndings o his
sec ion we e p esen ed in Tab. 4.
We can see om he able ha six i ems
shown we e conside ed o g ea impo an a
all. Acco ding o his esul s we can p edic
he ac s ha disclose annual epo h ough
in e ne is being bene i cial o use s di ec ly
when hey used i . Thus, he esul ecei ed
shows all i ems a e ele ance and exceed he
mean 4.00 abo e.
Con inuously, in e es ingly he mos
impo an i em om he use s’ pe cep ion was
“inc ease e i ciency and imeliness in achie ing
o i nancial in o ma ion” wi h he highes in
his dimension mean 4.15. This indica es ha
use g oup e y conce n abou imeliness and
e i ciency o ge hei in o ma ion on annual
epo . I is no su p ising because mos o he
use g oup consis s o he wo king people and
some s uden s and hey need he in o ma ion
quickly ul i ll hei pu pose such as hei esea ch
and e c. Thus, he con en in annual epo mus
be upda ed and his is qui e di i cul o p epa e
and measu e i . Howe e , he upda ed annual
epo can a oid complain om use s and
main ain hei epu a ion.
The second mos impo an sou ce o
pe cep ion was make in es men decision
p ocess easie and as e . Acco ding o in es o
pe cep ion o example, he needed o analyze
he pe o mance o he company ha hey
wan o in es . Thus, o hose companies who
ha e enough in o ma ion and always upda e
hei annual epo , i will be easie and as e
o in es o o make decision in in es men o
business o ha company in he u u e. The
I em Mean S d. De . Rank K uskal Wallis es
χ2 Sig.
G ea impo ance
A ac o eign in es o s 4.30 .727 1 24.335 .000**
P omo e company mo e wide o he public 4.24 .754 2 36.183 .000**
A ac local in es o s 4.18 .732 3 26.810 .000**
P o ide wide co e age 4.18 .728 4 26.357 .000**
A ac po en ial cus ome s 4.13 .791 5 18.970 .001**
P omo e anspa ency 4.08 .790 6 9.274 .055
Enhance manage ial e i ciency 4.04 .820 7 30.158 .000**
Discha ge accoun abili y 4.04 .800 8 15.895 .003**
Mode a e impo ance
Imp o e i nancial pe o mance 3.92 .847 9 8.781 .067
Sou ce: own esea ch on pe cep ions o In e ne Financial Repo ing
*sig 5%; **sig 1% (1 = no impo an a all; 5 = e y impo an )
Tab. 3: Bene i s o company
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Finance
i ndings o K uskal Wallis es demons a ed
ha ; ega ding o use g oups ega ding he e
a e no signi i can di e ences among he
pe cep ion ela ed o he use s bene i s and
o he i ems can be classi i ed as ele ance and
signi i can .
This s udy a emp ed o ge opinions om
he esponden s on he signi i can o he
ac o s in l uences companies o p ac ice IFR.
The e a e 11 i ems asked o he esponden
and he esul shows only ou i ems a e
signi i can a one pe cen . Meanwhile, all i ems
a e ele ance wi h exceed mean 3.50 and only
h ee i ems exceed mean 4.00. The esul s
shows all i ems will ca ego ized as g ea
impo ance shown in Tab. 5.
In e es ingly, he mos impo an sou ce
o pe cep ion wi h he highes mean 4.21 is
o enhance co po a e image. I shows ha
company will ge good epu a ion i hey ad e ise
hei annual epo o he public because he
en i e use s can access hei in o ma ion easie
hus con ibu e o enhance co po a e image.
Pe haps, i will a ac people such as a ac
o eign in es o in Tab. 3 when he company
a e known in public. Nex , compe i o in he
indus y would con ibu e company o mo e
compe i i e o announce hei annual epo
h ough in e ne . As we know he main pu pose
o es ablish he company is o minimize he
weal h and make he p o i so o measu e i he
company mus gi e he bes se ice om o he
companies. Thus, compe i o s in he indus y
in l uence he companies he mos o p ac ice
IFR.
The esu ls o K uskal Wallis es ound ha
he e a e signi i can di e ences among use
g oup o hei iew o all he i ems in Tab. 5
and Mann Whi ney es ed illus a ed signi i can
di e ence ega ding he i ems show. The esul
o en i ems a e ca ego ized as signi i can om
he ele en i ems we e asked o he esponden s.
The s udy has also in es iga ed he ac o s
which con ibu ed o companies no p ac icing
IFR. Thus, esponden s we e asked o de e mine
he ex en o which he i ems a e ac o s which
mo i a e companies no o p ac ice IFR. The
ques ionnai e in oduced 11 possible easons
and he i ndings a e p esen ed in Tab. 6.
The Tab. 6 showed ha ; he e a e some
easons p esen ed o esponden s a e deemed
mode a ely impo an and only one i em as
o g ea impo ance. The i s h ee i ems a e
needed o company expe ise, equi ed o keep
upda e in o ma ion and conce n o e secu i y
o in o ma ion. Basically, implemen ing a new
sys em in o he company will incu i nancial
cos s and he equi ed expe ise o de elop
i . Thus, some companies don’ ha e onsi e
s a wi h he expe ise needed o ope a e he
sys em du ing and a e implemen a ion. The
leas impo ance eason was ea o losing
compe i i e ad an age.
The esul s o K uskal Wallis es showed
ha he e a e signi i can di e ence be ween he
use g oups only ega ding he mos impo ance
I em Mean S d. De . Rank K uskal Wallis es
χ2 Sig.
G ea impo ance
P o ides ano he medium o disclosu e 4.03 .715 6 14.403 .006**
P o ides in o ma ion o company,
inexpensi ely 4.10 .841 3 24.803 .000**
Makes in es men decision p ocess easie
& as e 4.13 .788 2 31.120 .000**
P o ides accessibili y o he use s 4.10 .784 4 29.160 .000**
Inc ease e i ciency and imeliness in achie ing
o i nancial in o ma ion 4.15 .770 1 27.547 .000**
Helps use s in he p ocess o decision making 4.06 .831 5 18.891 .001**
Sou ce: own esea ch on pe cep ions o In e ne Financial Repo ing
*sig 5%; **sig 1% (1 = no impo an a all; 5 = e y impo an )
Tab. 4: Bene i s o use s
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2, XX, 2017
Finance
I em Mean S d. De . Rank K uskal Wallis es
χ2 Sig.
G ea impo ance
Imp o e co po a e image 4.21 .751 1 17.222 .002**
Company speake wi h he de elop o
echnology 4.11 .813 2 15.228 .004**
Indus y Compe i o s 4.06 .774 3 20.634 .000**
Mode a e impo ance
Obliga ions o communi y 3.89 .764 4 5.505 .239
S abili y and imp o emen in sha e p ices 3.88 .855 5 17.696 .001**
Recei e go e nmen suppo 3.84 .841 6 7.322 .120
Ob ain unds om wide sou ces 3.82 .825 7 6.620 .177
Di ec o s desi e o engage IFR 3.80 .813 8 2.619 .623
Media a en ion 3.74 .887 9 3.271 .514
P essu es om s akeholde s 3.66 .868 10 3.061 .548
Win awa ds 3.46 .914 11 8.268 .082
Sou ce: own esea ch on pe cep ions o In e ne Financial Repo ing
*sig 5%; **sig 1% (1 = no impo an a all; 5 = e y impo an )
I em Mean S d. De . Rank K uskal Wallis es
χ2Sig.
G ea impo ance
Requi ed expe ise om he company 4.00 .783 1 2.732 .604
Mode a e impo ance
Too cos ly o se up and main ain 3.75 .926 5 2.247 .690
Conce n o e disclosu e o p op ie a y
in o ma ion 3.82 .795 4 6.780 .148
Do no wan o be oo anspa en 3.71 .958 6 7.069 .132
Need o keep in o ma ion upda ed o be o use 3.96 .788 2 9.363 .053
The e a e al e na i e o ms o ob aining
in o ma ion 3.70 .811 7 2.296 .681
Cos incu ed ou weigh bene i s o company 3.71 .958 8 1.655 .799
Po en ial legal liabili y 3.69 .875 9 5.387 .250
Conce n o e secu i y o in o ma ion 3.87 .887 3 3.966 .411
No legal equi emen 3.68 .936 10 15.290 .004**
Fea o losing compe i i e ad an age 3.57 .915 11 8.041 .090
Sou ce: own esea ch on pe cep ions o In e ne Financial Repo ing
*sig 5%; **sig 1% (1 = no impo an a all; 5 = e y impo an )
Tab. 5: Fac o s which in l uence companies o engage IFR
Tab. 6: Fac o s which in l uence a company no o engage IFR
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154 2017, XX, 2
Finance
eason, which is no legal equi emen . As a esul
only one i em which is no legal equi emen is
signi i can a 1%. Mos ly, all he companies a e
e y conce ned abou he secu i y o in o ma ion
and his leads a company o decide no o
p ac ice IFR. E en hough, companies y o
minimize he a ailabili y o sensi i e in o ma ion
abou he company on he in e ne , some imes
o he people can manipula e he da a wi hou
company knowledge.
In o de o de e mine he con en o annual
epo , i is impo an ha companies know he
ad an ages o disad an ages o dis ibu ing
hei annual epo h ough in e ne . This
ac ion is impo an o ensu e ha unexpec ed
p oblems do no a ise la e , and o companies
o be awa e o his po en ial p oblem in ad ance.
As shown in Tab. 7, all se en i ems display an
a e age use ulness mean abo e 3.5 on each o
he ad an ages o IFR. As a esul , esponden
ag ees ha he g ea es ad an age o IFR is
inc eased in o ma ion (downloadable) and
analysis (mean o 4.19). I is because he mo e
in o ma ion abou he company he use has,
he be e will be he analysis o he company.
The i nding shows ha he ad an age
o IFR in e ms o inc eased global each
and mass communica ion came second in
impo ance while na iga ional ease, inc eased
imeliness and up-da e abili y, and in e ac ion
and eedback we e eco ded as he mos
impo an wi h a mean exceeding 4.00. Thus,
all i ems shows signi i can amoun s compa ed
o o he i ems in Tab. 7.
K uskal Wallis es indica ed ha use
g oup di e ed signi i can ly in hei pe cep ion
abou he ad an age o IFR. The Mann Whi ney
es illus a ed ha e e y use has a di e en
pe cep ion ega ding he ad an age o IFR in
ela ion o p esen a ion l exibili y and isibili y
and cos bene i . I is because o he p epa e
hese c i e ia a e s ill signi i can bu o he use ,
i is no he main ad an age o IFR.
The s udy has also in es iga ed he
disad an ages o IFR in e ms o implemen a ion
and shows wha he cons ain deal wi h i .
Thus, he ques ionnai e in oduced six possible
easons and esponden s we e asked o ank
hem based in e ms o impo ance based on
hei pe cep ion and unde s anding. The esul s
a e shown in Tab. 8.
The i nding e ealed ha he six possible
easons in oduced o esponden s we e o
g ea o mode a e impo ance. Only one i em
was ca ego ized as o g ea impo ance namely
secu i y p oblems. As companies, ad e ise
hei annual epo o e he in e ne he da a
a e dange ously expose o anybody ha has
he skill o echnique o des oy he sys em o
sabo age he company o hei pu pose. All
he i ems in Tab. 8 a e s ill ele an when mean
exceeds 3.5.
K uskal Wallis es e ealed signi i can
di e ences be ween he use g oups and he
I em Mean S d. De . Rank K uskal Wallis es
χ2Sig.
G ea impo ance
Global each and mass communica ion 4.17 .755 2 22.776 .000**
In e ac ion and eedback 4.03 .801 5 5.720 .221
Timeliness and up-da e abili y 4.06 .771 4 12.929 .012*
Inc eased in o ma ion (downloadable) and
analysis 4.19 .718 1 12.664 .013
Na iga ional ease 4.09 .763 3 21.356 .000**
Mode a e impo ance
Cos bene i cial 3.91 .822 7 9.795 .044*
P esen a ion l exibili y and isibili y 3.95 .777 6 5.325 .256
Sou ce: own esea ch on pe cep ions o In e ne Financial Repo ing
*sig 5%; **sig 1% (1 = no impo an a all; 5 = e y impo an )
Tab. 7: Ad an ages o IFR
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Mohd Noo Azli Ali Khan, Ph.D.
Uni e si i Teknologi Malaysia
Facul y o Managemen
Depa men o Accoun ing and Finance
[email p o ec ed]
Noo Azizi Ismail, Ph.D.
Uni e si i U a a Malaysia
College o Business
O hman Yeop Abdullah G adua e School
o Business
[email p o ec ed]
Abbas Ma dani, Ph.D.
Uni e si i Teknologi Malaysia
Facul y o Managemen
Depa men o Business Adminis a ion
[email p o ec ed]
Edmundas Kazimie as Za adskas, Ph.D., D Sc.
Vilnius Gediminas Technical Uni e si y
Facul y o Ci il Enginee ing
Resea ch Ins i u e o Sma Building Technologies
[email p o ec ed]
A u as Kaklauskas, Ph.D., D Sc.
Vilnius Gediminas Technical Uni e si y
Facul y o Ci il Enginee ing
Depa men o Cons uc ion Economics
and P ope y Managemen
[email p o ec ed]
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162 2017, XX, 2
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Abs ac
EMPIRICAL RESEARCH OF USERS’ OPINIONS ON SELECTED ASPECTS IN
INTERNET FINANCIAL REPORTING
Mohd Noo Azli Ali Khan, Noo Azizi Ismail, Abbas Ma dani, Edmundas
Kazimie as Za adskas, A u as Kaklauskas
This s udy in es iga es he pe cep ions o use s o co po a e annual epo s in ela ion o selec ed
aspec s o in e ne i nancial epo ing. This s udy also analyzes Web analy ics (Web usage and
Web con en analy ics) o disco e i nancial and non- i nancial usage and con en pa e ns om
company websi es and o he sou ces o Wo ld da a. The case s udies submi ed in his a icle
pa ly demons a es he de eloped Web analy ics sys ems. To se e his pu pose, a ques ionnai e
was dis ibu ed o i e use g oups (academics, s uden s, manage s, bank o i ce s and audi o s).
F om he su ey, he analysis indica es ha a ac ing’s o eign in es o s, p omo ing he company
o a wide public, a ac local in es o s and p omo e wide co e age a e he ou mos impo an
bene i s o IFR o he company. The i ndings e ealed ha h ee main bene i s o he use s who
collec i nancial in o ma ion o companies ia hei websi e a e: inc eases imeliness and e i ciency in
ob aining i nancial in o ma ion, makes in es men decision p ocess easie and as e , and p o ides
in o ma ion abou a company inexpensi ely. P elimina y i ndings sugges ed h ee ac o s ha a e
pe cei ed as impo an by esponding i ms o engage in IFR: enhance co po a e image, company
elle wi h he echnology de elopmen , and compe i o s in he indus y. The i ndings also e ealed
h ee ac o s ha inhibi i ms om engaging in IFR: equi ed expe ise om he company, need
o keep in o ma ion up o da e o be o use and conce n o e secu i y o in o ma ion. The i ndings
also sugges ed inc eased in o ma ion and analysis, and global each and mass communica ion as
he mos impo an ad an ages om i nancial epo ing on he in e ne . On he o he hand, secu i y
p oblems, and cos and expe ise a e he bigges disad an ages o placing i nancial in o ma ion
on he in e ne . Finally, plausible implica ions o he i ndings o he s udy a e hen p esen ed and
a eas o u u e esea ch a e also p oposed. Taken oge he , hese esea ch ou comes make an
inc emen al con ibu ion o he exis ing i nancial epo ing li e a u e by p o iding use ul insigh s in o
ou knowledge o IFR especially o eme ging capi al ma ke s like Malaysia.
Key Wo ds: Use s’ opinions, selec ed aspec s, in e ne i nancial epo ing, web analy ics and
Malaysia.
JEL Classi i ca ion: M4.
DOI: 10.15240/ ul/001/2017-2-011
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