Proceedings of the 8th International Conference on Intellectual ...

Maria Cristina Morariu
economy and will assist to determine if Romanian firms appear to continue to rely on traditional
business practices or are shifting toward a greater reliance on IC factors in determining company’s
performance.
In order to achieve our objectives, <strong>the</strong> remainder <strong>of</strong> <strong>the</strong> present paper is organized as follows. Next
section discusses <strong>the</strong>oretical review and develops a series <strong>of</strong> empirically testable hypo<strong>the</strong>sis. Based
on section 2, Section 3 describes <strong>the</strong> research method. The empirical results and analysis are
discussed in section 4. The final section is by way <strong>of</strong> summary and conclusion and it ends <strong>the</strong> paper
with <strong>the</strong> ideas for future research directions.
2. Literature review
2.1 IC models
There have been developed a variety <strong>of</strong> methodologies for measuring intangible assets that are
classified according to different criteria (Sullivan, 1998; Sveiby, 2010). Herein we shall discuss some
<strong>of</strong> <strong>the</strong> selected approaches in terms <strong>of</strong> <strong>the</strong>ir strengths, weaknesses and reliability.
Balance Scorecard, proposed by Kaplan and Norton (1992), sets financial and non-financial
measures to indicate four perspectives: (1) financials; (2) customers; (3) internal process; and (4)
leaning and growth. It provides for <strong>the</strong> control <strong>of</strong> intangibles while simultaneously monitoring financial
results. It is very company specific and thus does not have general application and make comparison
impossible. Additionally, it is unable to assign a financial value for <strong>the</strong> intellectual assets in an
objective manner.
Skandia Navigator was proposed by Edvinsson and Malone (1997) and provides supplementary
information to annual financial reports. It focuses on non-financial measures covering five
components: (1) financial; (2) customer; (3) process; (4) renewal and development; and (5) human. It
recognizes <strong>the</strong> role <strong>of</strong> customer capital in creating value. Still, it uses proxy measures to track trends
in <strong>the</strong> assumed VA, can be monotonous and suffers <strong>of</strong> subjectivity and thus affecting comparability.
Intangible Asset Monitor was proposed by Sveiby (1997). It provides strategic information <strong>of</strong> <strong>the</strong> firm
concerning: (1) growth; (2) renewal; (3) efficiency; (4) stability; and (5) risk. Invisible assets are
matched on <strong>the</strong> financing side <strong>of</strong> <strong>the</strong> balance sheet by equally invisible finance, most <strong>of</strong> which are in
<strong>the</strong> form <strong>of</strong> invisible equity. Still, it is difficult to assign monetary financial values to <strong>the</strong> final measure
and it suffers <strong>the</strong> problems <strong>of</strong> subjectivity, thus making comparison difficult (Bontis, 2001).
CIV was developed and popularized in <strong>the</strong> year 1997 by Thomas Stewart (Titova, 2011). It is a
standardized and consistent basis <strong>of</strong> measure, <strong>the</strong>reby, better enabling <strong>the</strong> effective conduct <strong>of</strong> an
international comparative analysis, but for its calculation it needs average return on assets in <strong>the</strong>
industry, that sometimes is difficult to find; additionally, subjectitivity associated with <strong>the</strong>ir underlying
indicators and, <strong>the</strong>re are difficulties in verifying information used in calculating indicators comprising
o<strong>the</strong>r IC measures.
VAICTM was introduced by Pulic (2000). VAICTM model provides information regarding value
creation efficiency from company’s tangible and intangible assets. The drawbacks <strong>of</strong> this model are
<strong>the</strong> use <strong>of</strong> basic financial information in <strong>the</strong>ir composition; measurement for SC may be incomplete;
subjectitivity associated with underlying indicators and, difficulties in verifying information used in
calculating indicators comprising o<strong>the</strong>r IC measures.
Considering <strong>the</strong> advantages and limitations <strong>of</strong> <strong>the</strong> above models, it seems that no one model is
“perfect”. Never<strong>the</strong>less, as will be shown below, VAICTM has been widely applied to o<strong>the</strong>r research
studies for measuring IC. According to <strong>the</strong>se researchers, this model produces quantifiable, objective
and quantitative measurements. It can be easily applied by someone external to <strong>the</strong> company. Last
but not least <strong>the</strong> model was used in several studies conducted in emerging economies. Therefore, in
order to allow comparison between studies, <strong>the</strong> selection for this model in Romanian context is
justifiable.
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