Pan-Pacific Conference XXXIV. Designing New Business Models in Developing Economies

espectively Once market related variables like
informality, corruption or institutions are assessed
in the Delphi exercise, the following five
regression models will be used:
ROA = β0 + β1VAIC + β2CVEM + ε (1)
ROE = β0 + β1VAIC + β2CVEM +ε (2)
EPS = β0 + β1VAIC + β2CVEM +ε (3)
ECIN = β0 + β1VAIC + β2CVEM + ε (4)
MB = β0 + β1VAIC + β2CVEM +ε (5)
Where: β is the vector of coefficients and ε the
error on each equation.
ROA = β0 + β1HCE + β2SCE +β3CEE +
β4CVEM + ε (6)
ROE = β0 + β1HCE + β2SCE +β3CEE +
β4CVEM + ε (7)
EPS = β0 + β1HCE + β2SCE +β3CEE + β4CVEM
+ε (8)
ECIN = β0 + β1HCE + β2SCE +β3CEE +
β4CVEM +ε (9)
MB = β0 + β1HCE + β2SCE +β3CEE + β4CVEM
+ε (10)
Where: β is the vector of coefficients and ε the
error on each equation.
RESEARCH METHODOLOGY
We will apply a quantitative research process, nonexperimental,
that will be longitudinal with a panel
design type, with the purpose of analyzing changes
over time (p. 161). Design in the form of a model
connecting intangible assets proxies as independent
variables and performance indicators as dependent
ones, subject to the way of treatment granted to
some other intervening variables that are typical of
emerging markets, will be suited to achieve the
purpose of the research. There are several
longitudinal studies involving intangible assets
calculations like Rahim et al. (2011) and Mondal
and Ghosh (2013). We will be applying different
techniques that may include, but are not limited to:
1. Control Variables (i.e. size, leverage,
age).(Alipour, 2012); 2. Time Lags (Chen et al.,
2005); 3. Alternative definitions (i.e. SCE).
(Mondal & Ghosh, 2013); 4.Cross Sectional (Firer,
2003) versus longitudinal(Chen et al., 2005);
5.Control Groups. (Zhicheng et al., 2016). 6.
Depending on the data level of the
variables (i.e. market versus company level) we
might be using multilevel techniques as Hierarchical
Linear Models (HLMs) as was originally developed
by Bryk and Raudenbush (1992) and applied in a
longitudinal study for intangible assets by
Andonova, V., and Ruíz-Pava, G. (2016).
FIRM RELATED
INDUSTRY RELATED
MODEL/MARKET RELATED
DEPENDENT VARIABLES
Financial
Performance(ROA,ROE,EPS,ECIN,MB)
Market Value (MV)
Book Value (BV)
H1
Size,Leverage
Industry,R&D Intensity,
Advertisement Intensity
H0
Year, Time Lag ,Growth (IC and
Revenues), Informality,Corruption
and Institutional
Intangible Assets/Intellectual
Capital (VAIC)*;**
INDEPENDENT VARIABLES
Human Capital Efficiency (HCE)**
Structural Capital Efficiency (SCE)**;***
Capital Employed Efficiency (CEE)**
****
* = May include alternative transformation to Δ for VAIC and its
components (Amyulianthy,2015)
**=May include time lags (t-1) for VAIC and its components(Clarke,2011)
***= May include alternative definitions of SC
****= may include additional independent variables as Relations Capital
(RC)
H2
H3
H4
Company level data will be obtained from a
database produced by the information provider,
Bureau Van Dijk, OSIRIS © for the Pacific Alliance
countries (Peru, Chile, Colombia and Mexico) and
a sector that traditionally carry intangible assets,
such as consumer goods (BrandFinance, 2016;
Maverick, 2015; Razafindrambinina & Anggreni,
2008); 3) standardized information from audited
financial statements allows comparisons across the
board. Market related proxies might be obtained
from: Institutions Economic Freedom of the World
reports by Fraser Institute or the Index of Economic
Freedom by the Heritage Foundation (institutions);
ILO time series (Informality) and corruption index
by Transparency International (corruption). This
model is aimed to improve value generation in the
companies and supporting the development of
emerging markets, following what Kaplan et al.
(2004) said and expanding the thesis of De Soto
(2001) to relate to property of other asset types,
apart from physical ones. Therefore, the
contribution of this study will be its focus on
emerging markets, as Firer and Mitchell Williams
(2003) indicated, “considering that traditional
measures continue to dominate, it is important to
determine the extent to which such measures may
intrinsically capture the contribution of intellectual
capital resources and that this is particularly
important in emerging economies that often
have borrowed models from developed
economies”(p. 351).
CONCLUSION
We presented the instrument that will be
approached intended to answer our research
question: What would the best management of
intangible assets model be, for emerging market
companies?. The conclusion of the literature review
leads us towards an instrument that represents a
model for value creation involving intangible assets
in emerging markets. Such model can be built as an
application of the theoretical principles of the
Value Added Intellectual Coefficient (VAIC TM ).
Criticism around this instrument comes from some
alleged theoretical contradictions, and the apparent
mixed results obtained by different authors, who
might be overlooking particular features in the
markets that it has been applied. Therefore, the goal
of this research is going to be to fill this knowledge
gap. We will achieve the research objectives, by
means of a quantitative, longitudinal approach,
testing different database cuts, incorporating more
variables and making the necessary adjustments to
improve the robustness and consistency of the
results and to apply those in a longer time span in
the countries of the Pacific Alliance. The study is
limited to the Consumer Goods Industry in those
countries, but we expect to shed some light for
future research in the area and for the application in
other emerging markets as well.
REFERENCES
References can be provided upon request.
CONTROL VARIABLES EMERGING
MARKETS (CVEM)
Figure 1 Conceptual Framework
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