Proceedings of the 3rd European Conference on Intellectual Capital

Organisational structure Level <strong>of</strong> management:
technology
Intangibles Theoretical justification
Client Portfolio
Image and International
Institutional Relations
Innovation, Research and
Development
Social and Environmental
Responsibility
Víctor Raúl López Ruiz et al.
firms as <strong>of</strong> 31st
December
Relational or Trade Capital
Product brand name
quality
Line index: adjusted mobile and
land lines/inhabitant
Indicators
Internet users per 100
inhabitants
Absolute (AI) Efficiency (EI)
Trade balance in goods
and services
Marketing or Image Capital
Internal image
External image
Foreign direct
investment
Research, Development and Innovation Capital
Level <strong>of</strong> innovation and
development Investment in R&D&i
Technological level
(UNESCO)
Social and Enviornmental Capital
Environment
Sustainability
Quality <strong>of</strong> life, welfare
society
Health expenditure
(WHO)
Source: own elaboration. Note: Sources in brackets if not WBG.
High Technology Export Index
1-Development aid index
GDP Ranking
Life Expectancy Index
Travel and Tourism
Infrastructure Index (WEF)
Line Index: adjusted mobile
and land lines/inhabitant
Internet users per 100
inhabitants
CO2 emissions per capita
Hectares <strong>of</strong> green
areas/habitant
Life Expectancy Index
Access to health system in
rural areas
Access to water
The latter filter book expenditure included by <strong>the</strong> national government in <strong>the</strong> budget or its market
value, according to <strong>the</strong> objective efficiency recorded and equation 4 below. Expense filtering was
inspired by <strong>the</strong> process presented for Skandia Navigator by Edvinsson and Malone (1997), later
modified in Integrated Analysis method by López and Nevado (2006).
C
m
c 1
AI
c
EI c
(4)
Where human or structural capitals (C) are estimated by one or more absolute indicators m, filtered
by k efficiency indicators and syn<strong>the</strong>sized into only one indicator, weighted in accordance with a
subjective weighting w. The procedure followed to allocate weights to efficiency indicators is based on
<strong>the</strong> development <strong>of</strong> a principal component analysis (PCA) that makes it possible to assign weights to
each indicator highly objectively. More specifically, bearing in mind that it is impossible to directly
assign weights to each efficiency indicator, we proceeded to transform <strong>the</strong>m into <strong>the</strong> same number <strong>of</strong>
principal components (PC) as indicators available:
PC
ic
k
i 1
u x
i
i
Where ui are <strong>the</strong> characteristic vectors <strong>of</strong> each principal component and xi <strong>the</strong> variables used to make
<strong>the</strong> efficiency indicators. Once <strong>the</strong>se components have been obtained, we proceeded to build one
indicator <strong>of</strong> efficiency by weighting each component in accordance with <strong>the</strong> percentage <strong>of</strong> variance
retained by each.
191
(5)