Proceedings of the 12th European Conference on Knowledge ...

Eduardo Rodriguez, John Edwards and Angel Facundo
Marketing or
organisational Marketing or Product or
Manufacturing
& Product or organisational process
process
innovation
innovation only innovation only
Germany 54 22 7
South Africa (2002-04) 45 10 21
Luxembourg 38 20 12
Belgium 41 13 14
Estonia 39 12 16
Aus tria 41 15 11
Japan (1999-2001) 22 40 4
United Kingdom 29 17 19
Ireland 32 7 24
Denmark 41 12 8
Australia (2006-07) 36 7 18
Portugal 32 21 7
Iceland (2002-04) 31 7 20
Finland 36 6 16
Ne<strong>the</strong>rlands 23 10 20
Italy 21 16 16
Czech Republic 24 12 12
Spain 21 12 14
Norway 22 15 9
Chile 25 7 7
Korea (2005-07) 16 3 17
Table 2-6 Types <strong>of</strong> innovation (Source OECD 2010)
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3. Leverage on Knowledge Management to mitigate risk
The first part <strong>of</strong> this section introduces <strong>the</strong> terms used for <strong>the</strong> academic program based on intelligence
approaches. The second part introduces <strong>the</strong> KM concepts that support <strong>the</strong> integration <strong>of</strong> <strong>the</strong> research
lines. The concept <strong>of</strong> a unique intelligence, a unique way <strong>of</strong> seeing <strong>the</strong> intelligence and a single
measurement has changed, and <strong>the</strong> <strong>the</strong>mes <strong>of</strong> intelligence are involved in multiple fields <strong>of</strong> human
activity. Based on leveraging individuals’ intelligence and <strong>the</strong>ir work in organizations and
communities, <strong>the</strong> proposed doctoral program in KM is based on <strong>the</strong> following views:
3.1 Knowledge Management and Artificial Intelligence
The study <strong>of</strong> human intelligence and its applications in improving <strong>the</strong> learning <strong>of</strong> human expertise
through automation <strong>of</strong> intelligent behavior (Luger and Stubblefield 1993), reasoning, recognizing
patterns, acquiring and retaining knowledge for solving problems (Min 2010) falls in <strong>the</strong> field <strong>of</strong>
artificial intelligence developments. Artificial intelligence (AI) focuses on <strong>the</strong> simulation <strong>of</strong> natural
intelligence, taking as a paradigm human intelligence and behavior (Turing, 1950) and introduces
some methodological and for analysing questions about intelligence. Knowledge creation through
data mining techniques, some decision support systems for making decisions and new technologies
for inference provide value to <strong>the</strong> organization
3.2 Knowledge Management and Collective Intelligence
Within <strong>the</strong> social sciences and computer science, surrounding what today is known as collective
intelligence (Levy 1997) and following various trends ranging from <strong>the</strong> analysis <strong>of</strong> social interactions
and networks <strong>of</strong> cyber-culture to cyber-societies, and even tries to create a new anthropology (Levy
1997) or new mechanisms and forms <strong>of</strong> social behavior (Noubel, 2004) or <strong>the</strong> creation <strong>of</strong> a global
brain (Bloom, 1995).
The behavior <strong>of</strong> a group is not <strong>the</strong> sum <strong>of</strong> individual behaviors, but <strong>the</strong> integration <strong>of</strong> individuals into a
whole. A well-integrated human group shows traits <strong>of</strong> intelligence that may be higher than that <strong>of</strong>
groups with ‘smarter’ members who may be acting clumsily. This leads to <strong>the</strong> <strong>the</strong>ory <strong>of</strong> intelligent
organizations, collective intelligence and learning organizations.
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