Knowledge and Learning in Complex Urban Renewal Projects; Towards a Process Design



Learning in urban renewal - PhD project Janneke van Bemmel OTB Delft

shared in the form of data, manuals and the like. Implicit knowledge is highly personal and hard to
capture in forma language and documents. Implicit knowledge is rooted in actions, routines, ideals
and values (Polanyi, 1958).

Learning means the enrichment of existing knowledge and the creation of new knowledge.
There is growing consensus amongst contemporary theorists on organizational learning that learning
is possible only when individuals are learning; organizations as such are incapable of learning (Senge,
1990; Simon, 1991; Weggeman, 2000). Simon explains this point of view as follows (1991):
“All
learning takes place inside individual human heads; an organization learns only in two ways: (a) by
the learning of its members, or (b) by ingesting new members who have knowledge the organization
didn’t previously have.”
However, when organizations are viewed as collections of people that, to a
certain extent, pursue the same goals, then there can be individual and collective learning processes
within these organizations.

There are six steps that make up organisational learning processes (Weggeman, 2000):
formulation of the vision, goals and strategy of the organisation; determine which knowledge is
needed and which is available to realise the strategy; the development of knowledge; the sharing of
knowledge; the application of knowledge; and the evaluation of knowledge.

Figure 2. Learning as a cyclical process

Source: Based on Weggeman (2000:152)

To investigate how new knowledge is created in urban renewal networks, can be done by
looking at for instance doing research, hiring experts, or experimenting. The sharing of knowledge is
studied by mapping which people share which knowledge with whom and why. The use of knowledge
is examined by looking at to what extent the knowledge available in urban renewal networks is
actually used when decisions are made. The evaluation of knowledge is considered by looking at the
occurrence of moments of reflection, like evaluation meetings.

The learning organisation ideal provides helpful insights for improving performance in policy
networks; however, a range of features specific for policy networks must be reckoned with (see also
Smith and Taylor, 2000). These features are, amongst others, ambiguity over the problem definition
and ambiguity over purposes and means, as described earlier. This means that learning in policy
networks also involves a collective
interpretation process during which the policy problem is
interpreted and
ambiguity is reduced. Different actors have different values, perceptions and interest,

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