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



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

INTRODUCTION

Today’s network society (Castells, 1996) is characterised by high levels of complexity and insecurity
due to, amongst others, globalisation and an increased speed of (technological) developments. This is
not a new perspective, many authors have argued that society is changing faster and becomes more
complex and turbulent (Drucker, 1969; Galbraith, 1977, Emery and Trist, 1965; Michael, 1973). This
has implications for planning processes and practice; it has become difficult to predict what the future
holds and it is unclear which actions will lead to which results. Therefore, an important challenge for
planning practice is to understand and manage
uncertainty. This uncertainty results from the social
environment or planning context, as well as from the planning process itself (Abbot, 2005). The
simplistic views of linear causality, the ability to predict, control and manipulate are a thing of the
past, present-day characteristics of planning practice are uncertainty, networks, connection,
interdependence, and survival and development through adaptation and change (Morrison, 2005).

These new key words all apply to contemporary large-scale, long-term urban renewal
processes, which are complex and uncertain and take place in networks of interdependent partners.
Urban renewal projects are complex because many actors are involved, the goals and strategies of
these actors can change over time, and contextual factors (such as the housing market, residents´
wishes, the political direction) change constantly. This creates a lot of uncertainty in urban renewal;
uncertainty about knowledge and values (substantive uncertainty), uncertainty about the intentions
and strategies of the parties involved (strategic uncertainty), and uncertainty about when, where and
by whom decisions are made (institutional uncertainty). (Koppenjan and Klijn, 2004)

The high level of uncertainty of urban renewal processes means that there are new demands
for the way the planning processes are organized, and the application of knowledge, plans and
designs in decision-making. Several authors emphasize that
learning is of vital importance for
successful planning processes that are complex and uncertain (e.g. Faludi, 2000; Korthals Altes, 2002;
Klijn, 2003; Van der Schaar, 2005). Learning in urban renewal networks helps to respond to changes
regarding the content of urban renewal plans, the strategies of the parties involved, and the
institutions in which the decision-making process takes place. Learning can be defined as the creation
of knowledge that is applicable in the activities of the parties involved (Argyris and Schon, 1996).

Another reason for increasing learning in urban renewal stems from the idea that the
management strategy for
knowledge work is not top down control but knowledge management and
the facilitation of learning (Weggeman, 2000). People working in the early stages of the urban
renewal process are professionals that carry out knowledge work. Drawing up plans, making designs,
decision making; these are knowledge intensive task. When the creation, sharing and application of
knowledge during these tasks is increased, it can be assumed that the quality of the work is higher.

Studying urban renewal processes from a learning perspective is a relatively new approach. A
limited amount of studies has been done that have a strong relation with the topic. Examples are
Goldfarb’s study on evaluation of urban renewal programs that takes ‘learning by doing’ into account
(Goldfarb, 1975), Healy’s study on the kinds of knowledge used in planning practice (Healey, 1992)
and Van Herzele’s study on the use of local knowledge in planning processes (Van Herzele, 2004).



More intriguing information

1. The name is absent
2. The name is absent
3. Modelling the Effects of Public Support to Small Firms in the UK - Paradise Gained?
4. The name is absent
5. The name is absent
6. Federal Tax-Transfer Policy and Intergovernmental Pre-Commitment
7. Evidence of coevolution in multi-objective evolutionary algorithms
8. Competition In or For the Field: Which is Better
9. The Shepherd Sinfonia
10. The name is absent
11. Clinical Teaching and OSCE in Pediatrics
12. A dynamic approach to the tendency of industries to cluster
13. Food Prices and Overweight Patterns in Italy
14. The Nobel Memorial Prize for Robert F. Engle
15. CREDIT SCORING, LOAN PRICING, AND FARM BUSINESS PERFORMANCE
16. The name is absent
17. Towards a Mirror System for the Development of Socially-Mediated Skills
18. Importing Feminist Criticism
19. New issues in Indian macro policy.
20. The name is absent