Research in planning as a design science Planning is not just concerned with understanding the world, but also, and fundamentally, with changing it. Academic research in planning should reflect this fact, which sets it apart from research in most natural and social sciences. These are primarily concerned with comprehending phenomena, and only secondarily and indirectly with influencing them (if at all). In this respect, research in planning appears closer to research in disciplines such as management, law, engineering, or medicine, which, in spite of great differences in their domains of application, are all primarily concerned with how to affect (rather than just describe and explain) their objects of study. Much academic research in planning does not seem, however, to acknowledge this. In this paper, we will argue why we believe so, and propose an approach to academic research in planning that might better reflect its primary concern with changing, rather than just understanding, planning practices. However, first we need to elaborate further on the notion of an orientation of research towards understanding as opposed to an orientation towards change, and on the implications of the difference. In order to distinguish it from the`explanatory science' type of research that all research tends to be identified and compared with, Van Aken (2004; 2005) calls change-oriented research`design science' [inspired by Simon (1969); see also Scho« n (1983)]. What design sciences have in common is the awareness that``understanding a problem is only halfway to solving it. The second step is to develop and test
In both the scientific and the professional communities, the need to integrate transport and land use policies to achieve more sustainable mobility patterns is widely recognized. Three challenges to attaining integrated strategies are identified. The first challenge is to find a common language and concepts that stimulate communication between disciplines. The second challenge is to create more explicit links between broader economic, social, and environmental goals and transport policies. The third challenge is to put more emphasis on policy design, the phase in the planning process in which opportunities for policy integration are maximal but which is poorly supported by current transport planning approaches. Accessibility is a concept that can address all three challenges. It relates to features of the transport system (speed, travel costs) as well as the land use system (densities, opportunities) and can be related to wider goals within society (for example, access to jobs). A well-known and well-studied concept within the scientific literature, accessibility is nonetheless not often used. This paper develops a framework to stimulate the joint design of accessibility-enhancing strategies, and the framework is then tested and developed in cooperation with practitioners in two case studies in the Netherlands.
Adapting cities and region to facilitate car use is not only a technical issue. It has made society heavily car-dependent, increasing the vulnerability of society to adverse changes in social, economic, environmental, or other spheres. This paper analyzes how the spatial context shapes conditions for car dependency, specifically focusing on the case of the Netherlands. Our research shows that, except in the periphery of the country, most daily amenities are within walking or biking distance, both in cities as well as in suburban and rural areas. However, regarding accessibility to jobs, there is no competitive alternative to the car-even in central city areas, which provide many more travel choices. The differences are not only related to population density or land use within the city, as is often thought, but also to the position of the urban area in the regional spatial context (i.e., its location relative to other urban areas). The bicycle as an alternative transport mode to the car scores highest in monocentric urban regions and in the central areas of cities close to a coastline or a national border. Public transport scores highest in central areas of medium-sized cities in polycentric regions and satellite towns near big cities.
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