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Post-contingency draws from contingency studies and their indication that the performance of alternative planning approaches is influenced by the different environmental circumstances encountered. Complexity is in these contingency studies among the criteria used to distinguish between various environmental circumstances. The performance of alternative planning approaches is subsequently considered to depend on the degree of complexity encountered. Counterintuitively, complexity is now approached from a ‘static perspective’. Rather than appreciating complexity from the perspective of a dynamically evolving world, it is then seen as but as a characteristic of a planning situation to be identified and contingently responded to in the ‘here and now’. While such a reading of complexity is arguably simplistic and limited, post-contingency argues it can nevertheless be useful. Post-contingency goes one step further than ‘classic’ contingency studies and their suggestion that the complexity of the environment directly informs planning approaches and organizational formats. Rather, post-contingency considers the role of those involved in decision-making in perceiving, interpreting and responding to complexity. The argument is that both interpreting issues’ complexity and subsequently relating a planning approach to these issues are, at least partly, socially mediated choices. Post-contingency, therefore, argues that complexity is not presented to us planners as an objectified reality, nor that it determines planning choices. Instead, post-contingency highlights notions of perception and choice as essential intervening variables in how policy approaches and organizational formats are adapted to changing conditions of complexity and uncertainty.

Using a complexity lens has not gained widespread attention for explaining why certain planning processes succeed and others fail. This chapter responds by proposing Qualitative Comparative Analysis (QCA) as a method for analyzing the performance of spatial planning processes, taking into account the perceived complexity of the contextual environments encountered. This proposal is rooted in a contingency perspective. Contingency perspectives assume that, for spatial planning approaches and organizational formats to perform well, they should be adapted to the environment in which they intend to operate; i.e., a degree of ‘fit’ is required. The perceived complexity of the contextual environments is among the key arguments contingency studies propose as informing fit. QCA follows this argument, but also responds to some of its main critiques. First, QCA can help avoid a deterministic perspective on complexity informing fit, as it assumes complexity as being conceptualized by stakeholders involved in the planning process. Second, QCA can help overcome a reductionist perspective and its simplistic reliance on a pairwise analysis of relations between isolated environmental variables and isolated organizational or decision-making variables. QCA approaches ‘fit’ from a more holistic perspective, by analyzing the performance of spatial planning processes as configurations of alternative spatial planning approaches, organizational forms, and contextual environments. The result is an understanding of ‘fit’ following what QCA considers ‘complex causality’, which is manifested in configurations of various interacting and interdependent conditions. Next to being able to analyze relationships between the performance of spatial planning processes and the perceived complexity of the contextual environment, by using the notion of ‘complex causality’ QCA also allows for analyzing spatial planning processes as complex adaptive systems.

The debate on urban complexity, and, more specifically, the application of a fractal logic in urban planning and design gained prominence in the late twentieth century. Several researchers have engaged in this theoretical debate, while others have applied this logic within spatial analyses of urban patterns, with the aim of better understanding urban planning effects. Further, some researchers have simulated ‘fractal’ cities. In this chapter, we demonstrate how a multifractal, multiscalar simulation model can be used as a tool for guiding spatial development to enable the identification of potential areas of urbanization and to protect continuous green or unbuilt areas. This simulation model can facilitate the implementation of strategic urban development plans across different scales, ranging from the neighbourhood scale to the regional scale. All scalar levels are interlinked through the application of an iterative logic underlying a multifractal pattern. We demonstrate how this multifractal, multiscalar model can be applied to resolve planning issues.

This chapter is about rationality as a frame of reference for choice, planning and decision-making and that is susceptible to evolutionary and revolutionary tendencies. To begin with, rationality as it is commonly used in today’s planning debate no longer holds and the debate is progressing towards new understandings. This is a rather challenging and perhaps a somewhat controversial statement, knowing that the mainstream planning debate on rationality, communicative action and intersubjective reasoning is already far beyond the traditional, but still dominant, ‘rational choice theory’. This existing planning model positions two rationalities – the technical and the communicative – as opposing and complementary extremes that frame and explain planning behaviour in the governmental domain. Between these extremes, a multitude of realities regarding public choice, planning and decision-making can be assigned, each reality representing a specific course of action. However, to relate public choice, planning and decision-making to the governmental domain only is increasingly perceived as a limitation. Consequently, developments within planning practice require additional and innovative steps outside the existing rationality model for planning behaviour. This chapter proposes a multi-level expansion of the rationality model for planning behaviour. The rise of social movements, civil initiatives and collective action, as well as the ongoing democracy crisis, inspire the idea of seeking rationalities beyond the governmental domain. These new movements, initiatives and actions no longer relate to approaches within the traditional range from command-and-control government to shared governance. Consequently, planners and decision-makers are looking for frames of reference that include processes of self-governance. Building on the concepts of dynamic patterning, co-evolution and multiple layering, taken from the complexity sciences, a new rationality model will be constructed with multiple frames of reference for public choice, planning and decision-making.

Making a suitable career choice is a difficult task. Every year, many adolescents prematurely end their studies, commonly citing “having made the wrong choice” as the main reason. This is a problem, both for the adolescents making these choices, and for society, which bears at least part of the cost of higher education. A thorough understanding of how adolescents make these career choices is essential to identifying the factors responsible for why the wrong choices are often made. Identity development theory emphasizes the role of exploration in career choice, but neglects many of the micro-level processes likely to play an important role. Similarly, traditional decision theory often focuses on optimization of choice, thereby neglecting the cognitive mechanisms that may explain deviations from optimal choice. Here, we present a novel computational approach to modeling long-term decision making. We combine elements of the macro-level theory on identity development with a firm rooting in micro-level cognitive processes. Specifically, we model decision making as an iterative process in which individuals can explore new options or more deeply investigate options that are already under consideration. The output of our model allows us to analyze how the quality of decisions depends on various factors, such as aspiration levels, the tendency to explore new options, and the ability to judge the fit of an option with one’s interests and capabilities. We present some preliminary results that already show our approach can lead to surprising conclusions, encouraging further development of this model in the future.

Adaptive planning has potential as an answer to coping with autonomous and spontaneous change. Such changes occur at all time and recently have been accompanied by an unprecedented dynamism and complexity. The interconnectedness of such processes is only increasing, and their dynamics have an unstoppable effect on almost everything. What seems to us as stable is often not much more than a temporal period of persistence, a frozen momentum within a dynamic world, the lee side of a world in flow. We consider this world to be out of equilibrium. And this is fundamental: while we like to see ourselves – the planner in particular – as the ‘creator’ of space and place, we seriously have to consider a world, as well, which is creating itself without purposeful interventions, develops often beyond our control, and despite our intentions progresses autonomously. These unexpected and unpredictable changes demand a different perspective in which planning will be ‘following’ and ‘responding to’ instead of ‘leading’ and ‘controlling’. Adaptive planning stands out in the search for alternatives to cope with these changes. Various kinds of adaptive planning will be identified in this chapter. We will explore their relationship with the current planning debate and its paradigmatic rationalities, i.e. the technical and the communicative rationality. We will extend the contemporary rationality framework for planning behaviour with several rationalities that each could be a ‘frame of reference’ for adaptive behaviour dealing with wide-ranging situations in a dynamically changing and transformative environment. This results in an extensive rationality framework for planning behaviour, which presents various new forms of adaptive planning and offers a vastly expanded world of planning possibilities!

Change occurs at all times. However, current changes are accompanied by an unprecedented dynamism and complexity. It is a consequence of an enormous and increasing rate at which new developments emerge, developments with a global nature that are also completely interwoven with the local environment, such as the internet, social media, economic uncertainty and the energy transition. The interconnectedness of these processes is only increasing, and their dynamics have an unstoppable effect on almost everything. Societal processes are part of a dynamism in which connections that are deemed relevant, the intended approaches and the targeted processes that were embraced yesterday and still feel familiar today, could very well be entirely outdated by tomorrow. These are the circumstances that spatial planning is confronted with. Planning can no longer afford to ignore fundamental uncertainties. Key is how planning can relate to change in a way that is different from before. Adaptivity is often mentioned as the answer to increasing uncertainty, societal dynamism and spatial transformation. It is then about the way in which planning is able to respond to unforeseen, autonomous or spontaneously occurring changes (acting in response to change), the way in which planning is able to influence such changes (addressing the possibility to change) and how planning may increase the options for dealing with change (capacity to perform in moments of change). Based on this distinction, various forms of adaptive planning will be presented that together offer a world of planning opportunities.