Jenni Partanen & Sirkku Wallin

Abstract

Cities are becoming increasingly complex in both form and function, while the planning system retains the rational top-down mode – assuming that urbanity is predictable. However, complexity thinking affords a promising perspective on cities as uncertain and dissipative, bottom-up organizing systems.

Emerging from social sciences, the methodology of communicative approaches in urban planning is mainly qualitative, while the origin of complexity thinking is in natural sciences, relying on quantitative methods. In both discourses the concept of self-organisation in particular occurs constantly. Regarding their backgrounds, the approaches in urban planning research typically differ from each other rendering the use of the concept unclear and thereby limiting its overall applicability.

In this paper we seek to explore concepts of self-organisation and urban complexity in two different kinds of urban analyses, and to build a shared understanding which supports urban planning and development endeavours in practice.

Introduction

The traditional planning system, with intrinsic reliance on rationality, predictability and control often collides with the enormous complexity of cities.  Urban processes often emerge from interaction between individuals or organisations. In recent decades various ways to acknowledge human interaction have been adopted in urban planning to tackle the problem. This is often referred to as the communicative shift in planning. However, the multifaceted perspective on urban self-organisation remains limited, usually manifest in either reduced statistical or spatial analyses, or participatory practices. More agile and adaptive planning systems and related research methodologies are required to respond to the variety of self-organizing urban processes (e.g. Rantanen & Joutsiniemi 2016; Partanen 2018; Wallin 2015).

In the processes of interrelated and unexpected urban changes in particular, or in those concerning local patterns of urban development, statistical and spatial analysis, or participatory practices may not yield a complete picture of the complex situation. This paper builds on a perspective of local urban planning and development, in which research methodologies do not always support the sense-making in practice.

The planning approach, along with data analysis and simulation tools, building on theories of complex systems provides a promising approach for managing uncertainty, bottom-up organisation and urban change in cities. This progress embraces qualitative as well as quantitative approaches to complexity and planning (e.g. de Roo et al. 2012, Portugali et al. 2012). Practical applications are in progress, applying quantitative methods from complexity thinking originating in natural sciences and qualitative planning research methods emerging from social sciences. The methods share a similar vocabulary, notably the concept of self-organisation. However, methodological differences cause inconsistent use of the concepts, thereby limiting discussion across disciplines.

In this paper we propose different definitions for self-organisation, first by conceptualizing the ontological and epistemological characteristics (and challenges) of qualitative, ‘soft’, and quantitative, ‘hard’, approaches in urban complexity research.

We argue for a more coherent understanding of self-organisation by adopting a variety of methods and tools, and overcoming the dualism of soft and hard approaches. We suggest that a conceptual frame of emergence provides planning practice with a new perspective on this dilemma by perceiving the two as logically continuous yet separate ways to contemplate self-organizing systems. This would entail adopting different methodologies through smooth, continuous triangulation, enabling a shared conceptualization of the key urban factors and complex dynamics.

We revert to two existing case studies applying different research methodologies. We discuss their contribution to understanding the local urban development and planning. Specifically, we ask how self-organisation in soft and hard methodologies can be understood in a complementary manner that supports multifaceted urban development and planning in practice.

Both case studies are part of our doctoral dissertations addressing respectively urban development on a local level, achieving similar research outcomes with completely different methodological approaches. The first case study is a quantitative analysis of self-organizing economic actors in the Nekala neighbourhood of the Finnish city of Tampere. The second one comprises a qualitative analysis on self-organizing urban development in the Herttoniemi neighbourhood of Helsinki. The case studies represent the different ends of the methodological spectrum in urban planning research, describing and analysing spontaneously occurring local urban development, and producing knowledge for actual planning.

First, we introduce the key concepts and their empirical methodological varieties. We then analyse our cases and, reflecting on the experiences, highlight shared research solutions applicable in urban planning. We conclude the paper by answering the research questions.

A conceptual frame for bridging hard and soft

What is urban complexity?

Theories of complex systems appear in scientific discourse as an umbrella concept. Emerging in natural sciences starting from the 1970s, these distinct theories range from the study of fractals, chaos and dynamic systems to self-organisation and scaling. Overall, they address specific dynamic systems, evincing typical features: shifting balance between periods of predictable and non-equilibrium behaviour causing different qualitative states; unpredictability; nonlinearity and dissipative decision-making among interconnected actors (Casti 1997; Mitchell 2009).   Complexity has recently been established, for example, in social sciences, economics and psychology (ibid.; Allen 2012). Regarding cities, complexity helps to understand the role of unpredictability in seemingly autonomous, dynamic urban processes, and to develop guiding methods for urban change (Portugali et al. 2012; de Roo et al. 2012).

The ‘classical’, quantitative complexity methods including scalarity, fractality or dynamic simulations are widely applied in urban research. In addition, complexity sciences have been enriched by reflecting back from empiria to theory, accepting the limitations of formal mathematical models in human systems (e.g. Cottineau et al. 2015).  Despite the emphases on quantitative methods, a variety of qualitative complexity approaches is also emerging (de Roo et al. 2012; Wallin 2013). Beyond methodology, the power of complexity is also in urban planning (Baynes 2009). Novel complexity planning methods and applications are proliferating. While becoming more feasible and empirically grounded, they provide new applications for both strategic and land use planning (see e.g. de Roo et al. 2012, Portugali et al. 2012; Partanen 2016).

Complexity challenges the very foundations of alleged stasis and equilibrium in society. New modes of production, transportation and communication, therefore, are surprising revolutions that change the system qualitatively, allowing the emergence of new forms of living – and a (temporary) steady systemic state. In complexity thinking, the mechanism responsible for both ‘dynamic stability’ and reorganisation of the system is called self-organisation. In the following we concentrate on this concept, exploring definitions from the perspective of complex urban systems on participatory urban planning.

Self-organisation in ‘hard’ and ‘soft’ sciences

Self-organisation as a mechanism

Self-organisation is common in natural open complex systems, as multiple agents (living or inanimate) interact, producing unintentional order without guidance from outside the system. For example, the functioning of the brain, animal flocking and molecular organisation follow this mechanism (Casti 1994; Kauffman 1995). Ground-breaking studies from the 1970s influencing the concept include dissipative structures, synergetics and autopoiesis introduced by Prigogine, Haken and Varela et al. (Mitchell 2009; Partanen 2015).

In cities, households or firms seeking for optimal locations for residence or business generate self-organizing, spontaneous patterns (economic clustering, gentrification, segregation) within border conditions (laws, regulations) and feedback from the resulting pattern. In that sense, self-organisation often benefits actors (as in activity clusters or innovation networks).

Urban patterns, for example in mobility, housing, cultural interaction and organisations, change constantly. As complex systems they can be described, analysed and modelled, but not predicted or steered (Allen 2012; Alfasi & Portugali 2007). Therefore the main task of planning is still to reduce negative impacts causing social inequality or economic degradation.

Originating in the natural sciences and building on system thinking, research on self-organisation in complex urban systems (both theoretical and methodological) is traditionally quantitative, analysing emerging patterns from agents’ interaction measuring systemic properties (e.g. fractality and power laws, phase transitions) and simulation. In the natural scientific literature the typical requirements for self-organisation usually include the following: open system, far-from-equilibrium (critical state) and complexity. Furthermore, a constant ‘flow of energy’ generates interaction between many agents, thereby producing patterns which are not guided from outside the system. These patterns, along with other border conditions (including laws and regulations in cities) provide feedback and ‘control’ the agents. This process operates in both directions throughout scales. Usually the system also increases in complexity over time due to self-organisation. The system is multistable and resilient and evolves through qualitative transitions (Allen 2012; Kauffman 1995; Partanen 2015).

The quantitative analysis is based on statistical data, and it often fails to paint the overall picture of the complete meshwork of human interaction.  While the forecasting of a complex system is by default impossible, particularly the inductive and indicative quantitative methodologies are limited in regard to the endeavours, intentions and actions of human agents and stakeholders.  We need to acknowledge that society is a meshwork of interest groups, networks, organisations and units with separate minds and tasks (Putnam 1995; Lin 2001; Rhodes 1997).

Self-organisation as human interaction

The patterns originated and deployed by stakeholders are recognized both in complexity thinking (Batty 2010; Allen 2004) and in urban governance research (Rauws 2016; Boonstra 2015). They find a counterpart in recently evolved participatory urban planning, which arises from post-structuralist geography and from evolutionary and actor-initiated planning (Murdoch 2006; Hillier 2007; 2010; Boelens 2009). Instead of conflicts between stakeholders, as in the communicative approach (e.g. Forester 1998; Innes & Booher 2010), the interest is in spatial and behavioural patterns, which accelerate urban actions.

The perspective of participatory urban planning has since the 1960s addressed actors and stakeholders and their actions, and emphasized qualitative approaches. Methodologies have been applied from the fields of sociology, psychology, geography and management studies. Most of the participatory urban planning research serves planning processes in actual spatial and land use planning (Taylor 1998; Healey 1997). Since the communicative turn, the discipline has promoted sense-making based on dialectical rather than purely inductive or deductive reasoning. Due to the procedural nature of participatory planning research, it has difficulties reaching conclusions beyond the case studies it promotes. Also, like urban planning practice itself, participatory urban planning research has suffered from top-down inertia. The research design follows the linear logics of administration and planners, not the patterns of the stakeholders and agents it seeks to address.

Thus the participatory urban planning definition of self-organisation as a social movement or a joint action of stakeholders is often related to urban governance and local urban development outside the formal planning processes and public participation. Due to its difficulties to comprehend urban development occurring outside the actual planning process, self-organisation has provided a comprehensive definition for this. (Boonstra & Boelens 2011).

In recent studies self-organized production of urban space and functions has taken place through activism, first on a local level, and later on regional or even global level. There are ad hoc urban movements in which community engagement has turned into a strategic endeavour and eventually a pattern to change urban policies and space (Hernberg 2013; Berglund & Kohtala 2014; Faehnle & al. 2016). For example, in a movement called Tactical Urbanism, local residents have claimed their streets for pedestrian use in large metropolitan cities of the USA. Their manifestations were well suited to the official planning endeavours addressing new urbanism and they have turned into experimentations in new urban development and regeneration (Lydon & Garcia 2015).

The research on urban activism and local development is very much in line with the former disciplines of urban planning. Self-organisation has been considered to be a promoter of urban change in studies on urban planning and sociology since the 1960s. American scholars have criticized spatial planning for being a vehicle of exclusive social reform and provided inclusive evidence that urban development enhanced by social movements and local activism would improve the urban environment and also social inclusion (Jacobs 1961; Gans 1968). According to them, planners should have a great interest in the everyday lives of citizens and their endeavours. People’s habits, preferences and attitudes concerning their living environment are just as important as their demographic and geographic distribution in space (Manzo & Perkins 2006).

The validity of planning research is not dependent solely on scientific achievement; it comes within the planning context in which the outcomes of research are utilized.  Planners designated to organize formal public participation often ignore or criticize citizens’ self-organisation. Even while providing a source of local knowledge, unmanaged civil engagement, and even formal non-governmental organisations would improve the procedure of public participation (Innes & Booher 2010). Analysis of urban self-organisation can provide civil servants and policy-makers with valuable information just as do official polls and surveys in public participation procedures (Batty 2010). For example, PPGIS tools and other sophisticated e-planning instruments make available data on people’s everyday lives (Saad-Sulonen 2013; Kahila-Tani 2015).

For a better conceptual understanding of human interaction and local urban patterns, various types of civic engagement need to be acknowledged (Wallin 2015; Wallin 2018 (forthcoming)); including public participation (Innes & Booher 2010; Healey 1997), self-organisation (Boelens & Boonstra 2011; Hamdi 2004) and everyday life practices (Kuoppa 2016). These tend to be mutually supportive. Everyday life practices provide the plinth of mobility, social interaction and networking patterns. They are a manifestation of individual prospects and shared contingency. Limited local affordances restrain inhabitants. Thus, self-organisation relies on the physical, social and psychological capabilities to which people have access.

Analysis of urban complexity and local development: Two sides of the same coin

In this section we present two examples of hard and soft approaches to self-organizing local urban development. The case studies have something in common with urban morphology and with geographical position as a part of a larger city region. Their change patterns eventually also proved very similar. This was unintentional, as the case studies used utterly different research designs and methodologies.

The case of Nekala: a quantitative analysis of local economic self-organisation

First, we scrutinize the findings of a research project (Partanen 2018; 2015 and Partanen & Joutsiniemi 2015) concerning an old industrial area in the city of Tampere, Finland. The Nekala neighbourhood was planned in the 1930s for heavy industry and processing of agrarian products, but it has subsequently transformed into an economically and culturally diverse urban area.  As a centrally located area, it seems to have adapted to the societal and economic changes. Nekala provides today a vital seedbed for many knowledge-based and cultural actors, commercial and public services, warehouses and industry.

The Nekala study used a classical quantitative, natural scientific method to study self-organisation. It explored whether clustering of similar actors was a prevalent mechanism producing continuous, emergent dynamics in the area. The aim was to build a dynamic model based on the self-organizing actor interactions. The study explored general indicators of urban self-organisation, such as traffic flows, increasing complexity and internal order, applying in particular GIS data on uses, thereby enabling the emergence of dynamic, unplanned activity clusters. Clusters form autonomously, as similar actors – retail units, services and industries – gravitate to each other to benefit from each other’s proximity¹. Clusters were defined according to their geographical proximity using the original definitions of self-organisation in natural sciences and earlier studies.

The results proved that actors formed clusters in a self-organizing manner, which was validated using a scaling method. Next, for purposes of elimination, we scrutinized clustering against other factors that may have affected it in addition to mutual attraction. These were the plan, the age of the buildings and potential local externalities. The most interesting findings were the discovery of novel, previously invisible statistical and spatial patterns of self-organisation indicating the multifaceted nature of the phenomenon². These patterns were systematic and apparently resulted from self-organisation, with no other explanatory factor. The area appears capable of renewing itself through self-organisation without any actual input from land use planning.

The results demand that actors’ location preferences be respected in planning. Not only should we try to better understand the role of self-organisation in the renewal of urban systems but also to recognize their mechanisms and complex interactions. Positive self-organisation could support the prosperity of the city and its cultural and social networks, as long as negative effects are restricted (e.g. negative spirals, distorted power asymmetries). In a larger economic landscape, coincidentally, Nekala has turned by chance into an experimental field for autonomous urban progress: it is one of the areas in the city awaiting future major planning decisions, and is hence currently lacking active development and investments (Kuusela & Partanen 2017). At the same time, this study also indicated that such conscious, limited ‘non-planning’ could be fruitful in certain urban areas, if not overall: if it works, why fix it?

There were also some pitfalls in this methodological approach. The quantitative studies managed to pinpoint emerging spatial patterns, clusters, as a result of agent behaviour, of which they probably do not have complete information themselves, despite acting intentionally. Also, the scope is naturally limited. By observing agents’ interactions it is impossible to grasp the whole extent of their deeper motivations or associations beyond neighbourhood relations. Qualitative research is needed to track actors’ experiential and social ties across scales and their emerging social bonds, the effect of which may be decidedly unpredictable.

The case showed that a certain intellectual methodological separation of approaches is necessary: the findings in the quantitative study are relevant within the scope of the study, and reveal essential hidden features and mechanisms of the local dynamics which it would otherwise be impossible to discover. A mental model accommodating numerous incomparable variables would not be epistemologically and ontologically coherent or able to generate relevant scientific or practical knowledge. Although the two approaches, qualitative and quantitative, could not be simply integrated, in hindsight, a reflective triangulation or a multi-methodological approach (chaining the research operations and building the question on previous results, even in a circular manner) would have expanded the spectrum and provided knowledge of the area.

The case of Herttoniemi: a qualitative analysis of self-organizing movements

The second case is situated in Helsinki, in the neighbourhood of Herttoniemi, an old industrial area which has transformed into a housing and retail area.

The case study focused on urban development by observing local stakeholders and urban activists working to improve the quality of the urban environment and local services, and comparing them to the on-going urban planning processes in the area (Wallin 2013; 2015; 2018). The activists and their actions could not be reached through urban planning research methodologies based on statistics, nor by analysing plans, strategies or planning procedures, because these groups did not operate through public participation processes, nor did they co-operate with the planners inside the planning procedures. However, the stakeholders’ input had a major developmental impact on their neighbourhood and on the planning endeavours.

In order to produce knowledge on these emergent and trans-scalar (reaching from one level to another) urban development initiatives, the researchers had to use qualitative methodologies, such as storytelling, drawing of mental maps, and observation of the stakeholders and activists. However, the research design had to be made in collaboration with the stakeholders and actors which the study concerned. Otherwise it might not have detected the reasons for their actions, nor their modes of action.

Therefore methods of ethnography and sociology, often used in urban studies, were applied through the methodology of a longitudinal action research (Alasuutari 1993).  The objects studied, the stakeholders and activists, became subjects. With the methodology of action research, the activists made their own agendas and conducted the actual developmental initiatives while producing data for the researchers (Wallin 2015; Wallin & Horelli 2012; Saad-Sulonen 2013). The objectives of the data gathering were to collect actors’ views, first, to develop the neighbourhood, second, to disseminate information on urban planning procedures, and third, to monitor the evolving local context and the outcomes of local initiatives.

The action research methodology consisted of several research strategies. The stakeholders produced the primary data in co-operation with the researchers. Active residents and people from local associations and NGOs delivered memos and e-mails describing their local actions. Researchers conducted interviews and surveys of the stakeholders and local residents and analysed urban policies and spatial planning data that provided a context for the action as a whole.

The outcomes of the agent and change analysis prove that local agents organized gatherings, events and festivals, initiated new enterprises, organisations and voluntary work providing new local services and improving green space. They designed and constructed a community park and a community centre, called Roihuvuori village hall (Saad-Sulonen & Horelli 2013). They made changes to the actual physical urban space without an official building permit, and definitely out of sight of local planners. They also arranged family services and produced local events and digital arenas defining the image of Herttoniemi faster, more interestingly and precisely than official development strategies or planning procedures (Wallin 2015).

The research gathered empirical data on self-organized human interaction and introduced developmental action patterns which were difficult, if not impossible, for city administration or official urban planning processes to steer. These emergent local developments underlined the complex nature of the planning, but also the complexity of urban systems. The local level action research could not open up the urban complexity in a form that could be analysed in terms micro-simulation models based on cellular automata (CA). This option was simply not considered during the qualitative research that lasted for ten years.

Regrettably much of the local action data was produced through social media applications and blueprints, which could also have been analysed with a quantitative measures and spatial analysis.  Combinations of traditional and soft GIS data along with voluntary mapping and tracking also provided a lot of potential for actual planning practice.

Methodological variety, similarity and the praxis of urban planning

Regarding similarities and differences between these case studies, we consider that self-organisation and urban complexity can be approached with both hard and soft methodologies. In this section we analyse the outcomes and relevance of the methodologies used for applying the definition of self-organisation. The main message is that the difference in the research design and phenomena studied, and on the other hand the temptation to perceive similarities between sites of the case studies should be viewed with caution. There is a need to address what kind of self-organisation emerges in the outcomes, and for what reason the study of urban complexity is conducted.

In the case of the Nekala spatial analyses, self-organisation referred to firms and other activities as agents deciding on their locations; clusters as patterns resulting from their interaction; constant logistic and customer flows supporting the firms’ operations; and the feedback from the pattern, implying that the firm may benefit or suffer from co-location with the competitors.

We perceived similar self-organisation in the case of Herttoniemi. Local stakeholders became interacting agents (e.g. associations, organisations, groups), their interventions turned into development patterns (co-ordination of voluntary work, scheduled tasks, shared sense-making with commonly agreed rules, schedules, policies), separate from official development strategies and policy-making. The local self-organizing networks and their patterns of action shaping the actual urban environment became visible through the qualitative analysis in action research. It provided a basis for further discussion and interaction between people, planners and local developers.

In both studies self-organisation and its connection to urban complexity became evident, even if defined and studied differently. Both studies conceptualized self-organisation through the same metaphors borrowed from the natural sciences. Also, there was a shared understanding of dynamics, even if the actual objects of the study were completely different.  Self-organisation was multi-scalar in the cases of Nekala and Herttoniemi, from an individual level to the neighbourhood or transnational organisations. In both cases, they were also trans-scalar. This means a phenomenon that penetrates several levels of social movements from the global to the local level and vice versa (Salet & al. 2013).

There were limitations in both methodologies: In ‘soft’ humanistic research it is impossible to gather coherent data on all levels and scales of a social movement. In action research methodology, research design and data collection imitate life with its shortcomings and biases, whereas ‘hard’ spatial analysis disregards these. Certain emerging qualities cannot be measured quantitatively, namely those such as ‘meaning’, ‘belonging’, or ’empowerment’. The upside is that if the data gathered is rich enough, the analysis is usable for triangulation.

The most outstanding outcome is the shared outcome of the case studies in the context of planning recommendations and policy-making. For planning praxis, this would mean that self-organized urban processes need to be allowed, and that plans should merely provide certain frameworks of rules which prevent negative externalities but allow the actual actor-based dynamics. Planning ideals should shift from anticipating and controlling to steering and nurturing human action.

Both studies also address the complex nature of urban development. Nevertheless, the scale or the nature of self-organisation, the steering effect of urban planning turned out to be weak. In Nekala it might have been a sort of a strategy of its own; to keep the area on hold for future progress. In Herttoniemi, planning was blind to local level development. The planning department did not have access on the actual stakeholders of local development. They negotiated with construction companies and investment bodies with housing development interests in Herttoniemi, but rarely with parties interested in developing the neighbourhood as whole.

Shifting the scientific viewpoint or jumping from one level of action to another (along with adopting certain ontological and methodological perspectives) produces qualitatively novel interpretations, which are not necessarily observable within another frame. However, with constant triangulation (not only by enriching the data with different data sources and methods, but also by moving back and forth between the layers of analysis), we may produce a wide variety of complementary knowledge for gradually building a more coherent and multifaceted understanding of the planning of complex cities.

The current development of spatial analysis as well as citizen science and digital platforms, especially on social media applications, offers planners completely new applications and tools to collect data and analyse it (Horelli, 2013; Saad-Sulonen 2013). However, synchronic triangulation, visionary and even disruptive perspectives alien to official and formal planning procedures could be presented in the multifaceted data delivery and analysis, along with sources for public discussion and sense-making processes between planners and different stakeholders, and the complex urban context they share.  Planners themselves are better equipped to adopt various digital planning tools for crowdsourcing, co-creation, data gathering and even data processing.

Using a variety of methods from different methodological backgrounds does not mean abandoning scientific rules: we do not propose combining different methodologies into a singular meta-analysis following the principles of triangulation. We stress that disparate case studies and their outcomes can be interpreted by following the emergence of urban phenomena and actions. Therefore shared knowledge production would favour the understanding of urban complexity in urban planning practices.

Conclusions and discussion

Echoing Portugali (1999), urban complexity could successfully bridge subjective and objective grounds in knowledge production. Bridging the ‘two worlds’ of objective-realistic and subjective, somewhat relativistic views, complexity may offer a potential post-positivist approach both methodologically and epistemologically.

Methodologically, systemic views of urban complexity abandon the analytical reduction typical of positivism characteristic of the social sciences; both accept the revolutionary, emergent transitions of the system and many consider space as an ‘enslaving’ environment produced by and producing human action, resembling complexity (Portugali 1999; Batty & Marshall 2009). Epistemologically, although quantitative methods are often used in urban complexity research, system definition is always a strategic decision implying constantly re-evaluated relational classifications (Cilliers 2005). Such work approaches a qualitative view constantly giving meanings and interpreting urban phenomena.

In this article, we asked how to understand self-organisation in soft and hard methodologies in a complementary manner that supports multifaceted urban development and planning in practice.

While self-organisation became explicit in both case studies, even if the phenomena studied, urban patterns and stakeholders were different in nature. In both cases self-organized urban development consisted of a complex set of interactions, multi-scalar actions and urban patterns. This reconciliatory interpretation enables the recognition of qualitatively unique situations regarding the local forms of organisation and the spatial structure.

We suggest that there are two logically consistent, yet separate ways of contemplating self-organizing systems. Based on the case study analyses, we argue for a more coherent understanding of urban complexity and self-organisation by adopting a variety of methods and tools, and particularly by overcoming the dichotomy of soft and hard. A shift of attitude is needed from command-and-control thinking towards practices concentrating more on observing, supporting and guiding the socio-economic processes. For future research, we consider promising to study the relationship between quantitative and qualitative self-organisation through the framework of emergence. This concept would also allow these two to be coupled in a theoretically more robust manner, to form an intellectually continuous view combining them.

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