The civic and neighbourhood commons as complex adaptive systems: The economic vitality of the centre

Introduction

Since the advent of third wave systems theories in the last decades of the 20th century, the notion that there is a complex self-organising system and should be analysed and understood as such has been regularly advanced. Portugali (2011) claims that complexity theory has become ‘an established interdisciplinary research domain engaging urban geographers, planners, urban designers, regional scientists, mathematicians, physicists and others’ (p. 97). It has become widely accepted that planning, urban design and architecture have much to learn from third wave systems theory.

This article begins with an outline of some of the major principles that lie behind complex adaptive systems and how these are relevant to the understanding of an analysis of urban environments. A major principle of complex adaptive systems is that they are scalar and hierarchical (Mitchell, 2009). Hierarchy and scale in complex adaptive systems refer to each system being made up of a mosaic of other complex adaptive subsystems that are in turn made up of other complex adaptive subsystems. In this way, cities should not just be analysed as single systems but rather a mosaic of complex adaptive systems each interrelated and overlapping without as well as within and impacting each other in diverse ways. Cities are hierarchical assemblies of complex adaptive systems exhibiting complexity at any level and are as a result, using another biological metaphor, rhizome rather than arborescent (Hillier, 2008; Martin, 2012; Page, 2011).

By understanding the city as a complex adaptive system, one sees a major part of the city’s strength, resilience and dynamism lying within the mosaic of subsystems that form it. The strength and dynamism of the individual neighbourhoods that form their districts and the districts that form their regions ultimately impact the strength of the metropolis as a whole. Conversely, exogenous forces and change emanating from higher systems can affect the viability and evolutionary paths of lower subsystems (Allen, 1997).

The focus of this article is the subsystems of the city, in particular its regional, district and neighbourhood activity centres that together form the complex whole that is the metropolis. All metropolitan areas are organic, multilayered, self-organised and evolving, and within them a myriad of functions are carried out and coordinated without an overseer or choreographer and therefore, complex adaptive systems; however, many subsystems of cities, particularly their urban transaction/gathering places or activity centres, are not. They are instead either chaotic or controlled by mechanical order.

Childs (2004) identified three types of urban gathering places: the civic commons, the neighbourhood or community commons and the membership commons. The civic and neighbourhood commons are publicly owned ‘open-minded’ gathering and transaction places that draw large numbers of people to a single bounded location for a diversity of reasons. The civic commons are gathering places open to all and controlled by a myriad diversity of stakeholders and users. These are bustling city centres where one can be anonymous in the crowd and at liberty to test limits. The neighbourhood commons are, like the civic commons, open to all; however, unlike the civic commons, they are frequented by a community of people whose routine use of the space defines both their function and character. They are smaller and more intimate than the civic commons and there are ties of acquaintance between the majorities of users, while strangers are conspicuous. In the modern metropolis, the lines between the civic and neighbourhood commons are often blurred – one person’s neighbourhood commons can be another person’s civic commons. Finally, there are membership commons, which are usually privately owned spaces open to all but shared by a limited group willing to pay the price of admission. The neighbourhood and civic commons will be referred to according to these definitions throughout this article.

Another activity centre referred to in this article is the shopping centre. The term ‘shopping centre’ can have different meanings in different parts of the world; the definition used is the one provided by the Urban Land Institute of America (Casazza et al., 1985) and the Urban Development Institute of Australia (Golledge, 1985: 12):

A group of architecturally unified commercial establishments built on a site that is planned, developed owned and managed as an operational unit related to its location, size and type of shops to the trade area that it serves. The unit provides on-site parking in definite relationship to the types and total size of the store.

An additional universal feature of shopping centres that should be added to this definition is that the major organisational element of uses within each is privately owned, whether in the form of car parks, pedestrian malls or plazas. By these definitions, shopping centres are membership commons.

In nature, complex adaptive systems comprised the living, biotic agents and non-living, abiotic elements. In this article, the non-active elements of the commons, its streets, built form and physical infrastructure will reflect the natural system roots of the theory of complex adaptive systems and be referred to as abiotic elements, while the living components of the commons, its activities, institutions, businesses and so on are referred to as biotic agents.

The article analyses three styles of metropolitan activity centre: the arterial strip, the shopping centre and the traditional civic or neighbourhood commons in the light of the principles of complex adaptive systems. This analysis suggests that only the traditional ‘commons’ has the principles required to be defined as complex. Furthermore, self-organisation within the bounds of a complex adaptive system produces unique phenomena, benefits and challenges for urban subsystems. Analysing these is the major focus of this article.

Complex adaptive systems theory

The dynamic of all complex adaptive systems is that they produce enormous collective intelligence and abilities arising from, in many cases, the agglomeration and interconnection of otherwise quite simple agents making relatively simple decisions bound by relatively simple rules. Examples include neurons in the brain or cells in an embryo, which only have the ability to turn themselves on or off in multiplicity creating consciousness and autonomous living beings. Ants offer another example; they individually make very few autonomous decisions but by following a set of simple instinctive rules, in combination with multitudes of the same species, create the enormous complexity of the ant colony (Dawkins, 2009; Mitchell, 2009; Page, 2011). Finally, ecosystems are complex adaptive systems that contain a diversity of biotic agents along with abiotic elements, which in combination create systems of rich and exquisite complexity (Collins et al., 2000).

Within all complex adaptive systems, there is no architect, choreographer or divine force controlling the organisation. Instead, organisation arises from micro-behaviour dispersed among individual agents cooperating and competing to survive and flourish. From this dispersed bottom-up decision-making, complex adaptive systems gain spontaneous order and self-organisation (Holland, 1995; Johnson, 2004; Mitchell, 2009).

While diversity is both a prerequisite of complexity and an outcome of it, diversity does not necessarily result in complexity as complexity only exists where there is inter-agent connection, relationships and interaction within a system. Within a complex adaptive system, information turns diversity into complexity by providing connection and self-organisation and preventing systems from descending into disorder or chaos. Information comes in the form of reverberating loops, which act as connected assemblies that are diverse, multilayered, overlapping and multifaceted, and provide negative or positive feedback to individual agents within the system. These reverberating loops of information allow opportunities for relationships to develop into synergies, alliances, rivalries and catalysts, as well as giving rise to constant opportunities for serendipity, happenstance and sequential behaviour (Holland, 1997; Mitchell, 2009; Page, 2011).

A shared aspect of evolved complex adaptive systems is that many of the biotic agents that constitute them only exist by virtue of the presence of other agents connected within the system or the system as a whole. As a result, the complex adaptive system creates non-linear dynamics and growth via constant bifurcation which evolves diversity and mass beyond what would be possible without the relationships made possible by networked connection (Allen, 1997).

Complexity theory and the city

Like an ecosystem, the urban complex adaptive system is an agglomeration of abiotic elements, in this case in the form of infrastructure and buildings, and diverse biotic elements in the form of businesses, institutions, civic, social, cultural and political organisations and people drawn together within space and time. The abiotic elements provide many of the physical space and connections that bind the diverse elements into the integrated whole that is the city, town, village, society or economy in which relationships, routines, decisions and knowledge emerge. A significant difference between civic ecosystems and natural ecosystems is that biotic agents within the former are thinking, learning entities able to adapt and change quickly and with intent in response to reverberating information flows.

Complex adaptive systems exist and evolve because of their ability to tap into and then metabolise exogenously derived sources of energy or materials. While the energy of the ecosystem comes from the sun, in the complex adaptive systems of the city, the energy enters in the form of human activity. As a subsystem of the greater city, the neighbourhood or civic commons is what is referred to in biology as a heterotrophic ecosystem, dependent upon external flows of energy and materials but individually able to metabolise them in different ways. The energy of the subsystems of neighbourhood or civic commons comes primarily by way of the human as pedestrian. It is the energy of pedestrian formed crowds – moving, sitting, standing, observing and playing, that provides life in public places and delivers the exogenously derived nutrients (money) into the system that can then be cycled to evolve complexity, richness, diversity and mass.

Although all cities are self-evidently complex adaptive systems, like natural ecosystems, some are far more complex, rich, diverse and self-contained than others. A major reason for this is that some cities are made up of far greater numbers of complex subsystems than others. In the modern city, not all constituent districts and neighbourhoods are subsystems of complex adaptive systems, as post-war urban development has largely provided either chaos or order in newly added subsystems.

Chaos in metropolitan transaction places is observable in the form of the arterial strip. The strip provides lines of often diverse but discrete agents attached to the greater city by the road network and mass marketing, but it is detached from the local and the energy of pedestrian activity by poor or non-existent pedestrian connections, distance, intentional ugliness and legibility aimed at speeding motorists. Without the design and connectivity needed for the energy supply of pedestrian activity, the strip is restricted in its ability to provide opportunities for relationships and synergies to form. Without them, the often quite diverse primary uses contained within the strip provide diminished opportunities for secondary and tertiary activity, complexity and emergence. In reference to Gehl’s (2010) three types of urban activities, the strip is highly restricted in its ability to build social and resultant activity in, around, between and upon the necessary activities that proliferate along them. Consequently, the strip is a largely linear place, restricted by design in creating something greater than the sum of its functions.

Order, on the other hand, comes in the form of the shopping centre in all its various forms. The shopping centre purposely isolates itself from potential relationships by creating places of controlled and reduced diversity, single ownership, synergy within and dysergy without (Kowinski, 2002; Mitchell, 2006). The ultimate form of order is that of the hypermarket, which isolates most of what needs to be bought on a daily, weekly or even monthly basis within a single premise away from potential relationships and synergies. Hypermarkets often offer a broad diversity of products, but no diversity of premises, agents or ownership.

As distinct from the hypermarket, the shopping mall uses primary attractors and choreographed pedestrian movement as a means to generate opportunities for secondary uses via synergy and symbiosis. However, they do so, not by the principles found in a complex adaptive system but rather via the engineered system of the machine (Goss, 1993).

Within the machine for shopping, there is little space for the spontaneity, self-organisation or bottom-up regulation on the edge of chaos. The allocation of space, locations, mix, aesthetics and design is primarily driven by top-down command and control structures and policies devised by experts, implemented by standards and bureaucratic processes (Goss, 1993; Kowinski, 2002; Mitchell, 2006; Voyce, 2003). Therefore, while a shopping centre can be large, diverse and complicated, top-down control and the sidelining of dispersed bottom-up-derived self-organisation means they can never be complex adaptive systems (Mitchell, 2009; Page, 2011).

Between the chaos of the strip and the order of the shopping mall lies the pre-war town, village, parade or high street neighbourhood or civic commons (Childs, 2004). The neighbourhood and civic commons are subdivided and comprised multiple owned premises, land and businesses connected to form a compact systemic whole by the traversable public spaces that lie between them. The better these connections between biotic agents are, the more opportunities for interaction and relationship forming.

Most importantly, the neighbourhood and civic commons are self-organising and regulated by the multiple decision-making of many agents, as business owners, landlords or institutions, all of whom are connected and bound to one another via multiple relationships enabled and fostered by the public spaces that lie between them. As a result, they have the diverse bottom-up self-organisation required of complex adaptive systems (Amin, 2010; Brugmann, 2009; Childs, 2009). As complex adaptive systems, they, like their natural ecosystem cousins, are manifest in evolved relationships, reverberating catalytic loops, synergies and symbiosis and are alive with a dynamic tension fuelled by competition, cooperation and possibilities offering constant opportunities for serendipity, happenstance and niche exploitation, which in turn drives adaption, change and dynamic evolution.

Life on the edge of chaos exists in a state of flux and constant evolution where optimums or perfection can never be entertained, let alone achieved. Their dynamic is derived from responsiveness to opportunities available in time and space rather than notions of rationality, order or conventional ideas of efficiency (Page, 2011; Pickett et al., 2004; Walker et al., 2006).

Without an overarching hand to create order, as found in the mall or hypermarket, complex adaptive systems are characterised by messy departures from the rational, efficient, ideal or perfect. On the other hand, in the shopping mall, controlling the whole based upon notions of perfectibility, rationality and/or efficiency is the modus operandi (Goss, 1993; Mitchell, 2006; Voyce, 2003). The inevitable consequence of a drive for perfection is stasis and standardisation (Crawford, 1992).

Metabolising energy in the commons

It is hence the very messiness of the commons that gives it energy. In the natural sciences, the ability of an ecosystem to transform exogenous inputs of energy and materials into total biomass is the ultimate measure of its efficiency (Loreau, 2000). What is more, the same or similar inputs can have vastly different levels of efficiency concerning measures based upon total mass relative to exogenous inputs. Some systems produce comparatively little, while others, such as the rainforest, are extraordinarily efficient metabolisers of inorganic energy and materials into biomass. In nature, the key to this efficiency is complexity and the ability of niche species to recycle the nutrients created by dominant species. Moreover, complexity leads to still further diversity, which in turn leads to still greater complexity, a virtuous cycle that eventually slows with maturity but never stops (Mitchell, 2009).

In a similar way, much of what is provided by specialist stores or businesses within a commons could be provided more efficiently. A vending machine, for example, can provide a perfectly adequate coffee or drink. However, the cafe, like the elaborate flower attracting the bee, sells coffee in a highly inefficient and extravagant manner in order to entice customers by providing experiences beyond the simply instrumental. Similarly, like the flower, the allure of the cafe becomes a contributor to the small, diverse, idiosyncratic pleasures of place that benefit all, not just those who are the immediate targets of the display.

While cities and districts within cities can never be, nor would it be desirable for them to be, self-sufficient to the level of the rainforests, they have the ability, like all complex adaptive systems, to use the cycling of energy as a means to add diversity, mass, complexity and richness by metabolising inputs of energy. In addition, unlike complex adaptive systems in nature, the dynamism of dispersed decision-making by diverse agents is fundamental to the growth of abiotic elements within the commons. Multiple ownership of land and premises within the commons means numbers grow incrementally by the small-scale decisions of micro-agents without overall planning or top direction. While this leads to disorder in the form of occasional oversupply and boom-bust cycles, it keeps the system expanding and continually provides space for new biotic agents to enter (Harvey, 2010; O’Flaherty, 2005). This is in stark contrast to growth within the mall or hypermarket where growth comes by top-down fiat driven by an imperative to maintain optimum rental returns (Crawford, 1992; Mitchell, 2006; Voyce, 2003).

Cycling nutrients in the commons

It is vital to the long-term viability and health of any neighbourhood or civic commons that pedestrians not only use it but they also distribute the nutrient of money to agents within the system in the process. Therefore, the success of the commons is determined not just by drawing pedestrians into the system for specific purposes or necessary activities but also by then cycling them through the system as whole and subsequently drawing greater amounts of nutrients from them as a result.

In nature, ecosystems grow by ensuring that available nutrients are constantly recycled and recirculated over time and space through biotic agents within the system; by doing so they increase the levels of self-containment and diversity (Holland, 1997; Page, 2011; Trosper, 2005). The complex commons evolves similarly by incrementally increasing the recirculation and cycling of nutrients and decreasing the percentage of transactions that lead to direct outflows of money. A greater number and diversity of agents and consumption options within the neighbourhood can also reduce the flow of what is referred to in retail theory as escape expenditure or earnings spent by residents outside of their local neighbourhood or districts (Irwin and Clarke, 2006; Romer, 1994; Shuman, 2007).

In the non-linear economics of complexity, there is no assumption of perfect rationality, while the possibility that variables, such as availability, knowledge, proximity and emotional ties, might contribute to consumption choices are important considerations (Beinhocker, 2006; De Certeau and Rendall, 1988). Phenomena at play in an economy are thus likely to be subject to small shifts, chance, random and seemingly unrelated events, systemic relationships, serendipity, happenstance and small fortuitous events. As a result, systems are constantly in a state of flux subject to dynamic processes and are far from the deterministic, predictable, mechanistic approaches of neoclassical economics. Within theories of complexity, the nature of the system sharply influences what is transacted, as it can either broaden or narrow opportunities. For these reasons, phenomena or consumption opportunities present in time and space are far from economically neutral, as they can profoundly shape micro-behaviours that, when accumulated, drive the macro-economy (Arthur, 2009; Dosi et al., 2010). For example, the mere existence of large numbers of easily accessible restaurants, cafes, bars and so on in a neighbourhood can increase local expenditure in this labour and activity intensive and space extensive (relative to turnover) service sector, whereas distance can add significantly to the transaction costs (time and money) of utilising such services, reducing their appeal and use.

A further means of retaining nutrients within a system come via the non-linear dynamics associated with complex adaptive systems where the metabolising of nutrients is slowed by cycling. In the case of the commons, the cycling of nutrients comes from ensuring that more of the money that flows into the cash registers of agents within the system recirculates and finds its way into other cash registers within the system. This understanding of urban economics regards the strength of an economy lying not in its ability to tap into exogenous inputs but rather in the proliferation and diversification of endogenous focussed networks of production, distribution and exchange (Beinhocker, 2006; Fleming and Goetz, 2011; Jacobs, 1970; Romer, 1994; Schumacher, 1974).

The activity of biotic agents

One of the principles of complex adaptive systems is that they require no overarching understanding of the whole by its various agents. In the ecosystem, each agent operates with their own well-being at the fore. They cooperate and compete by virtue of self-interest with no regard to the health of the ecosystem as a whole, which in nature has no advocate (Dawkins, 2009; Mitchell, 2009). In the social system, cooperation and competition driven by monetary self-interest are elements of dynamic systems. However, human social systems have the added phenomenon of altruism, as well as the means to retain codified, historical knowledge and often concern for the well-being of other agents in the system as a whole, which produces further levels of complexity (Mitchell, 2006; Shuman, 2007).

Another difference between the non-human agents within an ecosystem and human actors in the complex commons is that the survival of the latter is not bound to genetic reproduction. Survival for most human agents within the social and economic systems rests upon an immediate ability to earn an income reasonably commensurate with the effort, capital and labour invested (Shuman, 2007).

The basis of cycling within complex systems is through evolved synergies and relationships between agents rather than a relationship to the whole. In nature, ecosystems evolve and grow by successfully cycling increasing amounts of nutrients through a dynamic where niche agents are continually finding and exploiting nutrient streams and then creating new streams of nutrients to be exploited by new agents. Such is the highly refined adaption and co-evolution of agents to a specific nutrient source; many agents within an ecosystem are unable to survive without a particular source of nutrients (Holland, 1997; Mitchell, 2009; Page, 2011). Like natural ecosystems, the complex commons provides a range of niche opportunities for agents to exploit that would not be available outside of the system. Therefore, many secondary uses found within a commons are reliant upon relationships and synergies with other agents and the catalytic attraction of the system as a whole.

The forces upon agents within a constantly changing environment can be both positive and negative – positive in providing evolving opportunities to be exploited by the adaptable, but negative also as demands placed upon individual agents can be great and their viability and survival are far from assured. Survival in a dynamic environment requires a capacity to continuously adapt and change in response to an ever-evolving unpredictable environment. In a natural system, adaption comes via the process of natural selection, mutation and genetic transfer within individual species over generations. However, in social systems, adaption is the result of the actions of cognitive individuals able to learn through experience, observation, word of mouth and research, as well as through the impact of social forces, collective action and institutions.

While the evolving system itself provides the necessary incentives for adaption, the process of adaption for individual human agents within the system comes via continuous and incremental processes of trial-and-error experimentation. The process begins with discovery and learning from a variety of sources, including the past, books, journals, travel, word of mouth and the Internet. Then, coupled with experience and knowledge of place, this learning can be reapplied, mimicked, adjusted and incrementally transformed into innovation via trial-and-error experimentation.

Trial and error is the dynamic behind innovation and creativity among individual agents and, when accumulated, a major dynamic across the system as a whole. Like the brain, embryo or the ant colony, it is not individual decisions and actions that are important, but rather their cumulative power. Change via dispersed small-scale decision-making has great benefits for the system as a whole, as it involves the application of insight, creativity and ideas instantaneously and directly without mediation. It does not require interim viability, can be adjusted quickly and easily, can be given time and space to succeed or fail and can proceed with relatively small investments of time and capital, while direct, embedded access to information loops within the system endows agents with immediate negative or positive feedback on which to base decisions to continue, make adjustments or withdraw.

Agents within complex adaptive systems constantly make poor choices and are regularly subject to exogenous forces (economic, social, cultural and political) that can challenge their viability. It is a universal phenomenon of all complex adaptive systems that new entrants and some established agents periodically fall victim to the winnowing process created by system demands. Consequently, agents within social systems can come and go with great regularity (Jacobs, 1970; Mitchell, 2009; Page, 2011). This is, of course, a negative for the agents concerned. However, it is not necessarily a negative to the system as a whole and can ultimately be a positive as it prevents run away diversity, builds complexity and provides regular opportunities for new entrants. It is also part of the learning process, as embedded agents are able to learn from both their own errors and the errors of others (Page, 2011).

The competitive forces within the system, which make life tense and difficult for individual agents, are a source of strength to the system as a whole. In an economic system, such as the commons, it makes innovation and creativity a survival technique and an intrinsic value. The result is a system dynamic driven by the constant application of the cognitive power of a multiplicity of agents in pursuit of fresh opportunities and access to niche flows of nutrients. Agents in such systems are by necessity sensitive to their environments and able to respond to them in subtle ways. They constantly interact with the system, receiving signals and adjusting to them, as survival within a niche requires being open to new ideas and seeking them out (Johnson, 2004; Loreau, 2000; Page, 2011). They can then respond to opportunities and impending change in subtle and idiosyncratic ways that cut across categories in attempts to add what Jacobs (1970) described as new work to old.

Jacobs (1970) referred to trial-and-error experimentation or adding new work to old as the force behind macro-economic dynamism, diversification and growth. She and others have also argued that large corporations generally view trial-and-error experimentation as problematic, as their structures are not conducive to tapping into the bottom-up creativity, resourcefulness and innovation of employees at the coal face (Chapman, 2004; Dosi et al., 2010; Johnson, 2004; Voyce, 2003). In contrast, independent businesses do this instinctively and easily as risks associated with trial-and-error experimentation are tempered by instant feedback and ownership.

Niche agents and their importance

In a highly evolved complex adaptive system, it is a long tail of diverse, highly specialised and often brittle niche agents that carry out the absorption and exploitation of nutrients. Their redundancy and inherent fragility means they come and go regularly, often contributing little to overall turnover and typically do so with observable levels of resource and spatial inefficiency, disorder and messiness. Consequently, within the mall or the hypermarket they are viewed as risky and unnecessary and are purposefully avoided in standard retail mixes (Brown, 1992; Reimers and Clulow, 2000a).

However, the redundant and the niche are imperative to the well-being and resilience of complex adaptive systems as their commitment to survival is a powerful system dynamic. Collectively, they also provide much of the commons’ strength, diversity and richness. Many fail, many endure for some time in a marginal state, while others manage over time to build incrementally a more robust position within the system. They also constitute a reservoir of alternatives or phenotypic trait variations, which enable systems to adapt and respond to exogenously derived disturbances. Over time, the once marginal and fragile can eke out a more solid position and replace declining or obsolete agents that once held key positions in the system (Holland, 1995; Page, 2011).

Synergies

Within an ecosystem, competition between types is quite limited compared to relationships that produce synergies of conscious and unconscious cooperation (Davies, 2004; Page, 2011). Similarly, in the commercial sphere of the commons, while competition between types competing for the same nutrient flows, say between two or more butchers, is likely to be intense, competition across types is likely to be slight compared to potential synergies. Some synergies, such as those between the butcher and greengrocer that strengthen both are obvious, but when the baker, delicatessen, newsagent, cafe, pharmacy, butcher and greengrocer are agglomerated within a reverberating connected loop, the synergies are multiplied and the loop becomes a catalyst for commercial relationships. Generally, this cooperation across type requires no formal effort on the part of individual agents, just proximity and connection within the commons.

Most importantly, the existence of diverse and multiple agents produces assured pedestrian activity. The highly specialised niche operator survives by attachment to the nutrient flows within the system, in particular the ability to tap into the impulse purchasing of passing pedestrians. In addition, being regularly passed by pedestrians makes an agent known through routine observation, which can become an impetus for later visits when circumstances are more serendipitous. On the other hand, outside of the synergies of a complex adaptive system, there are far fewer opportunities available to highly specialised niche agents.

In the commons, the small retailer, cafe or restaurant must continually look for niche opportunities and specialisation to survive, as many agents in competition attempting to appeal broadly are a recipe for decline for all. The ability to find, adapt and specialise in order to occupy a niche attached to a unique nutrient stream not only enhances individual survivability, it is a major dynamic within all complex systems and a catalyst for agents to evolve and add diversity, complexity and richness to the system as a whole (Loreau, 2000; Page, 2011). Niche positions are often fluid and shifting, and those agents that inhabit them are often fragile and constantly under pressure to adapt and change. Consequently, complex systems are described as being robust, despite being made up of predominantly brittle or fragile agents (Page, 2011).

In comparison, the shopping centre specialises in offering locations to the robust, generally those with a broad appeal and subsequent high turnovers, which produces stable environments where a small number of chain operators offer a range of standardised products to a broad clientele (Coleman, 2006; Voyce, 2003). Chain store dominance also means that personnel in the store are only in a minority of cases the owner operators. Even in the minority of owner-operated premises within a shopping centre, incremental trial-and-error experimentation is rarely an option. As even minor changes must be vetted and approved by the mall management to ensure the retail mix is not altered, change does not interfere with the business strategy of the centre as a whole or create competition between types that might reduce turnover in other premises (Coleman, 2006; Dennis et al., 2005; Voyce, 2003). Consequently, there are few incentives or opportunities available for innovation and creativity within the shopping centre, which stifles evolution towards specialisation and niche appeal.

Novelty

In addition to the ongoing trial-and-error adaption of embedded niche agents, the evolutionary paths of complex systems are in nature and society ‘unsatisfied’ and open to the immigration of new and novel agents (Arthur, 2009). The more a system is open to the immigration of the novel and the new over a sustained period, the greater its diversity and complexity. Novelty is described as the mutant force operating upon the evolution of complex systems that can send them in radically new directions (Martin, 2012; Page, 2011).

In nature, evolutionary change occurs by slow incremental adaption punctuated by profound change through mutation or species introduction. Page (2011) gives the example of islands close to the mainland compared to those further afield. The closer an island ecosystem is to the mainland, the greater the number of species able to emigrate there, and as a consequence, the greater the diversity found, while those further out have far less diversity. In a similar way, the more open a commons is to the new and novel, the greater the diversity and complexity within it. Openness in the commons comes through the regular availability of vacant premises within the system and the absence of top-down tenancy mix policing.

In both natural and social ecosystems, the accommodation of the new and novel can produce dynamic disturbance that redirects evolutionary paths (Arthur, 2009; Page, 2011). Such redirection is an anathema to the top-down control of the shopping mall, and their management seek to ensure such dynamic disturbances do not occur. Therefore, the idiosyncratic are rarely welcomed into the controlled mix of the mall. However, in a complex commons, dynamic disturbances are relatively common and occur in reaction to bottom-up processes and changes in the vernacular (Childs, 2012; Zukin, 2010).

Emergence

A defining principle of complex adaptive systems is that the system’s functions must be greater than the sum of its functions. In complexity theory, the phenomena or properties that exist beyond the sum of the systems functions are known as emergent. In the brain, for example, the assemblage of neurons forms a system from which the emergent phenomenon of consciousness emerges. Typical of all complex systems, the study of individual agents, neurons in this example, provides few insights into the nature of the emergent phenomena, in this case consciousness. It is also a principle of complex adaptive systems that ‘persistent’ emergent phenomena serve as agents or elements of even more emergent phenomena, for example, from assembled human consciousness, the emergent phenomenon of society emerges (Arthur, 2009; Johnson, 2004; Mitchell, 2009; Page, 2011).

In the complex commons, much of the biotic phenomena on display could be regarded as emergent. This includes secondary commercial activity, particularly the specialised niche agents that have evolved within the system and would be unable to survive outside it. Even some more robust agents would be more vulnerable, weaker and different without the synergies and symbiotic relationships provided by the system.

In Gehl’s (2010) analysis of life, in the spaces between buildings, most of the optional and social activities that exist in the commons is emergent as are the weak ties formed by routine encounter. Granovetter (1973), Jacobs (1993) and Putnam (2000) argue such ties can give rise to social and civic capital, such as cooperation, eyes on the street safety or serendipity, which in turn, as persistent phenomena, can give rise to emergent phenomena, such as gemeinschaft and a sense of community. At the highest level, the entwined phenomena of the endogenous economy, sense of place and/or local identity are the emergent unpredictable and non-deliberate results of the commons acting as a complex adaptive system.

Ultimately, emergent phenomena within a complex commons are created by the multiplicity of vernacular forces that exist within the communities that use them. Thus, the sense of place or local identity, that permeates the commons, is reflective of those that use it, able to evolve and change as they evolve and change rather than something deterministic. In comparison, in the shopping centre, experts and top-down fiat determine the mix of biotic elements and activities permitted. Therefore, shopping centres of a similar size have a strong tendency to resemble one another (Crawford, 1992; Voyce, 2003).

The vulnerability of complex adaptive systems

No agent within any system mechanical or organic is atomic. Agents, therefore, cannot be abstracted from the system without repercussions small or large, positive or negative, for other agents or the system as a whole. The repercussions of a loss vary enormously depending upon the position the agent has in the cycling process of the system. In particular, the loss of key agents can irreparably damage the system as a whole (Page, 2011). In addition, self-organising systems and the agents within them routinely change as an adaptive response to disturbances emanating from outside the system (Allen, 1997).

The mechanical system of the mall has proven to be the highly susceptible to the loss of major anchors. Typically, this has occurred when a newer, often larger and more modern mall or hypermarket is built within or near their catchment. In the United States, where this is a common occurrence, the result has been the quite rapid decline and almost inevitable closure of the older centre (Levy and Weitz, 2007).

In the complex adaptive system, each agent is better connected and as a result supported by synergetic relationships than in any mechanical system. What is more, the continual loss and replacement of the small or redundant is a routine dynamic of any complex system. Furthermore, the redundant provide a vital reservoir of alternatives in the face of periodic upheavals and loss of key agents. This helps makes complex adaptive systems robust and resilient and provides an innate ability to ride out upheavals and difficult circumstances although they might be permanently altered by them (Arthur, 2009; Loreau, 2000; Page, 2011).

The complex commons has proven adept at writing of economic downturns, technological change, evolving tastes and consumption patterns over decades or centuries. While they have proven resilient in the short-term to the speculative over-expansion of abiotic elements within, and actually benefitted from them over the long-term, they have proven far more vulnerable in cases where cataclysmic investment and monumental change have produced new systems and/or diverted supplies of energy and nutrients elsewhere. Primarily this has occurred when key agents are decanted outside the centre in stand-alone facilities such as hypermarkets, medical centres, office parks or entertainment venues or where alternative shopping centres are constructed close enough to a precinct to divert patrons (Kowinski, 2002; Mitchell, 2006).

The opening of competing activity centres rarely results in an instant abandonment but begins as a slow then cascading decline as thresholds are passed (Irwin and Clarke, 2006; Romer, 1994; Shuman, 2007). In small enterprises, fixed costs are far greater than running costs; therefore, relatively small decreases in turnover can move the solid to fragile and the fragile from marginal profitability to loss. What begins as a ripple of closures of the most fragile slowly morphs into contagious closure as thresholds are reached, and each closure bites into the bottom-line of those remaining and critical levels of diversity are lost. As diversity declines, the attractiveness of the centre as a whole declines and patrons are diverted to alternatives, leading to less and less energy and nutrients coming into the system in the form of pedestrian activity, which reduces turnover again. In a reversal of the dynamic that built the complex commons, the loss is incremental and often begins slowly but accelerates as the flows of energy and synergies that built it evaporate until the system is left with significantly less diversity, richness and complexity.

However, unlike in the shopping centre, closure and abandonment are not an inevitable outcome. The resilience of a complex system means that while it is left in a situation far less than its historical best, it at least has the potential to re-evolve diversity and complexity given the time and connected space to do so. For this reason, the 21st century has been far kinder to the precinct than superseded shopping centres. Many precincts have been able to re-evolve after years of decline as gentrified retail, restaurant or cafe strips catering to the new middle class, ethnoscapes or specialist centres (Amin, 2010; Zukin, 2010).

Conclusion: the advantages of the complex commons

In the human-made complex adaptive system of the city, the subsystems that form them are not necessarily complex. Complexity at the subsystem level does not just happen. It requires fostering, design and organisation, and dispersed and diverse ownership and decision-making. While these exist in complex civic and neighbourhood commons, they are usually absent in the order of the shopping mall or hypermarket.

The great benefit of the complex neighbourhood or civic commons to the communities they serve and the city as a whole over a mall or hypermarket are emergent phenomena. Furthermore, the complex neighbourhood or civic commons is able to evolve and sustain more mass and diversity in the form of biotic agents and broad activity than either the order of the mall or the hypermarket. They are able to do so because complex adaptive systems are more efficient metabolisers of exogenously derived inputs into mass through diversity, networked complexity and synergies than either ordered or chaotic systems.

Many of the social and resultant activities in the spaces between buildings in the commons are emergent phenomena. Emergent phenomena are a vital aspect of the commons as they draw the crowds and pedestrian movement that sustains commercial, recreational, social, civic and political activity beyond the purely instrumental. It is emergence in the form of a sense of place, local identity and an endogenous economy that ultimately allows the myriad vernacular cultural, political, economic, civic and social relationships within communities to become explicit and observable (Frick, 2007).

While the machine requires ordered parts to carry out its vital functions, the complex adaptive simply provides opportunities. Creativity can take leaps in new directions when agents are autonomous, free to experiment, learn from elsewhere and adapt ideas quickly and easily to local circumstances. Once complexity evolves within a system, the continued seeking out and exploitation of opportunities become routine and probable, leaving few stones unturned in the quest. This makes learning, experimentation, innovation and creativity inherent values of the system and at the fore of change and development. This bottom-up dynamism and autonomy stands in contrast to the top-down control imposed upon agents within the mechanistic system of the shopping centre.