A few extensions to path-dependence and emergence in complex social systems

Introduction

The theories of path-dependence and emergence in societal transformation will be in the focal point of this article. A dissection will be made in respect of Eve Mitleton-Kelly’s (2003: 23-50) description of complex social systems theory, where the main research areas of complexity and its general characteristics, e.g., path-dependence and emergence, are discussed.

In her article, Eve Mitleton-Kelly has presented ten generic principles of complexity, which are: 1. Self-organization, 2. Emergence, 3. Connectivity, 4. Interdependence, 5. Feedback, 6. Far from equilibrium, 7. Space of possibilities, 8. Coevolution, 9. Historicity & time, 10. Path-dependence. As she wants to point out, all these characteristics together incorporate more than complex adaptive systems (CAS). That is why she has established a more appropriate term complex evolving systems (CES) for describing both the creation of new order, and coevolutions within this whole social “ecosystem”.

Alongside with the ten generic characteristics of complexity, Mitleton-Kelly (ibid.) has pointed out five main areas of complexity research, which are either under natural sciences or social sciences. The research areas under natural sciences are: 1. Dissipative structures, chemistry-physics (e.g., Prigogine 1984, 1989); 2. Complex Adaptive Systems, evolutionary biology (Kauffman, 1993, 1995); 3. Autopoiesis and Self-generation, biology/cognition (e.g., Varela & Maturana, 1992); and 4. Chaos theory. Under social sciences she has located Niklas Luhmann’s (1990) work on autopoiesis’ applications to social systems, and Lane & Maxfield (1997), Parker & Stacey (1994), and Stacey’s (1995) work on strategy within complex social systems. Here, in relation to social sciences, Mitleton-Kelly especially emphasizes Brian Arthur’s (1990, 1995, 2002) theory of path-dependence and increasing returns in economics, which she raises as the fifth main research area of complexity research (c.f. Hodgson, 2001).

The above lists and discussions around them (Mitleton-Kelly, 2003: 23-50) have formulated the theoretical framework for this article and predefined my approach. Hence, the article focuses on that fifth area of complexity research, path-dependence (and social emergence) and increasing returns in economics.

I think it is important to add new points of view and extensive information on the theme because I believe there is in general, firstly, not enough research that combines the approaches of complexity and social sciences, and, secondly, it is important to map the state of the art and its different angles in the field to be able to understand it further. Many processes, logics, and findings may remain hidden or unformulated to us as long as we are staying inside a single ontology—whatever it may be. It has been told that Albert Einstein used to emphasise the necessity of using at least three totally different points of views with any issue that one might truly want to understand. That is also my understanding here, and therefore, I would like to recommend us to prefer the use of many additional inter- or transdisciplinary approaches, when we try to understand for instance the issues of social complexity, path-dependence, or societal emergence.

Thereby, I propose the following three inter- or transdisciplinary approaches as extensions to the fifth research area:

These three approaches are inter- or transdisciplinary in the sense that those are not in the fields of complexity research nor social science as such, but merely represent something else. But before going to the proposed extensions, I will briefly present the ground or the state of the art of the fifth research area, as discussed in Mitleton-Kelly (2003).

Path dependence and increasing returns by Brian W. Arthur

Brian W. Arthur’s (1990, 2002) theory firstly argues the conventional principles of economics, which imply that in any growth curve there is an equilibrium point that is reached by negative feedback loops and diminishing returns—c.f. stabilizing effects. Thereby, conventional economics often works according to the principle of ceteris paribus, in which only certain factors are taken into consideration, while all the other factors that affect the phenomenon are closed outside. Here, the example given by Arthur is the high oil prices of the 1970’s, which used to be explained by negative feedback loops and diminishing returns. Thus, high oil prices turned into lower level by early 1980’s, owing to energy conservation and increased oil exploration, which caused a predictable increase in supply. In this classical case the conventional principle operated correctly, but very often the case is not such (Mitleton-Kelly, 2003: 38-40). Stabilizing forces do not always operate or dominate, instead positive feedback loops sometimes magnify the effects of a small economic shift, and increasing returns from positive feedbacks create many possible equilibrium points depending, of course, on the negative feedback loops that may also operate and stabilise in the same system simultaneously. For instance, early small gain in market share would improve the competitive position of one system and help it further increase its lead, which happened in the even match between Beta and VHS formats. Here, increasing returns refer to the increasing pull of new technology in the markets—if there starts to be more products, more friends using them, more retailers and support services etc. around one format, a self-reinforcing growth process has been started. This entity is a process, which Arthur calls path-dependence (Arthur, 1990).

To continue, Mitleton-Kelly (2003, 39) points out that “in physico-chemical systems, two or several simultaneously stable states could coexist under the same boundary conditions.” Furthermore, as in physics, one given parameter can evolve to more than one stable states (Nicolis & Prigogine, 1989: 24). In other words, it is possible to say that past history affects future development, and there may be several possible paths or patterns that a system may follow. Therefore, future is not deterministic, not even in cases where there exists a set of strict boundary conditions, but the past does determine the possibilities or the possible patterns of the future to some extent (Aaltonen & Sanders, 2006). When it comes to economic transformation, it means that “markets and economies are complex systems that coevolve, and dissipative (in the sense that they are irreversible and have a history), show emergence which refers here to self-organization + creation of new order (Kauffman, 1995), and explore their space of possibilities. As all these characteristics play out, the progression of any technology or market is not smooth” (Mitleton-Kelly, 2003: 39). As a conclusion, Arthur’s first arguments on conventional economics can be defended, at least to some extent, by the selected findings from physics and complexity research.

To go back to Arthur’s theory, he wants to show that there exists a constant interplay between positive and negative feedback loops, which are moving markets between periods of expansion and stability. He also emphasizes coevolution in the markets, the exploration of the adjacent possibilities and the emergence of new order in his theory (ibid.). In brief, he claims there have been technological, economical and societal eras, epochs and revolutions that were started with one or more technological innovations that eventually enabled a whole new cluster which finally changed the way entire business is done and society is conducted. Here, he provides examples, e.g., oil refineries, electrification, automobile production lines, modern assembly methods (Arthur, 2002).

At first, the new technology clusters attracted little notice, but later on they started to achieve successes in early demonstrations. Small companies may be set up based on the new ideas, and as the success increased, the competition became intense at this early turbulent phase. Eventually, when the promise of large profits becomes apparent, the public may start to speculate, and finally the speculation itself may have become a self-reinforcing process in the economy and the whole society. In certain cases this first exuberant phase is marked by a crash, for instance, railway industry crash in the UK in 1847; the Canal Mania of the 1790’s; and the recent Internet crash (ibid). To conclude Arthur’s point, he wants to show with his examples that an analogy between different historical phases can be drawn. At first, new clusters have often been ignored. In the second phase, there have been self-reinforcing speculations around the new clusters, then the crash might have taken place, and finally a broad economic and technological growth around the speculated cluster has proceeded in the whole society. Hence, the latest finding of Arthur (2002) promises us that the major part of the economic growth due to Internet crash is yet to come.

View 1: Path-dependence and emergence in Malaska’s theory

Arthur’s theory and approach seems to contain many ontological similarities and mutual starting points with Malaska’s understanding and theory. As the basic elements of Arthur’s theory are technological innovations as seeds of new clusters of markets; periods of market stability and expansion; feedback loops; and emergence of new order and new logic of markets and society, Pentti Malaska’s Funnel Model seems to be another organized way to present the same basic ideas. Malaska’s theory’s basic elements are a source (a germinating embryo/seed), nucleation, bifurcation², extensive exponential growth, intensive growth, cultural evolution, and the emergence of (eras) or “societies” with different kind of needs, occupations and modes of production. I have discussed and compared Malaska’s theory to other theories of societal change more thoroughly in (Kuosa, 2005a).

In Malaska’s theory, bifurcation refers to a branching point of development, where the critical mass of one kind of development reaches a peak and starts to lose its dominance and thus leaves room for something new to emerge. The bifurcation of the agricultural world leads to the industrial one. However, some nations have never reached this bifurcation point and perhaps never will. The term ”post-industrial” society refers to a major bifurcation from industrial society to a new kind of society, that differs from industrial society as much as ours differed from the previous agricultural one (Malaska, 1991a: 137-8).

According to Malaska (ibid.), any major bifurcation requires a source (a germinating embryo/seed) to begin the bifurcation process. The germination serves two purposes for development. Firstly, it has to benefit the dominant production mode, in particular it has to increase its productivity and efficiency. This has applications beyond its initial use and produces a new form of activity. This activity is very different to and, in a way, external to the dominant production mode itself. By producing new means (e.g., software, hardware) for the dominant mode, a cross-catalytic effect then transforms the dominant sector from a stage of extensive growth to one of intensive growth. During the period of intensive growth wealth and welfare are accumulated and thus new societal needs are created and can also be satisfied. These new needs stimulate a chain reaction in the developmental process. The other function of the activity based on the germination of the idea is autocatalytic growth that leads to it taking the role of the dominant production mode in society for satisfying new and old needs. This process, which Malaska calls the Chain of Development, and the transition periods between the different types of growth, is illustrated in Figure 1. In the figure, the succeeding societies are classified according to their core needs, as; societies of basic needs (SBN), societies of tangible needs (STN) and societies of intangible needs (SIN) (see Kuosa 2005a).

View II: Path-dependence and emergence in John Naisbitt’s theory³

According to John Naisbitt (2004), societal revolutions emerge rarely and always in clusters. The future is like a picture puzzle. It has its pieces, platform and its borders. As there are borders, the space for the pieces in puzzle is therefore limited. The platforms are established or enabled by certain drivers or catalysts, which emerged inside a previous phase of development. These drivers or catalysts determine both the general direction of development and the types of pieces looked for in the puzzle.

Inside one puzzle or phase of development, the transformation is steady once it has been started. There is a demand for a certain type of pieces in the puzzle, and other kinds of pieces are rejected, as they do not fit in. The pieces that are strongly looked for may be social ideas or technological innovations to solve a certain problem, demand or bottleneck of development. The pieces that are rejected may be ideas ahead of their time, or any other initiatives that do not gain support or demand by the platform’s already existing pieces or its drivers. As the puzzle is general and represent the whole society, its pieces vary throughout all sectors of society. They may be related to politics, economics, geography, values, technology, natural environment, science, military, psychology or anything else (see picture 3). According to Naisbitt (ibid.), one may pick up any piece from the puzzle—regardless of whether the issue is big or small—to look at it more carefully, study its relations to other pieces, and then put it back to the puzzle. Thus, from the point of view of the whole puzzle, “smaller and larger issues can both be evaluated in detail according to the potentiality they represent and whether they are expected to change or remain as they are” (Aaltonen, 2007: Chapter 6).

The platforms construct chronological layers, where the newer and further developed layer could not exist without its historical less developed phases (see picture 4). Both between and inside a puzzle or a platform, the development alternates between “slowing bottlenecks” and phases of their solving. First, easier bottlenecks are solved, then the more demanding ones can be solved, but only if the time is ready for it. Hence, there can be said to be a strong belief in path-dependence in future’s societal transformation in Naisbitt’s (2004) theory.

Naisbitt understands the transformation of the future as a process towards qualitatively

The Pre-Industrial Platform was primarily based on steam and coal engines, railways, telegraph and iron industry. However, inside its market’s clusters and path-dependence logic, there emerged new founding and inventions, such as electricity, combustion engine (road transportation with cars), and radio (mass communication). Pre-Industrial Platform was replaced as these new discoveries

Furthermore, before the Industrial Platform’s puzzle itself was solved, new emerging inventions and discoveries, which did not directly fit the current puzzle, took place. These inventions were for example, transistor, aerospace aviation, DNA structure, and Arpanet-Internet. Probably, around the end of 20st century, these inventions established the new platform of Information Society.

As Information Society is not going to be the end, we are able to map inventions, drivers or fields from our current puzzle, which are most likely to become the platform of the next era, as they do not seem to fit optimally into the present one. These non-fitting new issues may well be, for instance, ubiquitous technology, NBG (Nano, Bio, Gene), cognitive engineering (manipulation of human brain and consciousness), and new materials science, which combines findings from NBG to more conventional advantages of chemistry, physics, medicine, metallurgy, etc⁴.

Naisbitt (2004) himself did not give name to the next platform, but Aaltonen (2007: Chapter 6) has called it NBIC (Nano, Bio, Information Technology, Cognitive Science) platform, for example. Nevertheless, in respect to this theory’s approach, I would instead prefer to call it The Age of Conscious Technology or the Fusion Age.

View III: Energy as the driver of societal change and emergence

Harold F. Blum (1968) can be considered as a pioneer of combining the laws of thermodynamics^5,6 into biological or other kinds of evolving systems. From the point of view of biology and social systems, his ground-breaking finding was, that all living things live far away from equilibrium (see Prigogine & Stengers, 1984: 131-176) by constantly absorbing free energy from their environment with which they are interconnected. If a living system’s connection to its environment’s energy sources is closed, the system will eventually die or move to an equilibrium state. When an organism lives (maintains its orderly existence or evolves) by absorbing free energy sources, it means, that there is a local process, where entropy is slightly decreased. To the environment, the effect of this process is a much larger increase of the overall entropy. Naturally, energy can only be transformed in one direction, from usable or warmer to unusable or colder, meaning towards entropy. However, it is possible to locally reverse entropy, to create or maintain order, but only by using up additional (or exponential amount of) energy in the process, which again of course increases the entropy of the whole environment.

According to Jeremy Rifkin (2002, 46-49), the sun is the source of free energy on the earth. Plants take up the sun’s energy in photosynthesis and provide a source of concentrated energy that animals can then consume. The process of maintaining a non-equilibrium state is costly in terms of energy, and the more evolved the organism, the more energy it requires to sustain itself against equilibrium. Rifkin (ibid.) gives an example: consider the case of a simple food chain consisting grass, grasshoppers, frogs, trout, and humans. Grass is able to collect certain amount of solar energy, which the first level predator may use as its primary energy source. The first level predator is a prey to the second level predator, which again is a prey to the third level predator and so on. In each step of devouring the prey, about 80-90% of the energy is simply wasted and lost as heat to the environment. Therefore, only 10 to 20 percent of the energy of the prey is absorbed by the predator. “Three hundred trout are required to support one man for a year. The trout, in turn, must consume 90,000 frogs, which must consume 27 million grasshoppers, which live off of 1,000 tons of grass” (ibid.). In other words, the amount of energy needed to keep each more evolved species up the food chain alive, especially a man, is a very demanding task, which wastes repeated exponential amounts of solar energy and increases the overall entropy.

McNeill & McNeill (2005: 330-350) have listed the changes in annual human energy consumption in history. An average adult’s basic metabolism requires 3 to 5 Gigajoules per year. In hunter-gatherer societies the total average energy consumption per adult was 3 to 6 times bigger than basic metabolism. In agricultural societies the average energy consumption per adult rose up to 18 to 24 times bigger, and in average industrial society it ended up to be 70 to 80 time bigger than adult’s basic metabolism (ibid). Furthermore, among industrial societies, the USA is another story, as pointed out. It is a home of less than 5% of the world’s population, but it consumes approximately 25% of all energy that is produced in the whole world.

Both Steven Johnson (2003: 109-112) and Jeremy Rifkin (2002: 53-63) are using the Roman Empire as a case study of correlation between the laws of thermodynamics and the rise and fall of a social organization. Johnson (2003: 110-111) proposes us to:

Rifkin (2002: 59) states that the popular conception is that the Roman Empire collapsed because of the decadence of its ruling class, the corruption of its leaders, the exploitations of its servants and slaves, and the superior military tactics of invading barbarian hordes. “While there is merit to this argument, the deeper cause of Rome’s collapse lies in the declining fertility of its soil and the decrease in agricultural yields.” Due to erosion and running out of sufficient forests, the agricultural or market production could finally not provide enough energy to maintain Rome’s infrastructure and the welfare of its citizens. Furthermore, this is exactly the same what has happened with all great civilizations; greater energy-flow through, in turn, allows human settlements and population to grow, social life to become more dense and varied, and culture to advance. Societies collapse when the energy flow is suddenly ceased. The collapse characterized by a reduction of food, fuel and goods surpluses, means less stockpiles for the government to distribute public aid to the poor, and more winnowing of invest or repair the critical infrastructure, in addition with less capabilities to maintain government bureaucracy, sufficient army or educated civil servants, etc. A large population, whose numbers grew during the good times, suddenly enjoys less energy per capita even though the people are working longer and harder. Finally, this causes defiance and lawlessness, a breakdown in central authority, a depopulation of urban areas, and increasing invasions and pillaging by marauding groups of armies (ibid.: 53-57).

In their massive work on all human history, McNeill & McNeill (2005) are following exactly the same kind of storyline as Rifkin here. These historians’ presentation goes from first showing what happened in history to explaining why these things happened that way after all. Their major point of view is to discuss the history of the evolving human network on the earth. In different parts of the earth, the human race has developed from hunter-gatherer groups to nomad and agricultural societies, and finally to more complex urban civilizations, which, however, have always eventually completely disappeared or fallen back to less complex societies (ibid.: 20-105). This has been an ever ongoing two-way process, which has been strongly related to climate changes (period of warmer or colder weather) (ibid.: 160-190), technological or social innovations (emergence or immergence [fading] of an innovation), and the strength of the human network (meaning especially the amount of goods, food, people, and ideas that are flowing from society to society, and the general division of labour—and the question where the core of flows is located) (ibid.: 170-190).

Energy⁷ has been proven to be a vital driver for any emergence or immergence [fading] of human societies in history (ibid.: 460-475; Diamond, 2003: 85-100). Energy surplus gathering to the centres of societies has taken place either through just one of the above mentioned energy gathering factors or through multiple such factors occurring simultaneously in an area. To give one example, ploughing groups turned out to be the major driver of European development. They enabled efficient grain growing in all most all Western Europe’s wet clay lands, which of course was followed by population growth and civilization growth. It strengthened the general confidence between people, which resulted in new economic innovations such as establishing limited companies. It enabled the establishment of chivalries, which ensured increasing inventories, investments and public security and stability. (McNeill & McNeill,

As mentioned above, the further from equilibrium the organization is, and the higher the level of its complexity (meaning more links, nodes and flows), the more energy is required to maintain its structure. As the USA alone is consuming 25% of the world’s energy production today, it is believable that its energy consuming structure may also be the most complex among the industrial countries.

According to Emmanuel Todd (2003: 78-120), the USA, as the “only” world Empire at the moment, has got its position, by becoming the core of the world economy’s flows, where it has been possible to gather most of the world economy’s surpluses, and therefore to strengthen itself. Its own industry has been practically declining since 1990, but its GDP has been growing strongly at the same time - how is this possible Todd asks?

In his study, Todd (ibid.) concludes⁸ the answer as follows. The world has accepted the USA to take the position of the State in world economy. In Keynesian theory this position refers to the actor which constantly consumes and thereby ensures the demand in the national markets. Todd claims, that the USA’s GDP is growing because its domestic enterprises have been able to gather more and more capital, and the volatility in the markets has been constantly growing. There, however, lays the underlying bubble of the USA economy. The USA trade deficit has been increasing in enormous speed for a long time. At the moment USA is borrowing $665 billion annually from foreign lenders to finance the gap, and the national debt is reaching a milestone of $10,000 billions quite soon. These trade deficit costs have been hidden for the past few years, predominantly by the historically low interest rates, which resulted from the Federal Reserve’s attempts to spur economic recovery after the 2001 (Economic Policy Institute 2006). In addition, the finance and insurance sectors’ share of the GDP in USA has been growing faster than has been realistic to expect. Todd believes that the Enron bankruptcy and the Andersen bookkeeping scandal 2002 were only the tip of the iceberg in the USA’s finance markets. Practically, USA has been financing its consumption by distributing and printing virtual currency to their trade partners, which is, according to Todd, just a more polite way to collect taxes to the elite in the centre of the Empire. In comparison, the Roman Empire had to use military forces to ensure its energy surplus gatherings from its reluctant provinces and neighboring countries (Todd, 2003: 95-110).

Interconnection and Deviations between the Three Theories

In this paper, I want to show both, how the three theories are intertwined in dissect of societal transformation, and how complexity research concepts, especially emergence, path-dependence and increasing returns, can be interconnected to such discussion⁹.

The basic ideas illustrated in Figure 5 are:

The top row of Figure 5 describes the principles of the third theory: Ultimately all emergence is enabled or blocked by the laws of thermodynamics and societal emergence makes no difference here. Increase in energy (and other resources) flows pushes also large and complex dissipative systems further from equilibrium, where interactions and speed of transfers are more intense and faster. That enables emergence of even more complex and energy consuming irreversible structures. In other words, increase of available “food/resources” in a system allows emergence of new levels to the “food chain”. However, that leads us to another question. If the energy surpluses enable societal emergence, then how, in practical terms, the new structures are self-organizing to social systems?

As presented above, the first practical way to explain the irreversible emergence in social systems or societal transformation is to emphasize autocatalysis, bifurcations, adjacent possible, regenerative growth, nucleation, above the other generic principles of complexity. This approach can especially be seen in Malaska’s theory, but also Brian W. Arthur’s theory has similar characteristics. Here, the basic idea is, that in societal transformation, the macro-level transformation is usually started with a catalyzing invention which is beneficial in terms of the dominant mode. Once the catalysis in the markets is started by that beneficial invention, the system will be pushed further from equilibrium, and therefore, there will be a more diverse space of possibilities created (stronger aim into adjacent possible). Next, due to aim into adjacent possible and increasing returns in the process, there will be a necessary bifurcation period ahead (see the small figure with increasing returns leading away from equilibrium growth curve). Finally, the process will turn into auto-catalysis where the original invention changes the whole system. For instance, a small invention or a cluster of inventions, such as ICT, will eventually become a vital part of every fields of the society, and furthermore, all processes of the society will be transformed into favorable form for the ICT.

The other approach for describing the emergence is to emphasize path-dependence, internal gating mechanisms, interdependence, coevolution, connections, historicity, platforms, bottom up clustering, and feedbacks, above the other generic principles of complexity. Here, instead of putting the stress on searching the space of possibilities, the focal interest is located on the role of internal gating mechanisms which hold together the internal structure and allow far from equilibrium in the transformation. These internal gating mechanisms base mostly on historicity, interdependence, connections and path-dependence, and they function as boundaries or gatekeepers to all clustering and emergence. However, due to interactions and feedback loops, these platforms or internal gating mechanisms allow many synchronic coevolutions, adaptations and minor (ad hoc) emergences, as long as the process remains within the boundaries (see the smaller platform figure in Figure 5).

In the previous paragraphs, basing on the study of the three theories, there was given two possible ways to explain irreversible emergence of more complex societal structures. Hence, it is crucial to ask, are these approaches just different ways to describe the very same phenomenon, or is there really some novelty for our understanding of complex evolving systems here? Are there situations where transformation sometimes follows more autocatalysis and search of space of possibilities, and it sometimes follows more path-dependence and attachment of internal gating mechanisms? And why would/wouldn’t it go that way?

Conclusions

In the previous sections, I have presented three main theories or approaches, which deal with societal change. Each of the theories discuss the social emergence and path-dependence in social organization, and the logic of societal transformation. Neither of the theories can be considered as purely social science or complexity research—they rather represent both, which here means that they are multi inter-, inter- or transdisciplinary approaches to the issue.

In Mitleton-Kelly (2003: 23-50), the original core of the complexity research’s fifth research area was the Brian Arthur’s theory. Here, I propose the following three theories to be considered as extensions or new benchmarking views to that research area. In the proposed first theory: Pentti Malaska appears to understand social emergence pretty much in the same way as Arthur - there are necessarily new seeds of transformation, which cluster and then start to change the entire market logic, if the time is favorable to it. However, Malaska’s point of view to path-dependence deviates from Arthur’s, as he emphasizes the social transformation’s necessity to have alternating extensive, intensive, and regenerative growth periods, which also occur partly in parallel with each other.

In the second theory, John Naisbitt understands the role of social emergence to some extent in the same way as Arthur and Malaska. For Naisbitt, it refers to an (important) seed, which establishes a platform together with a few other (important) seeds, which together support each other relevantly. Another (minor) social emergence is subordinate to the platform—here the subordinate emergence may be either absorbed or rejected by the platform. In addition, there is a strong belief on path-dependence in Naisbitt’s theory. There, the transformation is seen as a qualitative and chronological process where new platforms emerge, bottom-up, when the bottlenecks of previous level are fully fixed. In other words, when all of the platform’s relevant pieces are relevantly put together.

In the third theory, which here has been named energy as the driver of societal change and emergence, societal emergence and path-dependence are both explained through energy, as the name indicates. Different systems are in different levels of complexity. The higher the system’s complexity level is, and the further from equilibrium it is, the more energy gathering from the surrounding environment is required to maintain that position. Sudden or steady increase in flows of energy means acceleration in volatility in any kind of system—reversible or irreversible. Thus, more energy to dissipative and irreversible structure allows, e.g., more connections and more intense non-linear flows between nodes and its local networks, which eventually forces the system into more unstable structure (Mitleton-Kelly, 2003: 41). Finally, that enables a phase transition into higher level of complexity (Johnson, 2003: 110-111). And in the contrary case, the phase transition is forced into opposite direction—into immergence.

Therefore, in the third theory, both social path-dependence and social emergence are bound to laws of thermodynamics, where all the other factors that are effecting the societal transformation can be seen as subordinate to energy. Thereby, these other factors’ role is merely instrumental, as their true influence to transformation bases on the ability to advocate or prevent energy flows through the system.

To conclude, all three theories are dealing with social path-dependence and emergence in a way which allows us to add those to the fifth research area of complexity. The theories are congruent in some parts, but deviate in others. Together they provide a firm inter- or transdisciplinary ground for benchmarking issues of social systems complexity.

Notes