johnywrites.com

Category: Self-Organization

  • Effectual Self-Organization(Reposted): Could it be a mindful praxis for self-organization

    In the last few posts, I have been developing the idea of effectuation as a self-organization principle against the idea of expertise acquired by entrepreneurs via experience and deliberate practice. Following are two blog posts in which I have elaborated my thoughts.

    1. Why expertise theory of effectuation might be flawed?; Here I argue why expertise framing of effectuation might be flawed
    2. Self-Organization: Paul Cilliers and Saraswathy: Here I assess effectuation using Paul Cilliers’s attributes of self-organization. Arguing that effectuation simulates the action models of self-organizing systems.

    I have tried to demonstrate that the ideas proposed by effectuation might fit perfectly with self-organization principles. Advancing that point, the following are some of the complexity principles i find as potentially associated with effectuation and its core principles(heuristics).

    1. Self-Organization/Effectual dynamics

    I argue that “effectual dynamics” might be the dynamics of self-organization. Self-Organization refers to the feature of systems that appear to organize themselves without external direction or control. Self-organization has been used to describe swarms, flocks, traffic, and many other systems where the local interactions lead to a global pattern or behavior (Camazine et al, 2003; Gershenson, 2007). Intuitively, self-organization implies that a system increases its own organization. Self-organization of the effectual entrepreneur is initiated with an examination of the means available to an entrepreneur. The questions “Who am I?”, “What do I know?”, and “Whom do I know?” allow for an examination of the means available to an entrepreneur, which allows him or her to consider what he or she can do (Sarasvathy & Dew, 2005). Through interacting with others and engaging with stakeholders, the entrepreneur discovers new means and establishes new goals that allow for revaluation of means and possible courses of action (Fisher, 2012).

    2. The attractor/ Intention

    Self-organizing systems typically evolve towards a state of equilibrium, or an attractor state. Almost any dynamical system can be seen as self-organizing; if it has an attractor towards which the system dynamics will tend to move, thus increasing by itself its own organization. According to Kauffman(1995), “the trajectory converges onto a state-cycle attractor around which the system will cycle persistently thereafter. A variety of different trajectories may all converge on the same state cycle, like water draining into a lake. The state-cycle attractor is the lake, and the trajectories converging onto it constitute its basin of attraction”. So the question is, Who or what constitutes one of the key initial attractor according to effectuation. Is it the entrepreneur, or intention? Since effectuation has a lot of roots in the work of Herbert Simon, especially “The Sciences of the Artificial” (Simon, 1968), I prefer to take evidence from his work, quoted by Saraswathy herself; “For Simon, human intention and design were central to the social sciences, and the word ‘man-made’ was synonymous with artificial” (Sarasvathy, 2008). From that foundation, it is logical to assume recognition of “intention as the attractor (Juarrero, 2010)”. Intention is also a valid concept in entrepreneurship (Bird, 1989; Shapero and Sokol, 1982; Krueger and Carsrud, 1993). According to Juarrero(2004), “new intention reorganize the earlier state space into a more differentiated and complex set of qualitatively novel options. This means that once an agent formulates a prior intention, every possible behavioral alternative no longer requires consideration; only a partitioned subset does”.

    3. Phase space disposition

    According to Saraswathy, the process elements of effectuation begin with entrepreneurs asking who they are, what they know, and whom they know. This corresponds to the idea of knowing the disposition of phase space or state space of a complex adaptive system. In complexity science, the ‘phase space'(or state space) is the representation of all possible instantaneous states that can occur in a physical system (Butkovskiy 1990, Sayama 2015). It can be thought of as the space within, around, or adjacent to which a complex adaptive system can self-organize and emerge. While we may not be able to know precisely how a system might change, we do know that it will be most likely within the phase space. A change in emergent phenomena within a phase space may be incremental. A radical change suggests a shift in phase space, a qualitative difference in the system (Byrne & Callaghan, 2014). According to Dave Snowden(2017a), in complex adaptive systems, “at a system level, we have no linear material cause but instead we have a dispositional state, a set of possibilities and plausibilities in which a future state cannot be predicted.” This is particularly important because, in a complex system, phase space disposition, is what decides on the evolutionary potential of the system, not any specific fixed goal. If a system is complex(no causality), “you can’t set outcome targets a priori, but you can define a vector target (direction and speed of change from the present against intensity of effort). You can’t manage to a desired future state but have to manage the evolutionary potential of the situated present. You can’t predict the future, but you can increase resilience in there the here and now which will allow you to manage that uncertainty” (Snowden, 2017b). 

    I argue that an effectual entrepreneur, by asking questions such as; who they are? what do they know? and whom they know? etc. effectively is trying to make sense of the dispositional propensities, so that they can utilize the evolutionary potential of the present to decide what to do.

    4. Adjacent Possible.

    From the understanding of disposition comes the “The bird-in-hand principle” which refers to a principle of means-driven(as opposed to goal-driven) action. The emphasis here is on creating something new with existing means rather than discovering new ways to achieve given goals. To effectuation, entrepreneurs focus on what they can do and do it, without worrying much about what they ought to do. This idea is similar to acting in the adjacent possible (Kauffman, 1996), i.e. a kind of zone of proximal development (Vygotsky, 1978), towards which change and evolution are more likely because of the current disposition of the system. The concept of “adjacent possible” was introduced by Stuart Kauffman (1996; 2000) in evolutionary biology and complex adaptive systems to explain how biological evolution can be seen as exploration and actualization of what is adjacent possible. It can be defined as “the set of possibilities available to individuals, communities, institutions, organisms, productive processes, etc., at a given point in time during their evolution” (Loreto 2015, p. 9). The concept of the “adjacent possible” is useful for understanding how entrepreneurial adjacent possibilities emerge, and how the new adjacent possible will lead to yet newer adjacent possibilities. In the case of effectual entrepreneurs, they will focus on the adjacent possible than worry about things they don’t possess. They will focus on what they can do and do it.

    Any failure inside the zone of adjacent possible will not likely result in system destruction, but likely help the development of system resilience. The affordable-loss principle to me is a heuristics based on this idea. It prescribes committing in advance to what one is willing to lose rather than investing in calculations about expected returns to the project. If an effectual entrepreneur commits 6 months and 10000k, that commitment itself will shape the constraints of the adjacent possible.

    4. Co-evolution and Co-adaptation

    For a system to self-organize, its elements need to communicate: they need to “understand” what other elements, or mediators, “want” to tell them (Gershenson,2007). Thus, first of all, in a complex system, dynamics of self-organization are initiated and manifested by heterogeneous agents interacting with one another in a non-linear and continuous way. Even if specific agents may only interact with a few others, the impact of these interactions are propagated throughout the system. Accordingly, agents co-evolve with one another (Anderson, 1999). Through this interaction, agents strive to improve their fitness with the environment but the outcome of these attempts depends on the disposition and behaviors of other agents (Mitleton-Kelly, 2003). Thus, co-evolution is one of the key themes when it comes to viewing the system as a whole(the nested and entangled relationships with multiple complex adaptive systems), which refers to the simultaneous evolution of entities and their environments, whether these entities are organisms or organizations (Baum & Singh, 1994). It encompasses the twin notions of inter-dependency and mutual adaptation, with the idea that species or organizations evolve in relation to their environments, while at the same time these environments evolve in relation to them. In effectuation, this is parallel to initiated interaction and the crazy-quilt principle. This principle involves interacting and “negotiating with any and all stakeholders who are willing to make actual commitments to the project, without worrying about opportunity costs, or carrying out elaborate competitive analyses. Furthermore, who comes on board determines the goals of the enterprise. Not vice versa”. This involves the co-evolutionary potential of interacting agents constituted by the principles we have discussed till now but applied to the other side. They are; The Intention(attractor) of other agents, Phase space disposition of interacting agents, Adjacent-possible of interacting agents.

    5, Acknowledging and appropriating Emergent property

    Complex adaptive systems show emergent properties. Emergent properties refer to a characteristic that is found across the system but which individual parts of the system do not themselves hold. E.g. Human heart is made of heart cells. But heart cells on their own don’t have the property of pumping blood. You will need the whole heart to be able to pump blood. Thus, the pumping property of the heart is emergent. A complex system like entrepreneurship has emergent property. That means the emergent or emerging venture idea might be different from the ideas the entrepreneur has initially conceived. Thus initial idea may be to start HTML5 supported location-based service; The emergent outcome could be Instagram. The initial idea may be to develop an app to compare two people’s pictures and rate which one was more attractive; The emergent outcome could be Facebook. The lemonade principle of effectuation is based on adapting, using, and improvising according to emergent realities, whether it is perceived as negative or positive. It suggests acknowledging and appropriating contingency by leveraging surprises rather than trying to avoid them, overcome them, or adapt to them. This means accepting the emergent realities as it comes, adapting, acknowledging, and appropriating the contingencies as it unfolds.

    The pilot-in-the-plane principle urges relying on and working with the human agency as the prime driver of opportunity rather than limiting entrepreneurial efforts to exploiting exogenous factors such as technological trajectories and socioeconomic trends. This is equivalent to elements of Lichtenstein’s(2016) concept of generative emergence that views entrepreneurial emergence as intentional, and agency, even if distributed, as the source of successful organizing. To the framework, intention is the primary attractor around which self-organisation takes place. In order for effective self-organization to take place, the agent must use agency, not to exert control that is driven by his/her own bounded rationality, or the rules of perceived local optima, but a kind of agency that is distributed (Garud and Karnøe, 2005)and embedded as well (Garud and Karnøe, 2003)

    6. Effectual Self-organisation cycle

    A complex system is always dispositional and I have discussed quoting Snowden that we can only know the system by knowing how it is disposed. “you can’t set outcome targets a priori, but you can define a vector target (direction and speed of change from the present against intensity of effort). You can’t manage to a desired future state but have to manage the evolutionary potential of the situated present”. Since the system is always changing, the bird in hand or disposition is also parallelly evolving. This warrants continuous reappraisal of the situated present. The effectual cycle suggests always looping back and cycling through five core principles in a non-linear manner(bird-in-hand, affordable-loss, crazy-quilt, lemonade, pilot-in-the-plane). More specifically there are two types of converging cycles mentioned; expanding means and converging goals. The expanding-means cycle looks for increases in resources, and the Converging goals cycle adapts the goals. “It accretes constraints on the venture that converge into specific goals that get embodied in an effectual artifact over time” (Sarasvathy et al, 2014; Sarasvathy & Dew, 2005, pp. 543–544). This is also a feedback about emergent realities that will lead to estimation of the new phase space disposition, new adjacent possible, new co-evolutionary potential, new action, etc. 

    Part of ESOLoop: An Entrepreneurship Self-Organization Framework

    Citations

    Camazine, Scott, Jean-Louis Deneubourg, Nigel R. Franks, James Sneyd, Guy Theraula, and Eric Bonabeau. Self-organization in biological systems. Princeton university press, 2020.

    Gershenson, Carlos. Design and control of self-organizing systems. CopIt Arxives, 2007.

    Fisher, Greg. “Effectuation, causation, and bricolage: A behavioral comparison of
    emerging theories in entrepreneurship research.” Entrepreneurship theory and practice
    36, no. 5 (2012): 1019-1051.

    Simon, Herbert A. The sciences of the artificial. MIT press, 1996.

    Juarrero, Alicia. “Intentions as complex dynamical attractors.” Causing human actions:
    New perspectives on the causal theory of action (2010): 253-276.

    Bird, Barbara, and Mariann Jelinek. “The operation of entrepreneurial intentions.”
    Entrepreneurship theory and practice 13, no. 2 (1989): 21-30.

    Krueger, Norris F., and Alan L. Carsrud. “Entrepreneurial intentions: Applying the theory
    of planned behaviour.” Entrepreneurship & Regional Development 5, no. 4 (1993):
    315-330.

    Juarrero, Alicia. “The self-organization of intentional action.” Revue internationale de
    philosophie 2 (2004): 189-204.

    Butkovskiy, AG 1990, Phase Portraits of Control Dynamical Systems, Springer
    Netherlands

    Sayama, Hiroki. Introduction to the modeling and analysis of complex systems. Open
    SUNY Textbooks, 2015.

    Byrne, David, and Gillian Callaghan. Complexity theory and the social sciences: The
    state of the art. Routledge, 2013.

    Snowden, David. Inclinations-dispositions (https://thecynefin.co/inclinations-dispositions/), Snowden. 2017(a)

    Snowden, David. Systems thinking & complexity (https://thecynefin.co/systems-thinking-complexity/), Snowden. 2017(b)

    Goldstein, Jeffrey. “Emergence, creativity, and the logic of following and negating.” The Innovation Journal: The Public Sector Innovation Journal 10, no. 3 (2005): 1-10.

    Goldstein, Jeffrey. “The construction of emergent order, or, how to resist the temptation of hylozoism.” Nonlinear dynamics, psychology, and life sciences 7, no. 4 (2003): 295-314.

    Kauffman, Stuart A. “Investigations: The nature of autonomous agents and the worlds
    they mutually create.” Santa Fe Institute, 1996.

    Loreto, Vittorio. “Unfolding the dynamics of creativity, novelties and innovation.” White
    paper of the Kreyon project (2015).

    Gershenson, Carlos. Design and control of self-organizing systems. CopIt Arxives, 2007.

    Anderson, Philip. “Perspective: Complexity theory and organization science.”
    Organization science 10, no. 3 (1999): 216-232.

    Mitleton-Kelly, Eve. “Ten principles of complexity and enabling infrastructures.” Complex
    systems and evolutionary perspectives on organisations: The application of complexity
    theory to organisations 1 (2003): 23-50.

    Baum, Joel AC, and Jitendra V. Singh, eds. Evolutionary dynamics of organizations.
    Oxford University Press, 1994.

    Lichtenstein, Benyamin. “Emergence and emergents in entrepreneurship: Complexity
    science insights into new venture creation.” Entrepreneurship Research Journal 6, no. 1
    (2016): 43-52.

    Garud, Raghu, and Peter Karnøe. “Distributed agency and interactive emergence.”
    Innovating strategy process (2005): 88-96.

    Garud, Raghu, and Peter Karnøe. “Bricolage versus breakthrough: distributed and
    embedded agency in technology entrepreneurship.” Research policy 32, no. 2 (2003):
    277-300.

    Sarasvathy, Saras, K. Kumar, Jeffrey G. York, and Suresh Bhagavatula. “An effectual
    approach to international entrepreneurship: Overlaps, challenges, and provocative
    possibilities.” Entrepreneurship Theory and Practice 38, no. 1 (2014): 71-93.

    Sarasvathy, Saras D., and Nicholas Dew. “New market creation through transformation.”
    Journal of evolutionary economics 15, no. 5 (2005): 533-565

  • Entrepreneurship and Synergetics

    Synergetics is an interdisciplinary theoretical approach that studies self-organization in complex systems(systems that are characterized by openness, dynamics, and complexity). It was developed by physicist Hermann Haken(1969) through his research experiments on laser light. He noticed unpredictable patterns emerging that cannot be explained by linear models. The properties of light change in a self-organized manner when the laser reaches a critical point or “laser threshold”, and such emergent order sets the control parameter which enslaves the system.

    (This is an updated post)

    For a real explanation, listen directly from the master: Hermann Haken

    Synergetics and Entrepreneurship

    My initial exposure to synergetics from an entrepreneurship related scholarship started with reading Jeffrey Goldstein’s article(attached) in which he stressed his radical construction point of view that paints a negative picture. He argues;

    “Although these connotations of self-organization have provided a corrective to the outdated belief that novel order in a system can only come about through the imposition of external order, a careful inspection of research in complexity theory reveals that the emergence of new order is more appropriately constructed rather than self-organized as such (Goldstein 2003).”

    EMERGENCE, CREATIVITY, AND THE LOGIC OF FOLLOWING AND NEGATING by Goldstein’ 2015

    Goldstein further specifically pointed to Haken; in that he adds;

    “An example is that much touted emblem of self-organization, the laser with its property of ultra-focused coherence (see Haken, 1981). In actuality, though, laser light hardly comes about either spontaneously or through inner direction. On the contrary, it requires the most stringent of laboratory manipulations and constraints (see a list of these in Strogatz, 2003). An examination of other examples of self-organization reveals a similar constructional nature of emergent phenomena (see, e.g., Nicolis, 1989)”

    EMERGENCE, CREATIVITY, AND THE LOGIC OF FOLLOWING AND NEGATING by Goldstein’ 2015

    I definitely don’t buy this argument by Goldstein. I believe as always that self-organization is a ubiquitous feature of all open complex adaptive systems.

    Andreas Liening of TU Dortmund

    In entrepreneurship, a pioneering effort to apply Synergetics is coming from Prof Andreas Liening and colleagues of TU Dortmund. The top reads are;

    1. Complexity and Entrepreneurship: Modeling the Process of Entrepreneurship Education with the Theory of Synergetics
    2. Synergetics—Fundamental Attributes of the Theory of Self-Organization and Its Meaning for Economics(OPEN Access)

    Although I am extremely interested in reading anything relating to entrepreneurship and complexity, I totally disagree with the “Entrepreneurship Mindset” as the purpose of Entrepreneurship Education promoted by Liening. To see my reasons check this, this, this, this, this and this

    It is very easy to fall into the trap of traditional representational cognitive psychology and its lazy dependence on decontextualized hard or impossible to define concepts like Mindset.

    Some potential issues with application of self-organization and synergetics in education

    It is confusing when an outsider looks at education and learning science for the first time to find application ideas. It is very easy to be trapped in a cultish eco-chamber. Even though I agree that It is essential to read people whom we disagree with, a serious issue arises when we start to blindly believe everything they say. This is especially true if one doesn’t have the necessary expertise and diversity in their system to figure out the flaws of the argument. 

    Example; Paul A. Kirschner who is one of the most reductionist of all the education scholars with his famous works like, “Why Minimal Guidance During Instruction Does Not Work”  is also famous for his work on learning in complexity, ” Ten steps to complex learning”.  A new observer might be mistaken to believe that Kirschner is the go to authority in complexity in education. This is a huge mistake. This points to serious issues with the application of synergetics in particular and complexity science in general without any understanding of domain epistemology.

    1. Those with domain expertise may use complexity theory to fit in with their long-accumulated path dependency.
    2. They may use a complexity tag to avoid being called a reductionist.
    3. Those with complexity background may fall for the obvious and visible part of domain knowledge.
    4. Those with ideas and tools to sell may try craft a much less uncertain version of complexity;.
    5. As often pointed out by people like Dave Snowden, those with a complexity background, especially those associated with mathematical modeling and Santa Fe may assume that they can model human complexity by developing agent-based models as they do for some idealized version of Ant behavior. This can be viewed as a reductionistic tendency inside the complexity sciences (http://www.human-current.com/archived-episodes/tag/anthrocomplexity)

    All the above can be viewed as going against the ethics of complexity, especially when proposed as solutions for other people and other people’s children.

    According to Synergetics Philosophers Helena Knyazeva and Sergey Kurdyumov, “The synergetic assertions can apply to many scientific disciplines. They are functioning on the level from which a great scope of scientific disciplines can be embraced. However, such an approach has also a negative side. The higher the level of the view is the less concrete details can be distinguished. On the other hand, the deeper we penetrate particular details the less place seems to remain for synergetics itself” They adds; “Synergetics can provide us only with general frames of consideration, a mental scheme or a heuristic approach to a concrete scientific investigation. Concrete applications of synergetic models to complex human or social systems presuppose further detailed scientific investigations. Such investigations can be carried out only by the use of a profound knowledge of a certain disciplinary field and/or with a close collaboration with specialists in a corresponding scientific discipline. Thus, synergetics gives a certain approach or a direction of research, or, to put it in terms of psychology, a scientific attitude. The rest is the matter of every concrete investigation”

    Some interesting articles by Russian philosopher Helena Knyazeva on synergetics are attached

    Synergetics: New Universalism or Natural Philosophy of the Age of Post-Nonclassical Science?

    ARBITRARINESS IN NATURE: SYNERGETICS AND EVOLUTIONARY LAWS OF PROHIBITION(Co-authored with Haken)

    SYNERGETICS OF HUMAN CREATIVITY; HELENA and HAKEN

    The Synergetic Principles of Nonlinear Thinking

    Synergetics and the Images of Future

    THE COMPLEX NONLINEAR THINKING: EDGAR MORIN’S DEMAND OF A REFORM OF THINKING AND THE CONTRIBUTION OF SYNERGETICS

    Nonlinear synthesis and co‐evolution of complex systems

    NONLINEARITY OF TIME IN THE COMPLEX WORLD

    The Synergetic World View and Its Synthetic Value

    FIGURES OF TIME IN EVOLUTION OF COMPLEX SYSTEMS

    Recent works

    Virtual Reality from the Standpoint of Complexity Science

    Paradigm Shift in the Understanding of the Creative Abilities of Consciousness

    Strategies of Dynamic Complexity Management

    Active Innovative Media as Co-Evolutionary Landscapes

    Cognitive Networks: Interactivity, Intersubjectivity, and Synergy

    Complexity Studies: Interdisciplinarity in Act

    The Idea of Co-evolution; Towards a New Evolutionary Holism

  • What should be in a complexity friendly design solution for entrepreneurship

    Since entrepreneurship is a complex domain, proposed design solutions must recognize complexity as a core design challenge. It must also consider the disposition and bounded rationality of the decision-making agent in question.

    I have recently read an article by Herbert A. Simon “Can there be a science of complex systems?” in which he listed 4 principles of complex system design. (Meanwhile, the article is freely available Here online). They are;

    1. Homeostasis.
    2. Membranes
    3. Specialization
    4. Near-Decomposibility.

    Reading it inspired me to post an aggregate of ideas that I have assembled for an ongoing project. In my literature review, I have found the following features that might help in a sustainable complexity-friendly design.

    They;

    *Must begin with the right view: The right worldview (Dent, 1999) is a necessary precondition to effective design. If the world view is reductionist or simplistic, ignoring important unknowns, the design will reflect this weakness.

    *Must acknowledge and promote self-organization: Self-organization (Heylighen, 2008) refers to the feature of systems that appear to organize themselves without external direction, manipulation, or control. This promotes ecologically grounded evolution and dynamics. A sustainable, complexity-friendly model must promote self-organization instead of one-size-fits-all models, rigid prescriptions, or top-down order.

    *Must promote exploration: While self-organization may promote local optimization, the dispositional capability for exploration (Gupta et al, 2006) is necessary to facilitate the journey towards global optima. A sustainable complexity friendly model must have the capability for continuous multidimensional exploration.

    *Must promote diversity (Page, 2010) integration (Martin, 2009), and inclusiveness (Pless and Maak, 2004): Decisions in a complex domain like entrepreneurship cannot be understood with linear thinking or binaries. Since it is impossible to know various emergent decision contexts beforehand, it is always ideal to design solutions for such variables and contingencies. That means a design must promote diversity and not exclude ideas, models, theories, etc., by prescription or omission.

    *Must be contextually adaptive: Every context is unique, and thus we need solutions that are adaptable and usable for various contexts, as it emerges. Adaptive systems involve designing the elements of a system to find by themselves the solution of the problem. Like this, when the problem changes, the elements are able to dynamically find a new solution. We can say that such a system self-organizes (Gershenson, 2007).

    *Must provide evolvability to the agent and must have evolvability of its own: Evolution and evolvability (Pigliucci, 2008; ScienceDaily, 2013) are a fundamental feature of nature, biology, and human social life. A sustainable entrepreneurship framework must have the evolutionary potential of its own, and also must enable evolvability to the entrepreneurial agents.

    *Must protect agency from hijack: Prescriptive models have agency of their own, and are designed to hijack entrepreneurial agency by providing a model-centric view of the world. Commitment to one-size-fits-all models may result in the agent’s evolutionary, learning, adaptive potential being seriously compromised. Thus, a sustainable complexity-friendly model must protect and promote appropriate levels of entrepreneurial agency (Garud and Karnøe, 2003) and autonomy.

    *Must acknowledge the dispositional state, including ignorance and weaknesses: Most of the existing entrepreneurship models reinforce and augment bounded rationality. A sustainable complexity-friendly model must acknowledge the possibility for bounded rationality, ignorance, and weaknesses. It must have inbuilt dispositional capabilities like distributed sense-making (Weick, 2005; Fisher, 2012) and descriptive self-awareness (Snowden, 2002), etc. to continually scan inwards and outwards for issues like ignorance, weakness, or bounded rationality.

    *Must encapsulate various complexity-friendly functional dispositions: A complexity-friendly model must also be designed with a usability perspective in mind. It must encapsulate various complexity-friendly functional dispositions(above listed) into a single framework so that an ecology of ideas, in its dynamics, will transfer to the users, not just one or two ideas.

    *Must acknowledge provisionally imperative nature of solutions, models and frameworks: This means no one-size-fits-all solutions can exist in complexity. According to Cillers(1998), In complexity, interpretations are contingent and provisional, pertaining to a certain context and a certain time frame(p. 121-122). This leads to the idea of Provisional imperative (Preiser and Cilliers, 2010; Woermann and Cilliers, 2012).

    *Must strive forward as a continuous work in progress in a perpetual construction (Prigogine, 1997): Once proposed and written down, most models or prescriptive methods never change. This is a weakness when considering the speed of radical changes happening around us. Even with this vulnerability, most ideas and models in the entrepreneurship domain are designed to be self-aggrandizing and self-perpetuating. A sustainable complexity friendly model must have the capability to change itself according to challenges.

    Part of Esoloop Framework series

    Citations

    Dent, Eric B. “Complexity science: A worldview shift.” Emergence 1, no. 4 (1999): 5-19.

    Heylighen, Francis. “Complexity and self-organization.” Encyclopedia of library and
    information sciences 3 (2008): 1215-1224.

    Gupta, Anil K., Ken G. Smith, and Christina E. Shalley. “The interplay between exploration
    and exploitation.” Academy of management journal 49, no. 4 (2006): 693-706.

    Page, Scott. On Diversity and Complexity. Princeton University Press, 2010.

    Martin, Roger L. The opposable mind: How successful leaders win through integrative
    thinking. Harvard Business Press, 2009

    Pless, Nicola, and Thomas Maak. “Building an inclusive diversity culture: Principles,
    processes and practice.” Journal of business ethics 54, no. 2 (2004): 129-147.

    Gershenson, Carlos. Design and control of self-organizing systems. CopIt Arxives, 2007.

    Pigliucci, Massimo. “Is evolvability evolvable?.” Nature Reviews Genetics 9, no. 1 (2008):
    75-82.

    ScienceDaily. “Evolution Can Select for Evolvability, Biologists
    Find”(https://www.sciencedaily.com/releases/2013/11/131114193434.htm)ScienceDaily, 14 Nov.

    Garud, Raghu, and Peter Karnøe. “Bricolage versus breakthrough: distributed and embedded
    agency in technology entrepreneurship.” Research policy 32, no. 2 (2003): 277-300.

    Weick, Karl E. “5 Managing the unexpected: complexity as distributed sensemaking.” In
    Uncertainty and surprise in complex systems, pp. 51-65. Springer, Berlin, Heidelberg, 2005

    Fisher, Kristie, Scott Counts, and Aniket Kittur. “Distributed sensemaking: improving
    sensemaking by leveraging the efforts of previous users.” In Proceedings of the SIGCHI
    Conference on Human Factors in Computing Systems, pp. 247-256. 2012.

    Snowden, David. “Complex acts of knowing: paradox and descriptive self-awareness.”
    Journal of knowledge management (2002).

    Prigogine, Ilya, and Isabelle Stengers. The end of certainty. Simon and Schuster, 1997.

  • Why expertise theory applied in entrepreneurship is flawed?

    This is an updated version of my previous blog post that explored the flaws of effectuation.

    The series has two more posts which you can read here and here (Effectual Self-Organization: Could it be a mindful praxis for self-organization).

    The empirical evidence for effectuation came from the study of expert entrepreneurs conducted by Saraswathy. She contrasts her study on entrepreneurial expertise with entrepreneurial performance which has been traditionally studied either (1) as a set of personality traits of the entrepreneur that explains the success or failure of the firms he or she creates (Llewellyn and Wilson, 2003), or (2) as a set of circumstances or attributes of the project and its environment that contains the seeds of its success or failure (Thornton, 1999). In that, she conducted a cognitive science-based study of entrepreneurial expertise using think-aloud verbal protocols. Included in that, was a 17-page problem set of 10 typical decisions in a startup firm and had a representative sample of 27 expert entrepreneurs.

    I claim that this expertise framing of effectuation is flawed and counterproductive. I propose a much more scientific way of approaching or using effectuation, i.e. Effectuation as a praxis/logic/heuristics for self-organization in complex domains, not just as possessions of expert entrepreneurs.

    Following are some reasons why I consider the expertise theory of effectuation flawed;

    Firstly, entrepreneurship is a low validity domain (Kahneman and Klein, 2009) with extreme levels of complexity. To have genuine expertise to develop, the domains must be of high validity. i.e. “Skilled intuitions will only develop in an environment of sufficient regularity, which provides valid cues to the situation” (Kahneman and Klein, 2009). This was also previously spotted in a review by Shanteau(1992), in which he confirmed the importance of predictable environments and opportunities to learn them, in order to develop real expertise. To Kahneman and Klein(2009) prolonged practice and feedback that is both rapid and unequivocal are necessary conditions for expertise, provided by predictable environments. To be more specific about the contrast, Immediate Feedback, Repeatability & Regular environment are the fundamental conditions to develop expertise. Entrepreneurship is characterized by the opposite; Delayed feedback, Non-Repeatability, Irregular complex, and an emergent environment.

    Secondly, the effectiveness of deliberate practice as claimed by effectuation will not work in complex domains like entrepreneurship. There is no scientific evidence of it. Saraswathy(2008) defines an expert as someone who has attained a high level of performance in a domain as a result of years of experience and deliberate practice (Ericsson et al, 1993). Against this, Baron (2009) raised the important problem, ie “In what tasks or activities do successful entrepreneurs demonstrate expert performance?”. Advancing that point, Baron and Henry (2010) argued that deliberate practice may not be possible in entrepreneurship and that entrepreneurs instead either learn vicariously or transfer skills learned through practice in other domains into their new ventures. Frankish et al(2013) specifically questioned the idea of learning from experience. They pointed to the lack of repetition opportunities (owing to task diversity) and the difficulty of interpreting the various causes of new venture survival, suggesting that entrepreneurs improve performance only partially based on their experience in running new ventures. Further, in recent scholarly works, it has been demonstrated that deliberate practice may not guarantee better performance in extremely complex domains. A 2014 meta-analysis (Macnamara et al, 2014) has shown that deliberate practice only explained 26% of the variance in performance for games, 21% for music, 18% for sports, 4% for education, and less than 1% for professions. This further demonstrates a low connection between deliberate practice and performance in complex unstructured domains.

    Thirdly, expertise in complex social domains are distributed (Edwards, 2010). It is not necessary that an entrepreneur must be an expert in finance, accounting, programming, law, etc. Such expertise is distributed(and or extended) across various individuals(lawyer, doctor) institutions(law enforcement, companies) and artifacts(tools, software). etc. It is not even necessary that the entrepreneur has to know the entrepreneurial core activities. He or she can still win in case she or he is in the right high network place(e.g. Harvard, Stanford, etc.), get good people to mentor and work with (e.g. Facebook case of Sean Parker, Peter Thiel), get access to specialized institutions(e.g. YC in the case of Dropbox), have a rich family to support, etc. He can also fail despite all of this(see next).

    Fourthly, complex domains like entrepreneurship are subjected to various complexity laws like power laws, Mathew effects, reputation effects, ecosystem-embedded-preferential-attachment, etc. This invalidates success as a metric of expertise. Core events in complex systems like entrepreneurship never repeat in originality(strange attractor effect), feedback is delayed, and since complex systems are governed by power laws, small things(e.g. Harvard dorm Facebook) can result in huge success, and resource-rich interventions can fail(google plus). A tangent is that the emergent property of a system may not be the result of the expertise of a particular agent or agents, but because of the dynamics of the whole system co-evolving with the ecosystem as a whole. This may prevent us from establishing any valid causal relationship between expertise and performance in a domain like entrepreneurship. Thus in complexity, high performance may not guarantee success, in that, the success of an individual does not depend uniquely on the quality of performance (Barabási, 2018). 

    Fifthly, I believe that, like the personality view of entrepreneurial achievement (McClelland,1951, 1961; Llewellyn and Wilson, 2003), the expertise view may also have some unintended counter-productive effects. It can legitimize the hubris among successful entrepreneurs, and at the same time make the aspiring entrepreneurs think that they may require deliberate practice to become a successful entrepreneur, while in-fact success could be the result of complexity-effects like Mathew effects, reputation effects, preferential attachment, etc.

    Sixthly, A very important question to ask here is; Is it even desirable to start multiple ventures than make one single venture successful. Why do people start multiple ventures? Is it because they see it as playing chess or golf? Will they start another venture if they are incredibly successful in the first business? Will a few outlier cases like Elon Musk ethically suffice us to prescribe it as a standard scientific way of thinking about the world? Do multiple successful marriages make someone a marriage expert, or unlucky and bad at marriage?. The key point I am trying to make here is that in domains like chess, multiple success may be a sign of expertise. In many extremely complex questions of life, it may be undesirable.  

    Seventhly, as I have demonstrated, most effectuation principles correspond to the dynamics of self-organizing complex system. This means it must not be limited to entrepreneurs. Herbert Simon also hinted at this aspect and suggested that there might be a connection between effectuation and Near Decomposibility (Sarasvathy and Simon, 2000). According to him (Saraswathy, 2008), Near Decomposibility is an astonishingly ubiquitous principle in the architecture of rapidly evolving complex systems, and effectuation appears to be a preferred decision model with entrepreneurs who have created high-growth firms, we should be able to link Near Decomposibility to the processes these entrepreneurs use to create and grow enduring firms–whether in an experimental situation or in the real world (Saraswathy, 2008, p.163). But instead of trying out a more fundamental complexity science-based explanation of entrepreneurial behavior, Saraswathy used the expertise theory to build the theory of effectuation. 

    Finally, I believe that effectuation if developed as a self-organization logic can be applied in other domains. It has applications in complex domains like education, learning, economics, politics, etc. Framing effectuation as a science of action in social complexity will open up a lot of possibilities. This also will make the theory more robust and useful.

    Read also: Effectual Self-Organization: Could it be a mindful praxis for self-organization

    Part of Esoloop Framework Series

    Citations

    Barabási, Albert-László. The Formula: The science behind why people succeed or fail. Macmillan, 2018

    Baron, Robert A. “Effectual versus predictive logics in entrepreneurial decision making: Differences between experts and novices: Does experience in starting new ventures change the way entrepreneurs think? Perhaps, but for now,“caution” is essential.” Journal of Business Venturing 24, no. 4 (2009): 310-315

    Baron, Robert A., and Rebecca A. Henry. “How entrepreneurs acquire the capacity to excel: Insights from research on expert performance.” Strategic Entrepreneurship Journal 4, no. 1 (2010): 49-65.

    Ericsson, K. Anders, Ralf T. Krampe, and Clemens Tesch-Römer. “The role of deliberate practice in the acquisition of expert performance.” Psychological review 100, no. 3 (1993): 363

    Frankish, Julian S., Richard G. Roberts, Alex Coad, Taylor C. Spears, and David J. Storey. “Do entrepreneurs really learn? Or do they just tell us that they do?.” Industrial and Corporate Change22, no. 1 (2013): 73-106.

    Kahneman, Daniel, and Gary Klein. “Conditions for intuitive expertise: a failure to disagree.”American psychologist 64, no. 6 (2009): 515.

    Llewellyn, David J., and Kerry M. Wilson. “The controversial role of personality traits in entrepreneurial psychology.” Education+ Training (2003).

    Macnamara, Brooke N., David Z. Hambrick, and Frederick L. Oswald. “Deliberate practice and performance in music, games, sports, education, and professions: A meta-analysis.” Psychological science 25, no. 8 (2014): 1608-1618.
    McClelland, David C. “N achievement and entrepreneurship: A longitudinal study.” Journal of personality and Social Psychology 1, no. 4 (1965): 389.

    Sarasvathy, Saras D. Effectuation: Elements of entrepreneurial expertise. Edward Elgar Publishing, 2009.

    Sarasvathy, Saras D., and Herbert A. Simon. “Effectuation, near-decomposability, and the creation and growth of entrepreneurial firms.” In First Annual Research Policy Technology Entrepreneurship Conference. 2000.

    Shanteau, James. “Competence in experts: The role of task characteristics.” Organizational behavior and human decision processes 53, no. 2 (1992): 252-266.

  • Daniel Kahneman on expertise with reference to entrepreneurship

    I have already posted about Kahneman and Klein(2009) arguing that “Skilled intuitions will only develop in an environment of sufficient regularity, which provides valid cues to the situation”.

    In the following short video, Daniel Kahneman elaborates some of the conditions that are necessary for genuine expertise to develop.

  • Entrepreneurship and Synergetics

    Synergetics is an interdisciplinary theoretical approach that studies self-organization in complex systems(systems that are characterized by openness, dynamics, and complexity). It was developed by physicist Hermann Haken(1969) through his research experiments on laser light. He noticed unpredictable patterns emerging that cannot be explained by linear models. The properties of light change in a self-organized manner when the laser reaches a critical point or “laser threshold”, and such emergent order sets the control parameter which enslaves the system.

    (This is an updated post)

    For a real explanation, listen directly from the master: Hermann Haken

    Synergetics and Entrepreneurship

    My initial exposure to synergetics from an entrepreneurship related scholarship started with reading Jeffrey Goldstein’s article(attached) in which he stressed his radical construction point of view that paints a negative picture. He argues;

    “Although these connotations of self-organization have provided a corrective to the outdated belief that novel order in a system can only come about through the imposition of external order, a careful inspection of research in complexity theory reveals that the emergence of new order is more appropriately constructed rather than self-organized as such (Goldstein 2003).”

    EMERGENCE, CREATIVITY, AND THE LOGIC OF FOLLOWING AND NEGATING by Goldstein’ 2015

    Goldstein further specifically pointed to Haken; in that he adds;

    “An example is that much touted emblem of self-organization, the laser with its property of ultra-focused coherence (see Haken, 1981). In actuality, though, laser light hardly comes about either spontaneously or through inner direction. On the contrary, it requires the most stringent of laboratory manipulations and constraints (see a list of these in Strogatz, 2003). An examination of other examples of self-organization reveals a similar constructional nature of emergent phenomena (see, e.g., Nicolis, 1989)”

    EMERGENCE, CREATIVITY, AND THE LOGIC OF FOLLOWING AND NEGATING by Goldstein’ 2015

    Andreas Liening of TU Dortmund

    In entrepreneurship, a pioneering effort to apply Synergetics is coming from Prof Andreas Liening and colleagues of TU Dortmund. The top reads are;

    1. Complexity and Entrepreneurship: Modeling the Process of Entrepreneurship Education with the Theory of Synergetics
    2. Synergetics—Fundamental Attributes of the Theory of Self-Organization and Its Meaning for Economics(OPEN Access)

    Although I am extremely interested in reading anything relating to entrepreneurship and complexity, I totally disagree with the “Entrepreneurship Mindset” as the purpose of Entrepreneurship Education promoted by Liening. To see my reasons check this, this, this, this, this and this

    It is very easy to fall into the trap of traditional representational cognitive psychology and its lazy dependence on decontextualized hard or impossible to define concepts like Mindset.

    Some potential issues with application of self-organization and synergetics in education

    It is confusing when you as an outsider looks at education and learning science for the first time to find application ideas. It is very easy to be trapped in a cultish eco-chamber. Even though I agree that It is essential to read people whom we disagree with, a serious issue arises when we start to blindly believe everything they say. This is especially true if one doesn’t have the necessary expertise and diversity in their system to figure out the flaws of the argument. 

    Example; Paul A. Kirschner who is one of the most reductionist of all the education scholars with his famous works like, “Why Minimal Guidance During Instruction Does Not Work”  is also famous for his work on learning in complexity, ” Ten steps to complex learning”.  A new observer might be mistaken to believe that Kirschner is the go to authority in complexity in education. This is a huge mistake. This points to serious issues with the application of synergetics in particular and complexity science in general without any understanding of domain epistemology.

    1. Those with domain expertise may use complexity theory to fit in with their long-accumulated path dependency.
    2. They may use a complexity tag to avoid being called a reductionist.
    3. Those with complexity background may fall for the obvious and visible part of domain knowledge.
    4. Those with ideas and tools to sell may try craft a much less uncertain version of complexity;.
    5. As often pointed out by people like Dave Snowden, those with a complexity background, especially those associated with mathematical modeling and Santa Fe may assume that they can model human complexity by developing agent-based models as they do for some idealized version of Ant behavior. This can be viewed as a reductionistic tendency inside the complexity sciences (http://www.human-current.com/archived-episodes/tag/anthrocomplexity)

    All the above can be viewed as going against the ethics of complexity, especially when proposed as solutions for other people and other people’s children.

    According to Synergetics Philosophers Helena Knyazeva and Sergey Kurdyumov, “The synergetic assertions can apply to many scientific disciplines. They are functioning on the level from which a great scope of scientific disciplines can be embraced. However, such an approach has also a negative side. The higher the level of the view is the less concrete details can be distinguished. On the other hand, the deeper we penetrate particular details the less place seems to remain for synergetics itself” They adds; “Synergetics can provide us only with general frames of consideration, a mental scheme or a heuristic approach to a concrete scientific investigation. Concrete applications of synergetic models to complex human or social systems presuppose further detailed scientific investigations. Such investigations can be carried out only by the use of a profound knowledge of a certain disciplinary field and/or with a close collaboration with specialists in a corresponding scientific discipline. Thus, synergetics gives a certain approach or a direction of research, or, to put it in terms of psychology, a scientific attitude. The rest is the matter of every concrete investigation”

    Some interesting articles by Russian philosopher Helena Knyazeva on synergetics are attached

    Synergetics: New Universalism or Natural Philosophy of the Age of Post-Nonclassical Science?

    ARBITRARINESS IN NATURE: SYNERGETICS AND EVOLUTIONARY LAWS OF PROHIBITION(Co-authored with Haken)

    SYNERGETICS OF HUMAN CREATIVITY; HELENA and HAKEN

    The Synergetic Principles of Nonlinear Thinking

    Synergetics and the Images of Future

    THE COMPLEX NONLINEAR THINKING: EDGAR MORIN’S DEMAND OF A REFORM OF THINKING AND THE CONTRIBUTION OF SYNERGETICS

    Nonlinear synthesis and co‐evolution of complex systems

    NONLINEARITY OF TIME IN THE COMPLEX WORLD

    The Synergetic World View and Its Synthetic Value

    FIGURES OF TIME IN EVOLUTION OF COMPLEX SYSTEMS

    Recent works

    Virtual Reality from the Standpoint of Complexity Science

    Paradigm Shift in the Understanding of the Creative Abilities of Consciousness

    Strategies of Dynamic Complexity Management

    Active Innovative Media as Co-Evolutionary Landscapes

    Cognitive Networks: Interactivity, Intersubjectivity, and Synergy

    Complexity Studies: Interdisciplinarity in Act

    The Idea of Co-evolution; Towards a New Evolutionary Holism

  • Effectual Self-Organization: Could it be a mindful praxis for self-organization

    In the last few posts, I have been developing the idea of effectuation as a self-organization principle against the idea of expertise acquired by entrepreneurs via experience and deliberate practice. Following are two blog posts in which I have elaborated my thoughts.

    1. Why expertise theory of effectuation is flawed?; Here I argue why expertise framing of effectuation is flawed
    2. Self-Organization: Paul Cilliers and Saraswathy: Here I assess effectuation using Paul Cilliers’s attributes of self-organization. Arguing that effectuation simulates the action models of self-organizing systems.

    I have demonstrated that the ideas proposed by effectuation fit perfectly with self-organization principles. Advancing that point, the following are some of the complexity principles associated with effectuation and its core principles(heuristics).

    1. Self-Organization/Effectual dynamics

    I argue that “effectual dynamics” is the dynamics of self-organization. Self-Organization refers to the feature of systems that appear to organize themselves without external direction or control. Self-organization has been used to describe swarms, flocks, traffic, and many other systems where the local interactions lead to a global pattern or behavior (Camazine et al, 2003; Gershenson, 2007). Intuitively, self-organization implies that a system increases its own organization. Self-organization of the effectual entrepreneur is initiated with an examination of the means available to an entrepreneur. The questions “Who am I?”, “What do I know?”, and “Whom do I know?” allow for an examination of the means available to an entrepreneur, which allows him or her to consider what he or she can do (Sarasvathy & Dew, 2005). Through interacting with others and engaging with stakeholders, the entrepreneur discovers new means and establishes new goals that allow for revaluation of means and possible courses of action (Fisher, 2012).

    2. The attractor/ Intention

    Self-organizing systems typically evolve towards a state of equilibrium, or an attractor state. Almost any dynamical system can be seen as self-organizing; if it has an attractor towards which the system dynamics will tend to move, thus increasing by itself its own organization. According to Kauffman(1995), “the trajectory converges onto a state-cycle attractor around which the system will cycle persistently thereafter. A variety of different trajectories may all converge on the same state cycle, like water draining into a lake. The state-cycle attractor is the lake, and the trajectories converging onto it constitute its basin of attraction”. So the question is, Who or what constitutes one of the key initial attractor according to effectuation. Is it the entrepreneur, or intention? Since effectuation has a lot of roots in the work of Herbert Simon, especially “The Sciences of the Artificial” (Simon, 1968), I prefer to take evidence from his work, quoted by Saraswathy herself; “For Simon, human intention and design were central to the social sciences, and the word ‘man-made’ was synonymous with artificial” (Sarasvathy, 2008). From that foundation, it is logical to assume recognition of “intention as the attractor (Juarrero, 2010)”. Intention is also a valid concept in entrepreneurship (Bird, 1989; Shapero and Sokol, 1982; Krueger and Carsrud, 1993). According to Juarrero(2004), “new intention reorganize the earlier state space into a more differentiated and complex set of qualitatively novel options. This means that once an agent formulates a prior intention, every possible behavioral alternative no longer requires consideration; only a partitioned subset does”.

    3. Phase space disposition

    According to Saraswathy, the process elements of effectuation begin with entrepreneurs asking who they are, what they know, and whom they know. This corresponds to the idea of knowing the disposition of phase space or state space of a complex adaptive system. In complexity science, the ‘phase space'(or state space) is the representation of all possible instantaneous states that can occur in a physical system (Butkovskiy 1990, Sayama 2015). It can be thought of as the space within, around, or adjacent to which a complex adaptive system can self-organize and emerge. While we may not be able to know precisely how a system might change, we do know that it will be most likely within the phase space. A change in emergent phenomena within a phase space may be incremental. A radical change suggests a shift in phase space, a qualitative difference in the system (Byrne & Callaghan, 2014). According to Dave Snowden(2017a), in complex adaptive systems, “at a system level, we have no linear material cause but instead we have a dispositional state, a set of possibilities and plausibilities in which a future state cannot be predicted.” This is particularly important because, in a complex system, phase space disposition, is what decides on the evolutionary potential of the system, not any specific fixed goal. If a system is complex(no causality), “you can’t set outcome targets a priori, but you can define a vector target (direction and speed of change from the present against intensity of effort). You can’t manage to a desired future state but have to manage the evolutionary potential of the situated present. You can’t predict the future, but you can increase resilience in there the here and now which will allow you to manage that uncertainty” (Snowden, 2017b). 

    This importance of disposition can also be found in the works of scholars who specialize in entrepreneurship complexity. According to Jeffrey Goldstein, Self-transcending Constructions (Goldstein, 2003), which involves the emergence of radically novel outcomes—-operate on already extant order and creatively transform it along the way into radically novel outcomes.

    Following are some sources of this pre-existing order that are processed by Self-transcending Constructions (Goldstein, 2005);
    1. The already present nascent order in a system, i.e., the way it is functioning right now;
    2. The multifarious constraints currently in place, e.g., the geographical layout, the actual buildings, the already extant work groups, the constraints of money, time, goals, and so forth;
    3. Operations of recombining and manipulating the above;
    4. Supplemental means for introducing novelty such as randomization and negation, i.e., changing the rule.

    I argue that an effectual entrepreneur, by asking questions such as; who they are? what do they know? and whom they know? etc. effectively is trying to make sense of the dispositional propensities, so that they can utilize the evolutionary potential of the present to decide what to do.

    4. Adjacent Possible.

    From the understanding of disposition comes the “The bird-in-hand principle” which refers to a principle of means-driven(as opposed to goal-driven) action. The emphasis here is on creating something new with existing means rather than discovering new ways to achieve given goals. To effectuation, entrepreneurs focus on what they can do and do it, without worrying much about what they ought to do. This idea is similar to acting in the adjacent possible (Kauffman, 1996), i.e. a kind of zone of proximal development (Vygotsky, 1978), towards which change and evolution are more likely because of the current disposition of the system. The concept of “adjacent possible” was introduced by Stuart Kauffman (1996; 2000) in evolutionary biology and complex adaptive systems to explain how biological evolution can be seen as exploration and actualization of what is adjacent possible. It can be defined as “the set of possibilities available to individuals, communities, institutions, organisms, productive processes, etc., at a given point in time during their evolution” (Loreto 2015, p. 9). The concept of the “adjacent possible” is useful for understanding how entrepreneurial adjacent possibilities emerge, and how the new adjacent possible will lead to yet newer adjacent possibilities. In the case of effectual entrepreneurs, they will focus on the adjacent possible than worry about things they don’t possess. They will focus on what they can do and do it.

    Any failure inside the zone of adjacent possible will not likely result in system destruction, but likely help the development of system resilience. The affordable-loss principle to me is a heuristics based on this idea. It prescribes committing in advance to what one is willing to lose rather than investing in calculations about expected returns to the project. If an effectual entrepreneur commits 6 months and 10000k, that commitment itself will shape the constraints of the adjacent possible.

    4. Co-evolution and Co-adaptation

    For a system to self-organize, its elements need to communicate: they need to “understand” what other elements, or mediators, “want” to tell them (Gershenson,2007). Thus, first of all, in a complex system, dynamics of self-organization are initiated and manifested by heterogeneous agents interacting with one another in a non-linear and continuous way. Even if specific agents may only interact with a few others, the impact of these interactions are propagated throughout the system. Accordingly, agents co-evolve with one another (Anderson, 1999). Through this interaction, agents strive to improve their fitness with the environment but the outcome of these attempts depends on the disposition and behaviors of other agents (Mitleton-Kelly, 2003). Thus, co-evolution is one of the key themes when it comes to viewing the system as a whole(the nested and entangled relationships with multiple complex adaptive systems), which refers to the simultaneous evolution of entities and their environments, whether these entities are organisms or organizations (Baum & Singh, 1994). It encompasses the twin notions of inter-dependency and mutual adaptation, with the idea that species or organizations evolve in relation to their environments, while at the same time these environments evolve in relation to them. In effectuation, this is parallel to initiated interaction and the crazy-quilt principle. This principle involves interacting and “negotiating with any and all stakeholders who are willing to make actual commitments to the project, without worrying about opportunity costs, or carrying out elaborate competitive analyses. Furthermore, who comes on board determines the goals of the enterprise. Not vice versa”. This involves the co-evolutionary potential of interacting agents constituted by the principles we have discussed till now but applied to the other side. They are; The Intention(attractor) of other agents, Phase space disposition of interacting agents, Adjacent-possible of interacting agents.

    5, Acknowledging and appropriating Emergent property

    Complex adaptive systems show emergent properties. Emergent properties refer to a characteristic that is found across the system but which individual parts of the system do not themselves hold. E.g. Human heart is made of heart cells. But heart cells on their own don’t have the property of pumping blood. You will need the whole heart to be able to pump blood. Thus, the pumping property of the heart is emergent. A complex system like entrepreneurship has emergent property. That means the emergent or emerging venture idea might be different from the ideas the entrepreneur has initially conceived. Thus initial idea may be to start HTML5 supported location-based service; The emergent outcome could be Instagram. The initial idea may be to develop an app to compare two people’s pictures and rate which one was more attractive; The emergent outcome could be Facebook. The lemonade principle of effectuation is based on adapting, using, and improvising according to emergent realities, whether it is perceived as negative or positive. It suggests acknowledging and appropriating contingency by leveraging surprises rather than trying to avoid them, overcome them, or adapt to them. This means accepting the emergent realities as it comes, adapting, acknowledging, and appropriating the contingencies as it unfolds.

    The pilot-in-the-plane principle urges relying on and working with the human agency as the prime driver of opportunity rather than limiting entrepreneurial efforts to exploiting exogenous factors such as technological trajectories and socioeconomic trends. This is equivalent to elements of Lichtenstein’s(2016) concept of generative emergence that views entrepreneurial emergence as intentional, and agency, even if distributed, as the source of successful organizing. To the framework, intention is the primary attractor around which self-organisation takes place. In order for effective self-organization to take place, the agent must use agency, not to exert control that is driven by his/her own bounded rationality, or the rules of perceived local optima, but a kind of agency that is distributed (Garud and Karnøe, 2005)and embedded as well (Garud and Karnøe, 2003)

    6. Effectual Self-organisation cycle

    A complex system is always dispositional and I have discussed quoting Snowden that we can only know the system by knowing how it is disposed. “you can’t set outcome targets a priori, but you can define a vector target (direction and speed of change from the present against intensity of effort). You can’t manage to a desired future state but have to manage the evolutionary potential of the situated present”. Since the system is always changing, the bird in hand or disposition is also parallelly evolving. This warrants continuous reappraisal of the situated present. The effectual cycle suggests always looping back and cycling through five core principles in a non-linear manner(bird-in-hand, affordable-loss, crazy-quilt, lemonade, pilot-in-the-plane). More specifically there are two types of converging cycles mentioned; expanding means and converging goals. The expanding-means cycle looks for increases in resources, and the Converging goals cycle adapts the goals. “It accretes constraints on the venture that converge into specific goals that get embodied in an effectual artifact over time” (Sarasvathy et al, 2014; Sarasvathy & Dew, 2005, pp. 543–544). This is also a feedback about emergent realities that will lead to estimation of the new phase space disposition, new adjacent possible, new co-evolutionary potential, new action, etc. 

    This is part of Esoloop Framework

    Citations

    Camazine, Scott, Jean-Louis Deneubourg, Nigel R. Franks, James Sneyd, Guy Theraula, and Eric Bonabeau. Self-organization in biological systems. Princeton university press, 2020.

    Gershenson, Carlos. Design and control of self-organizing systems. CopIt Arxives, 2007.

    Fisher, Greg. “Effectuation, causation, and bricolage: A behavioral comparison of
    emerging theories in entrepreneurship research.” Entrepreneurship theory and practice
    36, no. 5 (2012): 1019-1051.

    Simon, Herbert A. The sciences of the artificial. MIT press, 1996.

    Juarrero, Alicia. “Intentions as complex dynamical attractors.” Causing human actions:
    New perspectives on the causal theory of action (2010): 253-276.

    Bird, Barbara, and Mariann Jelinek. “The operation of entrepreneurial intentions.”
    Entrepreneurship theory and practice 13, no. 2 (1989): 21-30.

    Krueger, Norris F., and Alan L. Carsrud. “Entrepreneurial intentions: Applying the theory
    of planned behaviour.” Entrepreneurship & Regional Development 5, no. 4 (1993):
    315-330.

    Juarrero, Alicia. “The self-organization of intentional action.” Revue internationale de
    philosophie 2 (2004): 189-204.

    Butkovskiy, AG 1990, Phase Portraits of Control Dynamical Systems, Springer
    Netherlands

    Sayama, Hiroki. Introduction to the modeling and analysis of complex systems. Open
    SUNY Textbooks, 2015.

    Byrne, David, and Gillian Callaghan. Complexity theory and the social sciences: The
    state of the art. Routledge, 2013.

    Snowden, David. Inclinations-dispositions (https://thecynefin.co/inclinations-dispositions/), Snowden. 2017(a)

    Snowden, David. Systems thinking & complexity (https://thecynefin.co/systems-thinking-complexity/), Snowden. 2017(b)

    Goldstein, Jeffrey. “Emergence, creativity, and the logic of following and negating.” The Innovation Journal: The Public Sector Innovation Journal 10, no. 3 (2005): 1-10.

    Goldstein, Jeffrey. “The construction of emergent order, or, how to resist the temptation of hylozoism.” Nonlinear dynamics, psychology, and life sciences 7, no. 4 (2003): 295-314.

    Kauffman, Stuart A. “Investigations: The nature of autonomous agents and the worlds
    they mutually create.” Santa Fe Institute, 1996.

    Loreto, Vittorio. “Unfolding the dynamics of creativity, novelties and innovation.” White
    paper of the Kreyon project (2015).

    Gershenson, Carlos. Design and control of self-organizing systems. CopIt Arxives, 2007.

    Anderson, Philip. “Perspective: Complexity theory and organization science.”
    Organization science 10, no. 3 (1999): 216-232.

    Mitleton-Kelly, Eve. “Ten principles of complexity and enabling infrastructures.” Complex
    systems and evolutionary perspectives on organisations: The application of complexity
    theory to organisations 1 (2003): 23-50.

    Baum, Joel AC, and Jitendra V. Singh, eds. Evolutionary dynamics of organizations.
    Oxford University Press, 1994.

    Lichtenstein, Benyamin. “Emergence and emergents in entrepreneurship: Complexity
    science insights into new venture creation.” Entrepreneurship Research Journal 6, no. 1
    (2016): 43-52.

    Garud, Raghu, and Peter Karnøe. “Distributed agency and interactive emergence.”
    Innovating strategy process (2005): 88-96.

    Garud, Raghu, and Peter Karnøe. “Bricolage versus breakthrough: distributed and
    embedded agency in technology entrepreneurship.” Research policy 32, no. 2 (2003):
    277-300.

    Sarasvathy, Saras, K. Kumar, Jeffrey G. York, and Suresh Bhagavatula. “An effectual
    approach to international entrepreneurship: Overlaps, challenges, and provocative
    possibilities.” Entrepreneurship Theory and Practice 38, no. 1 (2014): 71-93.

    Sarasvathy, Saras D., and Nicholas Dew. “New market creation through transformation.”
    Journal of evolutionary economics 15, no. 5 (2005): 533-565

  • Self-Organization: Paul Cilliers and Saraswathy

    According to Paul Cilliers(1998), “the capacity for self-organisation is a property of complex systems which enables them to develop or change internal structure spontaneously and adoptively in order to cope with, or manipulate, their environment”. To him, different systems that share the property of self-organisation will not necessarily exhibit the same range of characteristics. A living cell can certainly be classified as self-organizing, but its internal structure will be more stable than that of an economic system of a country. An economic system is self-organizing in the sense that it changes its internal structure in response to a large number of factors (money supply, growth rate, political stability, natural disasters, etc.).

    According to him, despite these important differences between various self-organizing systems with different functions, there are shared attributes that conform to the framework of the general model for complex systems (Paul Cilliers, 1998, p. 91). 

    In the following part, I will attempt to demonstrate the self-organization attributives of Saraswathy’s(2009) effectual entrepreneurship which are parallel to that of the 8 attributes listed by Cilliers. 

    General attributes of self-organizing systems include the following:

    (i) The structure of the system is not the result of an a priori design, nor is it determined directly by external conditions. It is a result of interaction between the system and its environment.

    What about effectuation? 

    Effectuation is not about top-down design, control, or delegation for an external agent. It is not based on pre-decided design or internal planning. Effectuation is the inverse of causation. Causal models begin with an effect to be created. They seek either to select between means to achieve those effects or to create new means to achieve preselected ends.

    (ii) The internal structure of the system can adapt dynamically to changes in the environment, even if these changes are not regular.

    What about effectuation? 

    The crazy-quilt and lemonade principles of effectuation correspond to this aspect. The crazy-quilt principle suggests co-evolving and co-adapting with other agents while negotiating with any and all stakeholders who are willing to make actual commitments to the project, without worrying about opportunity costs, or carrying out elaborate competitive analyses. Here, the important stress of Saraswathy is that “Who comes on board determines the goals of the enterprise. Not vice versa”. Secondly, the lemonade principle suggests acknowledging and appropriating contingency by leveraging surprises rather than trying to avoid them, overcome them, or adapt to them.

    (iii) Self-organisation is not merely the result of processes like feedback or regulation that can be described linearly. It involves higher-order, nonlinear processes that cannot be modelled by sets of linear differential equations.

    What about effectuation? 

    I argue that the entire effectuation logic is based on adapting to the potentialities of the environment by using it. This cannot be modeled by linear equations. More specifically the lemonade principle suggests acknowledging and appropriating contingency by leveraging surprises rather than trying to avoid them, overcome them, or adapt to them.

    (iv) Self-organisation is an emergent property of a system as a whole (or of large enough sub-systems). The system’s individual components only operate on local information and general principles. The macroscopic behaviour emerges from microscopic interactions that by themselves have a very meagre information content (only traces).

    What about effectuation? 

    The logic of effectuation acknowledges emergent property(not by explicitly naming it emergent property, but by implication) and its adaptive nature is part of this acknowledgment. Here also the lemonade principle needs stress because it is really the application of how to deal with surprises generated by such emergent property. Further, even though all of the five core principles( bird-in-hand, affordable-loss, crazy-quilt, lemonade, pilot-in-the-plane)are based on adaptive logic, in real dynamics we must also take into account two concurrent cycles: expanding means and converging goals. The expanding-means cycle looks for increases in resources, and the Converging goals cycle adapts the goals. “It accretes constraints on the venture that converge into specific goals that get embodied in an effectual artifact over time”(Sarasvathy et al, 2014; Sarasvathy & Dew, 2005, pp. 543–544). According to Saraswathy, “The history of new market creation is full of unusual partnerships leading to the emergence of new networks. Instead of arising naturally as a consequence of existing social networks, several of these seminal relationships began through unplanned encounters or serendipitous events”(Saraswathy, 2008, p.118)

    (v) Self-organizing systems increase in complexity…..(trimmed). The increase in complexity may also form part of the explanation why self-organizing systems tend to age. Since these systems are bound by the finite constraints of the physical world, they inevitably become saturated at some point.

    What about effectuation? 

    Effectuation acknowledges this increase in complexity. The effectual process begins in the effectual adjacent zone. It initiates the process from the means available and by doing the things the entrepreneur can do. The means will expand, goals will change, many stakeholders will join in bringing their insights to the table, etc. The effectual cycle is a continuous process that scans for changes in core dispositional realities. Further, there is no explicit mentioning of saturation and destruction in effectuation, but since the human agency is capable of awareness, solutions can be designed to an extend. As the pilot-in-the-plane principle suggest, “we can work with human agency as the prime driver”.

    (vi) Self-organisation is impossible without some form of memory, a point closely related to the previous one. Without memory, the system can do no better than merely mirror the environment. A self-organizing system therefore always has a history…(Trimmed)

    What about effectuation? 

    According to De Wolf and Holvoet(2004), in a self-organizing system,”…‘the arrangement of selected parts’ implies that the arrangement is a kind of historic memory of the process that becomes bigger when more and more parts are arranged”. In effectuation the entrepreneur start by acting in the adjacent possible. Gradually, more and more parts(agents, institutions, artifacts, etc) will be added to form part of the memory of the system. The effectual process involves a continuous cycle of going back to the dispositional factors like means, goals, and direction. This, I argue, is because the memory of a complex system is embedded in its disposition(position & propensity) itself through the ‘the arrangement of selected parts’. It is also distributed across the system. This can also be viewed as a system that augments its behavior with an associative memory of various attractors (Watson, 2011). In entrepreneurship, attractors can be many things like intentions, money, product, customers, stakeholders, vision statement, etc. This is also why Complex systems like entrepreneurship are path-dependent (Liebovitz and Margolis, 1995) and subject to Imprinting (Levinthal, 2003; Johnson, 2007) and lock-ins(Arthur, 1989).

    Further, the importance of a persons history and context was stressed by Saraswathy in a recent presentation where she talked about the case of Elon Musk, and the importance of knowing his past; Watch the clip “Elon Musk himself as an artifact”  Or watch directly from Twitter

    (vii) Since the self-organizing process is not guided or determined by specific goals, it is often difficult to talk about the function of such a system. Self-organisation in complex systems cannot be driven by the attempt to perform a function; it is rather the result of an evolutive process whereby a system will simply not survive if it cannot adapt to more complex circumstances.

    What about effectuation? 

    Effectuation absolutely embraces this philosophy. In effectuation, goals are driven by means and other interacting agents. This points to the coevolutionary potential of the entrepreneur and stakeholders both. According to the bird-in-hand principle, effectuation is means-driven (as opposed to goal-driven) action. The emphasis here is on creating something new with existing means rather than discovering new ways to achieve given goals. Further, Each stakeholder commitment results in new means and new goals for the venture.

    (viii) Similarly, it is not possible to give crudely reductionistic descriptions of self-organising systems. Since microscopic units do not ‘know’ about large-scale effects, while at the same time these effects manifest themselves in collections that do not involve anything besides these microscopic units, the various ‘levels’ of the system cannot be given independent descriptions. The levels are in principle intertwined.

    What about effectuation? 

    Effectuation is in a way a detour from reductionism that existed in entrepreneurship research that focused on a few isolated aspects of personality, attitude, or other personal or situational observables. This is evident from her comparison of effectuation with her doctoral advisor Herbert Simon’s concept of near-decomposable systems(Simon and Ando,1961) where she argues that “both effectuation and near-decomposability exploit locality and contingency in the evolution of the artifact. Just as effectuation creates rapidly evolving artifacts that leverage the interdependence of parts to exploit locality and contingency, so near-decomposability in the structure of such systems leverages the independence of parts to exploit the same locality and contingency. While effectuation stitches together pieces of entrepreneurial fabric into economic quilts that continue to make sense in an interactive and dynamically changing environment, ND identifies lines of ‘tearing’ so that entrepreneurship as a science of the artificial pieces can be reworked in synchrony with the overall pattern as the needs imposed by the environment change”(Saraswathy, 2008,p.165-166).

    Conclusion

    I conclude by proposing the need for a theory of effectual self-organization, suggesting that effectuation is an ideal praxis for every human and social complex system. It not only obeys laws of self-organization but also provides for flexible heuristics that can be intelligently applied according to the co-evolutionary potential around us.  

    It is high time to unshackle effectuation from entrepreneurial expertise and take it to general social science, particularly to domains like education. 

    This content is part of my EsoLoop Framework

    REF:

    Arthur, W. Brian. “Competing technologies, increasing returns, and lock-in by historical events.” The economic journal 99, no. 394 (1989): 116-131.
    Cilliers, Paul. Complexity and postmodernism: Understanding complex systems.

    De Wolf, Tom, and Tom Holvoet. “Emergence versus self-organisation: Different concepts but promising when combined.” In International workshop on engineering self-organising applications, pp. 1-15. Springer, Berlin, Heidelberg, 2004.
    Johnson, Victoria. “What is organizational imprinting? Cultural entrepreneurship in the founding of the Paris Opera.” American Journal of Sociology 113, no. 1 (2007): 97-127.
    Levinthal, Daniel A. “Imprinting and the evolution of firm capabilities.” The SMS Blackwell handbook of organizational capabilities: Emergence, development, and change (2003): 100-103.
    Liebowitz, Stan J., and Stephen E. Margolis. “Path dependence, lock-in, and history.” Journal of Law, Economics, & Organization (1995): 205-226.
    Llewellyn, David J., and Kerry M. Wilson. “The controversial role of personality traits in entrepreneurial psychology.” Education+ Training (2003).
    routledge, 2002.
    Sarasvathy, Saras, K. Kumar, Jeffrey G. York, and Suresh Bhagavatula. “An effectual approach to international entrepreneurship: Overlaps, challenges, and provocative possibilities.” Entrepreneurship Theory and Practice 38, no. 1 (2014): 71-93.
    Sarasvathy, Saras D., and Herbert A. Simon. “Effectuation, near-decomposability, and the creation and growth of entrepreneurial firms.” In First Annual Research Policy Technology Entrepreneurship Conference. 2000
    Sarasvathy, Saras D., and Nicholas Dew. “New market creation through transformation.” Journal of evolutionary economics 15, no. 5 (2005): 533-565.
    Sarasvathy, Saras D. Effectuation: Elements of entrepreneurial expertise. Edward Elgar Publishing, 2009.
    Simon, Herbert A., and Albert Ando. “Aggregation of variables in dynamic systems.” Econometrica: journal of the Econometric Society (1961): 111-138.
    Thornton, Patricia H. “The sociology of entrepreneurship.” Annual review of sociology 25, no. 1 (1999): 19-46.
    Watson, Richard A., Christopher L. Buckley, and Rob Mills. “Optimization in “self‐modeling” complex adaptive systems.” Complexity 16, no. 5 (2011): 17-26.