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Category: entrepreneurship

  • 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.

  • Major Entrepreneurship models: Lean startup, effectuation, bricolage, User-entrepreneurship and others

    Following models are suggested methods to use for starting a venture or develop a product/service.

    In this,– Business plan, Lean startup, Design thinking are the most popular among startup community. On the other hand effectuation leads as the most respected model among researchers.

    Further, I would consider(subjectively) Models 1 to 9 as Model Centric or Model driven because the models decide the way the agent must look up to the world.

    On the other hand, I would call Model 10 to 13 as Context driven(effectuation, bricolage, User-entrepreneurship, Copycat), since there are models that fits perfectly with the context or prefers contextual disposition.

    Here we go;

    1. Business Planning (Sahlman, 1997, Delmar and Shane, 2003 )

    A business plan is a written document that describes in detail how a startup defines its objectives and how it is going about achieving its goals. Most of the latest authors like Sahlman were business plan reformists(include next two models).

    1. Contingency planning (Honig, 2004, Marc Gruber 2017)

    Honig suggests that planning processes need to be governed by different planning regimes depending on the type of founding environment ie highly dynamic environments, less dynamic environments, etc. Thus planning must be adative. Gruber suggest that planning processes need to be governed by different planning regimes depending on the type of founding environment.

    1. Discovery-driven planning (McGrath and MacMillan, 1995)

    Discovery-driven planning is an approach that combines business planning with learning through a series of steps that reveal key discoveries (McGrath and MacMillan 2000). The core premise of the method is that when there isn’t enough information to develop a conventional business plan, the thrust of planning must instead be on learning, while at the same time reducing cost and risk. Conventional planning tends to lock an organization in, too early, to a specific operational trajectory.

    1. Probe-and-Learn approach (Lynn et al., 1996).

    Gary Lynn proposed the Probe-and-Learn approach in which companies develop products by probing potential markets with early versions, learning from the probes, and probing again. The initial product will not be the culmination of the development process but rather the first step.

    1. Lean start-up approach (Blank, 2013; Ries, 2011)

    Lean startup is one of the most successful prescritive models in the technology startup ecosystem. This is promoted as a hypothesis-driven approach that focuses on experimenting rather than planning. It proposes engaging with customers through a minimum viable product, which is built iteratively and incrementally according to customer feedback.

    1. Theory Based View(felin et al, 2020)

    The Theory based view stress on the importance of a theory to truly create new value. According to the authors, theory helps entrepreneurs see what others can’t see. Contrarian or unique beliefs provide the underlying raw material of a firm’s theory of value. Added to that theory allows entrepreneurs to be more scientific about value creation and to perform the right type of experiments.

    1. Disciplined Entrepreneurship. Sull (2004)

    Donald Sull notes that instead of ignoring, avoiding or getting affected by uncertainty while trying to fight it, entrepreneurs should manage it by taking a disciplined approach. Bill Aulet (Aulet, 2013) also suggests the deciplinary approch but also offers a step-by-step( 24 steps) approach to creating products.

    1. Design thinking

    Design and design science are broad terms with many different cannotations. In contract, design thinking means– the process approach developed for creating design solutions(products, services, etc.). Standford Design school proposed a process model of design thinking that includes 5 stages/steps ; empathize, define, ideate, prototype, and test. Even though it seems like a linier step by step process it’s proposed as a nonlinear and continues process.

    1. Design Cognition (Garbuio et al., 2017)

    Design cognition is not a prescriptive model. It is just a design science based pedagogical approach proposed for entrepreneurship education. I added it here because of the diversity value. It is developed as a critical counter to other prescriptive models including design thinking. This perspective involves four cognitive acts from the design cognition research to opportunity creation. Following are the four; Framing, Analogical reasoning, Abductive reasoning, and Mental simulation.

    1. Effectual entrepreneurship (Sarasvathy, 2001)

    This is one of the most popular and recognized models among entrepreneurship researchers. Effectuation suggest that entrepreneurs do not start with concrete goals as in the case of business plan, but constantly develop them on the fly through personal strengths and available resources. Effectual thinkers believe that “If I can control the future, I do not need to predict it.”

    1. Entrepreneurial bricolage: Baker, T., & Nelson, R. E. (2005).

    This is not essentially a prescriptive model. It is included because of its prescriptive value. Bricolage is an action-oriented or hands-on approach (Fisher, 2012) that mitigates the limitations of the resource environment by using available resources in ways that were not originally intended and therefore reduces resource uncertainty. According to Baker and Nelson (2005:334) bricolage includes ”making do by applying combinations of resources at hand to new problems and opportunities”.

    1. User Entrepreneurship( and User Innovation) User entrepreneurship: Shah, S. K. (2007)

    This is also not essentially a prescriptive model. It is included because of its prescriptive value. User entrepreneurship is the process by which lead users become entrepreneurs. When users experience a need in their own lives, they develop an innovative solution to address their need, and sometimes even openly share their solution with others before commercializing a product. This phenomenon has been labeled as user entrepreneurship (Shah and Tripsas 2007). This idea is grounded mostly on the early work of Von Hippel (Von Hippel 1988). His work has shown that users are an important and frequent source of innovation and user innovations may be qualitatively different than those of manufacturers.

    13. Copy Cat Model(Check Scholar hits)

    Copycat model, even though least appreciated, is one of the(or the) most successful way civilizations run business and trade. It is also a biologically consistent model. Even Steve Jobs once said a quote from Pablo Picasso. “Good artists copy. Great artists steal. ”essentially, appreciating copying.(not stealing)

    14. Government or Authority Sanctioned, Structure driven

    Traditionally business rights were often sanctioned by authorities. In India there were specialized caste groups who were doing business and nothing else. Even today there are many successful businesses that works under the government patronage.

    For comprehensive review and understanding on entrepreneurship models/methods check following papers:

    If you want to have a peek at few models from popular authors checkout the following video by Stanford’s Chuck Eesly.

    https://youtube.com/watch?v=Rf3xSqgpFHE%3Fversion%3D3%26rel%3D1%26showsearch%3D0%26showinfo%3D1%26iv_load_policy%3D1%26fs%3D1%26hl%3Den%26autohide%3D2%26wmode%3Dtransparent

  • 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

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    Journal of evolutionary economics 15, no. 5 (2005): 533-565

  • Age and High-Growth Entrepreneurship

    In the article titled “Age and High-Growth Entrepreneurship” (written by Pierre Azoulay, Benjamin F. Jones, J. Daniel Kim, and Javier Miranda), the authors examine the relationship between age and entrepreneurial success using data from the U.S. Census Bureau. Contrary to popular belief, the study finds that successful entrepreneurs are typically middle-aged rather than young. The mean age of founders for the fastest growing new ventures, representing the top 1 in 1,000, is 45 years old. These findings hold true across various sectors, including high-technology industries, entrepreneurial hubs, and successful firm exits. Furthermore, prior experience in a specific industry significantly predicts higher rates of entrepreneurial success. These results challenge the common misconception that youth is a determining factor for entrepreneurial success.

    Successful “Young Entrepreneurship” is Mostly a Myth

  • Pragmatic Turn And Entrepreneurship: Part one

    In his book The Pragmatic Turn, Richard Bernstein provides an account of what he calls the “the pragmatic turn” that has been taking place over the past several years as philosophers and practitioners have taken up many of the themes explored by the classic American pragmatists. He argues that they are all converging on pragmatic themes—especially on how social practices shape who we are and how these practices can be improved (pointing and seconding Robert Brandom’s observations). With recent key publications(See google scholar) and the debates triggered by them, the domain of entrepreneurship to me is witnessing a pragmatic turn. We can find scholarly efforts towards the pragmatic turn in many previous works like Sarasvathy(2009), Kraaijenbrink(2012), Rubleske and Berente(2017), Shepherd(2015), Taatila(2010), Watson(2013), etc. Though this is the case, in this blog post, I will only give an overview of the recent(post-2020) advancement of pragmatism in Entrepreneurship. This is because of a Twitter discussion that pushed me into becoming a participator. In the next post(part two), I will discuss my own thoughts, critical points about the current works, and my own visions about the future course of pragmatism applied in entrepreneurship.

    Following are the key articles that I will cover in this review.

    1. Zellweger and Zenger(2021); Entrepreneurs as scientists: A pragmatist approach to producing value out of uncertainty.”
      1. Sergeeva, Bhardwaj, and Dimov(2022); “Mutable reality and unknowable future: Revealing the broader potential of pragmatism.”
      2. Zellweger and Zenger(2022); Entrepreneurs as Scientists: A Pragmatist Alternative to the Creation-Discovery Debate
      3. Ehrig and Foss (2022); Why we need normative theories of entrepreneurial learning that go beyond Bayesianism.
      4. Zellweger and Zenger(2022, 1); Entrepreneurs as Scientists, Bayesian Inference, and Belief Revision
    2. Sergeeva, Bhardwaj, and Dimov(2021). “In the heat of the game: Analogical abduction in a pragmatist account of entrepreneurial reasoning.”  

    Entrepreneurs as scientists: A pragmatist approach to producing value out of uncertainty. (Zellweger and Zenger, 2021)

    Zellweger and Zenger (2021) try to advance an “entrepreneur-as-scientist” perspective viewing entrepreneurs as engaging in, “causally inferential action by forming beliefs, testing these beliefs, and responding to the feedback received”. They argue that entrepreneurs are “practical scientists” who form theories that aid entrepreneurial action under uncertainty. Under the philosophical umbrella of pragmatism, they attempt to bring together the “theory-based view” in entrepreneurship that was discussed in Camuffo et al(2020)and also mentioned in the Value-Lab paper(Felin et, al 2020) with a new addition, i.e. Bayesianism. To them, “Bayesian rationality proves helpful in understanding entrepreneurial reasoning. Consistent with Bayesian logic, entrepreneurial action rests on beliefs or priors that are updated as entrepreneurs incorporate information they gather.”

    Sergeeva et al(2022)’s critical response points out that many important aspects of pragmatist thought that is relevant to entrepreneurship research remain obscure in Zellweger and Zenger (2021) due to their focus on learning anchored on a determinate future. They structured their response along three themes: 

    • limitations of the “scientists” analogy, 
    • the ontological difference between the present and future, and its implications for epistemic barriers and 
    • the creative agency of the entrepreneur.

    Sergeeva et al(2022) basically call Zellweger and Zenger (2021) an opportunity-discovery theory that presupposes an unchanging universe. They reason that entrepreneurs are not just scientists, they are engineers, artists, and designers:  “To say that entrepreneurs are scientists is to say they get things right. To say they are engineers is to say they make things work. To say they are artists is to say they make things new. And to say they are designers is to say they make things practical. It is intuitive that, faced with an open future, they are all of these”. They argue that the future is not just unknown but unknowable. Citing emergence as a key feature of complex domains like entrepreneurship, they make a point that there are no future facts, “like the horizon, the future can never be reached.” With this, they expose the “scientist” perspective’s major weakness. i.e. no amount of information gathering at the level of the constituent elements in the present can foretell the “emergent” level as it remains beyond the horizon. For example, it is impossible to predict the new market category that will emerge from the complex web of interactions of entrepreneurs, consumers, media, etc. The market is more than an information discovery process: “future parts of a market simply do not exist; they are by definition not present”.

    Zellweger and Zenger(2022) respond to Sergeeva et al(2022) with a wholehearted agreement that, “entrepreneurs act to create value as they solve problems”. But in this response, they double down on the original argument that, by doing so, “all humans, including entrepreneurs, engineers, and artists act as scientists”. They further reject Sergeeva et al(2022)’s placement of their perspective in the discovery camp. They add that the entrepreneur-as-scientist perspective and pragmatism more generally find little use for the made vs. found distinction. I.e. “any difference between “real scientists” and any other category of individual lies solely “in the problems with which they are directly concerned, not in their respective logics” (Dewey, 1938, p. 81). Zellweger and Zenger(2022) further argue that entrepreneurs as scientists don’t mean “they get things right”, as interpreted by Sergeeva, et al (2022), but rather that they behave as scientists—that they follow a scientific process and that in doing so they increase their odds of finding value; “They increase the odds of solving the problems they confront and frame. They increase the odds of composing a productive belief, updating with data and feedback, and ultimately producing value.”.

    Ehrig and Foss (2022) primarily focused on Bayesianism which was proposed in Zellweger and Zenger(2021). They point to two major problems in Zellweger and Zenger(2021), that their model; 1) seeks to reduce uncertainty to risk and ignores the problem of unknown unknowns, and, 2) does not identify the key inferential problem of linking the few current data points known by an entrepreneur to her imagination as it pertains to an unknowable future.

    According to Ehrig and Foss (2022), applying Bayesian rationality in a domain of Knightian uncertainty must fail, because core theoretical assumptions are not met. Thus Zellweger and Zenger (2021) is fraught with internal inconsistencies and not viable. “Modelling entrepreneurial learning processes using Bayes rule is a highly limited approach, and not the umbrella approach”. They further clarify that, “Bayesian learning fails when entrepreneurs encounter unknown unknowns which is typical to entrepreneurs. These are events with prior probability of zero because they were not included in the decision-maker’s ex ante representation”. They point out that in the case of ill-defined problems like that in entrepreneurship, learning cannot be understood as “getting closer” to an existing reality, which is exactly the logic behind bayesian approach. i.e. to rule out states by conditioning on observed evidence. It inherently cannot cope with the inclusion of new possibilities which is the key feature of entrepreneurship. Bayesianism fails once the decision-maker encounters an event that was not pre-modeled. They further point out the positive side of Bayesianism that it may be the correct normative tool to test the subset of assumptions in an entrepreneurial theory that are already testable, given the resources of the focal firm.

    In the response, Zellweger and Zenger(2022, 1) agrees with the suggestion given by Ehrig and Foss (2022) but partially. They agree that “normative theory in which entrepreneurs are encouraged to act like scientists needs a model of learning that goes beyond Bayesianism or at least an augmented or qualified version of Bayesianism—one that allows unsupported beliefs or priors to be discarded and replaced”. Zellweger and Zenger(2022, 1) argue that this form of augmented bayesianism is what defines a pragmatist entrepreneur, an entrepreneur who acts like a scientist. They recognize that the entrepreneurial process is often filled with surprises or the arrival of information that lays outside the entrepreneur’s priors, which challenges Bayesian inference and its formal closure. Thus, “scientific entrepreneurship requires a version of or an addition to Bayesianism in which unsupported priors can be revised, discarded and replaced”. Zellweger and Zenger(2022, 1) further dilute the earlier rigid version with a much more pluralistic version. They “recognize wide variance in the degree to which entrepreneurs adopt and skillfully deploy the steps inherent to this pragmatic, scientific and at times Bayesian learning process. We thus refrain from suggesting that the scientific method is the only way to create value in entrepreneurship”. Another key insight revealed in this exchange was their aspirations to develop this theory to suit formal economic modeling. For them, “Bayesianism and theories of belief revision promise to render the entrepreneurial process more accessible to formal economic modeling, which should help augment the micro-foundations of entrepreneurial action”. They conclude by reiterating that “our scientific perspective of entrepreneurship is pragmatism”, but add a few new(but old) ideas that were traditionally considered part of Peircean pragmatism which “entails that entrepreneurship starts with abduction, suggesting that an idea may be, followed by deduction, suggesting what then must be, followed by induction, finding out whether the idea is actually operative. Adds further that, “getting to something actually operative may demand multiple cycles through this process as beliefs are revised.”

    In the heat of the game: Analogical abduction in a pragmatist account of entrepreneurial reasoning(Sergeeva, Bhardwaj, and Dimov; 2021)

    In this paper, Sergeeva et al(2021) introduce their key frame of pragmatism, i.e. “Navigating the entrepreneurial journey entails looking ahead to decide what to do next as well as looking back to take stock and learn”. They introduce a model of reasoning that balances these two stances, i.e. of player and analyst. Both as distinct ways for an entrepreneur to relate to the world: “one acting upon it to make her intentions work; the other taking it in to evaluate her premises”. With this in mind they use John Searle’s theory of speech acts and intentionality to distinguish;

    1. “opportunities” as utterances signifying an agentic stance towards the world, reflecting what entrepreneurs aim to make work and;
    2. opportunities as external conditions of satisfaction, or the way the future world will need to be for them to succeed.

    Under the player stance, one aims for the world to fit the mind (world-to-mind fit). Under the analyst stance, one aims for the mind to fit the world (mind-to-world fit). They reason that, “with current scholarship primarily focused on the analyst stance, we aim to advance the player stance and elaborate on how entrepreneurs reason about what to do next”. For the development of the player perspective, American pragmatism was introduced as a philosophical foundation. To advance the player stance they say they draw from three features of American pragmatism.

    “First, the pragmatist conception of truth is unique in that it evaluates the merits of beliefs in terms of the actions they enable and the consequences they bring. This allows us to conceptualize “opportunity” as something that, from the player perspective, one intends to make work.

    Second, this school of thought recognizes that in a complex world characterized by emergence and unknowability, beliefs are fallible, which, in turn, requires revising them in light of new experiences.

    Third, American pragmatists consider as empirical, and place at the center of their analysis, unobservable entities such as values, desires, and intentions. Adopting a pragmatist perspective of entrepreneurial reasoning and action opens up new exciting avenues in entrepreneurship research“.

    Analogical abduction

    They then introduce Peirce’s conceptualization of abduction and propose analogical abduction as one of the mechanisms for reasoning about and articulating “opportunities”. Analogical abduction involves drawing on the existing stock of knowledge and framing unfamiliar situations as if they were similar to familiar situations. It is introduced here as an engine that drives entrepreneurial reasoning and action and develops a corresponding process model as a dynamic guide for action. They reason that the role of analogies and imagination has already been examined in entrepreneurship research. The idea of analogical abduction here complements these studies by shedding light on the generative mechanism behind analogical or imaginative leaps conducted by entrepreneurs conjecturing about “opportunities”. They conclude by stressing analogical abduction as a – but not the only – mechanism through which entrepreneurs arrive at their conjectures about “opportunities”. 

    Meta-Cognitive rigidity

    The next key idea discussed in the work is the need to overcome, “metacognitive rigidity that impedes toggling between the player and analyst stances” or “toggling between the mind-to-world and world-to-mind direction”. They posit that metacognitive rigidity impedes learning because it precludes any attempts at even trying to update mental schemas. They further suggest that “Overcoming metacognitive rigidity enables entrepreneurs to interpret feedback from the world and act upon it with a renewed creative force”.

    Conclusion

    In this short review, I have touched on the recently(post-2020) published works that discussed pragmatism as a philosophical foundation for entrepreneurship theory. My agenda was to critically review this new development by sharing my own critical points and suggestions. Because of the content depth, I decided to divide the blog post into two. This part covered the recent literature. In part two, I will discuss my own thoughts, critical points about the current works, and my own visions about the future course of pragmatism applied in entrepreneurship.

    Citations

    Kraaijenbrink, Jeroen. “The nature of the entrepreneurial process: causation, effectuation, and pragmatism.” In New Technology-Based Firms in the New Millennium. Emerald Group Publishing Limited, 2012.

    McVea, John F., and Nicholas Dew. “Unshackling Imagination: How Philosophical Pragmatism can Liberate Entrepreneurial Decision-Making.” Journal of Business Ethics (2021): 1-16.

    Rubleske, Joseph, and Nicholas Berente. “A pragmatist perspective on entrepreneurial opportunities.” International Journal of Innovation Science (2017).

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

    Shepherd, Dean. “Party On! A call for entrepreneurship research that is more interactive, activity based, cognitively hot, compassionate, and prosocial.” Journal of Business Venturing 30, no. 4 (2015): 489-507.

    Taatila, Vesa. “Pragmatism as a philosophy of education for entrepreneurship.” In Innovation and entrepreneurship in universities. The Proceedings of the 3rd International Finnish Network of Entrepreneurship and Innovation for Higher Education (FININ) 2010 Conference, Joensuu, Finland, pp. 52-63. 2010.

    Watson, Tony J. “Entrepreneurial action and the Euro-American social science tradition: pragmatism, realism and looking beyond ‘the entrepreneur’.” Entrepreneurship & Regional Development 25, no. 1-2 (2013): 16-33.

  • Entrepreneurship is ecological. Outside the direct scope of academic credentialism.

    If it was for the academicians to decide entrepreneurial outcomes, they would have done it already with Psychometric MCQ tests. Luckily, that is not the case and will never be the case. But unfortunately there are many enthusiastic chaps.(not meant for Prof Mollick if you ever see this).

    As I have discussed elsewhere, GRE’isation of entrepreneurship is an unrealized dream for the academic community who lived through many GRE’s and GMAT’s thinking that MCQ tests is equal to generalized intelligence. They will never give-up so easily and this study shared by Prof Mollick is a good example; “What matters more for entrepreneurship success? A meta‐analysis comparing general mental ability and emotional intelligence in entrepreneurial settings”

    If it was for psychometric tests Richard Branson as a dyslexic wouldn’t have made it to become a billionaire entrepreneur;

    Richard Branson writes

    “When I was in my fifties, I was sat in a board meeting being taken through some financial figures when the subject of net and gross came up. I must admit I was quite confused – I didn’t know if the results were good or bad news.”…”As a dyslexic, I thought I’d been hiding my muddling of words and numbers well for years. But I’d been rumbled. I couldn’t tell the difference between net and gross.”

    Branson Blog

    Accumulated advantage matters :

    On the other hand accumulated advantage matters. Those with accumulated advantage might provide their kids with all kinds of resources to get admission to elite universities. This can give a false sense that because of higher education they become successful. This is wrong because they already are filthy rich and that’s why they got-in in the first place.

    I am ending this point with a Nassim Thaleb BS expose or Exposayyy. He writes(blogpost)

    “When the results come from dealing directly with reality rather than through the agency of commentators, image matters less, even if it correlates to skills. But image matters quite a bit when there is hierarchy and standardized “job evaluation”. Consider the chief executive officers of corporations: they not just look the part, but they even look the same. And, worse, when you listen to them talk, they will sound the same, down to the same vocabulary and metaphors. But that’s their jobs: as I keep reminding the reader, counter to the common belief, executives are different from entrepreneurs and are supposed to look like actors.”

  • Entrepreneurs as Scientists and Scientific Approach to Strategic Decision (Video playlist)

    Prof Alfonso Gambardella of Bocconi University and co-authors discuss Scientific Approach to entrepreneurship and Strategic Decision making in the following videos