Action! Moving beyond the intendedly-rational logics of entrepreneurship

Entrepreneurial action is central to entrepreneurship theory, and is broadly seen to arise as a consequence of intendedly rational logics (whether causal or effectual), reflecting reasoned judgment. But, is this always the case? While entrepreneurial action may often be the result of a judgmental decision (between alternative courses of action/inaction), the presumption that reasoned judgment encompasses all the motives, modes and mechanisms leading to entrepreneurial outcomes seems dubious. Building on an emerging literature that seeks to address the boundaries of reasoned entrepreneurial action, we develop the notion that non-deliberative impulse-driven behavioral logics can also be the basis for business venturing. Our framework offers a complementary perspective to the intendedly-rational, deliberate logics perspective, opening novel pathways for future research and theory-building

Inferring Actions, Intentions, and Causal Relations in a Deep Neural Network

From a young age, we can select actions to achieve desired goals, infer the goals of other agents, and learn causal relations in our environment through social interactions. Crucially, these abilities are productive and generative: we can impute desires to others that we have never held ourselves. These abilities are often captured by only partially overlapping models, each requiring substantial changes to fit combinations of abilities. Here, in an attempt to unify previous models, we present a neural network underpinned by the linearly solvable Markov Decision Process (LMDP) framework which permits a distributed representation of tasks. The network contains two pathways: one captures the desirability of states, and another encodes the passive dynamics of state transitions in the absence of control. Interactions between pathways are bound by a principle of rational action, enabling generative inference of actions, goals, and causal relations supported by gradient updates to parts of the network

Action! Moving beyond the intendedly-rational logics of entrepreneurship

Entrepreneurial action is central to entrepreneurship theory, and is broadly seen to arise as a consequence of intendedly rational logics (whether causal or effectual), reflecting reasoned judgment. But, is this always the case? While entrepreneurial action may often be the result of a judgmental decision (between alternative courses of action/inaction), the presumption that reasoned judgment encompasses all the motives, modes and mechanisms leading to entrepreneurial outcomes seems dubious. Building on an emerging literature that seeks to address the boundaries of reasoned entrepreneurial action, we develop the notion that non-deliberative impulse-driven behavioral logics can also be the basis for business venturing. Our framework offers a complementary perspective to the intendedly-rational, deliberate logics perspective, opening novel pathways for future research and theory-building

Aristotle on Epigenesis

It has become somewhat of a platitude to call Aristotle the first epigenesist insofar as he thought form and structure emerged gradually from an unorganized, amorphous embryo. But modern biology now recognizes two senses of “epigenesis”. The first is this more familiar idea about the gradual emergence of form and structure, which is traditionally opposed to the idea of preformationism. But modern biologists also use “epigenesis” to emphasize the context-dependency of the process itself. Used in this sense development is not simply the unfolding of a pre-determined sequence of changes specified in advance by the organism’s genotype. It is also sensitive to inputs from the internal and external environment, which help determine in real-time which of the many potential developmental pathways are actualized during the process. Within this paradigm developing embryos are viewed as dynamic and responsive systems that react to inputs from the internal and external environment ‘on the fly’. In this paper I argue that, while Aristotle was an epigenesist in the first sense, he would have rejected epigenesis in the more modern sense. First, Aristotle’s model of choice for a developing embryo is the automaton that executes a set of preset movements (GA 734b9-13, 741b7-15). The automatons he has in mind are not dynamic AI systems capable of modifying their behaviour on the fly in response to environmental cues but completely deterministic mechanisms whose movements are fixed by their original design. Second, given Aristotle’s views about the different kinds of causal powers there are, it looks like only intentional agents endowed with actual decision-making powers could be capable of the sort of plasticity at the core of a more dynamic epigenesis. For that kind of epigenesis requires powers for alternative outcomes, and Aristotle is explicit that such powers require rational desires (προαίρεσις) that control which of those alternatives to bring about. If I am right, then he could not have made sense of the idea of a developing embryo (as a non-intentional system) making adjustments to its phenotype on the fly in response to emerging problems and opportunities, given the conceptual resources available to him

Causal Modeling and the Efficacy of Action

This paper brings together Thompson's naive action explanation with interventionist modeling of causal structure to show how they work together to produce causal models that go beyond current modeling capabilities, when applied to specifically selected systems. By deploying well-justified assumptions about rationalization, we can strengthen existing causal modeling techniques' inferential power in cases where we take ourselves to be modeling causal systems that also involve actions. The internal connection between means and end exhibited in naive action explanation has a modal strength like that of distinctively mathematical explanation, rather than that of causal explanation. Because it is stronger than causation, it can be treated as if it were merely causal in a causal model without thereby overextending the justification it can provide for inferences. This chapter introduces and demonstrate the usage of the Rationalization condition in causal modeling, where it is apt for the system(s) being modeled, and to provide the basics for incorporating R variables into systems of variables and R arrows into DAGs. Use of the Rationalization condition supplements causal analysis with action analysis where it is apt

Mechanism-Based Thinking on Policy Diffusion. A Review of Current Approaches in Political Science

Despite theoretical and methodological progress in what is now coined as the third generation of diffusion studies, explicitly dealing with the causal mechanisms underlying diffusion processes and comparatively analyzing them is only of recent date. As a matter of fact, diffusion research has ended up in a diverse and often unconnected array of theoretical assumptions relying both on rational as well as constructivist reasoning – a circumstance calling for more theoretical coherence and consistency. Against this backdrop, this paper reviews and streamlines diffusion literature in political science. Diffusion mechanisms largely cluster around two causal arguments determining the desires and preferences of actors for choosing alternative policies. First, existing diffusion mechanisms accounts can be grouped according to the rationality for policy adoption, this means that government behavior is based on the instrumental considerations of actors or on constructivist arguments like norms and rule-driven actors. Second, diffusion mechanisms can either directly impact on the beliefs of actors or they might influence the structural conditions for decision-making. Following this logic, four basic diffusion mechanisms can be identified in mechanism-based thinking on policy diffusion: emulation, socialization, learning, and externalities.policy diffusion

(WP 2020-01) The Sea Battle Tomorrow: The Identity of Reflexive Economic Agents

This paper develops a conception of reflexive economic agents as an alternative to the standard utility conception, and explains individual identity in terms of how agents adjust to change in a self-organizing way, an idea developed from Herbert Simon. The paper distinguishes closed equilibrium and open process conceptions of the economy, and argues the former fails to explain time in a before-and-after sense in connection with Aristotle’s sea battle problem. A causal model is developed to represent the process conception, and a structure-agency understanding of the adjustment behavior of reflexive economic agents is illustrated using Merton’s self-fulfilling prophecy analysis. Simon’s account of how adjustment behavior has stopping points is then shown to underlie how agents’ identities are disrupted and then self-organized, and the identity analysis this involves is applied to the different identity models of Merton, Ross, Arthur, and Kirman. Finally, the self-organization idea is linked to the recent ‘preference purification’ debate in bounded rationality theory regarding the ‘inner rational agent trapped in an outer psychological shell,’ and it is argued that the behavior of self-organizing agents involves them taking positions toward their own individual identities

The concept of free will as an infinite metatheoretic recursion

It is argued that the concept of free will, like the concept of truth in formal languages, requires a separation between an object level and a meta-level for being consistently defined. The Jamesian two-stage model, which deconstructs free will into the causally open "free" stage with its closure in the "will" stage, is implicitly a move in this direction. However, to avoid the dilemma of determinism, free will additionally requires an infinite regress of causal meta-stages, making free choice a hypertask. We use this model to define free will of the rationalist-compatibilist type. This is shown to provide a natural three-way distinction between quantum indeterminism, freedom and free will, applicable respectively to artificial intelligence (AI), animal agents and human agents. We propose that the causal hierarchy in our model corresponds to a hierarchy of Turing uncomputability. Possible neurobiological and behavioral tests to demonstrate free will experimentally are suggested. Ramifications of the model for physics, evolutionary biology, neuroscience, neuropathological medicine and moral philosophy are briefly outlined.Comment: Accepted in INDECS (close to the accepted version

Between fallacy and feasibility? Dealing with the risk of ecological fallacies in the quantitative study of protest mobilization and conflict

In recent years, the quantitative study of conflict has increasingly focused on small-scale and/or localized conflicts in the developing world. In this paper, we analyze and critically reflect upon a major methodological shortcoming of many studies in this field of research. We argue that by using group- or macro-level empirical data and modelling techniques, while at the same time theoretically underpinning observed empirical associations with individual-level mechanisms, many of these studies risk committing an ecological fallacy. The individual-level mechanism on which many studies rely concerns the presence of grievances which mobilize people to participate in contentious politics. This motivational approach was also present in early studies on protest mobilization in Western societies, which often relied on similar research designs. However, subsequent advances in this literature and the use of methods that were targeted more directly at the individual level uncovered that grievances alone cannot explain mobilization and that organizational capabilities and complex psychological mechanisms of belonging also form part of the puzzle. While drawing on conflict events as well as survey data from Africa, we demonstrate empirically that here, as well, inferring micro-level relations and dynamics from macro-level empirical models can lead to erroneous interpretations and inferences. Hence, we argue that to improve our understanding of conflict mobilization in the developing world, especially for conflicts with low levels of violence, it is necessary to substantially expand our methodological toolbox beyond macro-level analyses