Abstract:Abstract:JEL Classifications: B41, B53, C63 Keywords: agent-based modeling, methodology It is plain that the Austrian revival that began in the 1970s has yet to succeed in convincing the mainstream of the academy to jettison their physics-based mathematical models in favor of the sort of models and forms of argumentation that contemporary Austrians advocate. Agent-based computational modeling is still in its relative infancy but is beginning to gain recognition among economists disenchanted with the neoclassic… Show more
“…Yang and Chandra (2013) suggested that agent-based models are ideal for investigating competition and strategy present in an evolutionary theory of entrepreneurship. Similarly, McKelvey (2004), Nell (2010), Seagren (2011) and Gangotena (2017) suggested that agent-based computation is essential for the study of order formation, as opposed to the study of equilibrium. The model follows Vriend (2002) in that agents make decision by heuristics and McKelvey’s suggestion that processes be identified where agents can make educated guesses[12].…”
Section: Methodsmentioning
confidence: 99%
“…Agent-based modeling presents an opportunity to integrate creativity into the core of a model of economic activity. Much discussion has focused on this potential without applying the insight or framework to an agent-based model (Nell, 2010; Seagren, 2011; Gangotena, 2017). Newell and Holian (2017) included creativity in an agent-based model in terms of product diversity, but they did not integrate an evolutionary paradigm into their model.…”
Purpose
The purpose of this paper is to integrate a detailed theory of perception and action with a theory of entrepreneurship. It considers how new knowledge is developed by entrepreneurs and how the level of creativity is regulated by a competitive system. It also shows how new knowledge may create value for the innovator as well as for other entrepreneurs in the system.
Design/methodology/approach
The theory builds on existing literature on creativity and entrepreneurship. It considers how transformation of mental technologies occurs at the individual and system levels, and how this transformation influences value creation.
Findings
Under a competitive system, the level of creativity is regulated by the need for new ways of doing things. Periods of crisis wherein old means of coordination begin to fail often precipitate an increase in creativity, whereas a lack of crisis often allows the system to settle to a stable equilibrium with lower levels of creativity.
Research limitations/implications
The combination of methodology and methods facilitates a description of discrete building blocks that guide perception and enable creativity. This framing enables consideration of how a changing set of knowledge interacts with a system of prices.
Practical implications
Policy makers must take care not to encumber markets with costs that unnecessarily constrain creativity, as experimentation makes the economic system robust to shocks.
Social implications
This work provides a framing of cognition that allows for a linking of agent understanding that permits explicit description of coordination between agents. It relates perception and ends of the individual to constraints enforced by the social system.
Originality/value
As far as the author is concerned, no other work ties together a robust framing of cognition with computational simulation of market processes. This research deepens understanding in multiple fields, most prominently for agent-based modeling and entrepreneurship.
“…Yang and Chandra (2013) suggested that agent-based models are ideal for investigating competition and strategy present in an evolutionary theory of entrepreneurship. Similarly, McKelvey (2004), Nell (2010), Seagren (2011) and Gangotena (2017) suggested that agent-based computation is essential for the study of order formation, as opposed to the study of equilibrium. The model follows Vriend (2002) in that agents make decision by heuristics and McKelvey’s suggestion that processes be identified where agents can make educated guesses[12].…”
Section: Methodsmentioning
confidence: 99%
“…Agent-based modeling presents an opportunity to integrate creativity into the core of a model of economic activity. Much discussion has focused on this potential without applying the insight or framework to an agent-based model (Nell, 2010; Seagren, 2011; Gangotena, 2017). Newell and Holian (2017) included creativity in an agent-based model in terms of product diversity, but they did not integrate an evolutionary paradigm into their model.…”
Purpose
The purpose of this paper is to integrate a detailed theory of perception and action with a theory of entrepreneurship. It considers how new knowledge is developed by entrepreneurs and how the level of creativity is regulated by a competitive system. It also shows how new knowledge may create value for the innovator as well as for other entrepreneurs in the system.
Design/methodology/approach
The theory builds on existing literature on creativity and entrepreneurship. It considers how transformation of mental technologies occurs at the individual and system levels, and how this transformation influences value creation.
Findings
Under a competitive system, the level of creativity is regulated by the need for new ways of doing things. Periods of crisis wherein old means of coordination begin to fail often precipitate an increase in creativity, whereas a lack of crisis often allows the system to settle to a stable equilibrium with lower levels of creativity.
Research limitations/implications
The combination of methodology and methods facilitates a description of discrete building blocks that guide perception and enable creativity. This framing enables consideration of how a changing set of knowledge interacts with a system of prices.
Practical implications
Policy makers must take care not to encumber markets with costs that unnecessarily constrain creativity, as experimentation makes the economic system robust to shocks.
Social implications
This work provides a framing of cognition that allows for a linking of agent understanding that permits explicit description of coordination between agents. It relates perception and ends of the individual to constraints enforced by the social system.
Originality/value
As far as the author is concerned, no other work ties together a robust framing of cognition with computational simulation of market processes. This research deepens understanding in multiple fields, most prominently for agent-based modeling and entrepreneurship.
“…While I have argued that the benefits of computational modeling for entrepreneurship, strategy and strategic entrepreneurship research, especially when grounded in Austrian economics, are many, I have also argued that existing computational models have a long way to go in terms of better aligning their models with the Austrian approach (see also Felin et al, ). An encouraging trend is that the usefulness of computational modeling is increasingly being emphasized within the Austrian economics school itself (Gloria‐Palermo, ; Nell, ; Seagren, ).…”
Section: Concluding Remarks and Future Directionsmentioning
Research Summary
This paper makes three key arguments: (a) that computational modeling is a key methodological tool that can aid in the development of formal economic foundations for entrepreneurship that are grounded in Austrian economics; (b) that computational modeling grounded in Austrian economics can serve to integrate models of competitive advantage in equilibrium (economic foundations of strategy) with models of the entrepreneurial function in disequilibrium (economic foundations of entrepreneurship), thereby providing an economic foundation for strategic entrepreneurship; and (c) that the mathematical precision of computational modeling grounded in Austrian economics can serve to clarify the logic behind differing perspectives that have led to debates fueled by the imprecision of natural languages, such as the opportunity debate in the entrepreneurship literature.
Managerial Summary
This paper asks: what are the implications for strategic entrepreneurship if we model it on the foundations of an economic logic developed by the Austrian economics school of thought in a way that integrates into existing economic logics of strategy and competitive advantage? The Austrian economics logic highlights the role of disequilibrium, creative imagination, time and uncertainty, while the traditional economic logic emphasizes the importance of structural sustainable advantages in equilibrium. In this integrative view, even if a firm does not enjoy any competitive advantage over rivals, opportunities for profit or development of competitive advantage still exist through entrepreneurial action. An entrepreneur adopting this view in practice would recognize their own agency, but also the limits to it and the role of external factors.
“…In the absence of such equalities, interaction on the micro level will generate turbulence at the macro level. How much turbulence will accompany the inconsistencies among plans that those inequalities point toward is a topic to be explored, and with some effort to sketch some of this in a framework of agent-based computational modeling set forth in Seagren (2011).…”
Section: Monetary Processes and Central Bankingmentioning
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