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Economic Opportunity and Evolution: Beyond
Landscapes and Bounded Rationality
Teppo Felin, Stuart Kauman, Roger Koppl, Giuseppe Longo
To cite this version:
Teppo Felin, Stuart Kauman, Roger Koppl, Giuseppe Longo. Economic Opportunity and Evolution:
Beyond Landscapes and Bounded Rationality. Strategic Entrepreneurship Journal, Wiley, 2014, 8,
pp.269 - 282. �10.1002/sej.1184�. �hal-01415115�
ECONOMIC OPPORTUNITY AND EVOLUTION: BEYOND LANDSCAPES
AND BOUNDED RATIONALITY
*
TEPPO FELIN
University of Oxford
Said Business School
OX1 1HP, Oxford
United Kingdom
teppo.felin@gmail.edu
STUART KAUFFMAN
Complex Systems Center,
University of Vermont,
Burlington, Vermont, USA
stukauffman@gmail.com
ROGER KOPPL
Whitman School of Management
Syracuse University
Syracuse, NY, USA
rogerkoppl@gmail.com
GIUSEPPE LONGO
CNRS - Ecole Normale Superieure,
Paris, France
giuseeppe.longo@ens.fr
http://www.di.ens.fr/users/longo/
*
In Strat. Entrepreneurship Journal, 8, issue 4: 269–282 (2014).
ECONOMIC OPPORTUNITY AND EVOLUTION: BEYOND
LANDSCAPES AND BOUNDED RATIONALITY
ABSTRACT
The nature of economic opportunity has recently received significant attention in
entrepreneurship and strategy. The notion of search on an (NK) opportunity
landscape has been particularly relevant to these conversations and debates. We
argue that existing notions of landscapes are overly focused on bounded
rationality and search (often instantiated as the problem of NP-completeness),
rather than focusing on how to account for the readily manifest, emergent
novelty we see in the economic sphere (the “frame problem”). We discuss the
entrepreneurial and economic implications of these arguments by building on
unique insights from biology, the natural and computational sciences.
Key words: entrepreneurship, economic opportunity, novelty, strategy
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1. Introduction
The origins of novelty and nature of economic opportunity have recently received significant
attention in entrepreneurship, strategy and organization science. The notion of boundedly rational
search (Simon, 1955, 1956)—on a strategy landscape or “phase space”—represents a particularly
powerful and influential metaphor and tool for thinking about the nature of economic activity.
2
For
example, NK modeling has been used to study how firms search locally or globally for peaks or
opportunities within landscapes (Levinthal, 1997; Winter et al., 2007). Some have argued that
behavior and “rationality” on this landscape is a process (Levinthal, 2011; also see March, 1994;
Simon, 1978), thus emphasizing mechanisms such as experiential learning and environmental
feedback—while yet others have recently focused on how novelty and opportunity might emerge via
distant, cognitive leaps on a landscape (e.g., Gavetti, 2011; cf. Holyoak and Thagard, 1996). The
discussion has centered on how economic actors navigate and map these opportunity landscapes,
given uncertainty and such factors as the resources of the economic actors, the cognition or biases of
the decision-makers, the dynamism of the environment, or competition and past experience. It is
important to note—given the arguments in this paper—that the origins of the landscape metaphor,
and associated tools such as NK modeling, can be traced back to computational and evolutionary
biology (see Kauffman and Levin, 1987; Kauffman and Weinberger, 1989).
3
Furthermore, it is also
quite significant that Herbert Simon’s (1955, 1956) path-breaking arguments about bounded
rationality were explicitly tied to biological intuition and mechanisms about organisms searching and
optimizing behavior in environments.
4
The metaphor and very nature of an opportunity landscape have recently been challenged and
2
As we will later discuss, phase spaces and various combinatorial landscapes have been central in a number of
disciplines, including physics, biology and chemistry (see Reidys and Stadler, 2002). To learn of the history and
basic mathematics behind phase spaces, see Nolte, 2010.
3
Links between biology and economics of course are deep, going back to Darwin and Malthus (Mayr, 1977). For a
history of the extensive links between biology and economics, see Hodgson, 2005.
4
Importantly, these arguments also provide the foundations for the field of artificial intelligence (Newell, Shaw and
Simon, 1958; Newell and Simon, 1959; for an overview, see Russell and Norvig, 2009).
3
debated, particularly in the context of explaining novelty in economic settings. For example, Winter
has raised questions about the notion of an opportunity landscape—specifically vis-à-vis Gavetti’s
(2011) arguments—and provocatively asks “why [we should even] theorize opportunity?” (2012:
291). Winter raises concerns about such issues as the stationary and objective nature of opportunity
landscapes and extant mischaracterizations of rationality. We share some of these concerns. Scholars
have also asked questions about how we specify the phase space of strategies and novel activities that
are not actualized, but nonetheless possible (e.g., Bryce and Winter, 2009). Winter (2011) further
argues that “serendipity” and “contextual factors” play an important role in the emergence of novelty
and in the discovery of profitable opportunities (cf. Denrell et al., 2007; also see Winter, 2012).
Importantly, scholars in entrepreneurship have also raised concerns that relate to the landscape
metaphor, specifically in recent debates about the subjective versus objective nature of economic
opportunities—whether opportunities are “created” and enacted versus “discovered” (e.g., Alvarez
and Barney, 2007; Alvarez, Barney and Anderson, 2012; Eckhardt and Shane, 2012).
The above debates raise important questions about the origins of novelty and nature of
economic opportunity. Given that scholars have extensively used phase spaces or landscapes both as
a metaphor and tool (such as NK modeling), we explicitly revisit the underlying assumptions
embedded in these approaches and more generally revisit the idea of bounded rationality and
organism-environment relations, particularly as these apply to entrepreneurship and novel economic
activity. We first discuss Herbert Simon’s foundational notion of bounded rationality, which partly
has led the field astray, and his ideas about search and computational complexity in uncertain
environments. We focus on the rationality-related and biological and computational assumptions
made by extant theories that focus on search, novelty and economic activity. In short, much of the
strategy and organizational literature is built on computation and algorithm-oriented conceptions of
activity and behavior, and we argue that these approaches suffer from some critical deficiencies. We
4