Content uploaded by Martin Kornberger
Author content
All content in this area was uploaded by Martin Kornberger on Oct 07, 2017
Content may be subject to copyright.
Strategic Organization
1 –20
© The Author(s) 2016
Reprints and permissions:
sagepub.co.uk/journalsPermissions.nav
DOI: 10.1177/1476127016648499
soq.sagepub.com
The visible hand and the crowd:
Analyzing organization design in
distributed innovation systems
Martin Kornberger
Copenhagen Business School / EM Lyon WU Wien and University of Edinburgh
Abstract
The effectiveness and creativity of Linux, Wikipedia, and a plethora of other distributed innovation systems
have attracted the attention of scholars, practitioners, and policy makers. The hallmark of these distributed
innovation systems is that value creation transcends the boundaries of hierarchically organized firms. To
date, only relatively few studies have focused on the organization design of distributed innovation systems.
This conceptual article addresses this lacuna by asking, how does organization design structure relationships
in distributed innovation systems, including interactions between the “visible hand” of the manager and the
“crowd” of distributed innovation? The purpose of this article is to shift the unit of analysis of organization
design from the individual firm to networks of actors providing a framework to study how design organizes
distributed innovation systems. In order to do so, three design mechanisms (interface design, the design
of participatory architectures, and the design of evaluative infrastructures) are proposed through which
firms and other network actors organize their encounter in “the open” and through which they manage
communication, coordination of tasks, and control in distributed innovation systems.
Keywords
crowds, distributed innovation, organization design, organization theory, search, strategy
The imperatives of technology and organization, not the images of ideology, are what determine the
shape of economic society
John Kenneth Galbraith, The New Industrial State (1967)
Introduction: the visible hand and the crowd
Distributed innovation systems have emerged as powerful and creative sources of new ideas, ser-
vices, and technologies. For instance, thousands of amateur contributors make Wikipedia the most
comprehensive encyclopedia in the world. The open source codebase Linux provides sophisticated
Corresponding author:
Martin Kornberger, Department of Organization, Copenhagen Business School, Kilevej 14A, DK-2000 Frederiksberg,
Denmark.
Email: mko.ioa@cbs.dk; from 2017 onwards he can be reached at EM Lyon.
648499SOQ0010.1177/1476127016648499Strategic OrganizationKornberger
research-article2016
Special Issue: Organizing Crowds and Innovation
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
2 Strategic Organization
software, used even for what the US government terms mission critical tasks. Since the start of
Apple’s open App Store, approximately 1.5 million applications have been developed by close to
400,000 publishers and downloaded 75 billion times. In the first week of 2015 alone, customers
spent nearly half a billion dollars on apps and in-app purchases.1 These examples illustrate how
distributed actors in innovation networks act effectively as producers and bricoleurs, creative users
and (occasionally) abusers of new products, services, and experiences. Taking these shifting loci of
innovation from firms to networks (Powell et al., 1996) as its point of departure, this article focuses
on one hitherto neglected question: How does organization design, defined as the structuring of
communication, coordination, and control (Simon, 1969, 1962), enable as well as constrain the
activities within distributed innovation networks?
Save for a few exceptions (Altman et al., 2015; Baldwin, 2012; Fjeldstad et al., 2012; Gulati
et al., 2012; Lakhani et al., 2013), extant research does not focus sufficiently on organization
design and its role in structuring relationships within distributed innovation systems, including
those among hierarchical firms, individual entrepreneurs, collectives, and other actors. As Baldwin
(2012) observed in the context of distributed innovation, “the so-called ‘modern corporation’ has
long been the central focus of the field of organization design. […] But individual organizations are
no longer adequate to serve as the primary unit of analysis” (p. 1). Therein lies the challenge this
article addresses: How to extend theory of organization design beyond firm boundaries and expli-
cate how organization design mechanisms structure systems of distributed innovation?
This article provides an answer to this question by proposing a novel conceptualization of organi-
zation design that explores how communication, coordination, and control are achieved in distrib-
uted innovation systems. Complementing theories of design for hierarchies and markets (Williamson,
1985, 1991), this article makes a specific contribution to organization theory through mapping a
framework for organization design in distributed innovation systems. In order to do so, this article
proposes three concrete design principles that resolve challenges of communication, coordination,
and control in distributed innovation systems. First, interface design is concerned with the organiza-
tion of the interaction within distributed innovation systems (mediating function); second, the design
of participatory architectures enables users to articulate their ideas and contribute meaningfully to
distributed innovation (enabling function); and, third, evaluative infrastructures function as account-
ing mechanisms to judge the quality and value of production in distributed innovation systems
(valuation function). In so doing, this article provides one step toward answering Boudreau and
Lakhani’s (2013) call that we need to “put as much energy and intelligence into designing systems
for organizing work outside company walls as we do for work within them” (p. 69).
The proposed theoretization of organization design advances our understanding of organizing
crowds and innovation in several ways. First, it offers a better understanding of the design mecha-
nisms that structure distributed innovation processes. Akin to Ford’s assembly line that represented
an organizational innovation for manufacturing physical goods (Weber, 2004), the proposed design
principles represent an invisible infrastructure that organizes economic activity in distributed inno-
vation systems. Second, this article contributes to the development of a design-based theory of
search in distributed innovation systems (Simon, 1969). Third, it adds to the resource-based litera-
ture by explicating how organization design functions as an access mechanism to knowledge, crea-
tivity, human ingenuity, and other resources that reside outside firm boundaries.
The article is structured as follows. First, it analyzes research on distributed innovation and situ-
ates its argument within this ongoing conversation. Next, it discusses the conceptualization of
organization design along three main trajectories (interface design, design of architectures of par-
ticipation, and design of evaluative infrastructures). This section draws on and enhances the inter-
disciplinary discourse of organization theory by grounding the three functions of organization
design analytically in software and media studies (concern with interfaces), the distributed
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
Kornberger 3
innovation literature (concern with architectures), and economic sociology and accounting studies
(concern with valuation). Then, the article discusses the implications for organization theory, search,
and the resource-based view. Finally, it reflects on future empirical research opportunities and con-
cludes with a reflection on management practice and the political economy of distributed
innovation.
Theoretical context: distributed innovation and the question of
organization design
Next, this article will review extant research on distributed innovation in order to locate the arti-
cle’s theoretical context, clarify the domain of applicability of the proposed framework, and indi-
cate where and how it departs from previous studies.
Defining distributed innovation systems
Several different conceptualizations of the phenomenon of distributed innovation compete for the
scholar’s attention, including user-driven innovation (Von Hippel, 2005), commons-based peer
production (Benkler, 2002), platform innovation (Gawer and Cusumano, 2002, 2008), co-creation
(Prahalad and Ramaswamy, 2004), crowdsourcing (Afuah and Tucci, 2012, 2013; Bloodgood,
2013), and other forms of collaboration with outsiders (see Table 1).
These approaches share the assumption that the “locus of innovation” shifts from hierarchically
structured firms to networks of distributed actors (Powell, 1990; Powell et al., 1996), theorizing
innovation as a distributed process to which users, rivals, and other non-firm members contribute
(Baldwin and Von Hippel, 2011; Bogers and West, 2012; Lakhani and Panetta, 2007; Von Hippel,
1988). These approaches define distributed innovation as “decentralized problem-solving, self-
selected participation, self-organizing coordination and collaboration, ‘free’ revealing of knowl-
edge, and hybrid organizational models that blend community with commercial success” (Lakhani
and Panetta, 2007: 98). The constitutive elements include crowdsourcing, contests, and tourna-
ments as forms of distributed innovation (see Boudreau and Lakhani, 2009, 2013; Pisano and
Verganti, 2008), which together define the domain of applicability for the organization design
framework of distributed innovation developed in this article.2
Importantly, the role of information and communication technology in distributed innovation
systems has to be acknowledged (see Altman et al., 2015; Lakhani et al., 2013; Zammuto et al.,
2007). Knowledge and informational goods can be digitized and travel through the Internet via a
rapidly spreading infrastructure of socio-cognitive processing devices, including PCs, laptops,
smartphones, tablets, and so on (Lakhani et al., 2013). The shared information is transmitted,
stored, and manipulated at ever-declining costs and at ever-increasing speeds. Past technology
advances such as filing systems, phones, and fax machines have contributed to an increase in the
internal efficiency of organizations (Yates, 1989). This has led to a decrease in management costs.
The Internet, on the other hand, is a technology that networks society and, hence, reduces com-
munication, information, and search costs (Altman et al., 2015; Langlois, 2003; Langlois and
Garzarelli, 2008). Questions concerning how to find the right supplier to deliver crucial input just
in time become, thanks to technology, easier to answer. Firms such as Procter & Gamble search
globally for talent to help solve the challenges it faces or to identify new opportunities; similarly,
InnoCentive is an open platform for crowdsourcing solutions for problems experienced in the
pharmaceutical industry (Huston and Sakkab, 2006; see also Boudreau and Lakhani, 2013; Pisano
and Verganti, 2008). These examples demonstrate that technology not only helps to reduce related
communication, information, and search costs but also provides a superior mechanism to access
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
4 Strategic Organization
talent and identify resources. Hence, technology provides the informational infrastructure for dis-
tributed innovation to occur.
Having said that, it is important to note that technology does not determine action within net-
works (Brynjolfsson, 1993). Rather, technologies afford (Gibson, 1977) “action possibilities”
which are latent in their design without determining them (Callon, 1987; Orlikowski, 1992).
Following this view, technology constitutes a space of possibilities; it is the task of organization
design to transform these possibilities into actualities by structuring communication, coordination,
and control in distributed innovation systems. What then do we know about organization design of
distributed innovation systems?
The research question: design of distributed innovation systems
Important works on motivation (Lerner and Triole, 2002; von Krogh et al., 2012), leadership and
governance mechanisms (Fleming and Waguespack, 2007; O’Mahony and Ferraro, 2007), forms
of institutional work as logics and professional identities shift from firm-based to open models
(Gawer and Phillips, 2013; Lifshitz-Assaf, 2015), boundary processes (Lakhani et al., 2013;
Ferraro and O’Mahony, 2012; West and O’Mahony, 2008), relative openness and closure
(Boudreau, 2012; West, 2003), and communities, socialization processes, and power (Ducheneaut,
2005; Jarvenpaa et al., 2013; O’Mahony and Lakhani, 2011) have significantly deepened our
understanding of the possibilities of managing distributed innovation strategically. These
Table 1. Mapping extant research on distributed innovation.
Theory and domain Key idea Analytical focus Exemplary theorists
Lead user innovation
Domain: innovation
Information asymmetry and
differences in information
quality between lead users
and innovation managers
enable the former to
outperform the latter
Economics and dynamics
of lead user innovation in
contrast to traditional R&D
management
Von Hippel (1976,
1986, 2005)
Value co-creation
Domain: strategy and
marketing
Value creation as distributed
process that takes place
in ecosystem in which
consumers, suppliers,
business partners, and others
co-produce value
Analyzing value creation
ecosystems and how
consumers are enrolled in
distributed innovation
Normann and
Ramirez (1993),
Prahalad and
Ramaswamy
(2004), and Vargo
and Lusch (2004)
Platform innovation
Domain: innovation
and strategy
Platforms as products,
services, or technologies that
function as foundations for
complementors to innovate
Focus on dynamic
interplay of collaboration,
competition, and strategic
choices characterizing
the relationship between
complementors and
platform owners
Gawer and
Cusumano (2002,
2008)
Commons-based
peer production
Domain: Law and
political economy
The social logic of peer
production coordinates
distributed innovation and
creates a commons as
shared resource
Peer production as
alternative coordination
mechanism to the visible
hand of the manager and the
invisible hand of the market
Benkler (2002,
2006)
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
Kornberger 5
literatures share a concern with the managerial challenge of making use of distributed innovation
and with the organizational challenge to develop absorptive capacity to appropriate external
knowledge.
However, only relatively few studies have explicitly focused on the design mechanisms that
structure communication, coordination, and control in distributed innovation systems (see Baldwin,
2012; Fjeldstad et al., 2012; Gulati et al., 2012). Despite the shifting locus of innovation from firms
toward networks, Gulati et al. (2012) stated that
our theories of organization design, with their strong intrafirm bias, continue to emphasize elements like
formal authority […], the design of incentives like salary, bonuses, benefits, and promotion opportunities,
and the collocation of individuals performing highly interdependent tasks. (p. 572)
The authors argued that the increase in collaboration with distributed external actors challenges
this theoretization of design, with the consequence that “an emphasis on intrafirm design may be
out of date, at the very least, incomplete” (Gulati et al., 2012: 572). This diagnosis echoes Baldwin’s
(2012) above quoted statement that individual organizations are “no longer adequate to serve as the
primary unit of analysis” (p. 1). Indeed, as firms “shrink their core” and “expand their periphery”
(Gulati and Kletter, 2005), the question of the design of collaborative processes becomes increas-
ingly pertinent.
While the literature on design of distributed innovation systems has articulated this challenge,
it has remained caught in a firm-centric perspective. For instance, Gulati et al. (2012: 582) intro-
duced the notion of meta-organization which describes a cluster of legally autonomous firms or
individuals that can be analyzed and designed as an organization. Their argument borrows much
from the traditional hierarchical design thinking the article aims to leave behind. Gulati et al.’s
discussion of the two dimensions of meta-organization design—permeability of boundaries and
stratification—serves as illustration. The question of boundaries is framed as decisions about
granting membership to the meta-organization (Gulati et al., 2012: 576). The authors then discuss
degrees of stratification within the meta-organization such as the control span as hierarchical
design choice: “Like hierarchies in traditional organizations, tiering serves to specify spans of
control within meta-organizations” (Gulati et al., 2012: 578). While traditional organization
design supposed a manager-architect that engineered the relationships between individual
employees, it is now the “focal firm” that plays the role of the system architect, shaping relation-
ships among suppliers, partners, and other network members. The corollary of Gulati et al.’s
approach is that open communities are analytically distinguished by what they are lacking in
comparison with hierarchically organized firms: boundaries toward the environment and internal
stratification. Rather than investigating the specific processes that structure distributed innovation
networks in which authorship of ideas, and by extension authority over the network, are distrib-
uted, the ideas put forward by Gulati et al. (2012) extend traditional firm-based design thinking.
Similarly, the notion of the actor-oriented design scheme proposed by Fjeldstad et al. (2012)
borrows much from the traditional organization design literature they criticize. For instance, dis-
cussing Accenture as case of an architecture of collaboration (Fjeldstad et al., 2012: 740–741), the
authors identify long-term development and training of staff, the information technology (IT)-
based internal knowledge management system, and general knowledge sharing between staff as
critical design elements of the actor-oriented architectural scheme. The authors conclude that the
characteristic feature of this and other examples is “that the locus of control and coordination
mechanisms is the organizational actor” (Fjeldstad et al., 2012: 744). Following this perspective,
the shifting locus of innovation is accompanied with the affirmation of the firm as steady locus of
design and control.
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
6 Strategic Organization
The critique of firm-centricity extends to much of the literature on design of distributed innova-
tion systems, including studies on the design of platform innovation. For instance, in Gawer and
Henderson’s (2007) influential work on platform leadership, design is understood quite tradition-
ally as the internal structuring of a firm (in their case, specifically job design at Intel; see Gawer,
2010: 292). Similarly, research on orchestration in network-centric innovation processes focused
on leadership rather than design (Dhanaraj and Parkhe, 2006; Nambisan and Sawhney, 2011). For
instance, Dhanaraj and Parkhe (2006) assumed that “the head cattle lead[s] the herd,” thanks to
superior managerial abilities (p. 659). Such metaphorical framing recaptures, if not the locus of
innovation, at least the locus of control in the visible hand of the manager.
This points toward the problematic assumption in extant research that this article addresses:
research focused on design choices articulates the challenges of design in distributed innovation
systems from a firm-centric perspective; yet, a theory of organization design in distributed net-
works needs to provide a specific framework for understanding those mechanisms that structure
decentralized innovation processes. It is the purpose of this article to explicate such a framework,
showing how design mediates the relationships between the “visible hand” of the manager and the
“crowd” of unruly producer-consumers and other external contributors.
Note that such a framework does not make a priori assumptions about the actors in or designers
of distributed innovation networks: actors may include entrepreneurial individuals (e.g. Linus
Torvalds), collectives (e.g. Wikipedia), crowds (e.g. TopCoder), or firms (e.g. Apple) that form
elements of the distributed innovation system. The design principles that structure network rela-
tions merely describe how the pivotal tasks of communication, coordination, and control between
these heterarchical subsystems are accomplished. In this sense, individuals, collectives, and firms
are treated as elements (nodes) within the network that engage with each other through interfaces,
participatory architectures, and evaluative infrastructures. The authors of these interfaces, partici-
patory architectures, and evaluative infrastructures may include, but are not limited to, firms that
seek to impose their designs on the “crowd.” Alternatively, authorship might be shared between
different actors and shift over time as design schemes evolve. While these are important questions
for future empirical research (see concluding section), this article focuses on the principle design
mechanisms that organize innovation networks.
The next section explicates in detail the three design mechanisms that structure distributed inno-
vation systems: interface design (mediating function), the design of architectures of participation
(enabling function), and the design of evaluative infrastructures (valuation function). Akin to
Baldwin and Clark’s (2000) design rules for evolvable technical systems, these three dimensions
of organization design in “the open” represent a complete set as they address the three fundamental
concerns of organization design: interaction between elements, task differentiation and integration,
and feedback (Simon, 1962).
Design principles for organizing distributed innovation
Design has been one of the key concerns for organization theorists (March and Simon, 1958;
Perrow, 1967; Simon, 1969). As Dunbar and Starbuck (2006) suggested, traditionally, design has
revolved around the notions of “alignment, congruence and fit” between the demands of an exter-
nal environment and the internal parameters at the disposal of the manager, such as people, archi-
tecture, routines, and culture (Roberts, 2004). Following this view, organization design is the
internal response to the strategic choices of management, which in turn are determined by environ-
mental constraints and opportunities (Altman et al., 2015; Chandler, 1962).
Distributed innovation problematizes organization design differently. It suggests shifting the
unit of analysis from the individual firm to networks of actors and their relationships. As Baldwin
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
Kornberger 7
(2012) argued, “the key problem for organization design will be the management of distributed
innovation” and the integration of diverse entities into coherent networks of value production
(p. 1). Because in distributed innovation systems the division of labor cuts across organizational
boundaries and production feeds on multiple, distributed agents, the question of design cannot be
understood as an internal organizational response to strategic choices. Rather, organization design
co-evolves with distributed innovation. Take the example of Apple and its iPhone application ecol-
ogy (see also Lakhani et al., 2012). Hundreds of thousands of applications are developed by exter-
nal parties and sold via Apple’s App Store. To a large degree, the experienced value and functional
versatility of the iPhone result from the creativity of the distributed innovation systems surround-
ing it. Since the creation of innovative applications (including their marketing) occurs outside
Apple’s boundaries, the question of organization design shifts, too. Hence, while organization
design refers to the structuring of communication, coordination, and control in both closed and
open systems, the mechanisms with which communication, coordination, and control are accom-
plished in networks are different.
Analytically this raises three distinct questions: First, how is the interaction between actors in dis-
tributed innovation systems structured? Second, how are production processes designed so that distrib-
uted actors with different motivations, skills, and commitment levels can contribute meaningfully?
And third, how can actors evaluate the results of distributed innovation and assess its qualities?
Principle 1: interface design
Hierarchies are communication structures that determine chains of command (down) and lines of
reporting (up). They are oblivious toward horizontal communication. In contrast, when interacting
with distributed innovation systems, the task of design is to facilitate horizontal communication
between network actors, including firms, on one hand, and external producers in distributed inno-
vation systems, on the other.
Organizational design addresses the problem through the design of interfaces.3 An interface is
defined as a medium that organizes the exchange between two or more heterarchically distributed
elements (Galloway, 2012). Interfaces can take many forms: online examples include forums, por-
tals, and websites that structure the flow of information and communication; offline, events such
as conferences or innovation camps provide interfaces between firms and communities; boundary
objects facilitate interaction between different epistemic communities (Nicolini et al., 2012); and,
more institutionally, boundary organizations such as the European Union (EU)-sponsored Living
Labs, or consultancies such as Hyve, provide structure to the interaction between distributed inno-
vators, including crowds and firms (Almirall and Wareham, 2008; O’Mahony and Bechky, 2008).
These examples point toward the main characteristic of an interface. It acts as a filter that structures
access to and the exchange of information between two or more elements.4
Analytically, interfaces have several important dimensions. First, as Simon (1969) posited,
interfaces are “meeting points” mediating between internal and external environments. They struc-
ture the interaction between different parties by organizing the exchange of information. Consider,
for example, the interface on email software that allows for three different types of recipients: those
addressed directly, those copied in, and those blind copied. In a subtle yet powerful way, the inter-
face structures choice between alternatives. In this sense, interfaces exercise power; they are
“architectural control points” (Woodward, 2008) that enable and constrain interaction simultane-
ously. “The common interface,” explained Langlois and Garzarelli (2008), “enables, but also gov-
erns and disciplines, the communication among subsystems” (p. 9). Interfaces represent often
technologically mediated affordances that encourage certain actions (e.g. press like button to show
support) and make others less likely (e.g. expressing dissensus on Facebook).
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
8 Strategic Organization
Second, and closely related, interfaces organize boundaries to enable communication between
heterarchical subsystems. While extant research has elaborated on the shifting nature and permea-
bility of boundaries (Lakhani et al., 2013; Lifshitz-Assaf, 2015; Ferraro and O’Mahony, 2012), a
focus on interfaces invites the researcher to zoom into the actual design of boundaries and the pas-
sages through which information flows. On a micro-level, interfaces may be analyzed as formatting
devices that govern exchange across boundaries. The notion of formatting captures the role of tech-
nology and its affordances in structuring communication through interfaces (Orlikowski, 1992).
Third, and in contradistinction to traditional organizational design, interfaces do not promote
integration. In distributed innovation systems, the integration of external producers would be det-
rimental, as Chatterji and Fabrizio (2012) argued: “If firms attempt to bring users into the firm to
capture their unique knowledge assets, they risk losing the attributes that make user input valuable
in the first place” (p. 984). There are three reasons for the diminishing return of integrating external
actors: socially, integration means that they grow distant from their network, which has been their
source of innovation (Powell et al., 1996); cognitively, integrated actors adapt to dominant frames
(March, 1991); and motivationally, contractual obligations and economic incentives might lead to
crowding-out effects (Fehr and Falk, 2002).
The specificity of interfaces resides in their ability to create communication between heteroge-
neous elements while maintaining their differences. Galloway and Thacker (2007) used the notion
of interoperability to describe how interfaces mediate between dissimilar data forms. The aim of
mediating interfaces is to create communication across multiplicities without reducing their differ-
ences; they are mechanisms for translation, not assimilation.
In sum, the concept of interface design expands related concepts of boundary spanning (Aldrich
and Herker, 1977), brokers (Burt, 1992), and the debate on absorptive capacities (Cohen and
Levinthal, 1990; Zahra and George, 2002) in significant ways. An interface represents systemati-
cally designed points of interaction between an element (for instance, a firm) and its surrounding
network that are (1) meeting points between internal and external elements which (2) translate
heterogeneous contributions into organizationally readable formats and (3) structure the work and
decisions of those producing in distributed innovation networks more or less clandestinely.5
A good example of the versatility of interface design is the social networking site Facebook,
which uses an existing technology (the internet), existing hardware (computers, smartphones, etc.),
and freely available programming languages (codes) and combines them to create supposedly
unique value for its users (see Baldwin, 2012: 9). In effect, Facebook’s value-add basically amounts
to an adept layering of interfaces on top of each other—for what else is Facebook if not a clever
nesting of interfaces onto a database generated by user activities?
Principle 2: design of architectures of participation
Hierarchically organized production is characterized as a grammar to reduce complexity and ambi-
guity (Weick, 1979). Equally, distributed innovation systems rely on a grammar to coordinate tasks
and integrate outputs. However, in contrast to hierarchical design, the grammar of distributed inno-
vation has to allow for distributed actors with varying degrees of motivation, skill, and commit-
ment levels to contribute to something that emerges without the planning of a managerial
mastermind. Hence, rather than organizing internal differentiation and integration, architectures of
participation provide a design mechanism for the integration of external production (Baldwin and
Clark, 2006; building on Simon, 1962; see also O’Reilly, 2004).
Architectures of participation structure the collaboration in distributed innovation systems by
designing open production processes. Following Baldwin and Clark (2006), these architectures of
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
Kornberger 9
participation refer to three design characteristics that organize collaboration within distributed
innovation systems. First, modularity refers to the idea that products can be deconstructed into
modular units and developed independently of each other. This is important as different people
with different skills may work at different times with different speeds on different aspects of one
and the same project. The modularity principle echoes Simon’s (1962) idea of a decomposable
system in which modular units interact with each other through interfaces. The benefit of such a
decomposable system is higher stability in the face of environmental uncertainty achieved through
a loose coupling of elements. Second, the principle of granularity states that modules have to be
small in size so that a given project attracts people with different levels of motivation and commit-
ment (Benkler, 2002). For instance, on Wikipedia, rating the usefulness of an entry with a click or
researching and writing a new entry from scratch illustrate the breadth of possible levels of contri-
bution. Third, low integration costs are pivotal as the task of relating modular and granular ele-
ments to each other would otherwise create costs that outrun the gains achieved through distributed
innovation. Integration can occur in various forms (Benkler, 2002: 441). For instance, a second-
order peer production mechanism can be used for the integration of the modular units, as is the case
in review-based quality control systems. Forms of normative control can act as mechanisms of
integration and quality control, such as in the case of Wikipedia (see Duguid, 2006 on the limits of
self-organization). Other forms of integration include technology which can perform the integra-
tive function by specifying conditions of integration, or a temporary return of managerial hierar-
chy. For instance, Linux developer community uses this mechanism for important decisions about
system evolution.
Importantly, architectures of participation do not reduce complexity (like traditional organi-
zation design does) but increase complexity in a controlled way. Lego provides a good example
of how a simple system that adheres to modularity, granularity, and low integration costs can
provide the grammar for open-ended creative expression. Indeed, Lego blocks can be under-
stood as a language that allows, through grammar and vocabulary, the creation of complex arti-
facts and experiences (Antorini, 2007). Hence, distributed innovation is not limited by the
overall complexity of a task, but by the modular, granular, and integrative characteristics of a
given project (Benkler, 2002).
There are a growing number of examples that illustrate the playful application of architectures
of participation in practice. One of the early examples was the “mole game” developed by the
Finnish National Library.6 The computer game invited players to build bridges for moles by typing
words that appear on a screen. The words, instead of being random, were the ones the automatic
scanning program of the Finnish National Library found illegible. Hence, players solved an other-
wise costly undertaking for the library. Scientists have developed similar gamification strategies to
solve laborious tasks. For instance, in the game Eyewire, amateur gamers map the connections of
the nervous system of the eye, while Foldit is an online puzzle in which players fold protein
structures.
These examples point toward the importance of an intelligent architecture of participation to
enable collaboration in distributed networks: in all three cases, complex challenges are broken
down into tasks that are modular (the problem can be decomposed into small sub-problems), gran-
ular (you can play once or many times, every input matters), and where integration costs remain
low (technology collects and processes gaming results). Such a modular, granular, and integrative
Lego-esque architecture provides a language for people to contribute to projects in the “open.”
Architectures of participation may also impact the expressiveness and creativity of actors in the
distributed innovation system, for every language is also always a system of rules (grammar) that
structures what can be said and what cannot.
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
10 Strategic Organization
Principle 3: design of evaluative infrastructures
In distributed innovation systems, the most valuable resources for production—know-how and
human ingenuity—are located outside firm boundaries. Interfaces and effective architectures of
participation result in a wealth of contributions. In fact, in many distributed innovation networks,
there are too many ideas, products, and experiences on offer. Think of websites such as kickstarter.
com, where to date more than 80,000 projects ranging from fashion to film and music have been
funded by over 8 million investors, pledging more than US$1.6 billion. The problem then becomes,
“How to evaluate innovations and ensure quality control?”
Evaluative infrastructures can be defined as methodologies and technologies of valuation that
are distributed across innovation networks. They are methodologies because they presuppose cer-
tain epistemological assumptions about what is valuable as well as calculative practices through
which things can be evaluated (Miller, 2001). They are technologies because they could not exist
without a plethora of material evaluation devices that measure, quantify, index, compare, fix, and
calculate values (Karpik, 2010). Examples of evaluative infrastructures include rankings, ratings,
reviews, tagging, bestseller lists, and awards (see Espeland and Sauder, 2007; Karpik, 2010;
Orlikowski and Scott, 2014). They can be produced by users (TripAdvisor or Facebook’s like but-
ton), experts (awards), or automatically through algorithms (Amazon’s reference function or
Google Search). In all instances, the “click” plays a pivotal role; it represents a new epistemologi-
cal category in which thinking and action, decision-making and execution coincide. And, because
every click leaves a trace, it provides much of the raw material for evaluative infrastructures.
Evaluative infrastructures evolve in parallel to distributed innovation systems. They fulfill sev-
eral important functions. First, they represent accounting regimes that make things visible (Miller,
2001). For instance, trust has been identified as an important characteristic in knowledge intensive
production processes (Adler, 2001). How do distributed innovators who have never met each other
develop trust in each other? Evaluative infrastructures represent technologies that make trust visi-
ble. For example, the online accommodation provider Airbnb is an interface for people who would
like to rent out their apartment temporarily and for tourists who would prefer staying in a more
personal, cheaper home rather than an anonymous, expensive hotel. The service begs the question
of trust: how can you offer your apartment to someone you have never met? Airbnb’s success is
based on its solution to this problem, which involves a rating system that creates a reputation for
each user. After each stay, both parties evaluate each other, which creates a profile that will impact
one’s future ability to either rent or lease a flat. The Airbnb co-founder, Nathan Blecharczyk,
described reputation as the social currency that makes the exchange work.7
More generally, reputation gains are important motivators for contributors to distributed inno-
vation (Lerner and Triole, 2002). Through valuation practices, reputation is made visible, which,
in turn, motivates members to contribute. Hence, evaluative infrastructures generate a reputation
economy by providing the scaffolding for people to build their careers in “the open.” An illustra-
tive example of this mechanism is TopCoder.com, which hosts competitions between its more than
750,000 talented programmers and software designers and connects them with firms that are in
need of software solutions (see Boudreau et al., 2011). Top coders’ achievements are displayed on
the website and the quality of the coders’ reputations indicated by badges awarded according to a
“progress meter.” Through such visualizations, evaluations allow the buildup of cultural and sym-
bolic capital.
Evaluative infrastructures do not merely make values visible; they are also constitutive of new
values. Having a certain number of followers in an online network such as Twitter is a new form of
social value that is inextricably linked to the technology that allows for its visualization. Reference
tools, such as Amazon’s “If you like books by [author’s name], you might like …,” create new
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
Kornberger 11
cartographies of products, bestowing forms of symbolic and cultural value upon them by relating
them. The networking site LinkedIn asks its users to tag (“endorse”) members in their network,
making qualities visible that constitute new profiles. Hence, evaluative infrastructures engender
new forms of accounting for multiple values. They are mechanisms to quantify qualities and coin
new currencies, such as trust quantified as grade on a scale (Airbnb) or an overall sellers rating
(eBay). In so doing, they do not simply measure but actively co-constitute new values.
In effect, evaluative infrastructures play an important role in organizing sense-making and deci-
sion-making. As argued, distributed innovation invites a wealth of proposals, prototypes, and prod-
ucts that are launched continuously. The question is how to navigate these productions that no-one
asked for and how to find those that are valuable and reliable. In a hierarchical system, selection is
based on a priori defined criteria; in distributed innovation networks, selection is based on a poste-
riori evaluations (Benkler, 2006). Rankings, ratings, and other evaluation devices represent regimes
of valuation that categorize and hierarchize products emerging from distributed innovation sys-
tems. Virtually anything (downloads, citations, references, etc.) can serve as raw material for valu-
ations. And, since everything leaves a trace, virtually every activity can be translated into an input
for a higher level evaluation (e.g. papers feed citation analyses, which feed the h-index). These
cascades of valuations create (at least temporarily stable) taxonomies that allow for users to make
sense and decision. As Karpik (2010) puts it, valuation devices are cognitive prosthesis that help
consumers through an increasingly complex world. Put simply, evaluative infrastructures emerge
at the point where the scare resource is the cognitive capacity to weigh alternatives. In fact, Apple’s
App Store ranks Apps that are hip, TripAdvisor suggests where to eat and sleep, and Google pro-
poses the most relevant answer to a particular inquiry; in each of these three instances, evaluative
infrastructures categorize and hierarchize otherwise overwhelming amount of new products, idea,
and experiences and through doing so support sense- and decision-making.
Discussion
Reconfiguring organization design in distributed innovation systems
As scholars from a variety of fields have suggested, given modern communication technology and
a wealth of new organizational forms, the locus of innovation shifts from firms to open networks.
This article suggests a framework for the study of how organization design accomplishes commu-
nication, coordination, and control in such networks. Interfaces, architectures of participation, and
evaluative infrastructures represent the design mechanisms that organize network interaction and
transaction.
This framework advances organization design’s traditional analytical vocabulary. To date,
organization design scholars have not responded sufficiently to the challenges and opportunities of
this shift toward distributed innovation (Dunbar and Starbuck, 2006). Foundational work from the
middle of the last century is still providing the vocabularies for current debates (Burns and Stalker,
1961; Chandler, 1962; Lawrence and Lorsch, 1967; March and Simon, 1958; Woodward, 1965).
For instance, Chandler (1962) proposed understanding structure as “the design of the organization
through which the enterprise is administered” (p. 14), including internal hierarchical structuring of
organization, division of labor (differentiation and integration), managerial control, and perfor-
mance measurement systems (see also Altman et al., 2015). The key concern is to create “fit”
between exogenous forces and what is treated as internal variables, such as people, architectures,
routines, and culture (Roberts, 2004). But when economic activity is organized outside the bounda-
ries of hierarchically organized firms, managers may have little or no jurisdiction over those vari-
ables and the performance of those who were neither hired by them nor can be fired by them.
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
12 Strategic Organization
The contribution that this article makes is to show how organization design can be conceptual-
ized as a novel form of structuring communication, coordination, and control in distributed innova-
tion systems. The key tenet of this article is that distributed innovation systems are characterized
by three specific design parameters: In the first place, interfaces structure interaction within dis-
tributed innovation systems; in the second place, architectures of participation provide a language
through which network innovators with varying degrees of commitment, motivation, and skills can
articulate their contributions; and finally, evaluative infrastructures encompass rankings, ratings,
and a myriad of other evaluation devices through which products are being compared, commensu-
rated, and categorized.
Most importantly, the primary function of organization design in distributed innovation sys-
tems is not to actually organize production or to innovate, but to provide the conditions in which
distributed innovators can do so. To return to the example of Ford, at the beginning of the 20th
century, Ford’s assembly line provided an internalized infrastructure that organized production.
The knowledge economy requires a different kind of infrastructure, one that invites distributed
actors to contribute and co-create. The assembly line is, so to speak, folded from the inside of the
firm out onto the innovation network. This infrastructure does not enforce internal hierarchy but
consists of multiple nested interfaces mediating between heterarchically organized, heterogene-
ous subsystems; it does not differentiate and integrate tasks internally but offers a language for
external actors to become co-authors of novel ideas, products, and technologies; it does not strive
for assimilation but represents a mechanism for translation; and, finally, it does not directly con-
trol those who produce but provides evaluative infrastructures that order and hierarchize what is
produced in “the open.”
Implications for theory
Design as mechanism to organize “the open” has some further implications for theories of search
and the resource-based view.
First, theorizing the “visible hand” and the “crowd” transforms the organizational search prob-
lem (March, 1991). Researchers have repeatedly argued that outstanding organizational perfor-
mance results form strategic leaders’ “superior ability to manage the mental processes necessary to
pursue cognitively distant opportunities” (Gavetti, 2012: 267). Yet, a well-established body of lit-
erature has evolved over the decades that shows management’s structural problems with search.
For instance, Salancik and Pfeffer (1974) argued that power dynamics determine resource alloca-
tion, making organizations paradoxically fit to respond to threats but, in the long run, unfit to cope
with new challenges. March described the “competency trap” (Levitt and March, 1988) which
results from successful past experience. Experience, he argued, “is likely to generate confidence
more reliably than it generates competence and to stop experimentation too soon” (March, 2010:
114). Because core competencies easily become “core rigidities” (Leonard-Barton, 1992), today’s
success may breed tomorrow’s failure.
The proposed framework shifts the question of search as an experiential and cognitive task
(Gavetti and Levinthal, 2000) toward search as a distributed process facilitated by organizational
design. Distributed innovation systems comprised a large number of actors with different needs,
competencies, and objectives. The actors are distributed heterachically and, each conditioned by
their own bounded rationalities, perform searches for new ideas according to their own evaluation
criteria. In other words, search is performed among a variety of distributed actors who have their
own definition of what counts (Stark, 2009). But what structures such a seemingly chaotic search
process? The proposed theory of design suggests three organizing principles for such searches.
Organization design in distributed innovation systems explicates (1) how contending search filters
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
Kornberger 13
can interact via interfaces, (2) how individual actors can build onto each others’ contributions, and
(3) how different valuations come about.
In regards to search, the last point deserves special emphasis. Evaluative infrastructures are
epistemic machines that scan open networks for different values, monitoring, comparing, and
visualizing them. From Facebook’s like button to TopCoder’s reputation hierarchies and
Amazon’s cross-referencing categorization system, these and other mechanisms have to be
understood as evaluation tools that monitor how orders of worth emerge. Hence, evaluative
infrastructures represent “heterogeneous systems of accounting for worth” (Stark, 2009: 25),
which are in and of themselves valuable, as Stark (2009) elaborated: “Where the organizational
environment is turbulent and there is uncertainty what might constitute a resource under changed
conditions, contending frameworks of value can themselves be a valuable organizational
resource” (p. 6).
Second, the arguments put forward in this article have implications for the resource-based view
of the firm. The resource-based view suggests that sustainable competitive advantage is rooted in
an organization’s specific resources, competencies, and capabilities (Barney, 1991; Prahalad and
Hamel, 1990; Teece et al., 1997; Wernerfelt, 1984). Prahalad and Hamel (1990) suggested the
metaphor of a tree, where products and services resemble the leaves exposed to the wind and
weather, but where the true “roots of competitiveness” are to be found in the core competencies,
hidden deep down in the soil, the roots storing away a firm’s main resource (knowledge). However,
the image of roots as representing an organization’s most valuable assets is misleading; rather,
knowledge is distributed across networks and located outside organizational boundaries. Hence, it
is not ownership or other forms of direct control over resources that bestows a competitive advan-
tage on firms but rather access to resources (Rifkin, 2000). For strategy, this raises the question,
“How can access be organized?” This article has identified three mechanisms that can facilitate
access to resources outside firm boundaries. Interface design organizes access and exchange
between heterachically organized subsystems; architectures of participation provide the language
(alphabet and grammar) to co-author innovative narratives and ideas; and evaluative infrastruc-
tures represent ordering mechanisms that classify, categorize, and hierarchize co-created products
and services. Moreover, evaluative infrastructures make visible resources such as talent (TopCoder),
reputation (reviews on Airbnb), or trust (eBay) which are in turn the crucial inputs for further stra-
tegic thought and action (see for the example of eBay Baron, 2001; Saeedi et al., 2013). In short,
the proposed analytics of organization design in distributed innovation systems contributes to the
resource-based view by explicating how external resources can be identified, coordinated, and to
some degree, governed.
These suggestions have implications for the debate between strategy and structure more gener-
ally. Under conditions of a distributed resource base, it can be hypothesized that strategy does not
determine structure, but that an organization’s interface design, participatory architecture, and
evaluative infrastructures determine its strategic options. By extension, organizational design is
not a question of fit but a generative force that creates new possibilities. To return to Prahalad and
Hamel’s metaphor, the competencies of a firm are not its roots; competencies reside in its ability to
design interfaces between externally situated know-how, to provide architectures for meaningful
conversation and collaboration, and to develop evaluative infrastructures to make contributions
visible and valuable.
Implications for further empirical research
This article’s conceptual vocabulary invites to broaden the empirical research agenda of scholars
studying the strategic organization of distributed innovation systems.
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
14 Strategic Organization
Following Baldwin’s (2012) call, this article provided a conceptualization of organization
design that does not take the individual firm but the network as unit of analysis. It suggests
studying interfaces, participatory architectures, and evaluative infrastructures as pivotal design
mechanisms that structure communication, coordination of tasks, and control in distributed
innovation systems. Future empirical research might focus on concrete enactments of these
design mechanisms in practice: How do interfaces format the flow, direction, and density of
information in distributed innovation networks? How do these interfaces as architectural control
points facilitate translations across boundaries, and what is lost in translation? How are modular-
ity, granularity, and low integration costs accomplished in networks? In how far do participatory
architectures (akin to languages) pre-configure network actors’ experiences of the present and
imagination of possible futures? How do evaluative infrastructures commensurate, categorize
and hierarchize the contributions of network actors, establishing new orders of worth? And how
do these evaluations inform sense-making and decision-making of network actors, consumers,
and other stakeholders? Such empirical research into organization design of networks needs to
be complemented with a focus on the specific affordances of technology: how does technology,
including devices, applications, software, algorithms, and so on structure the space of possible
actions of network actors? Such empirical inquiry into the organization design in networks will
also produce insights into the relationships between actual organization designs and networks’
innovation capacity and overall agility.
Last but not least, the suggested conceptualization of organization design in distributed innova-
tion systems invites further empirical analysis of the question of authorship of designs. Avoiding
firm-centricity, future research might analyze authorship of interfaces, participatory architectures,
and evaluative infrastructures as distributed phenomenon. Authors may include, but are not limited
to, firms that seek to impose their designs on the “crowd” as well as actors, such as entrepreneurs,
collectives, and others, that play significant roles in the emergence and ongoing evolution of
designs. Bringing in a temporal, dynamic perspective, over time authors’ roles might range from
active co-designers to users that appropriate dominant designs through their (performative) rou-
tines, bending and sometimes breaking design rules.
Concluding reflections
Theorizing organization design between the “visible hand” and the “crowd” invites a concluding
speculation. As Drucker (2002) argued, management is perhaps the most important socio-technical
invention of the 20th century. Management’s legitimacy is based on its efficiency claim, and thus
managers, at least theoretically, are held accountable for how the organization performs.
Distributed innovation challenges this theoretization of the manager. In the context of distrib-
uted innovation, the manager does not have formal authority over the production process. The
legitimizing claim of efficiency gains through managerial coordination cannot be upheld either.
Rather, unruly producer-consumers and other external agents whom the manager can neither hire
nor fire are valuable yet also uncontrollable organizational resources. In this context, the manage-
rial challenge shifts from being focused on the efficient allocation of internal resources to a con-
cern with organizing “the open,” that is, designing structures and systems for coordinating work
outside company walls (Boudreau and Lakhani, 2013).
How, then, can we rethink the role of the manager? Perhaps managing could be reimagined as
practice of diplomacy, with diplomacy defined as the “attempt to govern the ungovernable—the
anarchical society—through discursive and cultural practices” (Der Derian, 1987: 4). Diplomacy
is a potentially fruitful metaphor for describing management in “the open” because, historically,
the power of diplomacy evolved in inverse relation to the demise of the power of the sovereign.
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
Kornberger 15
Foreign cultures had to be decoded diplomatically because they could not any longer be firmly
oppressed or safely ignored. In other words, diplomacy marks the sovereign’s tacit acknowledge-
ment that the world is polycentric. The disaggregation of authority into multiple “spheres of author-
ity” (Rosenau, 1997, 2007) might characterize not only international but also organizational
relations. In open networks characterized by shifting alliances, dispersed leadership, distributed
agency and multiple authorship, the manager’s tasks might start resembling that of a diplomat, as
both are concerned with creating the conditions for collective action to occur.
Following from that, and emphasizing the Galbraith quote cited at the beginning of this article,
it is not ideological debates for or against capitalism that matter; rather, it is the imperatives of
technology and organization that shape society. New practices of value creation in distributed
innovation networks and new design mechanisms to organize “the open” may represent part and
parcel of such imperatives. Whether or not distributed innovation represents a new form of organ-
izing economic activity or merely an attempt to hollow out bureaucracies, whether it will lead to
groupthink on an unprecedented scale or valuable new ideas, whether it will debunk the expert and
install a regime of populism instead, these questions will depend at least partly on how distributed
innovation comes to be integrated into existing circuits of production and power. For better or
worse, organization design as a mechanism to structure the interaction between the “visible hand”
and the “crowd” will play a crucial role in these attempts to organize (and perhaps to disorganize)
“the open.”
Acknowledgements
I would like to thank José Ossandón, David Stark, Vitaliano Barberio, Stefano Ponte, Christian Frankel, Eric
von Hippel, Christof Brandtner, Alfred Kieser, and the participants at a Zeppelin University seminar about
The Visible Hand and the Crowd in spring 2013 for their comments. I would also like to thank the three
reviewers for their constructive comments and the editors of this special issue for their guidance.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publi-
cation of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
Notes
1. See http://148apps.biz/app-store-metrics/ and https://www.apple.com/pr/library/2015/01/08App-Store-
Rings-in-2015-with-New-Records.html
2. The definition excludes open innovation (Chesbrough, 2003) because it is predominantly concerned with
commercialization of distributed innovation from a firm perspective (Lichtenthaler, 2011) and revenue-
generating practices form a firm perspective (Bogers and West, 2012). Open innovation is defined as “the
use of purposive inflows and outflows of knowledge to accelerate internal innovation, and expand the
markets for external use of innovation, respectively” (Chesbrough, 2006: 1). Consequently, open inno-
vation studies focus on value capturing mechanisms that enable “the organization to sustain its position
in the industry value chain over time” (Chesbrough, 2006: 2; see also Chesbrough, 2003; Fosfuri et al.,
2008). In contrast, distributed innovation systems shift the analytical focus from firms, industries, and
value chains to networks and business ecosystems.
3. Note that communication in hierarchies is also enabled through interfaces (reports, performance reviews,
personnel assessments, etc. can be read as interfaces). The point of the analysis offered in this article is
to explore the specificity of those interfaces that act as filters structuring access to and the exchange of
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
16 Strategic Organization
information horizontally between two or more elements within distributed innovation systems. I would
like to thank one of the reviewers for bringing this point to my attention.
4. A technical interface is commonly analyzed as standard, which structures exchange within a network
(e.g. MPG as a technical standard that allows electronic file sharing). While technical standards play an
important role, this article focuses on communication interfaces (see Baldwin and Clark, 2000).
5. As one reviewer pointed out, there is a noteworthy parallel to Hayek’s idea that prices organize commu-
nication horizontally between distributed network actors. Prices may fulfill this function in a production-
focused (commodity-based) economy. However, in economic situations characterized by uncertainty
and ambiguity about the value of a new idea, product, or service, the price mechanism fails. Therefore,
horizontal communication between distributed network actors is accomplished through a plethora of new
interfaces and evaluative infrastructures that organize supply and demand.
6. http://dailycrowdsource.com/20-resources/projects/579-a-game-of-moles-crowdsourcing-the-archives-
of-the-finnish-national-library
7. Interview in Die Zeit, no. 34, 16 August 2012, p. 28.
References
Adler P (2001) Market, hierarchy, and trust: The knowledge economy and the future of capitalism.
Organization Science 12(2): 215–234.
Afuah A and Tucci CL (2012) Crowdsourcing as a solution to distant search. Academy of Management
Review 37: 355–375.
Afuah A and Tucci CL (2013) Value capture and crowdsourcing. Academy of Management Review 38(3):
457–460.
Aldrich H and Herker D (1977) Boundary spanning roles and organization structure. Academy of Management
Review 2: 217–230.
Almirall E and Wareham J (2008) Living labs and open innovation: Roles and applicability. The Electronic
Journal for Virtual Organizations and Networks 10(3): 21–46.
Altman EJ, Nagle F and Tushman ML (2015) Innovating without information constraints: Organizations,
communities, and innovation when information costs approach zero. In: Shalley MH and Zhou J (eds)
Oxford Handbook of Creativity, Innovation, and Entrepreneurship: Multilevel Linkages. Oxford: Oxford
University Press, pp. 353–379.
Antorini YM (2007) Brand community innovation—An intrinsic case study of the adult fans of LEGO com-
munity. PhD Thesis, Copenhagen Business School, Frederiksberg.
Baldwin CY (2012) Organization design for distributed innovation. Harvard Business School Working
Paper, 4 May, pp. 12–100. Available at: http://www.hbs.edu/faculty/Publication%20Files/12-100.pdf
Baldwin CY and Clark K (2000) Design Rules: The Power of Modularity. Cambridge: MIT Press.
Baldwin CY and Clark K (2006) The architecture of participation: Does code architecture mitigate free riding
in the open source development model? Management Science 52(7): 1116–1127.
Baldwin CY and Von Hippel E (2011) Modeling a paradigm shift: From producer innovation to user and open
collaborative innovation. Organization Science 22(6): 1399–1417.
Barney J (1991) Firm resources and sustained competitive advantage. Journal of Management 17(1): 99–120.
Baron DP (2001) Private ordering on the Internet: The eBay community of traders. Graduate School of
Business Stanford University Research Paper Series No. 1709. Available at: https://www.gsb.stanford.
edu/faculty-research/working-papers/private-ordering-internet-ebay-community-traders
Benkler Y (2002) Coase’s Penguin, or, Linux and the nature of the firm. The Yale Law Journal 112(3):
369–446.
Benkler Y (2006) The Wealth of Networks: How Social Production Transforms Markets and Freedom. Yale
University Press.
Bloodgood J (2013) Crowdsourcing: Useful for problem solving, but what about value capture? Academy of
Management Review 38(3): 455–457.
Bogers M and West J (2012) Managing distributed innovation: Strategic utilization of open and user innova-
tion. Creativity and Innovation Management 21(1): 61–75.
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
Kornberger 17
Boudreau KJ (2012) Let a thousand flowers bloom? An early look at large numbers of software app develop-
ers and patterns of innovation. Organization Science 23(5): 1409–1427.
Boudreau KJ and Lakhani KR (2009) How to manage outside innovation. MIT Sloan Management Review,
1 July, pp. 69–76.
Boudreau KJ and Lakhani KR (2013) Using the crowd as innovation partner. Harvard Business Review,
April, pp. 61–69.
Boudreau KJ, Lacetera N and Lakhani KR (2011) Incentives and problem uncertainty in innovation contests:
An empirical analysis. Management Science 57(5): 843–863.
Brynjolfsson E (1993) The productivity paradox of information technology. Communications of the ACM
36(12): 66–77.
Burns T and Stalker GM (1961) The Management of Innovation. London: Tavistock.
Burt R (1992) Brokerage and Closure: An Introduction to Social Capital. Oxford, NY: Oxford University
Press.
Callon M (1987) Society in the making: The study of technology as a tool for sociological analysis. In: Bijker
W, Hughes TP, Pinch T, et al. (eds) The Social Construction of Technological Systems: New Directions
in the Sociology and History of Technology. Cambridge, MA: MIT Press, pp. 88–103.
Chandler A (1962) Strategy and Structure: Chapters in the History of the American Enterprise. Boston, MA:
MIT Press.
Chatterji A and Fabrizio K (2012) How do product users influence corporate invention. Organization Science
23: 951–970.
Chesbrough HW (2003) Open Innovation: The New Imperative for Creating and Profiting from Technology.
Boston, MA: Harvard Business School Press.
Chesbrough HW (2006) Open innovation: A new paradigm to understanding industrial innovation. In:
Chesbrough HW, Vanhaverbeke W and West J (eds) Open Innovation: Researching a New Paradigm.
Oxford: Oxford University Press, pp. 1–12.
Cohen WM and Levinthal DA (1990) Absorptive capacity: A new perspective on learning and innovation.
Administrative Science Quarterly 35(1): 128–152.
Der Derian J (1987) On Diplomacy: A Genealogy of Western Estrangement. Oxford and New York: Basil
Blackwell.
Dhanaraj C and Parkhe A (2006) Orchestrating innovation networks. Academy of Management Review 31(3):
659–669.
Drucker P (2002) Managing in the Next Society. New York: Truman Talley Books/St. Martin’s Press.
Ducheneaut N (2005) Socialization in an open source software community: A socio-technical analysis.
Computer Supported Cooperative Work 14: 323–368.
Duguid P (2006) Limits of self-organization: Peer production and “laws of quality.” First Monday 11(10).
Available at: http://firstmonday.org/article/view/1405/1323#author
Dunbar RL and Starbuck WH (2006) Learning to design organizations and learning from designing them.
Organization Science 17(2): 171–178.
Espeland W and Sauder M (2007) Rankings and reactivity: How public measures recreate social worlds.
American Journal of Sociology 113(1): 1–40.
Fehr E and Falk A (2002) Psychological foundations of incentives. European Economic Review 46: 687–724.
Ferraro F and O’Mahony S (2012) “Managing the Boundary of an Open Project.” In: Powell W and Padgett J
(eds) Market Emergence and Transformation. Princeton, NJ: Princeton University Press, pp .545–565.
Fjeldstad OD, Snow CC, Miles RE, et al. (2012) The architecture of collaboration. Strategic Management
Journal 33: 734–750.
Fleming L and Waguespack DM (2007) Brokerage, boundary spanning, and leadership in open innovation
communities. Organization Science 18(2): 165–180.
Fosfuri A, Giarratana MS and Luzzi A (2008) The penguin has entered the building: The commercialization
of open source software products. Organization Science 19(2): 292–305.
Galbraith JK (1967) The New Industrial State. New York: New American Library.
Galloway A (2012) The Interface Effect. Cambridge and Malden, MA: Polity Press.
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
18 Strategic Organization
Galloway A and Thacker E (2007) The Exploit: A Theory of Networks. Minneapolis, MN and London:
University of Minnesota Press.
Gavetti G (2012) Towards a behavioral theory of strategy. Organization Science 23(1): 267–285.
Gavetti G and Levinthal D (2000) Looking forward and looking backward: Cognitive and experiential search.
Administrative Science Quarterly 45(1): 113–137.
Gawer A (2010) The organization of technological platforms. Research in the Sociology of Organizations
29: 287–296.
Gawer A and Cusumano M (2002) Platform Leadership: How Intel, Microsoft and Cisco Drive Industry
Innovation. Boston, MA: Harvard Business School Press.
Gawer A and Cusumano MA (2008) How companies become platform leaders. MIT/Sloan Management
Review 49.
Gawer A and Henderson R (2007) Platform owner entry and innovation in complementary markets: Evidence
from Intel. Journal of Economics & Management Strategy 16(1): 1–34.
Gawer A and Phillips N (2013) Institutional work as logics shift: The case of Intel’s transformation to plat-
form leader. Organization Studies 34(8): 1035–1071.
Gibson JJ (1977) The theory of affordances. In: Shaw R and Bransford J (eds) Perceiving, Acting, and
Knowing: Toward an Ecological Psychology. Hillsdale, NJ: Lawrence Erlbaum, pp. 67–82.
Gulati R and Kletter D (2005) Shrinking core—Expanding periphery: The relational architecture of high
performing organizations. California Management Review 47(1): 77–104.
Gulati R, Puranamn P and Tushman M (2012) Meta-organization design: Rethinking design in interorganiza-
tional and community contexts. Strategic Management Journal 33: 571–586.
Huston L and Sakkab N (2006) Connect and develop: Inside Procter & Gamble’s new model for innovation.
Harvard Business Review 84(3): 58–66.
Jarvenpaa SL, Lim R and Tuunainen VK (2013) Ambidextrous socialization: Exercising control in social
media environment. In: 2013 46th Hawaii International Conference on system sciences (HICSS),
Wailea, HI, 7–10 January, pp. 660–669. New York: IEEE.
Karpik L (2010) Valuing the Unique: The Economics of Singularities. Princeton, NJ and Oxford: Princeton
University Press.
Lakhani KR and Panetta JA (2007) The principles of distributed innovation. Innovations 2(3): 97–112.
Lakhani KR, Lifshitz-Assaf H and Tushman M (2012) Open innovation and organizational boundaries: The
impact of task decomposition and knowledge distribution on the locus of innovation. Harvard Business
School Technology & Operations Management Unit Working Paper 12-57. Available at: http://papers.
ssrn.com/sol3/papers.cfm?abstract_id=1980118
Lakhani KR, Lifshitz-Assaf H and Tushman M (2013) Open innovation and organizational boundaries: Task
decomposition, knowledge distribution and the locus of innovation. In: Grandori A (ed.) Handbook of
Economic Organization: Integrating Economic and Organization Theory. Northampton, MA: Edward
Elgar Publishing, pp. 355–382.
Langlois R (2003) The vanishing hand: The changing dynamics of industrial capitalism. Industrial and
Corporate Change 12(2): 351–385.
Langlois R and Garzarelli G (2008) Of hackers and hairdressers: Modularity and the organizational econom-
ics of open-source collaboration. Industry and Innovation 15: 125–143.
Lawrence PR and Lorsch JW (1967) Organization and Environment: Managing Differentiation and
Integration. Boston, MA: Division of Research, Graduate School of Business Administration, Harvard
University.
Leonard-Barton D (1992) Core capabilities and core rigidities: A paradox in managing new product develop-
ment. Strategic Management Journal 13: 111–125.
Lerner J and Triole J (2002) Some simple economics of open source. Journal of Industrial Economics 52(2):
197–234.
Levitt B and March J (1988) Organizational learning. Annual Review of Sociology 14: 319–340.
Lichtenthaler U (2011) Open innovation: Past research, current debates, and future directions. Academy of
Management Perspectives 25(1): 75–93.
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
Kornberger 19
Lifshitz-Assaf H (2015) From Problem Solvers to Solution Seekers: The Permeation of Knowledge
Boundaries at NASA. SSRN. Available at: http://ssrn.com/abstract=2431717; http://dx.doi.org/10.2139/
ssrn.2431717
March J (1991) Exploration and exploitation in organizational learning. Organization Science 2(1): 71–87.
March J (2010) The Ambiguities of Experience. Ithaca, NY and London: Cornell University Press.
March JG and Simon HA (1958) Organizations. New York: John Wiley.
Miller P (2001) Governing by numbers: Why calculative practices matter. Social Research 68: 379–396.
Nambisan S and Sawhney M (2011) Orchestration processes in network-centric innovation: Evidence from
the field. The Academy of Management Perspectives 25(3): 40–57.
Nicolini D, Mengis J and Swan J (2012) Understanding the role of objects in cross-disciplinary collaboration.
Organization Science 23(3): 612–629.
Normann R and Ramirez R (1993) From value chain to value constellation: Designing interactive strategy.
Harvard Business Review 71(4): 65–77.
O’Mahony S and Bechky BA (2008) Boundary organizations: Enabling collaboration among unexpected
allies. Administrative Science Quarterly 53(3): 422–459.
O’Mahony S and Ferraro F (2007) The emergence of governance in an open source community. Academy of
Management Journal 50(5): 1079–1106.
O’Mahony S and Lakhani KR (2011) Organizations in the shadow of communities. In: Marquis C, Lounsbury
M and Greenwood R (eds) Communities and Organizations: Research in the Sociology of Organizations.
Bingley: Emerald Group Publishing, pp. 3–36.
O’Reilly T (2004) The architecture of participation. Available at: http://oreilly.com/pub/a/oreilly/tim/articles/
architecture_of_participation.html (accessed 24 October 2013).
Orlikowski WJ (1992) The duality of technology: Rethinking the concept of technology in organizations.
Organization Science 3(3): 398–427.
Orlikowski WJ and Scott S (2014) What happens when evaluation goes online? Exploring apparatuses of
valuation in the travel sector. Organization Science 25(3): 868–891.
Perrow C (1967) A framework for the comparative analysis of organizations. American Sociological Review
32(2): 194–208.
Pisano GP and Verganti R (2008) Which kind of collaboration is right for you. Harvard Business Review
86(12): 78–86.
Powell WW (1990) Neither market nor hierarchy: Network forms of organization. In: Staw BM and Cummings
LL (eds) Research in Organizational Behavior. Greenwich, CT: JAI Press, pp. 295–336.
Powell WW, Koput KW and Smith-Doerr L (1996) Interorganizational collaboration and the locus of innova-
tion: Networks of learning in biotechnology. Administrative Science Quarterly 41: 116–145.
Prahalad CK and Hamel G (1990) The core competence of the corporation. Harvard Business Review 68(3):
79–91.
Prahalad CK and Ramaswamy V (2004) The Future of Competition: Co-Creating Unique Value with
Customers. Boston, MA: Harvard Business School Press.
Rifkin J (2000) The Age of Access. New York: Jeremy P. Tarcher/Putnam.
Roberts J (2004) The Modern Firm: Organizational Design for Performance and Growth. Oxford: Oxford
University Press.
Rosenau JN (1997) Along the Domestic-Foreign Frontier: Exploring Governance in a Turbulent World.
Cambridge: Cambridge University Press.
Rosenau JN (2007) Governing the ungovernable: The challenge of a global disaggregation of authority.
Regulation and Governance 1: 88–97.
Saeedi M, Shen Z and Sundaresan N (2013) The value of feedback: An analysis of reputation system. Working
Paper, The Ohio State University, Columbus, OH.
Salancik GR and Pfeffer J (1974) The bases and use of power in organizational decision making: The case of
a university. Administrative Science Quarterly 19(4): 453–473.
Simon H (1969) The Sciences of the Artificial. Cambridge: The MIT Press.
Simon HA (1962) The architecture of complexity. Proceedings of the American Philosophical Society 106(6):
467–482.
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
20 Strategic Organization
Stark D (2009) The Sense of Dissonance: Accounts of Worth in Economic Life. Princeton, NJ: Princeton
University Press.
Teece DJ, Pisano G and Shuen A (1997) Dynamic capabilities and strategic management. Strategic
Management Journal 18(7): 509–533.
Vargo S and Lusch R (2004) Evolving to a new dominant logic for marketing. Journal of Marketing 68: 1–17.
Von Hippel E (1976) The dominant role of users in the scientific instrument innovation process. Research
Policy 5: 212–239.
Von Hippel E (1986) Lead users: A source of novel product concepts. Management Science 32(7): 791–806.
Von Hippel E (1988) The Sources of Innovation. New York and Oxford: Oxford University Press.
Von Hippel E (2005) Democratizing Innovation. Cambridge: The MIT Press.
Von Krogh G, Haefliger S, Spaeth S, et al. (2012) Carrots and rainbows: Motivation and social practice in
open source software development. MIS Quarterly 36(2): 649–676.
Weber S (2004) The Success of Open Source. Cambridge, MA and London: Harvard University Press.
Weick K (1979) The Social Psychology of Organizing. Reading, MA: Addison-Wesley.
Wernerfelt B (1984) A resource based view of the firm. Strategic Management Journal 5(2): 171–180.
West J (2003) How open is open enough? Melding proprietary and open source platform strategies. Research
Policy 32(7): 1217–1241.
West J and O’Mahony S (2008) The role of participation architecture in growing sponsored open source com-
munities. Industry and Innovation 15(2): 145–168.
Williamson OE (1985) The Economic Institutions of Capitalism: Firms, Markets and Relational Contracting.
New York: The Free Press.
Williamson OE (1991) Introduction. In: Williamson OE and Winter S (eds) The Nature of the Firm: Origins,
Evolution, and Development. Oxford: Oxford University Press, pp. 3–17.
Woodward J (1965) Industrial Organization: Theory and Practice. London: Oxford University Press.
Woodward J (2008) Architectural control points. In: Proceedings of the third international conference on
design science research in information systems and technology (eds Vaishnavi V and Baskerville R),
Georgia State University, Atlanta, GA, 7–9 May.
Yates J (1989) Control through Communication: The Rise of System in American Management. Baltimore,
MD: Johns Hopkins University Press.
Zahra SA and George G (2002) Absorptive capacity: A review, reconceptualization, and extension. Academy
of Management Review 27(2): 185–203.
Zammuto RF, Griffith TL, Majchrzak A, et al. (2007) Information technology and the changing fabric of
organization. Organization Science 18(5): 749–762.
Author biography
Martin Kornberger is an undisciplined mind: he received his PhD in Philosophy from the University of
Vienna in 2002 and has held positions in strategy, organization theory, marketing, and design. After a decade
in Sydney, he currently works at Copenhagen Business School. He is also a visiting professor at The University
of Edinburgh Business School and a research fellow at the Vienna University of Economics and Business.
With an eclectic bookshelf behind him, his eyes are firmly focused on organizing practices that constrain,
enable, and sometimes subvert the organizational imagination of practitioners and scholars.
at Copenhagen Business School on May 18, 2016soq.sagepub.comDownloaded from
