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Starting from the several conceptual and empirical studies about open innovation modes, this paper attempts to integrate them by suggesting a framework which reveals four basic ways to collaborate. Two variables are considered that represent the degree of openness for a company: (i) the number/type of partners with which the company collaborates, briefly labelled as "partner variety"; (ii) the number/type of phases of the innovation process that the company opens to external contributions, briefly labelled as "innovation funnel openness". By crossing these two variables, four basic modes of open innovation are identified: closed innovators, open innovators, specialized collaborators and integrated collaborators. The framework shows its practical validity in an empirical study that is conducted in Italy with the specific aim at verifying whether companies can really be mapped using this framework, i.e. whether the four modes of open innovation can be found in real companies (framework applicability); whether different modes correspond to different companies' strategies, capabilities, organisational and managerial processes (framework explicative power and usefulness). The framework shows that, in some cases, being totally open in innovation activities is not the only and most suitable option, but that different degrees and ways of "openness" can be implemented successfully, as well as the totally closed option.
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November 21, 2009 16:42 WSPC/150-IJIM 00244
International Journal of Innovation Management
Vol. 13, No. 4 (Dec. 2009) pp. 615–636
© Imperial College Press
Università Carlo Cattaneo
Corso Matteotti 22, 21053 Castellanza (VA), Italy
Starting from the several conceptual and empirical studies about open innovation modes,
this paper attempts to integrate them by suggesting a framework which reveals four basic
ways to collaborate. Two variables are considered that represent the degree of openness for
a company: (i) the number/type of partners with which the company collaborates, briefly
labelled as “partner variety”; (ii) the number/type of phases of the innovation process that the
company opens to external contributions, briefly labelled as “innovation funnel openness”.
By crossing these two variables, four basic modes of open innovation are identified: closed
innovators,open innovators,specialized collaborators and integrated collaborators.The
framework shows its practical validity in an empirical study that is conducted in Italy
with the specific aim at verifying whether companies can really be mapped using this
framework, i.e. whether the four modes of open innovation can be found in real companies
(framework applicability); whether different modes correspond to different companies’
strategies, capabilities, organisational and managerial processes (framework explicative
power and usefulness). The framework shows that, in some cases, being totally open in
innovation activities is not the only and most suitable option, but that different degrees and
ways of “openness” can be implemented successfully, as well as the totally closed option.
Keywords: Open innovation; technological collaboration; partner variety; R&D process;
innovation funnel openness; modes of collaboration; innovation strategy; capabilities and
processes; multiple case study; Italy.
Corresponding author.
November 21, 2009 16:42 WSPC/150-IJIM 00244
616 V. Lazzarotti & R. Manzini
Open innovation may be pursued in many different ways, in terms of: (i) organi-
sational form of acquisition or exploitation and consequent time horizon; (ii) num-
ber of partners, from dyadic partnerships to networks, and typologies of partners,
from traditional supply chain relationships to collaboration with universities, techni-
cal service companies, competitors, firms operating in different industries (Chiesa
and Manzini, 1998); (iii) phases of the innovation process that exploit external
sources (Gassmann, 2006). The literature has already studied in depth the problem
of choosing the specific governance and organisation of open innovation processes,
analysing the relative organisational and managerial implications. In other words,
the literature has already characterised the different approaches to open innova-
tion in terms of level of integration, organisation and forms of governance (van de
Vrande et al., 2006).
This paper attempts to study and the implications of other variables — namely,
the number and attempts types of partners and the phases of the innovation process
which are “open” to external contributions — to significantly different approaches
to open innovation.
In the literature, many contributions have studied collaborations with specific
partners: universities, TSS, customers, suppliers, competitors, public governmental
institutions, private research centres (Chiesa et al., 2004; Hoegl and Wagner, 2005).
It seems that collaborating with different subjects gives rise to different problems
and advantages and requires specific organizational and managerial approaches.
Collaborating with a single partner, such as customers in NPD, would presumably
be quite easy. Accessing a wide set of external partners (e.g. customers, competitors,
universities), coordinating their contributions, organising the innovation process
around them and managing all the relationships is significantly different. In other
words, it can be argued that the number and type of partners with which a company
collaborates is something that determines the level of openness of the innovation
process of a company: the more partners the company has, the more “open” its
innovation process.
A second relevant observation concerns the number and type of phases in the
innovation process for which the company accesses external sources of technology
and know-how. Many authors have studied the specific advantages companies may
gain by opening their idea generation phase (Berger et al., 2005), the prototyping or
engineering phase, the production phase and the commercial phase (Emden et al.,
2006; Gassmann and Henkel, forthcoming). Again, it could be quite simple to open
a specific phase of the innovation process, while managing the whole innovation
funnel as an open funnel would probably more be complex. In any case, it can be
November 21, 2009 16:42 WSPC/150-IJIM 00244
Different Modes of Open Innovation 617
argued that the more phases of the innovation process in which the company accesses
external sources, the higher the level of openness of the innovation process.
Starting from the several conceptual and empirical studies that analyze and give
examples of different types of partners operating in different phases of the innovation
funnel this paper attempts to integrate them by suggesting a framework which reveals
four basic ways to collaborate. In fact, by crossing the two variables introduced
above, four degrees of openness are firstly identified to become the drivers of the four
basic ways to collaborate: low partner variety and few phases (closed innovators),
high partner variety and many phases (open innovators), high partner variety and
small phase variety (specialized innovators), and low partner variety and large phase
variety (integrated innovators). Secondly, the framework shows its practical validity
by means of an empirical study that is conducted in Italy with the specific aims at
Whether companies can really be mapped in this framework, i.e. whether the four
modes of collaboration can be found in real companies (framework applicability);
Whether different modes correspond to different companies’ features: strategies
as well as capabilities, assets, organisational and managerial processes (frame-
work explicative power and usefulness). This point is particularly important
in light of the literature that stresses the importance of the “right conditions”
(in terms of the company’s strategy, capabilities, organizational factors, etc.) to
successfully carry out any open approach for innovation (Pisano and Verganti,
2008). In other words it is important to pay attention to how firms can in real-
ity implement open innovation (Chesbrough et al., 2006). Following this sug-
gestion, we try to enrich the available evidence by identifying the strategic,
managerial and organizational contextual factors for some specific modes of
The result of the second aim of the empirical study is that the paper tries to give
also some normative indications of how to choose different collaboration modes.
Differences in strategies and companies’ capabilities, organizational and manage-
rial features can in fact lead to different kinds of open modes although compa-
nies are operating in the same industry, with analogous size (revenue, number of
The rest of the paper is organized as follows. First, it introduces the theoretical
framework of the variables entailing different modes of collaboration. This sec-
tion also points out the typical trade-offs of each mode. Second, it documents an
empirical study and discusses the specific conditions that make it easier to carry out
the different kinds of collaboration modes. Then, it draws the final conclusions by
summarizing the contribution of this study.
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618 V. Lazzarotti & R. Manzini
The Theoretical Framework
Since Chesbrough published his book in 2003, the concept of open innovation has
received a considerable amount of attention from practitioners and researchers. A
large number of studies are adopting this term to describe the phenomenon where
firms rely increasingly on external sources of innovation, which means that ideas,
resources and individuals flow in and out of organizations (Chesbrough, 2003).
While contributions are still growing, the debate on innovation management is
enriched by relevant studies that critically examine the open innovation concept
by exposing its weakness and limitations (Dahlander and Gann, 2007; Trott and
Hartmann, 2009). First of all, authors argue that the concept is not particularly
new and there has been a strong research tradition on the topic for decades, which
is evidence that innovation has always been open to some degree (Freeman, 1974;
Pavitt, 1984; von Hippel, 1986; Chandler, 1990; Tidd, 1993). Moreover, the concept
has been criticised for constructing an artificial dichotomy between closed and
open approaches (Dahlander and Gann, 2007), while the idea of exploring different
degrees and types of openness in a sort of continuum seems to provide a more
interesting and rich avenue for investigation. In particular, this view allows a deeper
and more realistic investigation of companies’ behaviour and of the particular nature
and context of sources of innovation (Gassmann, 2006; Dahlander and Gann, 2007).
The number of studies adopting this approach is growing: for example, Dahlander
and Gann identify three types of openness according to (1) the different degrees of
formal and informal protection, (2) the number of sources of external innovation,
(3) the degree to which firms are relying on informal and formal relationships with
other actors, while Lichtenthaler (2008) defines the degree of openness by crossing
two dimensions of a firm’s strategic approach to open innovation (i.e. the extent of
external technology acquisition and the extent of external technology exploitation).
Lichtenthaler identifies groups of firms that pursue homogeneous strategies and
then practically characterizes them in terms of variables such as R&D intensity,
emphasis on radical innovation, product diversification, etc.
In this paper, we follow this idea that openness needs to be placed on a continuum
and we try to explore its different degrees basically in terms of the number of sources
of external innovation.
On this topic, it has been recently suggested by literature that the degree of
openness in a collaboration network for innovation depends on the degree to which
membership is open to anyone who wants to join (Laursen and Salter, 2004; Pisano
and Verganti, 2008). In totally open collaboration (i.e. crowd sourcing), everyone
(suppliers, customers, universities, students, inventors, TSS, governmental institu-
tions, private research centres and even competitors) can participate. A company
makes a problem public and looks for support from an unlimited number of problem
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Different Modes of Open Innovation 619
solvers. Closed networks, in contrast, are like private clubs and tend to be smaller
than open ones (Pisano and Verganti, 2008). Here, the company shares the prob-
lem with few parties (usually, suppliers and customers) that it selects because it
believes they have the crucial capabilities and assets to provide innovative solu-
tions. Several conceptual and empirical studies hint at the importance of the outside
subject’s innovative capabilities as a major determinant of innovation success: tradi-
tionally, suppliers(Wynstra, 2001; Wagner, 2009) and customers (von Hippel, 1986;
Berger et al., 2005) and, more recently, an integration of different types of partners
in manifold relationships (Chesbrough et al., 2006). For example, some authors
(Gassmann and Henkel, forthcoming) provide a lot of empirical evidence of large
and well-known companies (e.g. IBM, BASF, BMW, etc.) that shows the existence
of different degrees of openness. Literature has also shed light on the advantages
and challenges characterizing the open versus closed approach as well as some basic
conditions that make it possible to adopt each approach. The big advantage of an
open network (i.e. high partner variety) is its potential to attract an extremely large
number of problem solvers and, consequently, a vast number of idea contributions
(Coombs and Hull, 1998; Gassmann and Henkel, forthcoming; Pisano and Ver-
ganti, 2008). Moreover, in extremely open approaches, it is not necessary to know
the potential contributors. Indeed, this fact could be particularly valuable: interest-
ing innovative solutions can come from people or organizations that the company
might never have imagined had something to contribute. However, open modes have
their disadvantages. First of all, the costs of screening and testing several solutions
could be very high. Rarely, in fact, is the screening process is cheap and fast (for
example, in the assessing the working of a software code). Usually, because expen-
sive and time-consuming experiments are necessary, it is better to consider fewer
ideas. This means choosing a closed mode by inviting those parties that company
thinks will have the best chance of providing good ideas. Besides, as the number
of participants increases, the likelihood that a participant’s solution will be selected
decreases. In such situations, transaction cost theory (Williamson, 1985) suggests
that the best potential partners can be discouraged from participating because they
do not want to make transaction-specific investments that cause resource-wasting,
if they are not sure of being selected. Thus, the best parties prefer to participate in
small relationships (i.e. closed modes), to be maintained in the long run (Pisano and
Verganti, 2008). In addition, repetitive cooperation builds familiarity between the
partnering firms, which in turn creates trust (Gulati, 1995). From a transaction cost
perspective, trust decreases the fear of opportunistic behaviour among the partner
firms, allowing the reduction of the spill-over risk. More generally, as the number
of selected partners increases, the need for coordination and control (of the above
behaviours and results) increases too, generating organizational costs and risks that
can become onerous (Mintzberg, 1983; Dahlander and Gann, 2007). In contrast,
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620 V. Lazzarotti & R. Manzini
fewer partners can be more easily coordinated and controlled and this is in favour
of more closed approaches. Such trade-offs suggest that extremely open modes can
be effective only under certain conditions: collaboration should concern problems
that can be partitioned into discrete parts that partners can work on autonomously
with low coordination needs (i.e. “high product modularity”, see Gassmann and
Henkel (forthcoming)). Over the last years, this has been made easier by informa-
tion technology that allows partners to make contributions, share work and observe
the solutions of others (Gassmann and von Zedtwitz, 2003; Dogson et al., 2006).
Of course, not all problems can be partitioned. Indeed, the research and develop-
ment related to new product concepts are usually integral tasks which require strong
integration and coordination among partners. In such cases, less open modes allow
coordination at a lower cost and thus they should be preferable (Pisano and Verganti,
Apart from the partner variety, relevant conceptual and empirical contributions
have focused on the so called “innovation funnel” (see Fig. 1). Openness is the
salient feature in this figure: in each phase, companies can potentially access exter-
nal sources of ideas, technology and know-how, or transfer them to the outside
environment (Chesbrough, 2003; van de Vrande et al., 2006) for different reasons:
gaining access to new areas of knowledge (also complementary knowledge), man-
aging capacity problems (more flexibility), concentration of core competencies,
Idea generation Experimentation Marketing and sales
= outside-in and inside-out
Fig. 1. The innovation process.
November 21, 2009 16:42 WSPC/150-IJIM 00244
Different Modes of Open Innovation 621
speed (reducing time-to-market) and sharing of risks and costs (Hour, 1992). There
is empirical evidence about companies that seek support in a specific phase of the
innovation funnel or that integrate partners into their entire innovation process in an
articulated network of relationships (Gassmann and Henkel, forthcoming). Thus, it
can be argued that the degree of openness for a collaboration network can be further
specified depending on the number and type of phases of the innovation process
for which the company accesses (or transfers) third sources. Openness in collab-
oration increases moving from external sources in a few phases of the innovation
funnel to their contributions to the overall innovation process. In other words, in a
less open or closed network, a company chooses one or a few phases (for example,
idea generation in the early stage of its innovation process) in which it looks for
interesting opportunities for collaborating, while in a totally open conception all the
phases are involved. Following the largely accepted suggestion by organizational
theories (Mintzberg, 1983), it can be assumed that as the number of phases involved
in collaboration increases, the level of complexity increases too, generating trans-
action costs in a similar way with respect to the partner variety. Therefore, it can
be argued that analogous trade-offs characterize open versus closed approaches: on
the one hand, managing the whole innovation funnel as an open funnel can pro-
vide advantages (in terms of creativity, access to new areas of knowledge, etc.).
On the other hand, some disadvantages in terms of coordination and control costs,
spill-over risks, etc. can become prevalent.
Recently, some of the studies emphasise the importance of investigating how
firms can in reality implement open innovation (Chesbrough et al., 2006; Dahlander
and Gann, 2007; Pisano and Verganti, 2008; Raasch et al., 2008; Bilgram et al.,
2008), stressing the importance of the “right conditions” (in terms of company’s
strategy, capabilities, organizational factors, managerial tools, etc.) to implement
any open approach successfully. For instance, Sakkab (2002) describes the dif-
ferent types of networks and the strategic planning process which characterizes
Procter & Gamble’s open innovation approach (Connect & Develop); another con-
tribution (Kirschbaum, 2005) describes how the multinational company DSM has
built teamwork and an appropriate culture for opening its innovation process; other
authors (Gassmann and Henkel, forthcoming; Christensen et al., 2005) identify the
characteristics (companies’ capabilities, characteristics of product, technology and
industry) to follow an open or closed innovation approach. Effectively managing
externally acquired technologies seems to also require the development of comple-
mentary internal networks (Hansen and Nohria, 2004), as it is largely recognized
that conducting internal research is a prerequisite for being perceived as an attractive
partner and for absorbing external knowledge (i.e. the concept of absorptive capac-
ity by Cohen and Levinthal (1990), more recently reviewed by Zahra and George,
(2002)). A relevant contribution by Chesbrough and Crowther (2006) highlights
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622 V. Lazzarotti & R. Manzini
the importance of specific organizational roles facilitating the implementation of
open innovation (i.e. the need of a champion) and the use of dedicated rewarding
systems as well as knowledge management systems (Chesbrough, 2003; Piller and
Walcher, 2006) that are able to support the diffusion, sharing and transfer of knowl-
edge within the firm and with the external environment. The relevant message from
the several cited authors is that “open innovation” is far more complicated than
“the more openness, the better” (Dahlander and Gann, 2008). It can be costly (with
respect to the benefits) and not always suited to the firm’s context.
In sum, the basic assumption in our study is that the two variables introduced
above (partner variety and phase variety) can represent the degree of openness of
collaboration networks for innovation. The literature has already in effect studied
these variables and it has pointed out different open (versus closed) approaches.
However, the attention is often focused on a single variable (for example, partner
variety with questions such as: “Is the involvement of suppliers important, or cus-
tomers, or both, or neither? What are the advantages and the challenges?”) or on
limited aspects of integration between the two variables (“Is it important to involve
customers in the idea generation?”). Moreover, the interest among scholars and
practitioners in the role of contextual factors (i.e. strategic, organisational and man-
agerial characteristics) that make possible different collaboration modes is growing
(Dahlander and Gann, 2008). First of all, we try to enrich this body of knowledge
by crossing the two variables in order to identify all the available options in terms of
degrees of openness. Consequently, four basic modes of collaboration are suggested
as synthesised in Fig. 2. The variables are defined as follows:
(1) The number/type of partners with which the company collaborates (labelled
“Partner variety”);
(2) The number/type of phases of the innovation process that the company opens
to external contributions (labelled “Innovation funnel openness”).
From a theoretical point of view, each area has significantly different characteristics:
The closed innovators model corresponds to companies that access external
sources of knowledge only for a specific, single phase of the innovation funnel
and typically in dyadic collaborations. This is the case, for example, in compa-
nies that access to external prototyping services in the new product development
The specialised collaborators model corresponds to companies that are able to
work with many different partners, but concentrate their collaborations at a single
point of the innovation funnel. This is the case, for example, of companies that
involve a wide set of actors (customers, experts, suppliers, research centres) in
the idea generation phase of the innovation process;
November 21, 2009 16:42 WSPC/150-IJIM 00244
Different Modes of Open Innovation 623
Partner variety
Innovation funnel openness
Fig. 2. The four modes of open innovation.
The integrated collaborators model corresponds to companies that open their
whole innovation funnel, but only to contributions coming from a few types of
partners (typically, suppliers and/or customers);
The open innovation model corresponds to companies that are really able to
manage a wide set of technological relationships, that impact the whole innovation
funnel and involves a wide set of different partners.
These are options that seem to be available from a theoretical point of view. There-
fore, our second attempt concerns the validation of the framework: it is necessary
to identify real companies for each suggested open approach (framework appli-
cability); each approach must then be contextualized by recognizing those factors
and features (strategies, characteristics of products, organizational and managerial
capabilities and assets) that lead to a particular approach or that make it suitable.
In the next section the empirical study will be described and its results will be
The Empirical Study
The empirical study started with a large set of interviews, with 52 Italian companies
involved, operating in different sectors of activities and including small, medium
and big companies, as shown in Table 1.
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624 V. Lazzarotti & R. Manzini
Table 1. Companies interviewed.
Company Sector of activity Size
Alenia Aermacchi Aerospace Big
Area3 Engineering R&D services Small
Explora Italia S.r.l. Chemical Small
BMP Bertelli Materie Plastiche S.p.A. Rubber and plastics Medium
CPC S.r.l. Textile Small
Rancilio S.p.A. Mechanical Medium
Ineos Rubber and plastics Medium
Nikem Research R&D services Medium
Condor’s Rubber Rubber and plastics Medium
Dipharma Francis S.r.l. Pharmaceutical Big
Blue Moon Electronic machineries Small
Ecofuel Chemical Medium
Kemira Chimica S.p.A. Chemical Medium
ICAP Leatherchem S.p.A. Chemical Big
National Starch S.p.A. Chemical Medium
Silvay-Solexis S.p.A. Chemical Big
Blue Star Silicones Rubber and plastics Small
Slimpa S.p.A. Mechanical Medium
Agusta (Westland) S.p.A. Mechanical Big
Afros S.p.A. Mechanical Medium
Gimac Mechanical Small
Rima Mechanical Small
MV Agusta Motor S.p.A. Mechanical Big
Cobra Automotive Technologies S.p.A. Electronic Big
Redco Telematica S.p.A. Electronic machineries Small
Digicom Electronics Medium
Mitric R&D services Small
Pietro Carnaghi Chemical Big
Vamag Electronic machineries Small
Munksjo Paper Paper Medium
Alfredo Grassi Textile Medium
Tintoria Finissaggio Ticino Textile Small
Vibram Rubber and plastics Big
Secondo Mona S.p.A. Mechanical Medium
Lodetex S.p.A. Textile Small
Mario Cavelli S.p.A. Textile Medium
Mario Crosta S.p.A. Mechanical Medium
Mobert S.r.l. Mechanical Small
Near Chimica Chemical Small
Diffuplast Rubber and plastics Small
Tema R&D services Small
November 21, 2009 16:42 WSPC/150-IJIM 00244
Different Modes of Open Innovation 625
Tab l e 1 . (Continued)
Company Sector of activity Size
Missoni Textile Medium
Ultrabatch S.r.l. Rubber and plastics Small
Scatolificio Da.Ra. Paper Small
Trigo R&D services Small
Vibiplast Rubber and plastics Small
A.D.E.A. R&D services Small
Rossi di Albizzate R&D services Small
Junior S.r.l. Textile Medium
Fratelli Rossetti Textile Big
BTSR International S.p.A Mechanical Medium
Bticino S.p.A. Electronic machineries Big
For each company, depending on the specific size and organization, the CEO and/or
the R&D manager were interviewed. Questions in these interviews concerned:
The company’s corporate and business strategy;
The characteristics of the company’s innovation process;
The R&D organisation and management;
The attitude with respect to technological collaborations and innovation networks
in terms of relevance to the innovation strategy, objectives and perceived risks,
most relevant partners, success and failure factors.
These interviews allowed us to form a general picture about whether and how
companies actually rely on external sources of knowledge and technology for their
innovation process. As expected, they demonstrated that companies adopt many
different ways to open their innovation process, not only in terms of partners involved
and phases opened, but also in terms of organisational and managerial approaches
adopted to open such processes. Some of them consider technological collaborations
as a strategic opportunity and dedicate time and resources to exploiting such an
opportunity; others believe that opening the innovation process is risky, and clearly
limit the aim and scope of their collaboration, defining tight rules and control; others,
again, avoid resources and time consumption, keeping their innovation process
completely closed. The “variety” observed in the way companies adopt to open
their innovation process was then classified according to the theoretical framework
laid out in the previous section, distinguishing open innovators, closed innovators,
specialised collaborators and integrated collaborators. This allowed us to verify the
November 21, 2009 16:42 WSPC/150-IJIM 00244
626 V. Lazzarotti & R. Manzini
Table 2. Companies mapped according to the theoretical framework.
Open Closed Specialised Integrated
innovators innovators collaborators collaborators
Number of
companies (as
percentage of
total companies
43% 41% 9% 7%
Size 25% big; 40%
medium; 35%
26% big; 21%
medium; 53%
0% big; 50%
medium; 50%
0% big; 67%
medium; 33%
Sectors of
All those
included in the
All those
included in the
Paper; rubber
and plastics;
R&D services;
applicability of the model, and also have a first rough picture of the diffusion of
each different model. The result of this process is synthesised in Table 2.
Table 2 clearly shows that:
The two “extreme” models (open and closed) are far more diffused then interme-
diate ones (specialised and integrated collaborators), but all models are actually
It does not seem that the sector of activity and the company’s size are main
drivers in determining the open innovation model adopted: for each of the four
models, we cannot identify a prevalent size or sector of activity. Thus, the degree
of openness seems to be determined mainly by the individual strategic choice of a
company, although this finding must be considered with caution due to the limited
sample size. Moreover, an analysis of prior, more extensive research suggests the
existence of industry and size differences regarding the degree of open innovation
(Pavitt, 1984; Chesbrough and Crowther, 2006; Lichtenthaler, 2008).
The various forms and levels of “openness” observed suggested that a more in-depth
analysis was necessary to fully understand the strategic, managerial and organisa-
tional choices of companies and that a multiple case study was the most suitable
research method to achieve this objective. This study was then designed by taking
as guidelines all the results achieved by means of the interviews. Twelve cases were
selected, according to the literal and theoretical replication criterion (Yin, 2003),
with three companies for each different open innovation model: companies from
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Different Modes of Open Innovation 627
different industries and of different sizes, but adopting the same open innovation
model (literal replication); companies from the same industry and of similar size, but
adopting different open innovation models (theoretical replication). Among others,
these companies were also selected because data and information were available
with a high level of reliability, transparency and detail. All companies selected con-
sidered their open innovation approach successful (meaning that the major part of
their partnerships are able to reach the defined objectives). A short profile of the
twelve companies selected for the multiple case study is given in Table 3.
Table 3. Companies involved in the multiple case study.
Company Open innovation Sector of Size Critical Success R&D
model activity Factors organisation
Open inn. Aerospace Big Technological
excellence; time to
market; brand,
business portfolio
Rancilio Open inn. Mechanics Medium Quality, service
level, technological
Input oriented
Open inn. R&D services Small Price, time to
No formal org.
Vibram Closed inn. Rubber &
Big Quality, service
level, brand
Input oriented
Digicom Closed inn. Electronics Medium Price, quality, time
to market,
Lodetex Closed inn. Textile Small Quality, time,
service level,
excellence, brand,
Input oriented
BMP Specialised
Plastics Medium Time to market,
service level,
business portfolio
Input oriented
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628 V. Lazzarotti & R. Manzini
Tab l e 3 . (Continued)
Company Open innovation Sector of Size Critical Success R&D
model activity Factors organisation
Cavelli Specialised
Textile Medium Quality, time,
service level,
Input oriented
Blue Moon Specialised
Small Technological
excellence, brand
Input oriented
Nearchimica Integrated
Chemical Small Time to market,
quality, business
Input oriented
Crosta Integrated
Mechanics Medium Quality, time,
service level,
Input oriented
Tema Integrated
Electronics Small Quality,
The case study allowed us to analyse more in depth:
The innovation process of companies, in terms of typical activities and actors
involved, phases/steps in the R&D activity, costs, technical and commercial risks,
The roles and organisation used by companies to support the open innovation
model adopted;
The process through which companies organise and manage their innovation
networks, i.e. (i) the definition of objectives and risks of activities “open” to
external partners; (ii) the selection and analysis of partners; (iii) the identification
of the organisational and contractual form for the partnerships; (iv) the planning
of network activities: time, technological and financial resources, competencies
and other intangible assets.
A research protocol was used in the study, consisting of a questionnaire with open
and closed questions and in a list of data and documents to be collected (such as, for
November 21, 2009 16:42 WSPC/150-IJIM 00244
Different Modes of Open Innovation 629
example, economic and financial exhibits, R&D indicators of performance, organ-
isational charts). This ensured homogeneous and coherent data and allowed cross
case analysis, a necessary technique for pointing out differences and/or similarities
among companies adopting the same open innovation models and between different
clusters of companies, adopting different models. The results of this analysis are
here briefly synthesised.
Open innovators
Open innovators are characterised by a high tension towards technological leader-
ship and internationalisation of activities, even R&D; technology and innovation
represent critical success factors and require excellent and diversified competen-
cies; R&D and innovation activities have a very high level of risk, both technical
and commercial and the level of R&D spending is quite high (as a percentage of
sales). In particular, this high internal R&D intensity has to be emphasized because
it supports the literature’s suggestion that firms find open innovation to be comple-
mentary with internal R&D, instead of being a substitute (Cohen and Levinthal,
1990; Zahra and George, 2002). Prior research suggests also that a high level of
R&D spending is required by the pursuit of a technological leadership (Freeman,
1982; Trott and Hartmann, 2009) and this seems the case of our “open innovator”
profile. On the other hand, the emphasis on radical rather than incremental innova-
tion further increases the relevance of external sources of technology. This finding
is also consistent with suggestions from previous literature (Lettl et al., 2006; Lich-
tenthaler, 2008): when developing radical innovations, firms may rely on a higher
degree of external technology acquisition because they are not able to internally
develop all the necessary knowledge. In addition, the high level of internationalisa-
tion seems to be a driver in favour of a high degree of openness, though findings on
the topic in the literature are controversial (Lichtenthaler, 2008). Nonetheless, this
open innovator said that opening the innovation process was perceived as a critical
opportunity, to be exploited for a broad set of objectives, including: sharing risks
with others, integrating and complementing arising competencies, increasing cre-
ativity, reducing time to market. The managerial style is highly participative, since
the functions of many different companies are involved in the innovation process
activities and decisions (R&D, marketing, manufacturing, after sales). The under-
lying idea is that high involvement makes for higher efficiency and effectiveness in
the innovation process. At the same time, it is perceived as a risk and the complexity
arising from several relationships to be managed (Mintzberg, 1983; Laursen and
Salter, 2004; Dahlander and Gann, 2007) could negatively affect the innovation
performance (Laursen and Salter, 2006). As a consequence, open innovators put in
place a rather sophisticated organisation and process for supporting technological
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630 V. Lazzarotti & R. Manzini
collaborations and partnerships, i.e. organising for open innovation (Hansen and
Nohria, 2004; Chesbrough and Crowther, 2006). This allows them to manage and
control innovation networks as a whole, from the definition of objectives and risks,
through partners analysis and selection, to the definition of each organisation’s spe-
cific role and contractual form of collaboration, the detailed planning of activities
and the measurement of actual results. Obviously, designing and implementing such
a complex organisational process requires advanced managerial competencies. As
a matter of fact, open innovators have proved to be experts at using sophisticated
techniques for the technical and economic-financial analysis of all activities and
decisions concerning innovation and technological collaborations (Dodgson et al.,
Specialised collaborators
These firms are very similar to the open innovators depicted above. They are char-
acterised by a similar drive towards technological excellence, implying high R&D
intensity (Freeman, 1982; Trott and Hartmann, 2009), but with a lower level of
internationalisation. R&D risk is medium-high and very often the commercial risk
is higher than the technical risk; together with technological excellence, other fac-
tors are strategic, such as the service and quality level and the variety of products.
This strategy, which is more defensive and focuses on incremental rather than rad-
ical innovations, still requires high R&D intensity (Trott and Hartmann, 2009) but
a lower degree of openness (Lichtenthaler, 2008). Open innovation is perceived
as an interesting opportunity that, on the other hand, entails significant risks and
requires too many resources (time, people, money). As a consequence, specialised
collaborators define specific roles and organisational mechanisms to support their
technological partnerships, but tend to limit relationships to a few phases of the
innovation process in order to limit their impact on the company’s resources and
activities. Technological collaborations are mainly aimed at integrating and comple-
menting competencies and concern only R&D phases in which those competencies
are actually lacking. High managerial competencies are necessary to support this
open innovation model, and, as in the case of open innovators, companies often use
sophisticated decision supporting tools and techniques.
Integrated collaborators
In this open innovation model, technological excellence is only one of the relevant
success factors, together with time, quality, service level, brand, and cost-cutting.
As a consequence, technological leadership is not the main purpose of these compa-
nies as they focus on incremental innovations. Even internationalisation is not a top
November 21, 2009 16:42 WSPC/150-IJIM 00244
Different Modes of Open Innovation 631
priority and mainly concerns commercialisation activities. R&D risk is medium-
low, particularly commercial risk. Managerial competencies are not very high, and
only in some cases are technical, economic and financial analyses are used to sup-
port decision-making concerning innovations and technological collaborations. In
accordance with these characteristics, integrated collaborators open their innova-
tion process in a very selective way, traditionally involving mainly suppliers and
customers and only in a few cases other types of partners. This choice allows them
to avoid the creation of a specific “organisation for open innovation”, since contacts
with suppliers and customers are usually already established and based on trust, and
are then exploited for R&D and the whole innovation process.
Closed innovators
These companies have decided to invest in their internal R&D effort and believe
that keeping the innovation process closed allows them to avoid significant costs
and risks. In other words, they perceive the openness and the relationships to be too
difficult and costly compared to the potential benefits (Laursen and Salter, 2006).
The idea is that all the resources (people, money, competencies) and managerial
ability should be focused internally to develop innovation. Therefore, these firms
develop most technologies in-house. Technological leadership is expected to be
mainly the result of an internal effort instead of being the result of an innovation
network. The R&D risk is not too high and there is little need to share it with other
parties. It can be managed by the company itself, by using sophisticated managerial
tools and techniques. Consequently, technological collaborations are episodic and
involve few partners with which long-term relationships are established, allowing
limited transaction costs and limited risk of spill-over.
The present study has analysed whether different models are used by companies
to open their innovation process. The framework, hypothesised in accordance with
existing literature, enriches it by identifying four specific different models of open
innovation that depend on the number and type of partners involved and on the num-
ber and type of phases opened to external contributions: open innovators, specialised
collaborators, integrated collaborators and closed innovators. The empirical study
has confirmed that these four models exist in practice (i.e. are actually adopted by
companies) and outlined them in terms of different levels of complexity and strate-
gic, organisational and managerial characteristics. Different levels of complexity
for the four models are depicted in Fig. 3.
Closed innovators avoid a great commitment, which means human, financial
and technological resources as well as time, but on the other hand, cannot share
November 21, 2009 16:42 WSPC/150-IJIM 00244
632 V. Lazzarotti & R. Manzini
Closed innovators
Integrated collaborators
Specialised collaborators
Open innovators
Organisational and
complexity and
transaction costs
Creativity and
opportunity to
share risk
Level of managerial
competencies required
Risk of spill over
Fig. 3. Different modes of open innovation and their implications.
risks with others and limit their technological opportunities to those achievable by
means of internal efforts. Open innovators maximise the exploitation of external
technological opportunities, but to this end dedicate large amounts of resources and
time to build the necessary organisation and processes. Specialised collaborators and
integrated collaborators represent intermediate models that allow them to exploit
some of the opportunities that can be captured externally, but limiting at the same
time the resources dedicated.
Two models — open and closed innovators — are most diffused among the
companies investigated, even if they probably represent “extreme” solutions with
“extreme” advantages and limits. The two “intermediate” models may offer several
advantages while reducing the disadvantages.
From this point of view, some normative indication can be drawn from the case
study, linking different open innovation models to the strategic, organisational and
managerial characteristics of different companies, as well as to different degrees
of benefits and costs (see Table 4). The table provides a synthesis of the elements
that drive choice among the described approaches. The relevant message is that that
no mode is better than the others. In particular, according to Dahlander and Gann
(2007), it is not true that “the more openness, the better”. It can be costly and it is
not always easy to have a high degree of openness. Indeed, the approach chosen by
companies should depend on its coherence with the strategic, organizational and
managerial contexts and on an acceptable balance between the benefits and costs.
By adopting this reasoning, the “intermediate” approaches also appear as interesting
options in the light of a reasonable compromise in terms of benefits and costs.
November 21, 2009 16:42 WSPC/150-IJIM 00244
Different Modes of Open Innovation 633
Table 4. Modes of open innovation and the relative context.
Open Main Level of Technical Commercial Creativity and Innovation Organizational Risk of spill- Level of Managerial
innovation critical internationalisation risk risk risk sharing emphasis and over managerial style
model success managerial competence
factors complexity and
innovator s
High High High High Radical High High High Highly
service, time +
Medium-high Medium-high Medium-high Medium-high Incremental Medium-high Medium-high High Participative
Quality, service,
time, brand +
Medium-low Medium-low Medium-low Medium-low Incremental Medium-low Medium-low Medium Mainly
innovator s
Quality, service,
time, brand,
excellence +
Medium-low Medium-low Medium-low Medium-low Incremental Medium-low Medium-low Medium-high Mainly
November 21, 2009 16:42 WSPC/150-IJIM 00244
634 V. Lazzarotti & R. Manzini
However, the above conclusions are drawn from a limited set of companies.
A further step in research could be by taking some of the relationships pointed
out here and verifying them in an extensive study, for example through a cluster
analysis that can validate the suggested framework in terms of its applicability and
the identification of differences in complexity and contextual factors among open
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... (Chesbrough, 2006;Mbieke, 2020;Melese et al., 2009) 32. External actors (Ardito et al., 2020;Lazzarotti & Manzini, 2009;Marcolin et al., 2017) Internal factors (organizational) 33. Exchange of knowledge (Alves Aranha et al., 2015;Dahlander & Gann, 2010;Gong et al., 2022;Shi et al., 2021) 34. ...
... Allen T. & Dominique P., 2013;Chesbrough & Appleyard, 2007;Howells, 2012;Lazzarotti & Manzini, 2009;Rostoka et al., 2019 Rostoka et al., ) et al., 2020Lazzarotti & Manzini, 2009;Rostoka et al., 2019;Shi et al., 2021) 28. Mechanisms and tools(Cervantes M. & Meissner D., 2014;Gassmann et al., 2010;Jonsson et al., 2015;Mbieke, 2020) ...
... Allen T. & Dominique P., 2013;Chesbrough & Appleyard, 2007;Howells, 2012;Lazzarotti & Manzini, 2009;Rostoka et al., 2019 Rostoka et al., ) et al., 2020Lazzarotti & Manzini, 2009;Rostoka et al., 2019;Shi et al., 2021) 28. Mechanisms and tools(Cervantes M. & Meissner D., 2014;Gassmann et al., 2010;Jonsson et al., 2015;Mbieke, 2020) ...
... Year of publication Definition given Chesbrough 2003 purposive inflows and outflows of knowledge to accelerate internal innovation, and expand the markets for external use of innovation Lazzarotti and Manzini 2009 A collaboration with a high variety of partners and a high count of partners Dahlander and Gann 2010 Outbound innovationnon-pecuniary, how internal Outbound innovationpecuniary, firms commercialize their inventions and technologies through selling or licensing out resources developed in other organizations Inbound innovation -non-pecuniary, firms use external sources of innovation Inbound innovationpecuniary, firms license in and acquire expertise from outside Banu, Dumitrescu, Purcărea and Isărescu 2016 ...
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Article info This article presents the open innovations status in human resource management practices within the Tanzania public service. The study focuses on open innovations in the Government of the United Republic of Tanzania, particularly from 1999. This was the period when the new policy on public service management and employment was crafted and adopted by the Government. The document review was conducted to identify open innovations that were anticipated and implemented within the public service. The results show that open innovation is constrained by the presence of uniform, less coordinated policies (and legislation) and inadequate pecuniary and non-pecuniary incentives to innovate. It is concluded that public sector institutions in Tanzania have to work together (non-symbiotic) to allow open innovations to take place within the public service. It is also recommended that public servants must be ready and flexible to utilize ideas and knowledge from outside that are relevant to their institutions. Similarly, public institutions should transmit their unused ideas and knowledge to other public institutions for use to improve the performance of their respective institutions. We recommend other researchers venture into researching open innovation in the context of digital governance transformation in the public service in Tanzania and or how open innovation may enhance co-design and co-delivery in the context of decentralization in Tanzania, specifically, the use of improved Opportunities and Obstacles to Development (OOD) tool.
... 5.4.1 Creative climate (CC). It can be argued that creativity can arise through interactions (Hargadon and Bechky, 2006;Matzler et al., 2015), and OI can improve creativity (Lazzarotti and Manzini, 2009;Matzler et al., 2015). G€ oran Ekvall described CC as "an attribute of the organization, a conglomerate of attitudes, feelings, and behaviors which characterize the organizational life" (Ekvall, 1996). ...
Purpose This study aims to examine and discuss the importance and benefits of Open Innovation (OI), Transformational Leadership (TL), Innovation Strategy (IS), Creative Climate (CC), Radical Innovation (RI) and Sustainable Competitive Advantage (SCA) for small and medium-sized enterprises (SMEs) in Dubai. This work also examines the mediating impact of future foresight drivers (FFD) on SMEs' SCA. The study provides a theoretical framework for enhancing SMEs' organizational performance and highlights the need for future empirical research. Design/methodology/approach The study uses a systematic literature review (SLR) approach and a bibliometric analysis approach to collect, examine and analyze data from previous research on OI, TL, IS, CC, RI and SCA. This work evaluated 110 publications from separate scholarly databases, Scopus and Web of Science (WoS). Findings The study finds a positive relationship between OI, TL, IS, CC, RI and SCA and that future empirical research is needed. While there is limited information on the impact of these concepts on SMEs in the Middle East and especially in Dubai, the study presents new concepts to be debated. The study provides a vital tool for businesses to improve their performance by adopting OI, TL and IS and analyzing their present competitive status to develop new strategies and build competitiveness. Originality/value The originality of this study lies in its contribution to understanding the relationships among OI, TL, IS, CC and RI and their impact on SMEs' SCA in Dubai. By emphasizing the importance of OI, TL and IS in improving SMEs' performance and competitiveness, this study provides valuable insights for SME managers seeking to enhance their organizations' sustainability and long-term success. The review also identifies a gap in the literature regarding the impact of these concepts on SMEs in the Middle East, emphasizing the need for further research in this area.
... The artificial intelligence-human sequential decision-making model is of particular interest to entrepreneurial firms as it can be used to optimize open innovation strategies for sourcing and selecting innovation ideas. This approach is advantageous as it shifts the "cost of problem-solving from generating solutions to evaluating and selecting solutions" [26]. It is important to consider the requirements of the artificial intelligence technologies' application to build the decision-making models on the directions and benchmark parameters of the organization's development [27]. ...
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Organizations see open innovation as important to their future growth strategy. The increasing interest in artificial intelligence has led to a heightened interest in its potential applications in many industries. Many firms invest heavily in artificial intelligence intending to innovate their business models, though managers often lack understanding when trying to implement artificial intelligence in their operations. The data was retrieved from the Scopus database and was analyzed using the R Bibliometrix Biblioshiny and VOSviewer software. The aim of the article is to indicate the consistency in the formation of open innovation processes while applying artificial intelligence and to provide the profile of perspectives on artificial intelligence adoption in innovation management. This paper provides a deeper perception of artificial intelligence and how it can be used to drive open innovation processes and business model innovation within the use of artificial intelligence in open innovation processes and artificial intelligence in the management of open innovation. The authors discuss how recent advances in artificial intelligence have created new opportunities for increased external collaboration. The study found that the rise of artificial intelligence as a key technology for promoting openness and collaboration has ushered in a new era of achievable open innovation. Our presented findings suggest the sequence of open innovation processes powered by artificial intelligence and insights into the artificial intelligence application to innovation management.
... Radical innovation thrives on diverse and new knowledge and needs a fruitful space for creative activities and paths to unconventional solutions and contexts (Lettl et al., 2006), but a highly routinised use of SM "limit[s] the user to a filter bubble that reinforces conformity rather than disruption" (Barker, 2018, p. 87). Radical innovation demands diverse opinions and competencies and is hindered by enforced accordance (Lazzarotti and Manzini, 2009). Hence, the more routinely SM is used, the more vulnerable an organisation becomes to algorithms and filter bubbles, which will weaken the positive link between the use of SM for NPD and radical innovation. ...
... Laursen and Salter (2006) propose a definition of openness based on the breadth (i.e., number of external sources used) and depth (i.e., how intensively the firm draws on each source) of external relations. Similarly, Lazzarotti and Manzini (2009) combine two dimensions of openness, namely, the number and type of partners, and the number and type of phases of the innovation process opened to external collaborations. However, recent evidence also shows that a more closed approach to product and process innovation is sometimes suited, and especially when the company relies on strong internal competencies and know-how that can hardly be protected through formal intellectual property protection mechanisms (Manzini et al., 2017). ...
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To keep up with rapid technological change, firms are pushed to acquire new competencies and resources, often leveraging the external networks in which they are involved. The paper examines how firms' engagement in inbound open innovation (OI) enables the adoption of Industry 4.0 (I4.0) technologies in small and medium‐sized enterprises (SMEs) through the deployment of technological capabilities. We combine the OI and dynamic capabilities frameworks to assess how the absorption of knowledge from different actors impacts the necessary technological capabilities for adopting I4.0 technologies. The capabilities are categorized in technological sensing, seizing and reconfiguring. The study is based on in‐depth case studies of two selected SMEs from the footwear industry. The cases show that engaging in external collaborations, particularly with universities, pushes SMEs to renew the bundle of competencies underlying their technological capabilities. However, this effect is influenced by the OI modalities adopted by both companies. While in Company A OI takes place through a broader array of formal and informal linkages that contribute to the exploration of distant knowledge bases and the experimentation of more diverse technologies, such as the Internet of Things, Company B relies on informal networking concentrated in its own field of specialization for the adoption of manufacturing‐specific I4.0 solutions, such as automated robots and 3D printing.
Open Innovation and Sustainability‐Oriented Innovation are undoubtedly two of the most debated topics of the last decades, gaining the interest of policymakers, practitioners, and scholars all over the world. Even if they have been usually described as two independent research fields, there are some emblematic examples presenting interplay and synergy between these topics, represented either by the hybrid perspectives of Open Sustainable Innovation , that is, the Open Innovation approach acting as an enabler of Sustainability‐Oriented Innovation, and Sustainable Open Innovation , which instead analyzes how firms developing Sustainability‐Oriented Innovation also adopt the Open Innovation approach. On the basis of these two perspectives and through a systematic literature review, this paper investigates the relationships between the Open Innovation and Sustainability‐Oriented Innovation approaches and frames these relationships by developing an innovative framework, which highlights the main aspects characterizing the hybrid perspectives of Open Sustainable Innovation and Sustainable Open Innovation . The proposed framework highlights the Open Innovation practices and strategies enabling Sustainability‐Oriented Innovation, as well as the contextual factors enabling both practices and strategies for Sustainability‐Oriented Innovation. In addition, it shows how firms developing Sustainability‐Oriented Innovation have a similar orientation toward the adoption of the Open Innovation approach both in terms of how they engage stakeholders, and the innovation capabilities they develop. Finally, a research agenda identifying the central issues and the key research gaps is offered for further development in future studies.
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Open access at Balancing value creation and value capture is a fundamental strategic issue for the management of open innovation. Insufficient compensation for created value may hinder the participation of a firm or individual in open innovation. It can thus provide an obstacle to the open innovation process as a whole. Hackathons provide an attractive setting for studying value appropriation in open innovation by actors of different types and with varying bargaining power. We define hackathons as idea competitions on specific topics in the form of a time-limited event. These competitions have gained more popularity throughout the years and have recently become more prominent. Therefore, an abductive empirical study was carried out in an international set-up with multiple embedded cases of hackathons. Results indicate that hackathons offer coupled open innovation processes. The value captured by the initiator of a hackathon in the form of inbound open innovation is balanced by outbound knowledge flows towards participants as well as with sideways knowledge flows between participants, which are a result of the generation of collective intelligence. Collective intelligence is thus identified as an alternative mechanism for value capture from open innovation.
Nowadays, virtually no companies innovate alone. Firms team up with a variety of partners, in a wide number of ways, to create new technologies, products, and services. But what is the best way to leverage the power of outsiders? To help executives answer that question, Pisano, of Harvard Business School, and Verganti, of Politecnico di Milano, developed a simple framework focused on two questions: Given your strategy, how open or closed should your network of collaborators be? And who should decide which problems to tackle and which solutions to adopt? There are four basic modes of collaboration, say the authors. An elite circle is a closed network with a hierarchical governance: One company selects the participants, defines the problem, and chooses the solution. For instance, Alessi, an Italian home-products company, invited 200 outside experts in postmodern architecture to contribute ideas for new home-product designs. An innovation mall is hierarchical but open: Anyone can post a problem or propose solutions in it, but the company posting the problem chooses the solution. An example is, an eBay-like site where companies post scientific challenges. An innovation community is open and decentralized: Anyone can propose problems, offer solutions, and decide which ideas to use - as happens in the Linux open-source software community. A consortium is a private group of participants that operate as equals and jointly select problems, decide how to conduct work, and choose solutions. IBM has set up a number of consortia with other companies to develop nextgeneration semiconductor technologies. No one approach is superior; each involves strategic trade-offs. When choosing among modes, firms must weigh their advantages and challenges, and assess which will work best with their strategy, capabilities, structure, and assets.
This paper addresses how the Open Innovation concept, as recently coined by Henry Chesbrough, can be analyzed from an industrial dynamics perspective. The main proposition of the paper is that the specific modes in which different companies manage Open Innovation in regard to an emerging technology reflect their differential position within the innovation system in question, the nature and stage of maturity of the technological regime, and the particular value proposition pursued by companies. The proposition is analyzed through an in-depth study of the current transformation of sound amplification from linear solid state technology to switched or digital technology within the consumer electronics system of innovation. The analysis especially addresses the complex interplay between technology entrepreneurs and incumbents, and demonstrates that Open Innovation sometimes has to be conducted under conditions of high transaction costs.
A number of manufacturing companies are realizing the significance of innovation suppliers, making efforts to manage them in an effective manner. It is being observed that suppliers are getting increasingly involved in design and development activities for companies. Siemens Automation Systems is one of these companies that understands the distinction between 'productivity suppliers' and 'innovation suppliers', managing them differently. Companies can adopt a number of ways of promoting, encouraging, implementing, and rewarding innovation with their suppliers. BMW has set up its Virtual Innovation Agency, a Web portal to support the search and encouragement of innovation from suppliers. Companies also need to realize that suppliers' downstream customer adjustment has a significant impact on innovativeness, along with cost and speed of new product development projects.
Previous research on supplier involvement in product development projects has produced contradictory results, with some studies showing a positive relationship, others no relationship, and still others a negative relationship between supplier involvement and project performance. Drawing on data from 124 managers, project leaders, buyer members, and supplier members pertaining to 28 product development projects, the authors find that buyer-supplier collaboration positively relates to product quality, adherence to product cost targets, adherence to development budgets, and adherence to development schedules. Furthermore, their analyses show that communication frequency and intensity has a curvilinear (inverted U-shaped) relationship with project development budget and product cost.
Examines the historical record of the ascendancy of science-related technology in modern economies, and presents an economic theory of innovation based on that record and it implications for policy-makers. Part One reviews the growth of the chemical, synthetic materials, and electronics industries with particular emphasis on costs, patent rates, firm sizes, marketing efforts, timing decisions. These data support a general theory presented in Part Two concerning the importance of professionalized research and development (R&D) capabilities and market awareness. Empirical data and analysis, including the results of Project SAPPHO, are used to provide further support for the theory. Characteristics of successful innovating firms include R&D strength, marketing abilities, understanding of user needs, and management strength. Implications for optimal firm size and the consequences of and reactions to uncertainty are treated in the remainder of Part Two. Uncertainty is responsible for a continuum of six strategies that firms take to meet the need to innovate, and leads to private under-investment in R&D. Part Three takes up the role of government and national science and technology policies and considers the social effects of technological innovation in terms of business cycles and unemployment figures, using a framework based on Schumpeter and Kondratiev. (CAR)