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The positive aspects of open innovation projects are widely discussed in innovation management research and practice by means of case studies and best practices. However, enterprises, particularly small and medium-sized enterprises (SMEs) also face miscellaneous challenges in open innovation practice, leading to uncertainty and even renunciation of open innovation project participation. Thus, it is essential for SMEs to find the right balance between possible positive effects and negative consequences – the latter being the less studied “dark sides” of open innovation. However, appropriate methods of finding this balance are still lacking. In this article, we discuss the assessment of open innovation project participation by presenting a weighing and decision process framework as a conceivable solution approach. The framework includes an internal, external, and integrated analysis as well as a recommendation and decision phase. Piece by piece, we investigate the current situation and the innovation goals of the enterprise as an initial point for a decision for or against engaging in open innovation. Furthermore, we discuss the development of a software tool that automatically applies this framework and allows self-assessment by SMEs.
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Technology Innovation Management Review April 2016 (Volume 6, Issue 4)
34
www.timreview.ca
Weighing the Pros and Cons of
Engaging in Open Innovation
André Ullrich and Gergana Vladova
Introduction
The advantages of open innovation projects are widely
discussed in innovation management research and
practice (e.g., Man & Duysters, 2005). Particularly, small
and medium-sized enterprises (SMEs) are expected to
gain most from open innovation collaborations due to
their inherently limited capabilities (Lee et al., 2010;
van de Vrande 2009). However, these enterprises also
face manifold challenges in open innovation practice,
leading to uncertainty and even renunciation of open
innovation project participation. Thus, SMEs often deal
with the decision dilemma of having to cooperate with
external partners in order to improve their own innova-
tion capacity, regardless of their ability to cope with the
correlated risks. Although it is essential for SMEs to find
the right balance between positive effects and possible
negative consequences (i.e., the “dark sides” of open in-
novation, cf. Huizingh, 2011) of open innovation pro-
ject participation, appropriate methods of finding this
balance are still lacking.
The research project “Open Darkness” was initiated
with the goal of enabling SMEs to weigh the risks and be-
nefits of open innovation participation by developing: i)
a weighing and decision process framework and ii) a
software tool that automatically applies this framework
and allows self-assessment for SMEs. Both solutions aim
to structure and support the decision process regarding
potential engagement in open innovation projects. In
order to tackle these targeted outcomes, an interdiscip-
linary consortium facilitates a multi-perspective and an
integrated holistic research approach. Besides several
SMEs, which function as requirement authority and im-
plementer, the consortium consists of three German re-
search institutions: the Chair of Economic Law
(University of Paderborn), the Chair of Technology and
Innovation Management (University of Aachen), and
the Chair of Business Informatics (University of Pots-
dam).
Given the importance of strategic thinking and of tacit
knowledge in decision making, decision outsourcing
The positive aspects of open innovation projects are widely discussed in innovation man-
agement research and practice by means of case studies and best practices. However, enter-
prises, particularly small and medium-sized enterprises (SMEs) also face miscellaneous
challenges in open innovation practice, leading to uncertainty and even renunciation of
open innovation project participation. Thus, it is essential for SMEs to find the right bal-
ance between possible positive effects and negative consequences – the latter being the less
studied “dark sides” of open innovation. However, appropriate methods of finding this bal-
ance are still lacking. In this article, we discuss the assessment of open innovation project
participation by presenting a weighing and decision process framework as a conceivable
solution approach. The framework includes an internal, external, and integrated analysis as
well as a recommendation and decision phase. Piece by piece, we investigate the current
situation and the innovation goals of the enterprise as an initial point for a decision for or
against engaging in open innovation. Furthermore, we discuss the development of a soft-
ware tool that automatically applies this framework and allows self-assessment by SMEs.
A ship is safe in harbor, but that's not
what ships are for.
William Shedd (1820–1894)
Theologian
Technology Innovation Management Review April 2016 (Volume 6, Issue 4)
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Weighing the Pros and Cons of Engaging in Open Innovation
André Ullrich and Gergana Vladova
from a person to a software-based solution is inher-
ently erroneous. Accordingly, it is explicitly not inten-
ded within the software tool to automate and process
decisions, thereby removing human responsibility. It is
envisaged to reduce insecurity in decision making for
open innovation participation by providing a support
structure that identifies causalities and alternatives and
leads to the identification of action alternatives. Fur-
thermore, the use of the tool is beneficial not only for
the decision makers: given the fact that “innovation is a
team sport” and employees “must be prepared to
change their way of thinking” (Valkokari, 2015), it can
also provide a basis for deeper understanding regarding
the new aspects of the innovation process.
The goal of the present article is to discuss the assess-
ment of potential open innovation project participation
against the background of the impossibility to either
predict the future or to capture all necessary environ-
mental information as well as the serious need of SMEs
for aid in this matter. This discussion will be conducted
by explicating a weighing and decision process frame-
work as a conceivable solution approach.
The remainder of the article is organized as follows.
First, we emphasize the relevant theoretical aspects of
open innovation. Next, we describe the methodological
approach used within the study. Then, we describe the
solution approach. Finally, we provide conclusions.
The Bright and Dark Sides of Open Innovation
According to conventional understanding, the primary
success factors in innovative enterprises are their em-
ployees, R&D divisions, and fault-tolerant corporate
cultures. This kind of innovation refers to the closed in-
novation paradigm (Chesbrough, 2003). Due to an in-
creasing trend towards globalization, new market
participants, and simultaneously shorter product life-
cycles with correspondingly increasing R&D costs, the
closed innovation paradigm was superseded last cen-
tury (Gerybadze & Reger, 1999) by the theory of open in-
novation, which emphasizes the significantly higher
importance of external resources (Chesbrough, 2003).
Open innovation is “the use of purposive inflows and
outflows of knowledge to accelerate internal innova-
tion” (Chesbrough et al., 2006). Thus, open innovation
can be described as an interactive and collaborative in-
novation process with external partners (Veer et al.,
2013). The positive aspects of open innovation for
SMEs are widely discussed (Lee et al., 2010). Table 1 de-
picts some of the “bright sides” of open innovation
structured into organizational, knowledge manage-
ment, and legal aspects.
Comparatively, the so-called “dark sides” of open in-
novation processes – as shown in Table 2 – have thus
far been neglected. Notably, the legal aspects are typic-
ally not structured or placed under the umbrella of
open innovation research (Müller, 2013).
Evaluation in innovation management
Broad evaluation is a crucial challenge of innovation
management (cf. Adams et al., 2006), particularly for as-
sessing an enterprise’s situation and developing suit-
able improvement measures. Existing approaches focus
either on isolated aspects of innovation management,
such as idea evaluation, or they consider the innovation
process as an internal activity (Afuah, 2003). They can,
however, be adapted for open innovation processes.
Business modelling with a focus on knowledge-intens-
ive processes (such as innovation processes) provides
another path to analyze and evaluate the current situ-
ation in an enterprise. Although the open innovation lit-
erature describes innovation processes with specific
phases, in reality, SMEs innovation processes are often
Table 1. The bright sides of open innovation (Chesbrough et al., 2006; Lee et al., 2010; Veer et al., 2010)
Technology Innovation Management Review April 2016 (Volume 6, Issue 4)
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Weighing the Pros and Cons of Engaging in Open Innovation
André Ullrich and Gergana Vladova
unstructured. Thus, such an analysis is an essential
starting point for evaluating knowledge and informa-
tion flows, business processes and personnel interac-
tions (Gronau, 2012).
Research Approach
The openness of innovation processes is associated
with uncertainty regarding positive and negative con-
sequences of the project design. Thus, enterprises often
need methodical support within the decision process of
open innovation project participation. However, ac-
cording to our review of the literature, no approaches
exist for weighing the risks and benefits of open innova-
tion project participation.
The lack of a decision support framework for weighing
benefits and risks of open innovation participation
leads to the contributions’ underlying question:
In terms of the development of a self-assessment
software tool for SMEs to evenly capture, analyse, and
weigh chances and risks of open innovation projects –
how should a weighing and decision process framework
be designed?
Methodological approach within the study
To ensure theoretical and practical relevant aspects
within the weighing and decision process framework
and the software tool are not neglected, our research
design includes a combination of qualitative, quantitat-
ive, and software development methods:
1. A literature review on the following topics: phases
and evaluation of open innovation processes in
SMEs, internal and external knowledge interfaces,
conditions of participation, measures for participa-
tion and risk reduction, and positive and negative as-
pects of open innovation.
2. Modelling and analysis of existing open innovation
processes for 15 SMEs, on the basis of more than 35
interviews with decision makers and employees. The
main result of this second step, combined with the
first step (i.e., the literature review) is the identifica-
tion of open innovation process assessment indicat-
ors for SMEs including knowledge management,
organizational, and legal aspects.
3. Indicator evaluation, through a survey and interviews
with open innovation experts. Part of this step is the
establishment of a community of open innovation ex-
perts, which acts as a supervisory body and valida-
tion group.
Applying the results of these three theoretical steps, the
following conceptual tasks are addressed:
4. Development of a methodological procedure in the
form of a weighing and decision framework with the
aid of an evaluation catalogue, ratio systems, and im-
plementation procedure models for SMEs.
5. Implementation of the methodological procedure
within a self-assessment tool. This step includes a de-
termination of requirements based on the results of
the previous and the actual development of the tool
based on the scrum software development frame-
work. Scrum (Sutherland & Schwaber, 2013) is an
agile software development framework that is based
on rules that define five activities (sprint planning,
daily scrum, sprint review, sprint retrospective,
product backlog refinement), three artefacts
(product backlog, sprint backlog, product incre-
ment), and three roles (product owner, development
team, scrum master) (cf. Beedle & Schwaber, 2002).
Due to ongoing group discussion and reflection at
the end of each work phase, a continuous improve-
ment process ensures a positive effect on the technic-
al results.
Table 2. The dark sides of open innovation (Enkel et al., 2009; Müller, 2013; Veer et al., 2013)
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Weighing the Pros and Cons of Engaging in Open Innovation
André Ullrich and Gergana Vladova
Approaching a Solution
Besides the theoretical outcomes that result from the
first three steps of the methodology as a state-of-the-art
extension, the second main emphasis of the project lies
in the implications of the results on enterprise practice.
This second aspect is addressed by the development of
the software tool on the basis of the weighing and de-
cision process framework. Due to the wide heterogen-
eity of open innovation situations and innovation
processes, it would be foolhardy to assume that a soft-
ware tool (as a main outcome) could take the entrepren-
eurial decision and, thereby, simply solve the complex
decision problem of open innovation participation.
However, the special value of the tool is the possibility
to assist SME innovation managers by guiding them
through the self-assessment weighing and decision pro-
cess in the run-up of a potential new open innovation
project.
In the given situation, decision makers and innovation
managers are confronted with strategic and operative
challenges, such as:
• What are our (innovation) goals?
• To what extent are we willing to take risks?
• How structured is the current (open innovation) pro
-
cess?
• How open could and should the innovation process be?
• What specific risks exist regarding potential partners
and knowledge and information losses?
• What is the level of preparation required to avert these
risks?
• What kind of improvement can be expected from co
-
operation with external partners?
These and further questions are addressed by the
weighing and decision process framework. The process
can be structured in five steps, which are described and
exemplified below and in Figure 1.
As a starting point of the process, three different as-
pects are evaluated with the active involvement of the
enterprise:
1. Identification of innovation goal, degree of innova-
tion, risk propensity, and strengths and weaknesses
analysis (a general analysis aspect, irrespective of a
concrete open innovation project): Primary and sec-
ondary value chain activities constitute the frame-
work to identify enterprises’ specific open
innovation strengths and weaknesses (e.g., innova-
tion project experience, own innovation process
structure, resource allocation). Applying the software
tool, profile tables, and process analysis models will
be used for these queries. The innovation goal will be
divided into output, input, and process goals. The de-
gree of innovation will be assessed as incremental or
radical and according to corporations’ innovation in-
tensity. The risk propensity categories are: risk seek-
ing, risk averse, and risk neutral. These aspects will
be queried by closed direct or indirect questions.
2. Identification of benefits and risks as well as assess-
ment of their occurrence probability (analysis aspect
Figure 1. Analysis and decision process framework
Technology Innovation Management Review April 2016 (Volume 6, Issue 4)
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Weighing the Pros and Cons of Engaging in Open Innovation
André Ullrich and Gergana Vladova
with regard to a concrete open innovation project):
Specific risks and benefits of open innovation co-
operation will be prompted using a predefined cata-
logue. Additionally, their respective occurrence
probability will be estimated by indirect closed ques-
tions, for example, regarding past experiences with
project partners, criticality of knowledge and inform-
ation, and assessment of their actual situation and
existing protection measures.
Within phase 1 and 2, indirect questions will be used to
determine the enterprise’s ideal degree of openness. In
addition, enterprises will be enabled to specify their
open innovation goals and relate specific project bene-
fits directly to them.
3. Assignment of measures to benefits and risks (analysis
aspect with regard to a concrete open innovation pro-
ject): Analytical findings will be considered to identi-
fy potential need for and comparative advantages of
protection measures. They provide the basis for the
assignment of relevant measures. If each risk and
each benefit can be associated with corresponding
specific measures in order to either avoid or enable
them, then: i) already existing enabling or protection
measures within the enterprise will be discovered
and ii) missing measures and necessary investments
and efforts for their establishment will be revealed.
Based on the present innovation process structure,
potential partner profiles, knowledge and informa-
tion flows, and legal situations, the enterprise’ risk
position will be clarified.
Within the next steps, the enterprise-specific informa-
tion gained within the three analysis phases will be eval-
uated automatically by the software and with no need
for the active involvement of the enterprise.
4. Presentation of analysis results: Based on the evalu-
ation of the aforementioned steps, three major res-
ults will be depicted: i) the optimal degree of
openness (by the aid of a type classification proxim-
ity/formalization [Diener 2015]); ii) expectable efforts
for necessary, promising, and risk propensity de-
pendent measures to enable context-specific optimal
degrees of openness and innovation; and iii) depic-
tion of advantages and disadvantages of the open in-
novation corporation project under consideration.
5. Come to a decision: Condensed information will be
provided as a basis for the decision to be made.
To sum up, the analysis and decision process frame-
work fulfils three functions: i) provision of understand-
ing for the present situation and, within this, ii)
reduction of the perceived risk of open innovation pro-
ject participation, and iii) general recommendation for
action, which serves as decision support for the innova-
tion manager. Within the five steps, different informa-
tion is requested in order to deduce the enterprise
specific initial situation and target goals. Part of the in-
formation can be used repeatedly within the decision-
making process regarding different open innovation
projects. However, some analysis content should be es-
timated de novo for every open innovation project.
The framework and the software tool provide a broad,
evaluative foundation to assist with the complexity of
the decision-making process. However, acting on their
own, the software tool can prepare the information
basis and formulate concrete recommendations but
cannot provide a definitive answer to the ultimate ques-
tion of whether or not to participate in an open innova-
tion project.
Conclusions and Outlook
After establishing the theoretical background, ap-
proach, and process model, the next steps include their
evaluation from the practical point of view. This is en-
sured by a close collaboration with enterprises (espe-
cially SMEs) and innovation experts and includes two
evaluation focuses. First, the innovation indicators de-
veloped (see step 3 above) will be evaluated according
to their importance within open innovation projects.
Given the mostly theoretical nature of these indicators,
this step is necessary in order to preserve their relev-
ance and applicability within the practice of the enter-
prise. For this purpose, innovation experts will be asked
to estimate and appraise the indicators on the basis of
their practical experience. The indicators selected build
the base for the development of the weighing and de-
cision framework. After the implementation of the
framework into the software tool, a second evaluation
of both – the potentiality and functionalities of the tool
– will be carried out in form of a test phase.
Whether a decision made in doubt was really good, ac-
curate, or solely sub-optimal, remains highly subject-
ive, simply because of the lack of the opportunity to
compare real-world situations. There is only one real-
time occurrence and no reliable further information
about alternative scenario developments available.
Technology Innovation Management Review April 2016 (Volume 6, Issue 4)
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Weighing the Pros and Cons of Engaging in Open Innovation
André Ullrich and Gergana Vladova
About the Authors
André Ullrich has worked as a Research Assistant
and a PhD Candidate at the Chair of Business In-
formatics with an emphasis on Processes and Sys-
tems at the University of Potsdam, Germany, since
graduating there with a Diploma in Business Admin-
istration in 2011. Currently, his research interests
are open innovation processes, employee qualifica-
tion, the performance capability of indicators for as-
sessing organizations, and change capability
research. Furthermore, he continuously moderates
creativity workshops regarding turbulences in busi-
ness environments. He has published several nation-
al and international articles in the research areas of
change capability, creativity techniques, seasonal-
ity’s, and employee qualification.
Gergana Vladova is a Research Assistant and a PhD
Candidate at the Chair of Business Informatics with
an emphasis on Processes and Systems at the Uni-
versity of Potsdam, Germany. She holds a Master's
degree in International Economic Relations from
the University of National and World Economy in
Sofia, Bulgaria, and a Magister degree from the Freie
Universitît Berlin, Germany. She has been working
within diverse research projects, and she lectures
graduate courses and seminars in the field of know-
ledge management. Her main fields of research are
corporate communication and culture, knowledge
management, product counterfeiting, and open in-
novation management.
Thus, guiding entrepreneurial decision processes is par-
ticularly beneficial in order to reduce insecurity (Simon,
1979) as a reason not to participate in an open innova-
tion project. Given that risk awareness is of particular
importance for enterprises, it is pivotal to provide an un-
derstanding that their "risks are greater if they choose
not to innovate" (Valkokari, 2015).
Although there is a plenty of research dealing with the
assessment of the positive aspects of open innovation
processes as well as some research with emphasis on
the “dark sides” of open innovation, the novelty of this
approach is the analysis of the interdependencies of
both facets and their combined impact on the open in-
novation project’s chances of success.
SMEs are particularly addressed because they are eco-
nomical backbones and will benefit more than corpora-
tions with economies of scale. Although facing similar
challenges, each is unique and requires tailored recom-
mendations for improvement.
Acknowledgements
The project Open Darkness (IGF promotion plan 18632
of the Institut für Energie- und Umwelttechnik (IUTA)),
is funded by the AiF within the programme for sponsor-
ship by Industrial Joint Research and Development
(IGF) of the German Federal Ministry of Economic
Affairs and Energy.
An earlier version of this article was presented at the
2015 ISPIM Innovation Summit in Brisbane, Australia,
December 6–9, 2015. ISPIM (
ispim.org
) – the International
Society for Professional Innovation Management – is a
network of researchers, industrialists, consultants, and
public bodies who share an interest in innovation man-
agement.
Technology Innovation Management Review April 2016 (Volume 6, Issue 4)
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Citation: Ullrich, A., & Vladova, G. 2016. Weighing the Pros and Cons of Engaging in Open Innovation. Technology Innovation Management
Review, 6(4): 34–40. http://timreview.ca/article/980
Keywords: open innovation, open innovation participation, self-assessment tool, risks, benefits, entrepreneurship, SMEs
Weighing the Pros and Cons of Engaging in Open Innovation
André Ullrich and Gergana Vladova
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This paper offers a systematic framework for Managerial Innovation (MI) that could be used in the military context as a significant public sector. The corporate sector and public sector have different characteristics, which create different internal environment and capacity to dynamically change to the surrounding environment. Strategy and Innovation science has always been a military endowment. However, the last four decades have witnesses unprecedented evolution of MI in the corporate sector than the military sector. This gap has been pointed out in Shultz (2016) and yet to be addressed.In this paper, the authors offer a systematic literature review to highlight the subjects, objects, tools, and outcomes of corporate MI. Then it proposes the activity theory as a conceptual lens to narrow down the gap between the corporate sector and military sector in understanding and practicing MI. Alternative innovation theories (including, innovation diffusion, open innovation, and inclusive innovation) have been reviewed and a gap has been found towards a systemic theoretical lens. Karanasios & Allen (2013) presented the activity theory a systemic lens to manage the public-sector decision-making activities in contaminating Chernobyl nuclear power disaster. Aiming to extend this attempt, our study offers a military perspective of MI activities that could be applied by the public sector in countries where the corporate sector does not have enough capacity to serve the economic ambition. This paper offers a pathway for military MI and encourage its contribution towards economy by enhancing their subjects, objects, tools, and outcomes. It offers transplants from the corporate sector to push new blood of MI in the military and overall public sector institutions.
... Although it can serve as a tool to minimize traditional business risks (Fu et al., 2014), open innovation itself creates risks that can, compared to traditional closed innovation, result in a higher number of unfavorable outcomes, including knowledge leaks, loss of competitive advantage (Linåker and Regnell, 2020;Chaudhary et al., 2022), loss of reputation, and damage to brand image, among others (Cao and Song, 2016). Delving more deeply, risk in open innovation can be defined as any source of uncertainty in the process; these might include a contributor's unwillingness to participate (Enkel et al., 2005) or technical difficulties (Onuchowska and De Vreede, 2017)with the potential to cause unintended outcomes, such as the failure to capture contributions, the inability to achieve innovation outcomes, the leakage of intellectual property (Alberti and Pizzurno, 2017;Ullrich and Vladova, 2016), or even the failure of innovation. Further, Lu and Chesbrough (2021) show that some open innovation practices, such as network and communities, industry-academia collaboration, and contracting and licensing, exhibit an inverted U-shaped relationship with financial performance. ...
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The open innovation paradigm has created substantial new opportunities for firms in various sectors. However, scholars have long expressed concern that open innovation also entails a dark side, which can result in value co-destruction. This concern highlights the importance of devoting attention to the perils of pursuing open innovation. Existing scholarship has given due credence to these perils by examining various associated risks and uncertainties. We observe that the extant literature is siloed and unorganized, which impedes future research. Positing that an endeavor to organize existing studies may enhance the pace of research in the area, we attempt to address this gap by reviewing the relevant literature. We thus utilize the systematic literature review approach to identify, synthesize, and critically analyze 80 related research articles. Based on this analysis, we present the bibliometric profile of the extant research and a typology of five risks in open innovation: data-related risks, people-related risks, firm-level risks, outcome risks, and other risks. In addition, we discuss a specific risk management approach for each of the identified risks. Beyond providing a lucid narrative of the extant literature, we also identify unexplored avenues and offer an overarching framework to conceptualize future research potential in the area. From a practical perspective, managers can utilize this framework as a risk assessment tool when engaging in open innovation. In sum, this review—one of the first of its kind—offers a valuable consolidation of the state of the art of open innovation risk research, which can meaningfully advance theory and practice in the area.
... Organizational limitations are mainly associated with limitations that require strategic resources or strategic decisions (e.g., decisions concerning cost, structure, policies). These limitations are thus related to the implementation and governance of OI independent from their inbound/outbound orientation [31], [40], [41]. Operational limitations are mainly associated with managing OI projects, from incentivizing external actors to time management and coordination. ...
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Open Innovation (OI) has become a popular method of value co-creation over the past two decades. While OI offers many benefits, it holds a high failure rate. Through a systematic literature review, this paper identifies 15 common limitations of OI that contribute to this high failure rate at three levels: organizational, operational, and individual. Accounting for these limitations and their relationships, we develop a framework for OI's critical success factors. This paper also offers an agenda for future research and makes contributions toward understanding OI systems and their governance from a practical standpoint.
... Tabella 2. The dark sides of open innovation, (Ullrich & Vladova, 2016) Tra i pro dell'OI troviamo in termini organizzativi: ...
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Fenomeni come la globalizzazione e la rivoluzione digitale, attualmente in corso stanno radicalmente cambiando il panorama economico mondiale. In questo contesto di rapido cambiamento, caratterizzato da una riduzione sempre più stringente del ciclo di vita dei prodotti, da una progressiva dilazione nel tempo del recupero degli investimenti in tecnologie, i costi interni di ricerca e sviluppo sono destinati ad aumentare. Ma come possono le organizzazioni, chiamate a rispondere alla continua domanda di innovazione, riuscire a destreggiarsi tra i crescenti costi dello sviluppo tecnologico e l’accorciarsi del ciclo di vita dei prodotti? La soluzione a tale quesito risiederebbe in un paradigma che sta prendendo sempre più piede nel contesto internazionale: l’open innovation. L'innovazione è stata percepita come fattore centrale per la sopravvivenza a lungo termine delle organizzazioni. Le aziende internazionali più evolute hanno saputo mettere in atto efficaci strategie di open innovation. L’innovazione aperta è materia di relazioni e rete, dentro l’azienda, ma anche con tutti gli attori dell’intero ecosistema, dai fornitori ai clienti. Uno strumento finalizzato all’adattamento del dinamismo ambientale ma soprattutto la chiave per ottenere il vantaggio competitivo, fornendo nuovi prodotti o servizi ai consumatori. Con tali potenziali vantaggi, l'innovazione ha suscitato un interesse costante tra ricercatori e professionisti. Ricerche precedenti suggeriscono che le innovazioni creano valore per le aziende, diminuendo i costi di prodotti o servizi esistenti, migliorandone la qualità, inventando nuovi prodotti o servizi per i quali esiste una domanda sufficiente o offrendo migliori modelli di business. Inoltre, innovazioni radicali trasformano o addirittura distruggono i mercati esistenti. Man mano che i moderni prodotti industriali diventano sempre più complessi, il loro sviluppo e la loro produzione deve attingere a una vasta gamma di idee esterne, tecnologie e complementari funzionalità. In questo panorama è praticamente impossibile per ogni singola impresa tenersi al passo con tutti i progressi tecnologici pertinenti. Ciò significa che il progresso di un’azienda coinvolge lo sviluppo di conoscenze specializzate, utilizzando input provenienti da una gamma più ampia di altre scienze e aree di conoscenza non scientifiche. Queste attività sono definite come pratiche di Open Innovation. Le reti gestite da singole imprese situate all'interno di un'economia nazionale o regionale rappresentano le basi per l'apprendimento e l'integrazione delle conoscenze a livello di sistema più ampio. Lo sviluppo e l'accumulo di conoscenze delle imprese arricchiscono l'economia in generale ponendo le basi per la mobilità del mercato del lavoro, la formazione di reti personali e promuovendo legami di collaborazione. Nella tesina si analizzano le pratiche di open innovation. Il punto di partenza è l’attuale nozione e successivi tentativi di trasformare questo concetto di gestione in prospettive globali su innovazione e crescita, in particolare in ambito europeo. L'obiettivo generale delle componenti concettuali della tesina intende mettere a confronto i pro e contro delle politiche di Open Innovation sia in termini di singola impresa e in senso lato nell’economia globale, in particolare quella europea. Come si leggerà nell’elaborato, il concetto di innovazione aperta non è così recente come si narra. Basti pensare infatti all'industria automobilistica giapponese, la quale vanta una lunga storia in termine di collaborazione con i fornitori durante l'intero processo di innovazione e non solo per la generazione di idee. La famosa strategia di inventario "just in time" di Toyota non avrebbe mai funzionato se i partner commerciali esterni non fossero stati coinvolti. Tuttavia, l'uso diffuso di Internet ha reso l'innovazione aperta più popolare e più pubblica. L’innovazione è infatti totale: dal marketing alle risorse umane, dalla produzione alle vendite fino al rapporto con i clienti. Infatti, rendere l’innovazione “aperta” garantisce al lavoro svolto dalle imprese un impatto maggiore, in quanto aumenterebbe la probabilità che i risultati possano essere utilizzati da altri attori, interni o esterni all’organizzazione d’origine. L’open innovation non rappresenterebbe più soltanto il motore dell’innovazione di una singola impresa ma, potenzialmente, di un intero ecosistema di aziende pronte ad innovare in modo continuativo e collaborativo, e a rinnovare settori in difficoltà. Di recente pubblicazione, da parte del Sole 24 Ore, è la notizia che vede l’università LUISS Guido Carli di Roma aprire un corso di studi sull’Open Innovation. La cattedra è stata assegnata a Henry Chesbrough, direttore del Garwood Centre for Corporate Innovation dell’università della California a Berkeley e padre intellettuale del concetto di open innovation (Picchio, 2020). Ciò potrebbe essere colto come un segnale alle università, agli istituti di ricerca, alle società, start-up, al mondo della finanza, e alle autorità pubbliche di porre l’attenzione al fenomeno dell’innovazione aperta.
... Dufour and Son (2015) moved a step forward and after individuating four potential barriers in the literature, namely corporate culture, networking, organisational structure and knowledge management systems, they applied the theoretical framework to a single case study to provide insights on how to overcome these barriers by analysing the diverse organisational changes undertaken by the company. Ullrich and Vladova (2016) proposed a weighing and decision process framework as a conceivable solution approach to increment projects' chances of success. According to their point of views, there are plenty of studies assessing the positive aspects of open innovation processes while few articles put emphasis on the dark sides. ...
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Governments are increasingly focusing their efforts on stimulating innovation within small and medium-sized enterprises (SMEs). As a result, university-industry-government collaboration is gaining importance among the agenda of policymakers to enable open innovation in SMEs. However, these inter-organisational relationships often fail to meet expectations, especially when projects are oriented to pre-competitive R&D. Nevertheless, the literature has not yet provided sufficient evidence of the challenges related to the participation of traditional SMEs (i.e., low- and medium-low tech SMEs) in this specific type of collaboration. We collected qualitative data to analyse longitudinally three pre-competitive projects, exploring the main challenges faced by traditional SMEs. We have bracketed the projects in four phases: initiation and planning phase, execution phase, closing phase, and monitoring and control phase. For each of these phases we have individuated firm- and project-level challenges, providing practical and theoretical insights for open innovation scholars.
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Chapter
Across the literature, is often claimed that the shortage of models to support projects in the collaborative dimension, creates distrust and pushes way organizations from those collaborative initiatives, such as the open innovation (OI). In the present work, a model based on three different scientific fields (Risk Management, Open Innovation, and Social Network Analysis), is introduces, aiming to support the management of OI projects. The model identifies project critical success factors (CSFs) by analysing three distinct collaborative dimensions (3-CD) that usually take place in OI projects - (1) Participation Degree, (2) Communication Degree, and (3) Response Agility Degree – of accomplished projects. Such CSFs can then be used to guide and estimate an outcome likelihood of upcoming or ongoing OI projects.
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In recent years due to the increased interest in the practice of open innovation as a promising model of innovation process management numerous studies have been conducted devoted to the discussion of various aspects of the open innovation implementation. The growing trend towards open innovation adoption causes the need for a more open approach to the management of the intellectual property (IP). However, despite the fact that the study of organizational determinants in the open innovation collaborative projects is an area of increased interest for both academics and practitioners of innovation management a modern understanding of these aspects at the enterprise level remains incomplete and needs further research. The IP management involves the implementation of the key managerial functions, such as developing a strategy and planning measures for the protection and commercialization of intellectual property, organizing activities to create conditions for their implementation, creating a supportive innovation culture and encouraging innovative climate, audit and monitoring the implementation of the IP management strategy. An effective IP management strategy should include an analysis of the internal factors of the organization, as well as taking into account market factors for the formation of an open innovation model.
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Open innovation has so far been studied mainly in high-tech, multinational enterprises. This exploratory paper investigates if open innovation practices are also applied by small-and medium-sized enterprises (SMEs). Drawing on a database collected from 605 innovative SMEs in the Netherlands, we explore the incidence of and apparent trend towards open innovation. The survey furthermore focuses on the motives and perceived challenges when SMEs adopt open innovation practices. Within the survey, open innovation is measured with eight innovation practices reflecting technology exploration and exploitation in SMEs. We find that the responding SMEs engage in many open innovation practices and have increasingly adopted such practices during the past 7 years. In addition, we find no major differences between manufacturing and services industries, but medium-sized firms are on average more heavily involved in open innovation than their smaller counterparts. We furthermore find that SMEs pursue open innovation primarily for market-related motives such as meeting customer demands, or keeping up with competitors. Their most important challenges relate to organizational and cultural issues as a consequence of dealing with increased external contacts.
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