OPEN INNOVATION PROJECT: THE SYSTEM OF ONLINE
INDICATORS IN SCIENCE, TECHNOLOGY AND INNOVATION OF AMAZONAS (SiON)
Moises Andrade Coelho
Federal University of Amazonas - UFAM, Brazil
E-mail: moises.acoelho@gmail.com
Submission: 03/12/2015
Revision: 17/12/2015
Accept: 14/01/2016
ABSTRACT
This study aims to evaluate the implementation of an open innovation
project in a public institution in the state of Amazonas. The study is
characterized as a qualitative and descriptive research, using the case study as
a methodological procedure. The universe delimitation was composed by a public
institution in the area of science, technology and innovation (ST&I). The
case study, was used an approach as tool to assess the implementation of open
innovation projects. The results are shown several stages of open innovation
project analyzed. The study demonstrates
the implications of the open innovation project adoption to the strengthening
of external networks and the maturing of the internal environment. The
relevance of the study is based on the evaluation of an the open innovation
project in a public institution in order to foster the transition from
traditional innovation processes to open innovation processes.
Keywords: Open
Innovation; ST&I indicators; SiON; Amazonas.
1. INTRODUCTION
The era of capitalism
is going through, not quickly, but inevitably, according to Rifkin (2014). For
the author, the new economic paradigm (cooperative communities) is growing from
the emergence of a hybrid economy, part capitalist market and part
collaborative communities
According Annunziata (2013), we live in the era of
industrial internet gathering intelligent machines, analytical advanced and
creativity of people at work. For him, the world experienced two waves of
innovation: first, the industrial revolution that brought machines, factories,
railways, electricity, air travel, among others; and second, the internet
revolution, which brought computing power, data networks, with unprecedented
access to information and communication.
Added to this scenario, the markets have become more
globalized, opening for new opportunities, as well as intensifying the level of
competition, with life cycles getting shorter products or pressure resulting in
a more intense and global competition with technological progress continuous.
Companies are forced to innovate faster and develop more efficient products and
services (OECD, 2010a).
In recent decades, the strong global competition has
led to the sharing and cooperation of labor between the innovation processes of
companies. In various industries, agility, flexibility and concentration are
essential skills considered as sources of competitive advantage. The open
innovation phenomenon is a complex issue that has received contributions from
different streams of research. This innovation process includes several
perspectives: (1) globalization of innovation, (2) outsourcing of research and
development (R&D), (3) integration with the supplier (4) Users of
innovation and (5) foreign trade and application of technology (GASSMANN,
2006).
In this context, open innovation implies that
businesses depend on external knowledge assets critical to the successful
realization of their innovative ventures (CHRISTENSEN et al., 2005). In open innovation, companies share ideas externally
(internally also occurs) for the implementation of ways to market (CHESBROUGH,
2003).
Thus, this study aims to evaluate the implementation
of an open innovation project in a public institution in the state of Amazonas
The work is structured in three parts: (1) theoretical and empirical
background, dealing on science, technology and innovation (ST&I) indicators
and open innovation; (2) methodology, with the study design, research
framework, methods of data collection and methods of data analysis; and
finally, (3) results in the institution, discussion, conclusion and references.
2. THEORETICAL AND EMPIRICAL BACKGROUND
2.1.
Indicators
of Science, Technology and Innovation (ST&I)
In the early 60s, the
OECD development indicators had focused on the relationship between research
and development, this situation has changed in the last 20 years having the
discussion expanded to work in areas of innovation; intellectual property;
measures for knowledge management, direct and indirect support of technology government
programs and R&D (research and development). Thus, there is a need for a
systemic approach to the development and classification of these new indicators
(GAULT, 2011).
Innovation has become a policy priority in many
countries supported by national strategies and large budgets. Subsequently,
innovation has taken a central role and many governments have established
ministries, departments and offices to support studies, integration and
implementation of innovation policies. In order to evaluate the effectiveness
of government interventions, various innovation indices have been developed in
recent years to measure innovation performance at national and sub-national
(MAHROUM & ASALEH, 2012).
Science indicators, technology and innovation
(ST&I) have become an essential ingredient in research focusing on
operating modes of STI subsystems and their relationship to the larger social
system. Dissatisfaction with the R&D indicators was the basis for the
successful development of new output indicators in ST&I within the
framework of the Oslo Manual (1992). Together with the different surveys waves
occurred in the early 90s by different actors, as European Union in applying
the Comunnity Innovation Survey (CIS), for example (FREEMNAN & SOETE,
2007).
The first CIS took place in 1993 with the goal of
being a major source of data for new innovations at the time. The purpose of
the CIS and other surveys of innovation was based on the first edition of the
Oslo Manual and sought to overcome some limitations of traditional R&D
questionnaires. They had two main goals, provide data innovation activities,
which were not included in R&D, and provide innovation outputs measures
(ARUNDEL, 2007).
The surveys of STI need to be redesigned to broaden
the vision of innovation, the goal is to help recognize the important role of
STI policies in promoting economic growth. Companies, statistics and research
communities are encouraged to work to measure and assess intangible assets,
reviewing the framework of measures for innovation and alignment with the
administrative and economic data aggregated to allow analysis of productivity.
In this context, the OECD Innovation strategy includes a measurement schedule
which will be implemented. Political actions need more reflection about the changing
nature of innovation; this implies an emphasis on the following areas,
according to the agenda (OECD, 2010a):
Another survey is called Nordic Innovation Monitor;
the instrument measures the innovation capacity of the OECD countries and
highlights areas where innovation needs to be strengthened. It is believed to
have been a major impact on innovation capacity four structural conditions are
necessary: (1) human resources; (2) knowledge creation; (3) innovation and
communication technology (ICT); and (4) entrepreneurship. The Nordic Innovation
Monitor measures the strength of the four conditions, as well as their outputs
(NORDEN, 2009).
In the United States, after years of lack of
innovation indicators, the National Science Foundation (NSF) in cooperation
with the economic directory Census Bureau redesigned the R&D Survey to
produce the Business R&D and Innovation Survey (BRDIS) whose pilot was held
in January 2009 (GAULT, 2010).
With regard to more recent indicators of innovation,
the publication Measuring Innovation, a new perspective (OECD, 2010b) presents
new measures and new ways of looking at traditional indicators; these new
indicators attempt to accurately reflect the diversity of actors and processes
of innovation and the links between them. The new indicators are divided into
six chapters and more than 40 innovation indicators that make up a much broader
and comprehensive framework of innovative measures, namely:
In the case of
Brazil, in 2001 the Brazilian Institute of Geography and Statistic (IBGE)
signed an agreement with the Financier of Studies and Projects (FINEP) to
conduct the first survey of Technological Innovation (PINTEC) which resulted in
a work group formed by representatives from IBGE, the Ministry of Science
Technology and Innovation (MCTI) and FINEP (IBGE, 2002).
PINTEC aims at building national indicators of
technological innovation activities in industrial companies, in line with
international methodologies in conceptual and methodological terms. The
conceptual and methodological framework of the research is the Oslo Manual and
the model used by EUROSTAT, Community Innovation Survey (CIS). The universe of
survey deals with companies with ten or more employees (IBGE, 2002). The first
edition (2000) occurred data for the period 1998 to 2000. The second edition
(2003) evaluated data the period from 2001 to 2003, the third edition (2005)
evaluated data from 2003 to 2005; the fourth edition (2008), evaluated data
from 2006 to 2008 and the fifth and last edition (2011) evaluated the data
between the years 2009 and 2011 (IBGE, 2002, 2005, 2007, 2010, 2013).
As a differential, the third edition of PINTEC (2005)
went on to evaluate the activities related to the services which include
telecommunications, computer activities and services related to research and
development (IBGE, 2007). In the 2008 edition, was an extension of valued
services activities with the addition of services, such as, editing and music
recording; activities of information technology services; and data processing,
internet hosting and other related activities (IBGE, 2010). In the 2011
edition, it started to evaluate innovative activities in biotechnology and
nanotechnology (IBGE, 2013).
2.2.
Open
Innovation
For years the R&D internal process was based on
the closed innovation model which successful innovation demanded control.
Companies should generate their own ideas and develop, produce, perform
marketing, distributing and selling on their own (CHESBROUGH, 2003).
This model worked very well throughout the twentieth
century, however at the end of the century a number of factors contributed to
the erosion of closed innovation model in the United States. In the open
innovation model, combinations of internal and external knowledge to the
organization allow to create value while establish internal mechanisms to claim
some of this knowledge to the company itself (CHESBROUGH et al., 2006).
Three essential processes can be differentiated in the
open innovation (ENKEL et al., 2009):
(1) outside-in process; (2) inside-out process; and (3) coupled process. In
work, Gassmann et al. (2010)
indicates nine perspectives necessary to develop a more complete theory of open
innovation; for authors, open innovation is based on these different research
streams.
Elsewhere, Dahlander & Gann (2007) seek to
identify the types of openings that take place within the framework of Open
Innovation and point to opening following characteristics: (1) different levels
of informal and formal protection; (2) the number of external innovation
sources; and (3) the degree to which companies are relying on formal and
informal relationships with other actors. Later, the authors sought to clarify
the definition of openness and reconceptualize the idea for future research on
the subject combining literature review of all papers published in the Web of
Knowledge (ISI) with a content analysis to develop a complete understanding of
the area (DAHLANDER & GANN, 2010).
Lazzarotti & Manzini (2009) follow the idea in
which the opening requires a local or continuity from the exploitation of their
different degrees in terms of the number of external sources of innovation.
They considered two variables to represent the degree of openness for a
company: (1) number or types of partners with whom the company collaborates and
(2) the number or types of stages of the innovation process that the company
open to external contributions. From these two variables, they identified four
open innovation modes: (1) closed innovators, (2) specialized collaborators,
(3) integrated collaborators and (4) open innovators. The most common models
found were open and closed innovative. In addition, the study shows that there
is no better model than another, nor that the open model is the best among the
four. In this case, the choice of one model by companies should consider the
strategic, organizational and managerial context and accept a balance between
the benefits and costs of each.
Other research related to open innovation, carried out
by Keupp & Gassmann (2009), the authors sought to understand why some
companies conduct open innovation on a larger scale than others and how these
companies differ. Unlike other contributions that explaining about these
differences as resulting from factors external to the company, the authors
explain that the differences result from factors internal to the company,
specifically the impediments to innovation.
Four archetypes of companies that differ significantly
were identified with respect to the breadth and depth of open innovation and
the importance of impediments. The four open innovation user archetypes are:
(1) professionals, companies that collaborate extensively as a large number of
external sources of knowledge and deep with respect to the intensity of
collaboration; (2) explorers, companies that collaborate with a large number of
sources, but does not cause the same degree of professional; (3) Scouts,
companies that collaborate with various sources, unlike the explorers, their
approach include not deep collaborations; and (4) isolationists, companies
still prefer to keep their closed innovation activities or just started
exploring the open innovation approach (KEUPP & GASSMANN, 2009).
In the case of Mortara & Minshall (2011), the
authors developed a taxonomy implementation of open innovation. This taxonomy
consists of four quadrants that are related to revolutionary change and
evolutionary aspects and distributed or central location. The implementation of
open innovation depends on three factors: (1) innovation requirements, (2) the
timing of the implementation and (3) organizational culture. Each of these
factors has led to differences in the way it has been implemented open
innovation in the companies studied.
In publishing, West & Gallagher (2006) identified
three core business challenges for implementing the concept of open innovation:
(1) finding creative ways to explore the internal innovation, (2) incorporating
external innovation in internal development and (3) motivate external agents
support the continued flow of external innovations . These challenges involve a
paradox: why companies invest efforts in R&D if the results of these
efforts will be available to rival companies?
From this paradox, examined whether the activities of
open-source software companies characterized by make investments that will be
shared with actual and potential rivals. Four strategies or ways of combining
internal and external innovation in open source have been identified: (1)
pooled R&D/product development; (2) spinouts; (3) selling complements; and
(4) Attraction donated complements.
For Chiaroni et
al. (2011), the paradigm of open innovation is implemented during the
process of three phases comprising the stages unfreezing, moving and
institutionalising. For this, the authors sought to answer two important
questions related to the subject: (1) understand the relevance of open
innovation beyond the high-tech industries and (2) to study how companies
implement open innovation in practice. The authors suggest that open innovation
as an organizational change process occurs through the sequence unfreezing,
moving and institutionalising, as proposed by Lewin (1947) and supplemented by
Armenakis & Bedeian (1999). In the case of levels of management to open
innovation, identifies four levels where the implementation of open innovation
impacts: (1) networks, (2) organizational structures, (3) evaluation processes
and (4) Knowledge Management Systems.
Dodgson et al.
(2006) present a case study of Procter & Gamble demonstrating the great
organizational and technological changes associated with open innovation. The
attractiveness of open innovation as a business strategy lies in how to deal to
explore the benefits of importing ideas from outside the company and exporting
intellectual capital hitherto idle. The model also enables large corporations
to become more entrepreneurial from new forms of finance, supporting start-ups
through venture funds and the like.
Finally, as opposed to Chesbrough ideas about open
innovation, Trott & Hartmann (2009) mention that the American author has
created a false dichotomy by arguing that open innovation is the only
alternative to the closed innovation model. The paradigm of open innovation is
shown by the contrast with the paradigm of closed innovation. The authors
demonstrate that the dichotomy between open and closed innovation may be true
in theory, but does not actually exist in the industry. In short, is an old wine
in a new bottle.
3. METHODOLOGY
3.1.
Study
Design
This study, in terms of problem approach is
characterized as a qualitative research (SILVA & MENEZES, 2005), with the
object a public institution of the state of Amazonas. With regard to its
objectives, it is revealed as a descriptive (GIL, 2002), the descriptive
research aims to provide greater familiarity with the problem in order to make
it explicit or build hypotheses. It involves literature, interviews and
analysis of examples. Assume forms of bibliographic research and case studies.
The methodological procedure used was the case study,
examining a phenomenon in its natural setting, using multiple data collection
methods to gather information from one or few entities, such as, individuals,
groups or organizations (BENBASAT et al.,
1987). The case study works from relational inferences or analytical generality
(MEREDITH, 1998; YIN, 1994), seeking to generalize the results of a study to
create a theory, in addition to trying to determine if a factor is related to
another.
The case study allows (GIL, 2002):
The delimitation of the universe was composed by the
State Secretary of Science, Technology and Innovation of Amazonas (SECTI). To
evaluate deployment of open innovation approach was used to Boscherini et al. (2010) consists of three phases
(conception, realization and transfer of results) and detailed in item 3.2.
3.2.
Research
Framework
In the case study, was used the approach presented in
Boscherini et al. (2010) as tool to
assess the implementation of open innovation projects. The approach allows
studying how companies plan and managing pilot project through open innovation.
The authors developed a research framework that has
been used to collect empirical data and interpret ways to analyze the case
studies. The approach consists of three phases (Figure 1):
Figure 1:
Research Framework
Source: Adapted from
Boscherini et al. (2010).
The conception phase consists of the following
variables: (1) source; (2) objective; (3) reason for adopting open innovation;
and (4) Scouting of partners. During the realization phase, the following
variables are adopted by the authors: (1) internal organization; (2) network;
(3) evaluation processes; and (4) knowledge management systems. Finally, in
transfer of results phase: (1) champion of the transfer; (2) organizational
changes; (3) sources of resistance; and (4) standardized methods, as variables
identified by the authors.
3.3.
Methods
of Data Collection
The sample was unintentional probabilistic character
(MARCONI & LAKATOS, 1990). The research techniques used for realization of
the study were: (1) indirect documentation (documental and literature
research); and (2) intensive direct observation (interview). The study was
conducted in three stages:
3.4.
Methods
of Data Analysis
Qualitative data obtained from answers of the
interviews were tabulated in summary table, grouped according to content and
stratified according to the structure of the research approach. Documentary
information raised at first were integrated and triangulated with data
collected by interviews in order to ensure the rationalization and validation.
For analysis of the qualitative data we used the methodology
proposed by Kvale (1996) by adopting the following phases of analysis:
4. RESULTS
4.1.
Objective
of the Pilot Project
The pilot project developed a system of
indicators in science, technology and
innovation that would bring together in the same environment the results of
various national databases (National Council of Scientific and Technological
Development - CNPq, Coordination for the Improvement of Higher Education -
CAPES, Brazilian Institute of Geography and Statistics - IBGE) thus allowing
the monitoring of policy results state public in this area, in addition to
serving as a source, for the scientific community, of technical and scientific
studies.
4.2.
Conception
The pilot project (source of pilot project) originated
internally at the institution where early in the second half of 2010 has
identified the need and the importance of monitoring data and information, as
well as the need to analyze several variables related to ST&I indicators at
the state level, in order to enable the accessibility and optimize the flow of
information enabling the analysis of historical data to identify possible
trends/scenarios of ST&I in the state, regional and national levels.
In this context, it was added to the transparency of
public needs and the ease of data collection available in databases scattered
in various organs of this area and the like. Soon, it was necessary to create a
ST&I indicator system that would allow measuring the economic and social
impacts of investments and actions in the area bringing together in a single
environment data from various databases (CNPq, CAPES, IBGE and FAPEAM).
In 2010, the SECTI submitted to the support of the
Amazonas Research Foundation (FAPEAM) proposal with the main objective of
structure a system of indicators that allow measuring the investment and
actions in the area carried out by the state of Amazonas and evaluate economic
and social impacts of these investments and actions. Among the expected outputs
were at:
The reason for adoption of open innovation in the
system pilot project occurred because the department did not have the necessary
expertise to the platform development in area. The process of exploring
external partners for the pilot project included the identification of possible
partnerships with public universities in the state, especially, the Federal
University of Amazonas (UFAM) that has the postgraduate program in the field of
computer science and the Amazonas Research foundation (FAPEAM) it would invest
funds through scholarships and support research.
4.3.
Realization
In late 2010, the FAPEAM launches notice for the
proposed contract for the development of the ST&I indicator system
contemplating the scholarships and support research. The approved proposal was
the responsibility of the Institute of Computing (Icomp) linked to the Federal
University of Amazonas.
The process of development indicator system required
the participation of the three institutions (SECTI, FAPEAM and Icomp) for the
design of the modules that would form the SiON. Thus, FAPEAM and SECTI, they
were responsible for identifying indicators and databases where they were
located and Icomp responsible for the creation of mechanisms for data
collection. Therefore, the project collaboration network was composed by SECTI,
FAPEAM and ICOMP which worked directly for the system development process.
Regarding the processes evaluation, the process development
of SiON modules occurred from the control of time and implementation costs
given the public nature of the investments being made up of seven stages,
namely:
The approaches to knowledge management in the project
involved the full support the dissemination, sharing and transfering of
knowledge not only among the project partners but also all the results that
could be achieved after its launch. The idea would be the full opening (access
to the source code) to other institutions that have interest in adopting
similar tool.
Thus, the System of Online Indicators in Science,
Technology and Innovation of Amazonas (SION), was officially launched in 2012,
consolidating its position as the leading management and advertising tool of
ST&I policy underway in the Amazon. The system has been set up as an
important management and public transparency tool as provides real-time
indicators that allow the public manager making decisions based on reliable and
consistent information with strategies outlined in the planning of
institutional actions and social control, via internet, goals and
implementation of budgets in each of the actions in progress.
In 2013, it was released version II of system with new
features, with the recasting of the technical notes, review and inclusion of
new indicators. Among the new modules stand out from the CNPq indicators and
state expenditures indicators in ST&I. The system became more complete,
presenting the results of the productivity of Amazonian researchers and state
expenditures in the area.
4.4.
Transfer
of the Results
Regarding the transfer process, in 2013 the system
source code has been transferred to another department of science and
technology for implementation at the state level. The system led to internal
organizational changes with regard to greater speed and reliability of data
considering the need for presentation of ST&I indicators for society. The
system became a tool for project development process to provide faster basis of
the results that the state system of ST&I has achieved in recent years.
During the project sources of internal resistance
sources have not been identified, nor even in different relationships between
partners to develop the system. For manual input data process in the system was
necessary to standardize data collection methods on responsibility of SECTI.
4.5.
Structure
of SiON
The first version of SiON launched in 2012, was
composed of four modules (human resources, financial resources, S&T
activities and innovation activities) and nine areas, totaling 37 indicators of
science, technology and innovation, as shown in Figure 2. Only the module
"innovation activities" did not have subordinate areas.
Figure 2:
Structure (modules and areas) of the first version - SiON
The second version launched in 2013, consisted of new
features, recasting of the technical notes, review and inclusion of new
indicators. The new indicators and the revised are grouped into four new areas:
(1) FAPEAM, (2) CNPq indicators, (3) state expenditures indicators in ST&I
and (4) composite indicators.
The "FAPEAM" area is composed of 18
indicators that present data proposals, resources, costs, scholarships and
other actions taken by the foundation. The "indicators of CNPq" area
consists of six indicators dealing primarily scientific production of Amazonas
from the CNPq Lattes database; the area of "composite indicators"
is made up of 10 indicators that reflect various combinations of input
indicators, proposals and expenses of FAPEAM. Finally, the area of
"state expenditures in ST&I" shows the results of the state's
investments in ST&I actions based on scientific, technical and related
(ACTC) and research and development (R&D) developed by the State.
In conclusion, the third version released in 2014 the
innovation module has changed going to have two new areas: (1) performance of
industrial companies with regard to innovation and (2) Internal factors
influencing innovation. In the module S&T activities included scientific
and technological production area with information concerning the state of
Amazonas.
Figure 3:
Structure (modules and areas) of the third version - SiON
5. DISCUSSION
Regarding the open innovation project analyzed, there
is the adequacy of the institution to open innovative definition proposed in
Lazzarotti & Manzini (2009) and demonstrated in the case studies in
Boscherini et al. (2010) (1) initiate
engagement of the pilot open innovation from a larger number of external
partners (FAPEAM and ICOMP) higher than it would in a traditional design
innovation; (2) make accessible to external actors participation in various
stages of the innovation process; and (3) act in different organizational
levels to facilitate access to the innovation process, resulting in increased
management complexity.
The reasons for the adoption of open innovation are
access to essential external expertise to deal with radical pilot projects
which often require skills and knowledge from different areas (BOSCHERINI et al., 2010), in the case of the
institution studied in conception phase was necessary to form partnerships with
a view to acquiring knowledge and skills in face of external project
complexity. Thus, the opening of the project has become the solution to achieve
the goals.
Analogously to Boscherini et al. (2010), in the realization phase, the institution began
changing its procedures and internal organization to better cope with open
innovation the approach. The shared activities among the partners made it
possible to optimize the innovation process and involvement of the institution
in evaluation processes. The evaluation of the process resembled the stage-gate
process served on Cooper (1994), which each phase for the development of system
modules should be executed within stipulated time and costs. The study pilot
project enabled new ways for knowledge management to provide the source code
with other interested institutions.
During Transfer phase, the central question was not
only to keep the know-how developed in open innovation management, but to
transfer it to the procedures and routines of day-to-day. This transfer
occurred by the delegation to a specific department responsible for monitoring
future open innovation projects, in addition to sharing all information on the
system design.
Thus, among the main findings stand out: first,
building a system of indicators on line of science, technology and innovation
would allow citizens to hold a follow-up of results from public policy in this
area, more transparent to demonstrate
the amounts invested in scholarships, support research, number of masters and
doctors, among other data. Second, the involvement of FAPEAM, Icomp and SECTI
in system design through the use of expertise in each institution,
characterizing the pilot as open innovation. In conclusion, the possibility of
the system to be shared with other institutions from the acquisition of the
source code.
Regarding to the theoretical and empirical background,
showed the importance that science, technology and innovation indicators have
taken in recent decades and contribute to the discussion about the concepts and
fundamental aspects of open innovation. From it was possible to characterize
the institution as integrated collaborators under the open innovation modes
explained in Lazzarotti & Manzini (2009). Regarding the archetypes proposed
by Keupp & Gassmann (2009), the institution is characterized as explorers;
adopted as a strategy for the development of SiON, used the pooled
R&D/product development as proposed in West & Gallagher (2006).
The study confirms importance of the contributions of
the various partners already observed in other studies, such as in Chiesa et al. (2004) who analyzed the process
of outsourcing of R&D activities and Hoegel & Wagner (2005)
investigated the collaborative relationship between buyer and supplier.
The advantages achieved with the opening of SiON
development process found results presented in Berger et al. (2005), which explored new ways of cooperation between
customers, retailers and manufacturers Resulting from co-design and Emden et
al. (2006) who investigated the partner selection process to verify the
potential of creating competitively advantageous products through
collaboration.
The results observed in SiON project reinforce that
even companies from mature and asset-intensive industries adopt the principles
of open innovation. These results are equal to the work of Chesbrough &
Crowther (2006) and Chiaroni et al.
(2010).
Finally, because is a small institution, observed that
open innovation in small and medium-sized enterprises (SMEs) has also been
identified as Van Vrande et al.
(2009) which explored open innovation practices in SMEs. The results showed
that SiON open innovation process was determined by an individual decision
instead of resulting feature the institution's operating area, reinforcing the
results obtained in Lichtenthaler (2008).
Charter 1 provides a summary of open innovation
project implemented compared the ratings in the literature review.
Charter 1: Comparing the SiON Project and literature ratings
Project/Rating |
Lazzarotti & Manzini (2009) |
Keupp & Gassmann (2009) |
West & Gallagher (2006) |
SiON Project |
Integrated collaborators |
Explorers |
Pooled
R&D/product development |
The
methodology used allowed a proper assessment of open innovation pilot project
from the adoption of the approach proposed by Boscherini et al. (2010) where it was possible to view the construction of the
indicator system (SiON) within the three phases of the approach. The approach
rose to the evaluation and understanding of the pilot project in open
innovation that led to the creation of SiON.
6. CONCLUSION
Open innovation enables organizations to the
development of new products (goods or services), through cooperation between
several partners, using the expertise of each one so that the end result
benefits both internally and externally the creator of the idea. In this
context, this study achieved its goal when evaluating the implementation of an
open innovation project (SiON) in the State Secretary of Science, Technology
and Innovation of Amazonas (SECTI).
The results can be highlighted: (1) the construction
of the system of online indicators of science, technology and innovation; (2)
the external participation of partners in building the system through the use
of knowledge and skills of each institution; (3) the ability to transfer the
knowledge acquired during the project to other institutions of science,
technology and innovation.
Among the limitations of research is the approach
application in one institution statistically impossible to generalize in other
public or private institutions with different characteristics. As suggestions
for future studies, it should be adopted an approach in other institutions both
public and private area through multiple case studies.
The research reinforces previous studies which open
innovation requires an organization that is interested in managing
technological relationships, developing internal and external knowledge; facing
the barriers to innovation; and the challenges of organizational change process
in order to achieve the strategic objectives. The study relevance based on an
open innovation project evaluation in a public institution in order to foster
the transition from traditional innovation processes to open innovation
processes.
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