=Paper=
{{Paper
|id=Vol-1604/Paper5
|storemode=property
|title=The Value of a Meta Perspective in Social Innovation
|pdfUrl=https://ceur-ws.org/Vol-1604/Paper5.pdf
|volume=Vol-1604
|authors=Hans Weigand,Paul Johannesson,Birger Andersson
|dblpUrl=https://dblp.org/rec/conf/caise/WeigandJA16a
}}
==The Value of a Meta Perspective in Social Innovation==
https://ceur-ws.org/Vol-1604/Paper5.pdf
Proceedings of STPIS'16
The Value of a Meta Perspective in Social Innovation
Hans Weigand1, Paul Johannesson2, Birger Andersson2
1Tilburg University, Dept. Management,
Tilburg, The Netherlands
H.Weigand@uvt.nl
2
Royal Institute of Technology,
Department of Computer and Systems Sciences,
Stockholm, Sweden
pajo,ba@dsv.su.se
Abstract: Collective Awareness Platforms (CAP) have been promoted as an
enabler of social innovation. A CAP supports the collection of data
(quantitative and qualitative, and using all the technical possibilities that are
rapidly becoming available, e.g. sensors), the integration of the data, and the
presentation of results to the community in order to adapt their behavior or
develop new behavior patterns. Typically, a CAP has many stakeholders. To
support the development and maintenance of CAPs, we propose the notion of
META-CAP, a platform that allows participants to reflect on the CAP from a
value and collaboration perspective. The META-CAP architecture described in
this paper is evaluated from the perspective of socio-technical design.
Keywords: value modeling, open innovation, collective awareness platform
1. Introduction
All over Europe, we see visionaries, grass-root communities, citizen groups and small
enterprises, sometimes in cooperation with local government, developing effective
solutions to real societal problems in a process of social innovation [S13]. Examples
include local pollution control, energy reduction, or elderly care. As in most
innovation ICT plays a key role and this is increasingly being recognized in the field
of social innovation as well. In addition to standard web sites and social media
recently a new group of ICT tools is being developed: Collective Awareness
Platforms (CAPs) [S12, A14]. Essential functional components of a CAP are the
collection of data (quantitative and qualitative, and using all the technical possibilities
that are rapidly becoming available, e.g. sensors), the integration of the data, and the
presentation of results to the community in order to adapt their behavior or support
new behavior patterns. The concept is promising for several reasons, not the least that
the CAP provides the development of a “shared mental model” and thus fosters
cooperative behavior and social motivation.
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In our own experience, we have found that social innovation teams are often
without any business modeling support, and therefore have a problem in structuring
their interactions and building mutual trust. Consequently, many innovation projects
are aborted in an early stage or end up in situations where some parties feel abused.
Traditionally, conceptual models are used in the Information System domain for
communicating between different stakeholders and explicating design choices. Most
of these models aim to contribute to the system design. They do not touch the trust
issue. What kind of tool support can enhance trust? Legal contracts are sometimes
used, but experience also shows that they can take away all trust and kill the
collaboration and creativity immediately. Still what legal contracts try to describe –
the expectations, the distribution of value, the safeguards – is relevant. Is it possible to
model these issues in a non-intrusive way?
Current value modeling approaches have provided several conceptual tools to
support the development of business models [A02,G05,V12], and some of them, in
particular the Business Model Canvas Method, are widely used in start-up companies.
So there is a ground for saying that value modeling is the answer. However, we claim
that these approaches fall short at the moment in supporting an analysis of value
creation in the following way:
To assess the sustainable value of network collaboration, the analysis must look
beyond economic transactions. The dynamics of intangible benefits, in particular
the effects on knowledge development, need to be taken into account as well.
Value is created not so much or not only in economic transactions, but in
collaborative activities. These activities are by definition not controlled by a
single actor. In the approaches mentioned above, this shared control cannot be
expressed.
Value modeling should make clear what value is derived from the collaborations
and what they require, and should not depend too much on the institutional form
of the collaboration, as this is becoming more and more flexible.
In addition, it must be realized that innovation is a process [O14,T99]. Traditional
value modeling is focused on the exploitation phase of some new product or service,
but this scope is too narrow. To address these shortcomings, earlier we have
introduced a new value modeling variant – value encounter modeling [W09]. This
modeling approach has been applied in several small-size innovation projects.
In this paper, we bring together the promising area of CAP with the value
encounter modeling approach, in two ways. On the one hand, we claim that value
encounter modeling can contribute to CAP projects by providing a business modeling
approach that has been proven to be suitable for social innovation support. The value
encounter modeling provides the participants with a meta-perspective that supports
reflection [W12]. On the other hand, value encounter modeling when embedded in a
tool can be designed itself as a CAP. A CAP that supports CAP development, hence
called META-CAP. The objective of this paper is to introduce the META-CAP as a
design artefact. Section 2 provides a background on CAP. Section 3 contains the
motivation and description of the META-CAP architecture and Section 4 an
evaluation from the perspective of socio-technical design.
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2. Collective Awareness Platforms
In this section, we briefly review the notion of Collective Awareness Platform (CAP).
CAP is a particular kind of collaborative tool aimed to support social innovation.
However, it can also be viewed as a solution pattern for cooperative systems in
general. It is a pattern that is particularly suitable in the new era of Smart Computing
[B09] and Big Data.
2.1 CAP and data-driven innovation
Collective Awareness Platforms (CAP) were introduced as a concept by Fabrizio
Sestini from the EC [S12] and defined as ICT systems leveraging the network effect
(collective intelligence [MLD10]) for gathering and making use of open data from a
combination of sources including social media, distributed knowledge creation
systems and IoT. It has a strong focus on social innovation, sustainability and
participatory democracy. As such, CAPs are positioned primarily in the public or
semi-public sector. However, the leveraging of collective intelligence has also
potential value in industrial domains such as logistics where, for instance, timely
performance reports from various sources can lead to re-routing of transportations. It
is a bottom-up “grass-root” rather than top-down approach to collaboration. As
sharing of data from many heterogeneous and distributed sources becomes easier
large-scale collaboration becomes possible; not on the basis of predefined
collaboration processes (too slow, too inflexible) but because actors influence each
other through the shared data (pooled interdependence). An often mentioned example
is the sharing of energy consumption data (anonymised) in a neighbourhood. It has
been demonstrated that this can urge consumers to reduce their energy consumption.
However, CAP is a new concept. How CAPs will work in the real-world, or under
which conditions, it still unknown, as Sestini admits. For project-oriented
collaborations with a specific target, time frame and division of labour it seems to be
not a good solution.
Collaboration platforms already exist for a long time [M07,M13]. It is widely
recognized that collaboration is an important enabler of innovation. Many companies
currently struggle with a transition from a traditional in-company way of thinking to a
more open mind-set with the realization that by sharing data one does not necessarily
risk to lose but rather get an opportunity to win (open innovation, [Ch03]). CAPs
may indeed contribute to so-called “data-driven innovation” [J14,LA014]. Several
unsolved problems remains though: sharing data can be a sensitive issue and the value
of data is hard to establish. The legal and economic concerns of data sharing must be
addressed explicitly.
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2.2 CAP examples
As an example of an advanced CAP platform we consider the BIVEE project
described in [SS14]. BIVEE has used an approach based on semantic technologies to
enrich user-generated content with structured data and enable interoperability across
applications. The platform covers 3 phases: (a) monitoring and evaluating. Based on
sensor data and reconciled using semantic techniques, (b) triggering and developing.
Based on the output of the monitoring, in this phase, disruptive interventions are
identified, and (c) co-creating, in which ideas are designed and implemented in a
collaborative way. One technique used in the second phase is knowledge routing that
works as follows (cf. Fig.1). A document is detected, e.g. a web page. Using textual
analysis techniques a semantic annotation is produced, which is the basis for a
selection on relevance. Relevance is measured with respect to a given domain
ontology (or ontologies) and to a user profile (or profiles). A document that is relevant
to a user but deals with a lateral domain, may trigger lateral thinking, while a
document relevant to the user that is cross-domain may trigger discussions between
different participant groups.
Fig. 1 DIKW framework used in the BIVEE project [SS14]
2.3 CAP as a pattern
Although the term “Collective Awareness Platform” is recent, the idea of influencing
behaviour by sharing data has been around already for some time. We mentioned
platforms in a neighbourhood that collect energy consumption data from the
inhabitants and publish the data in aggregated form, to increase the energy awareness.
Another real example is a website that wants to stimulate elderly people to move, in
particular, to bike. People can upload their geo data, so that they can see on their app,
during biking, where they could meet another biker. What is new is the technical
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advancements that make the massive automatic collection of data and their analysis
substantially easier and cheaper than in the past. For that reason, the new term CAP is
warranted, in our view. The advantage of naming it in such a way is that it allows us
to examine the pattern in more detail and to see how it can be combined with other
patterns into innovative forms.
A prototypical CAP meets the following conditions:
(i) Behavioural data are collected automatically or semi-automatically from a
collection of subjects
(ii) The data are aggregated and analysed
(iii) Results are presented to the subjects with the goal of influencing their
behaviour. The influence is based on some form of social influence, rather
than hierarchy or market.
Variations of the prototypical pattern lift one or more of these conditions. For
instance, a group brainstorm system that meets conditions (ii) and (iii), but the input
data is not behavioural and not entered manually. We say that condition (iii) is the
most distinctive because any Smart Computing system [B09] meets the first two
conditions. We deliberately write “some form of social influence”. The energy
savings case makes use of benchmarking, but this does not play a role, for instance, in
the BIVEE case, where the aggregated results are used for collaborative
recommendation. In other cases, the influence takes the form of a shared mental
model (global picture). We expect that in the future the various CAP subpatterns can
be identified more succinctly.
3. META-CAP
We define a META-CAP to be a tool that enables social innovators to make effective
use of the CAP tools that already exist or to develop new ones. A key feature of a
META-CAP is the priority it gives to conceptual models [M07,W12]. Conceptual
models are popular in ICT and in all design science. The strong points of conceptual
models are:
abstraction. In complex situations, humans with bounded rationality cannot
progress without abstraction. In the case of CAP projects, it is important to
abstract from specific technology and process details in the first phases.
communication. A conceptual model, especially with a graphical representation,
facilitates sharing of ideas within homogeneous groups and across. This is even
more so when the conceptual model is built collaboratively. It stimulates the
formulation of a shared mental model.
reflection. Research in design has found out that conceptual models play an
important role in a “build and evaluate” iterative way of working [W12]. This
reflection support is even stronger when the models produced are executable in
some way, for instance simulation. This provides very rich evaluation
possibilities.
Conceptual modeling approaches have also been criticized. The models can be
hard to understand for some people. Despite their formal or semi-formal character,
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they cannot eliminate ambiguity completely, if this is desirable at all. Conceptual
modeling is not a priori the best solution in all cases but it is at least worth
investigating.
3.2 META-CAP models
Ultimately social innovation projects aim to create value. Hence the highest model
level that our META-CAP provides is value (encounter) modeling [A02,G05,W09].
Value modeling helps the innovators to abstract from how value is produced and
instead identify what the gains and losses are for whom. Value models include
economic models but have a broader scope – not only considering monetary value,
but also intangible values, like social esteem, meaningful relationships, and
knowledge. Value models are not only relevant for the exploitation but can and
should be made for all phases of an innovation project. If some phase is not
sustainable – does not provide sufficient value to all stakeholders – the whole project
will stop. It should be realized that sustainability is not only needed for projects with a
commercial goal, but also for volunteer networks or cooperative enterprises that want
to have a durable effect.
Fig. 2 Example value encounter (energy reduction CAP)
Fig. 2 is a simple example of a value encounter model. The central white box
represents the value encounter. The grey boxes represent actors, and the model shows
what they expect from the value encounter and what they contribute. The model
represents choices – for instance, that the energy provider is not included (perhaps
because that is too complicated for data protection reasons). The model represents
commitments – if this model is agreed upon by the participants of an early project
meeting, it means that the government commits a subsidy amount, for instance. This
is important for the web provider. The commitments raise the mutual trust. The model
also gives prompts – the value encounter is empty and should be filled by value
activities for which the inputs and outputs are already given. The model allows also
for other kinds of reflection – for instance, we know that subsidies are temporary, so
either the time span of the project becomes a topic of discussion or the value
encounter of Fig. 2 is seen as a transitional one to be followed by a situation where
subsidy is no longer necessary. Fig. 3 shows a global value encounter model based on
this reflection. The white spaces again represent value encounters. The actors
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involved in each value encounter are not shown. The global model only shows the
value encounters and their dependencies. The motivation to distinguish value
encounters, e.g. initiation vs. development, is that the group of actors involved is
different: local government is involved in the initiation, but not in the development.
Note that the value encounter modeling usually starts with a single value encounter,
like Fig. 2, and after reflection splits it up in multiple related value encounters, such
as shown in the global value encounter model. In Fig. 3 it is assumed that the
awareness project stops at some time, and then is followed by a situation that the
energy provider monitors the consumption data and makes it available in aggregated
format. However, it is only willing to do that when there is a reasonable customer
base willing to cooperate, and this is what the awareness project can provide.
Fig. 3 Global value encounter model
The second modeling level is collaboration modeling. Value is often created in
collaboration through co-creation [Ch03,B11]. In the course of time, an innovation
project includes several networks or communities, like the developer network and the
user network [M13]. These networks have to communicate internally and externally.
Collaboration models abstract again from the “how”, that is, from the information
technology used and also from information content, and focus on commitments and
their fulfillments in terms of actions that use and produce value.
Collaboration modeling makes use of collaboration patterns, in the sense of
“relatively stable solutions to recurring problems at the right level of abstraction,
making them concrete enough to be useful in a particular case, while also sufficiently
abstract to be reusable across cases” [M13]. A classical collaboration pattern is the
workflow transaction in DEMO [D06] based on the LAP workflow loops (Fig. 4, nest
page). The transaction consists of request/commitment (O-phase), execution (E-
phase) and reporting/closing (R-phase).
Socio-technical design patterns go beyond the more technical-oriented design
patterns in Software Engineering and Human-Computer Interaction. Collaboration
patterns help innovation groups in finding effective ways of working together given
the goals they want to achieve. Lessons learned can be laid down and made
transferable by means of patterns as well. Fig. 5 (next page) is taken from [PF07]
where collaboration patterns are described as part of a collaboration ontology. It is
assumed that the patterns are also defined on different levels of abstraction.
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Fig. 4 Example collaboration pattern: the standard transaction pattern [D06]
Last but not least, collaboration patterns can be related to tools that have proven to
be useful for support the specific kind of collaboration. In the case of CAP projects,
at least two groups of tools should be distinguished: CAP tools that are used by a user
community (where the collaboration pattern corresponds to some innovative social
practice) and tools used by a developer community in the development of CAP tools.
Sometimes, a tool can be in both groups. For instance, an argumentation support tool
like COHERE [BS08] can be used in an e-democracy setting to bring together
arguments from a large group of stakeholders, but it may be used also in a
development group that aims to develop a new CAP tool and wants future users to
participate in the design. Via the collaboration modeling and the link between
collaboration patterns and tools (described in a CAP registry), META-CAP also
supports CAP tool selection.
It has been recognized for quite some time that ICT is a powerful tool for
collaboration. There is a whole research area, CSCW, devoted to this. Virtual
communities are critically dependent on online collaboration. A lot is possible
nowadays just using standard social media technology. However, these tools are not
sufficient when communities want to get at a higher level of collaboration, such as
producing a report together, or a fair democratic decision making process [M07].
Fortunately, more advanced tools have become available. Without trying to be
complete we mention COHERE (see above); Mindmeister, a mindmapping tool and
crowdsourcing platform; Edgesense, a CATALYST tool for social network analytics;
and SciCafe2.0, for crowdsourcing and knowledge management. Apart from these
tools, there are many traditional methods that support specific types of collaborative
work, such as brainstorming, project management and collaborative design.
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Fig. 5 Collaboration stack [PF07], slightly adapted
Social innovation is a process in which new ideas are generated that not only meet
social or economic needs, but also create new social relationships and collaborations
[M10]. Balancing creativity with rationale is essential in order to ensure that those
new ideas get generated and processed by the right combinations of stakeholders as
effectively and efficiently as possible [M13]. It has been found that collaboration
patterns can help community members specify customized systems that capture their
unique requirements, while reusing lessons learnt by other communities.
3.1 META-CAP principles
The META-CAP tool enables value modeling, collaboration modeling, and CAP
tool selection and configuration in an evolutionary, executable and value-sensitive
way. Evolutionary means that models are being built right from the beginning and get
refined in each iteration. If we consider the well-known NESTA social innovation
process phase model [M10], then we see that it starts with the phases prompts,
proposals and prototypes, followed by sustaining, scaling and systemic change. In a
naïve interpretation of this model, it is only in the fourth phase that the innovators
start thinking about the business model. Unfortunately, experience shows that this is
often too late. Trust is enhanced when participants can express and lay down their
expectations about value delivery right from the start. With an evolutionary method,
the participants are prompted to develop the value model and the idea concurrently.
During the process, it will be extended and adapted. The value model not only
considers the exploitation, but also the intended use context. The value (again, taken
in a broad sense) that users create in a future situation should exceed the value they
create in the current situation, and that not only for some stakeholders but for all. If
this is only the case after a systemic change, this new “system” should be modelled as
well. Not only the value aspect and the context aspect but also the technology and
legal aspect (e.g. management of sensitive data) should be considered right from the
start, and worked out in parallel in later cycles.
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Fig. 6 META-CAP to support evolutionary development of CAPs and knowledge
management
Evolutionary also means that META-CAP takes a long-term view on the
innovation project, and on the CAP use. Once a CAP is developed, it is monitored
(Fig. 6) so that it can be adapted or extended following the community needs. The
development process itself is the object of continuous monitoring and improvement in
a second-order management loop, in particular, by abstracting from the cases to new
or refined collaboration patterns, and in turn using these patterns to select and
configure the CAP.
Executable means that the models are actively used. We envision the META-CAP
platform as an online tool that is available to participants collectively in meetings and
off-line to each one individually. The models are stored and archived. They can also
play a role in configuring the platform. For instance, once the group has defined a
value model for the developers’ network, a collaboration space is created to which the
parties or roles modeled are given access with some basic communication tools.
Depending on the collaboration model they develop, more tools are added and
installed. This executability is an important distinction between META-CAP and the
way value modeling methods is done traditionally, where models are made for
discussion and analysis only
Value-sensitive design means that design decisions are related systematically to
values [P13]. For instance, the decision of the META-CAP users to select a
collaboration pattern for team formation can be positively related to the value “gender
balance” if the pattern explicitly includes a rule about the number of females. Value-
sensitive design is coherent with the META-CAP focus on value modeling and with
the end goals of social innovation. It does support the design decision process and
also traceability.
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Fig. 7 Architecture of the META-CAP tool
3.2 META-CAP architecture
Figure 7 depicts an architecture for a META-CAP tool. At the bottom level, the
platform layer provides basic web community support. META-CAP must be
multilingual to make it easily accessible for diverse user groups and provide protected
areas for each project. The data layer contains at least some standard functions (such
as a project database and user registry), a CAP tool registry, the collaboration pattern
library and the model repository. For the project-specific information, the database is
non-tamperable using versioning so that the database can function as a safe and
reliable archive. This is very important for enhancing trust. The integration layer
makes it possible to integrate external tools and configure the internal tools into the
project workspace.
Apart from the general META-CAP interface, that provides functions such as the
creation of a new project, we distinguish a modeling layer that contains the value
modeler and collaboration modeler, with graphical and form-based interfaces. The
project management wizard supports the project team in the steps they are
recommended to take and provides an overview of all project information.In the
background, the modeling layer contains a model quality checker that gives warnings
and recommendations. For instance, a value model that does not provide positive
value to all participants, is not sustainable. Pattern retrieval provides an intelligent
interface to the collaboration pattern library. The configurator makes models
executable by adapting the project workspace according to the model. This may imply
the deployment of an external tool. The system includes a Knowledge manager that
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supports the monitoring of projects for abstraction and improvement of the
collaboration patterns
3.3 Methodological support
The envisioned META-CAP platform provides methodological support. Two
levels of support can be distinguished: on an intra-project level (for some innovation
team) and on an inter-project level (for some governmental agency or organization
that supports many projects), and two support objects: knowledge management and
innovation management. Knowledge management support is relevant on both levels,
and can be built in into the Knowledge Manager (wizard style).
Collaboration patterns are the main vehicles here. The collaboration patterns
concern both the innovation teams and the intended CAP user communities.
Innovation management support is particularly relevant on the intra-project level, to
help the team in taking the steps needed for some phase. The methodology makes
heavy use of value modeling, and includes value encounter templates for different SI
phases (initialization, development, exploitation etc.). The Value modeler
incorporates the methodological support by means of wizards and the Model Quality
checker.
4. Evaluation
Socio-technical systems design is an approach to design that consider human, social
and organizational factors as well as technical factors in the design of organizational
systems. A CAP is typically a socio-technical system [BS11]. To what extent does
the META-CAP support socio-technical design?
Since its inception in the ‘70s several socio-technical design methods have been
developed but their uptake has been disappointing [BS11], for which several reasons
can be given. According to [M06], humanistic ideas will always keep their relevance.
[BS11] more pragmatically argues that we still see many IT projects fail “because
they do not recognize the social and organizational complexity of the environment in
which the systems are deployed”. Introducing an Information System involves both
technical development and organizational change, and the link between these two is
often too weak. To overcome this problem, [BS11] pleads for constructive
engagement and sensitization. To what extent does the META-CAP support these
elements?
Constructive engagement means that the socio-technical aspect is integrated in the
technical development and change management processes. It means (more) attention
to the problem definition in the requirement collection phase. It also means, according
to Baxter, that during the construction process technical and social aspects are
considered together, and that there is evaluation. Having a META-CAP that supports
the CAP construction clearly fosters constructive engagement, and radicalizes the
notion of evaluation. Rather than saying that after the project is finished, some
evaluation must be done, META-CAP asks from the participants to define their value
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indicators in an early stage, and ensures that procedures are in place to adapt the
system on the basis of continuous value monitoring (evolutionary principle).
Sensitization means that (all) stakeholders are made aware of the social
implications of design choices and the different, often conflicting, perspectives that
have to be reconciled. There are several ways to do sensitization, e.g. using workplace
vignettes. We claim that the META-CAP is also a sensitization instrument, as it
pushes the stakeholders to express their expectations in terms of value and gives them
an instrument to see whether these expectations will be met. Admittedly, the value
perspective includes some abstraction. It is not a good instrument to analyze how
work procedures are changed. However, it may be that one of the problems of socio-
technical design is that it has focused too much on this operational level. Resistance
to change is not only because people do not want to change but also because people
fear the consequences in terms of loss of value.
Other ways in which META-CAP address the socio-technical research challenges
expressed in [BS11] are: the use of modeling and abstraction; the use of learning and
organizational memory systems (not isolated, but integrated so that they are actually
used); knowledge transfer between organizations; tool support.
Traditionally, an important concern for socio-technical system design was the
problem of dull “inhuman” routine work created by industrialization and automation.
In the current Smart Computing era, much of this routine work is disappearing
because it is taken over by sensors, effectors and robots. Information overload is a
growing problem, but is mitigated by new intelligent techniques (e.g. information
fusion, visualization). However, in the background, there have always been social
problems of power differences and exploitation. These social problems are obscured
if the focus is on the technology only. They are not solved just by a tool, but a
reflective, participatory and value-sensitive design approach can help.
The META-CAP approach does not need to be confined to CAP development but
can be generalized. Our claim is that any application that involves multiple
stakeholders – any socio-technical system, we could say – will profit from a META
approach.
5. Conclusion
In this paper, we have described the idea of a META-CAP as a tool that can support
CAP systems in their development and evolution. In contrast to current business
model or value modeling approaches, such as BMO and e3value, META-CAP not
only gives modeling support in the early phases for models that are thrown away in
the next step of the development cycle, but a mechanism for continuous reflection.
We conjecture that a META-CAP solution pattern is applicable in a wide range of
multi-stakeholder information systems.
The further development and evaluation of META-CAP gives rise to many
research questions. What value does the META-CAP actually add and under which
conditions? What is a good representation for collaboration patterns? A specific
research question to be addressed relates to CAP platforms [S12, A14]. What kind of
collaboration patterns are possible that make effective use of collective awareness (cf.
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Proceedings of STPIS'16
[MLD10]? In what sense do these patterns differ from collaborations without
collective awareness? How to make males perform as well as females in collective
intelligence?
The power of social innovation has been recognized by government agencies and
researchers for quite some time. The Open Book of Social Innovation [M10]
represents a milestone in the maturing of the field. Many examples of successful
projects contributing to important social goals such as sustainable growth, gender
balance, and security are now available. At the same time, many projects also fail or
run against economic and legal barriers (e.g. [S13]). The challenge for the social
innovation field is to go beyond the development of creative ideas [H14]. Ideas must
lead to implementation and change. It must be realized that social innovation is a
socio-technical process that requires both technology (sometimes technology not
existing yet) and social change, not isolated but within a concrete economic and legal
context [W12] The META-CAP architecture suggests a tool and methodological
support that can bring innovation groups to a higher level of efficiency and
effectiveness.
References
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White paper presented at Transparent Enterprise, Madrid, 2002.
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2014. Collective Awareness Platform for Sustainability and Social Innovation: An
Introduction (downloadable from EC website)
[B09] Bartels, A, 2009. Smart Computing Drives The New Era of IT Growth. Forrester.
[B11] Baldwin, C., and Von Hippel, E., 2011. Modeling a paradigm shift: From producer
innovation to user and open collaborative innovation. Organization Science, 22(6), pp.
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