Exploring the Impact of Motivations on the
Attraction of Innovation Roles in Open
Innovation Web-Based Platforms
By Cinzia Battistella, Fabio Nonino
Originally presented at 2011 World Conference on Mass
Customization, Personalization, and Co-Creation:
Bridging Mass Customization & Open Innovation
November 16-19, 2011
San Francisco Airport Marriott Waterfront
All material in this document is the intellectual property of Technology and Innovation Management
Group at RWTH Aachen University and/or the respective author/owner. Any copying, distribution,
quotation, publishing, public displaying or other use needs the express written permission of the
respective owner of rights. © 2011, RWTH Aachen University, www.tim.rwth-aachen.de
Exploring the impact of motivations on the attraction of innovation roles in
open innovation web-based platforms
Abstract
Recently a high number of new innovative enterprises
faced different competitive markets by promoting
innovation both in products and services through
open innovation web-based platforms, which allow
the collaboration of individuals and companies and
the so-called crowdsourcing.
A key issue concerns the identification of the most
important motivations which could attract users with
a specific role to proactively participate and
contribute in the open and collaborative innovation
processes. The paper, after having highlighted the
theoretical background, grounded on a rich
psychological and sociological literature on
motivations in collaboration, proposes the results of
the analysis of 26 OIPs based on a multiple research
methodology (multiple case study, factor analysis and
multi-dimensional scaling) and discuss the effects of
“motivational systems” and platforms models on the
attraction of the individuals characterised by
different innovation roles.
1. Introduction
The recent history of innovation has shown a
progressive change on collaboration models enabled
and facilitated by the Internet: from models called
distributed resources, shared mails, discussion
groups, allowing access to multiple individuals to
contents in web pages, portals and intranet to more
advanced models as open source, peer to peer, wikis,
crowdsourcing, virtual communities and web-based
platforms (Aalbors et al. 2008). These new models
have grown up thanks to the democratization of the
information accessibility and the lower cost of
communication, production and distribution of the
content in Internet (Howe 2006, 2008). This is one of
the most important trends changing the way
knowledge can be shared and the way it contributes
to the innovation process.
In this paper we take in consideration the open
innovation (web-based) platforms (OIP), one of the
most advanced and most recently diffused
collaboration models, useful to aggregate different
members in an innovation community and to open up
the innovation process of companies. These platforms
empower creativity to solve potential problems and
issues (Parameswaran and Whinston 2007), help
social interactions and coordinate people. The
platforms support business thanks to a wide access to
contributors and experts (von Krogh and von Hippel
2006, Füller 2006) and a closer proximity to
customer (Jeppesen and Frederiksen 2006, Fleming
and Waguespack 2007) and they act as intermediaries
helping
in
problem
solving,
coordinating
contributions and enabling cooperation (Surowiecki
2004).
The innovation process is strongly based on
committed people, who have enthusiasm and selfmotivation to the idea or are at least convinced by an
external incentive (Amabile 1998, Wallin and von
Krogh 2010). This is true also for the open
innovation process that happens in these OIPs
(Antikainen et al. 2010). Therefore, a key issue
concerns the identification of the most successful
strategies for driving motivations which could
encourage users to play an active role in the contents
development. Moreover, a rich stream of literature
concentrated on the roles that people play in a general
innovation process (Hering and Phillips 2005, Hölze
et al. 2010), for example the trigger of innovation,
the facilitator, the gatekeeper, etc. Key aspects of
open innovation web-based platforms are:
 the reasons for the participation and contribution
in an open innovation community;
 the innovation roles attracted by open innovation
web-based platforms;
 the relationship between motivations and roles.
But research related to studying the effect of
motivations to the participation of the individuals
characterised by different innovation roles, especially
from the point of view of the recent community
models enabled by the world wide web, still presents
gaps. This research intends to fill this gap and add to
the current body of literature on community models
and open innovation web-based platforms. The paper
shows the investigation of the different motivational
system and of the innovation roles in 26 platforms.
Thanks to a factor analysis and a multi-dimensional
scaling analysis, this study provides insights on the
motivations determining the attraction of people with
specific innovation roles. The broader aim of the
research is to provide academicians and community
managers insights on how to design OIPs to attract
potentially innovative participants.
The present paper, after the review of the
theoretical background, grounded on a rich
psychological and sociological literature on
motivations in collaboration driven by incentives and
rewards, explains the research aim and design,
showing the sample of the web platforms analysed
and the variables chosen for the classification and
describing the factor analysis and multi-dimensional
scaling methods. Then, the results of the analysis of
26 OIPs are shown, presenting a systemic description
of the effects of their motivational system. Finally,
we discuss the empirical findings of our study and
describe practical implications.
2. Theoretical background
The success or failure of an attempt at
crowdsourced innovation lies with the community
managers’ ability to motivate contributors’
participation (Antikainen et al. 2010, Wallin and von
Krogh 2010). It is therefore fundamental to
understand how to stimulate users and companies
participation in OIPs and a proactive knowledgesharing in their innovation process.
As in any social community connected to the
innovation process, there are different roles people
can play during the process. And every role is pushed
by peculiar motivations. Therefore, it is important to
understand the specific motivations as keys for
attraction of a specific role.
2.1 Motivational system
The motivation is a stable psychological force
within individuals that activates goal-directed
behaviour (Kanfer 1990). According to Ryan and
Deci (2000), “to be motivated means to be moved to
do something”.
Behavioural motives can be divided into intrinsic
and extrinsic (Deci 1972):
 Intrinsic motivation is associated with the
motivating potential of the task itself: the activity
is valued for its own sake and it is the best
reward for doing something. The motivation
comes from within the person, from the pleasure
of working on the task or the satisfaction in
completing a task (Ryan and Deci 2000). In the
OIPs context, intrinsic motivations are for
example fun and enjoyment in working in a
challenging and innovative task, because people
feel passionate about the activity (Chen and
Francesco 2003).
 Extrinsic motivation comes from outside the
person (Ryan and Deci 2000). In its purest form
is based on the prospect of receiving a
compensation for performing a task: the reward
is separable from the task itself. Financial
compensation is an extrinsic motivation that can
motivate innovators (Amabile 1998). In the
empirical context of this study, the participants
could expect to be awarded with the cash prizes
promised for developing concepts for innovation
challenges or to gain a recognition and power in
their company.
What motivates the innovators? A rich stream of
literature has suggested different motivations that
push people to participate and contribute to web
communities (e.g. Hars and Ou 2002, Lerner and
Tirole 2002; Lakhani and von Hippel 2003, Roberts
et al. 2006) and recent studies have shown the impact
of motivations in participation and, in turn,
innovation-related performance. Since the motivation
of participants to contribute to community based
innovation in Internet has already been investigated,
we reviewed, adapted and enrich existing lists of
motivations (Von Krogh et al. 2008, Antikainen et al.
2010, Antikainen and Vaataja 2010). In a previous
study, Avenali et al. (2010) divided intrinsic
motivations in individual ones and social ones and
extrinsic motivations in economic, individual and
social ones. Economic motivations refer to all
behaviours that conduct to a direct or indirect
economic advantage. Individual motivations concern
the psychological sphere of individuals and their
reputation. Social motivations refer to actions that
derive from the social influence of the community.
The complete list of motivations is provided in Table
1, which is the framework that we used for the
analysis of the motivations of the 26 OIPs.
The existing research on individual motivations
has been driven by the question why users voluntarily
contribute to virtual communities (Füller 2006, von
Krogh and von Hippel 2006). Prior empirical work
has concentrated on providing descriptive findings on
the contributors’ evaluation of these motivations.
These studies have advanced the understanding about
the motivations that contributors to communities
perceive to be dominant. Nonetheless, we know from
the rich body of motivation research that motivations
need to be linked to specific behavioural traits of the
persons and in particular to the roles a person
assumes in a specific context of the innovation
process. In the context of this research this may
imply that some motivations, although important
from one contributor role’s perspective, are only
weakly associated with other roles of innovators
participating in the internet platforms. Hence, a key
challenge for OIPs’ managers is to understand how to
attract, give impulses and maintain innovators.
2.2 Innovation roles inside open innovation
platforms
The organization of the innovation process and in
particular the people driving the innovation are
deemed particularly important for the success of the
innovation process. Witte (1977) identified the
innovator roles and several studies deepened the
analysis identifying their personal traits (Griffin et al.
2009) and their behaviour (Howell 2005) and
enlighted their importance for innovation and
creativity (Amabile 1998).
The literature on innovation identifies different
roles that are played by individuals in the innovation
process. The champion of innovation is based on a
single person with a single role that puts himself in
the first line to generate ideas, transform them into
innovation and commercialize them to the market
(Howell et al. 2005). The promoter role refers to
people that support innovation (Witte, 1977), it is
based on four main roles: expert promotor, power
promotor, relationship promotor and process
promotor (Gemünden et al. 2007, Hölzle et al. 2010).
Moreover, very recently a new and important role has
emerged: the opponent or challenger. Finally, other
researchers have shown other roles, that can be seen
as a subdivision of these roles or a combination of
them (e.g. the “devil’s advocate” who is a
combination of champion and opponent role).
The roles we selected for our research are the
most general ones, as shown by the german literature
(Gemünden et al. 2007, Hölzle et al. 2010): they are
shown and described in
Table 2. This table will be used as a framework
for the investigation of the roles in the OIPs.
In this study, we build upon these two literatures
by deepening the analysis of the relationship between
motivations of OIPs and the innovators’ roles.
Literature seems to not face directly the problem.
Some considerations can be obtained by linking
different researches. For example, in general,
champion or expert roles seem to depend heavily on
intrinsic motivation (Amabile 1998, Frey and
Osterloh 2002), whereas more entrepreneurialoriented roles seem to be more connected to extrinsic
motivations (Westhead and Wright 1998).
3. Research Strategy
3.1 Research aim
Our research would like to investigate the
relationship among the different forms of
motivational system in OIPs and the specific
innovation roles described in the previous section.
Literature, in fact, found the motivations that
generally impact on participation (e.g. Roberts et al.
2006), without discussing their use referring to
specific roles of the people involved in the innovation
process inside the web-based platforms. Our paper
would like therefore to answer and discuss the
following research question:
RQ: What are the innovation roles attracted by
specific motivational systems inside open innovation
web-based platforms?
We chose to follow a multiple research
methodologies of multiple case study, factor analysis
and of multi-dimensional scaling.
3.2 Identifying the state of the art of OIPs
This work empirically investigates the state of the
art of the motivational systems of the OIPs through
an analysis of 26 open innovation web-based
platforms, deemed particularly relevant for the
purposes of the study. A critical first step in
uncovering the underlying structure of motivational
systems is the identification of most representatives
OIPs models.
The sample was selected starting from the list of
the P2P foundation1 and other lists of potential
services based on open source and open innovation
(open innovators list2). To identify the state of the art
of web-based collaborative innovation, we restricted
our analysis to the 26 OIPs most influential in terms
of participation, those where the concept originated
(as in the case of Innocentive) and the most
comprehensive in terms of possibilities given to the
innovators (as in the case of Ideawicket that helps in
scouting for technologies). To evaluate the impact of
open innovation platforms on the World Wide Web,
we used the woodrank indicator because it is one of
the most comprehensive ranking tools (i.e. it does not
measure performance only on participation, or sites
linking in, etc. but using a set of more 50 indicators).
To this end, we ordered this panel of OIPs according
to the average woodrank.
In OIPs, stakeholders contribute and collaborate
around ideas, propose new concepts and trends,
present solutions to win challenges and to answer
companies’ needs. When used by a firm, the platform
can be based on the contributions coming from
internal communities and/or external communities. In
1 http://p2pfoundation.net/Product_Hacking
2http://www.openinnovators.net/list-open-innovationcrowdsourcing-examples/
this research, we did not consider OIPs clearly owned
by a company, used for only internal business
purposes (to form an internal community of
employees) and not opened to external interactions.
Table 3 shows the list of the considered OIPs,
their classification in terms of popularity, a brief
description of their characteristics and the typology
of innovation (closed, collaborative, based on
challenges or on open source principles).
3.3. Multiple case study
The main characteristic of the case study
methodology is to be able to carry out a very detailed
and contextual analysis of a number of events and
situations and possible relationships that exist
between them. Another important characteristic is its
adaptability to various contexts: from organizationalmanagerial to the social one. Moreover, it is
particularly significant and explanatory when the
object of analysis has features that make it highly
complex, and when the study may lead to a widening
of theories or to a strengthening of the conclusions
that were made through other typology of researches.
The use of multiple case studies, and especially of a
high number of cases, is recommended to develop
research in this context, because it is more difficult to
discuss a number of common conclusions without
considering exceptions as in the individual case
studies or otherwise in a limited number of case
studies (Yin 2003, Eisenhardt and Graebner 2008).
We choose two main areas of classification to
examine the websites and highlight the constitutive
characters: (1) the motivations and (2) the roles.
We gathered the data by empirical observation
and an in-depth and systematic analysis of the
websites. In order to reduce the subjectivity of the
analysis of motivations and roles, web experts,
innovation experts, community members and
websites’ designers have been involved in a Delphi
study. They commented on the motivations and roles
of the OIPs and evaluated if they were present or not
in the website.
The use of multiple case studies methodology
requires to define a research protocol selected in
order to make a comparison and an aggregation of
data collected. The protocol of the analysis was
therefore constituted of the following parts:
 general description: aim of the website,
objects, stakeholders, opportunities, etc.
 motivations: starting from the framework
previously proposed on the basis of
theoretical considerations in open innovation
platforms, we report all motivations
identified by direct analysis of the website.

roles: individual and companies belonging
to the community or addressees of the
invitation to collaborate
3.4 Factor analysis and multi-dimensional
scaling
The next logical step has been to resume all the
motivations and the roles inferred from the in-depth
analysis of individual sites in a matrix and study their
relationships in terms of motivations pushed thanks
to the factor analysis and multi-dimensional scaling
methods.
The factor analysis is a valuable method to
discover a phenomenon’s underlying structure in
terms of changing degrees of affiliation among
entities belonging to the same context. In our
research we used it to determine the similarity among
OIPs starting from the assumption that if two
platforms drive the same motivations, they are related
by research of the same innovation roles (or the same
business model based on the research and
aggregation of the same innovation roles).
The more motivations they have in common, the
stronger the similarity and the more likely they
belong to the same business model.
We started from the n x m binary incidence matrix
(OIPs – motivations) obtained from the in-depth
analysis of motivations pushed by the OIPs and
converted it a raw n x n co-motivations matrix, a
square matrix, with rows and columns representing
the OPIs in the sample and cells representing the
number of times each pair of OIPs push the same
motivation. Then we converted the raw co-motivation
matrix into a matrix of Pearson’s correlation
coefficients where correlation coefficients represent a
measure of similarity between two OIPs. The
correlation coefficients are a better basis for the
successive statistical analyses as they make possible
the data standardization and reduce the number of
zeros. The last steps of our analysis implicate
applying two multivariate techniques to analyse the
data, and interpreting the findings: the factor analysis
and the multidimensional scaling (MDS).
4. Results of the analysis and discussion
As motivations and roles are part of a coherent
business model that a company can build in order to
set how to do business, the platforms build a coherent
motivational system to attract some typical roles to
facilitate, enhance and speed up their innovation
process.
INDIVIDUAL
ECONOMIC
SOCIAL
INTRINSIC
Table 1. Intrinsic and extrinsic motivations in the OIPs [adapted and improved from Avenali et al. 2010]
MOTIVATION
Entrepreneurial mindset
Opportunity to express
individual creativity
DESCRIPTION
This motivation refers to the natural entrepreneurial propensity of the individual.
This motivation refers to the possibility given by the platform to express the individual creativity
and “artistic” talent (often limited by the routine working).
AUTHORS
Tapscott and Williams (2006)
Amabile et al. (1994); Ryan and
Deci (2000)
Care for community and
attachment to the group, sense
of membership
This motivation rises from the sense of membership and companionship that is the interior necessity
and the human natural tendency to join a group, to feel ourselves part of a community and to
assume our responsibilities towards other members.
Stallman (1999); Stewart and
Gosain (2006);
Nardi et al. (2004)
Kinship
Hars and Ou (2002); Hemetsberger (2004); Hertel et al. (2003);
Lakhani and Wolf (2005); Zeityln (2003).
Altruism
Bitzer et al. (2007); Ghosh, (2005); Hars and Ou (2002); Hemetsberger
(2004); Osterloh and Rota (2007); Haruvy et al. (2003);Wu et al.
(2007).
Enjoyment, fun and
entertainment
This motivation refers to the fun and the personal pleasure that comes in doing what we like.
Wang and Fesenmaier (2003)
Benkler (2002); Hemetsberger (2004); Herkel et al. (2003); Lakhani
and von Hippel (2007); Lakhani and Wolf (2005); Luthiger and
Jungwith (2007); Roberts et al. (2006).
Psychological compensation
and sense of efficacy
This motivation refers to the feelings that people may experience by participating and contributing
to the achievement of shared projects, gaining awareness of their influence, and a personal
“revenge” when individuals feel overlooked or underestimated (especially in working environment).
Nardi et al. (2004)
Sense of cooperation in the
area of interest
Individuals feel obliged to contribute and to cooperate for the development of their area of interest.
Wang and Fesenmaier (2003)
Social Responsibility
Individuals feel motivated by ideals linked to the sustainability.
Benby and Belbaly (2010)
Monetary rewards
Free products (HW and SW)
Free Services
Monetary rewards are, by definition, the classic reasons for which individuals offer performance,
time and talent; as a matter of fact there is a positive correlation between the intensity of
contributors’ participation in collaborative projects and amount of money received.
Free products are “surrogate” of monetary rewards as they correspond to an economic benefit for
contributors; they are also physical products or software realized thanks to contributions received by
the community.
Services are usually associated with hardware or software developed; but often additional services
to the “base package”.
Learning
The learning motivation refers to the individuals’ goal to increase their competences and to acquire
new skills.
Reputation
Enhancing the own reputation helps to improve and increase the “value” of the individual work and
reach new levels of professionalism that could improve the economic condition
Anderson (2009); Tapscott and
Williams (2006)
Anderson (2009); Tapscott and
Williams (2006)
Anderson (2009); Tapscott and
Williams (2006)
Benby and Belbaly (2010);
Bowman and Willis (2003)
Von Krogh et al. 2008
Antikainen et al. 2010; Antikainen and Vaataja, 2010
Aalbers (2004); Kollock (1999).
Altruism
Aalbers (2004); Zeityln (2003).
Aalbers (2004; Nov (2007); Torvalds and Diamond (2001); von Hippel
and von Krogh (2003),
Recreation
Ridings and Gefen (2004)
Sense of efficacy
Bandura (1995), Constant et al. (1994); Kollock (1999).
Ideology
David et al. (2003); Ghosh, (2005); Hemetsberger (2004); Herkel et al.
(2003); Lakhani and von Hippel (2007);Lakhani and Wolf (2005).
Benkler (2002); Ghosh, (2005); Herkel et al. (2003); Lakhani and Wolf
(2005); Lattemann and Stieglitz (2005); Luthiger and Jungwith (2007);
Roberts et al. (2006).
Own use
Bitzer et al. (2007); David et al. (2003); Ghosh, (2005); Hemetsberger
(2004); Herkel et al. (2003); Lakhani and von Hippel (2007);Lakhani
and Wolf (2005); Lattemann and Stieglitz (2005); Osterloh and Rota
(2007); Roberts et al. (2006); Wu et al. (2007).
David et al. (2003); Ghosh, (2005); Hars and Ou (2002); Hemetsberger
(2004); Lakhani and Wolf (2005); Roberts et al. (2006); Spaeth et al.
(2008); Wu et al. (2007); Ye and Kishida (2003).
Interesting objectives and intellectual stimulations
Amabile (1998); Hagel and Armstrong (1997); Ridings and Gefen
(2004); McLure Wasko and Faraj (2000).
Ideology
Nov (2007).
Aalbers (2004); McLure Wasko and Faraj (2000).
Need, software improvements and technical reasons
Jeppesen and Frederiksen (2006); Kollock (1999); Ridings and Gefen
(2004).
see Social Capital
EXTRINSIC
PROFESSIONAL
Peer recognition
Recognition of the company
and growth of professional
status – career benefits (for
OWIPs used inside
corporation)
Reciprocity
SOCIAL
Individual accountability
Enhancing the own reputation and receiving special merit awards from the company helps to
improve and increase the “value” of the individual work and reach new levels of professionalism
that could improve the economic condition; in an open-source community individuals gain “respect,
reputation and credibility”, both in the eyes of other participants and both in the company where
they work and this status can be exploited in the workplace in order to improve the professional
status.
Reciprocity represents the possibility of establishing with a community a continuous and durable
exchange relationship over time.
Increasing the level of individual responsibility, the contributors feel compelled to “do well” and to
succeed in a project; the contributor feels a sort of obligation towards those who respected and
trusted her/him by giving her/him great responsibilities.
Bowman and Willis (2003)
Ghosh, (2005); Hars and Ou (2002); Hemetsberger (2004); Herkel et
al. (2003); Lakhani and von Hippel (2007);Lakhani and Wolf (2005);
Lattemann and Stieglitz (2005); Lerner and Tirole (2002); Roberts et al.
(2006); Spaeth et al. (2008).
Career
Benby and Belbaly (2010)
Raymond (1999)
Benby and Belbaly (2010)
Ghosh, (2005); Hars and Ou (2002); Hemetsberger (2004); Herkel et
al. (2003); Lakhani and Wolf (2005); Lerner and Tirole (2002); Roberts
et al. (2006); Wu et al. (2007).
Bergquist and Ljungberg (2001); David et al. (2003); Hemetsberger
(2004); Lakhani and von Hippel (2007);Lakhani and Wolf (2005).
Hargadon and Bechky (2006); Lerner and Tirole (2002).
Reputation and enhancement of professional status
Aalbers (2004); Bagozzi and Dholakia (2002); Dholakia, Bagozzi &
Pearo (2004); Hargadon and Bechky (2006); Lerner and Tirole (2002);
Lakhani and Wolf (2005); Rheingold (1993); McLure Wasko and Faraj
(2005).
Firm recognition
Jeppesen and Frederiksen (2006).
Aalbers (2004); Kollock (1999); McLure Wasko and Faraj (2000).
Sense of obligation to contribute
Benby and Belbaly (2010)
Bryant et al. (2005); Lakhani and Wolf (2005).
Knowledge exchange, personal learning and social capital
Social capital
This motivation refers to the set of interpersonal relationships, formal and informal, are essential for
the community functioning.
Bowman and Willis (2003); Wang
and Fesenmaier (2003)
Antikainen (2007); Gruen et al. (2005); Ridings and Gefen (2004); von
Hippel and von Krogh (2003); McLure Wasko and Faraj (2000); Wiertz
and Ruyter (2007).
Table 2. Roles in the innovation process
ROLES
DESCRIPTION
CHAMPION
The champion model focuses on one single role assuming that one outstanding individual supports all the innovation process.
EXPERT PROMOTOR
The expert promotor has specific technical knowledge to advance the idea, to find new solutions or to refine the proposed solution.
POWER PROMOTOR
RELATIONSHIP PROMOTOR
The power promotor has the necessary hierarchical power to drive the project, to provide needed resources, and to help to overcome any resource related
obstacles which might arise during the course of the project.
The relationship promotor who has strong personal ties not only inside but especially outside the organization, i.e. to customers, suppliers, and research
partners, facilitates inter-organizational cooperation.
PROCESS PROMOTOR
The process promotor derives his influence from organizational know-how and intra-organizational networks. He makes the connection between the power
and the expert promotor and has the necessary diplomatic skills to bring together the people needed for the innovation process.
OPPONENT
The opponent role challenges innovation projects to increase the quality of their output.
REFERENCE
Gemünden et al. 2007; Griffin et al.
2009; Hölzle et al. 2010
OTHER NAMES
Trigger / Idea generator
Leader
Hölzle et al. 2010
Gatekeeper
Scouter
Facilitator
Rohrbeck and Gemünden 2010
Strategist / Orchestrator
Antagonist / Challenger
FURTHER DESCRIPTION
The initiator role increases the number
of innovation concepts and ideas.
The facilitator tries to build an organization and
connections to facilitate innovation.
The strategist role explores new business fields.
-
Table 3. Open innovation web-based platforms [A = Closed innovation; B = Collaborative innovation; C = Challenge innovation; D = Open source]
#
OIP’S NAME
WOOR
ANK
81
1
Elance
2
99designs
73,4
3
4
5
6
7
Zooppa
Topcoder
Crowd Spring
Idea Connection
Ponoko
71,4
70,3
68,5
64,4
63,7
8
Quirky
63,1
9
10
uTest
Guerra Creativa
61,5
61,2
11
Jovoto
57,4
12
Hypios
57
13
14
15
16
17
IdeaBounty
Enterprise Spigit
Presans
Ideaken
InnoCentive
55,4
54,7
54,7
51,6
50,4
18
InnoGet
49,6
19
20
21
22
23
24
25
26
RedesignMe
IdeaWicket
Brainrack
NineSigma
Palkoo
Innovation Exchange
Whinot
Big Idea Group
49
48,5
47,1
45,4
43,1
42,4
37,6
31,5
TYPOLOGY OF INNOVATION
A
B
C
D
x
INNOVATION PROCESS BRIEF DESCRIPTION
Elance let you find and hire people who can form a group and collaborate together
99design hosts a design context and helps you with a set of pre-packages of design. The process is based on a strong interaction with you (“Be sure to provide continual feedback to help the designers deliver a concept you love!”). At the
end you award the winner.
Companies’ involvement: virality, sharing and brand awareness.
Topcoder helps in building a software community.
Crowd Spring is a platform specific for design. You post a request, the world submit ideas and you choose the most preferred one. The platform helps in pricing and projects.
It is an intermediary platform helping in building a community of experts and in technology scouting. You can identify collaboration partners.
Ponoko is a platform specific for design. It helps both in making and selling and in buying. The innovation process is facilitated by the presence of tools and the possibility to contact other actors of the supply chain.
Quirky permits a “social developed product”. The platform helps you in identifying through community if your idea is good and then research, design and engineering it. If the presale succeeds, Quirky manufacture the innovation and you
and Quirky share earned money.
uTest is a platform that permits you to test your product for feasibility and usability.
Guerra Creativa is a crowdsourcing website where you can launch a design contest. The community is built by designers and you can choose your winner.
Great brands, non-profits organizations and Jovoto itself can launch contests. The best concepts in each contest win Community Prize Money, distributed by the community to the community. Contest initiators choose their favourite
and license the concept in agreement with the author. Your ability is rated, and you reach levels so you can enter first to public contests, then private, then tba ones.
Hypios combines intelligent crowdsourcing and expert identification. Applying advanced Semantic Web and Machine-Learning technologies, hypios identifies problem-solvers (Solvers) based on publicly available data on the Internet. It
then invites them to compete to solve specific Research & Development (R&D) challenges in their area of expertise.
Idea Bounty is a social think tank that provides a secure channel for the world-wide creative community to offer solutions to creative briefs.
Enterprise Spigit is oriented to the employees and the contacts already developed.
In Preasans you can connect to other experts and solve technological challenges.
Ideaken enables individuals and enterprises to collaborate to innovate in return of reward and recognition.
Innocentive is one of the most famous platforms of open innovation and crowdsourcing.
There are three possible innovation processes: challenge, inbox and outbox. Innoget reproduces the open innovation environment by favouring the posting of patents and technologies and the relationships among people especially form the
point of view of science and technology.
Redesignme supports the challenge for ideas or designs.
Ideawicket helps in scouting technologies, connecting people in specific fields, solving R&D challenges, hosting competitions
Innovations by students to companies.
Strategic advisory, intermediary services, intelligent services, OI process integration services, collaboration for sustainability
Palkoo is specific for design. You can post a challenge with a certain amount of money.
It is an online open innovation marketplace. It's where diverse community members from all over the world respond to challenges sponsored by Global 5000 companies and not-for-profit organizations.
Whinot participates in the project, deciding about consultants and about best solutions.
It supports the innovation from idea generation to execution.
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Table 4. Motivational system in open innovation web-based platforms
MOTIVATIONS
Entrepreneuri
al mindset
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
Elance
99designs
Zooppa
Topcoder
Crowd Spring
Idea Connection
Ponoko
Quirky
uTest
Guerra Creativa
Jovoto
Hypios
IdeaBounty
Enterprise Spigit
Presans
Ideaken
InnoCentive
InnoGet
RedesignMe
IdeaWicket
Brainrack
NineSigma
Palkoo
Innovation Exchange
Whinot
Big Idea Group
x
x
x
x
Opportunity
to express
individual
creativity
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Sense of
membership
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
INTRINSIC
Enjoyment,
Psychologica
fun
l
and
compensatio
entertainment
n
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
EXTRINSIC
Sense of
cooperation
Social
Responsibilit
y
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Monetary
rewards
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Free products
(HW and
SW)
Free Services
Learning
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Reputation
Career
benefits
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Reciprocity
x
x
x
x
Individual
accountabilit
y
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Social capital
x
x
x
x
x
x
x
x
x
x
4.1 Motivations and roles in the open
innovation platforms
Following the motivational system and the
innovation roles system frameworks presented in the
methodology section, we mapped the extrinsic and
intrinsic motivations (Table 4) and the roles (Table 5)
enabled by the OIPs.
4.2 Findings from factor analysis
Factor analysis is a method usually employed for
purposes of data reduction. In our research we used
factor analysis to classify the OIPs into related
groups (usually named factors) on the basis of
varying degrees of similarity. The factors include
relatively homogenous groupings of OIPs that may
represent a typology.
We used the principal components analysis as the
extraction method, varimax rotation of the extracted
factors to interpret the results and Kaiser’s criterion
along with a scree test to determine the number of
extracted factors. As shown in Table 6, the analysis
resulted in four factors, explaining 87.3% of the
variance. The factor loadings represent the
correlation between an OIP and the factor (the degree
to which the OIP belongs to that group/typology). We
decided to maintain factors loading greater than 0.4.
Loadings higher than 0.8 indicate high correlation.
To characterize the factors, we studied the set of
OIPs loading on each factor for similarities in
innovation roles attracted, since this is a key driver of
co-motivation frequencies. After an iterative process
of independent evaluations made by the two
researchers, we labelled the four factors as: (i)
Champion and Expert roles attractors; (ii)
Relationship role attractors; (iii) Process and power
roles attractors; and (iv) Process role attractors.
Factor 1 (Champion and Expert roles attractors)
comprises a central element of the open innovation
platforms: the search for an expert in specific fields
or a person who characterises and owns all the
innovation process. These platforms have normally a
business model that aims at attracting big companies
and no-profit organizations as solvers, supporters of
the platform or seekers. The companies’ involvement
is connected to give them a high-quality expertise in
very different fields. This group includes the majority
of the platforms in our panel (10 out of 26) and
includes very popular platforms, as Innocentive.
Factor 2 (Relationship role attractors) seem to be
characterised in terms of the importance given to the
set of connections and links of the platform. Among
the platforms loading on this factor, there is the
majority of the platforms that set a context for design
(e.g. Redesign me, 99designs). This because these
OIPs declare as fundamental the ability to connect to
a community of designers and to rely on these
connections in order to obtain the innovation.
Factor 3 (Process and power roles attractors)
refers to platforms characterised by a strong
intermediary role of the platform itself. These OIPs
therefore declare the need of roles for innovation as
the leader and the manager of the entire process.
These roles permit the OIP to participate in a sort of
“intermediate innovation”.
Factor 4 (Process role attractors) constitutes only
a minor part of the OIPs, as they are in our opinion
example of most advanced typologies of platforms,
as they are based on semantic web and automatic
search engines and support complex projects in the
scientific and technological fields. Factor 4 echoes a
theme found in factor 3, about the importance of a
role of management and organisation of the
innovation process.
4.3 Findings from MDS
MDS provides a graphical representation of the
similarity, or conceptual proximity, between the
objects of analysis (Kruskal and Wish, 1978) - in this
case the panel of 26 platforms analysed. Using
Pearson’s correlation coefficients, MDS generates a
bi-dimensional map, shown in Figure 1, in which the
position of each platform on the map depends on its
relationship to the other OIPs in terms of motivations
in common. The closer platforms appear on the map,
the more likely they are to have similar business
model and attract the same innovation roles.
MDS shows co-motivations links among all of the
OIPs analysed. The proximity within a group
indicates an internal consistency of the set of
platforms, i.e. the tendency to have the same
motivations. The majority of the platforms within the
different factors are clustered very tightly together,
indicating a similarity within the group. This suggests
close links in terms of their underlying business
model and innovation roles.
The axes of the graph also require content-based
interpretation. We used the position of the four
factors on the map to help with this, but also
examined the platforms in depth. Our consensusbased interpretation is as follows.
The x-axis juxtaposes the support of web (i.e. in
terms of semantic) or the platform itself to the
innovation process. This is illustrated on the left side
of the map, by the position for example of Hypios,
uTest, Preasans. At the edge of the right side, we
have platforms where the role of the platform itself is
less: it serves only as a window or a facilitator of the
community building.
The y-axis represents a continuum going from
individual innovation to social innovation as we
move from the top to the bottom of the graph: while
the first is much more based on the capabilities of the
single person in terms of capabilities and expertise or
in terms of relationships and “know-who-knows”, the
second is much more based on a participating
process, with more attention to organization and
process activities.
*Extraction method: principal component analysis with varimax rotation. Variance
explained: 87.3%. Only factor loadings higher than 0.4 are reported.
INDIVIDUAL INNOVATION
1
0,95
0,9
0,85
F1 – champion and expert roles
0,8
0,75
PLATFORM OR WEB SUPPORT
0,7
0,65
InnoGet
0,6
Table 5. Innovation roles in open innovation web-based platforms
0,55
Elance
F2 – relationship role
Enterprise Spigit
Opponent
Process promotor
Relationship
promotor
Power promotor
Expert Promotor
Champion
NO SUPPORT
0,5
ROLES
0,45
99designs
Big Idea Group
0,4
0,35
uTest
Zooppa
Quirky
0,3
0,25
Jovoto
RedesignMe
0,2
0,15
0,05
InnoCentive
Brainrack
Topcoder
Palkoo
0,1
NineSigma
Idea Connection
Ponoko
IdeaBounty
Guerra Creativa
0
Innovation Exchange
-0,05
Crowd Spring
-0,1
-0,15
Whinot
IdeaWicket
-0,2
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
Elance
99designs
Zooppa
Topcoder
Crowd Spring
Idea Connection
Ponoko
Quirky
uTest
Guerra Creativa
Jovoto
Hypios
IdeaBounty
Enterprise Spigit
Presans
Ideaken
InnoCentive
InnoGet
RedesignMe
IdeaWicket
Brainrack
NineSigma
Palkoo
Innovation
Exchange
Whinot
Big Idea Group
x
x
x
x
x
-0,3
-0,35
x
x
x
x
-0,4
-0,45
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
Elance
Enterprise
Spigit
InnoGet
Big Idea
Group
uTest
InnoCentive
Zooppa
Jovoto
NineSigma
Idea
Connection
Palkoo
IdeaWicket
RedesignMe
Ponoko
Guerra
Creativa
99designs
Quirky
Brainrack
Hypios
Presans
Whinot
Crowd Spring
Innovation
Exchange
Topcoder
IdeaBounty
Ideaken
Ideaken
F4 – process and power roles
x
x
x
x
x
x
x
F3 ‐ process role
Hypios
-0,5
0
x
x
x
x
1
SOCIAL INNOVATION
x
x
Figure 1. Multidimensional Scaling (circles on the map show
where the four factors identified in Table 5 are positioned on the
map)
x
x
5. Conclusions
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Table 6. Factors loading*
Open innovation
platforms
Presans
-0,25
Champion
and expert
roles
Attractors
0.856
Relationship
roles
attractors
Process
roles
attractors
Process
and power
roles
attractors
0.832
0.779
0.778
0.745
0.734
0.673
0.649
0.627
0.588
-0.530
0.499
-0.450
-0.635
-0.594
-0.527
0.413
-0.973
-0.896
-0.891
-0.884
-0.845
0.525
0.533
-0.736
-0.697
-0.560
-0.496
-0.463
0.895
0.810
0.409
-0.439
-0.809
-0.787
0.460
-0.740
0.539
0.563
-0.475
0.422
0.486
-0.684
-0.627
-0.579
In this article, we employed a combination of
techniques such as case study, factor analysis and
multi-dimensional scaling in order to understand and
try to make sense of two important factors
underlining the business models of open innovation
web-based platforms, i.e. the motivations and the
roles. A possible interesting further research direction
is therefore to study in depth all the elements of the
business model of the platforms.
Our aim was to deciphering the relationship
among choices regarding the motivations as attractors
of specific roles in the OIPs. We contributed to the
literature and the practitioners by suggesting some
ways to attract specific roles for the innovation
process. By mapping the network of motivations and
identifying roles dimensions, we find potential hints
for application. Therefore, we can highlight a set of
connections among motivations and roles. The
reputation, the career benefits and the reciprocity for
example can be a lever to attract the champion, the
expert and the power roles; while the individual
intrinsic motivations can be much more related to the
relationship role.
Identifying specific motivations for specific
personal traits of innovation roles can broaden our
understanding of the importance for innovation of
setting a peculiar system for peculiar needs. Our
findings suggest that the open innovation web-based
platforms lever on different motivations to attract
different innovation roles: this can provide insights
for further research and for design and management
of the OIPs platforms.
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