Crowdsourcing as a problem solving strategy

This paper was presented at The XXIV ISPIM Conference – Innovating in Global Markets:
Challenges for Sustainable Growth in Helsinki, Finland on 16-19 June 2013. The publication is
available to ISPIM members at www.ispim.org.
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Cheer the crowd? Exploiting crowdsourcing as a
problem-solving strategy
Miia Kosonen*
Lappeenranta University of Technology, School of Business, P.O.Box
20, 53851 Lappeenranta, Finland.
E-mail: miia.kosonen@lut.fi
Kaisa Henttonen
Lappeenranta University of Technology, School of Business, P.O.Box
20, 53851 Lappeenranta, Finland.
E-mail: kaisa.henttonen@lut.fi
* Corresponding author
Abstract: To gain more novel ideas and empower users to take part in
innovation activities, many organizations outsource problem-solving tasks to
voluntary crowds. Yet a significant body of current knowledge concerns the
characteristics of innovative users at the expense of the hosting organization
and its actions. By reviewing literature from the fields of innovation
management, knowledge management, marketing and e-commerce, our study
identifies 10 practices to facilitate innovation-related problem solving among
external crowds. Firstly, breeding user motivation calls for providing
stimulating tasks, giving timely feedback, encouraging interaction, rewarding
appropriately, building sense of community, and selecting the right
communication technologies. Secondly, putting crowd know-how into action is
facilitated by assessing the degree and distribution of crowd know-how,
specifying tasks appropriately, providing support for task interpretation, and
encouraging collaboration.
Keywords: Crowdsourcing; crowd; innovation; knowledge, knowledge
creation, problem; problem-solving; idea generation
1 Introduction
Today, many consumers want to create their own experience rather than solely being
passive recipients of a firm’s offerings. For instance, online communities provide spaces
where individual users may participate in developing and modifying products on an on-
going basis, thus becoming co-creators of valuable knowledge (Sawhney and Prandelli,
2000, Füller et al., 2007). Another form of engaging consumers is crowdsourcing, where
firms solicit input from voluntary users interested in the firm’s products or services
(Leimeister et al., 2009, Poetz and Schreier, 2012, Afuah and Tucci, 2012).
Crowdsourcing has been coined as “a strategic model to attract interested, motivated
crowd of individuals capable of providing solutions superior in quality and quantity to

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those that even traditional forms of business can” (Brabham, 2010, p. 79). However, the
transformation from company-driven innovation into more user-driven models may also
raise challenges which need to be addressed by both researchers and practitioners.
Managers can no longer rely on the “if we build it, they will come” principle. Pouring
money into different types of online platforms is wasted investment if managers do not
understand how users are motivated and enabled to contribute.
While there is a growing stream of studies focusing on the characteristics of the
individual users participating in the generation of the innovative output (Lee and Cole,
2003, Bagozzi and Dholakia, 2006, Jeppesen and Frederiksen, 2006, Mahr and Lievens,
2012) also in idea crowdsourcing (Zheng et al., 2011, Kosonen et al., 2012a), less is
known about 1) under which conditions and 2) using which kinds of management
practices firms may successfully apply crowdsourcing. For the former, a notable
exception is the pioneering study by Afuah and Tucci (2012), where the authors compare
three problem-solving mechanisms: solving internally, applying crowdsourcing, and
designating to an exclusive contractor. Based on their work, crowdsourcing in general has
the potential to improve the efficiency and effectiveness of problem solving “under
certain circumstances” (ibid., p. 355), which depend on the characteristics of the
problem, the knowledge required, the crowd, and the solutions to be evaluated.
However, an important question remains in how innovation managers outsource
problem-solving tasks to an external crowd: which types of actions does this require from
the hosting organization? In line with Santonen et al. (2012), we note how current
research on crowdsourcing has limitations from the innovation-related knowledge
perspective. Hereby, we make a basic assumption that there is a hosting organization –
either private or public-sector organization – aiming at having benefit from the proposed
solutions. To gain more benefit, there is a need to develop practical roadmaps not only
for assessing the potential of crowdsourcing (Afuah and Tucci, 2012) but also for
optimally facilitating problem solving among external crowds. As there is myriad of tasks
and areas of interest where crowdsourcing has been applied (see Brabham, 2008, 2010),
our study takes a narrower focus on types of problem-solving where new product ideas or
designs are solicited from voluntary users. We believe this setting is justified as new
product development and innovation-related tasks involve high degrees of complexity
(von Hippel, 1994), while they may also imply more potential value outcomes than
simple or routine tasks. The research question can be formulated as follows: how to
facilitate crowdsourcing and innovation-related problem solving within external crowds?
Due to the newness of the research area, the study is conceptual in nature. The
theoretical knowledge base related to crowdsourcing still seems to be in its infancy
(Santonen et al., 2012) and therefore it is important to combine knowledge from existing
research and adapt it to crowdsourcing settings. Building on the literature from the fields
of innovation management, knowledge management, marketing and electronic
commerce, our study critically assesses how to facilitate crowd participation in the idea
generation phase of the crowdsourcing process. To provide practical insight, we
incorporate three case examples to illustrate how crowdsourcing has been applied as a
vehicle for problem-solving and spurring innovation. Further illustrations are drawn from
four interviews conducted with the hosts of IdeasProject, which is a company-hosted site
for idea crowdsourcing.

2 Conceptual background
In co-creation, a company seeks innovative ideas and commentary on new technologies
and new improved products or services (Zwass, 2010). With our focus on innovation-
related problem solving, we thus consider crowdsourcing participants as innovation co-
developers (Chesbrough, 2003, Jeppesen and Frederiksen, 2006, Füller et al., 2007).
Building on knowledge-based theory of the firm, it has recently been argued that a
firm’s problem-solving effectiveness is key to organizational performance (Nickerson
and Zenger, 2004, Jeppesen and Lakhani, 2010). Firms need both the capability to select
high-value problems, and have them solved either through internal hierarchies of external
markets (Nickerson and Zenger, 2004). Hereby, a focal question is under which
conditions external solvers are able to produce better solutions than firm-internal agents.
Jeppesen and Lakhani (2010) refer to “broadcast search” as a process of disclosing a
description of a problem and inviting anyone deeming themselves qualified to solve such
problem to participate. This brings us to the concept of crowdsourcing. In general, it is
defined as “the act of taking a task traditionally performed by a designated agent (such as
an employee or a contractor) and outsourcing it by making an open call to an undefined
but large group of people” (Howe, 2008).
A common feature to all forms of crowdsourcing is that they depend on the
contribution by a certain crowd. Two main types of crowdsourcing initiatives are
integrative, where complementary knowledge from a large number of users is pooled
together, and selective, where competing users are identified and selected to give input
(Schenk and Guittard, 2009). Selective crowdsourcing typically takes the form of idea
contests, where the best ideas are selected and rewarded either materially or by giving
recognition (Zheng et al., 2011). This could also be labelled Tournament-based
crowdsourcing (Afuah and Tucci, 2012). Schenk and Guittard (2009) further distinguish
crowdsourcing initiatives based on the complexity of tasks. Routine-types of tasks may
involve e.g. data collection or identifying valuable pieces of information from a large
mass of data, such as in the case of a medical institute which outsourced identifying
cancer cells from tens of thousands of pictures. Complex tasks are related to problem
solving within innovation projects and require creativity, such as in the case of design
contests (Brabham, 2010) which involve a high amount of information and a broad set of
potential alternatives (information diversity). Complexity thus implies there are a high
number of elements and their multiple interrelationships involved in a task. In addition,
potential changes may happen to both elements and relationships during task execution
(Wood, 1986), reflecting its dynamic nature. At least a certain degree of complexity is
typical for crowdsourcing with an aim at solving innovation-related problems.
3 Three modes of crowdsourcing – case examples
Contest mode: InnoCentive.com
InnoCentive was launched in 2001. It is designed as a two-sided platform where IC’s
clients – solution seekers – may announce R&D related problems within a wide range of
scientific domains. Thereafter, the problem solvers enter into contests to compete against

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each other to find a winning solution, which is awarded a preannounced cash prize and
recognition. The solutions are submitted through the web and reviewed by the seeker,
who remains anonymous at least during the open phase. Potential solvers only need to
provide contact information, while also identifying degrees earned and areas of research
interest while registering as users. Similarly, providing solutions is easy, requiring only
uploading a word-processes solution written into a template. Currently, there are more
than 270,000 registered solvers from over 200 countries. (See Lakhani et al., 2007,
Jeppesen and Lakhani, 2010, Brabham, 2010)
Community mode: Lego Cuusoo
The Danish toy company Lego closely works with its fan community in order to develop
new designs and products. Lego Cuusoo was launched in 2008. It allows a cost-effective
way to search for new designs, and a wider community for ideation. Any user may create
a project in order to suggest a new product concept, which others may then vote for.
Those having 10,000 supporters have a chance to become official products. Original
contributors receive 1 % royalty of the net revenue of the designs chosen for production,
where Shinkai 6500 submarine was the first project completing the process. In contrast to
the contest mode, users do not directly compete with each other; instead, they share an
enthusiasm towards LEGO products and willingness to develop even more fascinating
designs. Such communities operate by freely accumulating and recombining ideas, and
also by voting on the best designs. (Boudreau and Lakhani, 2013)
Hybrid mode: IdeasProject.com
IdeasProject is an open innovation and brainstorming community, enabling the two-way
exchange of ideas between users and developers. The site was launched in 2011 firstly in
English and less than one year later also in Chinese. IdeasProject is powered and hosted
by telecommunications company Nokia. The common denominator for users is
enthusiasm towards Nokia products and mobile lifestyle in general. A significant amount
of the ideas derive from competitions organized by the hosting company (termed
“challenges” as in the case of InnoCentive), but the community also provides an open
idea space, where users may freely suggest ideas in different topic categories. In either
case, they may comment or rate each others’ input to give feedback and help to develop
ideas further. The site thus involves elements from both modes described above: contest
and community (Kosonen et al., 2012b).
4 Facilitating crowd participation with managerial actions
To provide insight on how to manage crowdsourcing, in the following we focus our lens
to the nature of the crowd and facilitating its participation. We first review practices that
a company can use when it is trying to motivate individuals taking part in the

crowdsourcing activities, and thereafter discuss how to get the best advantage of the
know-how within the crowd.
Breeding crowd motivation
Firstly, the starting point in cheering voluntary crowds to participate is to provide
mentally stimulating tasks. Several studies have underlined the importance of subjective
experiences in order to participate in crowdsourcing tasks (Zheng et al., 2011, Kosonen et
al., 2012a) and in community-based problem solving (Wasko and Faraj, 2000, Nambisan
and Baron, 2007). Such experiences are related to both personal learning (e.g., gaining
new knowledge, curiosity) and enjoyment provided by solving a given task (e.g., pleasure
of sharing own ideas, helping to develop better solutions, challenging one’s mental
boundaries). Respectively, organizations need to make sure the given tasks are
appropriately designed and provide mental stimulus for the solvers. For instance, “pilot
crowds” can be used to test the problem setting.
Secondly, in community-based modes of crowdsourcing it seems beneficial that the
organization provides feedback for users. For example, Jeppesen and Frederiksen (2006)
studied voluntary contribution in a firm-hosted community. They found that company
feedback was one motivating factor for user activity. Similar findings have been reported
in idea crowdsourcing hosted by a company (Kosonen et al., 2012a). In organizational
settings, Grant (2012) notes that when employees receive feedback concerning their
performance and results of their tasks, they feel their self-enhancement motives are
fulfilled and they are more willing to take part in valuable activities also in the future.
Bandura (1977) pointed out how people who receive positive feedback are likely to
produce more and make higher-quality contributions in comparison to those who receive
negative feedback. Furthermore, the speed of company feedback may also impact user
activity over time. Previous research in different settings has implied that timely feedback
is important e.g. in group decision making (Xanthopulos et al., 2000). One of the hosts of
IdeasProject described:
“Once you have a prosperous community, you have to give credit back to its
members, by giving attention and taking effort alike.”
Thirdly, if the hosting organization is making an effort to facilitate interaction,
favourable user beliefs are likely to emerge, as social interaction further motivates people
to share information and engage in problem solving in online communities (Porter and
Donthu, 2008, Wasko and Faraj, 2000). Both user-to-user and company-to-user
interactions are considered valuable in this respect. Being recognized by the hosting
organization has a positive effect on user participation in product development activities
online (Jeppesen and Frederiksen, 2006). Idea generation is strengthened also by user-to-
user interaction in terms of 1) quantity (frequency and time spent) 2) scope (topics
discussed in depth and the diversity of topics) and 3) mode (number of participants and
forms of communication) (Wu and Fang, 2010). Support for interaction calls for
coherence in site content and structure, as well as appropriate tools on the site. For
instance, knowledge creation needs to be organized using well-defined and structured

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topics, which allow users to rate and comment each other’s input without being lost in the
jungle of new ideas (Kosonen et al., 2012b).
Fourthly, while mere enjoyment of problem-solving and striving for better solutions
may be enough in community-based modes of crowdsourcing (see Wasko and Faraj,
2000, Jeppesen and Frederiksen, 2006, Kosonen et al., 2012a), current research
demonstrates that users engaging in contests are motivated by material rewards such as
cash prizes or awards (Leimeister et al., 2009, Zheng et al., 2011). From the hosting
organization’s part, this notion calls for subtle understanding on what attracts users to
contribute; a common fallacy is to rely on the mere existence of a crowdsourcing
platform. Users’ participation is driven by the benefits they expect, being personal, social,
hedonic or learning-related by nature (Nambisan and Baron, 2007). Hosting organizations
need to gain insight on the expectations of users sharing an interest in the task in
question, before sticking into a certain mode of crowdsourcing. While material rewards
match with contest mode, in communities they should be applied with caution. Awards
and cash prices may turn counterproductive by hampering intrinsic motivation, which is
not returned even if there are no longer rewards offered (see Bock and Kim, 2002).
Fifthly, an important implication concerns crowdsourcing settings involving on-going
collaborative elements. This is related to building sense of community and feelings of
being a part of a social collective. In technical terms, one workable solution could be
using real-time connections in the ideation sessions. Users “should feel like they are
sitting around same virtual table in same room” (Antikainen et al., 2010). Also when the
hosting organization’s employees are involved as visible members of the community, it
helps in creating a certain feeling of efficacy – “my input matters” – as these employees
are just one or two mouse-clicks away and signal other users that they are a part of a
professional community. This, in turn, may increase commitment. On the other hand, the
hosting organization should avoid exaggerated control over user-driven interactions, as it
may deteriorate commitment and identification: users no longer feel that this is also their
place (Tonteri et al., 2011). Instead, community hosts need to publicize most active
contributors and make success stories more visible, thus positively affecting users’
feelings of belonging to the collective.
Finally, attention should be paid to the selected communication technologies.
According to Antikainen et al. (2010), active participation calls for easy-to-use tools that
allow users to express themselves and share their personal insight. Appropriate online
tools reduce the cognitive effort of users to be able to develop new knowledge (Füller et
al., 2007) and positively affect the usage experience. Easiness of use becomes even more
important as the sites grow larger in content and also provide many kinds of
functionalities simultaneously, including various types of textual and multimedia content,
writing posts and reviews, rating and commenting (Kosonen et al., 2012b).
In sum, the means to facilitate user motivation are stimulating tasks, giving feedback
on a timely basis, encouraging interaction, rewarding appropriately, building sense of
community, and selecting the right communication technologies. No matter of what the
motivational factors are, the prevailing rule of thumb is “know your crowd” and its
expectations. For instance, earlier studies indicate that women are generally more
reluctant to participate in competitive problem-solving than men (Jeppesen and Lakhani,
2010) and will do so only when very confident of having a winning solution. Intuitively,
targeting a crowd with high proportion of women engaging in problem solving would

thus favour community-based or hybrid modes. Even if crowdsourcing by nature implies
designating problem-solving into large mass of users, it does not need to involve mere
“shouting in the dark”.
Putting crowd know-how into action
In general, the ability of users to come up with potential new solutions depends most
heavily on the underlying industry or product category, as well as the nature of the task in
question. When the knowledge needed is directly linked to user experience, it is easier for
users to succeed in formulating their ideas (Poetz and Scheier, 2012, Afuah and Tucci,
2012). Paradoxically, the more radical ideas the organization pursues, the more it seems
to benefit from outsourcing a task to a “marginal” crowd possessing e.g. less technical
expertise related to the field (Jeppesen and Lakhani, 2010, Poetz and Schreier, 2012),
which is seen to derive from the fact that solving complex problems requires
heterogeneous capabilities (Afuah and Tucci, 2012). The technical marginality should
not, however, be interpreted as if solving the problem required no domain-specific
knowledge at all, but rather it is conditional on the self-selection of solvers to participate
(Jeppesen and Lakhani, 2010).
Firstly, in any case of complex problem solving the limited size of the crowd makes
assessing the degree of know-how and its distribution among potential solvers a
necessity. For instance, Brabham (2008) notes how users of Threadless.com cannot
submit design ideas unless they have access to problem-specific skills and technologies,
such as editing software and graphics, and knowledge of their use. How can the
practicing managers assess the levels of crowd know-how, then? There are methods they
can use to identify lead users from the crowd, such as a process based on netnography
(Belz and Baumbach, 2010). Also social network visualization and analysis on the
patterns of replies for each user in an event could be used to find different types of
participants and evaluate their input, as demonstrated e.g. by Hutter et al. (2011) in their
study of OSRAM LED crowdsourcing contest. Analogously, Liu et al. (2005) applied
social network analysis to evaluate the impact of an individual author in a co-authorship
network. However, such evaluation can only be conducted a posteriori. Thus it is best
applicable in community-based modes of crowdsourcing where it is likely that the same
users will engage in solving problems also in the future, whereas in contest-based modes
the hosting organization relies on the above mentioned self-selection of most
knowledgeable users.
Secondly, the hosting organization needs to develop capabilities for the task/problem
specification to avoid mismatch between the desired output and the crowd’s cognitive
limits. According to a prior study by Zheng et al. (2011), it is desirable that crowdsourced
tasks require a set of different skills, but are explicitly specified to reduce complexity and
allure crowds to use their skills in a creative way. Like one of the hosts of Nokia’s
IdeasProject described:
“At times, we have had challenges [contests] with less ideas provided by the
crowd. These have been moments of learning to us: the core things are, firstly,

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finding the right community, and secondly, kind of having the right level of
specifying what we are actually looking for. We had to be more accurate.”
Thirdly, not only may the small amount of potential problem-solvers or their lack of
domain-specific knowledge limit the applicability of crowdsourcing (Afuah and Tucci,
2012), but the ability to interpret the given problems also raises challenges. Novel
solutions to problems may be difficult to propose when crowds pick only “the lowest
hanging fruits” which are already widely available, or problem-solvers misinterpret the
task due to tacitness and complexity of the knowledge involved (Cramton, 2001). One
possible solution could be using “marginal” crowds also in problem design and definition
phases (Jeppesen and Lakhani, 2010) – an act that has traditionally been assigned to firm
managers and employees, but carries the risk that the problem is conceived differently
than the problem holder originally intended. This holds particularly for contest-based
crowdsourcing where there is less opportunity to interact around the problem after it has
been designed, due to the cost of such interactions (Afuah and Tucci, 2012). For
community-based crowdsourcing, a workable solution is to provide ongoing support for
users’ interpretation of the tasks on the community site. To help solvers to outperform,
the community may provide additional knowledge resources and feedback, which support
taking a more detailed perspective into problem and providing a richer understanding of
the knowledge domain in question. In this manner, the cognitive workload of users is
eased and attention focused towards proposing more feasible solutions to problems
(Kosonen et al., 2012b).
Finally, the need to interact not only concerns the features of the problem itself as
described above, but also the solutions to follow. This supports users in specifying their
ideas further, reflecting back, and learning from each other (Hutter et al., 2011).
Depending on the mode of crowdsourcing, user collaboration could be encouraged e.g.
by targeting “sub-crowds” with a smaller amount of users all having specific domain
knowledge and a specific problem to solve. These subgroups may eventually compete
with each other to find a winning solution. At simplest, providing interactive features
such as commenting may be enough to facilitate collaboration. Like one host of Nokia’s
IdeasProject described idea development:
“There are many examples of long discussions and comment threads. Building
ideas on ideas has operated perfectly in this recent case [an idea competition
around one specific product]. Thereafter, the original ideator adds ‘Hey, look at
my idea, I’ve revised it, I’ve made it better based on your feedback’.”
It is worth noting that while problem solving in this case was originally organized using
the Tournament-based/competition mode, it functionally resembled the Collaboration-
based/community mode. Such ‘hybrid’ form and interactions among dispersed problem-
solvers allowed the hosting firm to harvest ideas of better quality. Hutter et al. (2011)
refer to ‘communitition’ as a form of community-based collaboration among competing
participants engaged in a crowdsourcing contest. On organizational and network levels,
simultaneous competition and co-operation has been coined as co-opetition
(Brandenburger and Nalebuff, 1996), reducing risks and cost associated with e.g. new
product development. Hutter et al. (2011) come into the conclusion that the benefits of
simultaneous collaboration and competition are high also on individual level, yielding the
greatest potential for successful innovation outcomes in crowdsourcing. A certain crowd

may thus act both in competitive and cooperative manner even with the same task - or,
simply put, one crowd involves both highly competitive and highly cooperative users and
needs to be managed accordingly. While contributions differ in nature based on the role
users take in the community, it is of particular importance 1) to identify communititors
(i.e. users who most likely embody the necessary combination of co-opetitive behaviour)
and 2) attract and reward communititors to take part in ideation and design (Hutter et al.,
2011).
In sum, the means to facilitate putting know-how into action are related to assessing
the degree and distribution of crowd know-how, appropriate task/problem
specification to avoid too broad or complex tasks, providing support for task
interpretation, and encouraging collaboration in order to establish more high-quality
solutions. Table 1 summarizes our findings.
Table 1 Modes of organization-hosted crowdsourcing and their management practices
Practices Contest mode Community mode
Breeding motivation
Provide stimulating tasks x x
Give feedback on a timely basis x
Encourage interaction x
Reward appropriately material immaterial
Build sense of community x
Select the right communication technologies x x
Putting know-how into action
Assess the degree and distribution of know-how self-selection based on user data
Specify tasks/problems on an appropriate level x x
Support task interpretation beforehand on-going basis
Encourage collaboration, support communititors x x
5 Discussion and conclusions
Crowdsourcing has raised increasing debate among innovation management scholars and
practitioners. For the hosting organization, its benefits seem two-fold: not only gaining
more novel solutions to problems when compared to those deriving from employees or
contractors (Poetz and Schreier, 2012, Jeppesen and Lakhani, 2010), but also increasing
commitment and interest e.g. towards a firm’s product offerings by empowering users to
take an active role in developing and modifying products (Nambisan and Baron, 2007,
Füller et al., 2007). Hence, we asked how to best facilitate crowdsourcing and
innovation-related problem solving among external crowds. As a result, we identified 10
practices that are likely to favour users’ motivation and putting know-how into action.
Our study has implications within the emerging research on crowdsourcing, where most

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studies so far have dealt on individual users’ level and neglected the hosting
organization’s perspective.
Firstly, our study contributes to innovation management literature by presenting a
preliminary framework of the factors that support innovation-related problem solving
among external crowds. We encourage future research establishing measures for the
identified factors and testing their effect on the problem-solving outcomes within
different types of crowdsourcing sites. Secondly, we contribute to the evolving discussion
on crowdsourcing by outlining its different modes to be applied by hosting organizations:
Tournament/contest-based, Collaboration/community-based, and hybrid, involving
elements from both contest and community. To our knowledge, the simultaneous
competition and collaboration in crowdsourcing has not been tackled in existing research
except for the study by Hutter et al. (2011). Their study focused on individual users and
their role in engaging in problem-solving tasks, thus lacking the hosting organization’s
point of view, whereas we aimed at understanding how to facilitate participation in 1)
contests and 2) communities. We welcome future research endeavours where each mode
of crowdsourcing is studied more in detail. For instance, the suitability of contest-based,
community-based and hybrid modes for solving different types of problems deserve
further attention.
For innovation managers, our study gives practical insight on how to cultivate the
know-how and motivation of external crowds in organization-hosted crowdsourcing
settings. Indeed, our results underline that facilitation is a task to be taken seriously in
terms of internal resourcing and learning from experience, particularly when aiming at
applying the community-based mode. We offered guidelines for organizations aiming to
develop their management practices that support co-creative innovation processes among
crowds. Our lenses were in managing crowdsourcing and also in evaluating its potential
critically instead of focusing on the “hype” side of the phenomenon.
As a limitation, it is noteworthy that we only outlined the managerial practices that
concern the nature of crowds (Afuah and Tucci, 2012). The actual knowledge processes
in creating new knowledge, developing an appropriate technical infrastructure, and
evaluating the potential solutions remain important issues for further research in solving
innovation-related problems with external crowds. For simplicity, we limited our
investigation to the idea generation phase within the organization-user interface. In line
with di Gangi and Wasko (2009) who studied the path of adopting innovations from a
user community, we believe it is important for crowdsourcing researchers to gain more
understanding on the process from original ideas into the market, while further examining
the overall value of new ideas and designs suggested by voluntary crowds.
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