Crowd-Innovation: Crowdsourcing Platforms for Innovation
Roberta Cuel
a
Department of Economics and Management, University of Trento, Trento, Italy
Keywords: Crowdsourcing, Digital Platforms, Taxonomy, Open Innovation.
Abstract: Companies fostering innovation take advantage of an emergent combination of various factors such as the
human brains, tools, networks, and technologies. Crowdsourcing platforms support all these elements
together and offer quite an interesting tool for all the innovation phases, from idea creation to the market.
Despite increasing utilization of these platforms, a systematic analysis of the supported type of services and
contributions is missing. This work aims to analyze some of the most used crowdsourcing platforms and to
classify them according to the type of contribution they may provide in the innovation process. Using an
emerging approach analysis, the following contribution phases have been revealed: idea contests, ongoing
idea platforms, platforms for idea screening, innovation platforms, R&D platforms, design contest platforms,
ongoing design platforms, creative contests, and platforms for virtual concept testing. In this paper, these
nine categories are described in depth to explain how they serve various phases of the innovation process:
idea generation and testing; research and development of rough concepts, detailed concept and testing,
production, and market launch.
a
https://orcid.org/0000-0002-0699-3109
1 INTRODUCTION
Conceptually in open innovation, any actor can take
advantage of “purposive inflows and outflows of
knowledge to accelerate internal innovation, and
expand the markets for external use of innovation,
respectively” (Chesbrough, 2006).
Figure 1: Open innovation model.
As depicted in Figure 1, R&D activity can be
seen as an open system in which valuable ideas
could come either from inside and/or outside the
company (Chesbrough, 2003), and the boundaries
between the company and its periphery are therefore
becoming more and more “porous” (Howe, 2008).
In coherence with this trend, networked
information systems, distributed knowledge
management procedures, e-commerce marketplaces,
and crowdsourcing platforms are becoming
mainstream. The term crowdsourcing was coined by
Jeff Howe and Mark Robinson in 2006 and was the
compound contraction of “crowd” and
“outsourcing”.
In more detail:
“Crowdsourcing represents the act of a
company or institution taking a function once
performed by employees and outsourcing it to an
undefined (and generally large) network of people in
the form of an open call. This can take the form of
peer-production (when the job is performed
collaboratively), but it can also be undertaken by
sole individuals. The crucial prerequisite of
crowdsourcing is the use of the open call format and
a large network of potential laborers”. (Howe,
2006).
In addition, “Crowdsourcing is the act of taking
a job traditionally performed by a designated agent
(usually an employee) and outsourcing it to an
792
Cuel, R.
Crowd-Innovation: Crowdsourcing Platforms for Innovation.
DOI: 10.5220/0010495007920799
In Proceedings of the 23rd International Conference on Enterprise Information Systems (ICEIS 2021) - Volume 2, pages 792-799
ISBN: 978-989-758-509-8
Copyright
c
2021 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
undefined, generally large group of people in the
form of an open call.” and “Crowdsourcing is the
application of Open Source principles to fields
outside of software.” (Howe, 2008)
Despite that crowdsourcing refers to the most
recent internet-based network, various notable
historical examples were grounded in this concept,
for instance, the project supported by the London
Philological Society to develop the Oxford English
Dictionary. An open call was made and over a
period of 70 years, more than 6 million submitted
terms and definitions were obtained. (Winchester,
2003).
The crowdsourcing phenomenon is usually
depicted as an actor (an individual or an
organization) externalized in an activity (simple or
complex) through an open call. The open call can be
made through a corporate portal or an intermediary
platform such as Amazons' Mechanical Turk,
Innocentive, and Clickworker. The open call may
refer to various forms of contributions: among
others, a donation of money (crowdfunding); a
provision of opinions and judgments (crowd-voting),
and a donation of labor (crowd-creation). This latter
can be organized as:
Microtasks: a set of small, or even very small,
well-defined simple tasks that together may
comprise a large project/product. These tasks
are performed by individuals who often
autonomously contribute to validate data, tag
images, provide simple content, translate
phrases, etc.
Macrotasks: more complex often not clearly
defined activities, which usually require the
involvement of teams. Macrotasks are suitable
for research projects, product and service
innovation in which the crowd is empowered
to provide the best course of action to solve a
complex problem.
In other words, Open Innovation is transformed
into Crowd Innovation as depicted in Figure 2
(Boudreau and Lakhani, 2013).
Companies, then, may foster innovation via
crowdsourcing in two ways: (i) developing a
corporate platform (LEGO Ideas platform, Muji
challenge, etc.) or (ii) using services provided by
intermediary platforms, the so-called
“innomediaries” (Sawhney et al., 2003; Palacios et
al., 2016; Ghezzi et al., 2018).
More recent studies focus on the models of
crowdsourced service for value co-creation
(Haidong et al., 2019; Liu et al., 2018; Pera et al.
2016), and on the role of customers in co-creation
processes (de Mattos et al., 2018; Zhao et al., 2016).
According to these studies, companies take
advantage of a corporate crowdsourcing platform to
acquire information from customers and other
stakeholders who may provide very useful
knowledge to the company. They gather, track, and
share relevant industry trends to inspire the
development of enriched ideas for the company’s
innovation program (Lorenzo-Romero &
Constantinides, 2019).
In a more effective, accurate, rapid, and cheap
way, crowdsourcing corporate platforms can also
Figure 2: Crowd innovation model
1
.
identify the biggest struggles of customers, end-
users, and employees by involving them in the
design thinking process in order to find meaningful
patterns for ideation boosts. Moreover, these
platforms can acquire information about the needs of
customers and the most appropriate products and
services that satisfy clients, and can also create a
common technological base through which
consumers gather together in a community (e.g., the
famous case of MyStarbucks idea).
Companies can also involve large numbers of
external ecosystem stakeholders (customers,
business partners, expert communities, academia,
start-ups & entrepreneurs, and even citizens) in an
open collective intelligence initiative (Fedorenko &
Berthon, 2017; Kohler & Nickel, 2017; de Mattos et
al., 2018). In most cases, customers are intrinsically
motivated to offer their innovative ideas for free as
future users of those innovative products and
services (von Hippel, 2005). Analyzing the
contributions of the crowd can trace, evaluate, and
manage scouting opportunities for technology usage,
joint ventures, mergers, partnerships and
1
source: https://www.zdnet.com/blog/hinchcliffe
Crowd-Innovation: Crowdsourcing Platforms for Innovation
793
acquisitions and become the leading ideal
management solution for capturing the collective
intelligence of employees in order to generate
groundbreaking results and successfully compete on
the market.
2 AIMS OF THE PAPER AND
METHOD OF ANALYSIS
In the last few years, researchers have identified
various elements that strongly affect the success of
crowdsourcing initiatives, but little work has been
done on how various crowdsourcing platforms
influence company innovation process. The study
proposed here is aimed at a systematic exploration
of the most important crowdsourcing platforms, with
the aim to identify the most common features and
elements that support a company innovation process.
The analysis was conducted as follows:
Literature review on crowdsourcing platforms
and innovation.
Identification of the most important
crowdsourcing platform on innovation.
Analysis of the crowdsourcing platforms and
data collection.
Data were collected through a three-step process:
Desk analysis: the initial collection of
secondary data needed to frame the research
work.
Direct observation of the platform features.
Semi-structured interviews. An interview
protocol was developed to facilitate and guide
semi-structured open-ended interviews. All
the interviews were recorded, classified, and
analyzed.
All the collected data were analyzed. To improve
the reliability of the study (Merriam, 2009) the
following actions was undertaken:
Data triangulation of multiple sources of
information.
Saturation and continuous data collection to the
point where more data added little to
regularities that had already surfaced.
Peer review, or consultation interviewing of
expert crowdsourcing contributors and
developers.
Plausible alternatives, or the rationale for ruling
out alternative explanations and accounting
for discrepant (negative) cases.
Significant features and episodes emerged, and a
common taxonomy was developed for innovation
mechanisms and processes supported by the
crowdsourcing platforms.
The taxonomy derives from a comparison
between real cases of online platforms and the
theoretical concept developed in the literature.
2.1 The Sample of Analysis
In the recent past, an increasing number of
crowdsourcing platforms have been launched:
Deloitte calculated more than three billion enterprise
crowdsourcing platforms grouped as in Table 1
(Deloitte, 2016).
Table 1: Crowdsourcing platforms: a classification.
Crowdsourcing models Examples
Crowd collaboration
99Designs
X Prize
Quirky
Crowd competition
TopCoder
Kaggle
InnoCentive
Applause
Crowd labor (microtasks)
TaskRabbit
Amazon’s Mech. Turk
Streetbees
Gigwalk
Samasource
Crowd labor (mesotasks)
Lionbridge
CrowdFlower
Crowd labor (macrotasks)
10EQS
Wikistrat
OnFrontiers
Applause
Crowdfunding
Kickstarter
CrowdCube
Crowd curation
Wikipedia
TripAdvisor
User-generated content
YouTube
iStockphoto
The above-mentioned platforms are classified
according to the type of service they support as
depicted in Table 2.
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Table 2: Crowdsourcing platform services.
Crowdsourcing
models
Services
Crowd
collaboration
- Tasks requiring the aggregate
‘wisdom of the crowd’
- Generating outside ideas
Crowd
competition
- Creating actionable solutions
- Developing prototypes
- Building a sense of community
- Generating outside ideas
- ‘Gamification’
Crowd labor
(microtasks)
- Well-defined, everyday tasks for
individuals that require general
skills only
- On-site manual work, such as
store restocking, furniture
assembly and cleaning
- Large crowds
- Manpower when the company
does not want to hire permanent
employees or contractors
- Real-time market intelligence or
data gathering
Crowd labor
(mesotasks)
- Well-defined tasks that require
specialist processing skills
- Routine but time-consuming
activities, such as data entry
- Manpower when the company
does not want to hire permanent
employees or contractors
Crowd labor
(macrotasks)
- Poorly defined or unstructured
tasks or problems, such as
strategy development, research,
or consulting
- Tasks requiring subjective
judgement or specialist skills
- Manpower when the company
does not want to hire permanent
employees or contractors
Crowdfunding
- Fundraising
- Start-ups
Crowd curation - Building and sharing knowledge
User-generated
content
- Building large content
repositories
However, these traditional classifications do not
shed light on how a company can be supported by
crowdsourcing platforms in the process of
innovation (Ghezzi et al., 2018). As a result, ten
well-known platforms for creativity and innovation
were selected from the thousands available using the
following criteria:
- platforms that deal with innovation
- platforms that have or will have a significant
impact on the market
- industry-specific platform (where designers
are involved)
- corporate platforms that deal with the
company innovation process.
Generalist platforms were also studied to have a
complete understanding of the innovation process.
Some industry-specific platforms were analyzed to
gain a more in-depth understanding of the first
findings and then two corporate crowdsourcing
platforms were examined to identify hypothetical
differences between corporate and intermediary
platforms.
The selected platforms are (Figure 3):
InnoCentive (https://www.innocentive.com/)
Idea storm (http://www.ideastorm.com/)
99 design (https://99designs.it/)
Zooppa (https://www.zooppa.com)
Slow/d (http://slowd.it/)
The industry-specific platforms are:
Open Source Footwear
(https://www.fluevog.com)
Threadless (https://www.threadless.com/)
Designhill (https://www.designhill.com/)
Corporate crowdsourcing platforms:
P&GConnect+develop
(www.pgconnectdevelop.com/)
Heineken Ideas Brewery
Figure 3: A selection of crowdsourcing platforms.
Crowd-Innovation: Crowdsourcing Platforms for Innovation
795
A selection of crowdsourcing contributors and
platform developers were interviewed to verify the
findings of desk analysis.
2.2 Framework of Analysis and
Interview Protocol
To carry out more objective observations, a
framework of analysis was developed. This was also
used as the interview protocol. The framework takes
into consideration the following relevant elements:
The set of activities a company can carry out on
the platform (resources, call, timing, etc.).
Mechanisms of interaction among contributors
and between the requester (the company) and
the provider (the contributor).
The set of incentives a company can provide on
the platform.
The type of knowledge provided and shared on
the platform.
Mechanisms of social networking and
connection with other social networks
(LinkedIn, Facebook, etc.).
The ID of the company and the contributors.
All the above-mentioned elements have a strong
impact on the company inventions since they affect
various innovation phases, the quality of the
innovative ideas, the set of rewards that drive
contributors to create content, and the set of
incentives that spur users to participate.
All these data were collected and analyzed to
identify any common characteristics.
3 THEORETICAL, EMPIRICAL
AND MANAGERIAL
IMPLICATIONS AND
CONTRIBUTIONS
From the structured analysis of collected data, the
identified crowdsourcing platform functionalities,
and the expert interviews a new taxonomy became
apparent, and the following nine categories of
crowdsourcing platforms for innovation emerged:
idea contests,
ongoing idea platforms,
platforms for idea screening,
innovation platforms,
R&D platforms,
design contest platforms,
ongoing design platforms,
creative contests, and
platforms for virtual concept testing.
This classification is quite new because it does
not intend to analyze only the platform features but
to identify how the different features affect the
innovation process and are perfectly suited to
specific innovation phases of the innovation process:
idea creation and testing; research, development and
testing, production, and commercialization
(summarized in Figure 4).
Figure 4: Crowdsourcing platforms and the innovation
process.
In Section 3.1, the nine categories are fully
described, examples of existing and used
crowdsourcing platforms are provided and how they
serve the various phases of the innovation process is
explained. It will be quite clear that each category
represents a different set of:
types of contribution,
decision processes, and
incentives for the contributors.
Figure 5: Crowdsourcing platforms and the innovation
process: the sample of analysis.
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3.1 Idea Creation/Generation
As is evident from Figure 5, the first phase of the
innovation process consists of the generation of
ideas. To engage the crowd in these very first
moments, two approaches are possible: the creation
of ongoing idea platforms or idea contests for
organizations. Although they are both part of the
idea creation phase, these two approaches are
considered distinctive in order to highlight their
characteristic operation mechanisms.
An idea contest constitutes a particular case of
“innovation contest”, where “a firm (the seeker)
facing an innovation-related problem [...] posts this
problem to a population of independent agents (the
solvers) and then provides an award to the agent
that generated the best solution” (Terwiesch, Xu,
2008). The contest usually has a theme that should
characterize contributions and a deadline for posting
them online. In the case of an idea contest, the best
ideas generated as a response to a certain input are
rewarded usually by a monetary reward. The explicit
reward contributes to further foster the self-selection
mechanism underlying any crowdsourcing initiative
(Piller, Walcher, 2006) and to raise the average
quality of the ideas produced (Piller, Walcher,
2006). According to Piller and Walcher (2006), from
this approach is possible to identify lead users that
could be engaged in other phases of the innovation
process in a better, cheaper, and more rapid way
compared to other techniques.
Another important advantage of the approach in
question is that the company pays only for
contributions that it considers worthy of
implementation or further development: this
significantly reduces the risks of failures in the
innovation process since the burden is on the
contributors themselves (Terwiesch, Xu, 2008). An
example of this approach is the Heineken platform
called Ideas Brewery
2
, where the company organizes
idea contests to get creative ideas regarding strategic
topics for future development.
By employing idea platforms, the company
continuously/regularly collects innovative ideas for
new products, services, or processes, or that could
improve and integrate existing products, services, or
processes (Bayus, 2013). Howe (2008) defines the
approach under consideration as idea jam”: it
consists of an online brainstorming session that
involves a huge and undefined number of
participants. The request for contribution is rather
generic and there is no fixed deadline for posting
2
www.ideasbrewery.com
ideas: the only requisite is to register on the website.
Generally, no monetary incentives are provided (or
those which are, are symbolic prizes) and the level
of contributions will probably vary and, on average,
not be that high.
The idea screening platform enables any user to
vote and comment on different innovative ideas. As
a result, it is determined what ideas, if further
developed or directly implemented, would obtain
positive feedback on the market. The examined
platforms are usually integrated into the idea
platforms described previously. The effort requested
from the single individual is rather low but produces
value is the final ranking resulting from the
combination of the crowd actions (Howe, 2008).
3.2 Development
Considering the development phase of designs for
new products, design contest platforms, and ongoing
design platforms are considered different since they
present a differentiated set of characteristics. More
than in the idea(s) platforms, not only information
about needs is requested but also how to practically
satisfy those needs. In most cases the work of the
crowd is rewarded with monetary incentives:
therefore, the most used type of design platform is
the contest approach. A design contest is based on
the operational mechanism and incentives illustrated
in the idea contest, but contributors are professionals
and specialized workers, mainly motivated by the
monetary prizes and by the possibility to gain
visibility in the design industry and to sell their
creations via websites.
Less common is the ongoing design platform
approach where a company can continuously collect
ideas for new designs using a corporate platform,
request general ideas, and decide whether to
implement them or not. An example of this kind of
platform is that of the company Fluevog Shoes,
Open Source Footwear
3
: this brand collects ideas for
new designs of shoes and can decide which
contributions are worthy of further development.
3.3 Marketing and Distribution
Even in the testing and selection phase of the best
design proposal, a company can exploit the work of
the crowd (Dahan, Srinivasan, 2000). In the case of
virtual concept testing platforms, however, the
engagement significance is even higher given the
fact that the evaluation concerns proposals that are
3
www.fluevog.com/community/opensource-footwear/
Crowd-Innovation: Crowdsourcing Platforms for Innovation
797
much closer to the launch on the market. As a result,
it is possible to reduce the risks of the market launch
of new products because the producer learns about
customer preferences in a more direct and precise
mode before the production starts and when the
product is still in the concept phase (Ogawa, Piller,
2006). Ogawa and Piller (2006) call this approach
"collective customer commitment": it consists of
asking the clients to commit to buy a new product
before starting the final phases of the development
process and the production.
If the virtual testing mechanism concerns
concepts internally developed by the company, these
platforms become online concept labs and enable the
testing of customer reactions to products that are still
in the development phase (Sawhney et al., 2005). In
this case, the customers have a role that is much
closer to the traditional of final users and buyers
(Piller, Ihl, 2009). Thanks to the evolution of
rendering and simulation technologies, it is easier,
cheaper, and quicker to generate prototypes so that it
is possible to get many concepts tested in parallel
(Dahan, Srinivasan, 2000). It is very important to
engage with the company's customers in this phase
because the customers could direct the company's
supply.
4 CONCLUSIONS
The proposed taxonomy aims to present to the
classification of online crowdsourcing platforms
under a new perspective, namely which phase of the
innovation process they could best serve.
From a scientific point of view this taxonomy
can be used to improve the model of open
innovation and of innovation ecosystem. The
ecosystem can be characterized by both internal and
external stakeholder crowdsourcing solutions, by
corporate platforms and innomediaries. In other
words, the crowd innovation model can be enriched
with the innovation phases and the taxonomy
identified in this research as depicted in Figure 6.
Referring to the managerial implications: the
main advantage of this classification is to present an
analysis by the innovation process thus helping
companies to decide on what the most suitable
crowdsourcing platform to use is. This allows a
company, that wants to crowdsource part of its
innovation process, to have a panoramic and organic
view of the different existing possibilities.
The limit of this research is that the taxonomy
proposed in the paper enables the researchers to
classify crowdsourcing platforms according to the
Figure 6: The new model of crowd innovation.
phases of the innovation process. However, not
every platform could be easily allocated to a single
category since they may offer more than one service,
covering more than one phase of the innovation
process.
ACKNOWLEDGEMENTS
I would like to thank Francesca Frisanco for the
work of collecting data and discussing the research
findings with me.
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