A Review on User Innovation Virtual Community and Suggestions for Future
Research
Da-liang Zhang 1, Yuan-yi Zhang2
1
2
Department of Business Management, Zhejiang University, Hangzhou, China
Department of Business Management, Zhejiang University, Hangzhou, China
(Zdl@zju.edu.cn,Zhangyuanyihao@163.com)
Abstract - User innovation in virtual environment has
become an important form, which companies need to
promote. However, academic research on user innovation
behavior in the virtual environment is far from sufficient.
This study reviews user innovation research in the virtual
community to discuss the basis and method of user
innovation incentives in virtual community and summarizes
existing research on innovation performance. Based on it,
incentive objects, contextual factors, measurement are
discussed for future research.
Keywords - Virtue environment; user innovation;
incentive; literature review
I. INTRODUCTION
With growing shortage of resources, enterprise
innovation system is undergoing dramatic changes.
Companies change their relatively closed innovation
towards open innovation to take full advantage of
resources and build a sustainable innovation system. In
response to fast development of Internet economic and
increasing number of Internet users, user innovation
research has been gradually extended to the Internet
context. User innovation in the virtual community gets
researchers’ attention due to its rapid development and
novel form. One of the important questions is how to
motivate users. This study reviews the user innovation
research in the virtual community, discusses ways to
motivate user innovation in the virtual community,
summarizes existing research on innovation performance,
and lists valuable direction for future research.
II. User innovation in virtual environment
User innovation refers to new ideas or improvements
on products or services by users of these products or
services or improvements. There are various form of user
innovation. It can be divided into concept and product
innovation according to the tangibility level[1] (Hoffman,
Kopalle, 2010) and to core-module and sub-module
innovation according to product innovation domain. By
user’s position it can be divided into the intermediary and
end-user innovation [2] (Bogers, Afuah, 2010). By the
platform, it can be divided into the traditional sense of
innovation and IT-based innovation. The former appears
in traditional product with special using context, such as
sports equipment and medical equipment. The latter often
appears with information technology, such as innovation
on virtual platform [3] (Nambisan, 2002), Web 2.0-based
innovation [4] (Bilgram, Brem, 2008), innovation in
online communities, and innovation packages.
By leading position, user innovation in the virtual
environment can be divided into community-led and userled one. By different roles of development stages,
Nambisan designed a virtual user innovation platform,
including interactive mode, knowledge creation, user
motivation, and integration with R & D team.[3]
(Nambisan, 2002). Nambisan further integrated theories
to discuss that different user motivation may lead to
different contribution to community or company [5]
(Nambisan and Baron, 2010). As for importance of
different user, Von Hippel used lead user concept
emphasizing willingness and ability differences ,while
Trusov used influential, mainly referring to one who has
major impact on other users in social networking site such
as Blog and other content innovation media[6] (Trusov,
Bodapati, 2010).
Different theories have different interpretations for
user behavior in virtual environment. It is believed by
theory of social capital that relation can strengthen the
commitment of members to help others among the groups,
thus contributing to collective action [7] (Nahapiet and
Ghoshal, 1998). Studies show that in a virtual
environment, the more responsible members are, the more
likely they could share knowledge and make contribution
[8] (Wasko, and Faraj, 2005). In addition, social exchange
theory. holds exchange is based on a mutually benefit. A
support for this is study which finds reputation and
learning promote user innovation behavior [9] (Harhoff,
Henkel, 2003). Different theory interpretation enhances
the interest of user innovation study in the virtual
environment. However, above studies were conducted at
individual level, little is known about differences among
communities.
III. User innovation incentives in virtual environment
Although there is no systematic theory, guide for user
innovation, however, has already developed in two
aspects: What is the basis of incentives and the way of it.
Incentives are mainly based on innovation
motivation. Volker [4] (Bilgram, Brem, 2008) reviewed
past research and found that in empirical research users
innovate to seek happiness of the process, make use of
potential ability and creativity and also are driven by
external motivation such as money ,ease of use and use in
special context. Xu Lan [11] (2007) introduced unique
product and experience needs to innovation motivation
studies, and found unique need affects consumer
innovation. Nambisan divided motivation into four
categories (Namibian and Baron, 2010),based on different
theoretical background: community responsibility, selfimage enhancement expectation, professional skills
enhancement expectations and the company's partnership.
This classification underlines theoretical basis and helps
to explain the type and size of the user contribution.
Another basis of incentive is the place played by user
in innovation, including the stage and the importance. In
innovative design research in virtual community ,
Nambisan pointed out that users played different roles in
different stages, thus leading to different management
challenges [3] (Nambisan, 2002). He believed that in the
stage of the product idea, users play the role of innovation
resources and companies are mainly concerned about how
to get user knowledge; play a co-creation role in product
design and development stage and companies should
focus on how to strengthen user knowledge; in product
testing and support phase and companies should be
concerned about how to promote interaction between
users. As for importance, it involves the investigation into
target capacity. Von Hipple and other scholars use lead
user to depict users with strong innovation willingness
and . Another concept is emergent nature, which refers to
innovation characteristics that can identify product market
trend[1] (Hoffman,, Kopalle, 2010). Companies should
make different incentive policies based on different role
user plays.
According to social exchange theory, incentives can
be broadly divided into social-emotional and economic
kind (Foa, 1974). Social-emotional incentive will lead to
social-emotional results, such as trust and acceptance of
company.It shows that trust in business can affect user
willingness to innovate [11] (Xu Lan, 2007). Virtual
community studies have shown that the relationship will
affect the user's sense of being respected, thereby
affecting the willingness to cooperate in the new product
development [13] (Porter and Donthu, 2008). The
economic incentive is the incentive in the form of
monetary incentives.
There are some gaps. First, the current discussion just
stays in the user level rather than the community level.
From the community level, scholars can compare
communities and find out key incentive model to help to
build core competitive advantage. Second, it has not been
discussed in depth how users feel as psychological
process of incentives.
IV.User innovation incentives measurement
After discussion on innovation incentives, there is a
need to know incentive performance. The study of
organizational innovation performance measurement
includes
results-oriented
and
process-oriented
measurement [16] (Adams, Bessant, 2006). The former
focuses to the cost-benefit analysis from the perspective
such as investment in human, material and financial
resources, tools and their output market value. The latter
considers innovation process, such as knowledge
management including idea number, knowledge storage
and information flow; innovation strategy including
strategic direction and strategic leadership; organizational
culture including culture, structure; project management
including benefit analysis, communication, cooperation,
and commercialization including market research, testing
and sales. Table 1 summarizes ways of user innovation
performance appraisal.
TABLE I: Measurement on user involved innovation performance
Key
point
Produc
t
attribu
tes
R
e
s
u
l
t
s
o
r
i
e
n
t
e
d
B
e
h
a
v
i
o
r
o
r
i
e
n
t
e
d
Potenti
al
value
Variable
Area
Paper
Degree
of
customization,
property quality,
external
sensitivity
characteristics
Perceived relative
advantage,
compatibility,
community
prevalence
Investor
evaluation
Open design of
online
games
platform for key
product attributes
Shu-Yu
Yeh,2010
Key attributes of
virtual
user
innovation
Paul M.Di
Gangi,2009
Evaluation
of
user
improvement’s
commercial value
on
library
information
system
innovations
adoption in sports
community
User innovations
on
medical
device
User innovation
encouragement’s
impact
on
business
innovation cost
User innovation
ratio in total
innovation
of
each industry
User-oriented
design
Morrison,20
00
consumers
‘
intention
to
participate in hair
design
Non-economic
incentives
on
different maturity
user
Lan Xu,2004
Marke
t value
Sales
rate
production
Techni
cal
value
Invest
ment
cost
Number of patents
Innova
tion
covera
ge
Innova
tion
cooper
ation
Intenti
on to
innova
te
Innova
tion
behavi
or
Innovation ratio
Information costs
、support costs
Information
sharing,
integration,
design
Have or not
co-
Innovation
frequency, time
Franke&Sha
h,2002
Lu¨thje,2003
Lu¨thje,2003
Christian
Lu¨thje,2004
Robert
Veryzer,200
5
Yafeng
Xie,2012
Learning from the above research, user innovation
performance measurement in the virtual environment can
also include results-oriented and process-oriented forms,
as table 1 shows. A common practice is to measure
product value. Paul M.Di Gangi [17] (Di Gangi and
Wasko, 2009) defines key product attributes of innovation
adoption, including the perception of relative advantage,
compatibility, community prevalence and scaled it to
measure user innovation value.
V.Future direction for user innovation incentives in
virtual environment
A. Object
There are two possible innovative behaviors to
motivate: one is spontaneous user innovation and the
other is under the influence of company or community.
These two type is different in motivation and performance,
which future research could focus on. The virtual
community works as space for consumer to consumer
interaction, in which they can interact in pairs or in
groups.[18] (Libai, Bolton, 2010). Consumer to consumer
interaction perspective is future direction of user
innovation research. There is difference between single
innovation behavior and group innovation. In addition, the
difference between online and offline innovation is
another problem for making incentive policy. How to
make effective incentive to make online and offline
innovation behavior promote each other has become
valuable in future research. Finally, how to understand the
lead user's contribution to the community and the
company's growth and profits is also worthy of discussion.
B. Context
Innovation climate in organization studies provides a
reference for study on user innovation in virtual
community environment. As for definition of atmosphere,
there are two different views: one defines atmosphere as
objective environment [19] (Mauss, 1970) while the other
as the overall perception of the environment by the
innovation subject, as a product of cognitive experience
[20] (Tesluk, Farr, 1997, Weick, 1995).
Future research can focus on cognitive experience to
examine the psychological impact of the climate on user
innovation. For example, the innovation climate is
measured by level and intensity. Level refers assessment
of the level of community atmosphere and strength refers
to the internal consistency in perception. Organizational
innovation studies have demonstrated a positive relation
between innovation climate level and performance.
Climate strength moderate the relation. The higher the
strength, the greater climate level’s impact on innovation
performance. However, level and strength may have
correlation, thus moderate effect may be weakened
(Lindell & Brand, 2000). Future research can discuss the
level and strength of climate on the incentive effects.
The relationship between the community and the
individual may affect the innovation incentives effect.
Social identity theory (Ashforth, 1989) holds that the
social identity of individual to his group may lead to some
kind of interaction between individual and group, thereby
enhances the participation behavior. Identification is
critical for users to participate [22] (Muniz Jr., 2001).
Community identity will increase user’s contribution to
community innovation and corporate identity will
increase user’s contribution to enterprise. Future research
can use social identity to find out how relationship
between the community and the individual affects the
innovation incentives effect. For example, according to
social identity theory, the identity of a thing may lead to
psychological ownership of the things [23](Pierce,
Kostova, 2001),which will help to understand the
relationship between the individual and the community.
Psychological ownership is a concept proposed by Pierce,
which is different from formal ownership. It refers to
mind state that one thinks the target is owned by his own
and emphasizes the psychological control and possession
of the target. There is no formal ownership to the
community for users and the use of virtual space can meet
the users’ self efficacy Future research can focus on
potential value of psychological ownership in
understanding user innovation.
The type of product may moderate incentives
mechanism. Past studies have shown that user innovation
behavior is different for different products. Product with a
strong "stickiness" will promote a higher level of
innovative behavior. Future research could consider the
moderate role of the product type on the incentives effect.
Also, the life cycle of the product may lead to different
types and level of innovation. Future research could
consider different innovation incentive policies in
different stages of life cycle.
There may be different types of incentives for
different virtual communities. Community as for
management type can be divided into normative
governance community and reputation-based community
[18] (Libai, Bolton, 2010). Normative governance is
established on normative force and it requires all parties
involved to accept rules, make commitment and keep
consensus based on reciprocity, dedication, trust. Its rules
can be visible or not. Reputation-based community refers
to the system designed by community managers with a
feedback function, in which members of the different
contributions have different social recognition and
rewards. These two kinds of community management
may also affect the implementation of the user innovation
behavior and incentives.
C. Measurement
It can be drawn on other policy measurement for the
measurement of innovation policies. For example, in the
safety climate study, Zohar described security policy by
three factors: Orientation, that is the relative importance
compared with other policy, policy coherence, that is the
degree of policy changes with environment and
simplicity, that is the degree it can be identified [12]
(Zohar and Luria, 2004).
Future research can learn from multi-level methods in
organization research to research innovation performance
at both users’ level and community’s. It is interesting to
study the interaction between community incentive policy
and user motivation on innovation performance. Also,
how does user innovation performance calculate as
community performance remains unknown. The multilevel research is direction for future research.
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