Inbound and Outbound Open Innovation in Clusters
Yin-jie Xu 1, Jian-zhuang Zheng2
1
School of Management, Zhejiang University, Hangzhou, China
Business School, Zhejiang University City College, Hangzhou, China
2
(xymstc@163.com, zjzd2@163.com)
Abstract - This paper investigates the impact of the
inbound and outbound open innovation on innovative
performance in firms of industrial clusters. We argue that
firms with higher levels of absorptive capacity manage
external knowledge flows more efficiently and stimulate
innovative outcomes. And in a cluster with more trust
between the firms, firms will achieve higher innovative
performance through outbound open innovation. What’s
more, we discuss open innovation in firms of labor-intensive,
capital-intensive and technology-intensive industrial clusters,
respectively. We argue that sourcing and revealing are more
popular than acquiring and selling in firms of laborintensive clusters. However, acquiring and sourcing are both
very popular while revealing is more popular than selling in
firms of capital-intensive and technology-intensive clusters.
Keywords - innovation performence, inbound open
innovation, outbound open innovation
I. INTRODUCTION
Zhejiang province, one of the most prosperous
regions in China is home to various industrial clusters
ranging from labor-intensive (e.g., clothes, neckties, and
flooring) to capital-intensive products (e.g., equipment
manufacturing and automobile parts). In recent years,
industrial clusters developed very rapidly in both scale
and economic benefit in Zhejiang. There are more than
300 industrial clusters with annual sales above 1 billion in
Zhejiang Province. Among those industrial clusters, there
are 5 clusters with annual sales above 100 billion. The 5
clusters are Hangzhou equipment manufacturing cluster,
Shaoxing textile cluster, Xiaoshan chemical fiber textile
cluster, Yongkang hardware cluster and Ningbo clothing
cluster.
However, there are some problems in Zhejiang’s
industrial clusters. One of the critical problems is the
“double lock-in”, which stands for two situations. In one
situation, the whole industrial chain is locked at a low
level. And in the other situation, part of the industrial
chain is locked at a low level. In the labor-intensive
industrial clusters, firms imitate with each other within the
same cluster. They hardly learn from the excellent firms
outside the cluster. As a result, their products lack the
technology and they have low profits. The whole
industrial chain is locked at a low level. In the capitalintensive or technology-intensive industrial clusters,
although there are several superior firms in the cluster,
they are reluctant to transfer their redundant patent or
technology to other firms within the same cluster. As a
result, the majority is locked at the low part of the
industrial chain and the cluster can not develop in balance.
In a word, the former ignores the search strategy for the
knowledge and technology and the latter does not open
toward outside to share knowledge. The two situations
just reflect the firms are lack of open innovation, which
has two faces-inbound and outbound.
Chesbrough first proposed open innovation as a new
paradigm for the management of innovation in [1]. Open
innovation is defined as the use of outflows and inflows
of knowledge to promote internal innovation, and to
expand the markets for external use of innovative ideas,
respectively. It comprises both outside-in (inbound) and
inside-out (outbound) movements of technologies and
ideas. Open innovation has received increasingly attention
both in theoretical research and business practice, but so
far it has hardly been analyzed in inbound and outbound
simultaneously. Moreover, although the relationship
between open innovation and innovative performance has
been studied in prior works, the mechanism of the process
is considered as a ‘black box’. This study addresses this
gap by considering both inbound and outbound open
innovation and studying the mechanism of how open
innovation affects innovative performance.
II. CONCEPTUAL BACKGROUND
The role of networks, communities, and linkages has
been more and more popular in investigations of
innovation. Reference [2] indicates that open innovation
is not new; already in the 1980s many authors comment
on how the approach towards innovation changed from a
closed model to a model in which firms across industries
started to increasingly rely on the acquisition of external
technologies to complement their technology portfolios.
Reference [3] divides the concept of open innovation into
two main types of activities: inbound open innovation and
outbound open innovation. In the case of inbound open
innovation, ideas are external to the firm, stemming from
suppliers, customers and other external actors (through
technology
in-licensing,
acquisition
or
joint
development), increases the innovativeness of the firm. In
the case of outbound open innovation, companies look for
external organizations that are better suited to
commercialize (part of) the firms’ given technology (for
instance through intellectual property or brand outlicensing). Dahlander and Gann combine bibliographic
analysis of all papers on the topic published in Thomson’s
ISI Web of Knowledge (ISI) with a systematic content
analysis of the field to develop a deeper understanding of
earlier work. Their review indicates two inbound
processes: sourcing and acquiring, and two outbound
processes: revealing and selling in [4]. Sourcing refers to
how firms can use external sources of innovation.
Acquiring refers to acquiring input to the innovation
process through the market place. Following this
reasoning, openness can be understood as how firms
license-in and acquire expertise from outside. Revealing
refers to how internal resources are revealed to the
external environment. In particular, this approach deals
with how firms reveal internal resources without
immediate financial rewards, seeking indirect benefits to
the focal firm. Selling refers to how firms commercialize
their inventions and technologies through selling or
licensing out resources developed in other organizations.
In aspect of inbound open innovation, Reference [5]
examines the impact of acquisitions on the subsequent
innovation performance of acquiring firms in the
chemicals industry. Ahuja and Katila find that within
technological acquisitions absolute size of the acquired
knowledge base enhances innovation performance, while
relative size of the acquired knowledge base reduces
innovation output in [5]. Katila and Ahuja's findings in
the global robotics industry suggest that firms' search
efforts vary across two distinct dimensions: search depth
or how frequently the firm re-uses its existing knowledge,
and search scope or how widely the firm explores new
knowledge [6]. Zhang Yan and Li Haiyang examine the
relationships between new ventures’ ties with service
intermediaries and their product innovation in the context
of a technology cluster. They propose that new ventures'
ties with service intermediaries enable the ventures to
plug into these networks and contribute to the ventures'
product innovation by broadening the scope of their
external innovation search and reducing their search cost
[7]. Using a large-scale sample of U.K. manufacturing
firms, Laursen and Salter link search strategy to
innovative performance, finding that searching widely and
deeply is curvilinearly (taking an inverted U-shape)
related to performance [8]. In [9], Chen, Chen, and
Vanhaverbeke analyze how the innovative performance is
affected by the scope, depth, and orientation of firms’
external search strategies. They apply this analysis to
firms using STI (science, technology and innovation) and
DUI (doing, using and interacting) innovation modes.
Based on a survey among firms in China, they find that
greater scope and depth of openness for both innovation
modes improves innovative performance indicating that
open innovation is also relevant beyond science and
technology based innovation.
In aspect of outbound open innovation, Lichtenthaler
uses data from 136 industrial firms to test four hypotheses
on the moderating effects of environmental factors in the
relationship between open innovation strategies and firm
performance. The results show that the degree of
technological turbulence, the transaction rate in
technology markets, and the competitive intensity in
technology markets strengthen the positive effects of
outbound open innovation on firm performance. By
contrast, the degree of patent protection does not facilitate
successful open innovation [10]. Lichtenthaler and Ernst
use data from a survey of 154 industrial firms are to test
three hypotheses relating technology aggressiveness,
external technology acquisition, and external technology
exploitation[11]. The results show that technology
aggressiveness is negatively related to the extent of
external technology acquisition and is highly positively
related to external technology commercialization.
Reference [12] have shown that most firms’ External
technology commercialization (ETC) activities are still
relatively limited in comparison with internal technology
exploitation, i.e., product marketing. Owing to the high
margins that may be realized in these activities, however,
successful ETC operations may strongly contribute to the
operating income of firms. As this aspect had only been
described for the examples of some pioneering firms, their
results have provided empirical evidence for this fact.
Furthermore, a considerable increase in ETC over the past
5 years could be observed, and firms that do not actively
address this issue will tend to fall behind their competitors.
As ETC may have a considerable impact on a firm’s
product business due to its strategic dimension, e.g., by
setting industry standards, successful ETC may essentially
contribute to firm performance. When come to the other
process of outbound open innovation, Henkel argues that
revealing is strongly heterogeneous among firms.
Multivariate analysis can partly explain this heterogeneity
by firm characteristics and the firm’s purpose behind
revealing. An analysis of reasons for revealing and of the
type of revealed code shows that different types of firms
have different rationales for openness [13]. von Hippel
discusses three conditions under which user innovation
networks can function entirely independently of
manufacturers. He then explores related empirical
evidence, and concludes that conditions favorable to
horizontal user innovation networks are often present in
the economy [14].
III. THE MECHANISM OF HOW OPEN
INNOVATION AFFECTS INNOVATIVE
PERFORMANCE
Reference [2] indicates that firms may open up their
innovation processes on two dimensions. While inbound
open innovation refers to the acquisition of external
technology in open exploration processes, outbound open
innovation describes the outward transfer of technology in
open exploitation processes. Prior open innovation
research has focused on the inbound dimension, whereas
the outbound dimension has been relatively neglected.
Therefore, we address the relationship between
inbound/outbound open innovation and firm innovative
performance.
A. Inbound Open Innovation And Innovative Performance
The use that firms make of external knowledge in the
production process is called inbound open innovation in
[3]. But this external knowledge does not percolate
smoothly through the boundaries of the firms. Knowledge
has to be identified first; and firms have to look for
mechanisms to assimilate and transform this knowledge.
In other words, they have to rely on absorptive capacity to
take advantage of inbound open innovation.
Stated in [2], Cohen and Levinthal argue that the
ability of a firm to recognize the value of new, external
information, assimilate it, and apply it to commercial ends
is critical to its innovative capacity. Therefore the concept
of absorptive capacity is the key in understanding
successful inbound open innovation, which is
characterized by the reliance on external knowledge.
According to Cohen and Levinthal, the ability to evaluate
and use outside knowledge is a function of the knowledge
source and the level of prior related knowledge and
depends on the ability to appropriate this external
knowledge. As a result, firms with higher levels of
absorptive capacity manage external knowledge flows
more efficiently, stimulate innovative outcomes and thus
obtain competitive advantage.
B. Outbound Open Innovation And Innovative
Performance
Outbound open innovation refers to outward
technology transfer, and it suggests that firms can look for
external organizations with business models that are
suited to commercialize a technology exclusively or in
addition to its internal application in [3]. Therefore,
outbound open innovation points to actively pursuing
external technology exploitation, which refers to the
commercialization
of
technological
knowledge
exclusively or in addition to its internal application, e.g.,
out-licensing.
In the process of open innovation, if a firm goes too
far in emphasizing the protection of internal knowledge, it
will be isolated by other firms. Therefore, it can not
acquire the knowledge from outside. In other words,
proper outbound open innovation can prevent a firm from
being isolated by other firms and improve its influence in
the innovative network. As a result, outbound open
innovation is positively related to innovative performance.
Prior research into outbound open innovation has
primarily focused on internal factors, e.g., complementary
assets. Because of the inter-firm nature of open innovation
processes, the effect is not exclusively determined within
the firm. Instead, transaction cost theory underlines the
role of a firm’s environment in outbound open innovation.
It is hard to make ‘keep or sell’ decisions independently
from a firm’s environment. We propose that the
relationship between outbound open innovation and
innovative performance is influenced by environmental
moderators. If firms in a cluster trust in each other, they
will release more knowledge. Firms can get more
knowledge they need and improve their innovative
performance. As a result, in a cluster with more trust,
firms will achieve higher innovative performance through
outbound open innovation.
IV. OPEN INNOVATION IN DIFFERENT TYPES OF
INDUSTRIAL CLUSTERS
We divide industrial clusters of Zhejiang Province
into 3 types: labor-intensive, capital-intensive and
technology-intensive. The importance of inbound and
outbound open innovation may differ in different types of
industrial clusters. Again, we consider two inbound
processes: sourcing and acquiring, and two outbound
processes: revealing and selling in different types of
clusters. We will discuss this issue in detail in the
following parts.
A．Labor-intensive industrial clusters
Labor-intensive clusters in developing countries are
often marked by low wages, unskilled work, and
sweatshop conditions of employment. Labor-intensive
industries are particularly susceptible to vertically
disintegrated network forms of organization and to largescale labor pooling processes, and both of these features
promote agglomeration, especially where producers face
intensely competitive and unstable markets. Tendencies to
agglomeration are boosted by localized learning effects.
As a result, in the process of inbound open innovation,
firms in the labor-intensive clusters tend to implement
sourcing rather than acquiring. Meanwhile, the lowtechnology nature of these firms makes it easy to learn
from each other. Therefore, it is difficult for these firms to
prevent revealing, one type of outbound open innovation.
Because there is little intellectual property in these firms,
acquiring and selling are not popular in labor-intensive
clusters.
Stated in [15], in more advanced agglomerations, the
bottom tiers of the production system seem nowadays to
be less and less strongly tied to local accretions of
competitive advantages,
and
many of these
agglomerations are now rapidly losing significant shares
of their low-end production activity in spite of widespread
employment of cheap immigrant workers. One of the
great policy issues for agglomerations in less developed
countries therefore is how to achieve quality upgrading
and to escape from the low road of pure price competition.
We therefore propose that the breadth of these firms’ open
search strategy should be expanded. Reference [8]
identifies 16 sources of information and knowledge for
innovation activities in U.K. manufacturing firms. They
are suppliers, customers, competitors, consultants,
commercial laboratories, universities, government
research organizations, other public sector, private
research institutes, professional conferences, trade
associations, technical/trade press, exhibitions, technical
standards, health and safety standards and regulations,
environmental standards and regulations. Searching
widely and deeply across a variety of search channels can
provide ideas and resources that help firms gain and
exploit innovative opportunities.
Firms in labor-intensive clusters of Zhejiang are
limited within the cluster in open innovation. We will take
Yuhang home textile cluster for example. Yuhang home
textile cluster has a history over 20 years. Home textile is
one of the pillar industries of Yuhang. In recent years,
home textile industry has grown rapidly. National
industrial policy encourages the textile industry develop
towards high-tech direction. Yuhang home textile industry
continues to expand its scale. Firm’s new investment
projects are gradually increasing. However, firms in
Yuhang home textile cluster are at the risk of lock-in at the
low end of value chain. Firm’s design idea is far behind
developed countries and the products position at low-end
markets. Local firms do not spend much money on R&D
and design. As a result, the profit is low. In selling,
because there is no local firms dominating, selling is
controlled by large enterprises over seas. To break the
lock-in at the low end of value chain, local firms should
enhance the R&D and design capabilities. Besides,
local firms should search for new knowledge at a larger
range. Inbound open innovation is necessary.
B．Capital-intensive and technology-intensive industrial
clusters
Reference [9] argues that managing innovation is
quite heterogeneous across industries. Reference [16]
explains this heterogeneity by distinguishing between two
modes of innovation: the STI-mode (science–technology–
innovation) and DUI-mode (learning by doing, using, and
interacting).
Science–technology–innovation
is
characterized by a scientific approach and is largely based
on codified scientific and technical knowledge. This mode
relies strongly on research and development activities in
the companies. According to the intrinsic characteristics
of technological innovation, firms using STI-mode of
innovation have to cope with the rapid change of both
technological opportunities and market conditions.
In capital-intensive and technology-intensive clusters,
STI innovation mode is dominant. Firms in these clusters
spend much time and money on innovating. In this
situation, open innovation is critical to these firms. In the
process of inbound open innovation, acquiring and
sourcing is both very important. Firms are willing to buy
intellectual property and technologies from outside.
Meanwhile, they use open search strategy to accessing
external knowledge and absorb external ideas and assess,
internalize and make them fit with internal processes.
Reference [9] argues that for developing STI-mode of
innovations, firms should be open to particular types of
partners to improve innovative performance. Vertical
relations with lead users, major users, suppliers, and
knowledge organizations such as universities and research
institutions may be particularly important as sources of
new products. In the process of outbound open innovation,
many firms are not willing to sell their intellectual
property or technologies to the competitors. Innovations
driven by science and technology are based on R&D and
scientific knowledge. Codified knowledge dominates the
process of innovation. Creating and utilizing explicit
knowledge plays a key role. Codified knowledge is not
sticky and knowledge transfer is easy. Revealing of
knowledge is therefore more probable in capital-intensive
and technology-intensive clusters.
Firms in capital-intensive and technology-intensive
clusters in Zhejiang are lack of outbound open innovation.
We take Jiande chemical industrial cluster for example. Jiande is
a traditional chemical industrial district. Jiande chemical
industry includes about 69 firms. In 2010, the total industrial
output is 8.66 billion. The local chemical industry was formed
by the small firms with products of home-made fertilizers and
pesticides. In the 1990’s, Wynca Chemical Industry Group
eliminated high toxicity and high pollution products and
developed
efficiency
and
low
toxicity of
green pesticide products. At the same time, Jiande
chemical industry developed rapidly. By now, Jiande has
become the largest production base of glyphosate in the
world after the Monsanto. A large number of
SMEs in the cluster emerged during that time.
However, because of the nature of the chemical
industry, every firm’s technology research and
development team is lack of cooperation. Currently,
research and development institutions of Jiande chemical
industry are mainly concentrated in large firms. Under the
concept of technology protection, large firms are reluctant
to sell the technology patents. As a result, there is little
cooperation between the firms in the cluster. The
innovation capability of the cluster is at a low level.
To solve this problem, the firms should change their
way of thinking. The failure rate of technological
innovation is relatively high. Many technical achievements
will not be commercialized successfully. Firms usually
have redundant technology inside. Then firms can
commercialize their technology externally by selling or
licensing. As a result, firms not only get economic returns,
but also enhance its embeddedness in the innovation
network by improve inter-organizational trust and
information sharing process. And firms’ innovation
performance will rise. However, not all the redundant
technology should be externally commercialized. Firms
should protect their core technology which is critical to
their competitive position in the industry.
V. CONCLUSION
In this study, we focus on the impact of the inbound
and outbound open innovation on innovative performance
in firms of industrial clusters. More particularly, we
discuss open innovation in firms from labor-intensive,
capital-intensive and technology-intensive industrial
clusters, respectively. We argue that firms with higher
levels of absorptive capacity manage external knowledge
flows more efficiently, stimulate innovative outcomes and
thus obtain competitive advantage. And in a cluster with
more trust between the firms, firms will achieve higher
innovative performance through outbound open
innovation. What’s more, sourcing and revealing are more
popular than acquiring and selling in firms of laborintensive clusters. However, acquiring and sourcing is both
very important while revealing is more popular than
selling in firms of capital-intensive and technologyintensive clusters.
ACKNOWLEDGMENT
This research is funded by National Science
Foundation of China (71173188), Humanity and Social
Science Foundation of Ministry of Education of China
(10YJA630218), Zhejiang Provincial Natural Science
Foundation (Y7100501) and the construct program of the
key laboratory in Hangzhou.
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