Emerging industries, Open Innovation and Innovation policies
Paolo Landoni
Abstract
Emerging industries are pivotal for socio-economic development, but very difficult to identify and
support. An interesting course of action for policy makers interested in promoting emerging
industries could be to 1) promote mobility and radical open innovation projects of both existing and
new firms (pioneers) 2) support research centres and universities and their collaboration with
pioneers 3) help the re-integration of struggling pioneers in other firms and research centres.
Keywords: Innovation, innovation policies, emerging industries, open innovation, pioneers
Profile
Paolo Landoni is Assistant Professor at the Politecnico di Milano university and co-director of the
Master on Open Innovation and Knowledge Transfer of the MIP Business School. His research is
in the area of social, sustainable and collaborative innovation management and he considers both
the firms’ perspective and the perspectives of public institutions and non-profit and hybrid
organizations. He has published 5 books and papers in relevant peer-reviewed journals (such as
Research Policy, Technological Forecasting and Social Change, International Journal of
Technology Management, Creativity and Innovation Management, Project Management Journal,
Research Evaluation, Technology Analysis & Strategic Management). He has served as a
consultant for firms, non-profits organisations and governments and governmental institutions for
the development of innovations and innovation policies.
Emerging industries, Open Innovation and Innovation policies
Introduction
In this discussion paper we are going to address the relationship between two concepts that are
increasingly important in the innovation policy debate: emerging industries and open innovation.
We will argue that innovation policies aimed at promoting the development of emerging industries
both at local and national level could do so favouring an open innovation approach in the
innovation systems.
The discussion paper is organized as follows: first, we introduce the concept of emerging industries
and open innovation, then we will discuss the interaction between these concepts and the
implications for innovation policies.
Emerging industries
The concept of an emerging industry can be seen as the intersection of a unit of analysis and a
temporal interval (Forbes and Kirsch, 2011). The unit of analysis is the industry or the industrial
sector, that is a group of firms using similar technologies and/or producing products that are close
substitutes for one another (Porter, 1980; Hitt et al., 2009; Horii, 2012). The temporal interval refers
to the fact that emerging industries are industries in the earliest stage of development (Low and
Abrahamson, 1997; Van de Ven and Garud,1989).
From this definition it follows that the concept of emerging industry corresponds to one temporal
interval within an “industry life cycle” model (McGahan et al., 2004). It assumes that industries
evolve over time and that it is possible to identify a beginning and an end to this evolution.
However, while it is widely acknowledged that industries change significantly over time, it is not
easy to identify laws regarding their evolution and precise definitions regarding the evolution
phases.
In particular, the length of the “emergence interval” can vary significantly across industries, and its
precise temporal boundaries are a subject of disagreement.
Low and Abrahamson (1997) mark the end of the emergent stage at the beginning of an industry's
growth stage, but others extend the emergent stage past the growth stage to some later point,
alternately characterized as “maturity”, “legitimation”, or “stability” (Aldrich and Ruef, 2006; Klepper
and Graddy, 1990).
Some authors identify the beginning of emerging industries inside pre-existing industries and
before the concrete manifestation of the new products or services. For instance Christensen's
historical analyses of the disk drive industry (e.g., Christensen, 1993) consider when and why firms
in relatively established industries are vulnerable to the disruptive threats of emerging industries.
Garud et al.'s (2002) study SunMicrosystems' efforts to sponsor its Java technology as a common
standard even before the clear emergence of product-markets based on that technology.
Klepper and Graddy (1990) shown that an industry can take as few as two years to more than fifth
years to achieve stability, which they define as the point at which the number of firms in the
industry peaked. However, not all industries last long enough to experience all stages of
development: some never grow to maturity or legitimacy. Of these inchoate industries, some lie
dormant for decades.
Forbes and Kirsch (2011) argue that there are still many open questions also regarding “which
types of firms tend to arise in new industries, and under what conditions”.
The firms that comprise a new industry may be either de alio (i.e., firms that already had a
presence in another market) or de novo entrants (i.e., newly established firms), or both (Khessina
and Carroll, 2008; Lange et al., 2009). Some industries arise primarily through the entry of new,
independent (de novo) firms, such as the many “dotcom” firms that took root in new Internetrelated industries in the mid-1990s (Goldfarb et al., 2007).
However, industry emergence need not depend primarily on de novo entrants. For example, the
disk array industry that emerged in the late 1980s and early 1990s was comprised primarily of
large firms, such as IBM and Compaq, that had established businesses in other computer-related
industries (McKendrick et al., 2003).
The reasons behind the emerge of emerging industries
The notion that long-term economic growth is primarily the result of the growth of knowledge is now
a widely held view among economists. The growth of knowledge, especially technological
knowledge, is the results of research activities in research centres and universities (mainly bluesky, basic, fundamental research) and of R&D activities in firms.
However firms experience a conflict in the choice of technology, and therefore in the direction in
which knowledge grows (Horii, 2012; Bloom et al. 2007). On one hand, a firm has an incentive to
adopt the same technologies, knowledge and product offer as existing firms to reduce its operating
costs and risks. This leads to groups of firms, i.e. industries, that exploit the benefits of
accumulated knowledge. On the other hand, firms can attract large demand if they can adopt
previously unexplored technologies and ideas so that their new goods and services fit consumers'
unsatisfied wants and needs.
Once some pioneering firms adopt the new technology or ideas, more firms use the same
approach or technology to leverage the knowledge accumulated by the pioneers, which gives rise
to a new industry.
In his model Horii (2012) shows that by repeating this process, the economy grows through the
emergence of new industries that serve a progressively wider range of human wants and needs
while reasonably utilizing past knowledge. This type of dynamics causes the rate of economic
growth to fluctuate. In particular, it captures the observed tendency that the emergence of a new
industry that utilizes a new technology (e.g., electricity or information technology) reduces the rate
of per capita GDP growth in the initial phase, a phenomenon known as the “productivity slowdown
puzzle.” The model shows that this slowdown occurs because emerging industries diversify the
GDP share of individual industries and diminish the benefits of the agglomeration economy
resulting from knowledge accumulation within an industry. The model demonstrate that new
industries disproportionately contribute to the economy's productivity growth after they become
large.
Open Innovation
After Solow (1957) found innovation and technical progress to be the main drivers for economic
growth, researchers and managers associated the establishment of a strong internal R&D
capability with innovativeness. Today, due in particular to stronger global competition, higher risks
and higher costs many companies are adopting open innovation approaches that go beyond the
‘do-ityourself’ approach.
In the old model of closed innovation, firms relied on the assumption that innovation processes
need to be controlled by the company – the old model was based on self-reliance (fig. 1).
Open innovation is an approach where firms commercialize both external and internal
ideas/technologies and use both external and internal resources. In an open innovation process,
projects can be launched from internal or external sources and new technology can enter at
various stages. Projects can also go to market in many ways, such as out-licensing or a spin-off
venture in addition to traditional sales channels (Chesbrough,2003b).
Figure 1 - Closed innovation vs Open Innovation
Research
Development
Research
Development
Markets
boundaries
Markets
boundaries
Source: adapted from Chesbrough, 2003b
A central part of the Open innovation process is an organized search for new ideas that have
commercial potential (Laursen & Salter, 2006), for new technologies and new partners.
Furthermore Open innovation entails the shift in perspective described in table 1.
However internal R&D capabilities remain a prerequisite. Cohen and Levinthal (1990) underlined
the importance of investing in internal research in order to be able to utilize external technology, an
ability they termed, ‘absorptive capacity.’
Table 1 – contrasting principles of closed and open innovation
Source: Chesbrough, 2003a
Both big and small firms can benefit from an open innovation approach. Big firms can find new
ideas and technologies for their products and services, small firms can complement with external
sources their limited internal R&D resources.
Firms can involve in their open innovation processes suppliers, clients, engineering and design
companies, research centres and universities and firms in other industries.
In the past these relationships have been mainly one-to-one (e.g. technology transfer) or in small
groups (consortia). Recently, leveraging on Information and Communication Technologies firms
have involved also crowds of users and inventors in open source projects and in crowdsourcing
initiatives (e.g., Innocentive or Ninesigma platforms).
Furthermore, firms have always learnt from competitors and potential competitors. For instance
Chesbrough (2003b) remembers the classic example of Xerox and its Palo Alto Research Center
(PARC). PARC’s researchers developed numerous new technologies such as Ethernet and the
graphical user interface (GUI). However, Xerox did not viewed these inventions as promising
businesses because it was focused on copiers and printers. These technologies languished inside
Xerox, only to be commercialized by other companies. Apple Computer, for instance, exploited the
GUI in its Macintosh operating system while Microsoft did the same in its Windows operating
system.
Innovation policies for emerging industries
Given the importance of innovation for social and economic development it is easy to understand
the interest of policy makers for innovation policies. In particular policy makers will be happy to
identify in advance emerging industries and to invest on them in their countries or regions to gain a
competitive advantage.
However, as previously seen, it is not easy to identify the most promising emerging industries in
advance and there are many different ones that can be interesting to invest in. Some emerging
industries will not mature at all, some of them will remain emerging industries for decades.
Furthermore, as previously seen, it is not easy to identify the pioneer firms, also because they can
be both new firms and existing ones.
Finally, as can be noted also from a recent policy paper for the EU (Monfardini et al., 2012), it is
difficult to understand the difference and the priority between emerging industries (e.g. drones
industry, driverless car industry, personal medicine industry, wearable product industries) and
emerging technologies (e.g. nanotech, human sensors, artificial intelligence, etc.). As a matter of
fact it is also very difficult to understand which are the most promising technologies and the most
promising area of development inside these technologies (e.g., Salerno, Landoni, Verganti, 2008).
Innovation policies to support well recognized emerging industries as the ones above remain
important. However efforts to identify and promote new emerging industries can be misplaced.
Given the increasing importance of the new Open Innovation approach, policies that leverage this
approach could be useful to promote the birth and development of new industries. On the one
hand, many new industries have been based on the successful combination of existing knowledge
from different sources and, on the other hand, new technologies increasingly need the pooling of
resources and capabilities of different actors. As highlighted in Boschma and Gianelle (2014) there
are many examples in which “technologically unrelated activities made new combinations and led
to new growth impulses.” The tourist industry is such an example, as it is making new connections
between unrelated activities, like ICT, design, art and gastronomical activities.
An interesting course of action for policy makers interested in promoting emerging industries could
thus be to 1) promote mobility and radical open innovation projects of both existing and new firms
(pioneers) 2) support research centres and universities and their collaboration with pioneers 3)
help the re-integration of struggling pioneers in other firms and research centres.
First, there is increasing evidence that labour mobility is a crucial mechanism through which skills
and experiences are transferred between firms, industries, regions and nations (e.g., Baruffaldi and
Landoni, 2012; Neffke and Henning, 2013). Promoting mobility and collaborative projects between
firms could help develop new knowledge and new industries. In particular if the collaborative
projects are designed to involve firms across different industries and to involve both new and
existing firms together.
Second, given the importance of the development of new knowledge, the investment in research
and thus in research centres (including industrial design and engineering centers) and universities
remain essential. As remain essential the involvement of these actors in collaborative projects to
transform the research results in new technologies and innovation. To promote this collaborative
projects, and the ones previously described, policy support to innovation platform and
crowdsourcing platform could be useful.
Third, there is evidence that de novo entry is more common than de alio entry in emerging
industries and also that de novo firms are, on average, less successful than de alio entrants
(Dinlersoz and MacMillan, 2009; Geroski, 2003). For this reasons, besides promoting the
collaboration between existing and new firms, policy makers could support the new firms that have
tried to introduce new technologies and products but are struggling to cover the costs that they
have sustained. As a matter of facts, pioneers invest time and resources for results that, as
previously noted, can then became common knowledge for entire industries. As a matter of facts
many pioneers encounter financial problems (e.g., Olleros, 1986). Help from policy makers to reintegrate struggling pioneers in other firms and universities could lower the risk for the pioneers
and could strengthen the receiving firms and research centres.
In general there are many information and technologies available and being developed, what is
needed are entrepreneurs able to understand their potential and to have visions of future products
and services that incorporates them. This is what happened when Nintendo in 2006 met
STMicroelectronics, which together with Analog Devices manufactured the MEMS motion detecting
microchips that were used in the Wii’s motion controllers and that are present everywhere these
day. This is what happened when Steve Jobs of Apple met the researchers of the Xerox research
lab and learnt about the GUI.
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