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Corporate Accelerators: Transferring Technology Innovation to Incumbent Companies

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The recent phenomenon of corporate accelerators is an excellent opportunity for incumbent companies to participate in promising innovations from startups all over the globe. Incumbent companies introduce structured accelerator programs for cohorts of startups, which in turn benefit from resources, mentoring and networks. The underlying research analyzes the growing interdisciplinary scientific literature on corporate accelerators to shed light on this uprising topic. We conducted a literature review according to the guideline of Webster and Watson (2002) by analyzing 20 scientific references. The results show that researchers applied qualitative methods to explore accelerators in detail and quantitative methods are used to analyze secondary data on startups and accelerators. Overall, most findings of recent research are of exploratory nature and our results summaries the main findings of the articles. Finally, we extracted a list of success factors for incumbent companies running corporate accelerators as well as for startups participating in such programs. In terms of theoretical impact, the articles analyzed apply open innovation theory, the resource based view and institutional theory to explain corporate accelerators. Our study reveals that Information Systems research has so far neglected to conduct studies researching corporate accelerators although the findings of our review show large potential for future research. http://aisel.aisnet.org/mcis2016/57
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Tenth Mediterranean Conference on Information Systems (MCIS), Paphos, Cyprus, September 2016
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CORPORATE ACCELERATORS: TRANSFERRING
TECHNOLOGY INNOVATION TO INCUMBENT
COMPANIES
Completed Research
Bauer, Stefan, Vienna University of Economics and Business, Vienna, Austria,
Stefangeorgbauer84@gmail.com
Obwegeser, Nikolaus, Aarhus University, Aarhus, Denmark, nikolaus@mgmt.au.dk
Avdagic, Zlatko, Vienna University of Economics and Business, Vienna, Austria,
Zlatko.Avdagic@gmx.at
Abstract
The recent phenomenon of corporate accelerators is an excellent opportunity for incumbent
companies to participate in promising innovations from startups all over the globe. Incumbent
companies introduce structured accelerator programs for cohorts of startups, which in turn benefit
from resources, mentoring and networks. The underlying research analyzes the growing
interdisciplinary scientific literature on corporate accelerators to shed light on this uprising topic. We
conducted a literature review according to the guideline of Webster and Watson (2002) by analyzing
20 scientific references. The results show that researchers applied qualitative methods to explore
accelerators in detail and quantitative methods are used to analyze secondary data on startups and
accelerators. Overall, most findings of recent research are of exploratory nature and our results
summaries the main findings of the articles. Finally, we extracted a list of success factors for
incumbent companies running corporate accelerators as well as for startups participating in such
programs. In terms of theoretical impact, the articles analyzed apply open innovation theory, the
resource based view and institutional theory to explain corporate accelerators. Our study reveals that
Information Systems research has so far neglected to conduct studies researching corporate
accelerators although the findings of our review show large potential for future research.
Keywords: Corporate Accelerator, Outside-In Open Innovation, Startups.
Bauer et al. /Corporate Accelerators for Technology Innovation
Tenth Mediterranean Conference on Information Systems (MCIS), Paphos, Cyprus, September 2016
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1 Introduction
Incumbent companies are under pressure because disruptive new technology innovations are on the
rise and undermine traditional business models (Chesbrough, 2010). Recent history shows clearly that
many incumbent companies such as Kodak overlooked innovative tech trends (Lucas and Goh, 2009).
Incumbent companies struggle to be innovative, because they suffer from organizational inertia (Hill
and Rothaermel, 2003). According to previous research and practitioners’ reports, many incumbent
companies fail to develop innovative solutions.
The number of startups is growing across all industries, often focusing on promising and disruptive
innovations (Chesbrough, 2010). During the last decade, there are many examples of disruptive
innovations found by startups, such as new digital products using disruptive technologies (e.g. mobile
applications) for achieving service innovation (Pai, 2014). In general, a startup is a growth-oriented
business that is seeking for a repeatable, scalable business model, which builds on innovative products
or services in an uncertain and volatile environment (Radojevich-Kelley and Hoffman, 2012).
Founders and startup teams are mostly known for their drive for innovation and performance, their
flexibility and innovativeness (Wasserman, 2016).
The innovation gap between incumbent companies and startups led to the development of various
mechanisms, designed to allow incumbent firms to take advantage from startups innovation potential
(Miller and Bound, 2011). However, the increasing amount of venture capital available results in
higher competition for promising tech innovations. Promising innovative startups in late stages are
overpriced/high in price and therefore incumbent companies are searching for ways to attract startups
before their development is completed and the valuation is high. Corporate accelerators are a
possibility for incumbent companies to transfer innovation from startups to incumbent companies
(Kohler, 2016).
Corporate accelerators are special organizational forms to create an outside-in open innovation process
(Weiblen and Chesbrough, 2015). The outside-in process is defined as the integration of external
knowledge from external partners (e.g. startups, universities, customers) to increase the quality and
pace in the innovation process of the company (Gassmann and Enkel, 2006; Miller and Bound, 2011).
Further, corporate accelerators are defined as “a time-limited program which startups can apply for if
their product falls into a certain category“ (Weiblen and Chesbrough, 2015). Recently corporate
accelerators received growing attention in academic and practitioners’ literature (Miller and Bound,
2011).
The underlying paper aims to analyze the academic literature on corporate accelerators since 2005.
Until now, only few theories are applied to the concept of corporate accelerators and the academic
research has just began to understand the concept of accelerators. The research objective is to highlight
research gaps and possibilities for further empirical research. Further, we aim to uncover possible links
to scientific theories from the Information Systems field to outline a future research agenda.
The remainder of the paper is structured as follows. Section two consists of definitions and
delimitations of the topic and the terms. Afterwards, we move on to describe the research
methodology. Then we present the results of the literature review in detail. Finally, we critically
discuss previous findings and outline connections to interdisciplinary research. Section six gives a
short conclusion.
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2 Theoretical Background
Corporate accelerators offer development programs for promising high tech startups to develop their
products and services mostly in early stages by offering mentoring, networking, management services,
knowledge and expertise, services, access resources from stakeholders and office space (Clarysse and
Yusubova, 2014; Malek et al., 2014; Radojevich-Kelley and Hoffman, 2012). YCombinator, the first
accelerator, was founded in US in the year 2005 and since that year several accelerators have been
introduced all over the world such as 500 Startups, Techstars and Amplify LA (Regmi et al., 2015;
Kohler, 2016). The first corporate accelerator was founded in 2010 (Kohler, 2016). Some authors
define accelerators as special types of incubators (Malek et al., 2014). However, these two models can
be distinguished by different characteristics. Accelerator programs are set up for short time periods,
commonly three months (Cohen and Hochberg, 2014; Weiblen and Chesbrough, 2015), in opposite to
incubators, which usually last between one and five years (Barrow, 2001). The limited duration of an
accelerator raises the founder’s attention on the startup and lead to a fast evaluation of the ideas
(Cohen, 2013). Longer relationships often lead into mutual dependencies between the agents and
therefore accelerators promote quick growth or failure of a startup (Kohler, 2016).
Networking and funding are essential aspects for startups joining an accelerator program. A corporate
accelerator selects a cohort of startups from the applications to participate in an accelerator program
(Cohen and Hochberg, 2014). The founders of these cohorts in an accelerator program get the
possibility to connect with each other, benefiting from their diverse skills and helping each other in
difficult situations (Cohen and Hochberg, 2014). One of the highlights of an accelerator program is the
public pitch event, often called demo day, where investors and business angels participate (Kohler,
2016).
Accelerators often tackle one main challenge for startups, namely the life support trap (Mian et al.,
2016). Accelerators usually receive an equity stake of 5 to 7% in return for a five-figure investment
(Clarysse and Yusubova, 2014; Fehder and Hochberg, 2014). Figure one summaries the relationships
of the agents within an accelerator program.
Figure 1 Relationship of Agents within an Accelerator Program (own creation)
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In principle, there are two different models of corporate accelerators, namely generic and specific
accelerators (Cohen and Hochberg, 2014). Generic accelerator programs are targeting many kinds of
startups, in contrast to specific accelerators, which focus on particular industries and technologies.
Interestingly, most corporate accelerators are vertically focused (digital products) (Kohler, 2016).
Famous corporate accelerators are run in the field of healthcare (Bayer), insurance (Allianz),
entertainment (Disney) or consumer packaged goods (Coca-Cola) (Kohler, 2016).
Compared to the dot-com era, new startups profit from shrinking costs for setting up innovative
business models (Miller and Bound, 2011). First, hardware and software costs of technology are
cheaper because of cloud services and the open source trend. Second, there are easier routes to acquire
customers through social media and search engines. Third, business model innovations lead to better
forms of direct monetization (Miller and Bound, 2011; Dempwolf et al., 2014).
3 Methodology
For our literature review we followed the methodological guidelines of Webster and Watson (2002).
We defined the research area of corporate accelerators and set the goal of getting an in depth review of
the scientific literature from 2005 to 2016. The research scope was limited to include scientific articles
since 2005 because the first accelerator was found in that year. After defining the research scope, the
keywords ‘corporate accelerator(s)’, ‘business accelerator(s)’ and ‘accelerator(s)’ were used to find
academic literature in the databases Google scholar (https://scholar.google.at/) and Sciencedirect
(http://www.sciencedirect.com/). We selected these two databases because both databases index most
significant journals and conferences in the Information Systems and Management domain.
Unfortunately, due to legal rights, few articles are not accessible for us (Hallen et al., 2014; Yu, 2014).
As a first step we manually screened all relevant articles. We excluded all articles, which were not
relevant to our topic of interest by a screening the articles for insights on corporate accelerators. We
arrived at a final set of 20 scientific articles, which we analyzed in detail following (Webster and
Watson, 2002).
4 Results
4.1 Journals and Conference Proceedings
Most scientific literature was published in Management journals (e.g. California management review,
Long Range Planning), Finance journals (e.g. The Journal of Private Equity, Journal of Corporate
Finance) and innovation journals (e.g. Technovation). Further, several articles were published in
conference proceedings from the field of Management and Innovation research. Interestingly, no paper
was published in an Information Systems outlet, although information technology plays a crucial role
for accelerators and technology startups. Besides the academic literature, we also used the findings of
reports (Dempwolf et al., 2014) and practitioners literature (Miller and Bound, 2011) for our analysis.
4.2 Research Methodologies
In terms of methods, most scientific research on accelerators is of qualitative nature. These studies are
often based on semi-structured interviews of accelerator managers and participants (startups).
Accelerators are a relatively young phenomenon; hence science explores the field by qualitative
studies. Some authors point out that the field is not (yet) accessible by traditional quantitative
methods, as it lacks large sample sizes for statistical analysis (Radojevich-Kelley and Hoffman, 2012).
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We found four quantitative papers, which all used secondary data for their analysis. One paper used a
mix of qualitative and quantitative methods, in contrast to one research, which conducted a literature
review on incubators and dealt with accelerators in their paper. Finally, one economic analysis in form
of a portfolio analysis was carried out.
4.3 Overview of main findings
Author/Paper Methodology Findings
(Kohler, 2016) Qualitative analysis: In total 40
interviews with corporations’
managers and participants
(startups) of corporate
accelerators.
Framework and strategies for managers to design
corporate accelerators (proposition [relationship
between the corporation and the startup in terms of
process, people, and place], process [from selection
phase to graduation], people [both inside and outside
the company], and place).
(Pauwels et al.,
2016)
Qualitative analysis: Semi-
structured interviews with
managing directors of 13 cases
(accelerators) combined with
analyzation of archival data.
Identification of key design parameters. There exists
three different types of accelerators (The ecosystem
builder, the deal-flow maker, the welfare stimulator)
and five different building blocks. Accelerators are
seen as a distinctive incubation model.
(Mian et al.,
2016)
Literature Review of the business
incubator literature from 1985 to
2014. Accelerators are discussed
as a new phenomenon in the
ecosystem.
There is a lack of scientific research on the role and
efficacy of accelerator programs. Accelerators are an
important part of the ecosystem.
(Weiblen and
Chesbrough,
2015)
Qualitative case study: Semi-
structured interviews with 12
executives, program managers,
industry analysts, and startup
CEOs.
Typology of corporate mechanisms to engage with
startups: corporate venturing, corporate incubation,
startup program outside-in and inside-out platform.
(Balance speed and agility against control and strategic
direction). Accelerators are outside-in open innovation
programs.
(Holstein, 2015) Descriptive study based on a not
defined number of interviews and
secondary sources (websites of
startups, universities).
VC firms and angel investors benefit from non-profit
accelerators because of the selective application
process. Startups are forced to grow or fail fast in the
short time period. There is a significant impact on
economy (jobs, taxes, and higher wages).
(Regmi et al.,
2015)
Quantitative analysis: Secondary
data from seed-db.com. Data
about 165 accelerators and 4800
startups since 2005 worldwide.
Accelerators increase the chances of a startup to
survive by approximately 25%. The study distinguishes
between accelerators based in US and outside US.
Compared to startups in US, startups from elsewhere
have a better success rate.
(Scott et al.,
2015)
Quantitative research: Secondary
data from 652 ventures in
multiple industry sectors
(evaluated over an eight year
period)
Empirical evidence for the higher chance of reaching
commercialization of positive evaluated innovations
(startups) from a large number of skilled practitioners
in the entrepreneurship and technology communities
(Cohen and
Hochberg,
2014)
Secondary data analysis based on
the seed accelerator ranking
project and previous research
(Cohen, 2013).
Definitions and delimitation of accelerators from other
stakeholders in the ecosystem (such as incubators,
angel investors) are provided. Description of different
kind of accelerators such as private and public
accelerators (distinguished by sponsors).
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(Fehder and
Hochberg,
2014)
Quantitative analysis of secondary
data: panel data set of US Census
MSA regions across ten years.
Accelerators have regional impact on the
entrepreneurial ecosystem. Accelerators lower the
search costs for both entrepreneurs and investors
seeking early stage investments. As such, accelerators
are predicted to stimulate an increase in the level of
startup investment activity in a region.
(Malek et al.,
2014)
Qualitative analysis: Interviews
with managers and entrepreneurs.
Benchmarking analysis based on
publically available data (web site
information and reports).
Development of a typology of accelerators’ capabilities
by considering strategy, governance, business model,
operations and finance. Finally, it is illustrated how the
typology can be utilized to describe, understand and
prescribe appropriate capabilities.
(Wise and
Valliere, 2014)
Quantitative research based on
408 firms after participating in
two accelerator programs.
Kaplan-Meier Analysis of exits.
There is a beneficial effect of the years of start-up
founder experience available in the accelerator
management team on the failure hazard of tenant firms
(each additional year decreases the probability). In
opposite, the degree of connectedness of the
management team has no effect on the failure exit
hazard of the tenant firms.
(Haines, 2014) Ethnography research of two
international field sites (Singapore
and Buenos Aires) complemented
by interviews with accelerator
participants around the world.
Accelerators are seen as sociotechnical systems
enabling innovation and they provide certain cultural
capital (explicit and implicit teaching of certain values
and norms). Founders have to focus on metrics to
benchmark progress. Accelerators play a direct role in
creating value for the product itself.
(Kim and
Wagman, 2014)
Economic analysis: Portfolio
analysis.
Accelerators tend to partially disclose information
(communication of positive signals and conceal
negative signals).
(Dempwolf et
al., 2014)
Conceptual research and analysis
of secondary data from
organizations and media groups.
Taxonomy of accelerators. Long and short term metrics
for accelerators and for startups.
(Sharma et al.,
2014)
Qualitative interviews with
stakeholders of 10 accelerators in
India. Secondary analysis of
available statistics.
Accelerators improve the mortality rate of startups.
Further, accelerators have a positive impact on startups
growth and on their value proposition, team building
and revenue plan.
(Clarysse and
Yusubova,
2014)
Qualitative analysis: Multiple
case study of 13 accelerators from
Europe (Paris, London, Berlin)
based on structured interviews
and informal talks with
accelerators managers.
Identification of success factors under the lens of
institutional theory: Selection process and criteria;
Business support services: mentoring is perceived as
the most important element; External and internal
network opportunity for new ventures (e.g. Demo day).
(Isabelle, 2013) Qualitative and quantitative
research: (1) 10 in-depth
interviews with managers from
six cases from Canada. (2)
Quantitative surveys (N=235) of
participants from incubators or
accelerators in US.
Key success factors which firms should consider: Stage
of venture (accelerators focus on increase growth
quickly); fit with accelerators mission, selection and
graduation policies (flexibility), services provided
(meet the needs), and network of partners (support
firms: legal, regulatory, technical, finance).
(Frimodig and
Torkkeli, 2013)
Qualitative analysis: Semi-
structured interviews with 15
managers of accelerators and
related professionals from various
countries.
The preconditions for the success of an accelerator are
the access to business competence and the ability to
transfer it from itself to the startup.
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(Radojevich-
Kelley and
Hoffman, 2012)
Qualitative analysis based on six
case studies (interviews, website
analysis, and observations).
Empirical evidence for the importance of mentorship
driven programs for increasing success rates of startups
(access to capital). Unique and specific selection
criteria are very important. The Resource Based View
of the firm theory was utilized for the analysis.
(Miller and
Bound, 2011)
Review of publications,
documents and reports from
organizations and science.
Description of the most successful accelerators.
Description of accelerator business models. Criticisms
of the accelerator programs.
Table 1. Main Findings per Article.
5 Discussion
5.1 Categories of Corporate Accelerators
Several articles discuss different categories of corporate accelerators (Cohen and Hochberg, 2014;
Dempwolf et al., 2014; Sharma et al., 2014; Kohler, 2016; Pauwels et al., 2016). While most authors
use simple models and distinguish among nonprofit, public and corporate accelerators (Cohen and
Hochberg, 2014), Pauwels et al. (2016) propose a motivation-based categorization into ecosystem
builder, the deal-flow maker and the welfare stimulator.
First, corporations use the ecosystem builder model for creating a network of stakeholders to finally
connect customers with startups. This model is best suited for incumbent corporations. Second, the
deal-flow maker accelerators aim to uncover promising startups for investors. Finally, the welfare
stimulator type yields to foster economic growth in a region or technological domain. Similar to that,
Sharma et al. (2014) and Dempwolf et al. (2014) distinguished between the driving forces behind an
accelerator. Therefore they differentiated between angel-backed accelerators, corporate-driven
accelerators, VC-backed accelerators and institution driven accelerators (Sharma et al., 2014). The
data of Pauwels et al. (2016) also shows that there exists mixtures of different types of accelerators.
We conclude that research might analyze the certain effects of the specific types of accelerator
programs for reaching the goals of all agents.
5.2 Success Factors for incumbent companies and for startups
Several success factors have been identified for incumbent firms as well as for startups participating in
accelerator programs. The plethora of different designs of corporate accelerators may lead to the fact
that not all success factors can be applied to all types of corporate accelerators. Table 2 provides a list
with all success factors identified for incumbent companies.
Scientific Articles Success Factors for Incumbent Companies
(Radojevich-Kelley and
Hoffman, 2012; Frimodig and
Torkkeli, 2013; Kohler, 2016)
Finding the right selection criteria of startups (e.g. dynamic and diverse
teams with a scalable business model). Unique selection criteria lead to
higher success rates.
(Kim and Wagman, 2014) Finding the right startup portfolio size (number of companies in an
accelerator program)
(Weiblen and Chesbrough,
2015)
Clear definition of companies’ value proposition towards a startup
(Kohler, 2016) Create mutual value through the accelerator program
(Wise and Valliere, 2014) Prior knowledge (number of years of start-up founder experience available
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in the accelerator management team)
(Dempwolf et al., 2014; Haines,
2014)
Incorporation of metrics to track progress of startups
(Weiblen and Chesbrough,
2015)
Definition of expected output of their engagement with startups
(Frimodig and Torkkeli, 2013) Provide access to business competence and ensure the ability to transfer
business competence to the startup
(Frimodig and Torkkeli, 2013) Mentor selection (congruent with primary vision and goals)
(Kohler, 2016) Commit experts and mentors from inside and outside the company
(Weiblen and Chesbrough,
2015)
Set procedures in place to ensure the intake of program created
innovations
Table 2. Success Factors for Incumbent companies and for startups.
Scientific literature on accelerators highlights several factors for incumbent corporates to ensure that
their accelerator programs are a success. First, finding the right selection criteria for startups is very
important (Kohler, 2016). Accelerators, which use unique selection criteria, have higher success rates
for their graduates (Radojevich-Kelley and Hoffman, 2012). The size of the portfolio of startups in an
accelerator cohort is important, because it seems that including too many or too little startups could
lead to unsatisfied results (Kim and Wagman, 2014). Next, the incumbent companies should have a
clear definition of the value proposition toward the startups, because they have to bring resources and
networks in the program (Weiblen and Chesbrough, 2015; Kohler, 2016). Further, corporate
accelerators should incorporate metrics to track the progress of the startup in the program and also to
track themselves (Dempwolf et al., 2014; Haines, 2014). For tech startups, short term metrics are
customer acquisition, activation (percentage that starts using the product), retention (percentage of
users that return to use the product or service again), and long term metrics are revenue or rate of
return to investors (Dempwolf et al., 2014). Moreover, there is a beneficial effect of the years of start-
up founder experience available in the accelerator management team (Wise and Valliere, 2014).
Further, mentorship driven programs increase the overall success rates of start-ups by providing
entrepreneurs with access to angel investors and venture capitalists which tend to increase success
rates (Radojevich-Kelley and Hoffman, 2012). Selecting the right mentors for the specific program
and commiting them to your program is another essential aspect (Frimodig and Torkkeli, 2013).
Finally yet importantly, incumbent companies have to set procedures in place to ensure the intake of
program created innovations
Scientific Articles Success Factors for Startups
(Kohler, 2016) Focus on achieving product - market fit (instead of achieving product -
corporate fit)
(Scott, Shu, and Lubynsky,
2015)
Frequent critical evaluations from a large number of skilled practitioners
(higher likelihood to reach commercialization)
(Haines, 2014) Prioritize the suggestions of mentors and incorporate only useful and
consistent recommendations
(Kohler, 2016) Acceptance that incumbent companies participate in your innovation
(Sharma, Joshi and Shukla,
2014)
Active participation in an accelerator program raises the likelihood of
survival (use the resources to offer freemium or not immediately
sustainable models first)
(Haines, 2014) Follow the lean startup principals
Table 2. Success Factors for Incumbent companies and for startups.
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Startups have to consider several factors for running through an accelerator program. First, startups
have to focus on achieving a product – market fit instead of achieving a product – corporate fit
(Kohler, 2016). Second, it is recommend that startups undergo a frequent critical evaluation form a
large number of skilled practitioners and mentors (Scott et al., 2015). But on the other hand, startups
should prioritize the suggestions of the mentors and they should only consider valuable feedback
(Haines, 2014). Next, startups have to accept that parts of their innovative technology are incorporated
by corporate accelerators (Kohler, 2016). If startups are not ready to accept the technology transfer,
then they should refuse to participate in an accelerator. A huge benefit for startups is the economic
capital, which incumbent companies bring in the relationship. Often, startups can afford to create a
product that is free or freemium or is not immediately sustainable because of the support of the
accelerator (Haines, 2014). Startups may develop their products and services according to the lean
startup principles, in which startups use agile developments practices to develop a minimum viable
product and further focus on customer development and continuous deployment (Haines, 2014).
5.3 Applied Theories and Recommendations for Future Research
Several scientific theories have been applied to accelerators research in recent years, such as the
Resource Based View of the Firm (Radojevich-Kelley and Hoffman, 2012), Open Innovation Theory
(Weiblen and Chesbrough, 2015), and Institutional Theory (Clarysse and Yusubova, 2014). The
applied theories are useful for explaining the phenomenon of accelerators, but there is room for more
elaborated theories in the research context. For example, the Resource Based View may be extended
by the concept of Dynamic Capabilities (Teece et al., 1997), which focuses on the dynamic aspects of
resource configuration and exploitation. Further, within the Open Innovation Theory, corporate
accelerators are categorized as Outside-In innovation (Weiblen and Chesbrough, 2015), but an in
depth analysis of the process of the intake of the innovation by the incumbent company was neglected
until now. Therefore, our interdisciplinary review uncovers a large potential for Information Systems
research to apply Information System theories to the research context of corporate accelerators, such
as absorptive capacity (Cohen and Levinthal, 1990).
Future research will benefit from establishing clear measurements to evaluate and benchmark the
success of accelerators and startups. Until now, secondary data has been analyzed by defining
successful outcomes as acquisitions and unsuccessful outcomes as firm failures (Radojevich-Kelley
and Hoffman, 2012; Wise and Valliere, 2014). In terms of corporate accelerators, success should be
measured by taking their goals of running a corporate accelerator program into account. Besides goals
such as attracting talent and change corporate culture, the main aim for incumbent companies is to
identify innovation from startups and to take advantage of the startups flexibility in the open
innovation process (Weiblen and Chesbrough, 2015). Corporate accelerators lead to market bubbles
because of incumbent companies’ heavy interest in investing (Dempwolf et al., 2014). Hence, we
suggest that strategic management of corporate accelerator programs needs more sophisticated metrics
to track their effectiveness.
Another promising area for future research is the cognitive bias of functional fixedness (Adamson,
1952). Corporates accelerators potentially act as gatekeepers for innovation. In this context, corporate
gatekeepers decide which startups are entering the accelerator and hence gatekeeper managers decide
on the progress of certain innovations. These gatekeeper managers possibly suffer from functional
fixedness, which is a cognitive bias that leads the managers to apply components in the way they are
traditionally used. Functional fixedness of the gatekeeper managers limit their opportunity recognition
and they actively force the startup founders in a specific (social) role through the accelerator program.
This situation is defined as the tactic of altercasting, which is used to force people to specific social
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roles. After joining an accelerator program, there is a mutual dependency between the founders and
the corporate accelerator, in which both agents are restricted by their social roles.
6 Conclusion
The underlying research sheds light on the upcoming trend of corporate accelerators for transforming
startups to sources of corporate innovation. Overall, 20 scientific articles have been analyzed for
uncovering research gaps and controversial discussions on corporate accelerators in the academic
literature. One of the main findings of this research is a list of success factors for incumbent
companies that are planning to or already run an accelerator, and for startups joining such accelerator
programs. Previous research conducted mainly exploratory qualitative research. Only few scientific
theories were applied in existing research. We conclude that research on corporate accelerators should
use previous findings to conduct quantitative and theory testing research in future to discover the
upcoming phenomenon of corporate accelerators.
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... In addition to office space, incubation programs offer various types of support, ranging from legal services and accountancy to training, mentoring, and networking (COHEN, 2013;BAUER;OBWEGESER;AVDAGIC, 2016). Some programs also offer investment capital for startups and connections with potential investors, such as angel investors and venture capitalists (COHEN, 2013;HOCHBERG, 2016). ...
... In addition to office space, incubation programs offer various types of support, ranging from legal services and accountancy to training, mentoring, and networking (COHEN, 2013;BAUER;OBWEGESER;AVDAGIC, 2016). Some programs also offer investment capital for startups and connections with potential investors, such as angel investors and venture capitalists (COHEN, 2013;HOCHBERG, 2016). ...
... In addition to office space, incubation programs offer various types of support, ranging from legal services and accountancy to training, mentoring, and networking (COHEN, 2013;BAUER;OBWEGESER;AVDAGIC, 2016). Some programs also offer investment capital for startups and connections with potential investors, such as angel investors and venture capitalists (COHEN, 2013;HOCHBERG, 2016). ...
Article
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The objective of this research is to understand how startups and established companies perceive the factors that are critical to the cooperation between them in the context of corporate incubation programs. We interviewed innovation managers, analysts, and project leaders from three large companies and the entrepreneurs of the startups that interacted with these companies. The results show that established companies and startups have different perceptions regarding insufficient dedication to the program and cultural differences, although both considered these factors to constrain the collaboration. Regarding motivation and incentives and autonomy, the findings were to some extent different. Implications include the difference in the perceptions of the startups and employees of the established companies directly involved in the program and the two factors identified as critical—dedication to the program and cultural differences—due to their potential to risk the incubation program. To practitioners, this research offers empirical results that can guide decision-making to manage corporate incubation programs. KEYWORDS Open innovation; Corporate incubation; Corporate acceleration; Startups; Technology innovation
... They both offer similar support (Pauwels et al., 2016), such as e.g., access to corporate resources, corporate expertise, mentoring and networking (Bauer et al., 2016). Both corporate accelerators and corporate incubators can be sub-divided, according to their orientation, into external and internal categories (Selig et al., 2018). ...
... According to Kohler (2016) "corporate accelerators are company-supported programs of limited duration that support cohorts of start-ups during the new venture process via mentoring, education, and company-specific resources". Corporate accelerators offer similar services as incubators (Pauwels et al., 2016), but their programs are shorter in duration, and they take a comparatively lower equity stake in the start-up than incubators (Bauer et al., 2016). Corporate accelerators can be described as batch-based, time-limited programs that aim to help the new ventures grow utilizing an intense, short process of development (Cohen, 2013). ...
... There are differences between internal and external accelerators, besides their orientation (Selig et al., 2018). External corporate accelerators aim to stimulate the development of external start-ups that have gone passed the early stage (Bauer et al., 2016). ...
Thesis
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This thesis explores the space of prediction of start-up success through founder personality traits, specifically in corporate accelerator setting. The goal of this thesis was to find out whether there are meaningful parameters that can reliably quantify founder personality characteristics, and whether differences can be found between the general population and successful start-up founder sample group. The thesis answers these questions from a multidisciplinary viewpoint, incorporating management and strategy theories, as well as personality psychology and other psychological viewpoints. The key findings were that there are personality parameters that can be reliably measured from start-up founders. Additionally, there are significant differences between general population and sample group’s results in said parameters. The conclusion is that a prediction model of start-up success based on founder personality parameters is feasible to be developed. This is an important finding within corporate venturing and can be further developed into different applications.
... CAs promise to bridge the gap between corporations and startups, benefitting both sides from the collaboration. Figure 4 (Bauer, Obwegeser and Avdagic, 2016) presents the relationship of all agents within a CA program and the potential two-sided benefits between company and startup. (Bauer, Obwegeser and Avdagic (2016) Establishing CAs can help to make the corporate-startup collaboration more efficient and might lead to a number of follow-up collaborations. ...
... Figure 4 (Bauer, Obwegeser and Avdagic, 2016) presents the relationship of all agents within a CA program and the potential two-sided benefits between company and startup. (Bauer, Obwegeser and Avdagic (2016) Establishing CAs can help to make the corporate-startup collaboration more efficient and might lead to a number of follow-up collaborations. In detail, the corporation might support a startup's pilot project to explore innovation opportunities, become the startups customer to solve one of its pain points, become the startup's distribution partner, invest in the startup to get access to new markets and capabilities or acquire the startup to quickly tackle a particular business problem or to enter a new market (Kohler, 2016). ...
... is an essential success driver because via networking CAs have the opportunity to scout promising startups with talented entrepreneurial teams and disruptive ideas and convince them of participating in their program. Table 5 gives an overview of existing literature on the impact of accelerators as well as on the success factors of setting up independent accelerators and CAs for corporations (based on Bauer et al., 2016). Bauer et al., 2016) Scientific Articles Type Findings Hallen, Bingham, and Cohen (2014) General Impact Compared graduates of some accelerator programs with a matched set of comparable companies that didn't participate in an accelerator program Findings: top programs do in fact accelerate the time for reaching key milestones but positive effects dissipate when looking at a broader sample of accelerators. ...
Thesis
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Corporate Accelerators (CAs) have become an important form of corporate-startup collaboration. According to mm1, two-thirds of all DAX 30 companies in Germany engaged with startups via an accelerator in the year 2018. Despite the clear importance of the CA phenomenon, there is still a lack of understanding of the concrete factors that determine a CA’s success. CAs can be designed in various different ways but business executives are still in the dark about the consequences of these design decisions on a CA’s performance. The study at hand closes this research gap by analyzing the success factors of a selected set of CAs. A database of 109 CAs was developed, from which all Germany based programs (28) were analyzed in greater detail regarding their performance and program design. Hereby, the study tests the statistical relevance of 14 potential success factors identified throughout the literature review. The results show that especially five factors have a significant positive correlation to a CA’s success: 1. The existence of corporate partners 2. A demanding selection process that contains selection days for shortlisted startups 3. A larger amount of startups per batch 4. The obligation for startups to be physically present in the facilities of the CA for the time of the program 5. The incorporation of metrics to track the progress of participating startups as well as the goal achievement of the CA itself. Additionally, the findings show (i) potential success factors that should be taken into account in spite of having no statistical significance, as well as (ii) factors that managers can deprioritize when setting up a CA program. As a result, this study benefits the academic world by closing the research gap on the success factors of CA’s. Moreover, the study provides managers with a practical guide on how to potentially improve their CA’s success and helps startups find the right CA program tailored to their needs.
... Organizationally separated innovation units bear names such as corporate accelerators (Bauer et al., 2016) and incubators (Becker & Gassmann, 2006). Companies may also acquire start-ups or develop spin-offs as means of structurally separating innovation (Burgelman, 1991;Lassen et al., 2006). ...
... As a counter-intuitive implication of such properties of digital artefacts, establishing new product identities can be more difficult in digital innovation. By new identities, we understand both new brands and the introduction of innovations that challenge the identity of organizations as a whole (Tripsas, 2009;Obwegeser & Bauer, 2016). ...
Thesis
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The aim of this dissertation is to explore the organizational and managerial challenges that arise from systematic involvement of digital technologies in innovation. The work in this dissertation primarily contributes to the literature on digital innovation, which identified systematic involvement of digital technologies as an occasion to revise or problematize existing theoretical perspectives on management of technology and innovation. Digital technologies have been theorized in the Information Systems literature as digital artefacts. Digital artefacts are objects made of algorithms and data. Digital products, profiles on social networks, databases of past transactions are all examples of digital artefacts. Digital artefacts are representative of an unusual type of materiality because they do not occupy physical space, can be duplicated and distributed freely. As a consequence, they can be arranged and recombined to achieve seemingly endless potential of configurations. The process of recombining digital artefacts is digital innovation, which this dissertation studies. Digital artefacts are also at the centre of born-digital companies, which provide empirical focus for this dissertation. Existing research has often focused on traditional companies in their efforts to learn to effectively exploit possibilities of digital technologies. Such research provides insight into how digital innovation clashes with traditional innovation and offers insights of undeniable relevance. In contrast, the research here joins the less voluminous stream of research on born-digital organizations. With focus on born-digital organizations, we can uncover logics of digital innovation in their distilled form rather than emphasizing how they contrast or clash with organizing logics of industrial or pre-digital innovation. The dissertation is composed of three papers: a theoretical literature review, a longitudinal case study and, a multiple case study. The first paper argues that consideration of digital artefacts is central to understanding the logic of digital innovation. This argument is developed by a means of a literature review. The theoretical literature review provides assessment of the attention given to digital artefacts in the extant literature and it constructs a research agenda. The second article presents a case study of organizing for innovation in a born-digital company, showcasing how distributable digital artefacts can stifle effectiveness of organizational separation as a vehicle for innovation. The third article investigates, by a multiple case study, how digital artefacts and organizational structures co-evolve as born-digitalcompanies innovate their products. Overall, the dissertation proceeds from a theoretical argument to exploration of an empirical case and development of a more robust theoretical understanding of the case by moving from a single to a multiple case design. Empirical studies in the dissertation relate to a practical problem and hold managerial implications. The empirical problem tackled in papers II and III relates to the situation in which a company wants to develop a radical digital innovation. Is it better to develop the innovation in a new, separated group or is it better to continue development in an existing organization? Paper II highlights that focusing only on organizing can be misleading because digital artefacts can freely travel across organizational boundaries and cause drift from radical to incremental innovation. Paper III presents a multiple case study that revisits this problem and finds out that the decision to organizationally separate an innovation effort appears to be more suitable when a new group of users with a distinct need is being targeted. Organizational separation goes hand in hand with development of separate digital artefacts because organizations and products tend to mirror one another. Overall, the dissertation first emphasizes that, when selecting organizational arrangements for innovation, handling of digital artefacts should be considered alongside organizational structures. Second, the dissertation implies that a choice to organizationally separate may be more appropriate when a new set of users with a distinct need is being targeted by the innovation. Overall, this dissertation uncovered some organizational and associated managerial challenges that are especially salient in born-digital organizations and therefore emblematic of digital innovation. Organizationally, this research highlights the effects that digital artefacts can exert on organizational structures. They can cause drift from organizational separation to integration. They can be re-interpreted and thus interact with identities of especially born digital businesses. Such organizational phenomena are associated with new managerial challenges. First of all, the research calls for more conscious management of digital artefacts for organizing for innovation. Architectural decision regarding to reuse or new development arise as an area of concern that accompanies decisions about organizational structures. A second managerial challenge is connected to unstable identity of a digital artefacts. The identity of digital artefacts is tied to its role in consumption or to the role they play for consumers. The same digital artefacts can provide a core for a product that solves a very different need. Therefore, effective management of digital innovation requires paying attention to the changing needs that the ever- changing digital products are directed to address.
... This is well captured in the so-called SkunkWorks approach, defined as 'enriched environment that is intended to help a small group of individuals design a new idea by escaping routine organizational procedures' (Rogers, 2003, p. 146). Organizationally separated innovation units bear names such as corporate accelerators (Bauer, Obwegeser, & Avdagic, 2016) and incubators (Becker & Gassmann, 2006). Companies may also acquire start-ups or develop spin-offs as means of structurally separating innovation (Burgelman, 1991;Lassen et al., 2006). ...
... As a counter-intuitive implication of such properties of digital artefacts, establishing new product identities can be more difficult in digital innovation. By new identities, we understand both new brands and the introduction of innovations that challenge the identity of organisations as a whole (Bauer et al., 2016;Tripsas, 2009). ...
Article
Full-text available
The literature on digital innovation often relies on examples of radical, even paradigm-changing novelties. In order to develop such radical innovations, organizational separation of innovation efforts has been advocated by many as an effective strategy. We have conducted a longitudinal case study of a radical innovation project at a born-digital company. The company established a separate organization to develop radical innovation, but over time, the innovation drifted from radical to incremental. Even keeping the organization separate proved difficult. In explaining the events in the case study, we follow the argument that new theories of digital innovation can be developed with reference to the specific properties of digital artefacts. We outline how properties like editability and distributability may contribute to innovation drift, i.e., the proclivity of radical innovation ambitions to gradually drift towards more incremental realizations. Due to their nature, digital artefacts can diffuse through the organization and, thus, pose a challenge to the effectiveness of organizational separation as a strategy for innovation. With this work, we contribute to the literature on digital innovation by responding to calls for research on new theories of digital innovation and the demand for greater appreciation of digital materiality in organizing. We also challenge the prevailing view of digital innovations as radical and aim to open a debate on the possibility and considerations surrounding incremental digital innovations.
... Consequently, tech start-up gestation remain tough and problematic (Reymen et al., 2015;Gruber et al., 2008), as founders continue to struggle for survival during commercialization. Despite these challenges, scholars (Carayannopoulos, 2009;Bauer et al., 2016) acknowledged that tech start-up emergence in any society contribute in driving job creation. In addition, tech start-ups foster socio-economic growth in emerging economies and acts as an attraction center for economic boost across the globe (Delmar et al., 2013;Subrahmanya, 2017). ...
Article
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Purpose: In pursuit of socio-economic growth, scholars and policymakers in emerging economies continues to show interest in understanding technology-based start-up (i.e. tech start-up) emergence, to help mitigate persistent failure experienced during commercialization. Howbeit, some scholars lamented that extant studies that investigated tech start-up emergence are mostly fragmented, because they focus on specific event/sub-process in tech start-up gestation. Thus, this study aims to conduct a systematic literature review to discover, harmonize and develop a framework that describes the interaction among varying dimensions of events/sub-processes that characterizes tech start-up emergence in an emerging economy. Design/methodology/approach: To conduct this study, the authors engaged a concept-centric systematic literature review. Having developed a search protocol, the authors searched through information systems database, and other relevant discipline databases, to select relevant articles for review. Findings: The systematic review revealed various dimensions of events (i.e. opportunity discovery and selection, team formation and domain consensus, bootstrapping and the development of minimum viable product and market experimentation feedback) that are critical to tech start-up emergence. Most prior studies are isolated, as they focus their investigation on specific event. Thus, from this review, the authors developed a framework harmonizing various dimensions of events characterizing emergence of a viable tech start-up. Originality/value: The researchers conducted this study in response to lingering call for harmonized study that provides in-depth description of how different dimensions of events interact and characterize tech start-up emergence. Consequently, the study resulted in a descriptive framework. Furthermore, the findings highlight some practical implications and proposes new study directions as future research agenda for scholars interested in tech start-up emergence.
... Open innovation enables to access a wider variety of ideas and solutions from various external innovation sources, thus accelerating development processes. Open innovation can be implemented using various strategies and often leverages the power of crowdsourcing, for example, in the form of programs such as accelerators and incubators [18] or eventlike initiatives, such as hackathons [10]. Crowdsourcing has been typically discussed as an in-bound open innovation tool that enables the collection of diverse inputs from a wider crowd of individuals outside the organizational boundaries [19]. ...
Article
The COVID-19 crisis brought about an unprecedented wave of interest into rapid ideation and innovation. Among others, the pandemic triggered a series of collaborative innovation events—so-called hackathons—to leverage the power of the crowd for crisis response. In contrast to earlier hackathons, these events are different in their speed of mobilization, global scale, and their fully virtual nature with organizers and teams being geographically dispersed. Analyzing this new empirical phenomenon, we characterize COVID-19 hackathons against other forms of innovation crowdsourcing and describe challenges and best practices in the areas of people management, session management, technology, and knowledge management. Based on our empirical findings, we develop a conceptual framework that emphasizes the importance of managing virtual crisis hackathons as the integrated sum of its different parts. Empirical evidence is presented to demonstrate how open innovation efforts such as hackathons can be leveraged for crisis management and more generally for ideation activities in increasingly remote working environments. This article contributes to crowdsourcing research by highlighting key differences of virtual hackathons from the traditional crowdsourcing approaches and hackathons investigated by prior research. Moreover, we affirm the value of mobilizing knowledge from different sources, particularly from a broad spectrum of civil society.
... The core of the accelerator program in these accelerators is services such as mentoring, networking, coaching and investor-oriented events. In this program, the corporate accelerator acts as a bridge between the parent organization and the startups and extracts resources, credit, market and capital from the parent organization and injects them into identified startups (Bauer et al., 2016). In recent years, the acceleration process has been presented in various models. ...
Article
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Purpose This study was designed to detect the failures in Iranian accelerators. This paper attempts to identify these effects from the perspective of accelerator managers and founders of startups. The main goals of this article are as follows: (1) What are the failures of Iran's acceleration programs from the perspective of accelerator managers? (2) What are the failures of Iran's acceleration programs from the perspective of startup teams? (3) What are some of failures of the acceleration programs that both groups agree on? Design/methodology/approach It has been attempted to conduct semi-structured interviews with managers of corporate accelerators on the one hand and startups accelerated in these accelerators on the other. The interviewees were selected using snowball method and consisted of 9 accelerator managers out of 7 accelerators and 15 startups based on 5 accelerators. The analysis of the information extracted from the interviews and coding of the failure identified in the accelerators was performed using the thematic analysis method. In order to assess the validity of this study, an entrepreneurial doctoral student was asked to codify the interviews individually to compare the extracted codes. Findings Finally, 34 problems have been identified that are divided into four main themes related to mentorship, acceleration program, acceleration structure and infrastructure and internal startup team problems. Overall, the greatest agreement among the failures identified as wrong orientation by untrained mentors, the lack of complementary in ability and skills of team members, the lack of knowledge of mentors, the lack of acceleration managers in entrepreneurship and the lack of a proper leader in startup teams. Originality/value This study aimed to investigate the failures of corporate accelerators in Iran as a developing country, which is the first survey in Iran. We have many researches about the pathology and identify failures of accelerators, but in corporate accelerators, little research has been done. The authors have a classification of failures in corporate accelerators by using thematic analysis. In this study, accelerators' managers and founders of startups were interviewed and 34 failures were identified.
... Past studies focused on CAs have generally been explorative in nature (Bauer, Obwegeser & Avdagic, 2016), and often aimed at providing a better understanding of CAs' design dimensions and their respective implications. While one stream of research highlights the design distinctiveness of CAs as a means of innovation accompanied by implementation advice (e.g., Kohler, 2016;Richter et al., 2018), another stream of research points to the differences among CAs depending on the peculiarities of their designs (e.g., Kanbach & Stubner, 2016;Moschner et al., 2019;Prexl et al., 2019;Shankar & Shepherd, 2019). ...
Article
Corporate accelerators (CAs) have become increasingly popular in both research and practice. In the past, analyses of CAs have centered on organizations in general, but those analyses focused on the particularities of CAs rather than the firms’ contexts. With regard to firm-specific contexts, a growing number of family firms in Germany have started CAs in recent years. Family firms are known for their idiosyncrasies due to the family’s involvement, which is argued to affect cooperation between family firms and start-ups. We claim that CAs also differ in the context of family firms. Taking a family firm specific perspective on corporate entrepreneurship, we argue that the design of family firms’ CAs is influenced by these firms’ idiosyncrasies. By connecting this perspective with general CA design dimensions, we conceptually derive family firm specific CA designs and discuss their implications for CAs in general and for CAs in the context of family firms.
Article
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Technology entrepreneurship rarely succeeds in isolation; increasingly, it occurs in interconnected networks of business partners and other organizations. For entrepreneurs lacking access to an established business ecosystem, incubators and accelerators provide a possible support mechanism for access to partners and resources. Yet, these relatively recent approaches to supporting entrepreneurship are still evolving. Therefore, it can be challenging for entrepreneurs to assess these mechanisms and to make insightful decisions on whether or not to join an incubator or accelerator, and which incubator or accelerator best meets their needs. In this article, five key factors that entrepreneurs should take into consideration about incubators and accelerators are offered. Insights are drawn from two surveys of managers and users of incubators and accelerators. An understanding of these five key success factors (stage of venture, fit with incubator’s mission, selection and graduation policies, services provided, and network of partners) and potential pitfalls will help entrepreneurs confidently enter into a relationship with an incubator or accelerator.
Technical Report
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This report was developed under a contract with the Small Business Administration, Office of Advocacy, and contains information and analysis that were reviewed by officials of the Office of Advocacy. However, the final conclusions of the report do not necessarily reflect the views of the Office of Advocacy.
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Recent years have seen the rapid emergence of a new type of program aimed at seeding startup companies. These programs, often referred to as accelerators, differ from previously known seed-stage institutions such as incubators and angel groups. While proliferation of such accelerators is evident, evidence on efficacy and role of these programs is scant. Nonetheless, local governments and founders of such programs often cite the motivation for their establishment and funding as the desire to transform their local economies through the establishment of a startup technology cluster in their region. In this paper, we attempt to assess the impact that such programs can have on the entrepreneurial ecosystem of the regions in which they are established, by exploring the effects of accelerators on the availability and provision of seed and early stage venture capital funding in the local region.
Chapter
The dynamic capabilities framework analyzes the sources and methods of wealth creation and capture by private enterprise firms operating in environments of rapid technological change. The competitive advantage of firms is seen as resting on distinctive processes (ways of coordinating and combining), shaped by the firm's (specific) asset positions (such as the firm's portfolio of difficult-to-trade knowledge assets and complementary assets), and the evolution path(s) it has adopted or inherited. The importance of path dependencies is amplified where conditions of increasing returns exist. Whether and how a firm's competitive advantage is eroded depends on the stability of market demand, and the ease of replicability (expanding internally) and imitatability (replication by competitors). If correct, the framework suggests that private wealth creation in regimes of rapid technological change depends in large measure on honing internal technological, organizational, and managerial processes inside the firm. In short, identifying new opportunities and organizing effectively and efficiently to embrace them are generally more fundamental to private wealth creation than is strategizing, if by strategizing one means engaging in business conduct that keeps competitors off balance, raises rival's costs, and excludes new entrants. © 2003 by World Scientific Publishing Co. Pte. Ltd. All rights reserved.
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Entrepreneurs face high uncertainty, and often make costly investments in new business ideas without knowing the expected payoff. This paper empirically examines whether ex-ante assessment of early-stage startup ideas can predict their subsequent commercialization. We leverage an entrepreneurship program at the Massachusetts Institute of Technology in which early-stage venture ideas, presented in the form of succinct standardized summaries, elicit subjective evaluations from a large set of experienced entrepreneurs and executives. Using data on 652 ventures in multiple industry sectors, evaluated over an 8-year period, we find that ideas that elicit more positive evaluations are significantly more likely to ultimately reach commercialization. We further show that these results are driven by venture ideas with documented intellectual capital in research-and-development-intensive sectors, such as life sciences and medical devices. We find no evidence, by contrast, that experts can effectively assess the commercial potential of venture ideas in non-R&D-intensive sectors such as consumer web and enterprise software. Finally, we find that industry-specific and scientific expertise is not critical to experts’ collective ability to predict ventures’ commercial viability.
Article
Today's startups are a major source of innovation, as they employ emerging technologies to invent products and reinvent business models. Corporations that embrace an open innovation strategy increasingly look to startups as a source of external innovation. Corporate accelerators offer a potent approach to nurturing innovations from entrepreneurial ventures. However, the vast differences between corporations and startups make collaboration a challenge. Corporate accelerators need to be designed effectively to add value for startups and create innovation benefits for the company. Based on information obtained during interviews with managers and participants of corporate accelerators (n=40), managers receive a framework and strategies for designing corporate accelerators. To leverage startups’ innovation and to make corporate accelerators an effective part of a firm's overall innovation strategy, managers need to systematically and thoughtfully consider the design dimensions of proposition, process, people, and place.