Tesi etd-09272018-222604
Link copiato negli appunti
Tipo di tesi
Perfezionamento
Autore
DEL SARTO, NICOLA
URN
etd-09272018-222604
Titolo
Exploring the Business Accelerator phenomenon through Resource Based View and Open Innovation lenses
Settore scientifico disciplinare
SECS-P/08
Corso di studi
SCIENZE ECONOMICHE E MANAGERIALI - Management
Commissione
relatore Prof. PICCALUGA, ANDREA MARIO CUORE
Membro Dott. ELIA, GIANLUCA
Membro Prof. DI MININ, ALBERTO
Membro Dott. ELIA, GIANLUCA
Membro Prof. DI MININ, ALBERTO
Parole chiave
- Business accelerators
- fsQCA
- Open Innovation
- Resource based view
- Tobit Regression.
Data inizio appello
26/11/2018;
Disponibilità
completa
Riassunto analitico
Since the seminal work of Schumpeter in 1934, creation of new ventures, their survival, scale and prosperity has been regarded as a crucial factor for economic growth and development of regions (Youl Lee, Florida and Acs, 2004). Startups in fact are an important means by which new ideas are brought to life, especially those ideas which challenge established industries or do not find ready support inside existing companies. According to Schumpeter the creation of firms is one of the mechanism through which entrepreneurs use technology to bring new product, processes and ways of organizing into existence. Scholars and practitioners are interested in the process of firms’ creation because of its positive impact on employment and because often new firms bring productive innovation into the market (Baumol, 2002). Hence firm creation, their survival and prosperity and economic growth are intertwined each other; innovative entry of new firms are the disruptive force that sustain economic growth in a capitalist system (Schumpeter, 1942).
In order to foster economic growth through firms’ creation one of the solution adopted by policy makers have been the introduction of a wide variety of incubation mechanism (Smilor and Gill, 1986). Such mechanism of startup assistance became widespread in the early 90s (Hackett and Dilts 2004), providing support for small ventures, mainly with physical and financial resources (Smilor and Gill 1986; Allen and McCluskey 1991). According to Hacket & Dilts (2004) incubation models evolve through three different stages. The first refers to the establishment of the first private incubator in New York in 1959 (Lewis, 2001) and the first public incubator in 1964 in Philadelphia (Campbell & Allen, 1987). Incubators of this “first wave” were characterized by a public nature and by the focus on economic development, providing incubated firms with office space and shared services (Mian et al., 2016). During the 1980s and 1990s the diffusion of incubation activity increased significantly (Hacket & Dilts, 2004). Incubators of this “second wave” offered an expanded range of value added services including mentoring and networking. During this period university-based incubators emerged and quickly diffuse (Etzkowitz, 2002). The “third wave” of incubators emerged in the late 1990s. Incubators within this wave comprised private independent or corporate incubators focusing on startups in the ICT and others high-tech sectors (Aerts, Matthyssens, & Vandenbempt 2007, Becker & Gassmann, 2006). Those incubators focused on specialized services and access to capital aiming to speed up the startups’ time to market (Grimaldi and Grandi, 2005). However, the incubator model has been criticised over the years for its lack of exit policy (Bruneel et al., 2012) and its reliance on long term public funding to be sustainable. When incubators emerged, in fact, many of the innovative new ventures were active in sectors such as biotechnology, micro–electronics and electrical equipment which are typically capital intensive (Wright et al., 2007).
In recent years, advances in technology and the rise of the digital economy (Clarysse et al. 2015) have led to the emergence of what is generally considered a new generation of business incubator model: the accelerator (Pauwels et al. 2016; Wise and Valliere 2014). This new model of startup assistance has attracted the interest of media and policy makers thanks to the success of well-known accelerated startups (e.g. Dropbox, Airbnb, Reddit and Zenefists). Accelerators support new venture creation through the provision of specific services over an intensive time-limited program, generally a few months in duration (Cohen and Hochberg 2014). Although considered by some scholars as an evolutionary descendant of incubators (Grimaldi and Grandi 2005; Pauwels et al. 2016), accelerators are quite distinct, unlike the previous three generations of business incubators, among which no significant differences in terms of services portfolio have been observed (Bruneel et al. 2012).
In particular, accelerators have a shorter-term horizon than incubators and are typically cohort-based. Importantly, their legal status often differs: most incubators are not-for-profit organizations, whereas accelerators are generally for-profit organizations with the aim of bringing a return on investment to their sponsors (Knopp 2012). Therefore, accelerators typically provide pre-seed investment in exchange for equity (Pauwels et al. 2016) and facilitate connections with potential investors. Accelerators focus on knowledge-intensive business services, moving away from the primary services for which the incubation model was developed (i.e. rental services) (Pauwels et al. 2016). In practice, these two models operate in overlapping domains (Dempwolf et al. 2014; Isabelle 2013).
Notwithstanding the rapid proliferation of accelerators around the world, the academic literature on this topic is surprisingly scarce. In particular, scholars have neglected to study this recent phenomenon in a comprehensive way, taking into account all the contributions about this topic that would have helped them to define the boundaries of the topic, in particular with respect to incubators. Moreover, there is a lack of theory in the study of accelerators that did not allows scholars to fully understand the phenomenon. Within this vein it is interesting to point out that, despite the first accelerator was established in 2005, the first academic paper on the topic was published in 2014 (Cohen and Hocheberg 2014) demonstrating that often the academic world does not examine properly new phenomena arising from the real world.
This thesis aims at investigating the emerging topic of business accelerators through the use of two theoretical lenses namely Resource based view and Open innovation. In order to do that, I look at startups accelerated in Italy by accelerators compliant with the definition provided by Cohen and Hochberg (2014) which is “a fixed-term, cohort-based program, including mentorship and educational components, that culminates in a public pitch event or demo-day”. After that I collected data about accelerated startups and I highlighted how the use of accelerators impact on startups that participated to an accelerator program. The work is articulated in three parts.
The first chapter presents a systematic literature review on business accelerators. We complement the literature review provided by Mian et al. (2016) which identified accelerators as an emerging topic that “requires special attention” (Mian et al. 2016: 7). From the systematic literature review it emerge that scholars investigated the topic of accelerators focusing on three different aspect namely: the Definition of business accelerators and description of accelerator programs; the Impact of business accelerator programs and the Business accelerators as an open innovation tool. This literature review allows us to identify the literature stream to which we want to contribute, which is the impact of accelerators on accelerate startups.
A preliminary version of this chapter was presented at ISPIM conference 2018 in Stockholm (Sweden) and was published in its book of proceedings with ISBN 978-952-335-219-3. This chapter has been co-authored with my colleague Dr. Cristina Marullo and prof. Alberto Di Minin.
The second chapter analyses 38 startups accelerated in 2013 by five Italian accelerators. Through the use of fsQCA methodology we investigated which interactions among which firms’ internal resources affect new firm survival. For the selection of internal resources we draw from the literature that takes benefit from Resource Based View (RBV) to explain new firm survival in terms of heterogeneity of tangible and intangible internal resources. The empirical results of our analysis show that, among the various combinations of internal resources analyzed, only the interaction between export activity and human capital has a positive effect on new firm survival. By offering a theoretical explanation of this interaction, we contribute to RBV, and to research on international trade and on human capital.
This chapter has been co-authored with my colleague Dr Giulio Ferrigno, prof. Alberto Di Minin and prof. Andrea Piccaluga. I would like to thank prof. Chun Yang, Dr. Cristina Marullo, Dr. Elena Casprini and Dr. Nadia Di Paola for their precious insight which allowed us to improve the article.
Third chapter investigates if the external sources of knowledge provided by accelerators during the acceleration program increase innovation performance of accelerated startups. In order to reach our goal we developed an ad hoc questionnaire and we sent it to all startup accelerated in Italy from 2013 to 2016. We received 113 answers and we conducted a Tobit regression which highlight that the external sources of knowledge identified, namely competitors, mentors and educators and investors, increase both radical and incremental performance of accelerated startups. Our findings point out the importance of using investors as sources of knowledge to enhance the radical innovation performance of startups. At the same time we show that startups might enhance their incremental innovation performance by using mentors and educators and competitors as source of external knowledge.
This chapter results from the collaboration with prof. Claudio Cruz Cazares from University of Barcelona and Prof. Alberto Di Minin.
In order to foster economic growth through firms’ creation one of the solution adopted by policy makers have been the introduction of a wide variety of incubation mechanism (Smilor and Gill, 1986). Such mechanism of startup assistance became widespread in the early 90s (Hackett and Dilts 2004), providing support for small ventures, mainly with physical and financial resources (Smilor and Gill 1986; Allen and McCluskey 1991). According to Hacket & Dilts (2004) incubation models evolve through three different stages. The first refers to the establishment of the first private incubator in New York in 1959 (Lewis, 2001) and the first public incubator in 1964 in Philadelphia (Campbell & Allen, 1987). Incubators of this “first wave” were characterized by a public nature and by the focus on economic development, providing incubated firms with office space and shared services (Mian et al., 2016). During the 1980s and 1990s the diffusion of incubation activity increased significantly (Hacket & Dilts, 2004). Incubators of this “second wave” offered an expanded range of value added services including mentoring and networking. During this period university-based incubators emerged and quickly diffuse (Etzkowitz, 2002). The “third wave” of incubators emerged in the late 1990s. Incubators within this wave comprised private independent or corporate incubators focusing on startups in the ICT and others high-tech sectors (Aerts, Matthyssens, & Vandenbempt 2007, Becker & Gassmann, 2006). Those incubators focused on specialized services and access to capital aiming to speed up the startups’ time to market (Grimaldi and Grandi, 2005). However, the incubator model has been criticised over the years for its lack of exit policy (Bruneel et al., 2012) and its reliance on long term public funding to be sustainable. When incubators emerged, in fact, many of the innovative new ventures were active in sectors such as biotechnology, micro–electronics and electrical equipment which are typically capital intensive (Wright et al., 2007).
In recent years, advances in technology and the rise of the digital economy (Clarysse et al. 2015) have led to the emergence of what is generally considered a new generation of business incubator model: the accelerator (Pauwels et al. 2016; Wise and Valliere 2014). This new model of startup assistance has attracted the interest of media and policy makers thanks to the success of well-known accelerated startups (e.g. Dropbox, Airbnb, Reddit and Zenefists). Accelerators support new venture creation through the provision of specific services over an intensive time-limited program, generally a few months in duration (Cohen and Hochberg 2014). Although considered by some scholars as an evolutionary descendant of incubators (Grimaldi and Grandi 2005; Pauwels et al. 2016), accelerators are quite distinct, unlike the previous three generations of business incubators, among which no significant differences in terms of services portfolio have been observed (Bruneel et al. 2012).
In particular, accelerators have a shorter-term horizon than incubators and are typically cohort-based. Importantly, their legal status often differs: most incubators are not-for-profit organizations, whereas accelerators are generally for-profit organizations with the aim of bringing a return on investment to their sponsors (Knopp 2012). Therefore, accelerators typically provide pre-seed investment in exchange for equity (Pauwels et al. 2016) and facilitate connections with potential investors. Accelerators focus on knowledge-intensive business services, moving away from the primary services for which the incubation model was developed (i.e. rental services) (Pauwels et al. 2016). In practice, these two models operate in overlapping domains (Dempwolf et al. 2014; Isabelle 2013).
Notwithstanding the rapid proliferation of accelerators around the world, the academic literature on this topic is surprisingly scarce. In particular, scholars have neglected to study this recent phenomenon in a comprehensive way, taking into account all the contributions about this topic that would have helped them to define the boundaries of the topic, in particular with respect to incubators. Moreover, there is a lack of theory in the study of accelerators that did not allows scholars to fully understand the phenomenon. Within this vein it is interesting to point out that, despite the first accelerator was established in 2005, the first academic paper on the topic was published in 2014 (Cohen and Hocheberg 2014) demonstrating that often the academic world does not examine properly new phenomena arising from the real world.
This thesis aims at investigating the emerging topic of business accelerators through the use of two theoretical lenses namely Resource based view and Open innovation. In order to do that, I look at startups accelerated in Italy by accelerators compliant with the definition provided by Cohen and Hochberg (2014) which is “a fixed-term, cohort-based program, including mentorship and educational components, that culminates in a public pitch event or demo-day”. After that I collected data about accelerated startups and I highlighted how the use of accelerators impact on startups that participated to an accelerator program. The work is articulated in three parts.
The first chapter presents a systematic literature review on business accelerators. We complement the literature review provided by Mian et al. (2016) which identified accelerators as an emerging topic that “requires special attention” (Mian et al. 2016: 7). From the systematic literature review it emerge that scholars investigated the topic of accelerators focusing on three different aspect namely: the Definition of business accelerators and description of accelerator programs; the Impact of business accelerator programs and the Business accelerators as an open innovation tool. This literature review allows us to identify the literature stream to which we want to contribute, which is the impact of accelerators on accelerate startups.
A preliminary version of this chapter was presented at ISPIM conference 2018 in Stockholm (Sweden) and was published in its book of proceedings with ISBN 978-952-335-219-3. This chapter has been co-authored with my colleague Dr. Cristina Marullo and prof. Alberto Di Minin.
The second chapter analyses 38 startups accelerated in 2013 by five Italian accelerators. Through the use of fsQCA methodology we investigated which interactions among which firms’ internal resources affect new firm survival. For the selection of internal resources we draw from the literature that takes benefit from Resource Based View (RBV) to explain new firm survival in terms of heterogeneity of tangible and intangible internal resources. The empirical results of our analysis show that, among the various combinations of internal resources analyzed, only the interaction between export activity and human capital has a positive effect on new firm survival. By offering a theoretical explanation of this interaction, we contribute to RBV, and to research on international trade and on human capital.
This chapter has been co-authored with my colleague Dr Giulio Ferrigno, prof. Alberto Di Minin and prof. Andrea Piccaluga. I would like to thank prof. Chun Yang, Dr. Cristina Marullo, Dr. Elena Casprini and Dr. Nadia Di Paola for their precious insight which allowed us to improve the article.
Third chapter investigates if the external sources of knowledge provided by accelerators during the acceleration program increase innovation performance of accelerated startups. In order to reach our goal we developed an ad hoc questionnaire and we sent it to all startup accelerated in Italy from 2013 to 2016. We received 113 answers and we conducted a Tobit regression which highlight that the external sources of knowledge identified, namely competitors, mentors and educators and investors, increase both radical and incremental performance of accelerated startups. Our findings point out the importance of using investors as sources of knowledge to enhance the radical innovation performance of startups. At the same time we show that startups might enhance their incremental innovation performance by using mentors and educators and competitors as source of external knowledge.
This chapter results from the collaboration with prof. Claudio Cruz Cazares from University of Barcelona and Prof. Alberto Di Minin.
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