Periodic Reporting for period 4 - N4I_CLUSTERS (Networking for innovation: how entrepreneurs' network behaviours help clusters to innovate)
Reporting period: 2021-09-01 to 2023-02-28
My research program is based on the idea that the most innovative individuals may not simply have better networks, they may rather have more effective networking behavior. For example, such individuals build the right connections at the right time or make wise decisions on when to mobilize specific ties from their network. Likewise, clusters of entrepreneurial and innovative activity may thrive not simply because of the valuable social capital individual innovators and entrepreneurs may have access to; rather they may be home to network-savvy individuals that know how to build valuable social capital and how to leverage it successfully.
Existing research most often focuses on the role of network structure as drivers of information advantage and innovative success of individuals and clusters and tends to overlook the role of networking behaviour. To assess the role of networking behaviors in driving innovation and entrepreneurship outcomes, my research program aims to build a network behavioural approach to understanding the network-innovation relationship. At the micro-level, a better understanding of networking behaviors is important, as it will help shed light on some of the fundamental individual-level mechanisms through which networking facilitates innovation. At a macro-level, understanding the role of networking behaviors in capitalizing on local network opportunities is critical to better understand why some clusters are more vibrant and innovative than others.
My research programme is a mixed-method study that consists of five main phases with the following objectives:
1. Identify key networking behaviors of entrepreneurs and innovators
2. Monitor networking behaviors of entrepreneurs and innovators
3. Assess the relation between networking behavior and innovation outcomes at the micro level
4. Testing core mechanisms of the network-innovation relationship
5. Assess the relation between networking behavior and innovation outcomes at the macro level
Cumulatively, meeting the above objectives should lead to fundamentally new insights into why certain individuals contribute more to innovation outcomes than others, and why certain clusters thrive as hubs of innovation.
Existing research most often focuses on the role of network structure as drivers of information advantage and innovative success of individuals and clusters and tends to overlook the role of networking behaviour. To assess the role of networking behaviors in driving innovation and entrepreneurship outcomes, my research program aims to build a network behavioural approach to understanding the network-innovation relationship. At the micro-level, a better understanding of networking behaviors is important, as it will help shed light on some of the fundamental individual-level mechanisms through which networking facilitates innovation. At a macro-level, understanding the role of networking behaviors in capitalizing on local network opportunities is critical to better understand why some clusters are more vibrant and innovative than others.
My research programme is a mixed-method study that consists of five main phases with the following objectives:
1. Identify key networking behaviors of entrepreneurs and innovators
2. Monitor networking behaviors of entrepreneurs and innovators
3. Assess the relation between networking behavior and innovation outcomes at the micro level
4. Testing core mechanisms of the network-innovation relationship
5. Assess the relation between networking behavior and innovation outcomes at the macro level
Cumulatively, meeting the above objectives should lead to fundamentally new insights into why certain individuals contribute more to innovation outcomes than others, and why certain clusters thrive as hubs of innovation.
Over the duration of the grant, the research program has met the objectives as set out in the original proposal.
OBJECTIVE 1
We have collected granular qualitative data of the networking behavior of entrepreneurs and innovators. For entrepreneurs, we have performed a qualitative study of 50 experienced entrepreneurs in the entrepreneurial ecosystem of London and Paris and 230 hours of participant observation at entrepreneurial networking events. This work documents how entrepreneurs who are initially “unembedded” become gradually more embedded. For innovators, we have performed a range of interviews with R&D managers and R&D scientists inside a large multinational firm.
OBJECTIVE 2
We performed two sets of networking experiments that allow us to monitor the networking behaviors of entrepreneurs and innovators in a granular way. First, we performed an experiment in the form of a networking game to emulate the search for expertise through networking in event-like settings using sociometric badges developed by the MIT Media Labs. We find that letting others approach yields more referrals than taking the initiative in starting conversations, and that planning increases the tendency to maintain such initiative even when doing so is ineffective. Second, we collected experimental data on network mobilization behaviors of boundary-spanners: individuals with job roles across two different domains (e.g. academia and industry). Our findings imply that it may not be sufficient for organizations seeking to promote the cross-fertilization of ideas to allocate individuals to boundary-spanning roles; they need to train and encourage their staff to identify with the domains at both sides of the boundary to enable to fully leverage the potential from boundary spanning.
OBJECTIVE 3
We published two articles in relation to this objective, and a third one is currently under review. The first paper, accepted for publication in the Administrative Science Quarterly (2020), focuses on networking behavior in a corporate innovation setting and seeks to determine the extent to which individuals dividing the work across roles can also benefit from dividing their networking. The second paper, published in the Academy of Management Journal (2023), draws from the same context but focuses on the impact of network sequencing on individual innovation performance. A third paper, currently in progress, links the network mobilization decisions of academic scientists to their ability to publish high-impact scientific outputs.
OBJECTIVE 4
First, at the micro-level, we examined the role of interaction “pacing” at networking events using second-generation sociometric badges. Second, at a more macro-level, we investigated the role of social influence and imitation as a critical mechanism linking networks and innovation outcomes. In a study, published in Research Policy (2023), we examined the exit dynamics in open multiparty alliances, an important form of interfirm collaboration.
OBJECTIVE 5.
We performed a project that examined why some firms are better able than others to take advantage of the rich network opportunity space that entrepreneurial ecosystems provide. In this study, we introduce the notion of showcasing strategies and assess their effect on entrepreneurial ventures’ ability to obtain a first round of funding. Based on a comprehensive dataset of London-based technology ventures combining Crunchbase, LinkedIn and Twitter data (and using machine-learning), we find that entrepreneurs who showcase their similarity to established entrepreneurs in the ecosystem, and who balance between showcasing the specific achievements of their company and discussing more general issues relevant for their sector increase the likelihood of obtaining a first round of funding.
OBJECTIVE 1
We have collected granular qualitative data of the networking behavior of entrepreneurs and innovators. For entrepreneurs, we have performed a qualitative study of 50 experienced entrepreneurs in the entrepreneurial ecosystem of London and Paris and 230 hours of participant observation at entrepreneurial networking events. This work documents how entrepreneurs who are initially “unembedded” become gradually more embedded. For innovators, we have performed a range of interviews with R&D managers and R&D scientists inside a large multinational firm.
OBJECTIVE 2
We performed two sets of networking experiments that allow us to monitor the networking behaviors of entrepreneurs and innovators in a granular way. First, we performed an experiment in the form of a networking game to emulate the search for expertise through networking in event-like settings using sociometric badges developed by the MIT Media Labs. We find that letting others approach yields more referrals than taking the initiative in starting conversations, and that planning increases the tendency to maintain such initiative even when doing so is ineffective. Second, we collected experimental data on network mobilization behaviors of boundary-spanners: individuals with job roles across two different domains (e.g. academia and industry). Our findings imply that it may not be sufficient for organizations seeking to promote the cross-fertilization of ideas to allocate individuals to boundary-spanning roles; they need to train and encourage their staff to identify with the domains at both sides of the boundary to enable to fully leverage the potential from boundary spanning.
OBJECTIVE 3
We published two articles in relation to this objective, and a third one is currently under review. The first paper, accepted for publication in the Administrative Science Quarterly (2020), focuses on networking behavior in a corporate innovation setting and seeks to determine the extent to which individuals dividing the work across roles can also benefit from dividing their networking. The second paper, published in the Academy of Management Journal (2023), draws from the same context but focuses on the impact of network sequencing on individual innovation performance. A third paper, currently in progress, links the network mobilization decisions of academic scientists to their ability to publish high-impact scientific outputs.
OBJECTIVE 4
First, at the micro-level, we examined the role of interaction “pacing” at networking events using second-generation sociometric badges. Second, at a more macro-level, we investigated the role of social influence and imitation as a critical mechanism linking networks and innovation outcomes. In a study, published in Research Policy (2023), we examined the exit dynamics in open multiparty alliances, an important form of interfirm collaboration.
OBJECTIVE 5.
We performed a project that examined why some firms are better able than others to take advantage of the rich network opportunity space that entrepreneurial ecosystems provide. In this study, we introduce the notion of showcasing strategies and assess their effect on entrepreneurial ventures’ ability to obtain a first round of funding. Based on a comprehensive dataset of London-based technology ventures combining Crunchbase, LinkedIn and Twitter data (and using machine-learning), we find that entrepreneurs who showcase their similarity to established entrepreneurs in the ecosystem, and who balance between showcasing the specific achievements of their company and discussing more general issues relevant for their sector increase the likelihood of obtaining a first round of funding.
“Networking is just a letter away from not working”, a phrase that perhaps reflects the pervasive negative sentiment associated with deliberate attempts to build, maintain, or leverage one’s professional network. Despite this negative connotation, individuals continuously engage in behaviors – be they deliberate and strategic, or ad-hoc and spontaneous – that change their social network and the valuable resource it represents. Entrepreneurs and innovators in particular actively shape their professional networks to access key knowledge inputs, capital, and other resources.
In my research program I have undertaken a large-scale and intensive data collection effort of network structural data, network behavioral data, and innovation achievement data at multiple points in time using a range of novel data collection methods. More specifically, I have used interviews, participant observation, sociometric badges, social science experiments and data from the Twitter use to identify and measure network behaviors, and assess their impact on innovation and entrepreneurship outcomes. In doing so, my research has contributed to building the micro-foundations of networks research in the literature on innovation and entrepreneurship and led to fundamentally new insights into how networking behaviors can enable or constrain entrepreneurs and innovators to thrive in their pursuit of novel and impactful ideas.
In my research program I have undertaken a large-scale and intensive data collection effort of network structural data, network behavioral data, and innovation achievement data at multiple points in time using a range of novel data collection methods. More specifically, I have used interviews, participant observation, sociometric badges, social science experiments and data from the Twitter use to identify and measure network behaviors, and assess their impact on innovation and entrepreneurship outcomes. In doing so, my research has contributed to building the micro-foundations of networks research in the literature on innovation and entrepreneurship and led to fundamentally new insights into how networking behaviors can enable or constrain entrepreneurs and innovators to thrive in their pursuit of novel and impactful ideas.