Social networks of startup entrepreneurs:the case of the startup ecosystem in Lithuania

Dr Linas Eriksonas

International Business School at Vilnius University

Linas.Eriksonas@tvm.vu.lt

Content

• Research background and aims

• Hypotheses

• Setup of the experimental study

• Results

• Implications for path-dependence theory

Background and aims

• Forbes (June 2015): Vilnius - one of five entrepreneurial hotspots in Europe (alongside Eindhoven, Budapest, Tallinn and Lisbon):• “a fertile innovation hotspot for trailblazing entrepreneurs”

• “the proof lies in its burgeoning startup community in which over 100 million USD has been invested in recent years”

• Aims of the research (initiated in 2012): • to explain the factors which have been driving the growth of startup networks

in Lithuania

• to look for conditions that could create a path-dependence for sustaining themomentum

• to design a research-driven model for a longitudinal tracking of such networks

What is a startup?

• A collective of people characterised by informal arrangments of work, shared lifestyles, hobbies, values and the ambition to become rich• you can think of a startup as a way to compress your whole working life into a few

years. Instead of working at a low intensity for forty years, you work as hard as you possibly can for four. This pays especially well in technology, where you earn a premium for working fast (Paul Graham, Hackers and Painters, 2004)

• Venture labour or entrepreneurial workers (Neff, 2012)• Graduates, especially from business schools, without adequate possibilities on the

job market (first emerged in 2000-2001, then after 2008-2009) or after a career spellin the corporate world

• Skilled in management and STEM disciplines, technologically adept• Well integrated socially through alumni networks• Their value system informed by different strands of thought originating in subculture

(hackerism, liberatarianism, humanism) characterised by the dream-like ambition to succeed and change the world while taking execesive risks

Hypotheses

• Hypothesis 1: the growth of the startup networks in Lithuania has been driven by individuals having initial social capital but being without adequate employment opportunities on the job market following the financial crisis in 2008-2009.

• Hypothesis 2: the startup networks were largely shaped by the public and private funds which became available for networking activities and raising initial funds for pre-seed/seed capital.

• Hypothesis 3: the growth of entrepreneurial networks have been impacted by the use of social media, mainly Twitter which is one of the main platforms for global communication among entrepreneurs.

Research design

• The main part of the research was carried during three periods in 3 years(June 2013, October 2014 and September 2015) and consisted of 5 steps:

1. 20 experts have been identified and surveyed (using a respondent-driven snowballing sampling method) which helped to establish the initial seed list of 51 startups and 28 facilitators for analysis;

2. A consolidated list of startups and facilitators nominated each by more than 25% of the experts was drawn up and their social media accounts were collected

3. The data from the active Twitter accounts of 21 shortlisted subjects were collected (using Python scripts): gathered data about over 20000 users having more than22000 links; the core network analysed included some 1200 individuals.

4. The Twitter data were analysed and visualized with the help of software packages for social network analysis.

5. In 2015 the analysis was updated which allowed to create the dataset of longitudinal data and compare it with the initial dataset from 2013.

H1: growth of startup networks driven by demand/supply on the job market

• The biographical analysis based on Linkedin data and additional input from publicly available sources showed that >50% of startup founders were graduates without steady jobs.

• The first generation of hackers (2002-2004) was absorbed by the job market prior to 2008 (joined first IT companies which opened business in Lithuania - Unity Technologies, Bentley Systems)

• The majority of the early startup founders started their activities after 2006 having few years behind after graduation (ca. 26 yrs)

• A typical founder: BA level education in management or IT, almost exclusively male, with varied ethnic backgrounds

H2: the startup networks were largely shaped by the public and private funds and their facilitators

Core Facilitators

Data from October 2014

Core Founders

Facilitators at the centre of the network

StartupHighwayaccelerationprogramme

Hub Vilnius coworking centre

First startups (2011-2012)

The acceleration programme StartupHighway(at the co-working hub at Northtown technology park) setup in the emulation of Seedcamp London

The first co-working centre in Vilnius (HubVilnius) was setup in 2011 in emulation of Riga‘s TechHub, a franchise of TechHub London

Data from June 2013

H3: the growth of entrepreneurial networks have been impacted by the use of Twitter

Twitter account nameFollowers

(June 2013)

Following

(June

2013)

Social

authority

index

(Oct.

2014)

Followers

(Sept. 2015)

Followin

g

skaičius

(Sept.

2015)

Social

authority

index (Sept.

2015)

Last update

Social

authority

changes, %

xtgem 6333 5 19 7601 5 13 28/02/2014 -46,2%

pixelmator 6015 40 54 9598 134 70 01/09/2015 22,9%

StartupHighway 985 615 32 2829 2125 23 09/06/2015 -39,1%

IljaLaurs (naudoja getjar) 832 01 (getjar –

39)13700 1159 28 23/03/2013

lasas 777 98 23 1621 209 50 16/09/2015 54,0%

Edmundas4 555 333 25 1478 964 51 17/09/2015 51,0%

Impresspages 480 800 25 730 770 24 26/05/2015 -4,2%

Dragdisdiscoveries 463 17 31 713 140 25 19/04/2015 -24,0%

CG_Trader 375 892 11 1644 3115 60 18/09/2015 81,7%

EnterpriseLT 359 153 1 775 159 Discontinued 15/04/2014

AppCamplt 218 166 1 354 165 Discontinued 24/10/2014

KTUstartupspace 148 154 1 193 156 Discontinued 12/10/2014

PlateCulture 139 0 2 2865 1283 40 18/09/2015 95,0%

FridayLab 58 3 1 942 408 2 21/08/2015 50,0%

TransferGo 58 64 1 833 469 51 17/09/2015 98,0%

Whemsyhabit 42 72 1 38 117 Discontinued 15/01/2014

Exacaster 39 95 1 39 5 1 21/08/2015 0,0%

DVarkulevičius 37 27 3 663 1123 28 06/09/2015 89,3%

Pombai 32 88 1 Discontinued 27/04/2013

rokastamosiunas 32 80 1 58 96 Discontinued 18/09/2012

ikamantauskas 20 36 1 88 41 1 13/07/2015 0,0%

Results

• The startup networks have emerged after 2011 and have coincided withthe economic crisis in the country resulting in high levels of youthunemployment among skilled or semi-skilled graduates and a number ofjobless junior-management level professionals)

• The major role in setting up the networks was played by publicly andprivately supported facilitators and their institutions: the co-working placeand the accelleration programme.

• The patterns were emulated by transfering practices from London(Seedcamp, Open Coffee Club), via Riga (Riga TechHub) and Tallinn(Garage48), early links with Helsinki (Arctic Startup).

• Update: (since 2014) direct links to RocketSpace (San Francisco) underdevelopment, the transferred practices back to London (Drinkpreneur Live)

Implications for application of path-dependence theory

• The concept of imprinting (Marquis, Tilcsik, 2013):• nascent research reflects the notion that “a past network, with its

accumulated relational experience, becomes a kind of ‘network memory’

• Despite this recent development, much remains to be learned about network imprinting and, more generally, the lingering effects of network history

• Two factors can be considered using the longitudinal study:• Importance of past ties for new knowledge, practices and routines (creating

career advantages)

• Structure of a network sustains the imprint of conditions (new network entrants are likely to imitate the existing structural patterns)

• Average Degree: 1,414

• Modularity: 0,724

• Modularity with resolution: 0,724

• Number of Communities: 11?

• Diameter: 6

• Average Clustering Coefficient*: 0,070

• Average Path length#: 3.336760991859381

• Number of shortest paths: 45367802

Sept. 2015

June2013

• Average Degree: 1,166

• Modularity: 0,741

• Modularity with resolution: 0,741

• Number of Communities: 12

• Diameter: 8

• Average Clustering Coefficient: 0,019

• Average Path length: 4.180968027664934

• Number of shortest paths: 64889943

Imprinting via shared work practices

Hackerspacesshared

workshop tools and

work space

Startup incubators:

Team work in a shared space

Coworkingspaces:

Individual work places in a

shared work space

DIY/ Makers

Self-employedprofessionals

Hackers

Startup founders

Does path-dependence exist in startup networks?

• Hacker collective “demoscena” in Vilnius, Kaunas (2002)

A hacker collective at GamejamLT 2002: NeARAZ, Oasis, rtfb, Voblia, ReJ Teaman, ProNinja, OneHalf, simple

Viktoras Jucikas (hacker nickname BigtoP), Rytis Vitkauskas, founders of Yplan (founded in 2012)

• One of the ex-hackers pitching startup Yplan in London (2014)

Funding received for Yplan:$37.7M in 3 Rounds from 16 Investors

Paid career job

Work-in-progress: path-dependence model for analysing startup entrepreneurs longitudinally

• Involvement insubcultures

Hackers, DIY/Makers

• Professional career track

• Entreprenerialactivities

Startup teamChanges in personal community networks

Acknowledgements

• The research was funded by the Research Council of Lithuania (2012-2014) as part of the group research project on innovation networks

• The access to Twitter data via Twitter API granted for development purposes by Twitter

• Software used:• Python scripts for Twitter, courtesy of Dr Derek Ruths, Network Dynamics Lab,

School of Computer Science, McGill University

• Neo4J database, the academic license granted by Neo Technology Inc.

• Gephi, an open source software (licensed by the Gephi Consortium)

• Visone, a free software for academic purposes (University of Konstanz)

References

• Eriksonas, L. 2010. Peer Driven Survey Methodology and Indicators for Policy Relevant Research Competence Assessment [poster presentation]. European Network of Indicators Designers Indicators Conference, Paris.

• Eriksonas, L. 2013. The Impact of Time Zone Difference on Social Networks of Entrepreneurs. Sunbelt 2013 Conference, University of Hamburg, Hamburg

• L. Eriksonas et al., Inovacinių tinklų kūrimasis Lietuvoje: atvejų studijos(Innovation networks in Lithuania: case studies) (Vilnius, 2015)