The entrepreneurial process and online social networks: forecasting survival rate

Yang Song, Leo Paul Dana, Ron Berger

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

To launch a new business, entrepreneurs search for information and resources through their networks. We are concerned with collaboration among entrepreneurs with a network, and with the impact this has on new venture survival. Using entrepreneurs’ network data extracted from their respective online social networks, our paper develops a simulation model of the entrepreneurial process and its outcomes in terms of growth and survival. Findings from 273 entrepreneurs reveal that initial wealth at start-up, network density, and time to first collaboration have an impact on the probability of survival. We show that using numerical simulation, and based on one’s social network, the survival time of a start-up can be forecasted.

Original languageEnglish
Pages (from-to)1171-1190
Number of pages20
JournalSmall Business Economics
Volume56
Issue number3
DOIs
StatePublished - Feb 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019, Springer Science+Business Media, LLC, part of Springer Nature.

Funding

This paper is supported by the National Natural Science Foundation of China (No. 71874068), Youth Foundation of Humanities and Social Sciences, Ministry of Education of China (No. 17YJC790129), and Jilin Province Science and Technology Development Plan Project (20180418128FG).

FundersFunder number
Jilin Province Science and Technology Development Plan Project20180418128FG
National Natural Science Foundation of China71874068
Ministry of Education of the People's Republic of China17YJC790129

    Keywords

    • C15
    • Entrepreneurial process
    • L26
    • M13
    • Networks
    • Simulation
    • Social capital
    • Start-up
    • Survival rate

    Fingerprint

    Dive into the research topics of 'The entrepreneurial process and online social networks: forecasting survival rate'. Together they form a unique fingerprint.

    Cite this