Details
| Original language | English |
|---|---|
| Pages (from-to) | 673-694 |
| Number of pages | 22 |
| Journal | Small business economics |
| Volume | 55 |
| Issue number | 3 |
| Early online date | 13 Jun 2019 |
| Publication status | Published - Oct 2020 |
Abstract
Although conventional register and survey data on entrepreneurship have enabled remarkable insights into the phenomenon, the added value has slowed down noticeably over the last decade. There is a need for fresh approaches utilising modern data sources such as Big Data. Until now, it has been quite unknown whether Big Data actually embodies valuable contributions for entrepreneurship research and where it can perform better or worse than conventional approaches. To contribute towards the exploration of Big Data in entrepreneurship research, we use a newly developed dataset based on publications of the German Press Agency (dpa) to explore the relationship between news coverage of entrepreneurship and regional entrepreneurial activity. Furthermore, we apply sentiment analysis to investigate the impact on sentiment of entrepreneurial press releases. Our results show mixed outcomes regarding the relationship between reporting of entrepreneurial events, i.e. media coverage, and entrepreneurial activity in German planning regions. At this stage, our empirical results reject the idea of a strong relationship between actual entrepreneurial activities in regions and the intensity of it being reported. However, the results also imply much potential of Big Data approaches for further research with more sophisticated methodology approaches. Our paper provides an entry point into Big Data usage in entrepreneurship research and we suggest a number of relevant research opportunities based on our results.
Keywords
- Big Data, Entrepreneurial ecosystem, Entrepreneurship, GEM, Mass media, Media coverage, News data, Region, Sentiment analysis
ASJC Scopus subject areas
- Business, Management and Accounting(all)
- General Business,Management and Accounting
- Economics, Econometrics and Finance(all)
- Economics and Econometrics
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In: Small business economics, Vol. 55, No. 3, 10.2020, p. 673-694.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - New(s) data for entrepreneurship research? An innovative approach to use Big Data on media coverage
AU - von Bloh, Johannes
AU - Broekel, Tom
AU - Özgun, Burcu
AU - Sternberg, Rolf
N1 - Funding Information: We are grateful for the helpful comments of four anonymous reviewers. All Mistakes remain our own. This paper was made possible through support of the Lower Saxony Ministry of Science and Culture (Germany) under Grant number 76202-17-1/14.
PY - 2020/10
Y1 - 2020/10
N2 - Although conventional register and survey data on entrepreneurship have enabled remarkable insights into the phenomenon, the added value has slowed down noticeably over the last decade. There is a need for fresh approaches utilising modern data sources such as Big Data. Until now, it has been quite unknown whether Big Data actually embodies valuable contributions for entrepreneurship research and where it can perform better or worse than conventional approaches. To contribute towards the exploration of Big Data in entrepreneurship research, we use a newly developed dataset based on publications of the German Press Agency (dpa) to explore the relationship between news coverage of entrepreneurship and regional entrepreneurial activity. Furthermore, we apply sentiment analysis to investigate the impact on sentiment of entrepreneurial press releases. Our results show mixed outcomes regarding the relationship between reporting of entrepreneurial events, i.e. media coverage, and entrepreneurial activity in German planning regions. At this stage, our empirical results reject the idea of a strong relationship between actual entrepreneurial activities in regions and the intensity of it being reported. However, the results also imply much potential of Big Data approaches for further research with more sophisticated methodology approaches. Our paper provides an entry point into Big Data usage in entrepreneurship research and we suggest a number of relevant research opportunities based on our results.
AB - Although conventional register and survey data on entrepreneurship have enabled remarkable insights into the phenomenon, the added value has slowed down noticeably over the last decade. There is a need for fresh approaches utilising modern data sources such as Big Data. Until now, it has been quite unknown whether Big Data actually embodies valuable contributions for entrepreneurship research and where it can perform better or worse than conventional approaches. To contribute towards the exploration of Big Data in entrepreneurship research, we use a newly developed dataset based on publications of the German Press Agency (dpa) to explore the relationship between news coverage of entrepreneurship and regional entrepreneurial activity. Furthermore, we apply sentiment analysis to investigate the impact on sentiment of entrepreneurial press releases. Our results show mixed outcomes regarding the relationship between reporting of entrepreneurial events, i.e. media coverage, and entrepreneurial activity in German planning regions. At this stage, our empirical results reject the idea of a strong relationship between actual entrepreneurial activities in regions and the intensity of it being reported. However, the results also imply much potential of Big Data approaches for further research with more sophisticated methodology approaches. Our paper provides an entry point into Big Data usage in entrepreneurship research and we suggest a number of relevant research opportunities based on our results.
KW - Big Data
KW - Entrepreneurial ecosystem
KW - Entrepreneurship
KW - GEM
KW - Mass media
KW - Media coverage
KW - News data
KW - Region
KW - Sentiment analysis
UR - http://www.scopus.com/inward/record.url?scp=85067249719&partnerID=8YFLogxK
U2 - 10.1007/s11187-019-00209-x
DO - 10.1007/s11187-019-00209-x
M3 - Article
AN - SCOPUS:85067249719
VL - 55
SP - 673
EP - 694
JO - Small business economics
JF - Small business economics
SN - 0921-898X
IS - 3
ER -