Volltext-Downloads (blau) und Frontdoor-Views (grau)
The search result changed since you submitted your search request. Documents might be displayed in a different sort order.
  • search hit 5 of 60
Back to Result List

Applying Text Analytics to Business Plans in New Technology-Based Firm Survival Research

  • Text produced by entrepreneurs represents a data source in entrepreneurship research on venture performance and fund-raising success. Manual text coding of single variables is increasingly assisted or replaced by computer-aided text analysis. Yet, for the development of prediction models with several variables, such dictionary-based text analysis methods are less suitable. Natural language processing techniques are an alternative; however, the implementation is more complex and requires substantial programming skills. More work is required to understand how text analytics can advance entrepreneurship research. This study hence experiments with different artificial intelligence methods rooted in Natural Language Processing and deep learning. It uses 766 business plans to train a model for the automated measurement of transaction relations, a construct which is an indicator for new technology-based firm survival. Empirical findings show that the accuracy of construct measurement can be significantly increased with automated methods and improves with larger amounts of training data. Language complexity sets limits to the precision of automated construct measurement though. We therefore recommend a hybrid approach: making use of the inherent advantages of combining automated with human coding until the amount of training data is sufficiently large to substitute the human coding completely. The study provides insights into the applicability of different text analytics methods in entrepreneurship research and points at future research potential.

Export metadata

Additional Services

Search Google Scholar

Statistics

frontdoor_oas
Metadaten
Author:Christina UngererORCiD, Marc König, Guido H. BaltesORCiDGND
DOI:https://doi.org/10.1109/ICE/ITMC52061.2021.9570212
ISBN:978-1-6654-4963-2
Parent Title (English):27th IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), 21-23 June 2021, Cardiff, UK, virtual
Publisher:IEEE
Document Type:Conference Proceeding
Language:English
Year of Publication:2021
Release Date:2022/01/08
Tag:NTBF Survival; Artificial Intelligence; Text Analytics; Value Network; Transaction Relations
Page Number:19
Note:
Volltextzugriff für Angehörige der Hochschule Konstanz via Datenbank IEEE Xplore möglich
Institutes:Institut für Strategische Innovation und Technologiemanagement - IST
Relevance:Keine peer reviewed Publikation (Wissenschaftlicher Artikel und Aufsatz, Proceeding, Artikel in Tagungsband)
Open Access?:Nein
Licence (German):License LogoUrheberrechtlich geschützt