Bayesian network analysis for the dynamic prediction of early stage entrepreneurial activity index

So Young Sohn, Ann Sung Lee

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Entrepreneurship plays a critical role for the development and well-being of society. Illustration of its dynamic relationship with entrepreneurial attitudes and aspirations can provide a guideline for the cause of such activities. However, a time-lagged causal relationship among these concepts has not yet been established. In this study, we examine a dynamic relationship among early stage entrepreneurial attitudes, activities, and aspirations using Bayesian network (BN) analysis. In addition, we propose an early stage entrepreneurial activity index that can predict the percentage of both nascent entrepreneur and new business owner using the variables related to entrepreneurial attitudes of the previous year. This index, in turn, can be used to predict various aspects of entrepreneurial aspiration of the following year. The proposed index turns out to have very high prediction accuracy and is expected to provide effective policies to boost future entrepreneurial activity and aspiration.

Original languageEnglish
Pages (from-to)4003-4009
Number of pages7
JournalExpert Systems with Applications
Volume40
Issue number10
DOIs
Publication statusPublished - 2013 Aug 1

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Bayesian networks
Electric network analysis
Industry

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

Cite this

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Bayesian network analysis for the dynamic prediction of early stage entrepreneurial activity index. / Sohn, So Young; Lee, Ann Sung.

In: Expert Systems with Applications, Vol. 40, No. 10, 01.08.2013, p. 4003-4009.

Research output: Contribution to journalArticle

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