Identify Business Opportunities Through Policy Texts: Saturation State Test Method of the Concept Space

Ai Wang () and Xuedong Gao ()
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Ai Wang: University of Science and Technology Beijing
Xuedong Gao: University of Science and Technology Beijing

A chapter in LISS 2023, 2024, pp 781-790 from Springer

Abstract: Abstract Digital transformation offers a wealth of business opportunities for various enterprises across the world. This paper focuses on the saturation state test problem of (business) concept space, to help enterprises automatically identify business growth points through policy texts. Firstly, the concept space saturation is defined based on the variable-scale data analysis theory. In order to determine whether a concept space has reached the saturation state, the expected information quantity measurement of concept space is proposed. After establishing the saturation state test mechanism of thinking theme identification process, an algorithm of saturation state test of concept space (SST-CS) is also put forward. A case study on the real policy texts in urban green transportation industry demonstrates that the proposed SST-CS could identify business opportunities efficiently.

Keywords: digital transformation; variable-scale data analysis; saturation state test; policy texts; vehicle-to-grid (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/978-981-97-4045-1_61

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