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Open Access

Indicator-Type Grey Structure Incidence Analysis Method for Panel Data and Its Application in Identifying Technological Innovation Factors

School of Business, Jiangnan University, Wuxi 214122, China
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Abstract

There exist many panel data decision problems in real life, and they take on obvious structural similarities and lag effects among decision objects or indicators, which are difficult to solve effectively based on traditional panel data analysis methods. To deal with these problems, considering the structural characteristics of panel data and lag effect, from multiple structural dimensions such as scale volume, development trend, and volatility, we exploit grey incidence analysis and panel data to establish an indicator-type grey structural incidence analysis model, and utilize it to analyze and identify factors influencing technological innovation of industrial enterprises. The results show that the proposed method fully considers the structural characteristics of panel data and lag effect, and it can deal with panel data decision problems and provide a new methodological support for the grey incidence analysis.

Keywords

scale volumedevelopment trendvolatilitygrey structural incidence analysistime-lag effect

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Journal of Social Computing
Volume 6 Issue 2,
June 2025
Pages 145-157
DOI: 10.23919/JSC.2025.0004
Cite this article:
Gu S, Liu Y, Yue L. Indicator-Type Grey Structure Incidence Analysis Method for Panel Data and Its Application in Identifying Technological Innovation Factors. Journal of Social Computing, 2025, 6(2): 145-157. https://doi.org/10.23919/JSC.2025.0004

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Received: 30 October 2024
Revised: 06 January 2025
Accepted: 15 March 2025
Published: 30 June 2025
© The author(s) 2025.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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