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How to achieve the high‐quality development of SRDI enterprises? Evidence from machine learning

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  • Guimin Qu
  • Jingkun Bai

Abstract

Exploring how SRDI enterprises achieve high‐quality development constitutes a pivotal task for small and medium‐sized enterprises (SMEs) and niche leaders. While prior research primarily concentrated on the influence of innovative policies on SRDI enterprises, it has disregarded the intrinsic propelling forces intrinsic to these enterprises. To bridge this research gap, our study leverages a machine learning model that incorporates 19 feature variables spanning four dimensions—“specialization, refinement, distinctiveness, and innovation”—to anticipate high‐quality development in enterprises. Drawing on a sample of 667 A‐share SRDI‐listed enterprises from 2012 to 2022, and after subjecting the data to preprocessing, the study employs the mean of five machine learning models to predict high‐quality development in enterprises. Moreover, we discern pivotal feature variables and dimensions. Notably, outcomes underscore the paramount significance of market share in achieving high‐quality progress within SRDI enterprises, with refinement emerging as the foremost feature dimension among the four. Moreover, during the three stages delineated by SRDI policies, research and development intensity, equity financing, and market share emerge as the preeminent feature variables within their respective stages.

Suggested Citation

  • Guimin Qu & Jingkun Bai, 2024. "How to achieve the high‐quality development of SRDI enterprises? Evidence from machine learning," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 45(4), pages 2023-2041, June.
  • Handle: RePEc:wly:mgtdec:v:45:y:2024:i:4:p:2023-2041
    DOI: 10.1002/mde.4114
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