Research on Mergers and Acquisitions of Listed Companies Based on Dictionary Method and Development of New Quality Productivity

In the context of high-quality economic development, new productive forces have become a key force driving industrial upgrading and economic growth. The impact of mergers and acquisitions (M&A) on the development of new productive forces in listed companies has attracted significant attention. This paper uses M&A events of A-share listed companies from 2015 to 2023 as a sample, employing the text dictionary method to construct a dictionary of new productive forces, assessing the level of new productive forces in enterprises, and using the multi-period difference-in-differences method to investigate the impact of M&A on their development. The study finds that M&A significantly enhances the level of new productive forces in enterprises, with more pronounced positive effects on larger companies and those that have merged two roles into one, while having a negative effect on older companies with concentrated equity. Further heterogeneity tests show that M&A has a more significant promoting effect on new productive forces in state-owned enterprises, high-tech industry companies, and regions with well-developed factor markets. Mechanism analysis confirms that M&A promotes the development of new productive forces by enhancing human capital levels and R&D intensity. The study provides reference for corporate strategic decision-making and government policy formulation. Based on the above research, this paper recommends precise targeting of M&A to enhance new productive forces; formulating differentiated policies to support M&A upgrades; expanding research dimensions to delve deeper into the mechanisms of M&A impacts, thereby improving the service efficiency of M&A for new productive force enterprises.

Authors

Publication Details

Journal
Mathematical Modeling and Algorithm Application
Published
2025-10-09
DOI
https://doi.org/10.54097/1rejg923
Primary Topic
Educational Reforms and Innovations
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on Mergers and Acquisitions of Listed Companies Based on Dictionary Method and Development of New Quality Productivity

Jin Cui, Yihe Wang
Mathematical Modeling and Algorithm Application
Educational Reforms and Innovations
article

Research on Mergers and Acquisitions of Listed Companies Based on Dictionary Method and Development of New Quality Productivity

Jin Cui, Yihe Wang
article en

Abstract

In the context of high-quality economic development, new productive forces have become a key force driving industrial upgrading and economic growth. The impact of mergers and acquisitions (M&A) on the development of new productive forces in listed companies has attracted significant attention. This paper uses M&A events of A-share listed companies from 2015 to 2023 as a sample, employing the text dictionary method to construct a dictionary of new productive forces, assessing the level of new productive forces in enterprises, and using the multi-period difference-in-differences method to investigate the impact of M&A on their development. The study finds that M&A significantly enhances the level of new productive forces in enterprises, with more pronounced positive effects on larger companies and those that have merged two roles into one, while having a negative effect on older companies with concentrated equity. Further heterogeneity tests show that M&A has a more significant promoting effect on new productive forces in state-owned enterprises, high-tech industry companies, and regions with well-developed factor markets. Mechanism analysis confirms that M&A promotes the development of new productive forces by enhancing human capital levels and R&D intensity. The study provides reference for corporate strategic decision-making and government policy formulation. Based on the above research, this paper recommends precise targeting of M&A to enhance new productive forces; formulating differentiated policies to support M&A upgrades; expanding research dimensions to delve deeper into the mechanisms of M&A impacts, thereby improving the service efficiency of M&A for new productive force enterprises.

Mathematical Modeling and Algorithm ApplicationVol. 6(1)
Openalex Percentile: Top 62%
Educational Reforms and Innovations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Research on Mergers and Acquisitions of Listed Companies Based on Dictionary Method and Development of New Quality Productivity — Jin Cui, Yihe Wang · Mathematical Modeling and Algorithm Application (2025) | TGRS Research Map | TGRS