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RESEARCH ARTICLE
Research on the impact of enterprise mergers
and acquisitions on technological innovation:
An empirical analysis based on listed Chinese
enterprises
Yujiao Bai
1¤a
, Hao ZhangID
2¤b
*
1Center for Industrial and Business Organization, Dongbei University of Finance and Economics, Dalian,
Liaoning, China, 2School of Economics and Management, Huaibei Normal University, Huaibei, Anhui, China
¤a Current address: Dongbei University of Finance and Economics, Dalian City, Liaoning Province, China
¤b Current address: Huaibei Normal University, Huaibei City, Anhui Province, China
*zhangh@chnu.edu.cn
Abstract
As an important means for enterprises to acquire technological resources, the impact of
mergers and acquisitions on technological innovation and underlying mechanisms deserve
in-depth study. Using the merger and acquisition data of A-share listed Chinese companies
from 2007 to 2020 in Shanghai and Shenzhen, the causal effects and influence mechanisms
between mergers and acquisitions and technological innovation are identified and tested
using the Difference-in-Differences method. The study finds that mergers and acquisitions
have a long-term, sustained, technological innovation-enhancing effect on firms. Mecha-
nism tests show that mergers and acquisitions can promote the technological innovation of
enterprises by improving production efficiency, enriching digital knowledge, and enhancing
market power. A heterogeneity analysis shows that the effect of mergers and acquisitions in
enhancing technological innovation is more significant when the mergers and acquisitions
meet domestic merger and acquisition requirements, when there is a small transaction size,
and when the enterprises involved in the mergers and acquisitions are not state-owned. It is
suggested that enterprises and the government should use multiple measures, while con-
sidering the impact of heterogeneity, to take full advantage of the positive effects of mergers
and acquisitions on technological innovation.
1. Introduction
In 2010, China became the country with the greatest involvement in the manufacturing indus-
try; however, it has long faced the difficulties of serious duplication of industry construction,
low industrial concentration, a weak independent innovation ability, and weak market com-
petitiveness. Under the pattern of latecomer competition, breaking through the technological
blockade, solving the “bottleneck” problem, and achieving subversive innovation are necessary
strategies for Chinese enterprises to catch up with current technology. However, due to the
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OPEN ACCESS
Citation: Bai Y, Zhang H (2024) Research on the
impact of enterprise mergers and acquisitions on
technological innovation: An empirical analysis
based on listed Chinese enterprises. PLoS ONE
19(11): e0309569. https://doi.org/10.1371/journal.
pone.0309569
Editor: Pu-yan Nie, Guangdong University of
Finance and Economics, CHINA
Received: April 9, 2024
Accepted: August 13, 2024
Published: November 27, 2024
Peer Review History: PLOS recognizes the
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https://doi.org/10.1371/journal.pone.0309569
Copyright: ©2024 Bai, Zhang. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data are
within the manuscript and its Supporting
Information files.
lack of technical skills and the long technology research and development cycle, it is a relatively
slow method for enterprises to rely on independent innovation to improve their technological
levels [1,2]. According to the theory of open innovation, enterprises can rapidly acquire het-
erogeneous knowledge that is difficult to purchase in the factor market through mergers and
acquisitions [3], and external digital resources such as talent, technology and knowledge
acquired through mergers and acquisitions can be utilized to improve the level of technological
innovation of enterprises [4]. With the growing demand for technological innovation in
China, enterprises need to absorb new technological knowledge through cross-industry inte-
gration to more quickly achieve technological innovation in order to maintain competitive
advantages and make use of new opportunities [5]; thus, a large number of enterprises have
started to acquire external knowledge through mergers and acquisitions to enhance technolog-
ical innovation abilities.
According to CSMAR data, in terms of quantity and amount, China’s merger and acquisi-
tion activities have increased over the past decade [6]. In 2020, the number of China’s merger
and acquisition transactions reached a record high, with a total of 9,879 merger and acquisi-
tion events and a total merger and acquisition value of $409.969 billion, up 168% and 356%,
respectively, compared with 2007. However, there are many cases of failure. For example,
since 2015, Chengdu Tianxiang Environment Co., Ltd., China’s leading environmental protec-
tion equipment company, has acquired the U.S. sludge treatment equipment company Cen-
trisys Corporation, Germany’s Belfinger Water Treatment (BWT), and Germany’s “solid
waste giant” Euromonitor Group, but the company went bankrupt and delisted in December
2020 due to a lack of breakthroughs in core technology and poor operations.
Based on the above, this study aims to answer the following questions: Can mergers and
acquisitions promote the technological innovation of Chinese enterprises? If so, what is the
mechanism? As there are both state-owned and non-state-owned enterprises in China, does
the relationship between mergers and acquisitions and technological innovation reflect hetero-
geneity according to the characteristics of enterprises and types of mergers and acquisitions?
To address these questions, this paper identifies and examines the causal effect and influence
mechanism between mergers and acquisitions and technological innovation based on the
merger and acquisition data of Chinese A-share listed firms in Shanghai and Shenzhen under
the framework of the Difference-in-Differences method of empirical testing. This paper fur-
ther examines the impact of heterogeneity, i.e., firm idiosyncrasies, according to the type of
merger and acquisition transactions and the nature of firm ownership.
2. Literature review
2.1 Mergers and acquisitions
As a business strategy for enterprises to expand scale, increase market share, optimize
resources, and reduce costs, the merger and acquisition effect is a core issue of concern for
many parties. The literature on the effects of mergers and acquisitions mainly focuses on
merger and acquisition firms and explores the impact of mergers and acquisitions on their
market power, productivity and wealth [7–10]. Tang et al. (2022) [11] found that mergers and
acquisitions can significantly enhance the market power of manufacturing firms from the per-
spective of digital transformation. Jiang (2021) [12] utilized Thomson Reuters mergers and
acquisitions data from 2003 to 2007 and merged it with a database of Chinese industrial enter-
prises and found that mergers and acquisitions in China not only enhanced the market power
of the enterprises but also significantly improved their productivity. Focusing on the Chinese
coal industry, He et al (2020) [13] found that mergers and acquisitions by listed coal compa-
nies lead to efficiency gains. Using data from the U.S. manufacturing industry, Kim et al.
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Funding: This research was supported by Anhui
Province Excellent Youth Research Project in
Universities, grant number 2023AH030082. The
funders had no role in study design, data collection
and analysis, decision to publish, or preparation of
the manuscript.
Competing interests: The authors have declared
that no competing interests exist.
(2019) [14] found that the mergers and acquisition experience of merger and acquisition firms
is most positively correlated with productivity. Fich et al. (2018) [10] found that shareholders
of merger and acquisition firms gained wealth in merger and acquisition transactions.
2.2 Technological innovation
Technological innovation is a key driving force for enterprises to gain and maintain competi-
tiveness and performance [15]. This is also a necessary condition for promoting sustainable
economic growth in countries, especially emerging countries such as China. However, techno-
logical innovation is characterized by long investment returns, high costs, strong challenges,
and high uncertainty [16]. Therefore, studying how enterprises can achieve technological
innovation has attracted widespread attention from all sectors. Scholars have conducted exten-
sive discussions of the factors that affect corporate technological innovation, mainly focusing
on knowledge management [17,18], corporate governance [19], and tax policies [20]. For
example, Li et al. (2023) [19] used panel data from 30 provinces in China from 2013 to 2020
and found that promoting digitalization in manufacturing can promote technological innova-
tion. From the perspective of related industry layouts, Qian et al. (2023) [21] verified that the
agglomeration of the technology service industry can promote enterprise technological inno-
vation. Kanojia et al. (2023) [22] used data from 5747 Indian companies to explore the impact
of external and internal factors on technological innovation.
2.3 Mergers and acquisitions and technological innovation
In recent years, the relationship between mergers and acquisitions and technological innova-
tion has gradually received attention from academics, and some studies have shown that merg-
ers and acquisitions can drive technological innovation, and merger and acquisition firms gain
access to the technological resources of the acquired firms through acquisitions to drive the
technological change of the merger and acquisition firms after acquisitions [23–26]. Wang
et al. (2022) [27] found that firms carry out the redistribution of innovations through mergers
and acquisitions and increase their level of innovation. Bena et al. (2014) [28] argued that
innovation often leads to merger and acquisition synergies and that synergies from merger
and acquisition activities promote innovation output [29,30]. However, some studies have
shown that mergers and acquisitions lead to reduced innovation efficiency [31] and inhibit
firms’ innovation [32]. Haucap et al. (2019) [33], using data from the European pharmaceuti-
cal industry, showed that mergers and acquisitions inhibit firms’ R&D investment and reduce
the level of firms’ technological innovation. Using data from China’s manufacturing industry
as a sample, Ma et al. (2017) [34] empirically found that nontechnology mergers and acquisi-
tions have a negative impact on the technological innovation of merger and acquisition firms.
The empirical results of the impact of mergers and acquisitions on technological innovation
are inconsistent, with most studies suggesting that they are influenced by factors such as the
motives for mergers and acquisitions and firm and industry heterogeneity. In general, in non-
technology mergers and acquisitions, the acquired firms tend not to provide technical support
to the acquiring firms and thus often do not contribute to the technological innovation of the
acquiring firms [35].
2.4 Literature summary
Scholars have conducted rich research on the economic consequences of mergers and acquisi-
tions and the driving force of corporate technological innovation; however, the relationship
between mergers and acquisitions and technological innovation can still be further studied
based on the following three points. First, for the empirical analysis of different research
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objects, scholars have found that mergers and acquisitions may promote enterprise innovation
or may have a negative impact; therefore, the impact of mergers and acquisitions on technologi-
cal innovation needs to be further tested. Second, the research on the impact and mechanism of
mergers and acquisitions on technological innovation is still quite limited, and the path of how
to realize technological innovation through mergers and acquisitions is still unclear. Third,
there is a lack of research on whether the impact of mergers and acquisitions on technological
innovation varies according to firm ownership traits and merger and acquisition type.
In comparison with the literature, the contributions of this study are as follows. First, the
impact of mergers and acquisitions on technological innovation is examined using Chinese
listed firms as the research object. Second, this study further expands the research on the
mechanism and path of mergers and acquisitions on technological innovation and improves
the theoretical framework of mergers and acquisitions for technological innovation. Third,
this study captures the heterogeneous results of mergers and acquisitions for technological
innovation by grouping regressions based on the relevant factors affecting the promotion
effect, such as the type of merger and acquisition, the intensity of the merger and acquisition,
and the nature of firm ownership.
3. Theoretical analysis and research hypotheses
3.1 The impact of corporate mergers and acquisitions on technological
innovation
An innovative model is based on the research of Chen et al. (2019) [36]. Assuming a market
with two companies (i,l), the inverse demand function for both companies is P=a−Q, where
Qis the market’s product output. Assuming that the fixed cost of the enterprise is zero, it is
assumed that the enterprise has always made innovation investments (x
i
,x
j
) since its establish-
ment; that is, x
i
>0,x
j
>0, x
i
,x
j
follows the law of diminishing marginal returns and, thus,
appears in quadratic form. Next, we compare and analyze the changes in innovation before
and after corporate mergers and acquisitions.
3.1.1 No mergers or acquisitions. When there is no merger or acquisition, the cost of
company iis:
CT
i¼ ðCxiÞqiþ1
2gix2
ið1Þ
Here, γ
i
represents the cost efficiency of enterprise i’s technological innovation, and γ
i
decreases with an increase in enterprise i’s technological innovation level. The profit of com-
pany iis:
pi¼aQð ÞqiCxi
ð Þqiþ1
2gix2
i
ð2Þ
By taking the first derivative of q
i
and x
i
in Formula (2) in sequence, the equilibrium value
of x
i
can be obtained:
x∗
i¼4ðaCÞ
9gi4ð3Þ
The smaller γ
i
is, the larger x∗
iis, which means that a higher level of enterprise technological
innovation is associated with enterprises making more investments in technological innova-
tion. However, when enterprises’ technological innovation reaches a certain level, that is,
0<γ
i
<4/9, the enterprise no longer invests in technological innovation.
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3.1.2 Mergers and acquisitions. When company iacquires company l, the cost after the
acquisition of company iis:
CT
i¼C ðxiþφlxlÞqi
þ1
2gix2
iþdx2
l
ð4Þ
Here, φ
l
represents the absorption and digestion level of innovation resources by company i
to company l, which depends on the resource integration and digestion ability of enterprise i
after a merger or acquisition and is consistent with φ
l
>0; δrepresents the cost of enterprise i
absorbing technology and knowledge from enterprise l, which is consistent with δ>0. The
profit of enterprise iis:
pi¼aQCþxiþφlxl
qi1
2gix2
iþdx2
l
ð5Þ
By taking the first derivative of q
i
and x
i
in Formula (5) in sequence, the equilibrium value
of x
i
can be obtained:
x∗
i¼aCþφlxl
2gi1ð6Þ
According to Formula (6), if an enterprise still invests in technological innovation after a
merger or acquisition, it needs to meet γ
i
>1/2; when γ
i
<1/2, that is, x∗
i<0, mergers and
acquisitions inhibit the technological innovation of enterprise i.
On the basis of the previous text, we compare the changes in x
i
before and after the merger:
4x∗
i¼ðaCÞgiþ ð9gi4Þφlxl
ð2gi1Þð9gi4Þð7Þ
When the enterprise’s technological innovation is low, to absorb the new technologies
obtained from mergers and acquisitions, the enterprise must continue to increase its R&D
efforts, enhance its ability to absorb new technologies, and improve its technological innova-
tion level. When a company has high technological innovation, it acquires technological
knowledge through acquisitions. An acquiring party with a higher level of technological inno-
vation can innovate these new technologies, which can further enhance the company’s degree
of technological innovation. When the technological innovation in enterprises is moderate,
mergers and acquisitions often suppress the driving force of technological innovation under
the dual pressure of having to digest and absorb new technologies and continuous indepen-
dent innovation. Based on this, the following research hypothesis is proposed.
Hypothesis 1: Because the average technological innovation capability of Chinese enterprises is
relatively low, mergers and acquisitions can promote technological innovation.
3.2 Analysis of impact mechanisms
3.2.1 Path to improving production efficiency. Mergers and acquisitions can improve
enterprises’ production efficiency, thereby enhancing their technological innovation. Through
mergers and acquisitions, enterprises can achieve optimized resource allocation and improve
production efficiency [37]. Similarly, Chen et al. (2019) [36] found that Chinese manufactur-
ing companies can improve their production efficiency and promote innovation through
mergers and acquisitions. After the merger and acquisition of enterprises has been completed,
the integration of the enterprise’s original technology with the digital technology and resources
of the acquired enterprise will facilitate more intelligent and efficient use of digital technology
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for production [38], improve the overall efficiency of the enterprise’s production, increase the
enterprise’s R&D investment, and enhance the enterprise’s level of technological innovation.
In summary, the following research hypothesis is proposed:
Hypothesis 2: Mergers and acquisitions can promote technological innovation by improving
corporate productivity.
3.2.2 Path to enriching digital knowledge. Corporate mergers and acquisitions empower
digital transformation, increase intangible assets, and enhance knowledge spillover effects;
thus, they have a positive impact on technological innovation in enterprises. Corporate merg-
ers and acquisitions can facilitate the direct acquisition of digital assets and external knowl-
edge, allow for quick compensation for shortcomings in digital resources, help enterprises
achieve digital transformation [39], increase the stock of enterprise knowledge, improve enter-
prises’ ability to receive new external knowledge, and accelerate the speed of integration of the
knowledge resources of acquiring enterprises [40,41]. With such mergers and acquisitions,
enterprises can more easily leverage newly formed digital capabilities to expand their potential
knowledge portfolio, thereby enhancing their inclination toward technological innovation [42,
43]. Therefore, the increase in basic knowledge generated by corporate mergers and acquisi-
tions helps improve enterprises’ ability to integrate innovative resources, thereby promoting
technological innovation. In summary, the following research hypothesis is proposed:
Hypothesis 3: Mergers and acquisitions can promote technological innovation by enriching a
company’s digital knowledge.
3.2.3 Path to enhancing market power. Mergers and acquisitions can enhance a com-
pany’s market power, thereby enhancing its degree of technological innovation. First, through
mergers and acquisitions, enterprises can share resources such as human capital, intangible
assets, and advanced technology, which to a certain extent generates synergy in management
and technological R&D [44]. Moreover, the increase in market power generated by mergers
and acquisitions can accelerate the speed of enterprise technological integration, strengthen
enterprise R&D efforts [6], and increase the degree of enterprise innovation output. Second,
companies eliminate the threat of potential competitors through mergers and acquisitions [45,
46]. To absorb new technologies from competitors and maintain their market position, com-
panies increase their R&D funds, increase their R&D efforts, attach importance to R&D out-
put, and improve their technological innovation. In summary, the following research
hypothesis is proposed:
Hypothesis 4: Mergers and acquisitions can promote technological innovation by enhancing a
company’s market power.
Overall, corporate mergers and acquisitions can directly promote technological innovation.
In this process, the production efficiency of the enterprise is improved, technical knowledge is
enriched, and the market power of the enterprise is increased. These changes help enterprises
improve the quality and efficiency of their R&D processes and enhance their ability to inte-
grate and innovate cross-disciplinary technologies, giving them greater advantages in techno-
logical innovation.
4. Research design
4.1 Data sources
In this article, we summarize Chinese merger and acquisition cases and show that the informa-
tion on merger and acquisition cases was relatively complete and that the number of cases
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increased significantly in 2007. Therefore, Chinese A-share listed companies in Shanghai and
Shenzhen from 2007 to 2020 are selected as the research objects. To avoid the impact of outli-
ers on the regression results, all continuous variables are subjected to a 1% truncation process.
The screening of merger and acquisition data is as follows. First, all merger and acquisition
transaction events of A-share listed companies in Shanghai and Shenzhen are obtained from
the CSMAR database. Referring to the methods for processing merger and acquisition data
used by Ren et al. (2017) [6], Liu et al. (2018) [8] and Wang et al. (2023) [47], the sample of
financial industry companies is excluded. Second, merger and acquisition samples with
restructuring types such as share repurchases, debt restructuring, asset divestments, and pro-
duction replacements are excluded. Then, merger and acquisition samples with transaction
amounts less than one million RMB are excluded. Finally, incomplete information samples are
excluded. We obtain 2273 M&A companies, totaling 4631 samples.
The 4631 merger and acquisition transaction events are screened twice to eliminate the
effect of noise. According to the merger and acquisition information, based on the date of the
first merger and acquisition announcement, the acquiring firms have multiple merger and
acquisition events in the same year, one merger and acquisition event is held if the target firms
are the same firms, all of the merger and acquisition events are held if the target firms are dif-
ferent, and, finally, a sample of 1,940 M&A firms is obtained after processing.
4.2 Empirical model construction
Drawing on the practices of Li (2013) [48] and Li et al. (2016) [49], we establish Eq (8) to verify
whether a company’s technological innovation capability has improved after mergers and
acquisitions.
innoit ¼a0þa1Treatit∗Postit þX
7
c¼1
acControlit þYearFE þFirmFE þIndFE þProFE þεit ð8Þ
Here, inno
it
represents the technological innovation level of enterprise iin year t.Treat rep-
resents whether the enterprise has undergone mergers and acquisitions. For enterprises that
have not undergone mergers and acquisitions and for the years before the merger and acquisi-
tion, both have a value of 0, whereas for enterprises that have undergone mergers and acquisi-
tions, the value is 1 for the year of the merger and acquisition and subsequent years. If a
company underwent multiple mergers and acquisitions in different years, the year of the first
merger and acquisition is the processing year. Control represents other control variables;
Year
FE
,Firm
FE
,Ind
FE
, and Pro
FE
represent fixed effects for year, individual, industry, and prov-
ince, respectively; and ε
it
represents random error. The control variables are obtained from the
CSMAR database to match the financial data with merger and acquisition samples, and the
missing values of the acquirer firms are assigned to 0 after matching (firms where no merger
and acquisition has occurred are assigned a value of 0). The specific definitions and descrip-
tions of each variable are shown in Table 1.
4.3 Variable description
Dependent variable: Referring to Chen et al. (2019) [36], we examine the changes in techno-
logical innovation before and after mergers and acquisitions using the number of patent appli-
cations as a measure. In the robustness test section, we refer to the approach of Fang et al.
(2022) [5] and use the number of effective patents as the dependent variable for the regression.
Independent variable: Whether or not the business has undergone a merger or acquisition
(Treat∗Post). This variable is obtained by multiplying the virtual variable of enterprise
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grouping (Treat
it
, takes the value of 1 for the year of merger or acquisition and 0 otherwise) by
the virtual variable of event impact time (Post
it
, takes the value of 1 for the year of merger and
acquisition and subsequent years and 0 otherwise). We take the occurrence of mergers and
acquisitions as the core explanatory variable to test whether the innovation performance of the
treatment group of enterprises significantly differs from that of the control group of enter-
prises after mergers and acquisitions and then explore the causal effect of mergers and acquisi-
tions on their technological innovation ability.
Control variables: In accordance with the findings of Bena et al. (2014) [28] and Cheng
et al. (2023) [50], we select enterprise-level variables such as operating profit margin (ros),
enterprise size (size), leverage ratio (lev), capital intensity (kint), book-to-market ratio (bdm),
Tobin Q(tobinq), and total number of employees (lnwor) as control variables to best control
for the impact of observable enterprise characteristics on the estimation results. The descrip-
tive statistics of the variables are shown in Table 2.
5. Empirical analysis
5.1 The impact of corporate mergers and acquisitions on technological
innovation
The regression results for the impact of corporate mergers and acquisitions on technological
innovation are shown in Table 3. The first and third columns and the second and fourth
Table 1. Meaning and explanation of the variables.
Variable type Variable
symbol
Meaning of variables
Dependent
variable
inno Logarithm of 1 plus the number of patent applications from the mergers and
acquisitions company
Independent
variable
Treat Whether the mergers and acquisitions company has engaged in a merger (1 for
the year of merger and 0 otherwise)
Post Virtual variable (take the value of 1 for the year of a merger or acquisition and
subsequent years)
Control variable ros Operating profit margin (operating profit/operating revenue)
size Enterprise size (logarithmic of total assets)
lev Leverage ratio (total liabilities/total assets)
kint Capital intensity (total assets/operating income)
bdm Book to market ratio (total assets/market value)
tobinq Tobin Q (market value/total assets)
lnwor Total number of employees (logarithm of 1 plus the number total number of
employees)
https://doi.org/10.1371/journal.pone.0309569.t001
Table 2. Descriptive statistical results of the variables.
Variable (1) (2) (3) (4) (5)
Obs Mean Standard Deviation Minimum Maximum
inno 68,698 0.811 1.360 0 8.830
size 68,698 11.51 11.07 0 26.16
lev 68,698 0.230 0.272 0 0.937
kint 68,698 1.883 3.643 0 27.64
bdm 68,698 0.310 0.354 0 1.097
ros 68,698 0.0672 0.169 -0.848 0.582
tobinq 68,698 1.013 1.335 0 6.966
lnwor 68,698 3.946 3.905 0 10.75
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columns represent the fixed effects of uncontrolled and controlled years, enterprises, indus-
tries, and regions, respectively. The third and fourth columns present the regression results for
the controlling variables, such as enterprise operating profit margin (ros), enterprise size (size),
leverage ratio (lev), capital intensity (kint), and book-to-market ratio (bdm). The regression
results in columns (1)-(4) of Table 3 show that the coefficients of the core explanatory variables
(Treat*Post) are significantly positive, indicating that corporate mergers and acquisitions have
a positive effect on technological innovation. Therefore, hypothesis 1 proposed in this article
holds.
5.2 Multiple matching methods for testing the impact of corporate mergers
and acquisitions on technological innovation
To further reduce the impact of sample selection bias, we match the treatment group enterprises
with 1:1 propensity score matching (PSM). The regression estimation results for the matched
samples are shown in column (1) of Table 4. The estimated coefficient of the core explanatory
variable Treat*Post is significantly positive, once again verifying that mergers and acquisitions
have a significant positive impact on corporate innovation. In addition, we replace the matching
ratio with 1:3 and rerun the regression. The regression results are shown in column (2), and the
core explanatory variable is still significantly positive at the 1% level. We also draw on the
approach of Azoulay et al. (2010) [51] and McMullin et al. (2022) [52] and use the coarsened
exact matching (CEM) and entropy balance matching (EBM) methods to rematch the samples
and further test the core conclusions. The test results reveal that the estimated coefficient of the
CEM matching method Treat*Post is 0.307, and the coefficient of the EBM matching method
Treat*Post is 0.292. Both of these values are significantly positive, indicating that the conclusions
of this paper are still valid and relatively robust under the various matching methods.
5.3 Robustness testing
5.3.1 Testing of replacement regression methods. Due to the use of enterprise invention
patents as the dependent variable and the assignment of a value of 0 to missing data in this
Table 3. Impact of corporate mergers and acquisitions on technological innovation.
Variable (1) (2) (3) (4)
inno inno inno inno
Treat*Post 1.407***
(0.0131)
0.688***
(0.0270)
0.536***
(0.0117)
0.422***
(0.0244)
Controls NO NO YES YES
Year FE NO YES NO YES
Firm FE NO YES NO YES
Ind FE NO YES NO YES
Pro FE NO YES NO YES
Constant 0.586***
(0.00524)
0.701***
(0.00431)
0.00172
(0.00575)
0.0625***
(0.0157)
Observations 68,698 68,698 68,698 68,698
R−squared 0.144 0.685 0.437 0.754
Notes: t statistics in parentheses
*p<0.1
** p<0.05
*** p<0.01. These findings are consistent in the following tables.
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article, a Tobit model is used for robustness testing to avoid the impact of missing data on the
research conclusions. As shown in Table 5 (1), the regression coefficient of corporate mergers
and acquisitions is still significantly positive, and the conclusion obtained is consistent with
that in the previous text.
5.3.2 Substitution test for replacing the dependent variable. To test the reliability of the
estimation results, we use enterprises’ number of effective patents as a substitute variable for
innovation to test the merger and acquisition effect. The regression results are basically consis-
tent with the benchmark results, and the conclusion is still valid.
5.3.3 Excluding inspection of ICT-related industries. In the mergers and innovation
process, enterprises in the ICT industry have a natural demand for digital asset acquisition,
which may cause biased estimation results due to potential endogeneity. To alleviate this
impact, we exclude ICT-related industries (computer, communication, and electronic equip-
ment manufacturing industries) from the sample and rerun the regression analysis. The results
are shown in Table 5, paragraph (3), and indicate that, under the control of endogeneity issues,
the significant positive impact of corporate mergers and acquisitions on technological innova-
tion is still reliable.
Table 4. Multiple matching methods for testing the impact of corporate mergers and acquisitions on technological innovation.
Variable (1) (2) (3) (4)
1:1PSM 1:3PSM CEM EBM
Treat*Post 0.227***
(0.0253)
0.410***
(0.0243)
0.307***
(0.0406)
0.292***
(0.0250)
Controls YES YES YES YES
Year FE YES YES YES YES
Firm FE YES YES YES YES
Ind FE YES YES YES YES
Pro FE YES YES YES YES
Constant 0.246***
(0.0317)
0.0745***
(0.0161)
0.260***
(0.0361)
0.214***
(0.0239)
Observations 32,618 66,123 14,294 68,698
R−squared 0.750 0.756 0.805 0.743
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Table 5. Robustness test of the impact of corporate mergers and acquisitions on technological innovation.
Variable (1) (2) (3) (4)
Change regression method (Tobit) Replace the dependent variable Excluding ICT-related industries Add industry control variables
inno innoa inno inno
Treat*Post 0.228***
(0.0257)
0.315***
(0.0210)
0.397***
(0.0261)
0.421***
(0.0243)
Controls YES YES YES YES
Year FE YES YES YES YES
Firm FE — YES YES YES
Ind FE YES YES YES YES
Pro FE YES YES YES YES
Constant -9.436***
(0.272)
0.0844***
(0.0122)
0.0716***
(0.0177)
1.143***
(0.207)
Observations 68,698 68,698 56,938 68,698
Pseudo R
2
0.373
R−squared 0.689 0.745 0.755
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5.3.4 Increasing the testing of industry control variables. Wang et al. (2023) [47] noted
that changes in industry demand may also cause changes in factor inputs, thereby affecting
enterprise innovation. Therefore, we add variables that control for industry changes to the
benchmark regression for further estimation, including the number of enterprises in the
industry (Firmnum), the average company size in the industry (Sizeind), and the degree of
industry competition (HHI). Represented by the industry Herfindahl index, the estimated
results are still significantly positive, and the research conclusions remain robust. See Appen-
dix 1 in S1 File for the meanings of the abbreviations.
5.3.5 Parallel trend test. We draw on the approach of Beck et al. (2010) [53] and Li et al.
(2016) [49] to study multiple period DID events. The relative year information before and
after mergers and acquisitions is included in the regression, and the annual changes in the
technological innovation performance of enterprises before and after mergers and acquisitions
are estimated. Based on this, the dynamic DID model is extended to:
Innoit ¼a0þX
6
p¼ 5
gpdiditþpþX
7
c¼1
acControlitþpþYearFE þFirmFE þIndFE þProFE þεit ð9Þ
Here, diditþp¼Treatitþp∗Postit, and the year of a merger or acquisition is set as the base
period (current), with 1 for the current period and 0 for other years. Treat
it+p
represents the
relative pyear of a merger or acquisition for enterprise iin year t, with a value of 1 for that year
and 0 for other years. The meanings of the other variables are consistent with those in Eq (8).
See Appendix 1 in S1 File for the meanings of the abbreviations.
Fig 1, which shows the regression results of Eq (9), indicates that the estimated coefficients
γ
p
of the did
it+p
variable before the merger and acquisition (p�−1) are not significant. There-
fore, there is no significant difference in the level of technological innovation between the
Fig 1. Parallel trend test.
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control and treatment group samples before the merger or acquisition, satisfying the parallel
trend test. The estimated coefficients for the years in which a merger occurred and subsequent
years (p= 0,1,. . .6+)are significantly positive at least at the 5% level, indicating a relatively sta-
ble policy effect. The reason for the slight decrease in the regression coefficient two to three
years after a merger or acquisition is that the company needs a period for technological
research and innovation after completing the merger or acquisition in the same year. Alterna-
tively, a processing time of two to three years occurs between the occurrence and completion
of the merger. Fig 1 shows that the regression coefficient steadily increases in the fourth year
after a merger or acquisition, indicating that mergers and acquisitions have a significant pro-
moting effect on technological innovation.
5.3.6 Placebo test. We use the counterfactual method to design a placebo test for the
impact of mergers and acquisitions on corporate technological innovation. The wrong time
variable is set, and all merger and acquisition events are advanced by four years. The dummy
variables Treat_1, Treat_2, Treat_3, and Treat_4 are used to represent the year, two years,
three years, and four years before the actual merger and acquisition of the enterprise, respec-
tively. We observe whether mergers and acquisitions can have an impact on an enterprise’s
technological innovation during these four years [54]. If the dummy variable for new corpo-
rate mergers and acquisitions is still significant, then improvements in corporate technological
innovation capability are likely caused by other factors. In contrast, if the results for technolog-
ical innovation in the four years before mergers and acquisitions are not significant, then
mergers and acquisitions are a key factor affecting corporate technological innovation. Col-
umns (1) to (4) in Table 6 show that the estimated results for advancing mergers and acquisi-
tions by four years are not significant, which verifies the robustness of the previous results. See
Appendix 1 in S1 File for the meanings of the abbreviations.
We conduct a placebo test by randomly assigning merger and acquisition companies and
merger and acquisition years and use DIDpseudo
it instead of the core explanatory variable in Eq
(8) for the empirical testing. The experiment is repeated 1000 times, and the test results are
shown in Fig 2.Fig 2 shows that the estimated coefficients of the 1000 sampling results are all
Table 6. Placebo test.
Variable (1) (2) (3) (4)
inno inno inno inno
did_1 0.0524
(0.0344)
did_2 0.0474
(0.0362)
did_3 0.0274
(0.0389)
did_40.000709
(0.0430)
Controls YES YES YES YES
Year FE YES YES YES YES
Firm FE YES YES YES YES
Ind FE YES YES YES YES
Pro FE YES YES YES YES
Constant -5.646***
(0.615)
-5.682***
(0.613)
-5.721***
(0.613)
-5.743***
(0.614)
Observations 68,698 68,698 68,698 68,698
R−squared 0.774 0.774 0.774 0.774
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approximately 0, and the pvalue distribution is generally above 0.1. Moreover, the true esti-
mates in this article (column (4) of Table 3) are clearly outliers in the graph. The above placebo
test results show that mergers and acquisitions are the main cause of technological innovation
changes in enterprises.
5.3.7 Endogeneity testing. Controlling for the fixed effects of time, region, industry, and
enterprise can solve certain endogeneity problems. To further address endogeneity issues, we
need to identify variables that are strongly correlated with corporate merger and acquisition
behavior but are not related to corporate technological innovation.
Referring to the approach of Aiello et al. (2008) [55] and Zhou et al. (2012) [56], we quantify
the likelihood of a merger occurring for the M&A firms in an M&A, construct a probit model
to estimate the probability of a merger occurring for the M&A firms, and then estimate the fit-
ted value of its estimate as an instrumental variable for model (8) [57].
Probftreat ¼1g ¼ d0þd1lnnumiþX
7
c¼1
acControlit þYearFE þFirmFE þIndFE þProFE þεit ð10Þ
Here, lnnum
i
represents the logarithm of 1 plus the annual cumulative value of relevant arti-
cles, conferences, newspapers, etc., identified by the China National Knowledge Infrastructure
(CNKI) with "mergers and acquisitions" as the theme keyword. See Appendix 1 in S1 File for
the meanings of the abbreviations. The number of studies on mergers and acquisitions can sig-
nificantly affect the likelihood of a company engaging in mergers and acquisitions. When a
greater number of studies include mergers and acquisitions as the theme, the mergers and
acquisitions activity is greater but does not directly affect the company’s level of technological
innovation ability. Therefore, choosing this variable as an important influencing factor for a
company’s merger and acquisition behavior is reasonable. Table 7 shows that the validation
Fig 2. Placebo test.
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results obtained using the instrumental variable method indicate that the estimated coefficient
of mergers and acquisitions on the level of technological innovation is significant at the 1%
level. After introducing the instrumental variables, the estimation results once again verify the
positive incentive effect of mergers and acquisitions on technological innovation improve-
ments based on the rejection of under identification, weak instrumental variables, and over-
identification, indicating that the original conclusion is relatively robust. Therefore, the results
of this article are not affected by the endogeneity of corporate mergers and acquisitions.
5.4 Impact mechanism testing
To further examine the impact mechanism of mergers and acquisitions on corporate techno-
logical innovation, we first replace the original dependent variable, technological innovation
output, with a new dependent variable and regress it on the original core explanatory variable
[58,59]. The specific regression equation is as follows:
ml
it ¼alTreatit∗Postit þX
7
c¼1
acControlit þYearFE þFirmFE þIndFE þProFE þεl
it ð11Þ
Here, ml
itðl¼1;2;3;4Þrepresents the measurement indicators of the four types of impact
mechanism variables selected by enterprise iin year t, and the meanings of the other variables
are the same as in Eq (8). Then, all of the influencing mechanism variables are added as new
explanatory variables to the benchmark regression to test whether the different mechanism
variables can improve the level of enterprise technological innovation. See Appendix 1 in S1
File for the meanings of the abbreviations. The specific regression equation is as follows:
innoit ¼a0
0þa0
1Treatit∗Postit þX
4
l¼1
glml
it þX
7
c¼1
acControlit þYearFE þFirmFE þIndFE þProFE þεit ð12Þ
Table 7. Endogeneity test results.
Variable (1) (2) (3) (4)
Panel Tool Variables 2SLS
inno inno inno inno
Treat*Post 0.539***
(0.0118)
0.435***
(0.0235)
0.503***
(0.0765)
0.495***
(0.0771)
Controls YES YES YES YES
Year FE NO YES NO YES
Firm FE NO YES NO YES
Ind FE NO YES NO YES
Pro FE NO YES NO YES
F Value 5235.10 390.54 726.50 379.57
Kleibergen−Paap rkLM statistic — — 1087.724
[0.0000]
1210.106
[0.0000]
Kleibergen−Paap rkWald F statistic — — 726.504
{19.93}
1489.946
{16.38}
Hansen J statistic — — 9.1950 0.0000
Observations 68,698 68,698 68,698 68,698
R−squared 0.433 0.752 0.430 0.460
Note: () is the standard deviation of the coefficient, [] is the corresponding statistical P value, {} is the critical value of a 10% deviation in Stock−Yogo, and the Hansen J
statistic = 0 indicates that the identification is accurate; that is, the number of instrumental variables equals the number of endogenous variables.
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5.4.1 Production efficiency effect. This section verifies whether mergers and acquisitions
promote enterprises’ level of technological innovation by improving their production effi-
ciency. We draw on the approach of Wang (2023) [60] and calculate total factor productivity
to represent the production efficiency of enterprises for mechanism testing. The regression
results are shown in column (1) of Table 8. The estimated coefficient of the core explanatory
variable Treat
it
*Post
it
is 1.442 and significant, indicating that mergers and acquisitions can
improve enterprise total factor productivity. Moreover, based on the estimation results in col-
umn (5) of Table 8, the estimated coefficient of total factor productivity is 0.0324, which is sig-
nificantly positive at the 1% level, indicating that improving total factor productivity can
promote technological innovation in enterprises. Therefore, hypothesis 2 holds.
5.4.2 Digital knowledge effect. In this section, we verify whether mergers and acquisi-
tions improve an enterprise’s technological innovation level through an increase in its digital
knowledge base. We refer to the approach of Wu et al. (2021) [61] and Lim et al. (2020) [62]
and use digital transformation and intangible assets to represent enterprises’ basic digital
knowledge levels. The data are obtained from the annual reports of various listed companies
and the CSMAR database, and the types of data are denoted as Digit and ias. The following
digital transformation indicators are obtained. First, the annual reports of Chinese A-share
listed companies are collected and organized by a Python crawler, and all content was
extracted from the data pool used for feature word screening. Second, classical literature, pol-
icy documents and research reports with the theme of digital features are referred to, and spe-
cific keywords about digital transformation are summarized, mainly including cloud
computing technology, big data technology, artificial intelligence technology, blockchain tech-
nology and feature words related to the use of digital technology in practice. Third, the word
frequency of the feature words is counted to obtain the total word frequency, and the natural
logarithm is taken by adding 1 to the total word frequency as a measure of digital transforma-
tion; intangible assets are measured by adding 1 to the natural logarithm of the ratio of intangi-
ble assets to total assets. The estimated results in columns (2), (3), and (5) of Table 8 lead to the
Table 8. Impact mechanism test results.
Variable (1) (2) (3) (4) (5)
TFP_LP Digit ias lerner inno
Treat*Post 1.442***
(0.0561)
0.473***
(0.0239)
0.295***
(0.0484)
0.0121***
(0.00371)
0.306***
(0.0250)
TFP_LP 0.0324***
(0.00247)
Digit 0.130***
(0.00935)
ias 0.0206***
(0.00454)
lerner 0.123*
(0.0720)
Controls YES YES YES YES YES
Year FE YES YES YES YES YES
Firm FE YES YES YES YES YES
Ind FE YES YES YES YES YES
Pro FE YES YES YES YES YES
Constant 1.083***
(0.0294)
0.0250
(0.0153)
0.00184
(0.0271)
-0.0299***
(0.00369)
0.0279*
(0.0160)
Observations 68,698 68,698 68,698 68,698 68,698
R−Squared 0.836 0.833 0.978 0.688 0.761
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conclusion that corporate mergers and acquisitions can enrich the digital knowledge stock of
enterprises by enhancing their digital transformation and intangible assets, thereby positively
affecting improvements in technological innovation. Therefore, hypothesis 3 proposed in this
article is validated.
5.4.3 Market power effect. We refer to the approach of Peress (2010) [63] and Datta et al.
(2011) [64] and use the Lerner index (lerner) to measure a company’s market power, calcu-
lated as (operating revenues—costs)/operating revenues. The regression results in columns (4)
and (5) of Table 8 indicate that mergers and acquisitions can significantly improve a com-
pany’s Lerner index, which also significantly increases the number of patent applications.
Mergers and acquisitions are observed to promote technological innovation by enhancing a
company’s market power. This conclusion is consistent with the findings of Ringel et al.
(2017) [65]. Therefore, hypothesis 4 holds.
5.5 Heterogeneity analysis
At this point, we have tested and analyzed how corporate mergers and acquisitions can signifi-
cantly enhance technological innovation and how to enhance technological innovation. How-
ever, are the results of mergers and acquisitions influenced by factors such as the type of
merger and acquisition and the nature of the acquiring company? Therefore, in this section,
we analyze the impact of mergers and acquisitions using different corporate characteristics on
technological innovation from two perspectives: the heterogeneity of enterprise transactions
and the heterogeneity of enterprise ownership.
5.5.1 Heterogeneity of enterprise transactions. We mainly explore transaction heteroge-
neity from two perspectives: whether cross-border mergers and acquisitions occur and the
number of merger and acquisition transactions. First, merger and acquisition events are
divided into domestic and cross-border mergers and acquisitions for sample regression. The
regression results are shown in columns (1) and (2) of Table 9. The results indicate that both
domestic and cross-border mergers and acquisitions can promote enterprise technological
innovation to a certain extent. This discovery is highly in line with economic intuition. The
Table 9. Heterogeneity analysis.
Variable (1) (2) (3) (4) (5) (6)
Transaction heterogeneity Enterprise heterogeneity
Domestic
M&A
Cross-border
M&A
Large
amount
Small
amount
State-owned
enterprise
Non-state-owned
enterprises
inno inno inno inno inno inno
Treat*Post 0.277***
(9.67)
0.263*
(1.69)
0.274***
(0.0481)
0.330***
(0.0496)
0.0599
(0.0496)
0.452***
(0.0284)
Controls YES YES YES YES YES YES
Year FE YES YES YES YES YES YES
Firm FE YES YES YES YES YES YES
Ind FE YES YES YES YES YES YES
Pro FE YES YES YES YES YES YES
Constant 0.254***
(6.93)
0.552***
(3.60)
0.204***
(0.0699)
0.169***
(0.0478)
-4.733***
(1.544)
0.0124
(0.0120)
Observations 24,570 910 10,402 7,168 14,042 54,515
R−squared 0.742 0.804 0.748 0.726 0.800 0.745
Intergroup coefficient test for Treat*Post [P
value]
-0.014
[0.476]
0.056**
[0.046]
0.393***
[0.000]
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acquiring and target companies involved in domestic mergers and acquisitions have similar
cultural, business environment, and business models. Therefore, mergers and acquisitions can
be integrated at lower costs, allowing synergies to be realized faster and technological innova-
tion to be promoted. Cross-border mergers and acquisitions can provide more diverse merger
and acquisition resources for Chinese companies to absorb many high-quality foreign compa-
nies, thereby generating greater synergies and technology spillover effects.
Second, in this article, we use the median transaction amount as the standard for dividing
enterprises into large transaction mergers and acquisitions and small transaction mergers and
acquisitions and regressing them separately. The regression results in columns (3) and (4) of
Table 9 show that both large and small transaction mergers and acquisitions can promote
enterprise technological innovation. Moreover, the intergroup coefficient difference test
results for the core explanatory variable Treat*Post also indicate that transaction heterogeneity
is significant. This result is attributed to the fact that acquirers, whether they acquire large
firms or small firms, are able to acquire new knowledge from the acquired firms and rational-
ize the use of this knowledge resource for technological innovation.
5.5.2 Heterogeneity of enterprise ownership. We mainly examine the impact of corpo-
rate mergers and acquisitions on technological innovation from the perspective of the nature
of ownership of M&A firms. The regression results are shown in columns (5) and (6) of
Table 9. The results indicate that when an M&A enterprise is state-owned, its merger and
acquisition behavior does not significantly promote its innovation output. However, when an
M&A enterprise is non-state-owned, mergers and acquisitions can significantly promote its
technological innovation. Therefore, we believe that the reason for this result may be that
state-owned enterprises have relatively cumbersome organizational structures and overall low
efficiency, resulting in a slow enterprise technological innovation process. In contrast, non-
state-owned enterprises are self-reliant on profits and losses and are more eager to gain market
opportunities and advantages by accelerating technological innovation to maximize corporate
interests.
6. Discussion
The current research results are quite rich, and this paper builds on this foundation and fur-
ther enriches the body of knowledge by focusing on Chinese listed companies.
First, at present, academics have conducted many theoretical and empirical studies on the
relationship between mergers and acquisitions and technological innovation, but the conclu-
sions are significantly divergent. Taking Chinese A-share listed companies as the research
object, this paper finds that corporate mergers and acquisitions have a positive effect on tech-
nological innovation, which still holds after a parallel trend test and a placebo test, and further
verifies that corporate mergers and acquisitions are the main driving force of technological
innovation, which supports the conclusions of the studies by Wu et al. (2021) [25] and Chen
et al. (2024) [66]. Additionally, this paper finds that the enhancement effect of mergers and
acquisitions on technological innovation persists in the long term and becomes increasingly
obvious as the postmerger integration process advances. As shown in Fig 2,γ
6
= 0.6477 is sig-
nificant at the 1% level, indicating that six years after a merger and acquisition occurs, it can
still significantly enhance the technological innovation of the firm, and the economic signifi-
cance is high.
Second, current scholars focusing on high-tech enterprises and family-owned enterprises
believe that mergers and acquisitions can promote technological innovation, which is mainly
realized through saving transaction costs, improving enterprise productivity [66], reducing
R&D risks, and improving R&D efficiency (Ye et al., 2024) [67]. This paper verifies that
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improving productivity is an important path, which supports the current research. Addition-
ally, this paper finds that mergers and acquisitions can also promote technological innovation
through two paths, specifically, enriching the level of digital knowledge and enhancing market
power, of which the enhanced effect of enterprise digital transformation has the strongest
explanatory power, suggesting that it is an important pathway for enhancing technological
innovation. This further reveals the mechanism by which mergers and acquisitions promote
technological innovation.
Third, current research suggests that firms with high productivity [8], strong resource reor-
ganization capabilities [54], and few financing constraints [50] are more suitable for mergers
and acquisitions. This study contributes by showing that when a merger and acquisition firm
is a non-state-owned enterprise, its mergers and acquisitions have a significant positive effect
on technological innovation, and the mergers and acquisitions of state-owned enterprises do
not have a significant effect on technological innovation. Domestic mergers and acquisitions
play a more pronounced role in promoting technological innovation than cross-border merg-
ers and acquisitions, and small-dollar mergers and acquisitions play a more pronounced role
in promoting technological innovation than large-dollar mergers and acquisitions. This study
further reveals the characteristics of enterprises that are more suitable for promoting techno-
logical innovation through mergers and acquisitions from the perspectives of enterprise own-
ership, merger and acquisition type and merger and acquisition intensity.
Nonetheless, this study has some limitations. First, this study focuses on data from listed
companies in China and attempts to consider nonlisted companies in the subsequent period.
Second, this study observes the acquiring firms in merger and acquisition transactions, and
the traits of the acquired firms, as with the other participants in merger and acquisition trans-
actions, may also have an impact on technological innovation. Third, the positive impact of
M&A on technological innovation in enterprises has been demonstrated in many cases around
the world. For example, Qualcomm in the United States successfully acquired Nuvia, a chip
architecture design company, and utilized Nuvia’s advanced design concepts and technological
advantages to build a chip that surpassed the performance of Apple’s A17Pro and Snapdragon
8gen3 in 2023; this greatly enhanced the technological innovation level of the enterprise. As an
innovation-driven, research and development-based healthcare multinational, Roche Switzer-
land broadened its molecular diagnostics portfolio through the acquisitions of state-of-the-art
U.S.-based bioengineering companies Genentech and GeneMark Diagnostics as a means of
driving technological innovation and product development. Through the acquisition of Viv
Labs and Harman International Industries, South Korea’s Samsung has achieved technological
breakthroughs in intelligent voice interaction and autonomous driving, completing the indus-
try chain from software to hardware. However, there are significant differences in M&A
behaviors and external conditions in different countries, specifically in terms of economic
level, cultural variability, and political influence. Therefore, the impact of M&A on the techno-
logical innovation of enterprises is bound to vary among countries. Accordingly, future
research can be carried out in the following three ways. First, nonlisted companies can be used
as the research object in the subsequent period to comprehensively understand the impact of
mergers and acquisitions on technological innovation in Chinese enterprises. Second, the
acquired enterprises can be used as the research object to further enrich the body of knowledge
on the impact of mergers and acquisitions on technological innovation. Third, in the future, it
will be necessary to consider enterprises from countries other than China as research objects
and to further compare and analyze the different mechanisms and paths of the influence of
M&A on technological innovation among different countries.
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7. Conclusions and recommendations
7.1 Conclusions
This paper constructs a mathematical model, uses panel data on China’s A-share listed compa-
nies in Shanghai and Shenzhen from 2007 to 2020, constructs a theoretical framework for
mergers and acquisitions to promote technological innovation, utilizes the Difference-in-Dif-
ferences method to empirically test the impact of mergers and acquisitions on technological
innovation, and further examines the path of the role of the two and the impact of heterogene-
ity. The research presented in this paper finds the following.
First, corporate mergers and acquisitions can significantly promote technological innova-
tion in enterprises. After we change the regression method, explain the dependent variable,
remove ICT-related industries, and add industry control variables for robustness testing, this
conclusion still holds. The analysis of the dynamic effects shows that corporate mergers and
acquisitions have long-term and sustained effects on enhancing technological innovation. The
regression coefficient slightly decreases two to three years after a merger because of the com-
pany’s need for technology absorption, research and development, and innovation after com-
pleting a merger in the same year or the existence of a two- to three-year processing time
between the occurrence and completion of a merger. In the fourth year after a merger and
acquisition transaction, the promoting effect on technological innovation steadily increased
annually, indicating that corporate mergers and acquisitions have a significant and long-term
promoting effect on technological innovation.
Second, the production efficiency effect, knowledge effect, and market power effect are the
three important mechanisms through which enterprise mergers and acquisitions enhance
technological innovation. Improvements in production efficiency indicate a decrease in enter-
prises’ marginal costs, and such improvements generated by mergers and acquisitions mainly
occupy a market advantage position from the cost side. Given the gradual integration of intan-
gible assets, such as digital technology knowledge, management experience, and marketing
networks, the knowledge stock of merger and acquisition enterprises increases, which helps
improve their resource allocation efficiency and generate synergistic effects. Enterprises reduce
the number of market competitors through mergers and acquisitions, improve their market
competitiveness, and expand their market power. Further empirical results indicate that merg-
ers and acquisitions can promote technological innovation by improving enterprises’ total fac-
tor productivity, enriching their digital knowledge, and enhancing their market power.
Third, the impact of mergers and acquisitions on technological innovation exhibits hetero-
geneity due to the nature of corporate ownership. Compared to state-owned enterprises, non-
state-owned enterprises have a more significant effect on achieving technological innovation
through mergers and acquisitions. Regarding merger and acquisition transaction types,
whether domestic or cross-border, large- or small-scale mergers and acquisitions can enhance
a company’s technological innovation. When mergers and acquisitions meet the requirements
of domestic mergers and acquisitions and small transaction amounts and when the main
merging enterprise is a non-state-owned enterprise, the technological innovation enhance-
ment effect of enterprise mergers and acquisitions becomes more significant.
7.2 Policy recommendations
Based on the above findings, the following recommendations can be made.
First, the government should provide a strong policy environment and financing support
for mergers and acquisitions to provide a source of power for enterprise technological innova-
tion. Banks and other financial institutions should be guided to broaden the financing
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channels for mergers and acquisitions and provide governmental financing guarantees for
enterprises to carry out mergers and acquisitions. Additionally, appropriate policy subsidies
and tax exemptions and reductions for mergers and acquisitions should be provided to mini-
mize the risks and costs faced by enterprises in mergers and acquisitions. Enterprises should
make full use of the government’s supportive policies to support mergers and acquisitions,
focus on R&D innovation after mergers and acquisitions, increase R&D investment, cultivate
professional and technical talent, and truly transform the technological resources acquired
through mergers and acquisitions into the enterprise’s own technological strength. For exam-
ple, in 2014, the State Council of China issued the Opinions on Further Optimizing the Market
Environment for Corporate Mergers and Restructuring, which explicitly encourages financial
institutions to carry out mergers and restructuring of financing for businesses; additionally,
various types of financial investment entities can participate in mergers and restructuring by
setting up equity investment funds, venture capital funds, industrial investment funds, merger
and acquisition funds, etc. The use of diversified fundraising channels can help reduce the
financial constraints on merging and acquiring enterprises, safeguard further R&D investment
by enterprises, and thus promote their innovative activities. According to CSMAR database
statistics, in 2014, the number of M&A cases announced by A-share listed Chinese enterprises
in Shanghai and Shenzhen was 5,689, and the number of patent applications by enterprises
was 16,955. After the opinion was put forward, the number of M&A cases reached 7,945 in
2015, and the number of patent applications was 26,766, showing growth rates of 40% and
58%, respectively.
Second, the government should build a digital resource platform; promote the convergence
of innovative resources; accelerate the efficient circulation of data, knowledge and other factors
of production; strengthen the joint cultivation of schools and enterprises; expand the channels
for attracting talent from home and abroad; increase the introduction and training of technical
talent; open up the chain of talent from enterprises, universities and scientific research insti-
tutes; establish industry-academia-research cooperation teams; gather resources from indus-
try-academia-research; systematically promote the technological research of key areas; give
enterprises priority access to new products; and utilize their own influence and social credibil-
ity to promote quality products. Enterprises should absorb talent around the core technology
after the completion of mergers and acquisitions, promote the process of technology absorp-
tion and reinnovation, accelerate the transformation of core technology, emphasize the devel-
opment of new products, accelerate the promotion of new products, create unique brands
belonging to the enterprise, and enhance the competitiveness of the market. For example,
Shanxi Province in China, with its rich resources of universities and research institutes, has
been steadily moving forward in recent years in terms of the intensity of R&D investment in
general and by universities, the number of geographic contracts for technology output in the
technology market, the amount of cooperation between enterprises and universities and
research institutes, and the number of papers jointly published by enterprises and universities
and research institutes. These efforts have laid a solid foundation of science and technology
and industrial innovation for the cultivation and development of high-quality products.
Regarding enterprises, Tencent successively acquired Riot Games, Epic Games and Supercell
and then quickly absorbed resources and launched game products such as League of Legends,
Clash of Clans, and Clash Royale; it thereby smoothly entered the game industry and seized
the market position, and it has now become the world’s largest game publisher.
Third, the government should increase the promotion of technological mergers and acqui-
sitions by enterprises, focus on the selection of targets for mergers and acquisitions by enter-
prises, and encourage enterprises to achieve technological innovation through technological
mergers and acquisitions. It should implement merger and acquisition encouragement policies
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Research on the impact of enterprise mergers and acquisitions on technological innovation
PLOS ONE | https://doi.org/10.1371/journal.pone.0309569 November 27, 2024 20 / 24
in a prudent manner, avoid concentrating too many merger and acquisition resources on large
enterprises and state-owned enterprises, and provide a level playing field for the industry; in
particular, it should guide small and non-state-owned enterprises to cultivate their own core
competencies, which are symbolized by their technologies and patents. Enterprises should
select M&A objects by strategically considering technological innovation and the actual situa-
tion. In particular, enterprises with technology as the main driver of profit should give full play
to their absolute advantages and should pursue merges and acquisitions of other technology
enterprises to combine strengths; after completing a merger or acquisition, the company
should immediately begin the integration and utilization of innovative resources, accelerate
the process of technological innovation, and ultimately achieve innovation in key technologi-
cal fields. For example, Huawei Technologies Co., Ltd. acquired Caliopa, a silicon photonics
technology developer in the data communication and telecom markets, and then quickly
absorbed the core technology and innovation resources of the target enterprise and leveraged
new-generation information technologies such as big data, the Internet of Things, and block-
chain to enhance its independent innovation capability, make breakthroughs in core technolo-
gies, and solve bottleneck problems. Finally, Huawei successfully researched and developed its
own 5G base station core chip in September 2023, released the Kirin 9000S processor, achieved
the localization of the 5G chip, and thereby occupied a leading position in global 5G
technology.
Supporting information
S1 File. Appendix 1.
(ZIP)
S2 File. Original data.
(XLSX)
Author Contributions
Conceptualization: Yujiao Bai, Hao Zhang.
Formal analysis: Yujiao Bai, Hao Zhang.
Methodology: Yujiao Bai, Hao Zhang.
Software: Yujiao Bai.
Writing – original draft: Yujiao Bai.
Writing – review & editing: Yujiao Bai, Hao Zhang.
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