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The global cross-border mergers and acquisitions network between 1990 and 2021

Dominika Brózda-Wilamek
Dominika Brózda-Wilamek
   | 31 déc. 2023
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Article Category: Empirical Paper
Publié en ligne: 31 déc. 2023
Pages: 333 - 348
Reçu: 14 sept. 2022
Accepté: 14 juil. 2023
DOI: https://doi.org/10.2478/ijme-2023-0021
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© 2023 Dominika Brózda-Wilamek, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Number of global M&A transactions per year. Source: Own calculations. CBM&A, cross-border mergers and acquisitions; M&A, mergers and acquisitions.
Number of global M&A transactions per year. Source: Own calculations. CBM&A, cross-border mergers and acquisitions; M&A, mergers and acquisitions.

Figure 2.

The topological characteristics of the global CBM&A network from 1990 to 2021. Source: Own calculations. CBM&A, cross-border mergers and acquisitions
The topological characteristics of the global CBM&A network from 1990 to 2021. Source: Own calculations. CBM&A, cross-border mergers and acquisitions

Figure 3.

The global CBM&A network in 2021. *Nodes are represented by countries, and the tie strength is reflected by the number of transactions. The Fruchterman-Reingold algorithm is used to visualize the network. The size of the nodes replicates the level of the degree indicator. Source: Own calculations in Gephi 0.9.2. CBM&A, cross-border mergers and acquisitions.
The global CBM&A network in 2021. *Nodes are represented by countries, and the tie strength is reflected by the number of transactions. The Fruchterman-Reingold algorithm is used to visualize the network. The size of the nodes replicates the level of the degree indicator. Source: Own calculations in Gephi 0.9.2. CBM&A, cross-border mergers and acquisitions.

The ranking of the top 10 countries for different centrality measurements, 1990–2021 (the node representing USA was removed from the network)

Place in the ranking Average place
1990–1993 1994–1997 1998–2001 2002–2005 2006–2009 2010–2013 2014–2017 2018–2021 1990–2021
Degree centrality
1 GBR GBR GBR GBR GBR GBR GBR GBR GBR
2 FRA DEU DEU DEU DEU DEU DEU DEU DEU
3 DEU FRA FRA FRA FRA FRA FRA FRA FRA
4 NLD NLD NLD HKG AUS CHN CHN NLD NLD
5 ITA AUS SWE NLD NLD AUS HKG ESP SWE
6 SWE CAN CHE CHN CHN RUS NLD SWE AUS
7 CHE SWE ESP AUS SWE HKG SGP CHN HKG
8 ESP CHE ITA SWE HKG CAN ESP SGP CHN
9 JPN ITA AUS SGP CAN NLD AUS AUS CAN
10 AUS HKG BEL CAN CHE SGP CAN HKG ESP
Betweenness centrality
1 GBR GBR GBR GBR GBR GBR GBR GBR GBR
2 FRA DEU FRA CAN CAN CAN FRA FRA FRA
3 DEU FRA CAN DEU AUS AUS CAN DEU CAN
4 CAN CAN DEU FRA FRA FRA DEU CAN DEU
5 HKG AUS ESP AUS DEU RUS AUS ESP AUS
6 ESP ZAF AUS ESP RUS DEU ESP AUS ESP
7 ITA NLD CHE NLD ESP ESP NLD NLD NLD
8 AUS SGP RUS HKG NLD CHN RUS SGP RUS
9 CHE ITA ZAF CHE ITA SGP HKG ZAF HKG
10 NLD ESP NLD IND IND HKG ITA HKG ITA
Eigenvector centrality
1 FRA DEU DEU DEU DEU DEU DEU GBR DEU
2 DEU FRA FRA GBR GBR GBR GBR DEU GBR
3 GBR GBR GBR FRA AUS AUS FRA ESP FRA
4 ITA ITA ESP CHN FRA FRA ESP NLD ESP
5 ESP NLD NLD ESP CHN CHN ITA FRA ITA
6 NLD ESP ITA AUS ESP ESP NLD ITA NLD
7 CHE CHE CHE ITA ITA CAN CHN AUS AUS
8 BEL AUS AUS NLD CAN RUS AUS BEL CHE
9 SWE POL SWE CHE SWE NLD CAN IRL CHN
10 AUS AUT BEL SWE RUS ITA CHE SWE SWE

The main investment destinations of the top 10 countries with the highest average out-degree value, 1990–2021

Source country Target country Average number of CBM&A transactions
1990–1993 1994–1997 1998–2001 2002–2005 2006–2009 2010–2013 2014–2017 2018–2021 1990–2021
USA GBR 123 211 309 193 244 246 318 335 247
CAN 84 174 264 187 271 227 272 307 223
DEU 47 118 113 115 115 98 102 98 101
AUS 23 52 83 49 78 88 90 102 70
FRA 45 79 87 64 68 58 74 74 68
GBR USA 113 152 229 132 176 141 185 213 168
DEU 35 54 70 54 71 50 60 62 57
FRA 47 60 69 48 41 35 48 58 51
AUS 17 23 46 32 56 38 37 41 36
NLD 25 30 37 23 25 21 42 59 33
CAN USA 76 160 257 230 275 263 299 368 241
GBR 13 24 23 20 25 27 35 44 26
AUS 3 10 13 13 21 23 18 24 16
MEX 1 5 4 11 31 23 9 5 11
FRA 5 11 10 7 8 9 10 10 9
DEU USA 20 29 90 36 53 45 68 54 49
GBR 23 25 53 31 39 26 39 39 34
FRA 28 34 47 29 31 27 30 33 32
CHE 15 24 50 24 41 26 28 28 29
AUT 12 21 41 20 29 19 24 24 24
FRA USA 24 24 64 37 51 42 59 58 45
DEU 27 41 38 27 32 31 42 41 35
GBR 29 23 46 23 36 34 43 45 35
ESP 22 15 29 21 31 24 44 49 29
ITA 27 24 29 15 23 20 30 38 26
NLD CHN 4 26 66 102 132 154 186 111 97
USA 8 8 13 8 15 17 25 14 13
AUS 4 5 8 9 20 27 14 17 13
SGP 4 5 11 13 11 9 17 15 11
GBR 10 7 5 3 8 7 15 12 8
JPN FIN 12 26 35 22 31 19 26 48 27
NOR 9 9 29 23 36 37 34 40 27
USA 8 10 27 15 26 22 27 38 21
DNK 10 9 22 20 26 25 27 31 21
GBR 12 8 19 15 23 14 17 29 17
HKG USA 90 36 46 27 43 59 70 80 56
CHN 1 5 7 14 13 24 17 14 12
GBR 16 7 7 8 8 14 22 14 12
VNM 0 1 0 0 4 15 15 18 6
IND 1 1 5 3 6 18 18 16 9
SWE DEU 17 40 44 28 37 30 35 37 33
USA 14 22 44 13 29 21 25 31 25
GBR 16 20 34 21 30 23 22 29 24
BEL 11 14 23 19 25 16 19 21 18
FRA 9 20 29 15 15 13 18 14 17
CHE DEU 17 29 34 34 54 40 50 44 38
USA 12 20 30 19 36 30 38 36 28
FRA 16 14 15 12 15 11 16 20 15
GBR 8 8 14 9 17 12 11 18 12
ITA 6 6 14 5 11 11 13 13 10

Average percentage shares of individual economic sectors in the global CBM&A network, 1990–2021

Economic sector 1990–1993 1994–1997 1998–2001 2002–2005 2006–2009 2010–2013 2014–2017 2018–2021 1990–2021
TRBC* economic sector of the acquirer
Financial 17% 17% 19% 25% 29% 32% 36% 37% 26.4%
Industrial 22% 23% 22% 19% 18% 18% 17% 17% 19.4%
Basic materials 18% 17% 17% 14% 12% 12% 12% 10% 14.0%
Technology 16% 14% 11% 11% 11% 10% 8% 7% 10.8%
Consumer cyclicals 6% 8% 12% 12% 11% 10% 11% 14% 10.4%
Healthcare 9% 8% 6% 7% 5% 6% 5% 5% 6.4%
Consumer non-cyclicals 5% 4% 4% 5% 5% 5% 5% 6% 5.0%
Energy 4% 4% 3% 4% 4% 4% 3% 2% 3.5%
Telecommunications services 1% 2% 3% 3% 2% 1% 1% 1% 1.9%
Utilities 1% 1% 2% 2% 2% 1% 1% 1% 1.6%
TRBC* economic sector of the target
Industrial 25% 25% 27% 22% 22% 22% 21% 21% 23.2%
Financial 20% 20% 17% 16% 16% 16% 16% 14% 17.0%
Technology 11% 11% 12% 13% 14% 14% 16% 14% 13.1%
Consumer cyclicals 7% 7% 12% 13% 13% 12% 15% 19% 12.2%
Basic materials 15% 15% 11% 12% 12% 13% 9% 8% 11.8%
Consumer non-cyclicals 10% 9% 8% 8% 7% 8% 9% 7% 8.2%
Healthcare 6% 5% 5% 6% 6% 6% 7% 9% 6.3%
Energy 4% 4% 3% 4% 5% 6% 4% 3% 4.3%
Utilities 1% 2% 3% 3% 2% 2% 1% 2% 2.0%
Telecommunications services 1% 1% 2% 2% 2% 2% 2% 3% 1.9%

The ranking of the top 10 countries for different degree centrality measurements, 1990–2021

Place in the ranking Average place
1990–1993 1994–1997 1998–2001 2002–2005 2006–2009 2010–2013 2014–2017 2018–2021 1990–2021
Degree centrality
1 USA USA USA USA USA USA USA USA USA
2 GBR GBR GBR GBR GBR GBR GBR GBR GBR
3 FRA DEU DEU DEU DEU CAN DEU CAN DEU
4 DEU FRA FRA CAN CAN DEU CAN DEU CAN
5 CAN CAN CAN FRA FRA FRA FRA FRA FRA
6 JPN NLD NLD AUS AUS AUS CHN NLD NLD
7 NLD AUS SWE CHN CHN CHN HKG AUS AUS
8 ITA CHE AUS NLD NLD NLD NLD ESP SWE
9 SWE SWE CHE HKG SWE HKG AUS SWE CHN
10 CHE ITA ITA SWE HKG RUS ESP CHN HKG
In-degree centrality
1 USA USA USA USA USA USA USA USA USA
2 GBR GBR GBR GBR GBR GBR GBR GBR GBR
3 FRA DEU DEU DEU DEU DEU DEU DEU DEU
4 DEU FRA FRA CHN CAN CAN CAN CAN CAN
5 ITA CAN CAN CAN CHN CHN CHN ESP FRA
6 CAN AUS AUS FRA AUS AUS FRA FRA AUS
7 ESP ITA NLD AUS FRA RUS ESP NLD CHN
8 NLD NLD ESP HKG IND FRA AUS AUS ESP
9 AUS ESP ITA ESP RUS IND ITA ITA NLD
10 SWE SWE SWE SWE SWE BRA NLD CHN ITA
Out-degree centrality
1 USA USA USA USA USA USA USA USA USA
2 GBR GBR GBR GBR GBR GBR GBR GBR GBR
3 FRA CAN DEU CAN CAN CAN CAN CAN CAN
4 JPN DEU FRA DEU DEU DEU FRA FRA DEU
5 DEU FRA CAN FRA FRA FRA DEU DEU FRA
6 CAN NLD NLD NLD NLD HKG HKG JPN NLD
7 NLD CHE SWE HKG AUS JPN JPN SWE JPN
8 CHE SWE CHE SGP HKG NLD CHN NLD HKG
9 SWE JPN BEL SWE SWE CYP SGP SGP SWE
10 ITA AUS JPN AUS CHE SGP NLD HKG CHE

The synthesis of SNA parameters used in selected research concerning M&A transactions

Analysis level Authors of research Period Network type Nodes Edges Network indicators
Macro Sánchez-Díez et al. [2016] 1999–2012 The overall weighted-directed CBM&A network in Latin America Countries Value of CBM&A transactions Density, total degree, centrality, eigenvector, out-degree, in-degree
Three weighted-directed sectoral CBM&A networks for the energy, finance, and telecommunications sectors
Dueñas et al. [2017]* 1995–2010 The binary-directed CBM&As network Countries Number of CBM&A transactions Density, reciprocity, degree, average nearest-neighbor degree, clustering coefficient
The weighted-directed CBM&As network Value of CBM&A transactions
Galaso and Sánchez-Díez [2020] 1999–2013 The binary-directed CBM&As network Countries Number of CBM&A transactions Density, reciprocity, core-periphery model, in-degree, out-degree, eigenvector
The weighted-directed CBM&As network Value of CBM&A transactions
Meso Brózda-Wilamek [2020] 2000–2017 The directed Chinese CBM&As network Industry sectors Number of CBM&A transactions Degree, in-degree, out-degree, closeness, eigenvector
Brózda-Wilamek [2021] 2010–2020 Three separate directed networks for Hungarian, Czech, and Polish CBM&A transactions Business sector Number of CBM&A transactions Degree, in-degree, out-degree, betweenness, eigenvector
Waßenhoven et al. [2021] 1995–2018 The industry-directed network of M&A data Industry sectors where at least one sector is related to the bioeconomy Number of M&A transactions Density, average geodesic distance, reciprocity, degree, out-degree, in-degree, betweenness
Micro Guo et al. [2019] 2000–2017 The directed Chinese company M&A network Chinese companies Value of M&A transactions Out-degree, in-degree, betweenness, closeness, PageRank

The ranking of the top 10 countries in terms of the betweenness and eigenvector centrality, 1990–2021

Place in the ranking Average place
1990–1993 1994–1997 1998–2001 2002–2005 2006–2009 2010–2013 2014–2017 2018–2021 1990–2021
Betweenness centrality
1 USA USA USA USA USA USA USA USA USA
2 GBR GBR GBR GBR GBR GBR GBR GBR GBR
3 FRA FRA FRA CAN CAN CAN FRA FRA FRA
4 DEU DEU CAN DEU AUS AUS CAN CAN CAN
5 HKG CAN RUS FRA FRA RUS DEU AUS DEU
6 CAN ZAF DEU AUS DEU FRA HKG DEU AUS
7 ITA SGP AUS ESP RUS DEU AUS ESP RUS
8 AUS AUS ZAF IND NLD ESP SGP NLD ESP
9 NLD ITA ESP RUS ITA CHN CHN SGP NLD
10 ESP NLD IND CHE ESP ZAF ZAF HKG ZAF
Eigenvector centrality
1 USA USA USA USA USA USA USA USA USA
2 GBR GBR GBR GBR GBR GBR GBR GBR GBR
3 FRA DEU CAN CAN CAN CAN CAN CAN CAN
4 DEU CAN DEU DEU DEU DEU DEU DEU DEU
5 CAN FRA FRA FRA AUS AUS FRA AUS FRA
6 ITA AUS AUS AUS CHN FRA AUS FRA AUS
7 ESP ITA NLD CHN FRA BRA ESP ESP NLD
8 NLD NLD ITA NLD IND IND NLD NLD ESP
9 AUS ESP ESP ESP NLD CHN ITA ITA ITA
10 SWE CHE BRA IND ESP ESP IND IND CHN
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