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

Brózda-Wilamek, Dominika

doi:10.2478/ijme-2023-0021

Figures & Tables

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.

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

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
Place in the ranking	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
Source country	Target country	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
Place in the ranking	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
	Sánchez-Díez et al. [2016]	1999–2012	Three weighted-directed sectoral CBM&A networks for the energy, finance, and telecommunications sectors	Countries	Value of CBM&A transactions
	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
	Dueñas et al. [2017]*	1995–2010	The weighted-directed CBM&As network	Countries	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
	Galaso and Sánchez-Díez [2020]	1999–2013	The weighted-directed CBM&As network	Countries	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
Place in the ranking	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

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

Figures & Tables

Figure 1.

Figure 2.

Figure 3.

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

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

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

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

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

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

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