Understanding Trends, Patterns, and Dynamics in Global Company Acquisitions: A Network Perspective

Abstract

Studying acquisitions offers invaluable insights into startup trends, aiding informed investment decisions for businesses. However, the scarcity of studies in this domain prompts our focus on shedding light in this area. Employing Crunchbase data, our study delves into the global network of company acquisitions using diverse network analysis techniques. Our findings unveil an acquisition network characterized by a primarily sparse structure comprising localized dense connections. We reveal a prevalent tendency among organizations to acquire companies within their own country and industry, as well as those within the same age bracket. Furthermore, we show that the country, region, city, and category of the companies can affect the formation of acquisition relationships between them. Our temporal analysis indicates a growth in the number of weakly connected components of the network over time, accompanied by a trend toward a sparser network. Through centrality metrics computation in the cross-city acquisition network, we identify New York, London, and San Francisco as pivotal and central hubs in the global economic landscape. Finally, we show that the United States, United Kingdom, and Germany are predominant countries in international acquisitions. The insights from our research assist policymakers in crafting better regulations to foster global economic growth, and aid businesses in deciding which startups to acquire and which markets to target for expansion.

Figures (16)

• Figure 1: Entity-relationship diagram of the data, comprising three tables: organizations, acquisitions, and organization descriptions. This figure shows the relationships between these entities and how they interact within the database.
• Figure 2: Representation of company distribution across countries on a world map. Since the frequencies of companies follow a power law distribution, we used a logarithmic transformation to ensure that significant countries are highlighted by their colors. This figure illustrates that Western countries have a much greater number of startups compared to the rest of the world.
• Figure 3: Bubble plot of companies’ primary categories. The size of each bubble and its label corresponds to the frequency of its category. This figure demonstrates that Software, Healthcare, and Manufacturing are the prominent categories among startups.
• Figure 4: Distributions of companies' founding years and acquisitions across different years starting from 1990. This figure illustrates that these distributions are affected by worldwide events such as the dot-com boom and the COVID-19 pandemic.
• Figure 5: An example of data comprising companies' countries, cities, and their acquisition relationships.