activity
20232026
most citedMachine learning-based similarity measure to forecast M&A from patent data

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

econ.GN2026

Economic complexity at subnational level: A consistency analysis

Wenli Du, Andrea Zaccaria

Several network-based measures have been proposed to assess the economic complexity of countries. These measures have provided important insights into national economic development…

econ.GN2025

A job-based assessment of economic complexity: from hidden to revealed

Antonio Russo, Pasquale Scaramozzino, Andrea Zaccaria

Economic complexity measures aim to quantify the capability content or endowment of industries and territories; however, capabilities are not observable, and therefore cannot be di…

physics.soc-ph2025

Product-level value chains from firm data: mapping trophic levels into economic growth

Massimiliano Fessina, Andrea Tacchella, Andrea Zaccaria

We reconstruct a product-level input-output network based on firm-level import-export data of Italian firms. We show that the network has a statistically significant, yet nuanced t…

physics.soc-ph20241 cited

Machine learning-based similarity measure to forecast M&A from patent data

Giambattista Albora, Matteo Straccamore, Andrea Zaccaria

Defining and finalizing Mergers and Acquisitions (M&A) requires complex human skills, which makes it very hard to automatically find the best partner or predict which firms will ma…

physics.soc-ph2023

Pattern-detection in the global automotive industry: a manufacturer-supplier-product network analysis

Massimiliano Fessina, Andrea Zaccaria, Giulio Cimini +1

Production networks arise from supply and customer relations among firms. These systems are gaining growing attention as a consequence of disruptions due to natural or man-made dis…