DOI: 10.6084/m9.figshare.28777856.v1
title: Mapping patent integration strategies in a multinational firm

description: <b>Figure 1. Co-invention Network across Countries and Technological Domains</b>This network visualisation depicts cross-border co-invention ties in Bosch’s AI-related patents filed between 2017 and 2023. Each node represents a country, coloured by dominant technological domain (e.g., propulsion, embedded systems). Directed edges indicate co-patenting flows from subsidiaries to the German headquarters (DE). Node size reflects centrality in the network, and edge thickness indicates the frequency of co-invention ties. The network highlights Germany’s role as the central hub integrating diverse regional contributions, especially in transversal technologies such as artificial intelligence and advanced manufacturing.<br><br><b>Figure 2. Hierarchical Clustering of Inventor Home Countries Based on Co-invention Patterns</b>This dendrogram shows a hierarchical clustering of inventor home countries based on their involvement in Bosch’s AI-related co-invention activity from 2017 to 2023. The clustering uses Ward’s linkage and rescaled distance metrics to identify similarities in national co-patenting profiles. Each country represents the residence of inventors rather than patent ownership or filing location. The results indicate distinct groupings, with countries such as Germany, Austria, and France forming a tightly connected core, while others like Japan, Vietnam, and Israel appear more peripheral. The analysis captures how geographically distributed inventors are integrated into the firm’s internal innovation network.<br><br>This dataset contains structured patent and inventor information used in the analysis of transnational co-invention and patent integration strategies within Robert Bosch GmbH’s innovation network. It includes 380 patents filed between 2017 and 2023 that are classified under artificial intelligence and related transversal technologies.<b>Variables include:</b><b>Patent ID</b> (anonymised)<b>Filing Year</b><b>Jurisdiction of Filing</b> (e.g. EPO, WIPO)<b>IPC Technological Classification</b> (e.g. Artificial Intelligence, Embedded Systems)<b>Inventor ID</b> (anonymised)<b>Inventor Country</b> (home country based on affiliation at filing time)<b>Number of Inventors per Patent</b><b>Co-inventor Ties</b> (binary format for network construction)<b>Filing Authority</b><b>Assignment Location</b> (corporate entity receiving ownership)<br>R Script for Estimating Exponential Random Graph Models (ERGM) in Co-Inventor Networks<br><b>Description</b>:<br>This script contains the R code used to construct and analyse co-inventor networks based on patent data. It includes procedures for:Importing and formatting adjacency matrices and inventor attribute dataBuilding network objects using the <code>network</code> and <code>igraph</code> packagesAssigning node-level attributes such as inventor affiliation, technological classification, and team sizeEstimating Exponential Random Graph Models (ERGM) using the <code>ergm</code> packageTesting the significance of network structure, inventor-level effects, and filing-related covariatesRunning diagnostics to evaluate model fit and convergence