The K-means algorithm and its variants are well-known clustering techniques. In actuarial applications, these partitioning methods can identify clusters of policies with similar attributes. The resulting partitions provide an actuarial framework for creating maps of dominant risks and...

Since its inception in 2009, Bitcoin has become and is currently the most successful and widely used cryptocurrency. It introduced blockchain technology, which allows transactions that transfer funds between users to take place online, in an immutable manner. No real-world identities are needed...

The evolution of industrial clusters has received much attention in the recent literature on evolutionary economic geography (EEG) and regional science. However, scientific results on the influence of different factors on the decline or renewal of mature industrial clusters are scarce....

This study investigates the landscape of cyber-financial risks across Europe by identifying distinct risk profiles based on financial literacy, digital comfort, and economic vulnerability. Utilizing data from the Flash Eurobarometer 525 survey, we employ K-means cluster analysis to categorize...

Purpose: Automatic grouping of data according to certain characteristics is made possible by clustering algorithms, which makes them an essential tool when working with large datasets. However, although they are unsupervised tools, they generally require the specification of the number of...