Improving Business History Through Social Network Analysis and Data

Alberto Rinaldi (), Erica Salvaj (), Susie J. Pak () and Daniel S. Halgin ()
Additional contact information
Alberto Rinaldi: Università di Modena e Reggio Emilia
Erica Salvaj: Universidad del Desarrollo (UDD)
Susie J. Pak: St. John’s University
Daniel S. Halgin: University of Kentucky

Chapter 2 in Network Analysis for Economic, Business and Financial History, 2026, pp 47-70 from Palgrave Macmillan

Abstract: Abstract This chapter explores the application of Social Network Analysis (SNA) to corporate networks from a historical perspective. It explains how to convert archival data into network-ready formats and demonstrates the methodology through case studies spanning national corporate networks (Argentina, Chile, Italy 1900–2017), local business networks in nineteenth-century Southern Italy, and J.P. Morgan & Co.’s early twentieth-century connections. The examples show how SNA can reveal hidden patterns in traditional business sources and enable more systematic historical research, including the identification of absent ties.

Keywords: Social Network Analysis (SNA); Corporate networks; Business history; Historical quantitative archival data; Interlocking directorates (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pal:palscp:978-3-032-21355-6_2

Ordering information: This item can be ordered from
http://www.palgrave.com/9783032213556

DOI: 10.1007/978-3-032-21355-6_2

Access Statistics for this chapter

More chapters in Palgrave Studies in Economic History from Palgrave Macmillan
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().