Bridging Fields of Practice: How Boundary Objects Enable Collaboration in Data Science Initiatives

Nils Rahlmeier () and Konstantin Hopf ()
Additional contact information
Nils Rahlmeier: University of Bamberg, Information Systems and Energy Effieicnt Systems
Konstantin Hopf: University of Bamberg, Information Systems and Energy Effieicnt Systems

A chapter in Artificial Intelligence, Data, and Decision-Making, 2026, pp 189-205 from Springer

Abstract: Abstract Data-intensive technologies draw high investments. Yet, data science projects are reported to suffer from poor collaboration, unrealistic expectations, and difficulties in realizing practical solutions between business and data science units. Moving beyond the currently prevalent approach to study data science practices, our study emphasizes the use of boundary objects between data science and collaborating fields. We interviewed collaborators from diverse fields in six organizational data science initiatives. Our inductive analysis of this rich data source uncovered six distinct mechanisms and six archetypes of boundary objects in data science projects. While archetypes that we label Alignment, Temporary, Collaboration, and Outcome are procedural and appear in selective stages of the data value creation process, the archetypes Infrastructure and Upskilling support projects along the value creation process. The archetypes and their mechanisms inform the management of data science initiatives, help to advance boundary object theory, and provide instruments to study data science initiatives.

Keywords: Management of data science initiatives; Boundary objects; Knowledge sharing; Organizational development (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:spr:lnichp:978-3-032-08480-4_13

Ordering information: This item can be ordered from
http://www.springer.com/9783032084804

DOI: 10.1007/978-3-032-08480-4_13

Access Statistics for this chapter

More chapters in Lecture Notes in Information Systems and Organization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().