A data science and open source software approach to analytics for strategic sourcing

Brad Boehmke, Benjamin Hazen, Christopher A. Boone and Jessica L. Robinson

International Journal of Information Management, 2020, vol. 54, issue C

Abstract: Data science has emerged as a significant capability upon which firms compete. Although many data scientists and the high-performing companies that employ them seem to have developed robust methods to employ data sciences practices to achieve competitive advantages, there have been few attempts at defining and explaining how and why data science helps firms to achieve desired outcomes. In this paper, we describe how data science, which combines computer programming, domain knowledge, and analytic skillsets to scientifically extract insights from data, can be used to help meet the growing demand of analytic needs across an organization’s value chain. This is done through the illustration of an applied data science initiative to a strategic sourcing problem via the use of open-source technology. In doing so, we contribute to the growing data science literature by demonstrating the application of unique data science capabilities. Moreover, the paper provides a tutorial on how to use a specific R package along with an actual case in which that package use used.

Keywords: Data science; Strategic sourcing; Purchasing portfolio; Supply chain management; Open source; R programming; Decision support (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0268401219309867
Full text for ScienceDirect subscribers only

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:eee:ininma:v:54:y:2020:i:c:s0268401219309867

DOI: 10.1016/j.ijinfomgt.2020.102167

Access Statistics for this article

International Journal of Information Management is currently edited by Yogesh K. Dwivedi

More articles in International Journal of Information Management from Elsevier
Bibliographic data for series maintained by Catherine Liu ().