Prescriptive Analytics in Public-Sector Decision-Making: A Framework and Insights from Charging Infrastructure Planning

Tobias Brandt, S Wagner, D Neumann

Research output: Contribution to journalArticleAcademicpeer-review

26 Citations (Scopus)
45 Downloads (Pure)

Abstract

In this work, we investigate the challenges public-sector organizations face when seeking to leverage prescriptive analytics and provide insights into the public value such data-driven tools and methods can provide. Using the strategic triangle of value, legitimacy, and operational capacity as a starting point, we derive a framework to assess public-sector prescriptive analytics initiatives, along with six guiding questions that structure the assessment process. We present a case study applying prescriptive analytics to the placement of charge points in urban areas, a critical challenge many municipalities are currently facing in the transition towards electric mobility. Reflecting on the analytics application as well as its development and implementation process through the guiding questions, we derive key lessons for public-sector organizations seeking to apply prescriptive analytics.

Original languageEnglish
Pages (from-to)379-393
Number of pages15
JournalEuropean Journal of Operational Research
Volume291
Issue number1
DOIs
Publication statusPublished - 16 May 2021

Bibliographical note

Publisher Copyright:
© 2020 The Author(s)

Research programs

  • RSM LIS

Fingerprint

Dive into the research topics of 'Prescriptive Analytics in Public-Sector Decision-Making: A Framework and Insights from Charging Infrastructure Planning'. Together they form a unique fingerprint.

Cite this