Digitala Vetenskapliga Arkivet

Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Can we leverage process data from ERP systems for business process sustainability analyses?
Technical University of Munich, School of CIT, Munich, Germany; SAP Signavio, Berlin, Germany.
Technical University of Munich, School of CIT, Heilbronn, Germany; Weizenbaum Institute, Berlin, Germany.
Umeå University, Faculty of Science and Technology, Department of Computing Science. SAP Signavio, Berlin, Germany.ORCID iD: 0000-0002-6458-2252
Technical University of Munich, School of CIT, Heilbronn, Germany; Weizenbaum Institute, Berlin, Germany .
2025 (English)In: Process mining workshops / [ed] Andrea Delgado; Tijs Slaats, Cham: Springer Nature, 2025, p. 764-777Chapter in book (Refereed)
Abstract [en]

Sustainability is an increasingly important issue, which organizations need to take into account when assessing and improving their business processes. Doing so can contribute to enhancing an organisation’s overall sustainability. Green Business Process Management is a line of research concerned with supporting organisations to integrate a sustainability perspective into their processes. However, existing approaches that assess sustainability on activity and process levels using, for instance, Life-Cycle Assessment (LCA) are often time-consuming and complex. Therefore, this work explores whether Key Ecological Indicators (KEIs) used to assess the sustainability of a business process can be calculated using data already available within an organisation. Following a case study methodology, we analyse nine real-world datasets extracted from a business process analysis system of a large enterprise software vendor. Results indicate that current data availability is insufficient for exact assessments. To address this issue, we introduce a high-level conceptual model and provide recommendations for action based on the observations of the case study.

Place, publisher, year, edition, pages
Cham: Springer Nature, 2025. p. 764-777
Series
Lecture Notes in Business Information Processing ; 533
Keywords [en]
Sustainability, Green Business Process Management, Key Ecological Indicators, Process Data Analysis
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:umu:diva-237257DOI: 10.1007/978-3-031-82225-4_56Scopus ID: 2-s2.0-105002042355OAI: oai:DiVA.org:umu-237257DiVA, id: diva2:1949924
Conference
ICPM 2024 International Workshops, Lyngby, Denmark, October 14–18, 2024
Available from: 2025-04-03 Created: 2025-04-03 Last updated: 2025-05-06Bibliographically approved

Open Access in DiVA

fulltext(540 kB)16 downloads
File information
File name FULLTEXT01.pdfFile size 540 kBChecksum SHA-512
24b9cf3213d343749742fce9d5b11b340ce8264fb95c0e676fa117e0326224e9439b46ff437d7406728072279a8e9faadb729fcb36cf6be2bfa60a6ace26d831
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Kampik, Timotheus
By organisation
Department of Computing Science
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 16 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 289 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf