Details
| Original language | English |
|---|---|
| Title of host publication | Advances in Production Management Systems |
| Subtitle of host publication | International IFIP TC 5, WG 5.7 Conference on Advances in Production Management Systems (APMS 2007), September 17-19, Linkoping, Sweden |
| Editors | Jan Olhager, Fredrik Persson |
| Pages | 51-58 |
| Number of pages | 8 |
| Publication status | Published - 2007 |
Publication series
| Name | IFIP International Federation for Information Processing |
|---|---|
| Volume | 246 |
| ISSN (Print) | 1571-5736 |
Abstract
Manufacturing companies often merely attain reduced levels of logistic performance due to inconsistencies between their logistic objectives, logistic performance targets and logistic performance management actions. Qualitative influence models represent the inter-dependencies between these factors on two levels: firstly between logistic objectives, secondly between logistic performance measures and logistic planning and control parameters. Expert knowledge gained from modelling the dynamic behaviour of logistic systems facilitates the interpretation and evaluation of the qualitative influence models. On this basis, consistent logistic objectives can be defined and objective-oriented planning and control actions can be identified. The modelling insights are integrated into a logistic performance diagnosis procedure and tool that improve logisticians' understanding of the consequences of their management decisions and enhance the closed-loop management of logistic performance.
Keywords
- Logistic performance, Performance management, Qualitative model
ASJC Scopus subject areas
- Decision Sciences(all)
- Information Systems and Management
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
Advances in Production Management Systems: International IFIP TC 5, WG 5.7 Conference on Advances in Production Management Systems (APMS 2007), September 17-19, Linkoping, Sweden. ed. / Jan Olhager; Fredrik Persson. 2007. p. 51-58 (IFIP International Federation for Information Processing; Vol. 246).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Ensuring the consistency of competitive strategy and logistic performance management
AU - Von Cieminski, Gregor
AU - Nyhuis, Peter
PY - 2007
Y1 - 2007
N2 - Manufacturing companies often merely attain reduced levels of logistic performance due to inconsistencies between their logistic objectives, logistic performance targets and logistic performance management actions. Qualitative influence models represent the inter-dependencies between these factors on two levels: firstly between logistic objectives, secondly between logistic performance measures and logistic planning and control parameters. Expert knowledge gained from modelling the dynamic behaviour of logistic systems facilitates the interpretation and evaluation of the qualitative influence models. On this basis, consistent logistic objectives can be defined and objective-oriented planning and control actions can be identified. The modelling insights are integrated into a logistic performance diagnosis procedure and tool that improve logisticians' understanding of the consequences of their management decisions and enhance the closed-loop management of logistic performance.
AB - Manufacturing companies often merely attain reduced levels of logistic performance due to inconsistencies between their logistic objectives, logistic performance targets and logistic performance management actions. Qualitative influence models represent the inter-dependencies between these factors on two levels: firstly between logistic objectives, secondly between logistic performance measures and logistic planning and control parameters. Expert knowledge gained from modelling the dynamic behaviour of logistic systems facilitates the interpretation and evaluation of the qualitative influence models. On this basis, consistent logistic objectives can be defined and objective-oriented planning and control actions can be identified. The modelling insights are integrated into a logistic performance diagnosis procedure and tool that improve logisticians' understanding of the consequences of their management decisions and enhance the closed-loop management of logistic performance.
KW - Logistic performance
KW - Performance management
KW - Qualitative model
UR - http://www.scopus.com/inward/record.url?scp=37549032491&partnerID=8YFLogxK
U2 - 10.1007/978-0-387-74157-4_7
DO - 10.1007/978-0-387-74157-4_7
M3 - Conference contribution
AN - SCOPUS:37549032491
SN - 9780387741567
T3 - IFIP International Federation for Information Processing
SP - 51
EP - 58
BT - Advances in Production Management Systems
A2 - Olhager, Jan
A2 - Persson, Fredrik
ER -