Visual performance management as a fitness factor for Lean

Marcel van Assen and Jeroen de Mast

International Journal of Production Research, 2019, vol. 57, issue 1, 285-297

Abstract: Visual performance management (VPM) is a bundle of practices where visual techniques are used to offer timely information to shop-floor employees about the performance of processes. We investigate whether VPM contributes to the beneficial effects of Lean, and if so, what the relationship is between VPM and other Lean practices. Thus, the study builds on and adds to the stream of research that tries to establish how the various practices associated with Lean depend on and reinforce each other. Based on the outcomes of a survey, we establish that VPM is positively related with operations improvement. This effect is not direct, but mediated by Lean practices such as just-in-time and quality management. We conclude, therefore, that VPM should be seen as an infrastructural practice that reinforces an organisation’s general fitness, and acting as an enabler for more dedicated Lean practices. In addition, we find that VPM positively moderates the effects of Lean practices, which supports the same conclusion.

Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2018.1479545 (text/html)
Access to full text is restricted to subscribers.

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:taf:tprsxx:v:57:y:2019:i:1:p:285-297

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2018.1479545

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().