A test of inventory models with permissible delay in payment
Daniel Seifert,
Ralf W. Seifert and
Olov H.D. Isaksson
International Journal of Production Research, 2017, vol. 55, issue 4, 1117-1128
Abstract:
Contrary to the long-standing view in the finance literature that firms should maximise payment delays, research in operations management suggests that long payment delays can be suboptimal. In this study, we reconcile these two views by applying a secondary data approach to established operations management theory. Based on a sample of 3383 groups of public US firms from a novel database, we find that our data are consistent with the causal relations and theoretical predictions of the operations management literature. Firm profitability is positively associated with payment delay. Payment delay, in turn, is positively associated with the capital cost difference between buyer and supplier and negatively associated with the price elasticity of demand and the deterioration rate of inventory. However, we do not observe any significant interaction effects between these factors, which raise a number of questions for future research.
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2016.1224947 (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:55:y:2017:i:4:p:1117-1128
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2016.1224947
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 ().