Optimal process mean and quality improvement in a supply chain model with two-part trade credit based on Taguchi loss function
Cheng-Ju Chuang and
Chien-Wei Wu
International Journal of Production Research, 2018, vol. 56, issue 15, 5234-5248
Abstract:
The two-part trade credit policy is developed to accelerate cash inflow that can avoid bad debt risk in the earlier economic order quantity (EOQ) models allowing only one period of time for delay in payment. Taguchi loss function has proved to be a more realistic function for fitting the actual quality loss cost in economic product quantity (EPQ) model. To minimise quality loss, optimal process mean setting shifts process mean to balance the cost outside the specification limits, quality improvement applies investment to reduce process variation. Supply chain integration has been proved that it can be used to minimise the entire cost more effectively than independent EOQ or EPQ models. This paper improves the earlier studies by incorporating the above research topics that have not been simultaneously discussed before, develops a supply chain model based on the Taguchi loss function, which combines the trade strategy from the retailer’s perspective and the quality adjustments from the supplier’s perspective to maximise total supply chain profit. We find that the trade credit terms definitely affect suppliers and retailers’ optimal decisions, and numerical examples can provide decision references for supply chain managers to set a trade credit policy and control quality.
Date: 2018
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2017.1394591 (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:56:y:2018:i:15:p:5234-5248
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2017.1394591
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 ().