The impact of contract parameters on the supply chain performance under different power constellations
Richard Lackes,
Philipp Schlüter and
Markus Siepermann
International Journal of Production Research, 2016, vol. 54, issue 1, 251-264
Abstract:
Reporting forecast data is a common method used to improve the functioning of supply chains (SCs) and to reduce supply shortages. Customers tend to report the maximum possible demand as a forecast if restrictions are missing. Such a forecast is useless for suppliers. Hence, special contracts are needed to enhance the value of forecast data and therefore the cooperation between SC partners. In this paper, such a contract is presented. It encourages the customer to report a more realistic forecast. Deviations from the reported forecast are punished in different ways: If the customer reported too much and wants to release less than what was reported, he has to pay a penalty. On the other hand, the customer has the flexibility to purchase more than reported to meet the demand on his outlet but at the cost of an additional fee. This paper analyses how different contract parameters affect the performance of the SC, in particular when the bargaining power of customer and supplier is not equally distributed. Results show that the supplier and therefore the SC is better off if the supplier leaves the contractual cost parameters untouched but hides the true value of flexibility, especially when the customer is less powerful than the supplier.
Date: 2016
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2015.1076943 (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:54:y:2016:i:1:p:251-264
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2015.1076943
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 ().