Impact of supply chain strategy on mass customisation implementation and effectiveness: evidence from China
Min Zhang and
Yinan Qi
International Journal of Information and Decision Sciences, 2013, vol. 5, issue 4, 393-413
Abstract:
Currently, designing a supply chain for mass customisation (MC) has become an issue that intrigued both the academia and industrial practitioners. In this study, we examine the fit between supply chain strategy and MC practices and its impact on firm performance. We first develop supply chain configurations using cluster analysis and find that the whole sample can be divided into four groups (leagile, lean, agile, and traditional). We then link the supply chain strategies with MC practices (elicitation, process flexibility technology, and logistics). Our results show that the impact of MC practices on operational performance is moderated by supply chain strategy configurations and that these practices are most beneficial in the leagile group. Our results hence suggest that MC practices require a leagile supply chain structure and underscore the importance of aligning the supply chain strategy with a distinctive set of processes and technologies for MC adoption.
Keywords: mass customisation; supply chain strategy; survey; China; supply chain management; SCM; supply chain design; cluster analysis; leagile supply chains; lean supply chains; agile supply chains; traditional supply chains; process flexibility; logistics; operational performance. (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=58287 (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:ids:ijidsc:v:5:y:2013:i:4:p:393-413
Access Statistics for this article
More articles in International Journal of Information and Decision Sciences from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().