The Research on Electronically Collaborative Model in Automotive Industry Supply Chain

Luh, Yuan-Ping; Wang, Jeng-Bang; Chen, Jer-Jeong

doi:10.1109/icma.2007.4304201

Cited by 1 publication

(1 citation statement)

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“…For the purpose of this study the automotive supply chain has been analysed to develop a model which addresses the most significant identified enablers and rank the most dominant ones, prior to the CPFR implementation phase. The automotive supply chain is highly capitalised and technical intensive (Luh et al 2007) and characterized by intense global competition at which collaboration between trading partners is important for this industry (Binder and Clegg 2007). Earlier research identified the importance of collaboration (Binder et al 2008;Salzmann et al 2009) and information exchange (Aigbedo and Tanniru, 2005;Luh et al 2007) in automotive industry.…”

Section: Introductionmentioning

confidence: 99%

A hybrid approach to the study of CPFR implementation enablers

Panahifar

Byrne

Heavey

2015

Production Planning & Control

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Abstract:Collaborative planning, forecasting and replenishment (CPFR) is one of the most important, but also one of the most difficult collaborative strategies in supply chain management. CPFR has been well documented in past research as providing significant benefit to those that implement it well. It has also been noted that CPFR take up has been significantly lower than initially expected. The main reason for this slow up take is the general recognition that successful implementation of CPFR is not a trivial task and the fact that it inflicts dramatic changes to the 'usual' way of doing business. Based on the premise that CPFR has significant positive potential for supply chain collaboration, the motivation of this paper is to review CPFR enablers and to develop a model which addresses the most significant ones. To complete this task a hybrid modeling approach integrating fuzzy extended analytical hierarchy process (FEAHP) and interpretive structural modeling (ISM) is proposed. The model developed is based on an identified gap by the automotive sector and embeds expert opinion, from two separate industrial groups in the automotive sector through the use of workshops. Although potential success factors for CPFR implementation can vary across somewhat between differing supply chains, the results maintain wider general applicability due to the many common issues across sectors. The paper highlights the need for decision makers to be aware of the most influential enablers prior to a CPFR implementation project and to understand the relationships between these enablers.

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