A study of an augmented CPFR model for the 3C retail industry

Abstract

Purpose -To propose and test an augmented collaborative planning, forecasting, and replenishment (A-CPFR) model in a retailer-supplier context with a view to improving forecasting accuracy and then reducing the "bullwhip effect" in the supply chain. Design/methodology/approach -After a literature review, the paper presents a real case in which the present authors provided assistance. The description of the case includes: case company background; an "as-is" model analysis; a "to-be" (CPFR) model analysis; and a description of the results and potential benefits. The paper then proposes an A-CPFR model for the case and performs a simulation of the new model for comparison with the existing CPFR model. Findings -The results show that the mean absolute deviation of forecasting and the inventory variance are both better in the proposed model than in the existing CPFR model. The proposed model can thus improve the accuracy of sales forecasting, reduce inventory levels, and reduce the "bullwhip effect". Practical implications -In addition to information provided by the retailer, a logistics supplier should also obtain competitors' promotional information from the market as another factor for forecasting -thus enabling timely responses to demand fluctuations. Originality/value -The proposed model is an original and useful development on the existing CPFR model. It could become a reference model for the retail industry in implementing CPFR in the future.

Performance of supply chain collaboration – A simulation study

“…The advantage of using simulation is that an existing or proposed system can be designed using what if analysis in order to optimize the benefits by identifying the pitfalls in the system. Some researchers attempted to use system dynamics simulation for what-if analysis (Kim and Oh, 2005;Angerhofer and Angelides, 2006;Chang et al, 2007). In this research the purpose of what-if analysis is to identify the conducive environment to implement SCCs.…”

A Systematic Literature Review of Collaborative Planning Forecasting and Replenishment

“…The SC can then respond promptly to temporary fluctuations in market demand. With simulations, they (Chang et al, 2007) confirm that A-CPFR has a higher level of forecasting accuracy than the CPFR model. Du et al (2009) consider the VICS model far too complicated to implement and therefore propose a new model that combines the CPFR concept with the collaborative transportation management (CTM) concept.…”

“…Trust is the most cited enabler in the literature (e.g., Barratt and Oliveira, 2001, Larsen et al, 2003, Attaran and Attaran, 2007, Chang et al, 2007, Chen et al, 2007, Småros, 2007, Chang and Wang, 2008, Büyüközkan et al, 2009, Choi et al, 2010, Smith et al, 2010, Yuan et al, 2010, Büyüközkan and Vardaloğlu, 2012, Yao et al, 2013. Trust refers to the confidence between trading partners that no one of them will exploit vulnerabilities by one of them (Ghosh and Fedorowicz, 2008).…”

“…CPFR bridges supply and demand among SC trading partners (Stank et al, 1999, Simatupang and Sridharan, 2005, Chang et al, 2007, Sari, 2008b and results in (i) improved service level while simultaneously reducing inventory and costs (Stank et al, 1999, Larsen et al, 2003, VICS, 2004, Chen et al, 2007, Du et. al., 2009, Smith et al, 2010, VICS, 2010, (ii) promotion of greater integration, visibility and cooperation among partners (Büyüközkan et al, 2009), and (iii) a holistic approach to supply chain management (Sherman, 1998).…”

“…The autonomous agents are entities that have problem-solving capabilities can therefore propose solutions to solve the exceptions. Chang et al (2007) 9 This model is an augmented CPFR also based on VICS (1998). The authors include in the process an application service provider (ASP) that uses market information to improve forecast accuracy and replenishment.…”