Reason‐code based model to forecast product returns
暂无分享,去创建一个
Purpose – This paper aims to propose a method for forecasting product returns based on reason codes. The methodology uses two approaches, namely central tendency approach and extreme point approach, and is developed for the consumer electronics industry.Design/methodology/approach – The methodology presented here is based on the return reason codes (RC). The incoming returns are split into different categories using reason codes. These reason codes are further analyzed to forecast returns. The computation part of this model uses a combination of two approaches, namely extreme point approach and central tendency approach. Both the approaches are used separately for separate types of reason codes and then results are added together. The extreme point approach is based on data envelopment analysis (DEA) as a first step combined with a linear regression while central tendency approach uses a moving average. For certain type of returns, DEA evaluates relative ranks of products using single input and multiple o...
[1] Harvey Meyer,et al. WHEN THE CAUSE IS JUST , 1999 .
[2] Linda S Beltran. REVERSE LOGISTICS: CURRENT TRENDS AND PRACTICES IN THE COMMERCIAL WORLD , 2002 .
[3] J. D. Hess,et al. Modeling merchandise returns in direct marketing , 1997 .
[4] Ronald S. Tibben-Lembke,et al. Going Backwards: Reverse Logistics Trends and Practices , 1999 .