Impact of quality regulation policy on performance of a remanufacturing supply chain with non-waste returns

Abstract

Quality issues in a remanufacturing supply chain with non-waste returns have been reported many times. To address these issues, the government proposes different quality regulation policies. This paper develops a multi-agent simulation model to study how the quality regulation policy affects the performance of a remanufacturing supply chain with non-waste returns. Here, the main performance includes profit and hazard ratio of products. Our results indicate that self-regulation of the market cannot realize a desirable outcome (low hazard ratio and high manufacturer’s profit). Adjusting quality regulation probability is more efficient than adjusting the penalty for inferior products. From the view of increasing manufacturer’s average profit, or improving the government’s efficiency, the best policy is the solely adjusting supervision probability policy. From the view of reducing hazard ratio, the best policy is adjusting supervision probability- penalty policy. The appropriate penalty for inferior products can realize the desirable outcome. With an increasing supervision probability, the hazard ratio decreases, and the manufacturer’s average profit increases because the remanufacturing cost and penalty for inferior products decrease.

Keywords:

• supply chain management
• quality regulation policy
• non-waste returns
• multi-agent simulation

Notes

1 http://www.cqn.com.cn/ms/content/2016-12/09/content_3697627.htm.

2 http://www.bbc.com/news/uk-england-london-40272168.

3 Suppliers are heterogeneous in the offering price and inferior rate; retailers are heterogeneous in the trading price and demand.

4 http://www.ppgideascapes.com/.

5 Every supplier has unit offering price regardless of whether the supplier has a transaction or not. The offering price of components is the price that supplier $m$ selling it says that he wants for it, although he may accept less. For example, the offering price of the component is 3 yuan, while the trading price may be 2 yuan.

Additional information

Funding

This research was supported in part by: (i) China National Funds for Distinguished Young Scientists [grant number 71425001]; (ii) the National Natural Science Foundation of China [grant numbers 71871112 and 71371093]; and (iii) Postgraduate Research & Practice Innovation Program of Jiangsu Province [grant number KYCX18_0022].