Modeling Consumer Decisions on Returning End-of-Use Products Considering Design Features and Consumer Interactions: An Agent Based Simulation Approach
Modeling Consumer Decisions on Returning End-of-Use Products Considering Design Features and Consumer Interactions: An Agent Based Simulation Approach
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DOI：
10.1115/detc2015-46864
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发表时间：
2015-08
期刊：
影响因子：
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通讯作者：
A. Mashhadi;Behzad Esmaeilian;S. Behdad
中科院分区：
文献类型：
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作者：
A. Mashhadi;Behzad Esmaeilian;S. Behdad
随着电子废弃物成为增长最快的环境问题之一，再制造被认为是一个有前途的解决方案。然而，回收系统的盈利能力受到几个因素的阻碍，包括缺乏关于要返回到再制造设施的旧产品的数量和时间的信息。产品设计特点、消费者对回收机会的认识、社会人口信息、同伴压力以及消费者倾向于将用过的物品储存起来，都是造成废物流中不确定性增加的因素。预测客户退回使用过的产品的选择决定，包括客户停止使用产品的时间和最终使用决定（例如储存、转售、通过和返回废物流），可以帮助制造商更好地估计返回趋势。本文的目的是开发一个基于智能体的仿真（ABS）模型集成离散选择分析（DCA）技术来预测消费者的最终使用（EOU）产品的决策。建议的模拟工具的目的是调查的影响，设计特点，个人消费者之间的互动和社会人口特征的最终用户的退货数量。最后以手机回收系统为例，说明了模型的应用。Copyright © 2015 by ASME
As electronic waste (e-waste) becomes one of the fastest growing environmental concerns, remanufacturing is considered as a promising solution. However, the profitability of take back systems is hampered by several factors including the lack of information on the quantity and timing of to-be-returned used products to a remanufacturing facility. Product design features, consumers’ awareness of recycling opportunities, socio-demographic information, peer pressure, and the tendency of customer to keep used items in storage are among contributing factors in increasing uncertainties in the waste stream. Predicting customer choice decisions on returning back used products, including both the time in which the customer will stop using the product and the end-of-use decisions (e.g. storage, resell, through away, and return to the waste stream) could help manufacturers have a better estimation of the return trend. The objective of this paper is to develop an Agent Based Simulation (ABS) model integrated with Discrete Choice Analysis (DCA) technique to predict consumer decisions on the End-of-Use (EOU) products. The proposed simulation tool aims at investigating the impact of design features, interaction among individual consumers and socio-demographic characteristics of end users on the number of returns. A numerical example of cellphone take-back system has been provided to show the application of the model.Copyright © 2015 by ASME