| Title |
A framework for modeling fraud in E-waste management |
| ID_Doc |
6712 |
| Authors |
Salmon, D; Babbitt, CW; Babbitt, GA; Wilmer, CE |
| Title |
A framework for modeling fraud in E-waste management |
| Year |
2021 |
| Published |
|
| DOI |
10.1016/j.resconrec.2021.105613 |
| Abstract |
Despite the adoption of electronic waste recycler certification schemes in the United States, there remain notable instances in which recyclers might engage in dishonest practices. To better understand mechanisms that may encourage honest electronics end-of-life management, we develop a framework to analyze the decision calculus of electronic waste recyclers facing a decision between an honest choice that might be more expensive or a dishonest choice that saves money but has some probability of being caught. Building an analytical decision tree model under which a recycler maximizes expected returns, we explore the influence of supervision on the choices a recycler faces and provide an analytical solution that describes the boundaries that separate those choices. Using our framework, we systematically catalog which interventions may help and which may not. The model suggests that direct unqualified subsidies to recyclers may not be particularly effective, although properly targeted subsidies have promise. We also find that there are substitution effects between increasing the cost of fraud and decreasing the costs of proper electronic waste recycling. That is, increasing the cost of fraud can serve as a policy instrument to produce effects similar to decreasing a recycler's costs from engaging in honest behavior. We also discuss the role of digital fraud prevention technologies such as blockchain as another mechanism to help achieve sustainability outcomes in e-waste management while lowering the costs of third-party supervision. |
| Author Keywords |
Decision Tree Model; Circular Economy; Electronic Waste; Fraud Prevention; Expected Returns Maximization; Government Subsidy |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000667310900006 |
| WoS Category |
Engineering, Environmental; Environmental Sciences |
| Research Area |
Engineering; Environmental Sciences & Ecology |
| PDF |
http://manuscript.elsevier.com/S0921344921002226/pdf/S0921344921002226.pdf
|