Essays in sustainable operations

Aditya Vedantam, Purdue University

Abstract

In the first chapter, we study the impact of Environmentally Preferable Purchasing (EPP) and municipal supply uncertainty as a driver of recycled content in practice and explore the impact of recycled content claims made as an annual average vs. batch specific claims. We formulate a two stage stochastic dynamic program, consisting of a design stage, where a recycled content claim is declared, and a procurement stage where the manufacturer has recourse to self-collection to meet the commitment. Our goal is to compare manufacturer profits and recycled content levels under batch specific and time averaged claims and explore the effect of EPP and supply-side intervention i.e. moving from single stream to dual-stream collection of recyclables. Our main contributions are as follows: (a) We establish conditions under which batch specific claims are larger than time averaged claims; (b) we find that variability of supply in the municipal stream of recyclables increases (decreases) the recycled content claim if the collection cost is high (low), (c) we find that simultaneously increasing recovery of recyclables through dual-stream collection and/or container deposit legislation and creating demand side incentives for recycled content can create win-win conditions; and (d) show that EPP increases (decreases) the recycled content claim if the collection cost is sufficiently low (high). Based on analytical results, we show that demand side policies like EPP should be tailored to local supply limitations to achieve Pareto-improving outcomes for manufacturers and the environment. Our model is calibrated to data from the fiberglass insulation industry and a glass recycling study conducted in the State of Ohio. In the second chapter, we consider the case of a manufacturer investing production capacity in presence of R&D updates on development of an energy efficient technology. This problem is relevant to the development of clean energy technologies like direct drive wind turbines and energy efficient lighting, where R&D progress is tracked over a Technology Roadmap. We build a stylized model of a manufacturer adding assembly capacity based on realized R&D progress and calibrate it to data for the wind turbine industry. We provide option value estimates for the R&D projects along with the timing of capacity addition. In the third chapter, we consider the problem of a customer that contracts with a Product Recovery Facility (PRF) to dispose of its used electronic equipment in the most environmentally friendly manner i.e, by reuse and refurbishment or disassembly and recycling. Typical disposition contracts in the IT Asset disposition industry involve a fixed upfront payment by the customer to the PRF and a rebate for each unit resold that is credited back to the customer. We optimize the optimum transfer payment and rebate fraction, under uncertainty in condition of incoming units, while accounting for the PRFs bankruptcy risk. We find that as customers become increasingly environmentally conscious they choose a lower rebate fractions and decrease the upfront fee paid to the PRF. Moreover, as uncertainty in incoming condition and refurbishing cost increases customers again choose a lower rebate fraction. Overall, our model agrees with existing best practice in the industry i.e., customers who "refresh'' their IT Assets frequently keep a greater fraction of the resale value. We calibrate our model to a real dataset consisting of end-of-life laptops processed at a PRF.

Degree

Ph.D.

Advisors

Iyer, Purdue University.

Subject Area

Environmental economics|Management|Sustainability

COinS