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Unpredictability in the arrival time and quantity of discarded products at product recovery facilities (PRFs) and varying demand for recovered components contribute to the volatility in their inventory levels. Achieving profit under such capricious inventory levels and stringent environmental legislations remains a challenge to many PRFs. This paper presents a multi-criteria decision model to determine a pricing policy that can simultaneously address two issues: stabilize inventory fluctuations and boost profits. The model considers that PRFs passively accepts discarded products as well as acquires them proactively if necessary. Under a multi-criteria setting, the current work determines prices of reusable and recyclable components to maximize revenue and minimize product recovery costs. A genetic algorithm is employed to solve the multi-criteria decision making problem. Sensitivity analysis is performed to investigate the effect of sorting yield, disassembly yield, and reusable component yield on the profits, prices, inventory levels, and disposal quantities

The growing environmental awareness among consumers and the environmental hazards posed by heaps of discarded products, especially electronic products, have led to the enforcement of environmental regulations in the European Union [1], US [2], [3] and [4], and many other countries across the globe. The central theme of these regulations is to require the original equipment manufacturers (OEMs) accept the end of life products to promote the environmentally benign practices such as, product reuse, recycle, and proper disposal. Even though discarded products contain reusable and recyclable components, many OEMs hesitate to embrace product take back programs for the fear of cannibalizing the sales of their new products [5]. In addition, the labor intensity of product recovery operations and lackluster demand for reusable products discourage OEMs from entering into reuse-product markets. Encouraged by this stance from many OEMs, third party firms have started to enter the reuse-product markets. These third party firms, referred to as product recovery facilities (PRFs) thrive on the business of collecting the discarded end of life products, performing product recovery operations, and selling the recovered components as reuse or recycle items. The PRFs considered in this research predominantly operate as spare parts remanufacturers rather than as product remanufacturers. PRFs are usually challenged from various quarters: (a) competition from OEMs and other PRFs; (b) meager revenue from sales; (c) environmental regulations; (d) fleeting and piling inventory levels of recovered components. Among all the challenges faced by PRFs, inventory control is a serious problem [6]. It is governed by the following issues: (a) holding costs of surplus inventory; (b) lost sales due to stockouts; (c) threat of quick inventory obsolescence; (d) disposal cost of leftover and obsolete inventory; and (e) promotional and clearance price discounts. The uncertainties in timing and quantity of product disposal could contribute to either too low or too high inventory levels of recovered components. Appropriately modulating the price of the items in the inventory is an effective strategy to manage inventory under these circumstances. This strategy has a twofold impact: it facilitates inventory control and boosts the profit margin. The prices competitive with those of new products can promote the reuse and recycle of discarded products. The present work determines the prices of reusable and recyclable components in a multi-criteria environment where the goal is to concurrently maximize the revenue and minimize costs. An empirical study is performed to investigate the effect of sorting yield, disassembly yield, and reusable component yield on the profits, prices, inventory levels, and disposal quantities. Although Kongar et al. [7] and [8] have addressed issues in a multi-criteria environment for PRFs, they have not exclusively considered pricing aspects in their study. This work is unique in the sense that it addresses pricing issues in a multi-criteria setting, when PRFs passively accept discarded products and proactively acquire as needed. This work is probably the first of its kind in the literature to look at the pricing problem from the perspective of satisfying multiple criteria. Also the current work is distinct as it adopts a multi-criteria methodology (genetic algorithms) instead of nonlinear programming, which has already been investigated by the authors [9] and other researchers [10].

This work presented an analytical pricing model for PRFs which passively accept discarded products from customers and acquire them proactively when required. The model assumes that PRFs process multiple type of discarded products. The model determines the prices of reusable and recyclable components and acquisition price of discarded products in a multi-criteria environment, in which the conflicting objectives have to maximize revenue from sale and minimize product recovery costs, such as disposal cost, disassembly cost, preparation cost, holding cost, acquisition cost, and sorting cost. This paper is probably the first one in literature to formulate the pricing problem as a multi-criteria decision making problem. The effect of disassembly yield and sorting yield on the profits, prices, inventory levels, and disposal quantities was investigated. Good yield of reusable components results in the disposal quantities and prices of poor quality reusable components to remain unaffected unless product returns are acquired proactively; at the same time, prices of remanufactured components and as-is reusable components drop or rise as their inventory levels shoot up or plummet, respectively. When disassembly results in a high yield of reusable and recyclable components, the inventory levels of remanufactured, as-is reusable, and recyclable components shoot up, and consequently their prices go down. When the yield of poor quality reusable and poor quality recyclable components is small, they command high prices, and less of them go to disposal; these effects bring in big profits. Rise in sorting yield increases the quantity of recovered components and decreases the disposed quantity of poor quality products. The price, inventory level, and disposal quantity trends observed for high disassembly yield remains the same when sorting yield is high. The effects of sorting, disassembly, preparation, holding, and disposal costs on profitability and inventory level are in agreement with those reported in an earlier work [9]. In summary, low inventory levels and small disposal quantities enhance profits; so PRFs should adopt measures that would champion this cause. The future work will extend the analytical models to a multi-period case. The deterministic assumption on sorting and disassembly yields will be relaxed to study their effect on prices and inventory levels. Consideration of the customer price reservation, stochastic demand for recovered components, and oligopoly of PRFs could enrich the analytical models in understanding their impact on price decisions.