Used Products Return Pattern Analysis Using Agent-Based Modelling and Simulation

Used Products Return Pattern Analysis Using Agent-Based Modelling and Simulation

Copyright: © 2014 |Pages: 21
DOI: 10.4018/978-1-4666-4908-8.ch003
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This chapter examines the used products return service quality perceived by the end users and their corresponding willingness-to-return with respect to the used products in their possession. The chapter starts with an introduction about the issue of return quantity encountered at the used product collection stage. Then, related studies dealing with returns quantity are discussed in the background section. Next, the focal problem of this chapter is stated in the problem statement section. A detailed description about the approach (i.e., agent-based modelling and simulation) can be found in the proposed methodology section. Right after this, three simulations, with each one linked to a specific used products return scenario, are conducted in the experimental study section. The potential research directions regarding the main problem considered in this chapter are highlighted in the future trends section. Finally, the conclusion drawn in the last section closes this chapter.
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One of the major issues that hinder remanufacturing from being successful is the difficulty of acquiring used products (Franke, Basdere, Ciupek, & Seliger, 2006; V. Daniel R. Guide, Teunter, & Wassenhove, 2003; Robotis, Bhattacharya, & Wassenhove, 2005; Toffel, 2004). No matter how remanufacturing activities are practiced, a continuous flow of returned used products is often a necessary for any remanufacturer (Klausner & Hendrickson, 2000).

In remanufacturing field, used products collection is often referred to as all activities rendering used products available and physically moving them to some point within a remanufacturing process where further treatment is conducted (Sasikumar & Kannan, 2008a). It is indeed the first activity of used product recovery, and triggers the other activities of the recovery system. This includes processes such as transportation, consolidation, transhipment and storage (Blanc, 2006). To do that, Güngör and Gupta (1999) argued that collection of used products must be planned ahead in order to perform product recovery profitably and according to applicable laws and regulation, especially for high value and complex products such as cellular phones (V.D.R. Guide & Wassenhove, 2003), computers (White, Masanet, Rosen, & Beckmans, 2003), printers and scanners (Spengler, Ploog, & Schröter, 2003), as well as other computer peripherals (Blackburn, Guide, Souza, & Wassenhove, 2004) and single-use cameras (Grant & Banomyong, 2010). The automobile industry (N. Ferguson & Browne, 2001) is another major example as well as industrial automation products (Krikke, Blanc, & Velde, 2004; Kumar & Putnam, 2008) that collection of parts or modules have been convinced to reduced production costs and enhances profitability (Bostel, Dejax, & Lu, 2005).

As it is known, nowadays, major researchers focused on the considerable uncertainties in the quantity, timing, and quality of used product returns (Lundmark, Sundin, & Bjorrkman, 2009). Review the literatures, we found there are two efforts are made to deal with collection uncertainties. One is focused on price interation within collection processes, for instance, (Atasu, Sarvary, & Wassenhove, 2008; Ferrer & Swaminathan, 2006; V. Daniel R. Guide & Wassenhove, 2009; Hsueh, 2011; Liang, Pokharel, & Lim, 2009; Mahapatra, Pal, & Narasimhan, 2012; Supriya Mitra & Webster, 2008; Pokharel & Liang, 2012; Robotis et al., 2005; Robotis, Boyaci, & Verter, 2012; R. C. Savaskan, S. Bhattacharya, & L. N. V. Wassenhove, 2004; Savaskan & Wassenhove, 2006; Vadde, Zeid, & Kamarthi, 2011). On the other hand, some researchers discussed the use of incentive-systems (V. Daniel R. Guide et al., 2003; V. Daniel R. Guide & Wassenhove, 2001; Klausner & Hendrickson, 2000) or collecting channel options (Ahn, 2009; C. Savaskan, L. N. Bhattacharya, & L. N. V. Wassenhove, 2004; Savaskan & Wassenhove, 2006) to influence the quality distribution of cores.

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