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Hazard rate models for core return modeling in auto parts remanufacturing

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  • Kumar, Akhilesh
  • Chinnam, Ratna Babu
  • Murat, Alper

Abstract

Under growing consumer awareness and increasing legislation, firms are realizing the importance of including sustainability within their strategic objectives to promote their green image, enhance their corporate citizenship status, and also improve profit margins. Towards this end, sustainability through product remanufacturing is gaining momentum. However, a key complication for maintaining operational efficiencies during production planning and control of remanufacturing lies in the inability to accurately forecast core returns. These difficulties are mostly attributable to limited visibility and higher levels of uncertainty in reverse logistics. Despite significant advances in the remanufacturing literature over the last two decades, there is not yet a practical approach for modeling core return delay durations when the company is engaged in business with a large remanufacturing product catalog and many customer facilities. This is particularly true for suppliers that engage in both original equipment (OE) service as well as independent after-market (IAM) businesses. This research aims to address these limitations for suppliers by developing a range of hazard rate models for core returns duration modeling. Models are also validated using data from a large global automotive supplier.

Suggested Citation

  • Kumar, Akhilesh & Chinnam, Ratna Babu & Murat, Alper, 2017. "Hazard rate models for core return modeling in auto parts remanufacturing," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 354-361.
  • Handle: RePEc:eee:proeco:v:183:y:2017:i:pb:p:354-361
    DOI: 10.1016/j.ijpe.2016.07.002
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    References listed on IDEAS

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    1. Dipak C. Jain & Naufel J. Vilcassim, 1991. "Investigating Household Purchase Timing Decisions: A Conditional Hazard Function Approach," Marketing Science, INFORMS, vol. 10(1), pages 1-23.
    2. L. Beril Toktay & Lawrence M. Wein & Stefanos A. Zenios, 2000. "Inventory Management of Remanufacturable Products," Management Science, INFORMS, vol. 46(11), pages 1412-1426, November.
    3. Li, Jianzhi & González, Miguel & Zhu, Yun, 2009. "A hybrid simulation optimization method for production planning of dedicated remanufacturing," International Journal of Production Economics, Elsevier, vol. 117(2), pages 286-301, February.
    4. Barba-Gutierrez, Y. & Adenso-Diaz, B. & Gupta, S.M., 2008. "Lot sizing in reverse MRP for scheduling disassembly," International Journal of Production Economics, Elsevier, vol. 111(2), pages 741-751, February.
    5. Tang, Ou & Grubbstrom, Robert W., 2005. "Considering stochastic lead times in a manufacturing/remanufacturing system with deterministic demands and returns," International Journal of Production Economics, Elsevier, vol. 93(1), pages 285-300, January.
    6. Wang, Ziping & Yao, Dong-Qing & Huang, Peiqing, 2007. "A new location-inventory policy with reverse logistics applied to B2C e-markets of China," International Journal of Production Economics, Elsevier, vol. 107(2), pages 350-363, June.
    7. Krikke, Harold & le Blanc, Ieke & van Krieken, Maaike & Fleuren, Hein, 2008. "Low-frequency collection of materials disassembled from end-of-life vehicles: On the value of on-line monitoring in optimizing route planning," International Journal of Production Economics, Elsevier, vol. 111(2), pages 209-228, February.
    8. Kristiaan Helsen & David C. Schmittlein, 1993. "Analyzing Duration Times in Marketing: Evidence for the Effectiveness of Hazard Rate Models," Marketing Science, INFORMS, vol. 12(4), pages 395-414.
    9. Schultmann, Frank & Zumkeller, Moritz & Rentz, Otto, 2006. "Modeling reverse logistic tasks within closed-loop supply chains: An example from the automotive industry," European Journal of Operational Research, Elsevier, vol. 171(3), pages 1033-1050, June.
    10. Inderfurth, Karl, 2004. "Optimal policies in hybrid manufacturing/remanufacturing systems with product substitution," International Journal of Production Economics, Elsevier, vol. 90(3), pages 325-343, August.
    11. Aras, Necati & Aksen, Deniz, 2008. "Locating collection centers for distance- and incentive-dependent returns," International Journal of Production Economics, Elsevier, vol. 111(2), pages 316-333, February.
    12. Takahashi, Katsuhiko & Morikawa, Katsumi & Myreshka & Takeda, Daisuke & Mizuno, Akihiko, 2007. "Inventory control for a MARKOVIAN remanufacturing system with stochastic decomposition process," International Journal of Production Economics, Elsevier, vol. 108(1-2), pages 416-425, July.
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    1. Yanting Huang & Zongjun Wang, 2017. "Dual-Recycling Channel Decision in a Closed-Loop Supply Chain with Cost Disruptions," Sustainability, MDPI, Open Access Journal, vol. 9(11), pages 1-28, November.
    2. Huang, Yanting & Wang, Zongjun, 2017. "Information sharing in a closed-loop supply chain with technology licensing," International Journal of Production Economics, Elsevier, vol. 191(C), pages 113-127.

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