An inventory model with dependent product demands and returns

Kiesmüller, Gudrun P.; Laan, EP Ewout van der

doi:10.1016/s0925-5273(00)00080-3

Cited by 127 publications

(48 citation statements)

References 6 publications

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“…They reported that their method outperforms unimodal forecast procedures that disregard the correlation between returns and past sales. In this, they agree with Kiesmüller and van der Laan (2001), who modelled Poisson demand and returns (lagged by a constant time since sold) by incorporating the former in the forecast of the latter by means of Markov chains. Clottey (2016) provide further support to the claim for when returns follow an autoregressive pattern, but not when they are random noise.…”

Section: Forecasting In Closed-loop Supply Chainssupporting

confidence: 84%

The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems

Goltsos

Ponte

Wang

et al. 2018

International Journal of Production Research

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Recent years have witnessed companies abandon traditional open-loop supply chain structures in favour of closed-loop variants, in a bid to mitigate environmental impacts and exploit economic opportunities. Central to the closed-loop paradigm is remanufacturing: the restoration of used products to useful life. While this operational model has huge potential to extend product life-cycles, the collection and recovery processes diminish the effectiveness of existing control mechanisms for open-loop systems. We systematically review the literature in the field of closed-loop supply chain dynamics, which explores the time-varying interactions of material and information flows in the different elements of remanufacturing supply chains. We supplement this with further reviews of what we call the three 'pillars' of such systems, i.e. forecasting, collection, and inventory and production control. This provides us with an interdisciplinary lens to investigate how a 'boomerang' effect (i.e. sale, consumption, and return processes) impacts on the behaviour of the closed-loop system and to understand how it can be controlled. To facilitate this, we contrast closed-loop supply chain dynamics research to the welldeveloped research in each pillar; explore how different disciplines have accommodated the supply, process, demand, and control uncertainties; and provide insights for future research on the dynamics of remanufacturing systems.

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Section: Forecasting In Closed-loop Supply Chainssupporting

confidence: 84%

The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems

Goltsos

Ponte

Wang

et al. 2018

International Journal of Production Research

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“…Each region will form a state interval i S . 12 [ , ]( 1, 2 , , ) . We take the curve in the middle of the interval to be predict curve.…”

Section: The Grey-markov Prediction Modelmentioning

confidence: 99%

Research on Prediction of Reverse Returned Logistics Based on Grey-Markov Model

Luo¹

2016

IJUNESST

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“…smart phones (Kiesmüller and Van der Laan 2001;Sodhi and Reimer 2001;Savage et al 2006;Wakolbinger et al 2014). In order to cope with growing waste streams, regulations like the Waste of Electric and Electronic Equipment (WEEE) Directive (Directive 2002/96/EC) have been established to deal with the challenges of products at their end of life and to contribute to the aim of minimizing waste.…”

Section: Introductionmentioning

confidence: 99%

Sustainable sourcing of strategic raw materials by integrating recycled materials

2017

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In this paper we investigate a manufacturer's sustainable sourcing strategy that includes recycled materials. To produce a short life-cycle electronic good, strategic raw materials can be bought from virgin material suppliers in advance of the season and via emergency shipments, as well as from a recycler. Hence, we take into account virgin and recycled materials from different sources simultaneously. Recycling makes it possible to integrate raw materials out of steadily increasing waste streams back into production processes. Considering stochastic prices for recycled materials, stochastic supply quantities from the recycler and stochastic demand as well as their potential dependencies, we develop a single-period inventory model to derive the order quantities for virgin and recycled raw materials to determine the related costs and to evaluate the effectiveness of the sourcing strategy. We provide managerial insights into the benefits of such a green sourcing approach with recycling and compare this strategy to standard sourcing without recycling. We conduct a full factorial design and a detailed numerical sensitivity analysis on the key input parameters to evaluate the cost savings potential. Furthermore, we consider the effects of correlations between the stochastic parameters. Green sourcing is especially beneficial in terms of cost savings for high demand variability, high prices of virgin raw material and low expected recycling prices as well as for increasing standard deviation of the recycling price. Besides these advantages it also contributes to environmental sustainability as, compared to sourcing without recycling, it reduces the total quantity ordered and, hence, emissions are reduced.

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An inventory model with dependent product demands and returns

Cited by 127 publications

References 6 publications

The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems

The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems

Research on Prediction of Reverse Returned Logistics Based on Grey-Markov Model

Sustainable sourcing of strategic raw materials by integrating recycled materials

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