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ردیف | عنوان | نوع |
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1 |
Retailer-run resale market and supply chain coordination
بازار فروش مجدد و هماهنگی زنجیره تامین توسط خرده فروش-2021 This study proposes strategies for full coordination of a supply chain when the retailer enables buyers not only to return their product after inspection but also to resell it as used at the store after partial consumption. In recent years, mega-retailers have added resale service to their conventional business of selling new products, which is called the retailer-run resale market. Prior literature shows from the retailer’s perspective that the ultimate motive for running resale business is to reduce the volume of consumers’ product returns. Nevertheless, there is a lack of studies on the retailer’s resale business from the manufacturer’s perspective. We adopt a manufacturer’s perspective and derive strategies to motivate retailers to make decisions for the benefit of the entire supply chain in the presence of the retailer-run resale market using five commonly used types of contracts: revenue-sharing, buybacks, quantity flexibility, quantity discount, and two-part tariff. Ongoing digitalization and web security in retailing have provided a convenient environment for online transactions, which have emerged as a supply chain and become a staple for many shoppers. However, growing popularity of online shopping inevitably increases the volume of product returns because it lacks an opportunity to experience the product before purchase. Thus, an increasing number of online retailers have adopted a resale business unilaterally to reduce consumer returns. The study provides strategic guidelines for a manufacturer to induce such retailers to make decisions for joint profit maximization. Keywords: Supply chain management | Channel coordination | Product returns | Retailer-run resale market | Uncertainty of product value |
مقاله انگلیسی |
2 |
The impact of abusing return policies: A newsvendor model with opportunistic consumers
تاثیر سوء استفاده از سیاست های بازگشتی: یک مدل روزنامه فروشی با مشتری های فرصت طلب-2018 Consumers may return a product for a variety of reasons, such as the product having the wrong color or size, having poor functionality, being damaged during shipment, or simply prompting regret for an impulsive purchase. Retailers generally provide lenient return policies not only because they may signal high quality but also because they act as risk relievers for consumers’ purchasing decision processes. However, increasing product returns have become particularly challenging for the efficient management of inventory. As such, at the crux of a holistic inventory model lies the understanding of consumer return behavior. In this study, we introduce a variant of the classical single-period inventory (newsvendor) model with returns, in which heterogeneous consumers decide, based on their post-purchase valuation of the product, whether to return the product after using it. From the perspective of the retailer, such deliberate returns may abuse the return policy, which in turn may exacerbate reverse logistics and environmental costs. To that end, we incorporate demand uncertainty and consumer valuation uncertainty by explicitly gauging return probabilities and differentiated salvage values into a newsvendor model. We derive analytical results for the profit-maximizing order quantity for a single-period product that comes with a retailer return policy and exclusively identify the impact of return type as abused or normal. Also offered are closed-form optimal solutions in the cases where market demand is exponentially or uniformly distributed. Structural and numerical results lend managerial insight into how optimal ordering amount, profit, return rates and salvage values change with the price, return window, and hassle cost of returning the product.
keywords: Inventory management |Consumer behavior |Product returns |Fraudulent proclivity |Uncertain demand |Return policy |
مقاله انگلیسی |
3 |
Closed loop supply chain networks: Designs for energy and time value efficiency
شبکه های زنجیره تامین حلقه بسته: طرح های بازده انرژی و زمان-2017 Product recovery has become a viable option for many industries to realize economic gains while pro
tecting the environment. However, insufficient investment and inefficient supply chains have hampered
the viability of reuse and/or recycling because of the extended time intervals between the recycling
process of recovery and reuse. Manufacturers and distributors face the challenge and necessity to reduce
these process delays in order to recover the maximum value of the returned products through an
effective, responsive closed loop supply chain (CLSC). This paper quantitatively measures the effective
responsiveness of the CLSC model in terms of time and energy efficiency. The proposed multi-objective
mixed integer linear programming (MOMILP) model evaluates delay parameters with decision variables
that maximize profit, optimize customer surplus and minimize energy use. The model suggests decision
makers may achieve an optimal tradeoff among differing objectives in a multiple-objective CLSC sce
nario. We employed a multi-objective particle swarm optimization (MOPSO) approach to solve the
proposed MOMILP model and compared our approach with the Non-Dominated Sorted Genetic Algo
rithm (NSGA-II) for optimal solution. Results of the comparative evolutionary approaches shows that
MOPSO outperforms NSGA-II in almost all cases in achieving the best trade-off solutions. Sensitivity
analysis carried out to test the robustness of the model confirms that substantially less cost is feasible
through the reduction of return process delays. This paper aims to formulate a multi-objective CLSC
problem based on a network-flow model measuring the time value to recover maximum assets lost due
to delay at different stages of the recycle process. We also developed a particle swarm approach for a
multi-objective CLSC. Our study also offers valuable insights for designers wishing to create a product
flow network with an optimal capacity level in case of prioritized objectives scenarios.
Keywords: Closed loop supply chain | Product recovery | Time-sensitive product returns | Multi-objective particle swarm | optimization |
مقاله انگلیسی |
4 |
The impact of product returns and remanufacturing uncertainties on the dynamic performance of a multi-echelon closed-loop supply chain
تأثیر بازدهی محصول و عدم اطمینان بازسازی بر عملکرد دینامیکی زنجیره تأمین چند حلقه بسته-2017 We investigate a three-echelon manufacturing and remanufacturing closed-loop supply chain (CLSC)
constituting of a retailer, a manufacturer and a supplier. Each echelon, apart from its usual operations in
the forward SC (FSC), has its own reverse logistics (RL) operations. We assume that RL information is
transparent to the FSC, and the same replenishment policies are used throughout the supply chain. We
focus on the impact on dynamic performance of uncertainties in the return yield, RL lead time and the
product consumption lead time. Two outcomes are studied: order rate and serviceable inventory. The
results suggest that higher return yield improves dynamic performance in terms of overshoot and risk of
stock-out with a unit step response as input. However, when the return yield reaches a certain level, the
classic bullwhip propagation normally associated with the FSC does not always hold. The longer re
manufacturing and product consumption lead times result in a higher overshoot and a longer time to
recover inventory, as well as more oscillation in the step response at the upstream echelons. We also
study bullwhip and inventory variance when demand is a random variable. Our analysis suggests that
higher return yield contributes to reduced bullwhip and inventory variance at the echelon level but for
the CLSC as a whole the level of bullwhip may decrease as well as increase as it propagates along the
supply chain. The reason for such behaviour is due to the interaction of the various model parameters
and should be the subject of further analytical research. Furthermore, by studying the three-echelon
CLSC, we produce a general equation for eliminating inventory offsets in an n-echelon CLSC. This is
helpful to managers who wish to maintain inventory service levels in multi-echelon CLSCs.
Keywords: Dynamic performance | Bullwhip | Inventory variance | Remanufacturing | Closed-loop supply chain |APIOBPCS |
مقاله انگلیسی |
5 |
A hybrid CPU-GPU parallelization scheme of variable neighborhood search for inventory optimization problems
طرح موازی سازی ترکیبی cpu-gpu از جستجوی همسایگی متغیر برای مسائل بهینه سازی موجودی-2017 In this paper, we study various parallelization schemes for the Variable Neigh
borhood Search (VNS) metaheuristic on a CPU-GPU system via OpenMP and
OpenACC. A hybrid parallel VNS method is applied to recent benchmark problem
instances for the multi-product dynamic lot sizing problem with product returns
and recovery, which appears in reverse logistics and is known to be NP-hard. We
report our findings regarding these parallelization approaches and present promising
computational results.
Keywords: Variable Neighborhood Search | Parallel Computing | CPU-GPUcomputing | OpenMP | OpenACC |
مقاله انگلیسی |