Buyback Cost Research Articles

Ex-ante versus ex-post buyback pricing: An experimental study

We investigate behaviors and performance of a supply chain, in which a supplier uses buyback contracts to transact with a retailer under stochastic market demand. We compare ex-ante versus ex-post buyback pricing—the supplier decides the buyback price before demand realization in the former, but after demand realization in the latter. Theoretical analyses predict that the retailer order quantity and the supply chain efficiency are lower under ex-post buyback pricing. However, in experiments with human subjects playing both the supplier and retailer, we observe the opposite: the retailer order quantity and the supply chain efficiency are significantly higher under ex-post buyback pricing. Several behaviors are found significant. First, the supplier exhibits weaker advantageous fairness concern under ex-ante buyback pricing than under ex-post buyback pricing. Second, the supplier over-weights the buyback cost under the former, but under-weights (reciprocates) under the latter. Third, the retailer’s fairness concern is weaker under the latter. Fourth, the retailer exhibits trust behavior with the supplier under the latter. These drivers lead to less rejection and higher order quantity under ex-post buyback pricing than under ex-ante buyback pricing. Our results shed light on how human behaviors change with the decision timing and benefit supply chain performance.

Renegotiation Strategy of Public-Private Partnership Projects with Asymmetric Information—An Evolutionary Game Approach

The characteristics of public-private partnerships (PPPs) determine that renegotiation is inevitable. Moreover, the strategic choice of the government and investors during renegotiation is critical for the project to continue. Previous studies suggested that the government’s decision-making mistakes and investors’ opportunism during renegotiation are the significant reasons for project failures. However, most of the research focused on the behavioral decision of one party while few have applied evolutionary game theory to study the mutual influence of the strategy choices of both parties involved. To address this issue, this paper established an evolutionary game model of the government’s and investors’ renegotiation strategies, and analyzed the evolutionary stability strategy and related parameters. The results showed that the government’s selection of strategy is based on two values, i.e., the buyback cost and the difference between subsidy cost and the expected social benefit of the project in the future. The higher the expected social benefit, the higher the probability that the government chooses to maintain the project. Besides, investors’ strategy is mainly determined by speculative net benefit and financial status. The probability of investors’ opportunism is positively correlated with the speculative net benefit and negatively correlated with the project benefit of non-opportunism. In addition, cooperative benefits created by reasonable participation in the project will effectively restrict opportunistic behaviors, and the interactive behavior of both game players will move toward the optimal portfolio strategy. This study can provide relevant management suggestions for avoiding excessive subsidies and restraining opportunistic behaviors, which are conducive to the sustainable development of PPP projects.

Efficient Computation Resource Management in Mobile Edge-Cloud Computing

We study the computation resource management problem in mobile edge-cloud computing networks. Mobile edge servers shall first satisfy the computation requirements of mobile users and Internet of Things (IoT) devices, and then wholesale redundant computation resources to the cloud networks to maximize their profit. Due to the coarse time granularity of wholesales, computation resource buyback may happen occasionally to deal with traffic bursts. Thus, the mobile edge servers need to make a tradeoff between the wholesale profit and the buyback cost. In this paper, the computation resource management problem is modeled as profit maximization. To solve this problem, we first analyze the relationship among the reserved computation resources, the computation tasks of mobile users and IoT devices, and the buyback cost. Then, we design an efficient wholesale scheme to determine the amount of the wholesaled computation resources, by which the total expected profit of the mobile edge server can be maximized. Given the reserved computation resources, we also propose a fast-convergent realtime buyback scheme for mobile edge servers to minimize the buyback cost. Finally, the simulation results show that our proposed efficient wholesale and buyback scheme can increase the total profit while guaranteeing the computation delay of all the computation tasks, especially when the computation workloads are time-varying.

Optimal strategies for the closed-loop supply chain with the consideration of supply disruption and subsidy policy

Considering the circumstances of supply disruption and government subsidy, optimal recovery and production strategies for the closed-loop supply chain are investigated. It is assumed that the quality of returned products is exponentially distributed, buyback cost, return rate and remanufacturing cost are function of quality level of returned items, upon this, an optimal operation and subsidies policy model is built. A numerical example is used to verify the validity and credibility of the model by adopting Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The results show that the manufacturer could arrange properly the ratio of remanufacturing and manufacturing lots and the minimum quality of returned products to achieve system optimal outcome; besides, the enterprises should make effective decisions in the face of supply disruption; meanwhile, the government can adopt an appropriate subsidy policy to encourage the recovery of returned items. The research is helpful for the operation of the enterprises under supply disruption and the design of the government’s reasonable subsidy mechanism.

Effect of Inspection Policies and Residual Value of Collected Used Products: A Mathematical Model and Genetic Algorithm for a Closed-Loop Green Manufacturing System

In the green manufacturing system that pursues the reuse of used products, the residual value of collected used products (CUP) hugely affects a variety of managerial decisions to construct profitable and environmental remanufacturing plans. This paper deals with a closed-loop green manufacturing system for companies which perform both manufacturing with raw materials and remanufacturing with collected used products (CUP). The amount of CUP is assumed as a function of buy-back cost while the quality level of CUP, which means the residual value, follows a known distribution. In addition, the remanufacturing cost can differ according to the quality of the CUP. Moreover, nowadays companies are subject to existing environment-related laws such as Extended Producer Responsibility (EPR). Therefore, a company should collect more used products than its obligatory take-back quota or face fines from the government for not meeting its quota. Through the development of mathematical models, two kinds of inspection policies are examined to validate the efficiency of two different operation processes. To find a managerial solution, a genetic algorithm is proposed and tested with numerical examples.

Stochastic integrated manufacturing and remanufacturing model with shortage, rework and quality based return rate in a closed loop supply chain

Over the last few decades, inventory management of produced, recovered, and returned items in the closed loop supply chain (CLSC) systems has been significantly taken into consideration. Most of available works in the literature assumed that manufactured and remanufactured items have the same quality. However in practices, some customers perceive remanufactured items as lower quality products rather than newly produced items. Therefore, this paper assumes demands for manufactured items and remanufactured ones are not same. This assumption causes lost sales in which there are shortage periods for both produced and reproduced items. In the real-life production systems, the generation of nonconforming items is inevitable owing to deteriorating process or other uncontrollable factors. In order to take this issue into account, the production and reproduction processes are assumed to be imperfect as it can produce some defectives which would be reworked in the same cycles. Moreover, to make the study realistic, we assume the return rate of used items as a variable function which depends on the minimum acceptable quality level of returns. Furthermore, in this research the quality of returned items is considered as a random variable and based on this assumption, buyback cost, remanufacturing cost and salvage value depend on quality level of returned items. Basically, three different stochastic models, with different probability distribution functions, are mathematically developed for multiple manufacturing and remanufacturing cycles. A solution procedure is introduced and then there numerical studies are provided to show the applicability of the developed models and also to perform a sensitivity analysis. Finally, conclusion and future researches are presented.

Coordinating a multi-retailer decentralized distribution system with random demand based on buyback and compensation contracts

Purpose: The purpose of this paper is to set up the coordinating mechanism for a decentralized distribution system consisting of a manufacturer and multiple independent retailers by means of contracts. It is in the two-stage supply chain system that all retailers sell an identical product made by the manufacturer and determine their order quantities which directly affect the expected profit of the supply chain with random demand. Design/methodology/approach: First comparison of the optimal order quantities in the centralized and decentralized system shows that the supply chain needs coordination. Then the coordination model is given based on buyback cost and compensation benefit. Finally the coordination mechanism is set up in which the manufacturer as the leader uses a buyback policy to incentive these retailers and the retailers pay profit returns to compensate the manufacturer. Findings: The results of a numerical example show that the perfect supply chain coordination and the flexible allocation of the profit can be achieved in the multi-retailer supply chain by the buyback and compensation contracts. Research limitations: The results based on assumptions might not completely hold in practice and the paper only focuses on studying a single product in two-stage supply chain. Practical implications: The coordination mechanism is applicable to a realistic supply chain under a private information setting and the research results is the foundation of further developing the coordination mechanism for a realistic multi-stage supply chain system with more products. Originality/value: This paper focused on studying the coordination mechanism for a decentralized multi-retailer supply chain by the joint application of the buyback and compensation contracts. Furthermore the perfect supply chain coordination and the flexible allocation of the profit are achieved.

Optimal strategies for manufacturing/remanufacturing system with the consideration of recycled products

This paper analyzes the model of the recycled products which are considered with the minimum quality level in manufacturing/remanufacturing system. In this model, a constant demand is satisfied by manufacturing raw materials and remanufacturing recycled products which are up to the quality level. It is assumed that functions of recycling rate, buyback cost and remanufacturing cost are depend on the minimum quality level. The quality level of recycled products is set to be exponential distribution and then the model is established. The results show that when the buyback cost is low (the quality of the recycled products is low), the average total cost is low, though the remanufacturing cost is high. Namely, the companies are willing to recycle the used products with low quality level. Meanwhile, the optimal strategy of recycling, manufacturing and remanufacturing is investigated here. Through construction of a solution process on Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and numerical examples with sensitive analysis, the validity of the model has been proved.