Dynamic Pricing Game Under Different Channel Power Structures in a Closed-Loop Supply Chain

Under the background of low-carbon economy, cross-shareholding is introduced into the low-carbon closed-loop supply chain (CLSC) composed of a manufacturer and a retailer, a centralized and three decentralized decision-making models with different channel power structures are constructed. The recovery, emission reduction, and pricing decisions of low-carbon CLSC are studied, and a two-part-tariff contract is proposed to coordinate the low-carbon CLSC. The results indicate that under three channel power structures, the improvement of the cross-shareholding ratio and consumers’ low-carbon awareness are beneficial to improve recovery rate, carbon emission reduction and increase market demand. Under Nash Game, the profit of low-carbon CLSC can reach the centralized level which means cross-shareholding can realize the coordination of low-carbon CLSC. Under Stackelberg Game, the enterprise with larger channel power can always obtain higher profit. Cross-shareholding cannot coordinate the retailer-led low-carbon CLSC, however it can realize the partial coordination of the manufacturer-led low-carbon CLSC. Two-part-tariff contract can realize the coordination of low-carbon CLSC under both situations.

Based on the different receptivity of new and remanufactured products, considering the coexistence of “trade old for new” (TON) and “trade old for remanufactured” (TOR) programs, we develop a game model of closed-loop supply chain (CLSC) under distribution channel and direct channel. First, the conditions of TON and TOR programs are discussed under centralized decisions. Then, the optimal pricing decisions between distribution and direct channels are compared under decentralized scenarios. The results show the remanufacturing cost savings is closely related to TON and TOR programs; under the distribution channel, the price of new and remanufactured products is higher than the direct situation; under the direct channel, TOR program can promote the recycling of waste products, and the profits of the manufacturer and CLSC will be improved, while the retailer's profit will be reduced. In view of the efficiency loss of decentralized decisions, the perfect coordination of CLSC can be realized by using revenue sharing contract under distribution channel; while, to the direct channel, a profit sharing contract can coordinate the CLSC. Finally, combined with the numerical analysis to verify the above conclusions, and further analyzes the impacts of remanufactured products receptivity, products durability, residual value of waste products and remanufacturing cost savings on the profits of the manufacturer, the retailer and CLSC under different channels.

This paper studies the effects of channel power structure and participants' risk-averse attitude on differentiated pricing policies of closed-loop supply chains. It is assumed that the manufacturer is risk-averse and the retailer is risk-neutral. The manufacturer's expected utility function and the retailer's expected profit function are obtained by mean-variance theory. Then the differentiated pricing policies and profit allocation problem are discussed under three channel power structures: manufacturer-Stackelberg (MS), retailer-Stackelberg (RS) and Vertical Nash (VN) equilibrium. The optimal wholesale prices, retail prices and production quantities of new manufactured products and remanufactured products are derived and compared under different cases. Finally numerical analysis of risk-averse degree on participants' profits is given. The study has shown that the VN mode yields the best closed-loop supply chain performances, and then is the MS mode, the worst is the RS supply chain.

Retailer’s optimal CSR investment in closed-loop supply chains: the impacts of supply chain structure and channel power structure

Distribution channel and licensing strategy choice considering consumer online reviews in a closed-loop supply chain

In this paper, we consider a closed-loop supply chain (CLSC) consisting of two suppliers, one manufacturer, one risk-averse retailer and one fair-caring third-party in the presence of supply disruption. We focus on establishing a dynamic Stackelberg game model with bounded rational expectation and analyzing the game evolution process. The effects of key parameters on the Nash equilibrium solutions and their stability are investigated, as well as the complex dynamical behaviors of the CLSC system are explored by using the stability region, bifurcation graph, the largest Lyapunov exponent (LLE), strange attractors, etc. Moreover, the performance of channel members under different values of parameters is researched by utilizing the (average) expected profits or utilities index. The analysis results reveal that the excessive fast adjustment speed of the manufacturer will lead to the system losing stability and falling into chaos. Also, the retailer’s risk aversion and the third party’s fairness concerns have a destabilization effect on the Nash equilibrium point, while the possibility of supply disruption has different effects on the scope of the adjustment speed of decision variables of the manufacturer. Furthermore, in most cases, an over the top adjustment speed of the manufacturer is disadvantageous to all the channel members for more expected profits, but the third-party can achieve a better performance when the system is in periodic state. Finally, the time-delay feedback control method is proposed to eliminate the system chaos.

Reverse supply chain (RSC) is an extension of the traditional supply chain (TSC) motivated by environmental requirements and economic incentives. TSC management deals with planning, executing, monitoring, and controlling a collection of organizations, activities, resources, people, technology, and information as the materials and products move from manufacturers to the consumers. Except for a short warranty period, TSC excludes most of the responsibilities toward the product beyond the point of sale. However, because of growing environmental awareness and regulations (e.g. product stewardship statute), TSC alone is no longer an adequate industrial practice. New regulations and public awareness have forced manufacturers to take responsibilities of products when they reach their end of lives. This has necessitated the creation of an infrastructure, known as RSC, which includes collection, transportation, and management of end-of-life products (EOLPs). The advantages of implementing RSC include the reduction in the use of virgin resources, the decrease in the materials sent to landfills and the cost savings stemming from the reuse of EOLPs, disassembled components, and recycled materials. TSC and RSC together represent a closed loop of materials flow. The whole system of organizations, activities, resources, people, technology, and information flowing in this closed loop is known as the closed-loop supply chain (CLSC). In RSC, the management of EOLPs includes cleaning, disassembly, sorting, inspecting, and recovery or disposal. The recovery could take several forms depending on the condition of EOLPs, namely, product recovery (refurbishing, remanufacturing, repairing), component recovery (cannibalization), and material recovery (recycling). However, neither the quality nor the quantity of returning EOLPs is predictable. This unpredictable nature of RSC is what makes its management challenging and necessitates innovative management science solutions to control it. In this chapter, we address the order-driven component and product recovery (ODCPR) problem for sensor-embedded products (SEPs) in an RSC. SEPs contain sensors and radio-frequency identification tags implanted in them at the time of their production to monitor their critical components throughout their lives. By facilitating data collection during product usage, these embedded sensors enable one to predict product/component failures and estimate the remaining life of components as the products reach their end of lives. In an ODCPR system, EOLPs are either cannibalized or refurbished. Refurbishment activities are carried out to meet the demand for products and may require reusable components. The purpose of cannibalization is to recover a limited number of reusable components for customers and internal use. Internal component demand stems from the component requirements in the refurbishment operation. It is assumed that the customers have specific remaining-life requirements on components and products. Therefore, the problem is to find the optimal subset and sequence of the EOLPs to cannibalize and refurbish so that (1) the remaining-life-based demands are satisfied while making sure that the necessary reusable components are extracted before attempting to refurbish an EOLP and (2) the total system cost is minimized. We show that the problem could be formulated as an integer nonlinear program. We then develop a hybrid genetic algorithm to solve the problem that is shown to provide excellent results. A numerical example is presented to illustrate the methodology.

The impact of internal and external reference prices on brand choice: The moderating role of contextual variables

:Using a novel scanner data set, I study price-setting decisions of major retailers in an emerging market economy. Pricing dynamics are heterogeneous across retail chains. Heterogeneity is especially pronounced in the case of posted (as opposed to reference) prices. Furthermore, retail chains appear to set prices in a centralized fashion: most barcode/store-level prices coincide with the intrachain modal price. The relationship between reference and chain-wide prices reveals that deviations from reference prices cannot be solely attributed to shocks to local market conditions. I find strong evidence of synchronization of price changes across stores within chains but weaker evidence of synchronization across retail chains.

Investigation of near-field jet stability of a single-hole injector based on fast X-ray phase contrast imaging and image feature matching

A firm that accounts for consumer behavior sets the selling price of a product considering the reference price of consumers. In the literature, a reference price is usually modeled as depending on past selling prices. That is, past selling prices implicitly constrain the current selling price of a product. In this article, the author explicitly measures this constraint with an optimal control framework. He works on the structural properties of a general demand function, which depends on both selling and reference prices. Analytical results prove the following claims. Adjusting reference prices effects increase the price elasticity of demand, the demand function becoming flatter. Thus, the reference price effect weakens the market power of the firm. Also, the reference price effect constitutes a main driver of the dynamics of the selling price. But contrary to intuition, selling price dynamics does not systematically imitate reference price dynamics.

Eight-year performance evaluation of a field-scale zeolite permeable reactive barrier for the remediation of ammonium-contaminated groundwater

This paper explores a dual-channel closed-loop supply chain (CLSC) system consisting of a manufacturer and a retailer. The manufacturer is the CLSC Stackelberg leader. We investigate the effect of exerting marketing effort on the optimal decisions and profits of supply chain members by considering several marketing effort supported models, namely the models when the manufacturer is the investor, the retailer is the investor, and the centralized CLSC system, respectively. We propose a two-part tariff contract for coordinating the CLSC. We analytically reveal that the two-part tariff contract can coordinate the CLSC when the manufacturer is the investor but unable to coordinate supply chain when the retailer is the investor. Finally, we present the numerical analysis to uncover insights on how the consumers' preference toward the direct channel affects the optimal decisions in the dual-channel CLSC system.

We study a multi‐period, multi‐item dynamic pricing problem faced by a retailer. The objective is to maximize the total profit by choosing prices, while satisfying several business rules. The strength of our work lies in our graphical model reformulation, which allows us to use ideas from combinatorial optimization. We do not make any assumptions on the structure of the demand function. The complexity of our method depends linearly on the number of time periods but is exponential in the memory of the model (number of past prices that affect current demand) and in the number of items. We prove that the profit maximization problem is NP‐hard by showing an approximation preserving reduction from the weighted Max‐3‐SAT problem. We next introduce the discrete reference price model which is a discretized version of the reference price model, accounting for an exponentially smoothed contribution of all past prices. We show that our problem can be solved efficiently under this model. We then approximate common demand functions using the discrete reference price model. To handle cross‐item effects among multiple items, we propose to use a virtual reference price that assigns a reference price for each category of items (as opposed to a reference price for each item). To enhance the tractability of our approach, we cluster items into blocks and show how to adapt our method to include business constraints across blocks. Finally, we apply our solution approach using demand models calibrated with supermarket data and validate its practical performance.

On the base of the assumption that the recycled quantity of used products is affected by the interaction of recycling price and sales volume, this paper researches closed-loop supply chain's pricing and coordination, gives system members' optimal pricing and profits in decentralized decision and centralized decision and finds that reverse supply chain itself is in coordination and traditional forward supply chain is in incoordiantion under decentralized decision. Then it designs a revenue sharing contract which can coordinate closed-loop supply chain. At last, a numerical example is given to verify the conclusions drew in this paper.