Optimal pricing strategies with remanufacturing technological innovation under different power structures

Author(s):  
Renbang Shan ◽  
Li Luo ◽  
Bowen Xiang
Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Zhenyang Pi ◽  
Weiguo Fang

This paper studies the implication of channel discrepancy between the retail and direct channels in a dual-channel supply chain consisting of one common retailer and two manufacturers in which the manufacturers may have different market powers. Each manufacturer provides a substitutable product and opens an online channel to customers directly. We develop an analytical model to derive the optimal pricing strategies by using game theory and the backward induction method, and we examine related properties under three market power structures while considering channel discrepancy, including the Nash equilibrium, the Manufacturers leader Stackelberg, and the M1 leader Stackelberg models (denoted as the N, MS, and M1S models, respectively). Numerical simulations are examined to reveal and verify the effect of channel discrepancy on optimal prices, demands, and profits. We find that a higher level of channel discrepancy induces higher prices, demands, and profits for each member in both channels, while this kind of stimulating impact for the leader manufacturer who obtains a higher level of channel discrepancy will be more significant than it is for the other members in the three models. In addition, the profit of the supply chain in the N model is always higher than it is in the MS model, while it may be higher or lower than it is in the M1S model depending on the level of channel discrepancy.


Algorithms ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 186
Author(s):  
Tao Li ◽  
Yan Chen ◽  
Taoying Li

The problem of pricing distribution services is challenging due to the loss in value of product during its distribution process. Four logistics service pricing strategies are constructed in this study, including fixed pricing model, fixed pricing model with time constraints, dynamic pricing model, and dynamic pricing model with time constraints in combination with factors, such as the distribution time, customer satisfaction, optimal pricing, etc. By analyzing the relationship between optimal pricing and key parameters (such as the value of the decay index, the satisfaction of consumers, dispatch time, and the storage cost of the commodity), it is found that the larger the value of the attenuation coefficient, the easier the perishable goods become spoilage, which leads to lower distribution prices and impacts consumer satisfaction. Moreover, the analysis of the average profit of the logistics service providers in these four pricing models shows that the average profit in the dynamic pricing model with time constraints is better. Finally, a numerical experiment is given to support the findings.


2020 ◽  
Vol 19 (1) ◽  
pp. 1-41
Author(s):  
Nicolas Dupuis ◽  
Marc Ivaldi ◽  
Jerome Pouyet

AbstractWe study the welfare impact of revenue management, a practice which is widely spread in the transport industry, but whose impact on consumer surplus remains unclear. We develop a theoretical model of revenue management allowing for heterogeneity in product characteristics, capacity constraints, consumer preferences, and probabilities of arrival. We also introduce dynamic competition between revenue managers. We solve this model computationally and recover the optimal pricing strategies. We find that revenue management is generally welfare enhancing as it raises the number of sales.


2020 ◽  
Vol 14 (1) ◽  
Author(s):  
Guodaohou Song ◽  
Xiaofang Wang

AbstractProduction cost can be influenced by previous sales in an uncertain way. In reality, production cost may decrease in the number of initial buyers due to the learning effect, or increase in the number of initial buyers due to the quality-improving pressure from negative comments of unhappy users. Taking this uncertainty into account, this paper studies the optimal intertemporal pricing strategies of a firm when selling to strategic customers in two periods where production cost in the second period randomly changes with the number of buyers in the first period. Our results suggest how firms should adjust their optimal pricing strategies under different market circumstances.


2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Doo Ho Lee

This work investigates the optimal pricing strategies of a server and the equilibrium behavior of customers in an unobservable M/M/1 queueing system with negative customers and repair. In this work, we consider two pricing schemes. The first is termed the ex-post payment scheme, where the server charges a price that is proportional to the time spent by a customer in the system. The second scheme is the ex-ante payment scheme, where the server charges a flat rate for all services. Based on the reward-cost structure, the server (or system manager) should make optimal pricing decisions in order to maximize its expected profit per time unit in each payment scheme. This study also investigates equilibrium joining/balking behavior under the server’s optimal pricing strategies in the two pricing schemes. We show, given a customer’s equilibrium, that the two pricing schemes are perfectly identical from an economic point of view. Finally, we illustrate the effect of several system parameters on the optimal joining probabilities, the optimal price, and the equilibrium behavior via numerical examples.


2009 ◽  
Vol 23 (2) ◽  
pp. 205-230 ◽  
Author(s):  
Jean-Philippe Gayon ◽  
Işılay Talay-Değirmenci ◽  
Fikri Karaesmen ◽  
E. Lerzan Örmeci

We study the effects of different pricing strategies available to a production–inventory system with capacitated supply, which operates in a fluctuating demand environment. The demand depends on the environment and on the offered price. For such systems, three plausible pricing strategies are investigated: static pricing, for which only one price is used at all times, environment-dependent pricing, for which price changes with the environment, and dynamic pricing, for which price depends on both the current environment and the stock level. The objective is to find an optimal replenishment and pricing policy under each of these strategies. This article presents some structural properties of optimal replenishment policies and a numerical study that compares the performances of these three pricing strategies.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lei Li ◽  
Shaojun Ma ◽  
Xu Han ◽  
Chundong Zheng ◽  
Di Wang

PurposeBig data analytics (BDA) and machine learning (ML) can be used to identify the influencing factors of online service supply chains (OSSCs) and can help in the formulation of optimal pricing strategies. This paper analyzes the influencing factors of customer online shopping from the demand-side perspective and formulates optimal pricing strategies from the supply-side perspective.Design/methodology/approachThis paper uses ML and the Stackelberg game approach to discuss OSSC management. ML's feature selection algorithm is used to identify the important influencing factors of 12,330 customers' online shopping intention data using four different classifiers. The Stackelberg game approach is used to analyze the pricing strategies of integrators and suppliers in OSSCs.FindingsFirst, the feature selection algorithm can improve the efficiency of optimization in big data samples of OSSCs. Second, the level of visualization and the quality of information (page value) will affect the purchase behavior of customers. Finally, the relationship between the optimal pricing and the level of visualization is obtained through the Stackelberg game approach.Practical implicationsThis paper reveals the phenomenon of “mystery customers,” and the results of this paper can provide insights and suggestions regarding the decision-making behavior of integrators and suppliers in OSSC management.Originality/valueConsidering customer behavior intention, this paper uses a data-driven method to explore the influencing factors and pricing strategies of OSSCs. The empirical results enrich the existing OSSC management research, proposing that the level of product visualization and information quality plays an important role in OSSCs.


2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Du Zhao ◽  
Xumei Zhang ◽  
Tinghai Ren ◽  
Hongyong Fu

This paper examines optimal pricing in a two-tier product and service supply chain consisting of a manufacturer and a retailer in the context of vertical competition in extended warranty in two cases: one considering the retailer’s fairness concerns and one without considering the retailer’s fairness concerns. A manufacturer-dominated product and service supply chain game-theoretic model on the Stackelberg model is developed to analyse how the level of vertical competition in extended warranty service and the intensity of a retailer’s fairness concerns influence the optimal pricing of products and extended warranties for the manufacturer and retailer. This study finds the following: (i) Two parties of the supply chain employ differential pricing strategies for extended warranties when the retailer has fairness concerns. (ii) Compared to the same pricing strategies for extended warranty service when the retailer has no fairness concerns, the increase of competition intensity of vertical extended warranty service will enlarge the price difference of extended warranty service. Meanwhile, it is the intensity of fairness concerns that determines the influences of retailer’s fairness concerns on the price difference of extended warranties. (iii) If no fairness concerns are raised, an increase in the level of vertical competition in extended warranty service would benefit both supply chain parties, rather than hurting their profit. If the retailer is fair-minded, its fairness utility increases when the intensity of the fairness concerns rises in a reasonable range and decreases when the intensity exceeds the reasonable range, but for the manufacturer, its profits will be damaged as long as the retailer raises fairness concerns.


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