Cost-sharing contract design in a low-carbon service supply chain

In this study, we investigate two important questions related to dynamic pricing in distribution channels: (i) Are coordinated pricing decisions efficient in a context where prices have carry-over effects on demand? (ii) Should firms practice a skimming or a penetration strategy if they choose to coordinate or to decentralize their activities? To answer these questions, we consider a differential game that takes place in a bilateral monopoly where the past retail prices paid by consumers contribute to the building of a reference price. The latter is used by consumers as a benchmark to evaluate the value of the product, and by firms to decide whether to adopt a skimming or a penetration strategy.

Price Coordination in Distribution Channels: A Dynamic Perspective

Under the carbon regulation mechanism, managing operational strategies is a challenging task. Green innovation is introduced into a hybrid system of manufacturing and remanufacturing to handle the carbon emission constraints in a dynamic market environment. This paper aims to investigate the joint dynamic green innovation policy and pricing strategies in a hybrid manufacturing and remanufacturing system.,This paper first considers a monopolistic manufacturer who offers brand-new products and remanufactured items at the same price to consumers. Subsequently, the authors extend their analyses to distinct pricing strategies for both newly manufactured products and refurnished ones in such a hybrid system. Two different cases are considered: a loose carbon emission constraint and a binding carbon emission constraint. By solving the dynamic optimization problem, the differential game and Pontryagin’s maximum principle are used to obtain the joint green innovation and pricing strategies.,The retail price first increases then declines over a single period. The green innovation diminishes in the same pricing decision model, while it first increases then declines in a distinct pricing decision model over a single planning horizon. The green innovation investment as well as the retail price are discouraged by an emission cap and recycling fraction. The distinct retail price fluctuates violently, and they are, in descending order of the highest peak price as follows: the newly manufactured product, the same pricing product and the repaired product. Carbon emission caps that are either too high or too low decrease the revenue of the manufacturer. A small emission constraint margin benefits the manufacturer. The recycling policy, as well as other parameters, affects whether the hybrid system attains the carbon emission constraint or not, which suggests that the recycling policy is complementary to the carbon emission constraint mechanism in the hybrid system.,These results offer managerial implications to the hybrid system in terms of green innovation, pricing strategies and recycling policy.,This paper is among the first papers to research the joint dynamic green innovation policy and pricing strategies with/without a carbon emission constraint in a hybrid manufacturing and remanufacturing system with a differential game. Moreover, this paper presents a potential way of investigating other common resource constraints by a differential game in a manufacturing/remanufacturing system or closed loop supply chain.

The joint dynamic green innovation and pricing strategies for a hybrid system of manufacturing and remanufacturing with carbon emission constraints

The dynamic customer segmentation (DCS) is a useful tool for managers in implementing marketing strategies by observing dynamic changes that are happening in the customer segments over time. The Crespo’s dynamic fuzzy c-means (CDFCM) is one of the clustering algorithms introduced in the literature for DCS. We have suggested modifications to the CDFCM algorithm owing to certain shortcomings found in it, resulting in the modified dynamic fuzzy c-means (MDFCM) algorithm. To show the performance of the MDFCM algorithm, extensive experiments were carried out in comparison with the CDFCM algorithm using a retail supermarket dataset with eleven new data updates. To validate the results of the MDFCM algorithm, the fuzzy clustering evaluation measures such as Xie-Beni (XB) index, within sum of squared error (WSSE), root mean squared error (RMSE), Kwon index, and Tang index are utilized. The experimental results show that MDFCM is the most effective clustering algorithm for DCS, and the results are tested statistically to show its significance. The MDFCM algorithm is further compared with another successful algorithm available in the literature called Fathabadi’s dynamic fuzzy c-means (FDFCM). To show the usefulness of the MDFCM algorithm, a DCS framework is proposed and it has been demonstrated through a case study.

Modified dynamic fuzzy c-means clustering algorithm – Application in dynamic customer segmentation

Remanufacturing of returned products has been increasingly recognized in industries as an effective approach to face environmental responsibility, government regulations, and increased awareness of consumers. In this paper, we address a closed-loop supply chain (CLSC) in which the manufacturer produces the brand-new products, as well as the remanufactured goods while the retailer sells these products to customers. We consider several different scenarios: the manufacturer and the retailer adopt a steady-state price or a dynamic price with reference quality effects in a centralized case; either, neither or both the manufacturer and the retailer price dynamically with reference quality effects, respectively, in a decentralized model. We solve the problem with the retailer recycling the sold copies and deduce the optimal pricing strategies while the manufacturer in charge of recovering the used items in such a CLSC. The result shows that dynamic pricing strategies are much more profitable for the supply chain and its members when compared with pricing statically; the dynamic pricing strategies with time-varying quality characterized by reference quality are more suited to a long-term and cooperative closed-loop supply chain. Moreover, the optimal recycling fraction relies on the recovery cost coefficient and proves to be uniform despite adopting a dynamic price and quality in all distinct cases.

https://www.mdpi.com/2071-1050/10/1/157/pdf

Liyan Lei

Papers

Dynamic vs. static pricing in a supply chain with advertising

The effect of the alliance between manufacturer and weak retailer on supply chain performance