pricing

Escalating freshwater depletion and contamination driven by anthropogenic activities significantly threaten global water accessibility, jeopardizing food security, environmental integrity, and economic prosperity. The dearth of water resources worldwide and the significance of the adverse effects of wastewater pollution on the environment have promoted the discussion of water and wastewater treatment in the supply chain in this research. A subsidy has been proposed to encourage producers to treat wastewater to create a sustainable supply chain. The government will determine the subsidy. Wastewater generated during the production process undergoes treatment and is subsequently marketed for reuse within the supply chain. Wastewater treatment coupled with the reuse of treated wastewater in the supply chain effectively reduces freshwater consumption. Subsequently, the green manufacturer determines the selling price of each green product unit by considering the cost of wastewater treatment, the rise in fresh water consumption due to the rebound effect, and the impact of the amount of government subsidy for wastewater treatment. Given the concurrent roles of the government and the green producer within this domain and the impact of their decisions on each other, the game theory approach has been employed for the first time for pricing the green product under the mentioned conditions. This holistic approach offers a more realistic appraisal of freshwater consumption in production and paves the way for formulating effective water management strategies towards sustainable production. In this study, the designed game has been solved under two structures, namely Nash and Stackelberg. A parametric analysis of the parameters of the problem is conducted. A real-life case study from the food industry of Iran is solved. The analysis of the results revealed that wastewater treatment for both the government and the green producer as players in both structures generally yield higher profits than not treating wastewater.

In recent years, manufacturers have started selling their products online. This study examines pricing in a supply chain involving manufacturing, retailers, logistics service providers, and integrators. There are three products in this chain: two physical products from manufacturers and a service product from logistics providers. Physical products are sold online and in retail stores, with online purchases including two products. The problem is examined in four scenarios, including decentralized, manufacturer integration with retailer, functional logistics service provider integration with logistics service integrator, and a combined approach of manufacturer integration with retailer and functional logistics service provider integration with logistics service integrator. This paper introduces a novel approach by analyzing the impact of logistics supply chain members, focusing on logistics service levels and pricing. The study aims to explore how the integration of supply chain members influences the profits and service levels of other stakeholders. The results indicate that integrating two supply chain members typically lowers profits for other members. Integrating a logistics service provider and integrator can increase manufacturer profit and decrease retailer profit in certain cases, while in other cases profits remain unchanged. Similarly, integrating manufacturer and retailer usually results in decreased profits for logistics service providers and integrators. The integration of functional logistics service provider and logistics service integrator has an impact on the relationship of parameters with service level. In the decentralized scenario, if service price and service coefficients increase, service levels increase. It also increases service levels as the cost of service increases.

This research aims to configure a four-layer supply chain including suppliers, manufacturers, distribution centers and markets in the direct direction and three facilities including waste collection, separation and disposal centers in the reverse direction. The increase in environmental risks and lack of resources make it necessary to pay attention to the circular economy and products in the reverse chain of the supply network. On the other hand, making appropriate economic and environmental decisions at different stages of the life cycle of products increases the profitability of the supply chain network.

The reverse supply chain consists of collection centers, a separation center and a disposal center. Also, three types of grade 1, 2 and 3 products are produced in this network. Grade 1 product is a product in which all the components and raw materials are original and grade 1 and are procured directly from suppliers and then produced in their parts production centers, and finally, grade 1 product is provided to the customer. In Grade 2 products, all their constituent parts are reusable consumable parts that are provided to production centers through the reverse chain and from the separation center. These parts are then assembled and finally, the 2nd grade product will be produced. Grade 3 products are products whose constituent parts are a combination of original or grade 1 parts and reusable parts. The forward supply chain begins with the procurement of raw materials from suppliers. It is assumed that all the production steps are internal and are done inside the desired production centers. Then, the manufactured products are sent to the customer market.

In the reverse chain of the proposed network, the products are purchased from the customers by the collection centers after the passage of time and their depreciation. The collected returned products are then transported to the separation center. At the disassembly center, the disassembled parts will be inspected for quality and classified into reusable and non-reusable categories. The first category is the parts whose consumption has ended. They return to the production centers. The second category is considered waste and is transferred to the disposal center. To solve the proposed model in practical dimensions, genetic algorithms and particle swarm optimization have been used to find the optimal solution. By examining the results and analyses performed and considering the relative deviation percentage index and solution time, it was determined that the genetic algorithm had better performance.

Originality/Value:

 In the presented network, the life cycle of the product is considered, and therefore, it is a multi-cycle model. The facility of distribution centers is placed in the network between the two facilities of producers and customer markets. We will consider several separation and disposal centers. There are three demand types and return rates for each product type. A mixed integer linear programming model is presented with the aim of maximizing economic profit during the product life cycle and pricing. Due to the computational complexity in medium dimensions, a genetic algorithm has been used to find the optimal solution. The efficiency of the genetic algorithm is proved by numerical analysis.

With the increase in environmental pollution due to the disposal of used products in the environment, recovery of such products at the end of their life cycle has become one of the important issues in the field of reverse logistics and sustainable production. Remanufacturing is one of the options for used products recovery with high economic advantages and the least harmful environmental effects. The simultaneous planning of the production of new products and remanufacturing of used ones forms a combined manufacturing/remanufacturing system, which is among the complex issues in the field of production systems planning. The combined pricing, warranty, and competition considerations has so far not been seriously investigated in this field. The aim of this research is to create an optimal production plan for a multi-period hybrid manufacturing/remanufacturing system, where the producer decides on the price, the amount of production and the warranty period for both new and remanufactuted products. To achieve this goal, a multi-period mixed integer non-linear programming (MINLP) model is built. Only new products are produced and sold in the first period, then the used products (cores), in different quality levels, are purchased from customers in the following periods, and hence, remanufacturing is added to the model. Both types of products are sold in the same market, so there is competition between them to gain more market share. Due to the complexity of the developed model, particle swarm optimization (PSO), and simulated annealing (SA) algorithms are used for its solution. Numerical results show the efficiency and effectiveness of the proposed model and solution approaches.

Consider two substitutable electricity home-appliances that are produced by two competing manufacturers and are then sold to customers by two agencies. In the considered market, customers’ demands for these products are specified based on the selling prices as well as their energy-efficiency levels. To attract customers, one of the manufacturers aims to invest on the energy-efficiency improvement of his products. In this research, the pricing and energy-efficiency decisions are investigated on the mentioned problem. Moreover, the game theory is applied to set these decisions. In this setting, the problem is analyzed under Nash and Chain-to-chain games. In Nash game, the competition among the members is independently considered, while the products’ supply chains compete in Chain-to-chain game. Finally, the decisions are analyzed and some results and insights are provided. The results indicate that under some conditions, it is possible to attract more customers and obtain higher profits by investing on the energy-efficiency improvement. Due to the competition between both supply chains, the members’ profits in the cooperative mode ​​may be set lower than in the competitive mode. Also, policies that reduce the cost for the energy-efficiency improvement of an electricity appliance will be beneficial for its members.

The purpose of the current research is to design a green supply chain pricing model with a multi-criteria decision-making approach and game theory (case study: home appliance industry). In this research, after library study and identification of key indicators in predicting green supply chain pricing, using the fuzzy Delphi method, the screening of indicators was done in three stages, and out of 20 indicators, based on the opinions of 13 experts, 13 indicators were selected and based on the priority selection index approach, company D entered the game theory as the leader company because it had the highest priority. Finally, based on the game theory, the scenario between 4 members of the supply chain was evaluated and analyzed, and the best and worst scenarios were also introduced. Also, in order to test the structural validity of the proposed model, information related to the green supply chain of 9 selected home appliance companies was implemented using MATLAB software.

In today's world, due to the increase in competition between organizations and the increase in environmental and social concerns, sustainable supply chain management is a competitive advantage for organizations. Sustainable supply chain management is an approach in supply chain management with the aim to consider economic, environmental and social issues together. In this study, we consider two-echelon supply chain that consists both manufacturer and retailer in which the manufacturer decides on green quality of the product and level of health products donation as a social responsibility, and retailer decides on the selling price of the product to the end customers. We assumed that the customer has a social and environmental awareness and the demand is a function of the selling price, level of donation and green quality of the product. Generally, with an increase in the level of donation and the greenness of the product, the demand increases, and with an increase in the selling price of the product, the demand decreases. The results show that the coordination model in this sustainable supply chain is an appropriate alternative in comparison with the other models.

In this paper, we consider a Cournot Market for Chain-To-Chain Competition, which includes two distinct competing supply chains. Each supply chain has one Manufacturer, one Visitor, and one Retailer. The Retailer is in common between the two chains. This article will investigate the impact of using visitors to attract retailers as much as possible by the manufacturer. Each visitor should try to convince retailers to order more by paying a cost named Visit Cost in this article. After selling each unit of considered products, the manufacturer would pay a percentage of the wholesale price. It is assumed that there is a Stackelberg game between the manufacturer and visitor in each supply chain, in which the manufacturer is the leader. Furthermore, there is a Nash competition between manufacturers and the retailer.

In the current study, the competition between two substitutable products is investigated on a supply chain containing two manufacturers and two sellers. In this structure, two substitutable products are made by two competing manufacturers and are then delivered to customers through two competing sellers. One of the manufacturers sells his products with no investment on advertising, whereas another one aims to attract more customers by investing on the advertisement level. In this setting, a cooperative advertising contract is implemented between the manufacturer and seller of the second product in which the seller undertakes a portion of the related investment. Then, the game theory is applied to make the pricing and advertising decisions under the considered problem. Note that in the previous studies, the issue of the cooperative advertising has been considered for a specific product and then the game theory has been used in order to set the decisions among its supply chain members, while in this research, two substitutable products are considered and the effect of implementing a cooperative advertising contract is investigated on their demands and the profit values of their supply chain members. Regarding the results, increasing the elasticity of the demand for a product with respect to its advertisement level leads to enhancing the profits for its members and reducing the profits for the others. Moreover, if the required budget does not exceed a specific value, then investing on the advertisement level of a product is beneficial for its members.

Today online retailers all over the world are looking to oer virtual reality service through their online channels in order to attract customers to purchase product online and increase sales by creating a sense of customer condence. Virtual reality service provides information about how a product ts a customer and closes the gap between online and oine retailers. However, such services also facilitate consumer webrooming behavior, which may reduce online demand and intensify competition between traditional and online retailers. Webrooming behavior means customers use virtual reality service in the online channel and view the specications of the product, but they buy the product in the oine channel. On the other hand, providing virtual reality through the online channel due to the conditions of the testing products before the purchase can have a positive impact on the rate of returned products. This study aims to investigate the optimal amount of investment in virtual reality service and its impact on the rate of return, as well as the impact of webrooming behavior on pricing and competition between the two channels. To address this issue, we develop a dual-channel supply chain including an online and a traditional retailer under two dierent scenarios. In the rst scenario, the online retailer oers a partial refund in his channel to attract customers, but he does not provide virtual reality service. In the second scenario, the online retailer provides virtual reality service in the online channel to compete with the traditional retailer. The results show that providing virtual reality will have a positive eect on the demand of both channels and will increase retail prices on both online and oine channels. Also, providing virtual reality in the online channel causes the customers to view and test the product before buying. Therefore, the number of returned products was reduced.

In this paper, the problem of simultaneous production planning, inventory control, transportation, and pricing of perishable goods (with limited lifetime) in a twostage supply chain is investigated. Extensive research has examined each of the important supply chain subproblems, including production and inventory planning, distribution and transportation planning, and pricing, separately. On the other hand, the global optimum solution can be achieved when these sub-problems are solved simultaneously and in the form of an integrated model. However, less research has focused on integrating these decisions. There are also many research papers that assuming inventory items can be stored indenitely to meet future demands. While there are certain types of products that either decay or become obsolete over time and, as a result, become unused. Perishable goods include food, vegetables, human blood, photographic lms, etc. which have a maximum shelf life to use. If the product is perishable, then there will be more need for integrated decision-making. Another important issue to consider is the uncertainty of the available data. In other words, the parameters in uencing these decisions are not deterministic and this uncertainty must be controlled to minimize the possibility of losses associated with the decisions. A non-deterministic multi-period optimization model, in which demand uncertainty depends on the product price and the remaining periods, is proposed to solve the problem. In the proposed model, robust possibility planning is used to deal with uncertainty. To validate the proposed model and solution approach, data from a case study (taken from Patron Company, which produces green mortar and is used in the steel industry) were used. The results of computational experiments show that by applying the proposed approach while making integrated decision-making, supply chain costs can be reduced by an average of 16%. Also, by comparing the proposed robust possibility approach with the nominal approach in uncertainty control, it is observed that the maximum and average deviations from optimality are reduced by 46% and 11%, respectively.