Game-theoretic analysis of supply chain coordination under advertising and price dependent demand

Supply chain members cannot act independently and they need to act as a part of a unified system and coordinated with other members. Therefore, a coordination mechanism may be necessary to motivate members to achieve coordination. In this paper, the coordination problem is studied in a two-level supply chain consisting of a supplier and a retailer where demand is a function of price and advertising expenditures in two scenarios. The first scenario is “No coordination”, and the other scenario is “coordination with Revenue sharing contract”. The models are solved using game theory, Cooperative and Nash equilibrium. Finally, numerical examples are presented indicating that the average expected profit in the second scenario, coordination with revenue sharing, is higher than the first scenario. In addition numerical examples indicate that as price and advertising elasticity to demand increase, profitability of supply chain decreases

Solving closed-loop supply chain problems using game theoretic particle swarm optimisation

© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. In this paper, we propose a closed-loop supply chain network configuration model and a solution methodology that aim to address several research gaps in the literature. The proposed solution methodology employs a novel metaheuristic algorithm, along with the popular gradient descent search method, to aid location-allocation and pricing-inventory decisions in a two-stage process. In the first stage, we use an improved version of the particle swarm optimisation (PSO) algorithm, which we call improved PSO (IPSO), to solve the location-allocation problem (LAP). The IPSO algorithm is developed by introducing mutation to avoid premature convergence and embedding an evolutionary game-based procedure known as replicator dynamics to increase the rate of convergence. The results obtained through the application of IPSO are used as input in the second stage to solve the inventory-pricing problem. In this stage, we use the gradient descent search method to determine the selling price of new products and the buy-back price of returned products, as well as inventory cycle times for both product types. Numerical evaluations undertaken using problem instances of different scales confirm that the proposed IPSO algorithm performs better than the comparable traditional PSO, simulated annealing (SA) and genetic algorithm (GA) methods

Supply chain forecasting when information is not shared

The operations management literature is abundant in discussions on the benefits of information sharing in supply chains. However, there are many supply chains where information may not be shared due to constraints such as compatibility of information systems, information quality, trust and confidentiality. Furthermore, a steady stream of papers has explored a phenomenon known as Downstream Demand Inference (DDI) where the upstream member in a supply chain can infer the downstream demand without the need for a formal information sharing mechanism. Recent research has shown that, under more realistic circumstances, DDI is not possible with optimal forecasting methods or Single Exponential Smoothing but is possible when supply chains use a Simple Moving Average (SMA) method. In this paper, we evaluate a simple DDI strategy based on SMA for supply chains where information cannot be shared. This strategy allows the upstream member in the supply chain to infer the consumer demand mathematically rather than it being shared. We compare the DDI strategy with the No Information Sharing (NIS) strategy and an optimal Forecast Information Sharing (FIS) strategy in the supply chain. The comparison is made analytically and by experimentation on real sales data from a major European supermarket located in Germany. We show that using the DDI strategy improves on NIS by reducing the Mean Square Error (MSE) of the forecasts, and cutting inventory costs in the supply chain

Pricing Policies for a Dual-Channel Retailer with Cross-Channel Returns

Many retailers are adopting a dual-channel retailing strategy (DCRS) in which products are offered through two channels: physical stores and online stores. Due to regulations or competitive measures, such a strategy allows customers who find a purchase unsatisfactory to obtain a full refund through a same-channel return or a cross-channel return. No papers have collectively studied the aforementioned types of customer returns in a dual-channel context. This paper studies optimal pricing policies for a centralized and decentralized dual-channel retailer (DCR) with same- and cross-channel returns. How dual-channel pricing behavior is impacted by customer preference and rates of customer returns is discussed. It is found, through sensitivity analysis, that when a channel with significant customer preference faces a high rate of returns, decentralized channels generate a greater system profit for retailers than coordinated channels that have a unified pricing strategy. A DCR with a Stackelberg scheme has the proclivity to be more profitable when under the leadership of a channel with a high rate of returns and significant customer preference

The impact of sharing customer returns information in a supply chain with and without a buyback policy

In this paper, we examine a single period problem in a supply chain in which a Stackelberg manufacturer supplies a product to a retailer who faces customer returns and demand uncertainty. We show that the manufacturer incurs a significant profit loss with and without a buyback policy if it fails to account for customer returns in the wholesale price decision. Under the assumption that the retailer is better informed than the manufacturer on customer returns information, we show that without a buyback policy, the retailer prefers not to share if the manufacturer overestimates while it prefers to share customer returns information if the manufacturer underestimates this information. If the manufacturer offers a buyback policy, we have the opposite results. We also discuss incentives to share the customer returns information and some of the issues that are raised in sharing this information.Customer returns Information sharing Customer returns policies Buyback policies

Optimization of a Dual-Channel Retailing System with Customer Returns

A plethora of retailers have begun to embrace a dual-channel retailing strategy wherein items are provided to consumers through both an online store and a physical store. As a result of standards and competitive measures, many retailers provide buyers who are unhappy with their purchases with the ability to achieve a full refund. In a dualchannel retailing system, full reimbursements can be done through what is called a crosschannel return, when a buyer purchases a product from an online store and returns it to a physical store. They can also be done through what is called a same-channel return, when a buyer purchases a product from a physical store and returns it back to the physical store, or purchases a product from an online store and returns it back to the online store. No existing research has examined all common types of customer returns in the context of a dual-channel retailing system. Be notified that the practice of cross-returning an item purchased from the physical store back to the online store is not common. Thus, it is not considered in this dissertation. We first study the optimal pricing policies for a centralized and decentralized dual-channel retailer (DCR) with same- and cross-channel returns. We consider two factors: the dual-channel retailer’s performance under centralization with unified and differential pricing schemes, and the dual-channel retailer’s performance under decentralization with the Stackelberg and Nash games. How dual-channel pricing behaviour is impacted by customer preference and rates of customer returns is discussed. In this study, a channel’s sales requests is a linear function of a channel’s own pricing strategy and a cross-channel’s pricing strategy. The second problem is an extension of the first problem. The optimal pricing policies and online channel’s responsiveness level for a centralized and decentralized dual-channel retailer with same- and cross-channel returns are studied. Indeed, the online store is normally the distribution centre of the enterprise and is not limited to the customers in its neighbourhood. Also, the online store experiences a much higher return rate compared to the physical store. Thus, it has the capability and the need to optimize its responsiveness to customer returns along with its pricing strategy. A channel’s sales requests, in the second problem, is a linear function of a channel’s own price, a crosschannel’s price, and the online store’s responsiveness level. The third problem studies the dilemma of whether or not to allow unsatisfactory online purchases to be cross-returned to the physical store. If not properly considered, those returns may create havoc to the system and a retailer might overestimate or underestimate a channel’s order quantity. Therefore, we study and compare between four vi different strategies, and propose models to determine optimal order quantities for each strategy when a dual-channel retailer offers both same and cross-channel returns. Several decision making insights on choosing between the different cross-channel return strategies and some properties of the optimal solutions are presented. From the retailer’s perspective of outsourcing the e-channel’s management to a third party logistics and service provider, we finally study three different inventory strategies, namely transaction-based fee, flat-based fee, and gain sharing. For each strategy, we find both channels’ optimal inventory policies and expected profits. The performances of the different strategies are compared and the managerial insights are given using analytical and numerical analysis. Methodologies, insights, comparative analysis, and computational results are delivered in this dissertation for the above aforementioned problems

A Study on the Effect of New Technologies on Supply Chain Coordination

In this globalized economy, the fierce competition in the market, added to the increasingly exigences from customers demanding products with more added value and lower prices, force organizations to be always at the vanguard to maintain their positioning in the market. One critical ingredient for maintaining the competitive advantage is the acquisition and implementation of new technologies for achieving process and product enhancement. This is specially the case for high tech industries in sectors like aerospace, pharmaceutic and telecommunication, to name but a few. But investment in new technologies is a challenging decision due to their complexity for implementation and the cost involved. Therefore, it is of utmost importance to understand the effect of new technologies on the performance of the acquiring company and on its supply chain. Although the existence of an ample number of empirical studies in the current literature describing the relation between supply chain (SC) operation and new technologies acquisition, analytical research on this matter is quite scarce. In this thesis, our objective is to model and analyze the effect of new technologies on the SC members performance. We propose two main directions of research: (1) impact of technology transfer among SC members; and (2) impact of technology investment in the SC. In the first direction, we consider that an existing technology in the supply chain is transferred from its owner to a different member in the system. In the second direction, we assume that the new technology is independently acquired by an organization in the supply chain, i.e. obtained from a third-party or through internal R&D. Furthermore, we analyze the impact of new technologies on the performance of different system structures. On the first stream of research, we discuss the effect of technology transfer on a one-supplier one-manufacturer supply chain system involving technology transfer and market sharing. We consider the technology transfer decision to be made by the manufacturer, the key technology owner, as the decision affects its market share. It is proposed three models for analyzing the system performance: (i) a supply chain without technology transfer, (ii) a supply chain with technology transfer but without supplier’s market sharing, and (iii) a supply chain with technology transfer and supplier’s market sharing. Findings show that the optimal profit of the manufacturer in a supply chain with technology transfer and market sharing is typically greater than those without technology transfer or market sharing. The analysis also provides the conditions for the manufacturer to enhance technology transfer when the supplier’s market is open to the final products. On the second stream of research, we explore the impact of technology investment on supply chain coordination. We first investigate the optimal pricing and technology investment decisions in a system consisting of one manufacturer and two competing retailers. On one hand, the manufacturer is required to invest in new technologies in order to improve its performance. On the other hand, the retailers compete in the same market with different products. We determine the conditions at which the cost-revenue sharing contract and the two-part tariff contract are capable of coordinating the one-manufacturer two-retailer supply chain system. Lastly, we analyze a system consisting of multiple complementary suppliers and a single manufacturer. It is assumed that the suppliers are required to invest in new technologies in order to participate in the supply chain negotiations. While the manufacturer initially offers a wholesale price contract to the suppliers. We compare both the decentralized and centralized settings, and show that if the supply chain members decide to cooperate and coordinate the system, they could increase the overall expected profit by at least 1/3 compared to the non-cooperative scenario. We then find that although the cost-sharing contract is unable to coordinate the system, the cost-revenue sharing contract is capable of coordinating the multi-supplier and single-manufacturer supply chain. Moreover, we establish the conditions at which the cost-revenue sharing contract offers a win-win profit scenario to all parties of the negotiation and review how bargaining analysis can lead to the optimal negotiation ability of each member