Coordination of Multiechelon Supply Chains Using the Guaranteed Service Framework

2021 ◽  
Author(s):  
Tor Schoenmeyr ◽  
Stephen C. Graves
Keyword(s):  
Supply Chain ◽  
Wholesale Price ◽  
Problem Definition ◽  
Quantity Discounts ◽  
Minimum Order ◽  
Base Stock Policy ◽  
Decentralized Decision Making ◽  
Guaranteed Service ◽  
Stock Policy ◽  
Different Parts

Problem definition: We use the guaranteed service (GS) framework to investigate how to coordinate a multiechelon supply chain when two self-interested parties control different parts of the supply chain. For purposes of supply chain planning, we assume that each stage in a supply chain operates with a local base-stock policy and can provide guaranteed service to its customers, as long as the customer demand falls within certain bounds. Academic/practical relevance: The GS framework for supply chain inventory optimization has been deployed successfully in multiple industrial contexts with centralized control. In this paper, we show how to apply this framework to achieve coordination in a decentralized setting in which two parties control different parts of the supply chain. Methodology: The primary methodology is the analysis of a multiechelon supply chain under the assumptions of the GS model. Results: We find that the GS framework is naturally well suited for this decentralized decision making, and we propose a specific contract structure that facilitates such relationships. This contract is incentive compatible and has several other desirable properties. Under assumptions of complete and incomplete information, a reasonable negotiation process should lead the parties to contract terms that coordinate the supply chain. The contract is simpler than contracts proposed for coordination in the stochastic service (SS) framework. We also highlight the role of markup on the holding costs and some of the difficulties that this might cause in coordinating a decentralized supply chain. Managerial implications: The value from the paper is to show that a simple contract coordinates the chain when both parties plan with a GS model and framework; hence, we provide more evidence for the utility of this model. Furthermore, the simple coordinating contract matches reasonably well with practice; we observe that the most common contract terms include a per-unit wholesale price (possibly with a minimum order quantity and/or quantity discounts), along with a service time from order placement until delivery or until ready to ship. We also observe that firms need to pay a higher price if they want better service. What may differ from practice is the contract provision of a demand bound; our contract specifies that the supplier will provide GS as long as the buyer’s order are within the agreed on demand bound. This provision is essential so that each party can apply the GS framework for planning their supply chain. Of course, contracts have many other provisions for handling exceptions. Nevertheless, our research provides some validation for the GS model and the contracting practices we observe in practice.

When Variability Trumps Volatility: Optimal Control and Value of Reverse Logistics in Supply Chains with Multiple Flows of Product

2020 ◽  
Author(s):  
Alexandar Angelus ◽  
Özalp Özer
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Reverse Logistics ◽  
Demand Uncertainty ◽  
Problem Definition ◽  
Feasible Region ◽  
Base Stock Policy ◽  
Multiple Flows ◽  
Stock Policy ◽  
Heuristic Policy

Problem definition: We study how to optimally control a multistage supply chain in which each location can initiate multiple flows of product, including the reverse flow of orders. We also quantify the resulting value generated by reverse logistics and identify the drivers of that value. Academic/practical relevance: Reverse logistics has been gaining recognition in practice and theory for helping companies better match supply with demand, and thus reduce costs in their supply chains. Nevertheless, there remains a lack of clarity in practice and the research literature regarding precisely what in reverse logistics is so important, exactly how reverse logistics creates value, and what the drivers of that value are. Methodology: We first formulate a multistage inventory model to jointly optimize ordering decisions pertaining to regular, reverse, and expedited flows of product in a logistics supply chain, where the physical transformation of the product is completed at the most upstream location. With multiple product flows, the feasible region for the problem acquires multidimensional boundaries that lead to the curse of dimensionality. Next, we extend our analysis to product-transforming supply chains, in which product transformation is allowed to occur at each location. In such a system, it becomes necessary to keep track of both the location and stage of completion of each unit of inventory; thus, the number of state and decision variables increases with the square of the number of locations. Results: To solve the reverse logistics problem in logistics supply chains, we develop a different solution method that allows us to reduce the dimensionality of the feasible region and identify the structure of the optimal policy. We refer to this policy as a nested echelon base stock policy, as decisions for different product flows are sequentially nested within each other. We show that this policy renders the model analytically and numerically tractable. Our results provide actionable policies for firms to jointly manage the three different product flows in their supply chains and allow us to arrive at insights regarding the main drivers of the value of reverse logistics. One of our key findings is that, when it comes to the value generated by reverse logistics, demand variability (i.e., demand uncertainty across periods) matters more than demand volatility (i.e., demand uncertainty within each period). To analyze product-transforming supply chains, we first identify a policy that provides a lower bound on the total cost. Then, we establish a special decomposition of the objective cost function that allows us to propose a novel heuristic policy. We find that the performance gap of our heuristic policy relative to the lower-bounding policy averages less than 5% across a range of parameters and supply chain lengths. Managerial implications: Researchers can build on our methodology to study more complex reverse logistics settings, as well as tackle other inventory problems with multidimensional boundaries of the feasible region. Our insights can help companies involved in reverse logistics to better manage their orders for products, and better understand the value created by this capability and when (not) to invest in reverse logistics.

A Deep Q-Network for the Beer Game: Deep Reinforcement Learning for Inventory Optimization

2021 ◽  
Author(s):  
Afshin Oroojlooyjadid ◽  
MohammadReza Nazari ◽  
Lawrence V. Snyder ◽  
Martin Takáč
Keyword(s):  
Supply Chain ◽  
Reinforcement Learning ◽  
Transfer Learning ◽  
Problem Definition ◽  
Base Stock ◽  
Inventory Optimization ◽  
Base Stock Policy ◽  
Order Quantities ◽  
Stock Policy ◽  
Beer Game

Problem definition: The beer game is widely used in supply chain management classes to demonstrate the bullwhip effect and the importance of supply chain coordination. The game is a decentralized, multiagent, cooperative problem that can be modeled as a serial supply chain network in which agents choose order quantities while cooperatively attempting to minimize the network’s total cost, although each agent only observes local information. Academic/practical relevance: Under some conditions, a base-stock replenishment policy is optimal. However, in a decentralized supply chain in which some agents act irrationally, there is no known optimal policy for an agent wishing to act optimally. Methodology: We propose a deep reinforcement learning (RL) algorithm to play the beer game. Our algorithm makes no assumptions about costs or other settings. As with any deep RL algorithm, training is computationally intensive, but once trained, the algorithm executes in real time. We propose a transfer-learning approach so that training performed for one agent can be adapted quickly for other agents and settings. Results: When playing with teammates who follow a base-stock policy, our algorithm obtains near-optimal order quantities. More important, it performs significantly better than a base-stock policy when other agents use a more realistic model of human ordering behavior. We observe similar results using a real-world data set. Sensitivity analysis shows that a trained model is robust to changes in the cost coefficients. Finally, applying transfer learning reduces the training time by one order of magnitude. Managerial implications: This paper shows how artificial intelligence can be applied to inventory optimization. Our approach can be extended to other supply chain optimization problems, especially those in which supply chain partners act in irrational or unpredictable ways. Our RL agent has been integrated into a new online beer game, which has been played more than 17,000 times by more than 4,000 people.

Implications of Price Matching in Supply Chain Negotiation

2021 ◽  
Author(s):  
Weixin Shang ◽  
Gangshu (George) Cai
Keyword(s):  
Supply Chain ◽  
Social Welfare ◽  
Wholesale Price ◽  
Consumer Welfare ◽  
Problem Definition ◽  
Nash Bargaining ◽  
Price Matching ◽  
The Impact ◽  
Multiple Buyers ◽  
Wholesale Pricing

Problem definition: Few papers have explored the impact of price matching negotiation (PM), in which a channel matches its price with the resulting wholesale price bargained by another channel, on firms’ performances, consumer welfare, and social welfare, with and without supply chain coordination. Academic/practical relevance: Negotiation has been widely seen in determining both uniform and discriminatory wholesale prices, which affect outcomes of competitive supply chain practices. Methodology: To characterize the PM mechanism, we use game theory and Nash bargaining theory to compare PM with simultaneous negotiation (SN) through a common-seller two-buyer differentiated Bertrand competition model. Results: Our analysis reveals that PM can benefit the seller but hurt all buyers, which is at odds with some fair wholesale pricing clauses intending to protect buyers. Under coordination with side payments, however, all firms can conditionally benefit more from PM than from SN. Despite firms’ gains, PM leads to less consumer utility and social welfare compared with SN, unless the second buyer in PM is considerably less powerful than the first buyer. Coordination further worsens PM’s negative impact on consumer utility and social welfare. Moreover, the existence of a spot market can increase the wholesale price in PM, hurting buyers, consumers, and society. Furthermore, the qualitative results about PM remain robust under an alternative disagreement point for PM, multiple buyers, and other extensions. Managerial implications: This paper delivers insights on when price matching in supply chain wholesale price negotiation can benefit a seller, buyers, consumers, and society in a variety of scenarios. It advocates how managers can use PM to their own advantages and provides rationale to decision makers for policy regulations regarding wholesale pricing.

Supply Chain Coordination for E-Commerce: Risk Penalty vs. Flat Rate

2021 ◽  
Author(s):  
Ju Myung Song ◽  
Yao Zhao
Keyword(s):  
Supply Chain ◽  
Information Asymmetry ◽  
Risk Sharing ◽  
Supply Chain Coordination ◽  
Wholesale Price ◽  
Problem Definition ◽  
Third Party ◽  
Common Belief ◽  
Shipping Industry ◽  
Flat Rate

Problem definition: We study the coordination of an E-commerce supply chain between online sellers and third party shippers to meet random demand surges, induced by, for instance, online shopping holidays. Academic/practical relevance: Motivated by the challenge of meeting the unpredictable demand surges in E-commerce, we study shipping contracts and supply chain coordination between online sellers and third party shippers in a novel model taking into account the unique features of the shipping industry. Methodology: We compare two shipping contracts: the risk penalty (proposed by UPS) and the flat rate (used by FedEx), and analyze their impact on the seller, the shipper, and the supply chain. Results: Under information symmetry, the sophisticated risk penalty contract is no better than the simple flat rate contract for the shipper, against common belief. Although both the risk penalty and the flat rate can coordinate the supply chain, the risk penalty does so only if the shipper makes zero profit, but the flat rate can provide a positive profit for both. These results represent a new form of double marginalization and risk-sharing, in sharp contrast to the well-known literature on the classic supplier-retailer supply chain, where risk-sharing contracts (similar to the risk penalty) can bring benefits to all parties, but the single wholesale price contract (similar to the flat rate) can achieve supply chain coordination only when the supplier makes zero profit. We also find that only the online seller, but not the shipper, has the motivation to vertically integrate the seller-shipper supply chain. Under information asymmetry, however, the risk penalty brings more benefit to the shipper than the flat rate, but hurts the seller and the supply chain. Managerial implications: Our results imply that information plays an important role in the shipper’s choices of shipping contracts. Under information symmetry, the risk penalty is unnecessarily complex because the simple flat rate is as good as the risk penalty for the shipper; moreover, it is better for the seller-shipper coordination. However, under information asymmetry, the shipper faces additional shipping risk that can be offset by the extra flexibility of the risk penalty. Our study also explains and supports the recent practice of online sellers (e.g., Amazon.com and JD.com), but not shippers, to vertically integrate the supply chain by consistently expanding their shipping capabilities.

scholarly journals Contracts Adjustment under Bilateral Information Updating in a Supply Chain

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Xinhui Wang ◽  
Yingsheng Su ◽  
Zihan Zhou ◽  
Yiling Fang
Keyword(s):  
Supply Chain ◽  
Production Cost ◽  
Wholesale Price ◽  
Transfer Payment ◽  
Market Demand ◽  
Order Quantity ◽  
Minimum Order ◽  
Information Updating ◽  
Minimum Order Quantity ◽  
Market Outlook

This paper investigates contracts adjustment between one manufacturer and one retailer under bilateral information updating. The manufacturer incurs uncertain production cost and the retailer faces uncertain demand, but they can acquire independent signals to update production cost and demand, respectively. They commit an initial agreement on an initial wholesale price, minimum order quantity, and information sharing as well as the transfer payment and decisions adjustment when information is updated. We find that due to the joint impact of production cost variation and market variation, the manufacturer may not decrease (increase) her wholesale price when the updated production cost is lower (higher) than expected. The retailer places an additional order even if the wholesale price rises when the market outlook is good, but places an order with the minimum order quantity even if the wholesale price falls when the market outlook is bad. Secondly, for a certain level of information accuracy of the production cost and market demand, the retailer is always better off with information updating, but the manufacturer may be worse off with information updating when facing a bad market outlook. Thirdly, when information accuracy of the production cost and market demand varies, the manufacturer only benefits from a high accuracy of production cost. Profits of the retailer and the supply chain are increasing (decreasing) with accuracy of production cost if the updated production cost is larger (smaller) than expected.

scholarly journals The More Supply Chain Control Power, the Better? A Comparison among Four Kinds of Cooperation Models

2015 ◽  
Vol 2015 ◽  
pp. 1-19 ◽  
Author(s):  
Weihua Liu ◽  
Shuqing Wang ◽  
Donglei Zhu
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supply Chain Coordination ◽  
Wholesale Price ◽  
The Other ◽  
Order Quantity ◽  
Control Power ◽  
Decentralized Decision Making ◽  
Optimal Value ◽  
Total Profit

This paper introduces the parameter of supply chain control power into existing supply chain coordination models and explores the impacts of control power on the profits of manufacturer, retailer, and the overall supply chain under four modes of decision-making, including the decentralized decision-making dominated by manufacturer, the decentralized decision-making dominated by retailer, centralized decision-making, and Nash negotiation decision-making. Some significant conclusions are obtained. Firstly, supply chain control power does have great impact on the supply chain profits. The profit of the whole supply chain with centralized decision-making is higher than those of the other three modes, while the overall profit of supply chain with decentralized decision-making is superior to the profit when retailer and manufacturer dominate the supply chain together. Secondly, with decentralized decision-making, for manufacturer and retailer, it is beneficial to gain the control powers of the supply chain; however, control power has an optimal value, not the bigger, the better. Thirdly, under certain circumstances, order quantity will increase and the wholesale price will decrease when control power is transferred from manufacturer to retailer. In this case, the total profit of supply chain dominated by retailer will be greater than that dominated by manufacturer.

scholarly journals Supply chain contracting coordination for fresh products with fresh-keeping effort

2017 ◽  
Vol 117 (3) ◽  
pp. 538-559 ◽  
Author(s):  
Qi Zheng ◽  
Petros Ieromonachou ◽  
Tijun Fan ◽  
Li Zhou
Keyword(s):  
Supply Chain ◽  
Cost Sharing ◽  
Wholesale Price ◽  
Revenue Sharing ◽  
Optimal Decision ◽  
Decision Variable ◽  
Coordination Problem ◽  
Content Type ◽  
Revenue Sharing Contract ◽  
Decentralized Decision Making

Purpose Fresh product loss rates in supply chain operations are particularly high due to the nature of perishable products. The purpose of this paper is to maximize profit through the contract between retailer and supplier. The optimized prices for the retailer and the supplier, taking the fresh-keeping effort into consideration, are derived. Design/methodology/approach To address this issue, the authors consider a two-echelon supply chain consisting of a retailer and a supplier (i.e. wholesaler) for two scenarios: centralized and decentralized decision making. The authors start from investigating the optimal decision in the centralized supply chain and then comparing the results with those of the decentralized decision. Meanwhile, a fresh-keeping cost-sharing contract and a fresh-keeping cost- and revenue-sharing contract are designed. Numerical examples are provided, and managerial insights are discussed at the end. Findings The results show that the centralized decision is more profitable than the decentralized decision; a fresh product supply chain (FPSC) can only be coordinated through a fresh-keeping cost- and revenue-sharing contract; the optimal retail price, wholesale price and fresh-keeping effort can all be achieved; and the profit of a FPSC is positively related to consumers’ sensitivity to freshness and negatively correlated with their sensitivity to price. Research limitations/implications This research is based on the assumption that demand is relatively stable. It has not addressed when demand is stochastic. Practical implications The findings would be useful for managers in fresh food sector in terms of how to deal with suppliers in order to maximize total profit while also provide freshest food to the customers. Originality/value Few studies have considered fresh-keeping effort as a decision variable in the modelling of supply chain. In this paper, a mathematical model for the fresh-keeping effort and for price decisions in a supply chain is developed. In particular, fresh-keeping cost-sharing contract and revenue-sharing contract are examined simultaneously in the study of the supply chain coordination problem.

scholarly journals Emergency Strategies of Closed-Loop Supply Chain with Single Retailer Recycling under Demand Disruptions

2020 ◽  
Vol 2020 ◽  
pp. 1-19
Author(s):  
Jian Cao ◽  
Yuting Yan ◽  
Lingyuan Wang ◽  
Xihui Chen ◽  
Xuemei Zhang ◽  
...  
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Closed Loop ◽  
Wholesale Price ◽  
Normal Operation ◽  
Market Demand ◽  
Closed Loop Supply Chain ◽  
Decentralized Decision Making ◽  
Retail Prices ◽  
Emergency Decision

The uncertainty caused by emergencies will influence the normal operation of the supply chain. Considering demand disruptions, a closed-loop supply chain consisting of one manufacturer and two competing retailers based on decentralized decision-making is considered. In the supply chain, one retailer recovers end-of-life products while the other does not. Analytic results show that, when the disturbance of demand occurs, the manufacturer and retailers adjust the wholesale price and retail prices of products according to the direction of the market demand disruptions. Under demand disruptions, the retailer who participates in recovering can gain more profits, especially in the case of the positive disruption. Theoretic and pragmatic references for the emergency decision-making of closed-loop supply chain enterprises are provided.

Sharing Manufacturer’s Demand Information in a Supply Chain with Price and Service Effort Competition

2021 ◽  
Author(s):  
Yunjie Wang ◽  
Albert Y. Ha ◽  
Shilu Tong
Keyword(s):  
Supply Chain ◽  
Wholesale Price ◽  
Problem Definition ◽  
Theoretic Model ◽  
Price Distortion ◽  
Demand Information ◽  
Private Demand ◽  
The Cost ◽  
The Impact ◽  
Share Information

Problem definition: This paper investigates the issue of sharing the private demand information of a manufacturer that sells a product to retailers competing on prices and service efforts. Academic/practical relevance: In the existing literature, which ignores service effort competition, it is known that demand signaling induces an informed manufacturer to distort the wholesale price downward, which benefits the retailers, and so, they do not have any incentive to receive the manufacturer’s private information. In practice, many manufacturers share demand information with their retailers that compete on prices and service efforts (e.g., demand-enhancing retail activities), a setting that has not received much attention from the literature. Methodology: We develop a game-theoretic model with one manufacturer selling to two competing retailers and solve for the equilibrium of the game. Results: We show how an informed manufacturer may distort the wholesale price upward or downward to signal demand information to the retailers, depending on the cost of service effort, the intensity of effort competition, and the number of uninformed retailers. We fully characterize the impact of such wholesale price distortion on the firms’ incentive to share information and derive the conditions under which the manufacturer shares information with none, one, or both of the retailers. We derive conditions under which a higher cost of service effort makes the retailers or the manufacturer better off. Managerial implications: Our results provide novel insights about how service effort competition impacts the incentives for firms in a supply chain to share a manufacturer’s private demand information. For instance, when the cost of effort is high or service effort competition is intense, a manufacturer should share information with none or some, but not all, of the retailers.

scholarly journals Supply Chain Performance with Target-Oriented Firms

2021 ◽  
Author(s):  
Lucy Gongtao Chen ◽  
Qinshen Tang
Keyword(s):  
Supply Chain ◽  
Wholesale Price ◽  
Strong Support ◽  
Problem Definition ◽  
Expected Profit ◽  
Trading Partner ◽  
Supply Chain Performance ◽  
Decentralized System ◽  
Outside Option ◽  
Risk Neutral

Problem definition: We study a supply chain in which a supplier sets the wholesale price and a retailer responds with an order quantity. Both of the two firms can be either risk-neutral—maximizing the expected profit—or target-oriented, which is to maximize her or his ability to reach a target profit. Academic/practical relevance: Our work not only sheds light on the benefit/loss of trading with target-oriented decision makers but also, adds new knowledge to the supply chain coordination literature. Methodology: We provide strong support for firms’ target-based preference and the linear target formation model through a survey as well as analyzing company data. With the firms’ target-oriented behavior evaluated by a CVaR-satisficing measure, we apply a game theoretical framework to investigate how the target-based preference affects supply chain performance. Results: A firm, be it a supplier or a retailer, is always hurt by its target-based preference but can benefit from its trading partner’s target-based preference. A risk-neutral supplier, for example, can sometimes reap the whole supply chain’s profit if the retailer is target-oriented, and a target-oriented supplier always performs better with a target-oriented retailer than a risk-neutral one. Furthermore, a target-oriented retailer and/or supplier can help alleviate the double-marginalization effect and with a specific target, can help the supply chain achieve the same efficiency level as in a risk-neutral centralized system, with just a wholesale price contract. Another important finding is that if both firms are target-oriented, then the supply chain can have a higher expected profit under a decentralized system than a centralized one. This contrasts with the case when both firms are risk-neutral. We also investigate the role of outside option and retailer-type misidentification and find that both can alleviate the retailer’s disadvantage of being target-oriented. Managerial implications: (i) The target-based preference can be exploited by the trading partner, and hence, a firm should adopt the target-oriented decision criterion with caution. (ii) A target-oriented retailer can explore strategies such as revealing his outside option or hiding his target-based preference in order to be less manipulated. (iii) Whether a firm (and the supply chain) can benefit from its trading partner’s target-based preference often depends on how ambitious the trading partner (and the firm itself if it is target-oriented) sets the target. (iv) Target-based preference of one or both firms can help the supply chain reach the first-best efficiency. (v) When both firms are target-oriented, decentralization can be preferred to centralization.

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