Design of risk sharing and coordination mechanism in supply chain under demand and supply uncertainty

Perishable and short-life products can be seen everywhere in life. Due to the particularity of these products, they are more complicated in supply chain management. This paper studies whether the two-part tariff and ZRS contract can achieve the purpose of reducing risks and coordinating supply chain. We assume that market demand and supplier yield are uncertain, and we use game theory and probability distribution for research. The research results show that when the information is asymmetric, the manufacturer always ignore the demand forecast information provided by the retailer under the wholesale price contract. When the demand is uncertain, regardless of whether the information is symmetric or asymmetric, the two-part tariff contract and the ZRS contract can coordinate the supply chain and achieve maximum profit. When the retailer's degree of risk aversion is high, the ZRS contract is better than the two-part tariff, which can reduce the risk of retailers and achieve the purpose of coordinating the supply chain. When the supply is uncertain, the manufacturer can provide the supplier with a risk-sharing contract, including the return price and the sharing ratio that meet certain constraints. Such a contract can effectively reduce the supplier's risk and realize supply chain coordination.

Smart Sustainable City Manufacturing and Logistics: A Framework for City Logistics Node 4.0 Operations

The location of smart sustainable city multi-floor manufacturing (CMFM) directly in the residential area of a megapolis reduces the delivery time of goods to consumers, has a favorable effect on urban traffic and the environment, and contributes to the rational use of land resources. An important factor in the transformation of a smart city is the development of CMFM clusters and their city logistics nodes (CLNs); the key elements of the logistics system of a megapolis. The primary goal of this study was to examine the role of the CLN4.0, as a lead sustainability and smart service provider of a CMFM cluster within the Industry 4.0 paradigm, as well as its value in the system of logistics facilities and networks of a megalopolis. This paper presents an innovative model of a CLN4.0 under supply uncertainty using a material flow analysis (MFA) methodology, which allows for specific parameters of throughput capacity within the CMFM cluster and the management of supply chains (SCs) under uncertainty. The model was verified based on a case study (7th scenario) for various frameworks of a multi-floor CLN4.0. The validity of using a group of virtual CLNs4.0 to support the balanced operation of these framework operations under uncertainty, due to an uneven production workload of CMFM clusters, is discussed. The results may be useful for the decision-making and planning processes associated with supply chain management (SCM) within CMFM clusters in a megapolis.

Optimal Green Operation and Information Leakage Decisions under Government Subsidy and Supply Uncertainty

This study investigated optimal green operation and information leakage decisions in a green supply chain system. The system consists of one supplier, one leader retailer 1, one follower retailer 2, and the government. In this system, the government subsidizes each retailer based on the selling price of the product. The supplier is subject to a yield uncertainty process. The suppler decides whether to leak leader retailer 1′s order quantity to follower retailer 2 or not. In this study, we first built a Stackelberg game to address the equilibrium green operation decisions, when the supplier has and has not information leakage behavior, respectively. Subsequently, we identify the supplier’s information leakage equilibrium and how such behavior affects retailers’ ex ante profits, consumer surplus, and social welfare through a numerical study. Interestingly, we obtained the following results: (1) Supplier leaks are the unique equilibrium of the supplier. The product’s green degree and wholesale price at supplier’s equilibrium are higher under information leakage than under no information leakage. (2) The supplier’s information leakage behavior is good for leader retailer 1 and bad for follower retailer 2. (3) Information leakage behavior increases both consumer surplus and social welfare under certain conditions. (4) In general, key system parameters (e.g., the subsidy rate, supply uncertainty, supply correlation, and forecast accuracies) positively correlate with consumer surplus and social welfare in the same direction, while they affect retailer 1′s and retailer 2′s ex ante profit in the opposite direction. These findings provide useful insights for businesses to manage demand forecast information and make decisions on the green level of the product in green supply chain management.

Green Credit Financing Equilibrium under Government Subsidy and Supply Uncertainty

In this paper, we study the green credit financing equilibrium in a green supply chain (GSC) with government subsidy and supply uncertainty. The GSC system is composed of one manufacturer, two retailers, one bank, and the government. The manufacturer is subject to both supply uncertainty and limited capital. The manufacturer invests in the R&D of green products and borrows loans from the bank. The government subsidizes banks to encourage banks to provide loans to manufacturers with lower interest rates, which is termed “green credit financing”. The two retailers decide their order quantities with horizontal competition or horizontal cooperation. We first developed a Stackelberg model to investigate the green credit financing equilibriums (i.e., the interest rate of the bank, the manufacturer’s product green degree and wholesale price, and the retailers’ order quantity) under horizontal competition and horizontal cooperation, respectively. Subsequently, we analyzed how the subsidy interest rate, supply uncertainty, and supply correlation affect financing decisions regarding equilibrium green credit. We found that a high subsidy interest rate leads to a low interest rate of bank and the manufacturer can set a high level of green product and high wholesale price, while the retailers can set a high order quantity. Finally, we compared the green credit financing equilibriums under horizontal competition with those under horizontal cooperation using numerical and analytical methods. We found that, in general, the optimal decisions and profits of bank and SC members, consumer surplus, and social welfare under horizontal competition are higher than those under horizontal cooperation. The findings in this research could provide valuable insights for the management of capital-constrained GSCs with government subsidies and supply uncertainty in a competing market.

Fair Resource Allocation in a Volatile Marketplace

In settings where a platform must allocate finite supplies of goods to buyers, balancing overall platform revenues with the fairness of the individual allocations to platform participants is paramount to the well-functioning of the platform. This is made even more difficult by the fact that the supply of goods is in practice stochastic and difficult to forecast, such as in the case of online ad allocation, where the platform manages a supply of impressions that varies over time. In this paper, we design a fair allocation scheme that works in the presence of supply uncertainty. Algorithmically, the scheme repeatedly solves for Fisher market equilibria in a model predictive control fashion and is proved to admit constant factor guarantees versus the offline optimal. In addition, the scheme is tested on a sequence of real ad datasets, showing strong empirical performance.

Make-To-Order Production Planning With Seasonal Supply In Canned Pineapple Industry

This research studies a make-to-order production planning in a canned pineapple industry. Pineapple is a seasonal perishable fruit. Thus, the cost of fresh pineapple which is the main raw material in canned pineapple is inexpensive during its season. The color of the pineapple also determines the price of the canned pineapple. However, the availability of different colors (called “choice” and “standard”) is dependent. Specifically, if the ratio of the choice color is more, the ratio of the other color is less. There are several costs involve such as fresh pineapple cost, can cost, sugar cost, water cost, labor cost, energy cost, and inventory cost. The problem is formulated as a mathematical model to maximize the total profit over four-months planning horizon. Two supply uncertainty cases are tested which are low and high ratios of the choice color. The results show that the profit depends on available color ratios of the pineapple. The production planning is best if it matches with the availability of the color ratios. In certain months, some fresh pineapple purchased exceed the need of the production because of the dependency of the two colors. The inventory holding cost also influences the production decision—whether to produce the canned pineapple in earlier months or it is better to produce only the canned pineapple when it is needed to serve the customer orders.

Prepositioning and Local Purchasing for Emergency Operations Under Budget, Demand, and Supply Uncertainty

Problem definition: Considering a mix of prepositioning and local purchasing, common to cover humanitarian demands in the aftermath of a rapid-onset disaster, we propose policies to determine preposition stock. These formulations are developed in the presence of demand, budget, and local supply uncertainties and for single-items delivery. Academic/practical relevance: The immediate period aftermath of a disaster is the most crucial period during which humanitarian organizations must supply relief items to beneficiaries. Yet, because of many unknowns such as time, place, and magnitude of a disaster, supply management is a significant challenge, and these decisions are made intuitively. The features and complexities we examine have not been studied in the literature. Methodology: We derive properties of the optimal solution, identify exact solution methods, and determine approximate methods that are easy to implement. Results: We (i) characterize the interplay of supply, demand, and budget uncertainties, as well as the impact of product characteristics on optimal prepo stock levels; (ii) show in what conditions the prepo stock is a simple newsvendor solution; and (iii) discuss the value of emergency funds. Managerial implications: We show that budget level is a key determinant of the optimal policy. When it is above a threshold, inventory increases in disaster frequency and severity, but the reverse is true otherwise. When budget is limited, the rate of savings from improved forecasts is amplified (attenuated) for critical (noncritical) items, reflecting opposing directional effects of mismatch cost and cost of insufficient funding. Our model can also be used to estimate the value of initiatives to mitigate constraints on local spend (e.g., a line of credit underwritten by large donors that is available during the immediate relief period).

An Application of Simultaneous Stochastic Optimization at a Large Open-Pit Gold Mining Complex under Supply Uncertainty

The simultaneous stochastic optimization of mining complexes optimizes various components of the related mineral value chain jointly while considering material supply (geological) uncertainty. As a result, the optimization process capitalizes on the synergies between the components of the system while not only quantifying and considering geological uncertainty, but also producing strategic mine plans, maximizing the net present value. This paper presents an application of simultaneous stochastic optimization at a large gold mining complex. The complex contains three open-pit mines, three stockpiles, a waste dump, and a processing facility. Material hardness management is integrated at the processing facility. The case study generated production schedules for each mineral deposit considered, as well as an overall assessment of the project and related forecasts. It resulted in an 18 year life-of-asset and identified the semi-autogenous grinder (SAG) mill as the bottleneck of the operation.