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In this paper, we consider a supply chain with a single manufacturer and two competing retailers. The manufacturer sells his digital goods, which may be pirated, to customers through a traditional and a digital retail channel. It is assumed that the manufacturer takes a leader role and the retailers follow it. We investigate the contracts that the manufacturer offers to the retailers and our goal is to find the optimal pricing and ordering decisions made by retailers and the best contract that includes maximum profit for the supply chain. Also, we study a numerical example and examine the proposed contracts. On the other hand, in the sensitivity analysis section, we analyze the impact of each parameter of the problem, in particular, the impact of piracy on the profit of supply chain members and decision variables.

This paper determines categories of contracts that facilitate vertical information sharing in a supply chain while precluding horizontal information leakage among competing newsvendors. We consider a supply chain in which retailers replenish inventory from a common supplier to satisfy uncertain demand and are engaged in newsvendor competition. Each retailer has imperfect demand information. Yet one of the retailers (the incumbent) has a more accurate demand forecast than the other (the entrant). Information leakage among such competing retailers precludes vertical information sharing and is often the reason for many retailers to abandon collaborative forecast-sharing initiatives, leading to suboptimized supply chains. We show that whether a contract can prevent information leakage depends on how the inventory risk (i.e., cost of supply–demand mismatch) is allocated among the supplier and retailers in conjunction with the allocation of profits. We categorize contracts according to how they allocate inventory risk among firms when compared with a wholesale‐price contract. This comparison yields four mutually exclusive and collectively exhaustive categories of contracts. A downside-protection contract is one that effectively reduces retailers’ cost of excess inventory by shifting some of their overage cost to the supplier. Examples of such contracts include buy-back and revenue-sharing contracts. An upside-protection contract is one that effectively increases retailers’ cost of inventory shortage by shifting some of the supplier’s underage cost to retailers. Examples of such contracts include penalty and rebate contracts. A two-sided protection contract combines the properties of the previous two categories. A no-protection contract is one that fails to shift firms’ cost of inventory shortage or excess from one to the other. Examples of such contracts include wholesale-price and two-part tariff contracts. We show that no-protection contracts, which are extensively used in practice, cannot prevent information leakage, whereas others may do so. We also show that preventing information leakage could be costly for the supply chain (i.e., low channel efficiency). We conclude by illustrating how our unified framework to study a variety of contracts can enable a firm to determine the best-performing contract (among many) that precludes information leakage while almost coordinating the channel. For example, we show why buy‐back contracts perform significantly better than revenue‐sharing or rebate contracts. This paper was accepted by Serguei Netessine, operations management.

Purpose The Internet of Things (IoT) is used in the fresh agricultural product (FAP) supply chain, which can be coordinated through a revenue-sharing contract. The purpose of this paper is to make the three-level supply chain coordinate in IoT by considering the influence of FAP on market demand and costs of controlling freshness on the road. Design/methodology/approach A three-level FAP supply chain that comprises a manufacturer, distributor, and retailer in IoT is regarded as the research object. This study improves the revenue-sharing contract, determines the optimal solution when the supply chain achieves maximum profit in three types of decision-making situations, and develops the profit distribution model based on the improved revenue-sharing contract to coordinate the supply chain. Findings The improved revenue-sharing contract can coordinate the FAP supply chain that comprises a manufacturer, distributor, and retailer in IoT, as well as benefit all enterprises in the supply chain. Practical implications Resource utilization rate can be improved after coordinating the entire supply chain. Moreover, loss in the circulation process is reduced, and the circulation efficiency of FAPs is improved because of the application of IoT. The validity of the model is verified through a case analysis. Originality/value This study is different from other research in terms of the combination of supply chain coordination, FAPs, and radio frequency identification application in IoT.

The capacity-sharing strategy is a widely used strategy to alleviate the mismatch between supply and demand. To investigate the performance of the capacity-sharing strategy, we consider two firms competing for business in a single market in this paper. Both firms can choose to join the horizontal capacity-sharing strategy with a revenue-sharing contract. By comparing the equilibrium solutions of analytical models where firms share capacities and firms don’t share capacities respectively, we find that both firms raise their prices with a low revenue sharing rate when the total desired demand can be satisfied by the total capacities; But the change of prices depends on the combined effect of competition intensity and the revenue sharing rate if the capacity sharing can’t satisfy the total desired demand. In addition, we find that the profit of the firm with insufficient capacity increases if capacity sharing is present. However, the profit of the firm with underutilized capacity increases in the revenue sharing rate when it is small, but decreases in it when it becomes relatively large. Thus, capacity sharing is not always better for the firm with underutilized capacity.

This work develops a general model of a two-echelon supply chain in which a dominant retailer interacts with a manufacturer via a consignment contract with revenue sharing. The manufacturer’s cost function is known only to him, whereas the retailer has only an estimation of this function, which is based on common knowledge. We formulate the interaction between the parties as a Stackelberg game in which the less informed party (the retailer) moves first. We investigate a strategic information-sharing policy of the manufacturer under general formulations of (i) the supply chain’s revenue and cost functions, and (ii) the manufacturer’s decision functions. Two models are considered: (i) a point-estimation model—the retailer relies on a single-valued estimation of the manufacturer’s cost function, based on her “best belief”; and (ii) an interval-estimation model—the retailer faces uncertainty with regard to the cost function and thus estimates its parameter values within intervals. We find a condition that distinguishes between a case in which it is optimal for both parties for the manufacturer to share his exact cost function and a case in which such information-sharing is not optimal for the manufacturer but is optimal for the retailer. In the interval-estimation model, equilibrium is obtained using a normative (probabilistic) approach as well as behavioral-decision criteria (max–max, max–min and regret minimization). Under a normative approach both hidden and known superiority of the manufacturer are considered. Finally, we use our model to analyze a supply chain of a mobile application.

As an effective mode for resource recovery, remanufacturing has been widely recognized in practice and academia. However, coordination is needed and multi-uncertainties exist in a remanufacturing supply chain (RSC). Under a retailer collection mode, this paper extends the existing studies on a revenue-sharing mechanism for a forward supply chain to examine how to coordinate a RSC between a remanufacturer and a retailer by developing a mathematical model. This model considers two types of uncertainties, they are, the stochastic remanufacturability rate from the supply side of used products and the random demand occurring in remarketing of remanufactured products. This study fills the research gap on RSC coordination under the multi-uncertainty environment. Moreover, it introduces an iterative algorithm (the Newton–Raphson Method) to deal with difficulty in solving the implicit function of the payment to consumers under the non-uniform demand distribution by finding the approximate value. The research results show that a revenue-sharing contract for a RSC with multi-uncertainties can increase profit for the whole RSC as well as the remanufacturer and the retailer by eliminating double marginalization. Besides, the government subsidy to the remanufacturer can motivate the retailer to collect more used products under a revenue-sharing case since the retailer can share benefits of the whole RSC. A case study of remanufactured truck engines demonstrates benefits of the proposed revenue-sharing mechanism and the profit increase for the whole RSC with the government subsidy.

The present study examines a supply chain consisting of a manufacturer and a retailer. The manufacturer produces a product with a national brand (NB) and the retailer selling both the NB product and his own premium store brand (PSB) product. The manufacturer competes with the retailer through improving the quality by using innovation over time. It is assumed that both advertising and enhanced quality play positive roles in customers’ loyalty over time for the NB product. We propose four scenarios, including: (1) Decentralized (D), (2) Centralized (C), (3) Coordination with a revenue-sharing contract (RSH), and (4) Coordination with a two-part tariff contract (TPT). A Stackelberg differential game model is developed, and parametric analyses and managerial insights are provided based on a numerical example. Our results show that: (1) Introducing a PSB product alongside selling the NB product is profitable for the retailer, (2) In Scenario D and RSH, the manufacturer tries to increase the quality gap with the PSB product through innovation, (3) Customers’ loyalty leads to higher prices, levels of innovation, quality, and advertising for the NB product, (4) The TPT contract can lead to perfect coordination and yield higher profits for the manufacturer and the retailer.

Green innovation, implemented by enterprises, contributes to sustainable development and environmental protection. However, because of the high cost and high risk of green innovation, enterprises are reluctant to step into green innovation activities in practice. Government subsidies are conducive to promoting green innovation in enterprises. To investigate firms’ preferences for green innovation, we consider a three-player game in a supply chain where a government offers subsidies (price, innovation, or both subsidies) to a manufacturer and a retailer, while the latter two players cooperate with each other through contracts (revenue-sharing and cost-sharing contracts). By exploring the impacts of government subsidies and cooperative contracts on the optimal level of green innovation efforts and profits of participants, we find that: (1) for green innovation that leads to increased production costs, the government should subsidize both the retailer and the manufacturer to improve the level of green innovation; (2) the revenue-sharing contract is more effective than the cost-sharing contract under the premise of government subsidies; and (3) the revenue-sharing ratio decreases in production and innovation costs, while the cost-sharing ratio increases in these two costs.