The application of blockchain technology solves the trust problem between core enterprises (CEs), small and medium-sized enterprises (SMEs), and commercial banks, facilitating CEs and commercial banks to provide guarantee for SMEs and finance them, respectively. This study considers a three-level supply chain composed of a manufacturer, a distributor, and a capital-constrained retailer, and explores the operational strategies of blockchain platform finance (BPF), a supply chain finance mode enabled by blockchain technology. First, optimal decision solutions are obtained through decision and parameter sensitivity analyses. Second, by comparing the BPF and SME independent finance (SIF) modes, we obtain the applicable BPF mode conditions; for instance, when the retailer’s initial capital is low and the production cost is high, BPF is the better option for the manufacturer, distributor, and retailer compared to SIF. Third, we find that risk sharing improves the financing efficiency of the BPF mode. This study provides a theoretical basis for decision makers to implement blockchain supply chain finance at three levels: joint financing and operation decision-making, financing mode selection, and financing efficiency improvement.

Many companies are implementing trade-in programmes through multiple channels. This may ultimately lead to fiercer channel conflict and competition. Few studies have explored firms’ optimal trade-in policies in such an environment. To fill the gap, we build a theoretical model that captures the features of a dual-channel situation in which a manufacturer implements a trade-in programme through retail and direct channels simultaneously. Compared with the case in which there is no trade-in rebate, the results show that a trade-in programme can intensify or mitigate the double marginalisation effect if the retailer can initially decide the trade-in rebate in the retail channel. This significantly relies on market segmentation. However, when the retailer cannot decide the trade-in rebate in the retail channel, the trade-in programme aggravates the double marginalisation effect. Second, the trade-in rebate offered by the retailer may be higher than the subsidy offered by the manufacturer, as long as the retailer can autonomously decide the trade-in rebate in the retail channel. Furthermore, we find that both the manufacturer and retailer prefer to obtain the right to autonomously decide the trade-in rebate in the retail channel, but the supply chain prefers that the manufacturer do it. Some numerical examples are provided to further explain these outcomes.

The benefits of a consumer return policy have been extensively studied in extent literature. This paper explores the potentially damaging impact of a return policy on the retailer. We develop an analytical framework and examine the economic impact of consumer return among consumers, retailer and supply chain. We distinguish three network-externality (NE) cases: no network externality, fixed network-externality and variable network-externality contingent on return amount to discuss the retailer’s selling price, refund and inventory policies. Our analysis derives the optimal policies and shows that they take the form of contingence model in which the policies depend on consumer initial return and NE return. We also examine the influence of the consumer return NE effect on buy-back contracts of the supply chain and show that while the traditional buy-back contract fails to coordinate the supply chain, the NE effect does not render the differentiated buy-back contract less effective. Finally, we extend our study to a heterogeneous consumer case.