Bin Dan

The rise of online direct‐to‐consumer (DTC) channels expands fresh producers’ distribution networks while intensifying competition with traditional retail channels. Meteorological disasters threaten the DTC channel's reliability, dynamically reshaping the coopetition between fresh producers and retailers. This study develops a theoretical framework to examine strategic interactions within a fresh supply chain, comparing a traditional monopoly model with an integrated distribution system that incorporates both DTC and traditional retail channels. Disruption risks and yield constraints faced by producers are considered. The findings suggest producers should introduce DTC channels during yield contraction but exercise caution in surplus periods. Despite disruption risks, DTC channels pressure retailers to accept higher wholesale prices and increase orders, enhancing the sales revenue of fresh produce with limited yield. However, rising disruption probabilities incentivize retailers to reduce order quantities strategically, leading to a higher risk of stagnation for fresh produce.

Over the past decade, the platform‐driven fresh supply chain, a new business model, has been changing consumer lifestyles and the agricultural industry. Platforms are the leading force in this process of change. However, sustainable operation has become a major challenge for platforms. Focusing on JD, an extreme and revelatory case from China, this paper explores how the platform can drive the sustainable operation of the fresh supply chain from a process‐oriented perspective, with a proposed logical chain comprising “driving logic–adaptation mechanism–performance outcome.” Driving logic guides the platform in selecting intra‐chain mechanisms to yield constructive outcomes that can precipitate inter‐stage transitions, while intertemporal mechanisms enable inter‐stage transitions. Through a longitudinal case study, a process model for the sustainable operation of the platform‐driven fresh supply chain is developed. The model addresses dynamics in platform sustainability emerging through three stages from open legitimation to cautious expansion and then to principled enhancement, undergoing switches in driving logics. Adaptation mechanisms include three intrachain mechanisms (shaping, sorting, shifting, i.e., 3S) within stages and two intertemporal mechanisms between stages, for example, developing consumption proximity and advocating industrial interconnection. Legitimate identity, growth momentum, and organizational brand are performance outcomes in the process. This paper makes theoretical contributions to operations management in fresh produce businesses from a process‐oriented perspective and provides practical implications for the platform to operate the fresh supply chain.

Purpose: For cases with imbalanced capacity demands and supplies, this paper analyzes the impact of dynamics and uncertainty in capacity information, and studies the multi-period dynamic capacity matching problem faced by third-party shared manufacturing platforms. We aim to provide a reference method for platforms to optimize the multi-period matching strategies. Design/methodology/approach: To alleviate the demand-supply imbalance and avoid capacity losses due to its non-storability, we consider that the platform not only matches the current-period capacity demand and supply but also conducts cross-period matching. We formulate this problem as a multi-period stochastic dynamic capacity matching model and propose a solution method by integrating the characteristics of the capacity matching problem with the value function approximation policy. Findings: The results verify the effectiveness of the proposed capacity matching model and the dynamic approximation algorithm. They also show that matching demand in advance alleviates the imbalance between the demand and supply in a single period and optimizes the multi-period matching strategy. Originality/value: Focusing on the scenario where demand information is submitted in advance, this paper innovatively studies how and when to match dynamic production capacity under uncertainty. This research extends the previous studies and provides implications for the operations management of third-party shared manufacturing platforms.

This study investigates the quality information disclosure and blockchain technology adoption strategies of suppliers on a third-party e-commerce platform. Based on a Stackelberg game model, the impacts of blockchain technology adoption on the quality information disclosure decision and profit of the third-party e-commerce platform and suppliers are explored. The results indicate that whether blockchain adoption benefits suppliers depends on the unit blockchain cost and the reliability of quality information. Counterintuitively, higher information reliability may disadvantage suppliers under certain conditions. With the increase in unit blockchain cost, the incentive of suppliers to adopt blockchain is weakened, and suppliers need to adjust their strategies of quality information disclosure according to the adoption situation and the cost of blockchain. Adopting blockchain technology may be unfavorable to the suppliers but beneficial to the third-party e-commerce platform; the platform can incentivize suppliers to adopt blockchain and achieve a win-win situation. These findings provide some valuable managerial implications for the quality information disclosure decision of suppliers and blockchain adoption in the e-commerce platform supply chain.

The government establishes an emergency reserve system and releases reserved produce through competing retailers in a fresh produce supply chain. We study the release strategy of competing retailers for reserved produce under the government's emergency reserves with order constraints. Our results reveal that competing retailers are willing to release reserved produce despite intensifying market competition. The release of reserved produce does not necessarily cannibalize supplies of fresh produce; however, the order constraints on reserved produce may instead reduce fresh produce supplies. It can also simultaneously improve or reduce supply chain performance and consumer surplus, bringing a “win‐win” or “lose‐lose” situation.

Many third‐party platforms for shared manufacturing (platforms) have developed rapidly in recent years. The quality admission and pricing of production capacity are crucial issues for these platforms. This paper focuses on the platform supply chain composed of a platform, multiple manufacturers with surplus production capacity (sharers), and multiple manufacturers with insufficient production capacity (renters). Considering the impact of the production capacity quality on the shared scale and rental demand of production capacity, this paper constructs a game model for the platform supply chain under different quality admission scenarios, investigates the quality admission and price decisions of production capacity on the platform, and analyses the impact of the quality admission on the sharers’ and renters’ profits. The results show that the platform sets the quality admission when the sharers’ production capacity scale is small and the platform regulatory cost is low. The platform always increases its service price but may reduce the rental price of production capacity under the quality admission scenario. When the sharers’ production capacity scale is large, the platform lowers the threshold of quality admission with the quality elasticity of production capacity increasing. In addition, when the quality elasticity of production capacity and platform regulatory cost are low, and the sharers’ production capacity scale is small, the quality admission of the platform realizes the win–win–win situation for the platform, renters, and sharers.

Service-oriented third-party e-commerce platforms have emerged as a new trend in the manufacturing industry. This paper aims to investigate the platforms’ value-added service (VAS) and charging strategies with a dynamic evolution analysis. Considering the change in the user numbers and characteristics of the e-commerce industry, this paper proposes a system dynamics model composed of multi-value chains and a third-party e-commerce platform. The simulation results indicate that the platform should reduce VAS investment and appropriately increase the VAS fee in the early development period. After the number of users stabilizes, the platform should appropriately increase its VAS investment and reduce the VAS fee. When the VAS fee is low, the platform profit first increases and then decreases as the VAS level increases. Differently, the platform profit will first decrease, then increase, and finally decrease as the VAS level improves when the VAS fee is low. This paper further finds that the strong cross-network effect of manufacturers is not always beneficial to the platform.

Aiming to investigate whether a fresh produce e‐tailer should implement the strategy of advance selling considering the behavior of consumers' risk aversion, we build a two‐stage newsvendor decision‐making model and further explore how the advance selling value is affected by factors, such as the freshness‐keeping cost and the effect of demand information updating on reducing demand uncertainty. The results indicate that adopting advance selling strategy benefits the e‐tailer or not depends on consumer risk aversion and the effect of demand information updating on reducing demand uncertainty. The increasing effect of demand information updating on reducing demand uncertainty is conducive to improving the value of advance selling, and the freshness‐keeping cost may increase or decrease the value of advance selling. Besides, adopting the strategy of advance selling may benefit both the e‐tailer and the consumers under certain conditions.