Bulk logistics is an important part of the modern logistics system. The degree of digital transformation of bulk logistics has a significant gap compared with other logistics forms. Combined with the successful experience of digital transformation, value co-creation may become one of the key strategies to solve the problem of digital transformation of bulk logistics. This study formulates a four-party evolutionary game model to analyze the strategic choices and the stability of strategy combinations in value co-creation activities among bulk logistics enterprises and related entities and conducts numerical simulation analysis to explore the factors affecting the outcomes of the proposed game. The numerical results demonstrate that the bulk logistics enterprises and government departments are the key players in the game form that drive the success of value co-creation activities, and the additional costs required by various enterprises and the policies and financial support from government departments are key factors affecting strategic choices. Our findings can serve as a reference for bulk logistics enterprises.

Origin warehouses, positioned at the critical “first mile” of the agri-food supply chain, profoundly influence supply chain power structures and profit allocation, as well as supply chain stability and sustainable development. To explore the role of origin warehouses in the agri-food supply chain, this study develops a three-level game model comprising a “planter–origin warehouse operator–seller” framework. Notably, this study conceptualizes the dual-functional “origin warehouse” as observed in practice, proposing two theoretical modes: the Logistics Center (LC) and the Supply Chain Center (SCC). By treating quality level, service level, and selling price decisions as endogenous variables, this study further reveals the interconnected decision-making mechanisms under different operational modes. Overall, the LC mode performs better in quality-driven markets, generating higher system profits and greater social welfare, whereas the SCC mode is superior when consumers are more price-sensitive or place greater value on service. Based on these findings, this study provides decision-making guidance for origin warehouse operators aiming to select the optimal mode under varying market conditions and proposes targeted coordination strategies to promote the high-quality development and economic sustainability of the agri-food supply chain.

For logistics facilities at the county level, workforce scheduling is a basic operational concern. Although these facilities are developing rapidly, they still mostly rely on human and semi-automated work. Significant differences in employee productivity and skill levels, along with regular changes in demand, exacerbate this challenge. This study proposes a sustainability-oriented dual-objective optimization model to coordinate operational cost control with employee well-being enhancement. To address this issue, we designed an improved Genetic Algorithm that combines heuristic initialization with specialized repair operators, forming a systematic optimization framework. The effectiveness of the proposed system design and algorithm has been validated through real-world case studies. Experimental results demonstrate that this model not only achieves a balance between cost and employee satisfaction under uncertain demand conditions but also provides county-level logistics centers with sustainable scheduling solutions adaptable to business changes. Management recommendations based on the experimental results are proposed, such as implementing differentiated scheduling strategies, easing restrictions on maximum working hour variations, establishing a progressive optimization mechanism, and optimizing staffing and employee structure in accordance with corporate characteristics. This study provides scientific decision support for county-level logistics systems to achieve sustainable operations and human resource management transformation.