The rapid rise of "buy-online-and-pickup-in-store" (BOPS) and "ship-from-store" (SFS) has transformed retail, yet the optimal strategy to balance customer experience and operational efficiency remains unclear. Using a rational expectations equilibrium framework, we develop a newsvendor-like model to compare the performance of three omnichannel strategies: 1) BOPS; 2) SFS; and 3) their hybrid (BOPS&SFS) against an online-offline dual-channel baseline. Our analysis reveals three key insights: first, the additional delivery fee for the SFS service has a stronger impact on SFS fulfillment choices for low-urgency products compared to high-urgency products; second, in contrast to the dual-channel strategy, adopting an omnichannel strategy may lead to reduced offline inventory for low-urgency products because of lower stockout costs, while consistently increasing offline inventory for high-urgency products due to higher stockout costs; finally, the hybrid BOPS&SFS strategy does not universally dominate. In particular, the cross-selling benefit demonstrates "double-edged sword" effects: retailers only gain profit when cross-selling profits are low in some scenarios, whereas in other situations, profitability is achieved solely when cross-selling profits are high. Managerial Relevance Statement-For engineering managers, our findings provide a strategic framework for managing inventory and fulfillment channels. Managers should adopt differentiated strategies based on product urgency and store density. Specifically, we recommend implementing differentiated SFS delivery fees, setting higher delivery fees for low-urgency products, while offering discounts for high-urgency products. Furthermore, offline inventory levels must be adjusted strategically: they should increased for high-urgency products to prevent customer attrition, but can be calibrated downward for low-urgency products. Managers should also tailor their omnichannel portfolio to geographic context, prioritizing BOPS in high store-density areas and SFS in low store-density regions. Notably, the hybrid BOPS&SFS strategy is not universally optimal; its profitability depends on the existing channel structure, product urgency, local store density, SFS delivery fees, and cross-selling potential. For instance, for low-urgency products in high store-density areas, managers should avoid shifting firms' channel strategy from SFS to BOPS&SFS even when cross-selling potential is substantial; by contrast, for low-urgency products in low store-density regions, managers should shift from BOPS to BOPS&SFS when SFS delivery fees are high.

In modern manufacturing, the implementation of dual or multi-sourcing strategies presents challenges concerning the variability in component quality. This study investigates a supply chain where a manufacturer sources components from an incumbent and an entrant supplier, with the latter having lower quality but meeting standards. The entrant aims to enhance quality through research and development (R&D) efforts, which may succeed or fail. Failure in R&D leads the manufacturer to either limit the high-quality component use from the incumbent, offer consistent but lower-performance products in one market, or sell distinct products in two separate markets. We formulate the problem as a two-stage game within defined market structures (single- or two-market) and derive equilibrium solutions for both models. Our findings reveal interesting managerial insights. In both market structures, we surprisingly find that an increase in the likelihood of success for the entrant supplier's R&D may negatively impact the entrant supplier while benefiting the manufacturer and the other supplier. Dual sourcing is beneficial to the manufacturer in general, except when the entrant supplier is highly uncompetitive in quality. Furthermore, we derive analytical conditions that dictate when each member of the supply chain favors either the single-market model or the two-market model over the other.

The rapid development of global agriculture has increased supply chain complexity, with product quality becoming critical for competitiveness and consumer choice. Supply chain disruptions pose challenges for quality control and channel management. This study constructs an agricultural supply chain where quality is an endogenous variable, simulating disruptions to analyse stakeholder behaviour. The model incorporates a quality decay formula, establishes equilibrium conditions via variational inequality theory, and approximates the equilibrium solution with an iterative algorithm. Numerical results show that disruptions significantly reduce a firm's output and profits, while giving competitors an advantage with increased sales and greater pricing power. Disruptions also affect producers' control over product quality: producers improve quality to maintain market appeal during intensified competition, while increasing production in demand surges, potentially leading to lower quality. Meanwhile, a stable and self-owned supply chain network, particularly offline channels, is essential for the efficient operation of plantations.

In this paper, we investigate the problem of sharing medical resources through patient referrals for hospitals in a medical consortium. We address two main issues. One is to derive the optimal patient referral strategy for the consortium to minimize the total costs of the consortium; the other is to determine a fair cost allocation scheme to ensure the stability of the medical consortium. We first consider a general setting wherein patients can be referred between any two hospitals in the medical consortium. Then, we extend our analysis to the special setting wherein patient referrals are only allowed between hospitals in different categories. We formulate the patient referral problem as a convex optimization problem, and discuss the properties of the optimal patient referral strategy. We apply the framework of cooperative game theory to allocate the total costs arising from the medical consortium to the member hospitals. We propose a dual-price cost allocation scheme and show that it is in the core of the corresponding cooperative game. Numerical studies are conducted to further examine the proposed cost allocation schemes and to investigate the impact of parameters on the efficiency of a medical consortium.

Consumers' requirements regarding the level of freshness of certain perishable products have increased alongside continuous improvement in people's living standards. Thus, a growing number of retailers are taking freshness-keeping measures to satisfy consumers' demands. This study introduces an online-to-offline (O2O) dual-channel supply chain optimization model considering consumers' freshness preference. The model contains multiple suppliers, retailers and demand markets. The retailers purchase the products from suppliers through offline channels and sell the products to consumers via offline and online channels. On this basis, we describe the optimization model as a variational inequality problem and use an effective convergence algorithm to approximate the equilibrium solution of the supply chain. The computational results show that suppliers are always profitable from retailers' freshness-keeping effort, regardless of whether consumers' freshness preference is high or low. If more retailers invest in freshness-keeping effort, suppliers will obtain more profits. Furthermore, it is not always beneficial for retailers to engage in the freshness-keeping effort. They should take flexible freshness preservation measures on their products based on consumers' freshness preference. Moreover, an increase in consumers' freshness preference will incentive retailers to adopt more advanced freshness preservation technology to gain higher revenues.

We consider price and inventory decisions in a make-to-stock system from the perspectives of a profit-maximizing server and a social planner in which customers are delay-sensitive. Under two information cases (i.e. an almost unobservable case and a fully observable case), customers decide whether to purchase the product based on their utility. The utility is closely related to whether the inventory of the product is available, the product's price, and the waiting time. We first investigate the optimal decision in the almost unobservable case. In this case, the server's inventory strategy depends on the relationship between the unit holding cost of the product and the unit waiting cost of the customer. Additionally, the system utilization factor also affects the inventory strategy. Then, we analyse the corresponding results in the fully observable case. The results illustrate that, in both cases, profit maximization and welfare maximization lead to different pricing and inventory strategies. Finally, the numerical results show that the optimal price is sensitive to delay information, whereas the optimal stock level is not.

随着我国智慧物流的快速推进,物流领域"实践领先研究"的倒逼局面已经成为全国各高校物流类人才培养的普遍性问题.鉴于其典型的多学科交叉属性,构建了"实践+创客+竞赛"的物流跨学科创新人才培养模式,提出了支撑双创人才培养的改革思路与措施,为物流工程专业创新型人才培养提供一定的参考.

创客空间日益受到重视,创客式学习方法,取得了良好效果,是一种有效的学习模式.我国创客教育也已成为一种热门的教学模式.结合实践探讨创客的学习行为及特点,总结将创客式学习迁移到课堂教学中的模式及效果.创客式学习具有生活学习、问题导向、快速迭代、跨学科、建构主义、自我激励六个特点,在课程设计中应用其生活学习、快速迭代的理念.

针对全身交互界面用户参与的定量评估问题,提出基于行为特征分析的研究思路.利用Openpose获得用户身体关键点坐标并提取行为特征,对比不同全身交互界面和任务模式中行为特征的显著差异,以及客观行为特征与主观感知参与度的关系.发现客观行为特征与主观感知参与度具有相关性和互补性.用户行为特征在某些属性上可以指示用户主观感知的参与程度,但两者不具有替代关系,对涉及全身交互的用户参与评估需同时从客观行为和主观认知两个层面开展.VR界面中用户总体平均速度和感知参与度均显著高于Kinect界面,VR界面在支持用户认知和行为层面的用户参与具有显着优势;任务模式影响交互行为的选择,相较于休闲模式,生存模式的交互行为更加精细.

We study the equipment sharing problem where a group of food & beverage companies share the same equipment of a contractor and wish to have their processing tasks coordinated such that the total cost is minimized. The raw materials to be processed are perishable, which incur a decay cost as time goes. One key issue of this equipment sharing problem is how to allocate the total cost among the participants. We apply cooperative game theory to tackle this issue and formulate the problem as an equipment sharing game. First, we study the 1-equipment sharing game in which all participants share one equipment. We show that the 1-equipment sharing game is quasi-concave when the fixed operation cost is larger than a certain value. We then discuss the special case where the processing time for all participants is equal. For this case, we further investigate the properties of the 1-equipment sharing game and the multi-equipment sharing game. We identify the conditions under which the Shapely value and the τ-value can be easily calculated for the 1-equipment and multi-equipment sharing games.

本文对新工科背景下跨学科教育的重要性进行了探讨,提出工程领域跨学科教育应具备的五个要素:具有现实关注超出单门学科范畴的复杂问题,以既有学科为基础和依托,整合多门学科解决问题的迭代过程,以通过设计实现解决方案提升学生能力素质为目的,体现对利益相关者的关注.这五个要素与跨学科的教师、学生及环境一起构成跨学科的课堂.研究试图厘清关于跨学科教育的认识,结合三个案例分析了上述各要素如何在跨学科教育中发挥作用,并从教学设计、教师发展、课程计划等方面针对跨学科课程建设给出建议.

介绍了卫生列车在军事、救灾、普惠医疗3个方面的应用场景,阐述了不同类型卫生列车平台的特征,分析了卫生列车车厢以及在运行过程中存在的问题和研究现状,提出了高速动车组为卫生列车的创新发展提供了可能,指出了基于高速列车的卫生列车平台建设研究、卫生列车人机工效研究、卫生列车运行管理研究是卫生列车的研究趋势.

We study the problem where independent operators of queueing systems cooperate to generate a win–win solution through capacity transfer among each other. We consider two types of costs: the congestion cost in the queueing system and the capacity transfer cost, and two types of queueing systems: M/ M/1 and M/ M/ s. Service rates are considered to be capacities in M/ M/1 and are assumed to be continuous, while numbers of servers are capacities in M/ M/ s. For the capacity transfer problem in M/ M/1, we formulate it as a convex optimization problem and identify a cost‐sharing scheme which belongs to the core of the corresponding cooperative game. The special case with no transfer cost is also discussed. For the capacity transfer problem in M/ M/ s, we formulate it as a nonlinear integer optimization problem, which we refer to as the server transfer problem. We first develop a marginal analysis algorithm to solve this problem when the unit transfer costs are equal among agents, and then propose a cost‐sharing rule which is shown to be in the core of the corresponding game. For the more general case with unequal unit transfer costs, we first show that the core of the corresponding game is non‐empty. Then, we propose a greedy heuristic to find approximate solutions and design cost allocations rules for the corresponding game. Finally, we conduct numerical studies to evaluate the performance of the proposed greedy heuristic and the proposed cost allocation rules, and examine the value of capacity transfer.

We study cost allocation problem arising from less-than-truckload collaboration among perishable product retailers. The relevant costs we consider include fixed transportation cost, variable transportation cost, and decay loss of perishable products. Cooperative game theory is applied to study this cost allocation problem. The corresponding cooperative game, called transportation facility choice game, is established. First, we show that the core of the transportation facility choice game is non-empty. Then, we identify some conditions for concavity and quasi-concavity of the transportation facility choice game with the linear decay and negative exponential decay functions, respectively. Finally, simulation is conducted to analyze how optimal solutions differ under the linear decay and exponential decay functions, and intuitive cost allocation schemes are proposed and compared with the \(\tau \)-value and the Shapley value of the corresponding game. Simulation results show that the optimal solution under linear decay function tends to choose facilities with higher fixed cost than that under exponential decay function. Additionally, among all the cost allocation schemes compared, the simple cost allocation scheme called A-IM, the \(\tau \)-value, and the Shapley value have better performance in terms of the percentage of allocations lying in the core.

This paper investigates truth-telling mechanisms for individual M/M/1 queueing systems to share their capacity. The cost we consider in this paper is congestion cost incurred by customers in the queueing system, wherein the unit congestion cost of each individual queueing system is private information. We first propose two Grove-Clarke mechanisms (truth-telling mechanisms) that satisfy budget balancedness and individual rationality, respectively. Then, we conduct numerical studies to evaluate performance of the proposed mechanisms. The results show that the proposed mechanism which satisfies individual rationality has very high percentage of budget coverage. This mechanism justifies the practice of requiring membership fees to join a cooperative alliance, and has good potential for practical applications.

An adaptive back-stepping controller based on least squares-support vector machine (LS-SVM) is developed for precision positioning of robot manipulators that can compensate for dynamic friction and uncertainty in manipulator dynamics and actuator dynamics. Firstly, using cross-validation algorithm to get LS_SVM initial parameters based on offline learning. Secondly, introducing the error of LS-SVM into the adaptive law of the back-stepping control and designing the compound disturbance observer system by adjusting LS-SVM. Last, choosing Lyapunov function in turn based on the compound disturbance observer and the system error and designing the self-adaptive control system based on state feedback and compound disturbance observer. The Lyapunov stability theory is used to prove stability of the proposed control system. The simulation results show that the proposed method has stronger robustness, smaller tracking error and faster response speed than the conventional PD controller.

This paper considers the situation in which independent operators of individual queues may cooperate to generate a win-win solution through capacity transferring among each other. Two different types of costs are considered: the congestion cost incurred by customers in the system and the capacity transferring cost. We first model the capacity transferring problem as one to minimize the total cost. We then formulate the cooperation problem as a cooperative game and design a cost allocation scheme which is proven to be in the core of the game.

The paper studies the coopetition of the downstream different carriers by providing complementary transport services in intermodal freight transport chain. Considering different information structure, a two-stage dynamic game model with simultaneous actions on investment and price is first formulated. Equilibria show both parties have motivation to select coopetition even if the agreement for cooperation investment is reached in advance. When both firms agree on the specific allocation, the new coopetition with higher efficiency would be emerged. Moreover, we analyze the complexity and evolution of coopetition by repeated pricing game with finitely and infinitely time horizon. In the finitely repeated pricing game, both firms have incentive to reach a tacit understanding to alternate choosing price cooperation and competition after setting suitable allocation scheme; the repeated periods t are then going to be an issue. In the infinitely repeated pricing game, the perfect cooperation is realized by designing the suitable trigger strategy.

Few studies have adequately focused on passenger route choice behavior with congestion consideration, or provided useful guidance on passenger route choice and hence the transit assignment model, which is the writing motivation of this paper. With congestion consideration, travel cost is assessed and and ways to reduce it also identified. Finally, an actual transit network of Chengdu is used as a case study to demonstrate the benefits of the proposed model. The result indicates that the vehicle capacity is an important factor that can't be ignored and a better understanding of passenger route behavior could significantly benefit public transit system.

Meca et al. (2004) studied a class of inventory games which arise when a group of retailers who observe demand for a common item decide to cooperate and make joint orders with the EOQ policy. In this paper, we extend their model to the situation where retailer's delay in payments is permitted by the supplier. We introduce the corresponding inventory game with permissible delay in payments, and prove that its core is nonempty. Then, a core allocation rule is proposed which can be reached through population monotonic allocation scheme. Under this allocation rule, the grand coalition is shown to be stable from a farsighted point of view. (C) 2013 Elsevier B.V. All rights reserved.