Online channel strategies under different offline channel power structures for the Belt and Road of China

ABSTRACT

This paper explores the online channel strategies adopted by Chinese manufacturers with regard to the Belt and Road. It also investigates the effect of offline channel power structures and maritime transportation costs on online channel mode selection and pricing strategies. The offline channel power structures are classified into three types, namely, Chinese manufacturer Stackelberg (MS) structure, vertical Nash (VN) structure, and foreign retailer Stackelberg (RS) structure. Furthermore, a game model is developed among the Chinese manufacturer, foreign retailer, and cross-border e-tailer to investigate the interactions among offline channel power structures, maritime transportation costs, and Chinese manufacturers’ online channel mode selection. The results show that Chinese manufacturers’ preferences for the online agency selling mode increases correspondingly with the decrease in their market position and bargaining power. Moreover, foreign retailers can obtain higher profits in the online agency selling mode under the VN structure. However, the level of profit for foreign retailers depends on the intensity of their competition with cross-border e-tailers under the MS and RS structures. Finally, consumers in countries along the Belt and Road can obtain a higher surplus in the online agency selling mode under all of the structures.     

孕妇外周血PCR技术用于胎儿产前性别诊断的可靠性分析

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港口装卸皮带传送装置大型链轮的维修技术

在散粮皮带传送装置中,JC3驱动链轮的正常运行非常重要。由于其体积和重量较大,这给维修带来了不小的难度。本篇文章主要是介绍该大型链轮在链轮互换思想指导下所进行的维修技术和方法。     

基于马尔可夫链的极值波高预测

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基于交通因子状态网络的城市交叉口交通流预测

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地铁环境振动预测中链式结构振级落差灵敏度分析

针对地铁环境振动预测中使用的链式结构力学简化模型,利用灵敏度分析对链式结构中各参数变化对各振级落差影响规律进行系统研究;推导给出振级落差一阶灵敏度解析表达式和一种逆矩阵偏导数求解方法;并提出利用自由衰减时域段实测数据逆求链式结构中各力学参数方法。研究结果表明:通过灵敏度分析可以确定链式结构中任一力学参数改变对其任一层振级落差影响程度,找出对系统动态响应影响较大的环节。该方法有助于提高环境振动预测精度。     

供需链环境下提高企业订单执行效率分析

在企业的生产、管理过程中,如何提高订单执行力的研究仍是一个空白。此文针对当前制造业生产环境存在的主要问题,即生产面临复杂的环境、市场变化的不确定性导致激烈的市场竞争、订单执行过程的协调性较差,进行分析与探讨,提出提高企业订单执行力的方法和可采取的4个方面的措施,从而建立起一套在供需链管理模式下的高效订单执行力体系,使企业快速拓展市场,实现增值和稳步发展。     

北京市轨道交通产业化研究

分析北京城市轨道交通产业的特点,阐述其发展的优劣势,从规划设计咨询类、工程建设施工类、装备制造类、运营类及增值服务类等5个方面,分析北京城市轨道交通产业链的构成与发展情况及发展需求,并结合国家对轨道交通的战略性新型产业的定位,提出3点发展建议,为推动北京城市轨道交通产业的健康发展提供参考.     

船用伙食冷库自控系统的改造设计

文章针对早期船用伙食冷库以继电器为主导的控制系统所存在的问题,以某一滚装客船冷库为例,根据该冷库的运行技术特点,开发出以西门子s7系列可编程控制器为核心的自动控制系统,满足了冷库运行过程的精确掌控、节约耗能和可靠性等要求。     

Driving cycle prediction model based on bus route features

Bus fuel economy is deeply influenced by the driving cycles, which vary for different route conditions. Buses optimized for a standard driving cycle are not necessarily suitable for actual driving conditions, and, therefore, it is critical to predict the driving cycles based on the route conditions. To conveniently predict representative driving cycles of special bus routes, this paper proposed a prediction model based on bus route features, which supports bus optimization. The relations between 27 inter-station characteristics and bus fuel economy were analyzed. According to the analysis, five inter-station route characteristics were abstracted to represent the bus route features, and four inter-station driving characteristics were abstracted to represent the driving cycle features between bus stations. Inter-station driving characteristic equations were established based on the multiple linear regression, reflecting the linear relationships between the five inter-station route characteristics and the four inter-station driving characteristics. Using kinematic segment classification, a basic driving cycle database was established, including 4704 different transmission matrices. Based on the inter-station driving characteristic equations and the basic driving cycle database, the driving cycle prediction model was developed, generating drive cycles by the iterative Markov chain for the assigned bus lines. The model was finally validated by more than 2 years of acquired data. The experimental results show that the predicted driving cycle is consistent with the historical average velocity profile, and the prediction similarity is 78.69%. The proposed model can be an effective way for the driving cycle prediction of bus routes.