Purpose The paper aims to clarify the effects of brand differentiation on the platform's formulation of channel strategy and help the online platform formulate the optimal channel strategy, which involves selecting a proper selling mode for each brand. Design/methodology/approach The paper develops a multistage game model consisting of one online platform and two competing manufacturers with differentiated brands and examines the effects of brand differentiation on these three channel members' profits under each candidate channel strategy. Findings The results show that the platform prefers to offer the reselling mode for both brands when the brand differentiation is low, and this preference will be enhanced by the decrease in order fulfilment cost. By contrast, when the brand differentiation is high, it will offer the reselling mode for the premium brand but the marketplace service for the economy brand if the order fulfilment cost is not high; or the marketplace mode will be offered to both brands if this cost is high. Research limitations/implications This study assumes that the order fulfilment costs of platform and manufacturer are fixed and symmetric. Therefore, researchers are encouraged to consider asymmetric costs of order fulfilment. Practical implications The paper guides the online platform to formulate the optimal channel strategy for differentiated brands and provides managerial insights for differentiated brands entering online markets. Originality/value This paper explores platforms' optimal channel strategy by jointly considering the effects of brand differentiation and investigates the impacts of brand differentiation on the optimal decision making under four candidate options. Moreover, this paper has been extended to examine the case when the manufacturers' production costs cannot be neglected.
Growth of performance sensitive applications, such as voice and multimedia, has led to widespread adoption of resource virtualization by a variety of service providers (xSPs). For instance, Internet Service Providers (ISPs) increasingly differentiate their offerings by means of customized services, such as virtual private networks (VPN) with Quality of Service (QoS) guarantees or QVPNs. Similarly Storage Service Providers (SSPs) use storage area networks (SAN)/network attached storage (NAS) technology to provision virtual disks with QoS guarantees or QVDs. The key challenge faced by these xSPs is to maximize the number of virtual resource units they can support by exploiting the statistical multiplexing nature of the customers' input request load.While a number of measurement-based admission control algorithms utilize statistical multiplexing along the bandwidth dimension, they do not satisfactorily exploit statistical multiplexing along the delay dimension to guarantee distinct per-virtual-unit delay bounds. This article presents Delay Distribution Measurement (DDM) based admission control algorithm, the first measurement-based approach that effectively exploits statistical multiplexing along the delay dimension. In other words, DDM exploits the well-known fact that the actual delay experienced by most service requests (packets or disk I/O requests) for a virtual unit is usually far smaller than its worst-case delay bound requirement because multiple virtual units rarely send request bursts at the same time. Additionally, DDM supports virtual units with distinct probabilistic delay guarantees---virtual units that can tolerate more delay violations can reserve fewer resources than those that tolerate less, even though they require the same delay bound. Comprehensive trace-driven performance evaluation of QVPNs (using Voice over IP traces) and QVDs (using video stream, TPC-C, and Web search I/O traces) shows that, when compared to deterministic admission control, DDM can potentially increase the number of admitted virtual units (and resource utilization) by up to a factor of 3.
Owing to the influence of traffic incidents, natural expressway traffic flow will be influenced. In order to promote dissipation of traffic flow congestion or clog and reduce vehicle queue delay under the influence of traffic incidents, some intervention measures should be adopted in the upper reaches of the origin of traffic incidents. Based on hydrodynamic traffic flow wave theory, it is analyzed the interactive influence of traffic incidents and intervention measures on expressway traffic flow, established traffic flow wave speed model, traffic flow wave position models and corresponding time models under the interactive influence of intervention shock wave and concentration-wave, startup-wave and dissipation-wave result from traffic incidents and relieving diffluent intervention measures time model on the basis of linear model of speed related to traffic density. These models or critical parameters provide theoretical basis for effectively determining schemes to solve traffic incidents and quickly eliminating traffic congestion or clog.
Sight distance is an important indicator to ensure the safety of drivers, and is also an indispensable evaluation basis in highway safety engineering. In mountainous highways, high slopes and small radius often lead to poor visibility and traffic accidents. Through the combined calculation of horizontal and vertical sections, this paper comprehensively considers the specific sizes of roadside clearance, high slope, as well as the position and height of the driver’s view point and other factors, and it analyzes the limited visibility of the driver in the process of driving right turn. An effective and simplified calculation method based on design data for three dimensional (3D) stopping sight distance (S.S.D.) in high fill sections is proposed. Finally, the S.S.D. inspection of the actual highway, based on design speed and operating speed, is carried out, and the sight distance of the calculated point is judged by comparing the value with the normal value and the calculation result of the horizontal sightline offset. The results show that the method proposed in this paper is consistent with the sight distance results obtained by the horizontal sightline offset method, which indicates the calculation method is accurate and provides a technical reference for S.S.D. evaluation in highway safety engineering.
Aiming at the problem of low fault diagnosis rate of planetary gearbox caused by insufficient fault data in actual industry, a method was proposed based on dynamic adversarial network. The domain-shared one dimensional feature extraction network was first built from the fault data. Secondly, the global discriminator and subdomain discriminator was used to align adaptively the distribution of fault features, and the weight index was used to evaluate the relative weight of those discriminators. Then, the joint loss of weight index, discriminator loss and classification loss is used as the objective function for training. Finally, the trained model was used to identify the target domain health conditions. The experimental results show that the proposed dynamic adversarial network may achieve better accuracy in a small amount of fault data.
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