208,304 research outputs found
Multi-Channel Retail Supply Chain Management: Fulfillment systems in Multi-Channel Retailing - Customer Expectations and Economic Performance
Increasingly, store-based retailers are opening an additional online sales channel and becoming multi-channel retailers. The integration of these different channels raises the question how to redefine the strategic marketing elements and the operations, as the two channels have different constraints and require different competences. This multi-channel retailing has major impacts on the operations and the supply-chain management. Order fulfillment for the customers using the different sales channels is a key challenge, as customers are directly impacted from the performance of this process. In this paper, we will highlight the different strategic elements and operational challenges to be addressed by a multi-channel retailer. In order to evaluate the match between a fulfillment system and a multi-channel business model, we propose a framework analyzing the overall performance of different fulfillment systems regarding the two dimensions customer expectations and economic performance.Multi-Channel; Retail; Fulfillment; Distribution; E-commerce
On two-echelon inventory systems with Poisson demand and lost sales
We derive approximations for the service levels of two-echelon inventory systems with lost sales and Poisson demand. Our method is simple and accurate for a very broad range of problem instances, including cases with both high and low service levels. In contrast, existing methods only perform well for limited problem settings, or under restrictive assumptions.\u
Towards Data-driven Simulation of End-to-end Network Performance Indicators
Novel vehicular communication methods are mostly analyzed simulatively or
analytically as real world performance tests are highly time-consuming and
cost-intense. Moreover, the high number of uncontrollable effects makes it
practically impossible to reevaluate different approaches under the exact same
conditions. However, as these methods massively simplify the effects of the
radio environment and various cross-layer interdependencies, the results of
end-to-end indicators (e.g., the resulting data rate) often differ
significantly from real world measurements. In this paper, we present a
data-driven approach that exploits a combination of multiple machine learning
methods for modeling the end-to-end behavior of network performance indicators
within vehicular networks. The proposed approach can be exploited for fast and
close to reality evaluation and optimization of new methods in a controllable
environment as it implicitly considers cross-layer dependencies between
measurable features. Within an example case study for opportunistic vehicular
data transfer, the proposed approach is validated against real world
measurements and a classical system-level network simulation setup. Although
the proposed method does only require a fraction of the computation time of the
latter, it achieves a significantly better match with the real world
evaluations
A Novel Multiplex Network-based Sensor Information Fusion Model and Its Application to Industrial Multiphase Flow System
This work was supported by National Natural Science Foundation of China under Grant No. 61473203, and the Natural Science Foundation of Tianjin, China under Grant No. 16JCYBJC18200.Peer reviewedPostprin
- âŠ