23,346 research outputs found
E-Fulfillment and Multi-Channel Distribution ââŹâ A Review
This review addresses the specific supply chain management issues of Internet fulfillment in a multi-channel environment. It provides a systematic overview of managerial planning tasks and reviews corresponding quantitative models. In this way, we aim to enhance the understanding of multi-channel e-fulfillment and to identify gaps between relevant managerial issues and academic literature, thereby indicating directions for future research. One of the recurrent patterns in todayââŹâ˘s e-commerce operations is the combination of ââŹËbricks-and-clicksââŹâ˘, the integration of e-fulfillment into a portfolio of multiple alternative distribution channels. From a supply chain management perspective, multi-channel distribution provides opportunities for serving different customer segments, creating synergies, and exploiting economies of scale. However, in order to successfully exploit these opportunities companies need to master novel challenges. In particular, the design of a multi-channel distribution system requires a constant trade-off between process integration and separation across multiple channels. In addition, sales and operations decisions are ever more tightly intertwined as delivery and after-sales services are becoming key components of the product offering.Distribution;E-fulfillment;Literature Review;Online Retailing
Integrating Closed-loop Supply Chains and Spare Parts Management at IBM
Ever more companies are recognizing the benefits of closed-loop supplychains that integrate product returns into business operations. IBMhas been among the pioneers seeking to unlock the value dormant inthese resources. We report on a project exploiting product returns asa source of spare parts. Key decisions include the choice of recoveryopportunities to use, the channel design, and the coordination ofalternative supply sources. We developed an analytic inventory controlmodel and a simulation model to address these issues. Our results showthat procurement cost savings largely outweigh reverse logistics costsand that information management is key to an efficient solution. Ourrecommendations provide a basis for significantly expanding the usageof the novel parts supply source, which allows for cutting procurementcosts.supply chain management;reverse logistics;product recovery;inventory management;service management
Dynamic dependence networks: Financial time series forecasting and portfolio decisions (with discussion)
We discuss Bayesian forecasting of increasingly high-dimensional time series,
a key area of application of stochastic dynamic models in the financial
industry and allied areas of business. Novel state-space models characterizing
sparse patterns of dependence among multiple time series extend existing
multivariate volatility models to enable scaling to higher numbers of
individual time series. The theory of these "dynamic dependence network" models
shows how the individual series can be "decoupled" for sequential analysis, and
then "recoupled" for applied forecasting and decision analysis. Decoupling
allows fast, efficient analysis of each of the series in individual univariate
models that are linked-- for later recoupling-- through a theoretical
multivariate volatility structure defined by a sparse underlying graphical
model. Computational advances are especially significant in connection with
model uncertainty about the sparsity patterns among series that define this
graphical model; Bayesian model averaging using discounting of historical
information builds substantially on this computational advance. An extensive,
detailed case study showcases the use of these models, and the improvements in
forecasting and financial portfolio investment decisions that are achievable.
Using a long series of daily international currency, stock indices and
commodity prices, the case study includes evaluations of multi-day forecasts
and Bayesian portfolio analysis with a variety of practical utility functions,
as well as comparisons against commodity trading advisor benchmarks.Comment: 31 pages, 9 figures, 3 table
Competitive Positioning in International Logistics: Identifying a System of Attributes Through Neural Networks and Decision Trees
Firms involved in international logistics must develop a system of service attributes that give them a way to be profitable and to satisfy customersâ needs at the same time. How customers trade-off these various attributes in forming satisfaction with competing international logistics providers has not been explored well in the literature. This study explores the ocean freight shipping sector to identify the system of attributes that maximizes customersâ satisfaction. Data were collected from shipping managers in Singapore using personal interviews to identify the chief concerns in choosing and evaluating ocean freight services. The data were then examined using neural networks and decision trees, among other approaches to identify the system of attributes that is connected with customer satisfaction. The results illustrate the power of these methods in understanding how industrial customers with global operations process attributes to derive satisfaction. Implications are discussed
Bayesian Computation in Dynamic Latent Factor Models
Bayesian computation for filtering and forecasting analysis is developed for
a broad class of dynamic models. The ability to scale-up such analyses in
non-Gaussian, nonlinear multivariate time series models is advanced through the
introduction of a novel copula construction in sequential filtering of coupled
sets of dynamic generalized linear models. The new copula approach is
integrated into recently introduced multiscale models in which univariate time
series are coupled via nonlinear forms involving dynamic latent factors
representing cross-series relationships. The resulting methodology offers
dramatic speed-up in online Bayesian computations for sequential filtering and
forecasting in this broad, flexible class of multivariate models. Two examples
in nonlinear models for very heterogeneous time series of non-negative counts
demonstrate massive computational efficiencies relative to existing
simulation-based methods, while defining similar filtering and forecasting
outcomes.Comment: 21 pages, 7 figure
Structuring the decision process : an evaluation of methods in the structuring the decision process
This chapter examines the effectiveness of methods that are designed to provide structure and support to decision making. Those that are primarily aimed at individual decision makers are examined first and then attention is turned to groups. In each case weaknesses of unaided decision making are identified and how successful the application of formal methods is likely to be in mitigating these weaknesses is assessed
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