John J. Liu

Demand forecast sharing in a dual-channel supply chain

Abstract We assess the benefits of sharing demand forecast information in a manufacturer–retailer supply chain, consisting of a traditional retail channel and a direct channel. The demand is a linear function of price with a Gaussian primary demand (i.e., zero-price market potential). Both the manufacturer and the retailer set their price based on their forecast of the primary demand. In this setting, we investigate the value of sharing demand forecasts. We analyze the ‘make-to-order’ scenario, in which prices are set before and production takes place after the primary demand is known, and the ‘make-to-stock’ scenario, in which production takes place and prices are set before the primary demand is known. We also compare the supply chain performance with and without the direct channel under some assumptions (production cost is zero, and each demand function has the same slope of price). We find that the direct channel has a negative impact on the retailer’s performance, and, under some conditions, the manufacturer and the whole supply chain are better off. Our research extends and complements prior research that has investigated only the inventory and replenishment-related benefits of information sharing.

Pricing policies under direct vs. indirect channel competition and national vs. store brand competition

Abstract This paper analyzes channel pricing in multiple distribution channels under competition between a national brand (NB) and a store brand (SB), where an NB can be distributed both through a direct channel (e-channel) and an indirect channel (local stores) but an SB can be distributed only through an indirect channel. We first explore cross-brand and cross-channel pricing policies. Formulating the problem as a Nash pricing game, we reach two findings: (1) brand loyalty building is profitable for both an NB and an SB; and (2) marketing decisions are more restrictive for an NB channel than they are for the SB channel. We next assess supply chain coordination and reach two findings: (1) wholesale price change does not coordinate the supply chain and (2) an appropriate combination of markup and markdown prices can achieve both supply chain coordination and a win–win outcome for each channel.

Optimal lot-sizing in an imperfect production system with homogeneous reworkable jobs

Abstract We consider a lot-sizing problem in a single-stage imperfect production system where the job processing is failure-prone. The processing may generate two types of defects: 1) reworkable defects which must be sent back for rework; 2) nonreworkable defects which are discarded immediately. The production process will switch between new jobs and rework jobs. Both new-job processing time and rework time are random. We discuss the optimal lot-sizing control, under a class of operating policies, to maximize the average profit over an infinite time horizon. We establish the existence of an optimal lot size. Furthermore, we characterize the profit function. Through the discussion, we obtain a very efficient algorithm for determining an optimal lot size.

Channel redistribution with direct selling

Abstract It seems nowadays that a company can be considered either a “pure-direct” such as Amazon.com and Dell Computers, or an “adopted-direct”, like Barnes and Noble for example. An adopted-direct company’s decision to directly sell “on-line” has become a fashionable choice. But the results of such choice differ drastically. Glorious success mixed with pathetic failure. One of the pending issues has been the channel redistribution strategy, as whether to entirely switch to direct sell or to maintain a combination of both. In this paper, we develop a dynamic channel diffusion model and analyze how the sales will redistribute between the two channels in a given time-variant marketplace. This paper provides two major contributions: First, we obtain the existence of a steady-state redistribution between the two channels and the necessary conditions for this existence; Second, we establish measures of industry-specific suitability for on-line business operations. In short, our results concur with the theory: IT changes the way of doing business, but does not change the business itself.

Product Life Cycle, and Market Entry and Exit Decisions Under Uncertainty

A key characteristic of the Product Life Cycle (PLC) is the depletion of the products market potential due to technological obsolescence. Based on this concept, we develop a stochastic model for evaluating market entry and exit decisions during the PLC under uncertainty. The model explicitly shows the conditions for the optimality of a two-threshold policy based on the estimated earnings potential of the product, and can be used by manufacturing firms to assess entry and exit decisions under such conditions. To aid the applications of the model in actual decision situations, we also provide the procedures for computing the exact and approximate values of the two thresholds.

Optimal promotion planning-depth and frequency-for a two-stage supply chain under Markov switching demand

Abstract In considering the retailer–supplier supply chain, this paper analyzes how a retailer reasonably decides both the depth and frequency of the price discount promotion including or excluding a supplier’s inventory decision. Assuming that the promotion frequency used by the retailer is probabilistic, we model a promotion-inventory decision under an AR(1) demand with a Markov switching promotion regime. After obtaining the optimal promotion plan, our analysis also considers the behavior of the optimal promotion decision; the retailer’s price format selection, either an Every-Day-Low-Price policy (EDLP) or a Promotion policy (HiLo); and the impact of information sharing of promotion status on the system’s performance. Our results suggest that a retailer tends to overpromote if inventory cost is excluded in its promotion decision, that increasing the market share is a preferable action for both the retailer and the supplier, that total margin and price-elasticity play an important role in selecting the price format, and that the profitability for a supplier of sharing promotion information depends on the transition probabilities of the Markov switching regime.

Port-Focal Logistics and Global Supply Chains

Changes in the global economy have caused significant and far-reaching effects in many areas, including transportation, logistics, and supply chains. As supply chains evolve and adapt to these changes, ports will play a pivotal role. This book examines the challenges that ports, logistics, and supply chains have faced in the past decades, and introduces the concept of port focal logistics. Evolution of ports, industrial organization, government policies, and the role of institutions are explored. Development strategies undertaken by ports, logistics, and supply chain stakeholders are investigated using experiences from developed and developing countries. Case studies from Brazil and India are presented.

A MULTISCALE MODELING APPROACH INCORPORATING ARIMA AND ANNS FOR FINANCIAL MARKET VOLATILITY FORECASTING

The financial market volatility forecasting is regarded as a challenging task because of irregularity, high fluctuation, and noise. In this study, a multiscale ensemble forecasting model is proposed. The original financial series are decomposed firstly different scale components (i.e., approximation and details) using the maximum overlap discrete wavelet transform (MODWT). The approximation is predicted by a hybrid forecasting model that combines autoregressive integrated moving average (ARIMA) with feedforward neural network (FNN). ARIMA model is used to generate a linear forecast, and then FNN is developed as a tool for nonlinear pattern recognition to correct the estimation error in ARIMA forecast. Moreover, details are predicted by Elman neural networks. Three weekly exchange rates data are collected to establish and validate the forecasting model. Empirical results demonstrate consistent better performance of the proposed approach.

Groups in DEA based cross-evaluation: An application to Asian container ports

In container port performance evaluation, a group of ports in one country is always significantly different from a group of ports in another country. This is noticed as the heterogeneity of port performance. It is therefore necessary to further investigate the impact of the different groups on efficiency evaluation of ports. The cross-evaluation method is a DEA extension tool to identify best performing DMUs and to rank DMUs using cross efficiency scores linked to all DMUs. A factor that possibly reduces the usefulness of the cross efficiency evaluation method is that cross efficiency scores may not be unique due to the presence of alternative optima. Doyle and Green 1 propose the use of secondary goals to deal with the non-uniqueness issue by the aggressive/benevolent model formulations. This article extends the model of Doyle and Green by considering the groups of DMUs in the determination of final cross efficiency. A new approach based on cross efficiency evaluation method is developed and applied to efficiency analysis of 28 container ports from 12 countries in Asia. A comparative study between traditional and newly proposed methods is conducted.

Securing RFID Applications: Issues, Methods, and Controls

Abstract Radio frequency identification (RFID) is an automatic identification (auto- ID) technology developed by the Auto-ID Center at the Massachusetts Institute of Technology, relying on storing and remotely retrieving data using devices called RFID tags and readers (Auto-ID Center, 2002; Doyle, 2004; EPC, 2004b; Finkenzeller, 2000; Shepard, 2005). With RFID technology, physical assets will have embedded intelligence that allows them to communicate with each other and with the tracking points (Auto-ID Center, 2002; IBM, 2003; VeriSign, 2004).