Product Return Handling

In this article we focus on product return handling and warehousingissues. In some businesses return rates can be well over 20% andreturns can be especially costly when not handled properly. In spiteof this, many managers have handled returns extemporarily. The factthat quantitative methods barely exist to support return handlingdecisions adds to this. In this article we bridge those issues by 1)going over the key decisions related with return handling; 2)identifying quantitative models to support those decisions.Furthermore, we provide insights on directions for future research.reverse logistics;decision-making;quantitative models;retailing and warehousing

Product Return Handling

In this article we focus on product return handling and warehousing issues. In some businesses return rates can be well over 20% and returns can be especially costly when not handled properly. In spite of this, many managers have handled returns extemporarily. The fact that quantitative methods barely exist to support return handling decisions adds to this. In this article we bridge those issues by 1) going over the key decisions related with return handling; 2) identifying quantitative models to support those decisions. Furthermore, we provide insights on directions for future research

A Two-Echelon Location-inventory Model for a Multi-product Donation-demand Driven Industry

This study involves a joint bi-echelon location inventory model for a donation-demand driven industry in which Distribution Centers (DC) and retailers (R) exist. In this model, we confine the variables of interest to include; coverage radius, service level, and multiple products. Each retailer has two classes of product flowing to and from its assigned DC i.e. surpluses and deliveries. The proposed model determines the number of DCs, DC locations, and assignments of retailers to those DCs so that the total annual cost including: facility location costs, transportation costs, and inventory costs are minimized. Due to the complexity of problem, the proposed model structure allows for the relaxation of complicating terms in the objective function and the use of robust branch-and-bound heuristics to solve the non-linear, integer problem. We solve several numerical example problems and evaluate solution performance

On the Unique Features and Benefits of On-Demand Distribution Models

To close the gap between current distribution operations and today’s customer expectations, firms need to think differently about how resources are acquired, managed and allocated to fulfill customer requests. Rather than optimize planned resource capacity acquired through ownership or long- term partnerships, this work focuses on a specific supply-side innovation – on-demand distribution platforms. On-demand distribution systems move, store, and fulfill goods by matching autonomous suppliers\u27 resources (warehouse space, fulfillment capacity, truck space, delivery services) to requests on-demand. On-demand warehousing systems can provide resource elasticity by allowing capacity decisions to be made at a finer granularity (at the pallet-level) and commitment (monthly versus yearly), than construct or lease options. However, such systems are inherently more complex than traditional systems, as well as have varying costs and operational structures (e.g., higher variable costs, but little or no fixed costs). New decision- supporting models are needed to capture these trade-offs

Geographic Information Systems: A Tutorial and Introduction

his tutorial provides a foundation in GIS including its basic structure, concepts, and spatial analysis. GIS is a new field in business schools and presents opportunities for research. It is derived from about a dozen disciplines, some unfamiliar to most IS researchers. Following an overview of vertical-sector uses of GIS, the paper introduces their costs and benefits. The links of GIS to related technologies such as GPS, wireless, location-based technologies, web services, and RFID are examined. Conceptual models and research methodologies are discussed, including Spatial Decision Support Systems (SDSS), and GIS in visualization, organizational studies, and end user computing. Suggestions for future research are presented

Investigating the Effects of Daily Inventory Record Inaccuracy in Multichannel Retailing

Inventory record inaccuracy (IRI) challenges multichannel retailers in fulfilling both brick-and-mortar and direct channel demands from their distribution centers. The nature and damaging effects of IRI largely go unnoticed because retailers assume daily IRI remains stable over time within the replenishment cycle. While research shows that a high level of IRI is damaging, in reality the level of IRI can change every day. We posit that daily IRI variation increases the uncertainty in the system to negatively affect inventory and service levels. Our research uses data collected daily from a multichannel retailer to ground a discrete-event simulation experiment. Going beyond testing just the level of IRI, we evaluate daily IRI variation\u27s impact on operating performance. What we find in our empirical data challenges extant assumptions regarding the characteristics of IRI. In addition, our simulation results reveal that daily IRI variation has a paradoxical effect: it increases inventory levels while also decreasing service levels. Moreover, we also reveal that brick-and-mortar and direct channels are impacted differently. Our findings show that assumptions and practices that ignore daily IRI variation need revising. For managers, we demonstrate how periods of multiday counting help assess their daily IRI variation and indicate what the causes may be

Swedish shippers’ strategies for coping with slow-steaming in deep sea container shipping

When container shipping lines experience over-capacity and high fuel costs, they typically respond by decreasing sailing speeds and, consequently, increasing transport time. Most of the literature on this phenomenon, often referred to as slow-steaming, takes the perspective of the shipping lines addressing technical, operational and financial effects, or a society perspective focusing on lower emissions and energy use. Few studies investigate the effects on the demand side of the market for container liner shipping. Hence, the aim of this study is to elaborate on the logistics consequences of slow-steaming, particularly the strategies that Swedish shippers purchasing deep sea container transport services employ to mitigate the effects of slow-steaming. Workshops and semi-structured interviews revealed that shippers felt they had little or no impact on sailing schedules and were more or less subject to container shipping lines’ decisions. The effects of slow-steaming were obviously most severe for firms with complex supply chains, where intermediate products are sent back and forth between production stages on different continents. The shippers developed a set of strategies to cope with the low punctuality of containerised shipping, and these were categorised in the domains of transfer-the-problem, transport, sourcing and distribution, logistics and manufacturing, and product design. All firms applied changes in the transport domain, although the lack of service segmentation limited the effects of the strategy. Most measures were applied by two firms, whereas only one firm changed the product design

Effective use of product quality information in food supply chain logistics

Food supply chains have inherent characteristics, such as variability in product quality and quality decay, which put specific demands on logistics decision making. Furthermore, food supply chain organization and control has changed significantly in the past decades by factors such as scale intensification and globalization. In practice, these characteristics and developments frequently lead to supply chain problems, such as high levels of product waste, product quality problems, and high logistics costs. Recent technological developments have created the opportunity to gather, process, and communicate more information on the status of processes and products to support logistics decision making, providing business opportunities to realize performance improvements, and add extra value by differentiating products to specific market segments. This will, however, require the development of effective logistics management strategies that ensure the supply of products of appropriate quality in a cost-effective way to each stage of the supply chain. This thesis studies the use of product quality information in logistics decision making in food supply chains, captured in the following central research question: How can the effectiveness of logistics decision making in food supply chains be improved using advanced product quality information? This research question is investigated using four case studies: two in the context of the European Q-porkchains project (i.e. in pork supply chains), and two in the context of the European Veg-i-Trade project (i.e. in fruit- and vegetable supply chains). In these cases we investigated the impact of variability in product quality and quality decay on chain processes and studied if use of product quality information can improve logistics decision making regarding product sourcing and process design. In each case decision support models were developed – in close cooperation with industrial partners - to quantify the impact. Case study 1: Process design for advanced sorting of meat products The first case study, presented in chapter 2, considers the process design of a meat processing company that seeks to add value by sorting meat products for a specific product quality feature. The relation between product sorting, processing efficiency and process design is investigated using a discrete event simulation model. Results indicate that increasing sorting complexity by use of advanced product quality information results in a reduction of processing efficiency, whereas use of production buffers was found to mitigate negative effects of high sorting complexity. The simulation allows practitioners facing segmented customer demand to assess which scenario offers the best trade-off between benefits and drawbacks resulting from efforts to improve responsiveness and flexibility. Case study 2: Livestock sourcing decisions The second case study considers a meat processing company that faces quality feature variation in animals delivered to its slaughterhouses. To support sourcing decisions and ensure that the right product quality is received at its slaughterhouses two stochastic programming models are developed that exploit product quality data gathered during earlier deliveries. The presented implementations reveal that uncertainty in supplied product quality can be reduced using historical farmer delivery data, which improves processing performance. Case study 3: Product sourcing in international strawberry supply chains The third case study relates to an international strawberry distributor that faces frequent product quality problems and substantial product waste. Different sourcing strategies were tested using a combination of both a slow, but cheap transport mode (i.e. sea and truck), and a faster, but more expensive mode (i.e. plane). The performance of these sourcing strategies is examined using a discrete-continuous chain simulation that includes microbiological growth models to predict quality decay. Simulation results reveal that standard cost parameters (that do not take quality decay into account) result in substantial product waste, but if cost for expected shelf-life losses are included in the order policies the effectiveness of product sourcing for the considered supply chain is improved. Case study 4: Use of form postponement for food waste reduction The fourth case study concerns an international lettuce supply chain that struggles with effective product sourcing. Form postponement (FP) is a supply chain strategy which delays processing steps until a demand is realized. This allows a reduction of the total inventory in the supply chain. We studied supply chain scenarios that differ in where and when in the supply chain whole crop lettuce is converted into processed lettuce products. A discrete-continuous chain simulation model revealed that application of FP reduced both product waste and age and improves point-of-sale product quality. Integrated findings The findings of this thesis demonstrate that decision makers can improve logistics decisions and reduce food waste by using product quality information and predicting changes in product quality. The developed quantitative decision support models provided essential insights into trade-offs resulting from information-based supply chain performance improvement strategies. The presented case studies demonstrate that supply chain flexibility and responsiveness is required to reduce the impact of product variability and product quality decay. Increasing responsiveness and flexibility typically comes at the expense of other performance dimensions. This research demonstrates the potential of use of product quality information in food supply chain logistics, which may contribute to the effectiveness of food supply chains by improving consumer satisfaction, reducing overall costs, and reducing food waste.</p