70,071 research outputs found

    Business integration between manufacturing and transport-logistics firms

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    Purpose - This paper analyses how manufacturers and transport-logistics service providers (TLSPs) work together and integrate their business processes. The information technologies used to support the integration, the processes currently integrated, and the expected future integration, are searched. Design/methodology/approach - Six in-depth case studies were conducted among leading companies in the electrical, electronics, mechanical, food processing, and transport-logistics industries. The data was collected using comprehensive semi-structured interviews. Findings - Most of the firms are coupled electronically through EDI. The current business integration practices are primarily restricted to some sub-processes in three key SC processes: Customer service management, order fulfillment and backwards logistics. In the future the manufacturers want a better integration with the TLSPs, but at the same time, manufacturers would like to have the freedom of breaking the relationship, if the party does not fulfill the requisites and expectations. The future developments associated to the "commoditization" of TLSPs’ services would reinforce this trend. Originality/value - This research has shed light on a relatively unexplored area related to the integration between manufacturers and transport-logistics firms. Our research has highlighted the complexity of the integration between the two echelons, and has helped to the identification of current areas of integration. This research has also contributed to understand how the integration occurs in real contexts, by uncovering with a high degree of detail, what manufactures do to integrate their business with the TLSPsSupply chain management; Business process integration; Information technologies (IT); Standardization; Manufacturers; Transport and Logistics Service Providers (TLSPs)

    From supply chains to demand networks. Agents in retailing: the electrical bazaar

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    A paradigm shift is taking place in logistics. The focus is changing from operational effectiveness to adaptation. Supply Chains will develop into networks that will adapt to consumer demand in almost real time. Time to market, capacity of adaptation and enrichment of customer experience seem to be the key elements of this new paradigm. In this environment emerging technologies like RFID (Radio Frequency ID), Intelligent Products and the Internet, are triggering a reconsideration of methods, procedures and goals. We present a Multiagent System framework specialized in retail that addresses these changes with the use of rational agents and takes advantages of the new market opportunities. Like in an old bazaar, agents able to learn, cooperate, take advantage of gossip and distinguish between collaborators and competitors, have the ability to adapt, learn and react to a changing environment better than any other structure. Keywords: Supply Chains, Distributed Artificial Intelligence, Multiagent System.Postprint (published version

    Product Return Handling

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    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

    Research Directions in Information Systems for Humanitarian Logistics

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    This article systematically reviews the literature on using IT (Information Technology) in humanitarian logistics focusing on disaster relief operations. We first discuss problems in humanitarian relief logistics. We then identify the stage and disaster type for each article as well as the article’s research methodology and research contribution. Finally, we identify potential future research directions
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