4 research outputs found

    Monitoring type B buyer–supplier relationships

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    The ability to monitor supplier performance is a critical capability for maintaining strong buyer–supplier relationships. Monitoring type B suppliers is especially challenging as they are not as clearly defined as either type A, with strong strategic partnerships, or type C, with little partnership. This research develops a non-parametric multivariate Hoteling’s T 2 control chart to capture the in-control state of a dyadic relationship (Phase I), and show how it would be developed based on survey data of buyer–supplier relationship attributes. Modelling the satisfactory level of dyadic relationship performance is very useful for identifying when the relationship begins to move away from the desired state. We then use the designed control chart to monitor the relationship between dyads over time to determine if any unusual behaviour has occurred (Phase II) and illustrate its implementation through a case study from the auto industry. This research illustrates how supply chain managers can secure and improve their supply chain performance by monitoring and maintaining strong relationships with their partners. The proposed method extends the existing SPC tools to effectively manage Type B buyer–supplier relationships. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group

    Complexity drivers in manufacturing companies: a literature review

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    Increasing complexity in manufacturing companies has been one of the biggest issues during the last years. Companies in high-technology marketplaces are confronted with technology innovation, dynamic environmental conditions, changing customer requirements, globalization of markets and competitions as well as market uncertainty. Manufacturing companies can't escape these trends, which induce an increasing amount of complexity. Reasons for this phenomenon are internal and external sources of complexity so-called complexity drivers. Identifying, analyzing and understanding complexity drivers are the first step for complexity management's development and implementation. Complexity management is a strategic issue for companies to be competitive. The purpose of this literature review is to provide a general overview regarding complexity drivers in manufacturing companies. The different definitions of complexity drivers are described, and a new overall definition of complexity drivers is presented. Furthermore, the existing approaches for complexity driver's identification, operationalization and visualization are identified and specified. For complexity driver's clustering, a superior classification system was developed based upon existing classification systems in the literature. The literature review was done by systematically analyzing and collecting existing literature and reveals gaps according to methodology and issue. Existing literature reviews are only focused on specific issues, such as logistics or supply chain management, and do not point out the applied research methodology in detail. A general overview regarding complexity drivers in manufacturing companies and along the value chain does not exist yet
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