7,467 research outputs found

    Cultivating knowledge sharing through the relationship management maturity model

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    Purpose - The purpose of this paper is to present the development of the relationship management maturity model (RMMM), the output of an initiative aimed at bridging the gap between business units and the IT organisation. It does this through improving and assessing knowledge sharing between business and IT staff in Finco, a large financial services organisation. Design/methodology/approach - The objectives were achieved by undertaking ethnographic research with the relationship managers (RMs) as they carried out their activities, and developing the RMMM by visualizing the development of a community of practice (CoP) between business and IT. Findings - The RMMM demonstrates a learning mechanism to bridge the business/IT gap through an interpretive approach to knowledge sharing by defining knowledge sharing processes between business and IT and defining the tasks of the relationship managers as facilitators of knowledge sharing. Research limitations/implications - More research is necessary to determine whether the RMMM is a useful tool on which Finco can base the development of RM over the next few years. Practical implications - The RMMM acts as a practical knowledge management tool, and will act as a future reference for the RMs as they attempt to further develop the business/IT relationship. Originality/value - The findings provide an initial endorsement of the knowledge sharing perspective to understand the business/IT relationship. Also, the RMMM can be used to identify problematic issues and develop processes to address them

    Customer Enquiry Management in a Global Competitive Context: A Comparative Multi-Case Study Analysis

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    Business-to-Business (B2B) relationships, such as between a manufacturer and a customer, are increasingly important during the Customer Enquiry Management (CEM) process, particularly so for non-Make-To-Stock (non-MTS) companies operating in industrial markets. Few empirical studies have explored the CEM practices adopted by firms in practice. A study of the Italian capital goods sector by Zorzini et al. (2007) is a recent exception. Moreover, most studies have approached CEM from a cross-department integrated perspective but in the digital economy, and with globalization, outsourcing and extended supply chains, CEM needs to be approached from a broader supply chain-oriented perspective, incorporating B2B exchanges. This paper builds on the study by Zorzini et al. (2007) by conducting multi-case study research with seven UK-based companies in the capital goods sector, including three sales and support companies with offshore manufacturing. By adopting a cross-national research perspective, it assesses whether the proposed theory applies to other capital goods firms outside Italy. By also adopting a supply chain perspective of CEM it investigates current industry practice in B2B markets and explores whether cross-functional coordination and formalization issues can be extended into a global context. Evidence from the UK generally supports prior theory, confirming links between high levels of coordination, formalization of the CEM process and improved performance. Some refinements are proposed, for example, in order to make the theory suitable for a global context. The characteristics of a supply chain are important factors that affect CEM. This research has managerial implications for improving the CEM process in non-Make-To-Stock (non-MTS) capital goods companies from both an intra and an inter-organisational (B2B) perspective. Coordination with partners along the supply chain is needed at the enquiry stage and constraints linked to global customers should be considered when structuring the

    Interaction Templates for Multi-Robot Systems

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    This work describes a framework for multi-robot problems that require or utilize interactions between robots. Solutions consider interactions on a motion planning level to determine the feasibility and cost of the multi-robot team solution. Modeling these problems with current integrated task and motion planning (TMP) approaches typically requires reasoning about the possible interactions and checking many of the possible robot combinations when searching for a solution. We present a multi-robot planning method called Interaction Templates (ITs) which moves certain types of robot interactions from the task planner to the motion planner. ITs model interactions between a set of robots with a small roadmap. This roadmap is then tiled into the environment and connected to the robots’ individual roadmaps. The resulting combined roadmap allows interactions to be considered by the motion planner. We apply ITs to homogeneous and heterogeneous robot teams under both required and optional cooperation scenarios which previously required a task planning method. We show improved performance over a current TMP planning approach

    Fast Scheduling of Multi-Robot Teams with Temporospatial Constraints

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    Fast Scheduling of Robot Teams Performing Tasks With Temporospatial Constraints

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    The application of robotics to traditionally manual manufacturing processes requires careful coordination between human and robotic agents in order to support safe and efficient coordinated work. Tasks must be allocated to agents and sequenced according to temporal and spatial constraints. Also, systems must be capable of responding on-the-fly to disturbances and people working in close physical proximity to robots. In this paper, we present a centralized algorithm, named 'Tercio,' that handles tightly intercoupled temporal and spatial constraints. Our key innovation is a fast, satisficing multi-agent task sequencer inspired by real-time processor scheduling techniques and adapted to leverage a hierarchical problem structure. We use this sequencer in conjunction with a mixed-integer linear program solver and empirically demonstrate the ability to generate near-optimal schedules for real-world problems an order of magnitude larger than those reported in prior art. Finally, we demonstrate the use of our algorithm in a multirobot hardware testbed
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