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Nicky E. Shaw

Researcher at University of Leeds

Publications -  21
Citations -  611

Nicky E. Shaw is an academic researcher from University of Leeds. The author has contributed to research in topics: Supply chain & Social network analysis. The author has an hindex of 12, co-authored 20 publications receiving 547 citations.

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Asking both university and industry actors about their engagement in knowledge transfer: What single-group studies of motives omit

TL;DR: In this article, a qualitative approach and relying primarily on interviews, the authors show that the motives of (and outcomes for) university and industry actors correspond despite their differing work environments, emphasising stability-seeking as a key determinant of engagement.
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Traditional or contemporary? The prevalence of performance measurement system types

TL;DR: A framework for a contemporary type of PMS that integrates balanced scorecard and other balanced approaches is established, then collects data in an emerging economy and links use of contemporary PMS type to key organisational factors.
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Supply chain agility: the influence of industry culture on asset capabilities within capital intensive industries

TL;DR: In this paper, the need for agility in supply chains and links this to agile plant capabilities is reviewed and the research context and collaboration is described, which focused upon the speciality chemicals industry and involved three UK universities and thirteen industrial partners.
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Performance measurement in organisational networks: an exploratory case study

TL;DR: In this article, the authors introduce the concept of meta-performance, a two-dimensional construct which encapsulates performance per se and equity within a network, without a fair distribution of benefits, a network does not perform effectively in its collaborative dimension and thus could fail to perform altogether.
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Revitalising new process development in the UK fine chemicals industry

TL;DR: In this paper, an action research-derived framework that integrates the detailed processes, information requirements and decision making as a model of good practice for new product (or process) development in the fine chemicals industry is presented.