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Evaluating new techniques of evidence-based management using narrative evidence synthesis

Evaluating new techniques of evidence-based management using narrative evidence synthesis

Madden, Adrian ORCID: 0000-0002-3193-5808, Bailey, Catherine, Alfes, Kersten and Fletcher, Luke (2019) Evaluating new techniques of evidence-based management using narrative evidence synthesis. In: Wheatley, Daniel, (ed.) Handbook of Research Methods on the Quality of Working Lives. Handbooks of Research Methods in Management . Edward Elgar Publishing, United Kingdon, pp. 282-300. ISBN 978-1788118767 (doi:https://doi.org/10.4337/9781788118774.00028)

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Abstract

Evidence-based management is an approach to establishing ‘best evidence’ which developed from approaches in medical research in the form of systematic reviews. Its goal is to identify and verify relevant and reliable evidence. Interest in the approach has grown in the management field and new techniques have emerged to support this. We tested one of these techniques - narrative evidence synthesis - as a way to systematically identify and evaluate the evidence on employee engagement. Unlike systematic review, narrative evidence synthesis seeks to explain the effects and the contexts of research studies, to ‘tell the story’ of the research, through plausible explanation. However, it is a technique that has a number of strengths and weaknesses, not least placing overwhelming demands on researchers that are difficult to manage. We describe the use of this technique in some depth and the learning that arose from it.

Item Type: Book Section
Uncontrolled Keywords: evidence-based management, narrative synthesis, evidence review
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Department of Human Resources & Organisational Behaviour
Last Modified: 30 Sep 2019 15:15
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/25244

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