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Mixed methods practice in operational research: designs for wicked problems

Christie, Jane S. (2023) Mixed methods practice in operational research: designs for wicked problems. In: Cameron, Roslyn and Golenko, Xanthe, eds. Handbook of Mixed Methods Research in Business and Management. Edward Elgar Publishing Limited, Cheltenham, Glos, pp. 163-178. ISBN 978-1-80088-794-7. E-ISBN 978-1-80088-795-4. (doi:10.4337/9781800887954.00019) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:95250)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL:
https://doi.org/10.4337/9781800887954.00019

Abstract

In operational research (OR), practitioners model and analyse real-world issues, and support organizational and policy decision-making. Traditionally, they use quantitative methods, such as optimization, simulation, and statistical analysis. Many also use participative, qualitative modelling methodologies known as problem structuring methods (PSMs), which are particularly suitable for wicked problems. There have been recent, renewed calls for OR practice that integrates PSMs with traditional methods, and for guidance for practitioners, students and organizational clients on how to do it and its benefits. Accordingly, in this chapter, I introduce mixed methods practice and theory in OR, review the prevalence of mixing PSMs with traditional OR, and showcase six methodological designs with examples – typical and innovative – from OR interventions across public, private, and third sector organizations. I describe a range of benefits, including successful engagement with dynamic, social, organizational contexts, and discuss current and future research directions.

Item Type: Book section
DOI/Identification number: 10.4337/9781800887954.00019
Projects: Executive Decision-Making in Complex and Dynamic Environments
Additional information: For the purpose of open access, the author(s) has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising.
Uncontrolled keywords: Analytics; Behavioural OR; Hybrid modelling; Management science; Multimethodology; Systems thinking
Subjects: H Social Sciences
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Funders: Economic and Social Research Council (https://ror.org/03n0ht308)
Defence Science and Technology Laboratory (https://ror.org/04jswqb94)
Depositing User: Jane Christie
Date Deposited: 29 Sep 2022 08:29 UTC
Last Modified: 08 Feb 2024 14:10 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/95250 (The current URI for this page, for reference purposes)

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