The University of Southampton
University of Southampton Institutional Repository

Behavioural OR: recent developments and future perspectives

Behavioural OR: recent developments and future perspectives
Behavioural OR: recent developments and future perspectives

Behavioural OR (BOR) is not a new field of study but there have been many recent developments. A key one is the distinction of studying behaviour in, with, or beyond models. To showcase other developments, the chapter outlines the conceptual similarities and differences between BOR and behavioural operations management (BOM) . We also briefly survey the empirical connection with behavioural sciences such as economics and psychology. Interestingly, this survey points to a main future perspective of BOR, its connection to Artificial Intelligence (AI), which raises important issues of how to build transparent and at the same time effective models. The chapter also includes pointers to theoretical, methodological, and educational resources for BOR.

721-733
Springer
Kunc, Martin
0b254052-f9f5-49f9-ac0b-148c257ba412
Katsikopoulos, Konstantinos V.
b97c23d9-8b24-4225-8da4-be7ac2a14fba
Salhi, Saïd
Boylan, John
Kunc, Martin
0b254052-f9f5-49f9-ac0b-148c257ba412
Katsikopoulos, Konstantinos V.
b97c23d9-8b24-4225-8da4-be7ac2a14fba
Salhi, Saïd
Boylan, John

Kunc, Martin and Katsikopoulos, Konstantinos V. (2022) Behavioural OR: recent developments and future perspectives. In, Salhi, Saïd and Boylan, John (eds.) The Palgrave Handbook of Operations Research. Springer, pp. 721-733. (doi:10.1007/978-3-030-96935-6_22).

Record type: Book Section

Abstract

Behavioural OR (BOR) is not a new field of study but there have been many recent developments. A key one is the distinction of studying behaviour in, with, or beyond models. To showcase other developments, the chapter outlines the conceptual similarities and differences between BOR and behavioural operations management (BOM) . We also briefly survey the empirical connection with behavioural sciences such as economics and psychology. Interestingly, this survey points to a main future perspective of BOR, its connection to Artificial Intelligence (AI), which raises important issues of how to build transparent and at the same time effective models. The chapter also includes pointers to theoretical, methodological, and educational resources for BOR.

This record has no associated files available for download.

More information

Published date: 7 July 2022

Identifiers

Local EPrints ID: 479522
URI: http://eprints.soton.ac.uk/id/eprint/479522
PURE UUID: bfad41d1-42ff-41d5-97e2-5fa9a2f82a80
ORCID for Martin Kunc: ORCID iD orcid.org/0000-0002-3411-4052
ORCID for Konstantinos V. Katsikopoulos: ORCID iD orcid.org/0000-0002-9572-1980

Catalogue record

Date deposited: 25 Jul 2023 16:55
Last modified: 06 Jun 2024 02:05

Export record

Altmetrics

Contributors

Author: Martin Kunc ORCID iD
Editor: Saïd Salhi
Editor: John Boylan

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×