On complex adaptive systems and agent-based modelling for improving decision-making in manufacturing and logistics settings: Experiences from a packaging company
(2006) In International Journal of Operations & Production Management 26(12). p.1351-1373- Abstract
- Purpose – This paper aims to contribute to the tactical and operational decision making of
manufacturing and logistics operations by providing novel insights into modelling and simulation,
based on complex adaptive systems (CAS).
Design/methodology/approach – The research approach is theoretically based on CAS with
agent-based modelling (ABM) as the implementation method. A case study is presented where an
agent-based model has contributed to increased understanding and precision in decision making at a
packaging company in the UK.
Findings – The results suggest that ABM provides decision-makers with robust and accurate
“what-if” scenarios of the dynamic interplay... (More) - Purpose – This paper aims to contribute to the tactical and operational decision making of
manufacturing and logistics operations by providing novel insights into modelling and simulation,
based on complex adaptive systems (CAS).
Design/methodology/approach – The research approach is theoretically based on CAS with
agent-based modelling (ABM) as the implementation method. A case study is presented where an
agent-based model has contributed to increased understanding and precision in decision making at a
packaging company in the UK.
Findings – The results suggest that ABM provides decision-makers with robust and accurate
“what-if” scenarios of the dynamic interplay among several business functions. These scenarios can
guide managers in the process of moving from policy space to performance space, i.e. concerning
priorities of improvement efforts and choices of production/manufacturing policies, warehouse
policies, customer service policies and logistics policies. Furthermore, it is found that ABM can include
and pay attention to several aspects of CAS and thus provide understanding of, and explanation for,
the patterns and effects which emerge in manufacturing and logistics settings.
Practical implications – Aided by agent-based models and simulations, practitioners’ levels of
intuition can be enhanced since patterns on the macro level emerge from agents’ interactive behaviour.
Together with insights from CAS these emergent patterns can be explained and understood, and are
thus beneficial for the improvement of decision making in companies.
Originality/value – The case presented distinguishes this paper from what has been written in
previous articles on the application of ABM, since such articles have not produced any empirically
verified results after implementation of ABM. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/167150
- author
- Nilsson, Fredrik LU and Darley, Vince
- organization
- publishing date
- 2006
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Decision making, Modelling, Manufacturing systems, Simulation, Logistics data processing, packaging, Adaptive system theory, packaging logistics
- in
- International Journal of Operations & Production Management
- volume
- 26
- issue
- 12
- pages
- 1351 - 1373
- publisher
- Emerald Group Publishing Limited
- external identifiers
-
- wos:000241963300011
- scopus:33749407387
- ISSN
- 0144-3577
- DOI
- 10.1108/01443570610710588
- language
- English
- LU publication?
- yes
- id
- 3cc14b00-9973-4625-8e44-24dba2058e80 (old id 167150)
- date added to LUP
- 2016-04-01 12:22:42
- date last changed
- 2022-04-05 21:27:51
@article{3cc14b00-9973-4625-8e44-24dba2058e80,
abstract = {{Purpose – This paper aims to contribute to the tactical and operational decision making of<br/><br>
manufacturing and logistics operations by providing novel insights into modelling and simulation,<br/><br>
based on complex adaptive systems (CAS).<br/><br>
Design/methodology/approach – The research approach is theoretically based on CAS with<br/><br>
agent-based modelling (ABM) as the implementation method. A case study is presented where an<br/><br>
agent-based model has contributed to increased understanding and precision in decision making at a<br/><br>
packaging company in the UK.<br/><br>
Findings – The results suggest that ABM provides decision-makers with robust and accurate<br/><br>
“what-if” scenarios of the dynamic interplay among several business functions. These scenarios can<br/><br>
guide managers in the process of moving from policy space to performance space, i.e. concerning<br/><br>
priorities of improvement efforts and choices of production/manufacturing policies, warehouse<br/><br>
policies, customer service policies and logistics policies. Furthermore, it is found that ABM can include<br/><br>
and pay attention to several aspects of CAS and thus provide understanding of, and explanation for,<br/><br>
the patterns and effects which emerge in manufacturing and logistics settings.<br/><br>
Practical implications – Aided by agent-based models and simulations, practitioners’ levels of<br/><br>
intuition can be enhanced since patterns on the macro level emerge from agents’ interactive behaviour.<br/><br>
Together with insights from CAS these emergent patterns can be explained and understood, and are<br/><br>
thus beneficial for the improvement of decision making in companies.<br/><br>
Originality/value – The case presented distinguishes this paper from what has been written in<br/><br>
previous articles on the application of ABM, since such articles have not produced any empirically<br/><br>
verified results after implementation of ABM.}},
author = {{Nilsson, Fredrik and Darley, Vince}},
issn = {{0144-3577}},
keywords = {{Decision making; Modelling; Manufacturing systems; Simulation; Logistics data processing; packaging; Adaptive system theory; packaging logistics}},
language = {{eng}},
number = {{12}},
pages = {{1351--1373}},
publisher = {{Emerald Group Publishing Limited}},
series = {{International Journal of Operations & Production Management}},
title = {{On complex adaptive systems and agent-based modelling for improving decision-making in manufacturing and logistics settings: Experiences from a packaging company}},
url = {{https://lup.lub.lu.se/search/files/2898616/2540374.pdf}},
doi = {{10.1108/01443570610710588}},
volume = {{26}},
year = {{2006}},
}