Team problem solving and motivation under disorganization: an agent-based modeling approach

Dinuka Herath, Joyce Costello, Fabian Homberg

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Purpose: This paper aims at simulating on how “disorganization” affects team problem solving and motivation. The prime objective is to determine how team problem solving varies between an organized and disorganized environment.
Design/methodology/approach: Using agent-based modeling, we use a real world data set from 226 volunteers at five different types of non-profit organizations in Southwest England in order to define some attributes of the agents. We introduce the concepts of natural, structural and functional disorganization while operationalizing natural and functional disorganization.
Findings: The simulations show that “disorganization” is more conducive for problem solving efficiency than “organization” given enough flexibility (range) to search and acquire resources. Our findings further demonstrate that teams with resources above their hierarchical level (access to better quality resources) tend to perform better than teams that have only limited access to resources.
Originality/value: Our nuanced categories of “(dis-)organization” allow us to compare between various structural limitations, thus generating insights for improving the way managers structure teams for better problem solving.
LanguageEnglish
Pages46-65
Number of pages20
JournalTeam Performance Management
Volume23
Issue number1/2
DOIs
Publication statusPublished - 1 Jan 2017
Externally publishedYes

Fingerprint

Managers
Disorganization
Problem solving
Agent-based modeling
Resources
Design methodology
Nonprofit organization
Simulation
Volunteers
England

Cite this

@article{172b2ee315134286a47937347b6150e8,
title = "Team problem solving and motivation under disorganization: an agent-based modeling approach",
abstract = "Purpose: This paper aims at simulating on how “disorganization” affects team problem solving and motivation. The prime objective is to determine how team problem solving varies between an organized and disorganized environment.Design/methodology/approach: Using agent-based modeling, we use a real world data set from 226 volunteers at five different types of non-profit organizations in Southwest England in order to define some attributes of the agents. We introduce the concepts of natural, structural and functional disorganization while operationalizing natural and functional disorganization. Findings: The simulations show that “disorganization” is more conducive for problem solving efficiency than “organization” given enough flexibility (range) to search and acquire resources. Our findings further demonstrate that teams with resources above their hierarchical level (access to better quality resources) tend to perform better than teams that have only limited access to resources.Originality/value: Our nuanced categories of “(dis-)organization” allow us to compare between various structural limitations, thus generating insights for improving the way managers structure teams for better problem solving.",
keywords = "Agent-based modeling, Problem solving, Disorganization",
author = "Dinuka Herath and Joyce Costello and Fabian Homberg",
year = "2017",
month = "1",
day = "1",
doi = "10.1108/TPM-10-2015-0046",
language = "English",
volume = "23",
pages = "46--65",
journal = "Team Performance Management",
issn = "1352-7592",
publisher = "Emerald Group Publishing Ltd.",
number = "1/2",

}

Team problem solving and motivation under disorganization : an agent-based modeling approach. / Herath, Dinuka; Costello, Joyce; Homberg, Fabian.

In: Team Performance Management, Vol. 23, No. 1/2, 01.01.2017, p. 46-65.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Team problem solving and motivation under disorganization

T2 - Team Performance Management

AU - Herath, Dinuka

AU - Costello, Joyce

AU - Homberg, Fabian

PY - 2017/1/1

Y1 - 2017/1/1

N2 - Purpose: This paper aims at simulating on how “disorganization” affects team problem solving and motivation. The prime objective is to determine how team problem solving varies between an organized and disorganized environment.Design/methodology/approach: Using agent-based modeling, we use a real world data set from 226 volunteers at five different types of non-profit organizations in Southwest England in order to define some attributes of the agents. We introduce the concepts of natural, structural and functional disorganization while operationalizing natural and functional disorganization. Findings: The simulations show that “disorganization” is more conducive for problem solving efficiency than “organization” given enough flexibility (range) to search and acquire resources. Our findings further demonstrate that teams with resources above their hierarchical level (access to better quality resources) tend to perform better than teams that have only limited access to resources.Originality/value: Our nuanced categories of “(dis-)organization” allow us to compare between various structural limitations, thus generating insights for improving the way managers structure teams for better problem solving.

AB - Purpose: This paper aims at simulating on how “disorganization” affects team problem solving and motivation. The prime objective is to determine how team problem solving varies between an organized and disorganized environment.Design/methodology/approach: Using agent-based modeling, we use a real world data set from 226 volunteers at five different types of non-profit organizations in Southwest England in order to define some attributes of the agents. We introduce the concepts of natural, structural and functional disorganization while operationalizing natural and functional disorganization. Findings: The simulations show that “disorganization” is more conducive for problem solving efficiency than “organization” given enough flexibility (range) to search and acquire resources. Our findings further demonstrate that teams with resources above their hierarchical level (access to better quality resources) tend to perform better than teams that have only limited access to resources.Originality/value: Our nuanced categories of “(dis-)organization” allow us to compare between various structural limitations, thus generating insights for improving the way managers structure teams for better problem solving.

KW - Agent-based modeling

KW - Problem solving

KW - Disorganization

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85017242783&origin=resultslist&sort=plf-f&src=s&st1=Team+problem+solving+and+motivation+under+disorganization&st2=&sid=59a5b70182e16cacad390d36180987aa&sot=b&sdt=b&sl=72&s=TITLE-ABS-KEY%28Team+problem+solving+and+motivation+under+disorganization%29&relpos=0&citeCnt=4&searchTerm=

U2 - 10.1108/TPM-10-2015-0046

DO - 10.1108/TPM-10-2015-0046

M3 - Article

VL - 23

SP - 46

EP - 65

JO - Team Performance Management

JF - Team Performance Management

SN - 1352-7592

IS - 1/2

ER -