Collaboration and multitasking in networks

Prioritization and achievable capacity

Itai Gurvich, Jan Van Mieghem

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Motivated by the trend toward more collaboration in workflows, we study networks where some tasks require the simultaneous processing by multiple types of multitasking human or indivisible resources. The capacity of such networks is generally smaller than the bottleneck capacity. In Gurvich and Van Mieghem [Gurvich I, Van Mieghem JA (2015) Collaboration and multitasking in networks: Architectures, bottlenecks, and capacity. Manufacturing Service Oper. Management 17(1):16-33], we proved that both capacities are equal in networks with a hierarchical collaboration architecture, which define a collaboration level for each task depending on how many types of resources it requires. This paper studies how task prioritization impacts the achievable capacity of such hierarchical networks using a conceptual queueing framework that formalizes coordination and switching idleness. To maximize the capacity of a collaborative network, highest priority must be given to the tasks that require the most collaboration. Otherwise, a mismatch between priority levels and collaboration levels inevitably inflicts a capacity loss. We demonstrate this fundamental tension between flexibility in task prioritization (ability to adjust quality of service) and capacity (productivity) in a basic collaborative network and in parallel networks. To manage this trade-off, we present a hierarchical threshold priority policy that balances switching and coordination idleness.

Original languageEnglish (US)
Pages (from-to)2390-2406
Number of pages17
JournalManagement Science
Volume64
Issue number5
DOIs
StatePublished - May 1 2018

Fingerprint

Prioritization
Multitasking
Resources
Collaborative networks
Mismatch
Queueing
Quality of service
Manufacturing
Trade-offs
Productivity

Keywords

  • Architectures
  • Capacity
  • Collaboration
  • Control
  • Multitasking
  • Priority
  • Productivity
  • Resource sharing
  • Stability
  • Teams

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research

Cite this

@article{6b020360fcc041a6b373f3917a539d8d,
title = "Collaboration and multitasking in networks: Prioritization and achievable capacity",
abstract = "Motivated by the trend toward more collaboration in workflows, we study networks where some tasks require the simultaneous processing by multiple types of multitasking human or indivisible resources. The capacity of such networks is generally smaller than the bottleneck capacity. In Gurvich and Van Mieghem [Gurvich I, Van Mieghem JA (2015) Collaboration and multitasking in networks: Architectures, bottlenecks, and capacity. Manufacturing Service Oper. Management 17(1):16-33], we proved that both capacities are equal in networks with a hierarchical collaboration architecture, which define a collaboration level for each task depending on how many types of resources it requires. This paper studies how task prioritization impacts the achievable capacity of such hierarchical networks using a conceptual queueing framework that formalizes coordination and switching idleness. To maximize the capacity of a collaborative network, highest priority must be given to the tasks that require the most collaboration. Otherwise, a mismatch between priority levels and collaboration levels inevitably inflicts a capacity loss. We demonstrate this fundamental tension between flexibility in task prioritization (ability to adjust quality of service) and capacity (productivity) in a basic collaborative network and in parallel networks. To manage this trade-off, we present a hierarchical threshold priority policy that balances switching and coordination idleness.",
keywords = "Architectures, Capacity, Collaboration, Control, Multitasking, Priority, Productivity, Resource sharing, Stability, Teams",
author = "Itai Gurvich and {Van Mieghem}, Jan",
year = "2018",
month = "5",
day = "1",
doi = "10.1287/mnsc.2017.2722",
language = "English (US)",
volume = "64",
pages = "2390--2406",
journal = "Management Science",
issn = "0025-1909",
publisher = "INFORMS Inst.for Operations Res.and the Management Sciences",
number = "5",

}

Collaboration and multitasking in networks : Prioritization and achievable capacity. / Gurvich, Itai; Van Mieghem, Jan.

In: Management Science, Vol. 64, No. 5, 01.05.2018, p. 2390-2406.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Collaboration and multitasking in networks

T2 - Prioritization and achievable capacity

AU - Gurvich, Itai

AU - Van Mieghem, Jan

PY - 2018/5/1

Y1 - 2018/5/1

N2 - Motivated by the trend toward more collaboration in workflows, we study networks where some tasks require the simultaneous processing by multiple types of multitasking human or indivisible resources. The capacity of such networks is generally smaller than the bottleneck capacity. In Gurvich and Van Mieghem [Gurvich I, Van Mieghem JA (2015) Collaboration and multitasking in networks: Architectures, bottlenecks, and capacity. Manufacturing Service Oper. Management 17(1):16-33], we proved that both capacities are equal in networks with a hierarchical collaboration architecture, which define a collaboration level for each task depending on how many types of resources it requires. This paper studies how task prioritization impacts the achievable capacity of such hierarchical networks using a conceptual queueing framework that formalizes coordination and switching idleness. To maximize the capacity of a collaborative network, highest priority must be given to the tasks that require the most collaboration. Otherwise, a mismatch between priority levels and collaboration levels inevitably inflicts a capacity loss. We demonstrate this fundamental tension between flexibility in task prioritization (ability to adjust quality of service) and capacity (productivity) in a basic collaborative network and in parallel networks. To manage this trade-off, we present a hierarchical threshold priority policy that balances switching and coordination idleness.

AB - Motivated by the trend toward more collaboration in workflows, we study networks where some tasks require the simultaneous processing by multiple types of multitasking human or indivisible resources. The capacity of such networks is generally smaller than the bottleneck capacity. In Gurvich and Van Mieghem [Gurvich I, Van Mieghem JA (2015) Collaboration and multitasking in networks: Architectures, bottlenecks, and capacity. Manufacturing Service Oper. Management 17(1):16-33], we proved that both capacities are equal in networks with a hierarchical collaboration architecture, which define a collaboration level for each task depending on how many types of resources it requires. This paper studies how task prioritization impacts the achievable capacity of such hierarchical networks using a conceptual queueing framework that formalizes coordination and switching idleness. To maximize the capacity of a collaborative network, highest priority must be given to the tasks that require the most collaboration. Otherwise, a mismatch between priority levels and collaboration levels inevitably inflicts a capacity loss. We demonstrate this fundamental tension between flexibility in task prioritization (ability to adjust quality of service) and capacity (productivity) in a basic collaborative network and in parallel networks. To manage this trade-off, we present a hierarchical threshold priority policy that balances switching and coordination idleness.

KW - Architectures

KW - Capacity

KW - Collaboration

KW - Control

KW - Multitasking

KW - Priority

KW - Productivity

KW - Resource sharing

KW - Stability

KW - Teams

UR - http://www.scopus.com/inward/record.url?scp=85047193029&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85047193029&partnerID=8YFLogxK

U2 - 10.1287/mnsc.2017.2722

DO - 10.1287/mnsc.2017.2722

M3 - Article

VL - 64

SP - 2390

EP - 2406

JO - Management Science

JF - Management Science

SN - 0025-1909

IS - 5

ER -