Facilitating Collaboration on Crowd-Ideation Platforms through Cognitive Load Configuration

Mengyao FU; Weiquan WANG

Facilitating Collaboration on Crowd-Ideation Platforms through Cognitive Load Configuration

Mengyao FU^*
, Weiquan WANG

^*Corresponding author for this work

Department of Information Systems

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

Although crowd-ideation has harnessed digital technologies to tap on the wisdom of the crowd in solving a wide range of business problems, it suffers from issues of redundancy and wasted effort when compared to its traditional offline counterpart. Consequently, an elusive challenge for crowd-ideation platforms stems from how asynchronous collaboration can be fostered among contributors to achieve cumulative knowledge integration. Building on Cognitive Load Theory, this study delineates among three types of cognitive load in collaborative tasks and advances three analytics-driven design features that can be incorporated into crowd- ideation platforms to bolster contributors' efficiency in knowledge integration. A laboratory experiment is further proposed to validate our hypotheses. Findings from this study can contribute towards a deeper understanding of how crowd-ideation platforms can be designed to promote cumulative knowledge integration among contributors by decreasing information overload and configure cognitive load distribution.

Original language	English
Title of host publication	PACIS 2021 Proceedings
Publisher	Association for Information Systems
Chapter	513
ISBN (Print)	978-1-7336325-7-7
Publication status	Published - Jul 2021
Event	25th Pacific Asia Conference on Information Systems (PACIS 2021) - Virtual, Dubai, United Arab Emirates Duration: 12 Jul 2021 → 14 Jul 2021 https://www.pacis2021.org/

Conference

Conference	25th Pacific Asia Conference on Information Systems (PACIS 2021)
Abbreviated title	PACIS2021
Place	United Arab Emirates
City	Dubai
Period	12/07/21 → 14/07/21
Internet address	https://www.pacis2021.org/

Bibliographical note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Research Keywords

Crowdsourcing
Online Crowd-Ideation
Cognitive Load
Load Distribution

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title = "Facilitating Collaboration on Crowd-Ideation Platforms through Cognitive Load Configuration",

abstract = "Although crowd-ideation has harnessed digital technologies to tap on the wisdom of the crowd in solving a wide range of business problems, it suffers from issues of redundancy and wasted effort when compared to its traditional offline counterpart. Consequently, an elusive challenge for crowd-ideation platforms stems from how asynchronous collaboration can be fostered among contributors to achieve cumulative knowledge integration. Building on Cognitive Load Theory, this study delineates among three types of cognitive load in collaborative tasks and advances three analytics-driven design features that can be incorporated into crowd- ideation platforms to bolster contributors' efficiency in knowledge integration. A laboratory experiment is further proposed to validate our hypotheses. Findings from this study can contribute towards a deeper understanding of how crowd-ideation platforms can be designed to promote cumulative knowledge integration among contributors by decreasing information overload and configure cognitive load distribution.",

keywords = "Crowdsourcing, Online Crowd-Ideation, Cognitive Load, Load Distribution",

author = "Mengyao FU and Weiquan WANG",

note = "Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).; 25th Pacific Asia Conference on Information Systems (PACIS 2021), PACIS2021 ; Conference date: 12-07-2021 Through 14-07-2021",

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TY - GEN

T1 - Facilitating Collaboration on Crowd-Ideation Platforms through Cognitive Load Configuration

AU - FU, Mengyao

AU - WANG, Weiquan

N1 - Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

PY - 2021/7

Y1 - 2021/7

N2 - Although crowd-ideation has harnessed digital technologies to tap on the wisdom of the crowd in solving a wide range of business problems, it suffers from issues of redundancy and wasted effort when compared to its traditional offline counterpart. Consequently, an elusive challenge for crowd-ideation platforms stems from how asynchronous collaboration can be fostered among contributors to achieve cumulative knowledge integration. Building on Cognitive Load Theory, this study delineates among three types of cognitive load in collaborative tasks and advances three analytics-driven design features that can be incorporated into crowd- ideation platforms to bolster contributors' efficiency in knowledge integration. A laboratory experiment is further proposed to validate our hypotheses. Findings from this study can contribute towards a deeper understanding of how crowd-ideation platforms can be designed to promote cumulative knowledge integration among contributors by decreasing information overload and configure cognitive load distribution.

AB - Although crowd-ideation has harnessed digital technologies to tap on the wisdom of the crowd in solving a wide range of business problems, it suffers from issues of redundancy and wasted effort when compared to its traditional offline counterpart. Consequently, an elusive challenge for crowd-ideation platforms stems from how asynchronous collaboration can be fostered among contributors to achieve cumulative knowledge integration. Building on Cognitive Load Theory, this study delineates among three types of cognitive load in collaborative tasks and advances three analytics-driven design features that can be incorporated into crowd- ideation platforms to bolster contributors' efficiency in knowledge integration. A laboratory experiment is further proposed to validate our hypotheses. Findings from this study can contribute towards a deeper understanding of how crowd-ideation platforms can be designed to promote cumulative knowledge integration among contributors by decreasing information overload and configure cognitive load distribution.

KW - Crowdsourcing

KW - Online Crowd-Ideation

KW - Cognitive Load

KW - Load Distribution

UR - https://www.webofscience.com/wos/woscc/full-record/WOS:001435194500091

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 978-1-7336325-7-7

BT - PACIS 2021 Proceedings

PB - Association for Information Systems

T2 - 25th Pacific Asia Conference on Information Systems (PACIS 2021)

Y2 - 12 July 2021 through 14 July 2021

ER -

Facilitating Collaboration on Crowd-Ideation Platforms through Cognitive Load Configuration

Abstract

Conference

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Research Keywords

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