Comparing crowdsourcing initiatives: Toward a typology development

• Published date: 01 December 2016
• Author: Hesham Allam,Hossam Ali‐Hassan
• Date: 01 December 2016
• DOI: http://doi.org/10.1002/cjas.1395

Comparing crowdsourcing initiatives: Toward a

typology development

Hossam Ali-Hassan*

Dalhousie University

Hesham Allam

Higher Colleges of Technology

Abstract

Although numerous studies have examined the

crowdsourcing phenomenon, little consensus exists regard-

ing the classif‌ication of distinct types of activities within

crowdsourcing. In this study, we identify and classify 12

crowdsourcing initiatives that comprise the key categories

of crowdsourcing: Crowdpedia,Fansourcing,Crowd-

networking,Crowdsharing,Crowdvoting,Crowdfunding,

Ideation,Open Innovation,User Innovation,Scisourcing,

Crowd-Relief,and Open Source Software. Our main objec-

tive is to establish the similarities and differences between

basic crowdsourcing initiatives and develop a typology

based on nine crowdsourcing dimensions that we develop.

This crowdsourcing typology will provide a roadmap on

which researchers can anchor their research and practitioners

can make more informed decisions about which category of

crowdsourcing they should seek. Copyright © 2016 ASAC.

Published by John Wiley & Sons, Ltd.

Keywords: crowdsourcing, typology, initiatives, dimen-

sions, classif‌ication

Résumé

Même si plusieurs études se sont penchées sur le phénomène de

l’externalisation ouverte, la classif‌ication des différents types

d’activités ayant cours à l’intérieur de cette externalisation

ouverte ne fait pas l’unanimité. Dans cette étude, nous recensons

et classons 12 initiatives d’externalisation ouverte qui constitu-

ent les principales catégories de l’externalisation ouverte, à

savoir: le crowdpedia,le fansourcing,le réseau participatif,le

partage participatif,le vote participatif,le f‌inancement

participatif,l’idéation,l’innovation ouverte,l’innovation

amorcée par l’utilisateur,le scisourcing,le crowd-Relief,et le

logiciel libre. Notre objectif principal est d’établir les similitudes

entre les initiatives d’externalisation ouverte et de proposer une

typologie basée sur neuf dimensions d’externalisation ouverte.

Cette typologie constitue une feuille de route qui pourra aider

les chercheurs à orienter leurs recherches et les praticiens à

prendre des décisions informées concernant la catégorie

d’externalisation ouverte à privilégier. Copyright © 2016

ASAC. Published by John Wiley & Sons, Ltd.

Mots-clés : externalisation ouverte, typologie, initiatives,

dimensions, classif‌ication

Composed of the terms “crowd”and “outsourcing,”

crowdsourcing is a Web 2.0 phenomenon that means

outsourcing tasks to the crowd (Schenk & Guittard, 2011).

Among the early def‌initions is that by Jeff Howe and Mark

Robinson, who def‌ined it as:

the act of a company or institution taking a function once

performed by employees and outsourcing it to an unde-

f‌ined (and generally large) network of people in the form

of an open call. This can take the form of peer-production

(when the job is performed collaboratively), but is also

often undertaken by sole individuals. The crucial

prerequisite is the use of the open call format and the

large network of potential laborers. (Howe, 2006a, p. 1)

Crowdsourcing is an effective tool that uses the crowd to

accomplish work online. The tasks that the crowd accomplishes

range from classifying craters on planetary surfaces,

interpreting scanned text, discovering new galaxies (Kittur,

2010), creating knowledge repositories as in Wikipedia (Anhai,

Ramakrishnan, & Halvey, 2011), to completing routine tasks as

in Amazon Mechanical Turk (Bogers & West, 2012). In the

past, many crowdsourcing initiatives have emerged with similar

characteristics. The number of emerging crowdsourcing initia-

tives and the number of tasks the crowd can perform has led

to naming conventions and practices that have allowed many

studies to mistakenly treat some crowdsourcing sites as

noncrowdsourcing practices and vice versa. For example, sev-

eral studies (Bichler, Gupta, & Ketter, 2010; Di-Gangi &

Wasko, 2009; Jeppesen & Lakhani, 2010; Whitla, 2009) re-

stricted crowdsourcing practices to include only those explicit

The authors want to thank the two anonymous reviewers for their invaluable

feedback and suggestions to improve the paper. This study was generously

funded by a grant from the Social Sciences and Humanities Research

Council (SSHRC) of Canada.

*Please address correspondence to: Hossam Ali-Hassan, Dalhousie Univer-

sity, Rowe School of Business, 6100 University Ave., Halifax, Nova Scotia,

B3H 3 J5, Canada. Email: hossam@dal.ca

Canadian Journal of Administrative Sciences

Revue canadienne des sciences de l’administration

33: 318–331 (2016)

Published online 19 August 2016 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/CJAS.1395

Can J Adm Sci

33(4), 318–331 (2016)Copyright © 2016 ASAC. Published by John Wiley & Sons, Ltd. 318