Content uploaded by Qinghua Zhu
Author content
All content in this area was uploaded by Qinghua Zhu on Jul 14, 2016
Content may be subject to copyright.
Content uploaded by Qinghua Zhu
Author content
All content in this area was uploaded by Qinghua Zhu on Jul 14, 2016
Content may be subject to copyright.
Effects of extrinsic and intrinsic
motivation on participation in
crowdsourcing contest
A perspective of self-determination theory
Yuxiang Chris Zhao and Qinghua Zhu
School of Information Management, Nanjing University,
Nanjing, China
Abstract
Purpose – The rapid development of Web 2.0 and social media enables the rise of crowdsourcing.
Crowdsourcing contest is a typical case of crowdsourcing and has been adopted by many
organisations for business solution and decision making. From a participant’s perspective, it is
interesting to explore what motivates people to participate in crowdsourcing contest. The purpose of
this paper is to investigate the category of motivation based on self-determination theory and
synthesises various motivation factors in crowdsourcing contest. Meanwhile, perceived motivational
affordances and task granularity are also examined as the moderate constructs.
Design/methodology/approach – The paper builds a conceptual model to illustrate the
relationships between various motivations (extrinsic and intrinsic) and participation effort under
the moderating of perceived motivational affordances and task granularity. An empirical study is
conducted to test the research model by surveying the Chinese participants of crowdsourcing contest.
Findings – The results show that various motivations might play different roles in relating to
participation effort expended in the crowdsourcing contest. Moreover, task granularity may positively
moderate the relationship between external motivation and participation effort. The results also
show that supporting of a participant’s perceived motivational affordances might strengthen the
relationship between the individual’s motivation with an internal focus (intrinsic, integrated, identified
and introjected motivation) and participation effort.
Originality/value – Overall, the research has some conceptual and theoretical implications to the
literature. This study synthesises various motivation factors identified by previous studies in
crowdsourcing projects or communities as a form of motivation spectrum, namely external,
introjected, identified, integrated and intrinsic motivation, which contributes to the motivation
literatures. Meanwhile, the findings indicate that various motivations might play different roles in
relating to participation effort expended in the crowdsourcing contest. Also, the study theoretically
extends the crowdsourcing participation research to incorporate the effects of perceived motivational
affordances in crowdsourcing contest. In addition, the study may yield some practical implications for
sponsors, managers and designers in crowdsourcing contest.
Keywords Self-determination theory, Crowdsourcing contest, Moderating effects, Motivation theory,
Motivational affordances, Task granularity
Paper type Research paper
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1468-4527.htm
Received 13 August 2014
Third revision approved
24 September 2014
Online Information Review
Vol. 38 No. 7, 2014
pp. 896-917
rEmerald Group Publishing Limited
1468-4527
DOI 10.1108/OIR-08-2014-0188
The authors would like to thank the Editor-in-Chief and anonymous reviewers of Online
Information Review for their help in improving this paper. The authors also thank Professor
Susan Gasson for her insightful suggestions on an early draft of this manuscript and also
Professor Fiona Fui-Hoon Nah for her constructive comments on this paper in the AIS-Joint
Author Workshop at PACIS 2013. This work is jointly supported by the National Science
Foundation in China (No. 71403119, 71390521 and 71473114), and the Ministry of Education,
Humanities and Social Sciences Council in China (No. 13YJC870033).
896
OIR
38,7
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
Introduction
Crowdsourcing is a recent phenomenon that has been widely applied in practice and is
yet to receive intense attention from scholars. The term was first coined by Howe in a
Wired Magazine article in June 2006. It is defined as the act of a company or institution
taking a function once performed by employees and outsourcing it to an undefined
network of people in the form of an open call (Howe, 2006). In essence crowdsourcing is
based on a simple but powerful concept: virtually everyone has the potential to
contribute valuable information (Greengard, 2011). It is no surprise that crowdsourcing’s
popularity increased exponentially in parallel with the development of the internet
technologies and Web 2.0.
Although still at an early stage crowdsourcing has received considerable attention
in the business world, and many companies have realised its potential business value
and launched campaigns using it (Leimeister et al., 2009; Rouse, 2010; Whitla, 2009).
The crowdsourcing contest is one of the most important forms of crowdsourcing and
has been adopted by many firms for problem solving and decision making (Archak
and Sundararajan, 2009; Yang et al., 2008). By launching crowdsourcing contests
organisations can easily reach a large volume of external participants with diverse
skills and leverage the wisdom of the crowds. Nowadays there are many contest
markets with different foci or targets, such as 99Designs, Threadless, IStockPhoto,
Marketocracy and UTest, etc. (Zhao and Zhu, 2014). Furthermore, crowdsourcing
contests can be implemented through either firm-hosted communities or third-party
providers, such as Amazon Mechanical Turk, who help the firm to build and manage
portals (Zhao and Zhu, 2012; Zheng et al., 2011).
Since the essence of crowdsourcing is crowd wisdom and collective intelligence
(Gregg, 2010) the successful initialisation and sustainable development of crowdsourcing
communities largely depend on mass participation. Thus it is of great importance to
explore what motivates the crowd to participate in crowdsourcing contests, and how
to design an effective crowdsourcing contest to attract users’ participation is a high
priority for researchers and practitioners (Leimeister et al., 2009). Past research has
highlighted the significance of the intrinsic-extrinsic motivational orientation, indicating
that an individual may walk into a situation with a specific motivation orientation which
influences the type of motivation involved in a particular task (Chan, 2005). This study
examines motivation based on self-determination theory (Deci and Ryan, 2000; Ryan and
Deci, 2000) and synthesises various motivational factors in crowdsourcing contests
in the form of a motivation spectrum. Our work has both theoretical and practical
implications. Theoretically it is interesting to see how the various motivational
categories jointly affect participation efforts in crowdsourcing contests. Practically it
helps sponsors, vendors and designers to better understand the incentive mechanisms of
mass participation, and adjust their strategies to receive more high-quality feedback
from the crowd. Specifically we shall answer the following research questions:
RQ1. What are the motivational orientations and related sub-categories in
crowdsourcing contests?
RQ2. What are the relationships between those motivational categories and
participation efforts?
RQ3. How do perceived motivational affordances and task granularity moderate
various motivations and participation efforts in crowdsourcing contests?
897
Effects of
extrinsic and
intrinsic
motivation
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
Theoretical foundation
User participation has long been a hot topic in information systems theory and has been
widely examined in a set of related activities, such as open innovation, outsourcing,
co-creation and open source software (Bagozzi and Dholakia, 2006; Ke and Zhang, 2010;
Krishnamurthy, 2006). However, motivators in open innovation, outsourcing and open
source software are helpful but not precisely transferrable to crowdsourcing contests due
to the differences between them (Horton and Chilton, 2010; Stewart et al., 2009; Zhao and
Zhu, 2014). So far some empirical studies have been conducted to explain the many
reasons for user participation in crowdsourcing applications (e.g. Brabham, 2008, 2010;
Kaufmann et al., 2011; Zheng et al., 2011). On the one hand researchers have attempted to
explore how the sponsors’ actions can attract more participants (e.g. Di Gangi and
Wasko, 2009). On the other hand some studies have focused on the contestants’
characteristics that may have a direct influence on their participation intentions (e.g.
Zheng et al., 2011). However, some findings are conflicting, especially in regard to the
importance of making money as a motivator across varying crowdsourcing cases
(Brabham, 2010; Zheng et al., 2011; Zhong et al.,2011).
Self-determination theory
Although the evidence is mixed regarding the relative influence of intrinsic and
extrinsic motivational elements, most of the motivation studies found that both
intrinsic and extrinsic motivational components are important (Krishnamurthy, 2006).
However, many motivation theories treat motivation as a unitary concept that varies
in amount rather than type (Ke and Zhang, 2010), even theories that indicate the
intrinsic-extrinsic distinction may not be a sufficient taxonomy due to the complexity
of decision-making processes and real world cases.
Self-determination theory represents a broad framework for the study of human
motivation (Deci and Ryan, 2000; Ryan and Deci, 2000). It has been developed and
explored through a set of five sub-theories. Among them organismic integration theory
contends that motivation is neither a unitary nor a bipolar construct and a smooth
transition between internal and external motivation seems to exist within the extrinsic
category depending on the type of regulation and internalisation (Deci and Ryan, 2000).
Broadly speaking extrinsic motivation applies to behaviour that is instrumental – that
aims towards outcomes extrinsic to the behaviour itself (Deci and Ryan, 2000).
Yet there are distinct forms of instrumentality which include external regulation,
introjection, identification and integration (Ke and Zhang, 2010). These subtypes of
extrinsic motivation are seen as falling along a continuum of internalisation (Deci and
Ryan, 2000; Gagne and Deci, 2005; Ryan and Deci, 2000). External motivation indicates
an individual’s intention to achieve a desired result or avoid an undesired one (Ke and
Zhang, 2010). With an introjected motivation, the regulation has been absorbed by the
individual but has not been accepted as one (Deci and Ryan, 1995; Ke and Zhang, 2010).
When it comes to an identified motivation, a person feels greater freedom and volition
because the behaviour is more congruent with his or her personal goals and identity
(Ke and Zhang, 2010). Furthermore, integrated regulation can be viewed as the most
autonomous category of extrinsic motivation. It occurs when regulations are fully
assimilated by the actor and strongly embedded in his or her behaviours.
Figure 1 illustrates the various motivations as a spectrum anchored by the locus
of regulations. Accordingly we summarise some factors in each column that have
either been identified by previous studies or that have some potential impacts on
participants’ motivation in crowdsourcing contests.
898
OIR
38,7
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
Conceptual model
Dependent and independent constructs
Generally individuals expend a certain degree of effort in doing a task. Stewart
et al. (2010) propose a SCOUT model to demonstrate the varying participation in
crowdsourcing, based on the level of effort that can be measured in terms of quantity of
contribution and the nature of participants’ motivations. Terwiesch and Xu (2008) also
propose a linear model to formulise the quality of solutions in open innovation contests,
in which the variance of a solver’s performance is mainly based on their effort. Although
people tend to minimise the effort when they engage in a task (Todd and Benbasat, 1992),
the degree of participation effort required by a specific activity must be fully considered
when establishing a relationship between increases in effort and changes in performance
(Chan and Song, 2010). Thus in this study participation effort is the dependent variable
in our research model and defined as the extent of intensity and persistence of
intellectual resources that crowdsourcing contest participants invest in this activity.
Two characteristics are emphasised in this construct: intensity and persistence (Kanfer,
1991). Intensity measures how hard a participant works on the crowdsourcing
contest. Persistence refers to a participant’s commitment to the contest, and comprises
two components: time commitment and task persistence in face of difficulties (Ke and
Zhang, 2010).
In crowdsourcing contests participants are also motivated by internal and external
factors involved in this activity. In particular external motivation drives a participant
to work hard in order to get expected rewards such as monetary compensation (Archak
and Sundararajan, 2009; Stewart et al., 2009) and better job opportunities (Brabham,
2008, 2010). This is especially so when rewards are performance-contingent (Ryan and
Deci, 2000) and some crowdsourcing systems largely externalise the financial incentive
mechanism.
We also find that reciprocity and signalling capability to potential employers
(Lakhani and Wolf, 2005) are two important reasons which may lead to the enhancement
1. Monetary reward
(Archak, 2010; Bayus,
2010; DiPalantino and
Vojnovic, 2009; Horton
and Chilton, 2010;
Stewart et al., 2010)
2. To improve job
prospects (Brabham,
2008, 2010)
3. Reciprocity
4. To signal capability to
potential employers
(Lakhani and Wolf, 2005)
1. To gain peer
recognition (Brabham
2008, 2010)
2. Perceived
usefulness (Zhong et
al., 2011)
3.General trust
(Zheng et al., 2011)
4. Subjective norm
1. Glory (Archak,
2010)
2. Social
identification
(Lakhani and Wolf,
2005)
3. Specific trust
(Zheng et al., 2011)
4.Task requirement
and fit
1. Sense of virtual
community (Brabham,
2010; Zhong et al.,
2011)
2. Past experience
(Bayus, 2010)
3. Sense of belonging
4. Personal obligation
and commitment
1. Perceived
enjoyment and fun
(Brabham, 2008,
2010; Stewart et al.,
2010)
2. To develop
individual skills
(Brabham, 2010;
Zhong et al., 2011)
3. Curiosity and
interest (Brabham,
2010)
4. Self-affirmation
(Zhong et al., 2011)
5. Pastime (Ipeirotis,
2010)
6. Altruism
External
Motivation
Introjected
Motivation
Identified
Motivation
Integrated
Motivation
Intrinsic
Motivation
Figure 1.
Motivation spectrum
and related factors
in crowdsourcing contest
899
Effects of
extrinsic and
intrinsic
motivation
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
of participation effort. With introjected motivation a participant is pursuing recognition
among peers in a crowdsourcing community (Brabham, 2010) and thus puts effort into
the contest. Meanwhile general trust and subjective norms also play an important
role in regulation of an individual’s behaviour. In terms of identified motivation the
internalisation of regulatory control and identification with the project’s objective lead
the participant to gain a sense of emotional involvement (Allen and Meyer, 1996).
Therefore the participant is inspired to work hard on providing solutions and feedback,
which may in turn enhance their sense of glory (Archak, 2010) and social identification.
With integrated motivation the participants regard their work in the crowdsourcing
contest as meaningful and significant, which may cultivate a sense of virtual
community (Brabham, 2010; Zhong et al., 2011). The forming of a sense of virtual
community will further increase a participant’s sense of belonging and personal
obligation and commitment, which may lead to strong crowd loyalty and continuous
participation. Thus the participant perceives expending effort on the crowdsourcing
contest as worthwhile. In terms of intrinsic motivation prior studies have examined its
important role in facilitating the crowd’s participation and identified several key
factors such as perceived enjoyment and fun, curiosity and interest, developing
individual skills and self-affirmation, etc. (Brabham, 2010; Stewart et al., 2009).
Hence we propose the following motivation hypotheses:
H1a. A crowd’s external motivation positively relates to participation effort
expended in the crowdsourcing contest.
H1b. A crowd’s introjected motivation positively relates to participation effort
expended in the crowdsourcing contest.
H1c. A crowd’s identified motivation positively relates to participation effort
expended in the crowdsourcing contest.
H1d. A crowd’s integrated motivation positively relates to participation effort
expended in the crowdsourcing contest.
H1e. A crowd’s intrinsic motivation positively relates to participation effort
expended in the crowdsourcing contest.
Moderating constructs
Perceived motivational affordances. The concept “motivational affordances” is proposed
by Zhang (2008a, b) as facilitating the positive design and use of information and
communication technologies. It comprises the properties of an artefact that determine
whether and how it can support one’s motivational needs (Zhang, 2008a). Based on
Norman’s (1999) work it becomes increasingly important to differentiate an object’s
intended affordance by designers from the perceived affordance by users (Norman, 2008).
Thus in this study we define motivational affordances as a series of supporting elements
perceived by participants during their interaction with the crowdsourcing systems and
sponsors. Although perceived motivational affordances may have some direct effects on
internal motivation and participation effort, in this paper we focus on the moderating
effects of motivational affordances.
Some crowdsourcing platforms allow the users to personalise their interfaces
according to their interests or specialised categories; for instance users can select the
900
OIR
38,7
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
categories they participate in most often as their favourites on the personalised
homepage in Zhubajie (www.zhubajie.com) thus providing autonomy to enhance users’
introjected motivation to participate in crowdsourcing contests. Some crowdsourcing
systems provide their users with a detailed “personal growth record”, which illustrates
each user’s current stages, finished tasks, success ratio and growth rate to motivate
users to undertake challenging tasks. In such cases the satisfaction of competence may
facilitate users’ identified motivation. Although crowdsourcing contests have a strong
sense of competition, some platforms still provide a social network function for their
users to voluntarily connect with other people and get involved in online communities
(e.g. Threadless). Meanwhile some crowdsourcing systems (e.g. Taskcn) provide
interfaces for the contestants to contact the sponsors in an easy and convenient way.
Hence the satisfaction of relatedness may largely improve the quantity and quality of
crowd communities, and in turn facilitate users’ integrated motivation to participate
(sense of community and sense of belonging).
In addition leadership can be represented by success stories in social media as an
important user motive and embedded function (e.g. like, dislike, follow), which may
enhance users’ introjected, identified, integrated and intrinsic motivations to
participate in crowdsourcing contests (e.g. 99Designs’s billboard for designers).
Affect may influence the behavioural outcome of motivation and make individuals
evaluate things more favourably (Weiss and Cropanzano, 1996). Overall the incentive
mechanisms of crowdsourcing contests should support participants’ needs for
autonomy, competence, relatedness, leadership and affect. From the design perspective
crowdsourcing platforms and systems should satisfy such motivational affordances in
order to attract, provide incentives, sustain and guide the crowd to participate and
complete the task.
Hence we propose the following perceived motivational affordance hypotheses:
H2a. Supporting a participant’s perceived motivational affordances strengthens the
relationship between the individual’s intrinsic motivation and participation
effort.
H2b. Supporting a participant’s perceived motivational affordances strengthens
the relationship between the individual’s integrated motivation and
participation effort.
H2c. Supporting a participant’s perceived motivational affordances strengthens the
relationship between the individual’s identified motivation and participation
effort.
H2d. Supporting a participant’s perceived motivational affordances strengthens
the relationship between the individual’s introjected motivation and
participation effort.
A large number of psychological experiments have shown that under certain
conditions, extrinsic motivations displace intrinsic motivations (e.g. Deci, 1971).
In cases where incentives are contingent upon performance, or individuals expect to
be rewarded, external incentives undermine characteristics of intrinsic motivation.
Osterloh and Frey (2000) refer to this as the “crowding-out” effect. Previous research
has found that financial reward is one of the most influential factors in crowdsourcing
901
Effects of
extrinsic and
intrinsic
motivation
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
contests (e.g. Archak, 2010; Bayus, 2010; Brabham, 2010), which indicates that the
crowding-out effect may be, to some extent, significant in such cases. In other words,
when participants are engaged in a crowdsourcing contest, monetary incentives for
involvement weaken intrinsic motives for participating. However, as we depicted
above, satisfaction of a participant’s motivational affordances will have positive effects
on participation effort, which may in turn mitigate the crowding-out effect.
Thus we hypothesise the following:
H2e. Supporting a participant’s perceived motivational affordances mitigates the
relationship between the individual’s external motivation and participation
effort.
Task granularity. Some researchers attempt to characterise the functions of
crowdsourcing applications by the nature of the task (Rouse, 2010; Schenk and
Guittard, 2009). Crowdsourcing contests differ substantially in the “task granularity”
required of participants. Task granularity is defined as the smallest individual
investment necessary in order to make a contribution (Benkler, 2006). Task granularity
is associated with characteristics of a task such as complexity, difficulty, structure,
ambiguity and novelty (Chan and Song, 2010). In general it is obvious that different
task granularities require various levels of involvement (time and effort), intellectual
capital input and opportunity cost, etc. (Zhao and Zhu, 2014).
Nov et al. (2011) found that most motivational factors are susceptible to differences
in the contribution’s task granularity. We agree that task granularity influences the
composition of motivation. According to flow theory the difficulty of a task may
influence individuals’ intrinsic motivation (Csikszentmihalyi, 1975, 1990). However, the
result largely depends on the personality of an individual (some are more likely
to undertake challenges while others may feel frustrated if the difficulty of a task
is beyond their capability), so whether task granularity positively or negatively
moderates the relationship between internal motivation and participation effort is
affected by many factors, and the results are mixed due to different samples and
contexts. In this study we mainly focus on external motivation. Some researchers
found that the crowding-out effect is more observable for complicated rather than
simple tasks (Deci et al., 1999; Lepper and Henderlong, 2000), which indicates that the
higher the task granularity, the more significant positive influence the external
motivation plays in the effort participants put into crowdsourcing contests. Thus we
hypothesise the following:
H3. Task granularity positively moderates the relationship between external
motivation and participation effort.
Figure 2 illustrates the conceptual model and related hypotheses.
Research method
Data collection
To test our research model we conducted a survey to collect data from contestants in
crowdsourcing projects. We developed a pool of potential respondents in the following
way. First, we selected two well-known crowdsourcing contest platforms in China:
Taskcn (www.taskcn.com) and Zhubajie (www.zhubajie.com). According to our
observations and preliminary statistics, the top three types of contests in Taskcn were
902
OIR
38,7
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
graphic design, web site design and slogan design, together accounting for 58 per cent
of the total. In Zhubajie the top top three types of contests were design, writing and
business promotion and consulting, which are more diverse and sophisticated tasks
than those in Taskcn. We believe that the diversity of the contests may provide a good
indication of task granularity in our study.
Second, due to the nature of our study only those members who had prior
experience in participating in crowdsourcing contests should be included in our survey
pool. We selected discussion forums hosted by Taskcn and Zhubajie, and extracted
e-mail addresses or instant messenger addresses of the participants from the forums
and set up a contact list. We randomly selected 1,000 individual members from the list
and sent them invitations to participate in the survey. All the members we selected had
at least three participation experiences.
Third, we selected potential respondents from eight crowdsourcing contests in
Taskcn and Zhubajie to collect the subjective data. The time span of the contests
varied from one to six months, and the launch time ranged from 2010 to 2012. In this
round we selected all the participants in the contest (n¼1,946) and added them
to the survey pool. A total of 2,946 crowdsourcing contestants were included in the
final pool. From this list we randomly selected 2,000 respondents to be included in
our study and sent out invitations to fill out our questionnaire which was posted on
sojump.com (an online survey service provider). Before conducting the main survey we
also invited ten students from our school to perform a pre-test to validate the
instrument and then we revised the questionnaire to make the wording of the items
more precise.
By the time the survey closed we had received a total of 455 responses, resulting in
a response rate of 22.75 per cent. We then filtered out incomplete and inconsistent
responses. A total of 420 usable responses were finally included in the sample. The
entire survey took about 15-20 minutes to complete. The demographic data of the
respondents are shown in Table I. To test the non-response bias a wave analysis
was conducted to compare the first and last quartiles of respondents in terms of
demographic characteristics and research variables (Armstrong and Overton, 1977).
The results indicated that the later respondents were quite similar to the early ones.
This suggested that non-response bias was not present in our study.
External
Motivation H1a
H3
H2d
H2e
H2c
H2b
H2a
Task
Granularity
Participation
Effort
Supporting of Motivational
Affordances:
-Autonomy; -Competence;
-Relatedness; -Leadership
-Affect
H1b
H1c
H1d
H1e
Introjected
Motivation
Identified
Motivation
Integrated
Motivation
Intrinsic
Motivation Figure 2.
Conceptual model and
research hypotheses
903
Effects of
extrinsic and
intrinsic
motivation
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
Measures
We adopted or adapted the measurement items in our questionnaire from validated and
well-tested scales in the literature. In the questionnaire participation effort and support
of motivational affordances were modelled as formative factors. Participation effort is
a second-order formative latent construct that has two first-order formative factors
(intensity and persistence). Each of the first-order factors were measured by reflective
items. Support of motivational affordances is a second-order formative construct that
has four first-order formative factors (autonomy, competence, relatedness and
leadership). Each of the four first-order factors had several reflective items. It is worth
noting that we did not measure the affect-related motivational affordances in our
study due to their complex dimensions (Russell, 2003). All first-order constructs were
measured with seven-point Likert scales, ranging from “strongly disagree” to “strongly
agree”. The questionnaire was created by adjusting the measures of the constructs for
current crowdsourcing contest participants, and all the items from previous studies
were modified to make them relevant to the context of crowdsourcing contests. Before
conducting the survey we also validated the items through a pre-test procedure with
30 current crowdsourcing participants to ensure content validity, completeness,
readability and understandability. All these measurement items and related references
are listed in the Appendix.
Data analysis and results
Measurement model
The reliability, convergent validity and discriminant validity of the instrument were
first examined. Individual item reliability is reflected by the loadings of the measures
on their corresponding constructs and Cronbach’s afor each construct. It is generally
accepted that a factor loading of about 0.7 or greater is desirable, whereas a value
below 0.5 shows low trait variance (Bagozzi, 2011). Thus the cut-off point was set
at 0.5. Table II shows that only two factor loadings did not exceed 0.5. Therefore INTE3
and TASK4 were dropped from further analysis.
Variables Category Frequency (n¼420) %
Gender Female 146 35
Male 274 65
Age o18 4 1
18-22 43 10
23-26 86 20
27-30 107 25
31-36 82 20
37-40 58 14
41-50 34 8
451 6 2
Education Junior high school or less 9 2
Senior high school or vocational and technical school 56 13
College or university 208 50
Graduate school 147 35
Internet usage Few times/week 41 10
Few times/day 95 23
Many times/day 276 65
Others 8 2
Tabl e I.
Demographic
characteristics
of the sample
904
OIR
38,7
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
Convergent validity was assessed by reliability of items, composite reliability of
constructs and average variance extracted (AVE) (Fornell and Larcker, 1981).
Composite reliability and Cronbach’s awere both used for evaluating the internal
consistency of the constructs, and 0.7 is the recommended threshold for both indices.
It can be seen from Table II that all constructs met the criterion. AVE is the average
variance shared between a construct and its measures. All AVEs shown in Table II
are greater than the recommended value (0.5), suggesting that the latent constructs
account for the majority of the variance in their indicators on average (MacKenzie et al.,
2011). Therefore sufficient convergent validity was achieved in the study.
Construct Items Mean SD Loading CR CA AVE VIF
External motivation EXT1 4.89 1.512 0.791 0.931 0.890 0.819 2.061
EXT2 4.95 1.309 0.775
EXT3 5.39 1.194 0.705
Introjected motivation INTO1 4.75 1.439 0.671 0.864 0.764 0.679 1.659
INTO2 4.41 1.406 0.738
INTO3 4.39 1.161 0.739
Identified motivation IDEN1 3.41 1.130 0.843 0.891 0.754 0.803 1.098
IDEN2 3.56 1.215 0.876
Integrated motivation INTE1 4.51 1.429 0.656 0.866 0.691 0.764 1.270
INTE2 4.43 1.270 0.858
INTE3 3.41 1.503 0.256
Intrinsic motivation INTRI1 5.16 1.307 0.732 0.903 0.865 0.650 1.892
INTRI2 4.65 1.370 0.805
INTRI3 4.35 1.331 0.783
INTRI4 5.20 1.267 0.745
INTRI5 4.66 1.340 0.564
Autonomy AUTO1 3.82 1.024 0.812 0.880 0.795 0.710 1.217
AUTO2 3.86 1.157 0.836
AUTO3 3.65 1.245 0.743
Competence COMP1 4.97 1.386 0.831 0.962 0.941 0.894 1.956
COMP2 4.92 1.362 0.822
COMP3 5.00 1.334 0.811
Relatedness RELA1 3.37 0.963 0.820 0.867 0.769 0.687 1.207
RELA2 3.33 1.050 0.698
RELA3 3.42 1.113 0.844
Leadership LEAD1 3.00 0.830 0.767 0.852 0.736 0.661 1.183
LEAD2 3.04 0.880 0.866
LEAD3 2.95 0.740 0.714
Task granularity TASK1 4.04 0.951 0.912 0.948 0.917 0.858 1.086
TASK2 4.03 1.038 0.904
TASK3 4.08 1.182 0.894
TASK4 3.99 1.214 0.446
Intensity INTY1 5.01 1.023 0.759 0.918 0.865 0.790 1.910
INTY2 5.12 1.006 0.782
INTY3 4.79 1.099 0.640
Persistency PERS1 4.15 0.718 0.705 0.813 0.655 0.593 1.132
PERS2 4.43 0.670 0.811
PERS3 4.41 0.709 0.711
Notes: SD, standard deviation; CR, composite reliability; CA, Cronbach’s a; VIF, variance inflation
factor
Table II.
Results for measurement
model
905
Effects of
extrinsic and
intrinsic
motivation
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
For sufficient discriminant validity to be present, items should load more strongly
on their own constructs, and the average variance shared between each construct and
its measures should be greater than the variance shared between the construct
and other constructs (Compeau et al., 1999). Table III shows that all the square roots of
AVEs were greater than the correlations of research constructs. Therefore discriminant
validity was achieved.
In order to prevent the potential problems caused by multicollinearity, it is
suggested that the variance inflation factor of each construct should be less than ten
(Mason and Perreault, 1991). As Table II shows, all variance inflation factors are far
below ten. This indicates that multicollinearity is not a serious issue for our research.
Since our data were perceptual and collected from only two sources at one point
in time, common method bias might be a problem (Podsakoff et al., 2003). As
recommended by Ke and Zhang (2010) we examined the possibility of common method
bias with the Harman’s one-factor test (Podsakoff and Organ, 1986). First, the adequacy
of sample size was assessed using the Kaiser-Meyer-Olkin (KMO) measure. The results
showed that the value of KMO was 0.794, suggesting that factor analysis would be
adequate regardless of sample size. Second, we conducted a principal components
analysis with an oblique rotation. The results showed that there were 12 constructs
with eigenvalues 41.0. These 12 constructs in total accounted for 76.25 per cent of
the variance, while the first construct only accounted for 23.41 per cent of the variance.
We also adopted principal axis factoring to verify the results of principal components
analysis. The results indicated that there were 12 constructs with eigenvalues 41.0.
These 12 constructs and the first construct accounted for 66.04 and 22.64 per cent
of the variance, respectively. The results of these two methods were consistent,
suggesting that common method bias was not a serious concern for this study.
Structural model
We ran AMOS to conduct the confirmatory factor analysis and test path coefficients
of the structural model. We conducted a series of models to examine hypotheses.
Model 1 does not contain any moderator. Model 2 has one moderator (task granularity)
and Model 3 contains both of the two moderators (task granularity and motivational
affordance). Fit indices were evaluated using established thresholds (Byrne, 1998).
As can be seen from Table IV, most of the fitness indices meet the criterion, suggesting
these three models are acceptable (Hair et al., 2006). Meanwhile Model 2 provides
higher explanation of variance (R
2
¼0.31) than Model 1 (R
2
¼0.18), while Model 3 also
123 4 5678
1. External motivation (0.90)
2. Introjected motivation 0.15 (0.82)
3. Identified motivation 0.27 0.12 (0.89)
4. Integrated motivation 0.18 0.09 0.23 (0.87 )
5. Intrinsic motivation 0.18 0.23 0.32 0.23 (0.81)
6. Task granularity 0.43 0.26 0.21 0.20 0.33 (0.92)
7. Participation effort 0.31 0.11 0.31 0.10 0.08 0.28 (0.63)
8. Motivational affordance 0.28 0.27 0.26 0.27 0.39 0.51 0.11 (0.69)
Note: Values on the diagonal are the square root of the average variance extracted (AVE) for each
construct
Table III.
Correlations among
constructs
906
OIR
38,7
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
provides significantly higher explanation of variance (R
2
¼0.49) than Model 2.
The summary of hypotheses testing can be concluded as follows and is shown in
Figure 3.
The results of Model 1 indicate that external motivation ( b¼0.33, po0.001) and
introjected motivation ( b¼0.13, po0.001) have significant effects on participation
effort. Model 1’s results also show that the link between intrinsic motivation and
participation effort ( b¼0.33, po0.001) is positive and significant. Thus H1a,H1b
and H1e are supported, respectively. However, the results show that the path
coefficient of the link between identified motivation and task effort is not significant
(b¼0.01, p40.50). As such H1c on the positive effect of identified motivation on
Model 1 Model 2 Model 3
b-coefficient t-value b-coefficient t-value b-coefficient t-value
External motivation (EXT) 0.33*** 7.05 0.31*** 6.96 0.14** 3.05
Introjected motivation (INTO) 0.13*** 3.22 0.14*** 3.66 0.12*** 3.21
Identified motivation (IDEN) 0.01 0.23 0.00 0.03 0.08 1.72
Integrated motivation (INTE) 0.07 1.45 0.05 0.99 0.02 0.35
Intrinsic motivation (INTRI) 0.24*** 3.73 0.27*** 4.60 0.13** 2.99
Task granularity (TG) 0.20*** 5.35 0.30*** 6.47
TGEXT 0.24*** 5.73 0.29*** 6.40
Motivational affordances (MA) 0.22*** 4.94
MAEXT 0.16*** 4.02
MAINTRO 0.19*** 4.67
MAIDEN 0.22*** 5.30
MAINTE 0.12** 2.80
MAINTRI 0.23*** 5.66
R
2
0.18 0.31 0.49
w
2
/df 3.17 2.98 2.63
RMSEA 0.83 0.71 0.60
SRMR 0.072 0.056 0.054
GFI 0.93 0.91 0.96
CFI 0.931 0.929 0.974
Notes: ** po0.01; *** po0.001
Tabl e IV.
Results of the
structural models
External
Motivation 0.33***
0.13***
0.24***
0.24***
–0.16***
0.23***
0.12**
0.22*** 0.19***
0.01ns
0.07ns
Introjected
Motivation
Identified
Motivation
Integrated
Motivation
Intrinsic
Motivation
Tas k
Granularity
Participation
Effort (R2=49%)
Motivational Affordances:
-Autonomy; -Competence;
-Relatedness; -Leadership
Figure 3.
Hypotheses testing results
907
Effects of
extrinsic and
intrinsic
motivation
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
participation effort is not supported. In addition, the results show that the influence of
integrated motivation on participation effort is not significant ( b¼0.07, p40.20).
Thus H1d, on the positive effect of integrated motivation, is not supported.
The results from Model 2 suggest that, when task granularity is incorporated in the
model, the link between external motivation and participation effort ( b¼0.24, po0.001)
is positively moderated and significant. Thus H3 is supported. Furthermore, the results
of Model 3 show that, when perceived motivational affordance is incorporated in the
model, the multiplication terms of introjected motivation and motivational affordances
(b¼0.19, po0.001), identified motivation and motivational affordances ( b¼0.22,
po0.001) and integrated motivation and motivational affordances ( b¼0.12, po0.01)
are significant. Thus H2b,H2c and H2d are supported, respectively. The multiplication
term of intrinsic motivation and motivational affordances ( b¼0.23, po0.001) is also
significant and thus lends support to H2a.
In addition the results of Model 3 indicate that the multiplication term of external
motivation and motivational affordances ( b¼0.16, po0.001) is significant, but
in the opposite direction. Thus H2e is supported. As shown in Figure 3 the main
effects-only model shows that the variables explained 18 per cent of the variance
in participation effort. When two moderating effects were included, the R
2
increased to
49 per cent, indicating an effect size of 0.38. According to Cohen’s (1988) formula which
suggested 0.02, 0.15 and 0.35 as operational definitions of small, medium and large
effect sizes, respectively, our moderating result represents a large effect size.
Discussion and conclusions
Major findings
The results suggest that a majority of the participants in crowdsourcing contests had
a mixture of intrinsic and extrinsic motivation, which is consistent with previous
studies (Krishnamurthy, 2006; Zheng et al., 2011). The motivation to gain financial
rewards was significantly associated with participation effort. Although this finding
contradicts several studies (e.g. Leimeister et al., 2009; Zheng et al., 2011), it is
consistent with many others (Archak and Sundararajan, 2009; Horton and Chilton,
2010; Stewart et al., 2009; Zhong et al., 2011).
The finding regarding introjected motivation suggest that participants in
crowdsourcing contests may be positively motivated by recognition from the sponsor
and other contestants, which is consistent with other studies on crowdsourcing
(Brabham, 2010; Zheng et al., 2011). This indicates that although crowdsourcing
contestants have a sense of competition during participation, they still would like to
pursue recognition among peers and from the task assigners, and look for a degree of
ego-enhancement from the crowdsourcing contest. At the same time the results show
that intrinsic motivation can exert influence on participation effort, which has been
supported by many other empirical studies (Brabham, 2010; Zheng et al., 2011).
Identified motivation and integrated motivation, in contrast, do not have a
significant effect on participation effort. One explanation for the insignificant direct
influence of identified motivation and integrated motivation on participation effort is
that the obligation and sense of belonging towards the crowdsourcing community
or project may be offset by two dimensions of attributes, i.e. utilitarian and hedonic.
Research in marketing suggests that “consumers purchase goods and services and
perform consumption behaviours for two basic reasons: consummatory affective
(hedonic) gratification, and instrumental, utilitarian reasons” (Batra and Ahtola,
1990, p. 161). However, in our study these two dimensions are mapped to external
908
OIR
38,7
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
motivation and intrinsic motivation, respectively, and we did not measure these two
dimensions by empirical data.
The findings confirm that task granularity positively moderates the relationship
between external motivation and participation effort. Previous studies have indicated
that the features of contest tasks have important implications for contestants’
participation (Zheng et al., 2011; Zwass, 2010). According to our findings, if the task
granularity is high, which means less perceived control, high perceived difficulties and
a trivial sequence of steps, the contestants will need more external motivation to drive
them to participate in a crowdsourcing contest. Since crowdsourcing contests are
organised via an open call and without any contracts with the contestants, participants
may cautiously evaluate their time and energy and other resources put in the project.
Thus, for those complex or trivial tasks, more monetary awards are needed to
stimulate the enthusiasm of participants.
Furthermore, the analyses confirm the hypothesised moderating effects of
perceived motivational affordances on the relationships between various motivations
and participation effort. The support of participants’ perceived motivational
affordances may, to some degree, strengthen their intrinsic motivation and extrinsic
motivation with an internalised focus, which is consistent with motivational
affordances theory (Zhang, 2008b) and Ke and Zhang’s (2010) work. Interestingly this
study makes a contribution to the literature by finding a significant negative
moderating effect of motivational affordances between external motivation and
participation effort. This indicates that the perceived motivational affordances may
partially mitigate the crowding-out effect. From the system design perspective, if the
crowdsourcing platform can improve usability and sociability and enhance users’
experiences, participants may care less about the financial rewards, or in some cases,
even if the external incentives are not well designed, individuals can still have strong
internal motivation to participate in the crowdsourcing contest.
Limitations
It is important to note that several limitations of this study may negatively affect the
generalisability of the results. First, all the constructs in our research model were
measured by respondents’ perceptions, which are subjective data collected from one
period of time. Regarding participation effort it is better to collect objective data about
the individual’s actual participation. However, the two crowdsourcing contest
platforms in our empirical study did not provide such data. Future research may collect
objective data about individuals’ participation and convert those real behavioural data
into discrete categorical values.
Second, from the methodology perspective the cross-sectional survey method largely
depends on the immediate recall and experience of respondents, who to some extent
may have difficulties in measuring or reflecting the real conditions of participation
effort. Future research could conduct a longitudinal study to enrich the findings by
providing more relevant information on the potential variations of the links between
independent and dependent variables within the same sample across time. In addition
a lab experiment or field experiment can also be used to test the moderating effects of
motivational affordances from the design science research perspective.
Third, the conceptualisation of task granularity could be more robust. In this study
we defined the task granularity based on job design theory (Hackman and Oldham,
1976). However, task granularity is a term with multiple dimensions. One measurement
item related to task granularity was dropped due to its low loading in this study.
909
Effects of
extrinsic and
intrinsic
motivation
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
Thus future research could treat it as a formative construct or investigate the
antecedent factors of task granularity, which may bring more interesting findings for
task-oriented crowdsourcing contests.
Implications for research
Overall our research has some conceptual and theoretical implications for the
literature. First, this study describes motivation as a spectrum, in which the subtypes
of extrinsic motivation are seen as falling along a continuum of internalisation (Deci
and Ryan, 2000; Ryan and Deci, 2000). Meanwhile the findings indicate that various
motivations might play different roles in relating to participation effort expended in
crowdsourcing contests. This conceptualisation helps to enrich our understanding of
the differential effects of different types of motivation on participation effort in
crowdsourcing contests. However, given that identified motivation and integrated
motivation have no significant effects on participation effort, we suggest that future
research pay attention to these two constructs.
Second, the current study is also one of the first to examine the moderating effect of
task granularity in crowdsourcing contests, which has been described by Zheng et al.
(2011) as a promising future topic. Studying how task design may influence intrinsic
motivation has been highlighted in some IS literature (e.g. Thatcher et al., 2006; Zheng
et al., 2011). However, few, if any, prior studies have explored how task granularity can
moderate the effect of external motivation on participation effort in crowdsourcing
contests. The present study highlights that a well-designed incentive mechanism is
important for crowdsourcing contestants, especially when the task is complex or
involves a tedious and trivial sequence of steps.
Third, the study is one of the first studies exploring the moderating effects of
motivational affordances between various motivations and participation effort in
crowdsourcing contests. The findings suggest that the satisfaction of participants’
motivational affordances, such as autonomy, competence, relatedness and leadership
may to some extent strengthen their intrinsic and extrinsic motivation with an
internalised focus. Furthermore, this study makes a major contribution to the literature
by finding a significant negative moderating effect of motivational affordances on
external motivation.
Implications for practice
The findings of this research have important practical implications for sponsors,
managers and designers of crowdsourcing contests as well. First, contest sponsors
should be aware of the importance of various types of motivations in driving
contestants to participate in crowdsourcing contests. Some extrinsic motivations, such
as external rewards and social identification, should be fully incorporated into the
design of incentive mechanisms. In addition for some contestants who have a strong
motivation to gain peer recognition or sponsor identification, financial awards only
may not work. In that case, for example reputation systems should be developed to rate
contestants and evaluate their performance.
Second, our research also suggests that supporting the perceived motivational
affordances of contestants may strengthen the effects of external and internal
motivations on participation efforts in crowdsourcing contests. Nowadays many
crowdsourcing platforms or systems have a very similar appearance, which may lead
to aesthetic fatigue. Thus the design of crowdsourcing platforms should be innovative
and original, which will be eye-catching and attractive to their current or potential
910
OIR
38,7
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
users. In addition to address competence and relatedness, sponsors and managers
should interact closely with their contestants and provide timely feedback to
contestants’ questions and submissions. Meanwhile designers should develop
convenient communication tools and friendly user interfaces to enhance the
efficiency of human-computer interaction and human-human interaction.
Third, the findings of our study also highlight the importance of task granularity in
crowdsourcing contests. Service providers and task assigners should work together to
ensure that task requirements and descriptions are defined clearly. Given that
crowdsourcing contests are different from outsourcing which has explicit contracts,
task design in crowdsourcing contests should be easy to follow and divided into
segments; otherwise contestants may keep away from those tasks with low perceived
control. Specifically designers and managers should enhance the self-efficacy of
participants. For example sponsors can set up the crowdsourcing task step by step in
granularity, and provide some detailed guidance and instructions for newcomers,
while providing challenging work for veterans to use their capabilities and talents.
References
Allen, N.J. and Meyer, J.P. (1996), “Affective, continuance, and normative commitment to the
organization: an examination of construct validity”, Journal of Vocational Behavior, Vol. 49
No. 3, pp. 252-276.
Amabile, T.M. (1994), “Motivational synergy: toward new conceptualizations of intrinsic and
extrinsic motivation in the workplace”, Human Resource Management Review, Vol. 3 No. 3,
pp. 185-201.
Archak, N. (2010), “Money, glory and cheap talk: analyzing strategic behavior of contestants
in simultaneous crowdsourcing contests on TopCoder.com”, Proceedings of the 19th
International Conference on World Wide Web, ACM, New York, NY, pp. 21-30.
Archak, N. and Sundararajan, A. (2009), “Optimal design of crowdsourcing contest”, Proceedings
of the Thirtieth International Conference on Information Systems (ICIS 2009), Phoenix,
AZ, 8-12 December.
Armstrong, J. and Overton, T. (1977), “Estimating nonresponse bias in mail surveys”,
Journal of Marketing Research, Vol. 14 No. 3, pp. 396-402.
Bagozzi, R.P. (2011), “Measurement and meaning in information systems and organizational
research: methodological and philosophical foundations”, MIS Quarterly, Vol. 35 No. 2,
pp. 261-292.
Bagozzi, R.P. and Dholakia, U.M. (2006), “Open source software user communities: a study of
participation in Linux user groups”, Management Science, Vol. 52 No. 7, pp. 1099-1115.
Bass, B. and Bass, R. (2008), The Bass Handbook of Leadership: Theory, Research, and
Managerial Applications, Simon & Schuster, New York, NY.
Batra, R. and Ahtola, O.T. (1990), “Measuring the hedonic and utilitarian sources of consumer
attitudes”, Marketing Letters, Vol. 2 No. 2, pp. 159-170.
Baumeister, R.F. and Leary, M.R. (1995), “The need to belong: desire for interpersonal attachments as
a fundamental human motivation”, Psychological Bulletin, Vol. 117 No. 3, pp. 497-529.
Bayus, B.L. (2010), “Crowdsourcing and individual creativity over time: the detrimental effects of
past success”, SSRN Quantitative Marketing eJournal, available at: http://ssrn.com/
abstract¼166710 (accessed 15 May 2011).
Becker, T.E., Billings, R.S., Eveleth, D.M. and Gilbert, N.W. (1996), “Foci and bases of
commitment: implications for performance”, Academy of Management Journal, Vol. 39
No. 2, pp. 464-482.
911
Effects of
extrinsic and
intrinsic
motivation
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
Benkler, Y. (2006), The Wealth of Networks: How Social Production Transforms Markets and
Freedom, Yale University Press, New Haven, CT.
Bergami, M. and Bagozzi, R.P. (2000), “Self-categorization, affective commitment and group
self-esteem as distinct aspects of social identity in the organization”, British Journal of
Social Psychology, Vol. 39 No. 4, pp. 555-577.
Brabham, D.C. (2008), “Moving the crowd at iStockphoto: the composition of the crowd and
motivations for participation in a crowdsourcing application”, First Monday, Vol. 13, No. 6,
available at: http://ssr n.com/abstract ¼1667101 (accessed 21 March 2011).
Brabham, D.C. (2010), “Moving the crowd at Threadless: motivations for participation in
a crowdsourcing application”, Information, Communication & Society, Vol. 13 No. 8,
pp. 1122-1145.
Byrne, B.M. (1998), Structural Equation Modeling With Lisrel, Prelis, and Simpl is: Basic
Concepts, Applications, and Programming, Lawrence Erlbaum, Hillsdale, NJ.
Chan, S.H. (2005), “A motivational framework for understanding IS use and decision
performance”, Review of Business Information Systems, Vol. 9 No. 4, pp. 101-117.
Chan, S.H. and Song, Q. (2010), “Motivational framework: insights into decision support system
use and decision performance”, in Jao, C.S. (Ed.), Decision Support Systems, available at:
www.intechopen.com/books/decision-support-systems/motivational-framework-insights-
into-decision-support-system-use-and-decision-performance (accessed 20 July 2013).
Cohen, J. (1988), Statistical Power Analysis for the Behavioral Sciences, Lawrence Erlbaum,
Hillsdale, NJ.
Compeau, D.R., Higgins, C.A. and Huff, S. (1999), “Social cognitive theory and individual
reactions to computing technology: a longitudinal study”, MIS Quarterly, Vol. 23 No. 2,
pp. 145-158.
Csikszentmihalyi, M. (1975), Beyond Boredom and Anxiety, Jossey-Bass, San Francisco, CA.
Csikszentmihalyi, M. (1990), Flow: The Psychology of Optimal Experience, Harpers Perennial,
New York, NY.
Deci, E.L. (1971), “Effects of externally mediated rewards on intrinsic motivation”, Journal of
Personality Social Psychology, Vol. 18 No. 1, pp. 105-115.
Deci, E.L. and Ryan, R.M. (1995), “Human autonomy: the basis for true self-esteem”, in Kernis, M.
(Ed.), Efficacy, Agency, and Self-Esteem, Plenum, New York, NY, pp. 31-49.
Deci, E.L. and Ryan, R.M. (2000), “The ‘what’ and ‘why’ of goal pursuits: human needs and the
self-determination of behavior”, Psychological Inquiry, Vol. 11 No. 4, pp. 227-268.
Deci, E.L., Koestner, R. and Ryan, R.M. (1999), “A meta-analytic review of experiments
examining the effects of extrinsic rewards on intrinsic motivation”, Psychological Bulletin,
Vol. 125 No. 6, pp. 627-668.
Di Gangi, P. and Wasko, M. (2009), “Steal my idea! Organizational adoption of user innovations
from a user innovation community: a case study of Dell ideaStorm”, Decision Support
Systems, Vol. 48 No. 1, pp. 303-312.
Elliot, A.J. and Church, M.A. (1997), “A hierarchical model of approach and avoidance
achievement motivation”, Journal of Personality and Social Psychology, Vol. 72 No. 1,
pp. 218-232.
Fornell, C. and Larcker, D.F. (1981), “Evaluating structural equation models with unobservable
variables and measurement error”, Journal of Marketing Research, Vol. 18 No. 1, pp. 39-50.
Gagne, M. and Deci, E.L. (2005), “Self-determination theory and work motivation”, Journal of
Organizational Behavior, Vol. 26 No. 4, pp. 331-362.
Greengard, S. (2011), “Following the crowd”, Communications of the ACM,Vol.54No.2,pp.20-22.
Gregg, D.G. (2010), “Designing for collective intelligence”, Communications of the ACM, Vol. 53
No. 4, pp. 134-138.
912
OIR
38,7
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
Hackman, J.R. and Oldham, G.R. (1976), “Motivation through the design of work: test of a theory”,
Organizational Behavior and Human Performance, Vol. 16 No. 2, pp. 250-279.
Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. and Tatham, R.L. (2006), Multivariate Data
Analysis, 6th ed., Prentice-Hall, Upper Saddle River, NJ.
Horton, J.J. and Chilton, L.B. (2010), “The labor economics of paid crowdsourcing”, Proceedings of
the 11th ACM Conference on Electronic Commerce, ACM, New York, NY, pp. 209-218.
Howe, J. (2006), “The rise of crowdsourcing”, Wired Magazine, Vol. 14 No. 6, pp. 1-4.
Kanfer, R. (1991), “Motivation theory and industrial and organizational psychology”,
in Dunnette, M.D. and Hough, L.M. (Eds), Handbook of Industrial and Organizational
Psychology, 2nd ed., Vol. 1, Consulting Psychologists Press, Palo Alto, CA, pp. 75-170.
Kaufmann, N., Schulze, T. and Veit, D. (2011), “More than fun and money. Worker motivation in
crowdsourcing – a study on Mechanical Turk”, paper presented at 17th Americas
Conference on Information Systems, Detroit, 4-7 August.
Ke, W. and Zhang, P. (2010), “The effects of extrinsic motivations and satisfaction in open source
software development”, Journal of the Association for Information Systems, Vol. 11 No. 12,
pp. 784-808.
Krishnamurthy, S. (2006), “On the intrinsic and extrinsic motivation of free/libre/open source
(floss) developers”, Knowledge, Technology & Policy, Vol. 18 No. 4, pp. 17-39.
Lakhani, K.R. and Wolf, R.G. (2005), “Why hackers do what they do: understanding motivation
and effort in free/open source software projects”, in Feller, J., Fitzgerald, B., Hissam, S. and
Lakhani, K.R. (Eds), Perspectives on Free and Open Source Software, MIT Press,
Cambridge, MA, pp. 3-22.
Leimeister, J.M., Huber, M., Bretschneider, U. and Krcmar, H. (2009), “Leveraging crowdsourcing-
activation-supporting components for IT-based idea competitions”, Journal of
Management Information Systems, Vol. 26 No. 1, pp. 197-224.
Lepper, M.R. and Henderlong, J. (2000), “Turning ‘play’ into ‘work’ and ‘work’ into ‘play’: 25 years
research on intrinsic versus extrinsic motivation”, in Sansone, C. and Harackiewicz, J.M.
(Eds), Intrinsic and Extrinsic Motivation: The Search for Optimal Motivation and
Performance, Academic Press, San Diego, CA, pp. 257-307.
MacKenzie, S.B., Podsakoff, P.M. and Podsakoff, N.P. (2011), “Construct measurement and
validation procedures in MIS and behavioral research: integrating new and existing
techniques”, MIS Quarterly, Vol. 35 No. 2, pp. 293-334.
Mason, C.H. and Perreault, W.D. (1991), “Collinearity, power, and interpretation of multiple
regression analysis”, Journal of Marketing Research, Vol. 28 No. 3, pp. 268-280.
Norman, D.A. (1999), “Affordance, conventions, and design”, Interaction, Vol. 6 No. 3,
pp. 38-42.
Norman, D.A. (2008), “The way I see it: signifiers, not affordances”, Interaction, Vol. 15 No. 6,
pp. 18-19.
Nov, O., Arazy, O. and Anderson, D. (2011), “Technology-mediated citizen science participation:
a motivational model”, Proceedings of the AAAI International Conference on Weblogs and
Social Media, ICWSM, Barcelona, pp. 249-256.
Osterloh, M. and Frey, B. (2000), “Motivation, knowledge, and organizational forms”,
Organization Science, Vol. 11 No. 5, pp. 539-550.
Podsakoff, P.M. and Organ, D.W. (1986), “Self-reports in organizational research: problems and
prospects”, Journal of Management, Vol. 12 No. 4, pp. 531-544.
Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y. and Podsakoff, N.P. (2003), “Common method biases
in behavioral research: a critical review of the literature and recommended remedies”,
Journal of Applied Psychology, Vol. 88 No. 5, pp. 879-903.
913
Effects of
extrinsic and
intrinsic
motivation
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
Rouse, A. (2010), “Apreliminary taxonomy of crowdsourcing”, ACIS 2010 Proceedings, Brisbane, 1-3
December, Paper No. 76, available at: http://aisel.aisnet.org/acis2010/76 (accessed 19 April 2011).
Russell, J.A. (2003), “Core affect and the psychological construction of emotion”, Psychological
Review, Vol. 110 No. 1, pp. 145-172.
Ryan, R.M. and Deci, E.L. (2000), “Self-determination theory and the facilitation of intrinsic
motivation, social development, and well-being”, The American Psychologist, Vol. 55 No. 1,
pp. 68-78.
Schenk, E. and Guittard, C. (2009), “Crowdsourcing: what can be outsourced to the crowd,
and why?”, Workshop on Open Source Innovation, Strasbourg, 8 December, available at:
http://raptor1.bizlab.mtsu.edu/s-drive/DMORRELL/Mgmt%204990/Crowdsourcing/
Schenk%20and%20Guittard.pdf (accessed 16 September 2010).
Spreitzer, G.M. (1995), “Psychological empowerment in the workplace – dimensions, measurement,
and validation”, Academy of Management Journal, Vol. 38 No. 5, pp. 1442-1465.
Stewart, O., Huerta, J.M. and Sader, M. (2009), “Designing crowdsourcing community for the
enterprise”, Proceedings of the ACM SIGKDD Workshop on Human Computation, ACM,
New York, NY, pp. 50-53.
Stewart, O., Lubensky, D. and Huerta, J.M. (2010), “Crowdsourcing participation inequality:
a SCOUT model for the enterprise domain”, Proceedings of the ACM SIGKDD Workshop
on Human Computation, ACM, New York, NY, pp. 30-33.
Terwiesch, C. and Xu, Y. (2008), “Innovation contests, open innovation, and multiagent problem
solving”, Management Science, Vol. 54 No. 9, pp. 1529-1543.
Thatcher, J.B., Liu, Y., Stepina, L.P., Goodman, J.B. and Treadway, D.C. (2006), “IT worker
turnover: an empirical examination of intrinsic motivation”, DATA BASE for Advances in
Information Systems, Vol. 37 No. 2, pp. 133-146.
Todd, P. and Benbasat, I. (1992), “The use of information in decision making: an experimental
investigation of the impact of computer-based decision aids”, MIS Quarterly, Vol. 16 No. 3,
pp. 373-393.
Weiss, H.M. and Cropanzano, R. (1996), “Affective events theory: a theoretical discussion of
the structure, causes and consequences of affective experiences at work”, in Staw, B.M.
and Cummings, L.L. (Eds), Research in Organizational Behavior: An Annual Series of
Analytical Essays and Critical Reviews, Vol. 18, JAI Press, Stamford, CT, pp. 1-74.
Whitla, P. (2009), “Crowdsourcing and its application in marketing activities”, Contemporary
Management Research, Vol. 5 No. 1, pp. 15-28.
Yang, J., Adamic, L.A. and Ackerman, M.S. (2008), “Crowdsourcing and knowledge sharing:
strategic user behavior on Taskcn”, Proceedings of ACM Electronic Commerce’08 ACM,
New York, NY, pp. 246-255.
Yeo, G.B. and Neal, A. (2004), “A multilevel analysis of effort, practice, and performance: effects
of ability, conscientiousness, and goal orientation”, Journal of Applied Psychology, Vol. 89
No. 2, pp. 231-247.
Zhang, P. (2008a), “Motivational affordances: reasons for ICT design and use”, Communications
of the ACM, Vol. 51 No. 11, pp. 145-147.
Zhang, P. (2008b), “Toward a positive design theory: principles for designing motivating
information and communication technologies”, in Avital, M., Boland, R.J. and
Cooperrider, D.L. (Eds), Designing Information and Organizations with a Positive Lens,
Vol. 2, Advances in Appreciative Inquiry, JAI Press, Amsterdam, pp. 45-74.
Zhao, Y.X. and Zhu, Q.H. (2012), “Exploring the motivation of participation in crowdsourcing
contest”, Proceedings of ICIS 2012, Orlando, FL, 16 December, Paper 4.
Zhao, Y.X. and Zhu, Q.H. (2014), “Evaluation on crowdsourcing research: current status and
future direction”, Information Systems Frontier, Vol. 16 No. 3, pp. 417-434.
914
OIR
38,7
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
Zheng, H., Li, D. and Hou, W. (2011), “Task design, motivation, and participation in crowdsourcing
contests”, International Journal of Electronic Commerce, Vol. 15 No. 4, pp. 57-88.
Zhong, Q.Y., Wang, Y.J. and Qiu, J.N. (2011), “Empirical research on users’ continuous
participation behavior in crowdsourcing community”, Journal of Dalian University of
Technology (Social Sciences), Vol. 32 No. 1, pp. 1-6.
Zwass, V. (2010), “Co-creation: toward a taxonomy and integrated research perspective”,
International Journal of Electronic Commerce, Vol. 15 No. 1, pp. 11-48.
Further reading
DiPalantino, D. and Vojnovic, M. (2009), “Crowdsourcing and all-pay auctions”, Proceedings of
the Tenth ACM Conference on Electronic Commerce, ACM, New York, NY, pp. 119-118.
Ipeirotis, P. (2010), “Demographics of mechanical turk”, available at: http://archive.nyu.edu/fda/
bitstream/2451/29585/2/CeDER-10-01.pdf (accessed 12 August 2011).
Appendix. Measurement items
External motivation (adapted from Amabile, 1994)
(1) I am concerned about the financial rewards in crowdsourcing contests.
(2) I am strongly aware of the income goals I have for myself if I participate in crowdsourcing
contests.
(3) I am keenly aware of the possible career promotion that may be brought about by my
participation in crowdsourcing contests.
Introjected motivation (adapted from Amabile, 1994)
(1) I am strongly motivated by the recognition I can earn from the task assigners.
(2) I want other participants to find out how good I really can be in solving crowdsourcing
contest problems.
(3) Successful participation in crowdsourcing contests means doing better than other
people.
Identified motivation (adapted from Allen and Meyer, 1996; Bergami and Bagozzi, 2000)
(1) I have a strong positive feeling towards this crowdsourcing project.
(2) I have a strong obligation towards this crowdsourcing project.
Integrated motivation (adapted from Becker et al., 1996; Ke and Zhang, 2010)
(1) The reason I participate in this crowdsourcing contest is because of what it stands for,
i.e. its values.
(2) If the values of the crowdsourcing project were different, I would not be as attached to it.
(3) I have a strong sense of belonging towards the crowdsourcing community.
Intrinsic motivation (adapted from Amabile, 1994; Zheng et al., 2011)
(1) Curiosity is the driving force behind much of what I do in this crowdsourcing contest.
(2) I enjoy what I do and have great fun in crowdsourcing contests.
(3) I want to challenge myself to solve the problem and enhance my skill in crowdsourcing
contests.
915
Effects of
extrinsic and
intrinsic
motivation
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
(4) Crowdsourcing contests can help me kill time and avoid boredom.
(5) Crowdsourcing contests can provide me with an opportunity to help others.
Motivational affordances
Autonomy (adapted from Deci and Ryan, 2000; Ke and Zhang, 2010)
(1) I can pretty much be myself when working on the crowdsourcing systems.
(2) I can freely decide when and how I participate in crowdsourcing contests via
crowdsourcing systems.
(3) I can personalise the interfaces of crowdsourcing systems according to my preference.
Competence (adapted from Deci and Ryan, 2000; Elliot and Church, 1997)
(1) I feel very competent when participating in crowdsourcing contests via crowdsourcing
systems.
(2) I often feel confident when using the crowdsourcing systems to solve the problems.
(3) I get many chances to show my talents in crowdsourcing contests.
Relatedness (adapted from Baumeister and Leary, 1995; Spreitzer, 1995)
(1) I feel I can easily contact task assigners via the crowdsourcing systems/platforms.
(2) I can communicate with other participants via the crowdsourcing systems/platforms.
(3) Crowdsourcing contests provide me with opportunities to build my personal social
networks.
Leadership (adapted from Bass and Bass, 2008)
(1) I feel I can delegate work to others via the crowdsourcing systems/platforms.
(2) I am good at planning and developing goals.
(3) Giving directions is comfortable for me.
Task granularity (adapted from Benkler, 2006; Zheng et al., 2011)
(1) I prefer to select the tasks with a higher perceived control.
(2) I prefer to solve the problems with fewer perceived difficulties.
(3) I may give up my attempt to solve those crowdsourcing problems which need complex
knowledge.
(4) I may give up my attempt to solve those crowdsourcing problems which require a trivial
sequence of steps.
Participation effort (adapted from Ke and Zhang, 2010; Yeo and Neal, 2004)
Intensity
(1) When I participate in a crowdsourcing contest, I really exert myself to the fullest.
(2) I devoted a large number of hours to crowdsourcing contests.
(3) I will use different skills and talents to solve crowdsourcing contest problems.
916
OIR
38,7
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
Persistence
(1) I have worked a long time on crowdsourcing contests.
(2) I persist in overcoming obstacles to complete tasks in crowdsourcing contests.
(3) I will continue participating in the crowdsourcing contests.
About the authors
Yuxiang Chris Zhao is an Assistant Professor in the School of Information Management at the
Nanjing University. He has been involved in a wide range of research activities, with particular
focus on human-computer interaction and social media. His research has been published in such
journals as the International Journal of Information Management,Information Systems Frontiers
and the Aslib Journal of Information Management among others. Yuxiang Chris Zhao is the
corresponding author and can be contacted at: yxzhao@vip.163.com
Qinghua Zhu is a Professor in the School of Information Management at the Nanjing
University. His research interests are in information resources management, human information
behaviour and social media. His research has been published in journals such as the
International Journal of Information Management,Online Information Review,Information
Systems Frontiers and Scientometrics among others.
To purchase reprints of this article please e-mail: reprints@emeraldinsight.com
Or visit our web site for further details: www.emeraldinsight.com/reprints
917
Effects of
extrinsic and
intrinsic
motivation
Downloaded by MAHIDOL UNIVERSITY At 06:51 07 March 2015 (PT)
