CROWDSOURCING IT WORK: A THREE-FOLD PERSPECTIVE FROM THE

WORKERS, BUYERS AND PLATFORM PROVIDERS

By

JOSEPH DALE TAYLOR

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A dissertation submitted in partial fulfillment of
the requirements for the degree of
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DOCTOR OF PHILOSOPHY
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WASHINGTON STATE UNIVERSITY

Carson College of Business

MAY 2016

© Copyright by JOSEPH DALE TAYLOR, 2016

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© Copyright by JOSEPH DALE TAYLOR, 2016

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To the Faculty of Washington State University:

The members of the Committee appointed to examine the dissertation of JOSEPH

DALE TAYLOR find it satisfactory and recommend that it be accepted.

____________________________
KD Joshi, Ph.D, Chair

____________________________
Arvin Sahaym, Ph.D.

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Kenneth Butterfield, Ph.D.
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____________________________
Terence Saldanha, Ph.D.
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 CROWDSOURCING IT WORK: A THREE-FOLD PERSPECTIVE FROM

THE WORKERS, BUYERS AND PLATFORM PROVIDERS

Abstract

by Joseph Dale Taylor, Ph.D.

Washington State University
May 2016

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Chair: KD Joshi
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This dissertation examines the phenomena of crowdsourcing within the context of the IT

services market. Crowdsourcing is presented as a mechanism to enhance and expand the

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technology workforce. This research examines the technology crowdsourcing phenomena from

three perspectives: the worker (or labor supply), the buyer of technology services (or labor

demand) and the marketplaces that facility the buyer-seller transaction. It explores how
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workforce development and IT Flexibility theories can be applied in explaining how

crowdsourcing can be applied to technology tasks. This dissertation will be structured in a three

essay format. Essay one explores the technology crowdsourcing phenomena from a

“crowdworker” perspective. This essay examines technology crowdwork from a career anchors

perspective, and highlights the potential role of crowdsourcing in expanding the technology

workforce to additional sources of worker capacity. Essay one establishes the theories that

describe the motivations and outcomes achieved by workers in crowdsourcing project

engagements, and utilizes Schein’s Careen Anchors to examine the motivations of workers

technology enabled collaborative work environments. Essay two uses IT Flexibility theory to

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examine the relationship between IT flexibility, the rigidity of IT administration and an

organization’s choice to use crowdsourcing as means of IT services delivery. Essay two uses

survey data to show that higher levels of IT flexibility are associated with higher levels of usage

of crowdsourcing. Essay three uses a design science perspective to examine the ability of

crowdsourcing marketplace platforms to meet the needs of IT service buyers and IT service

workers as identified in Essay’s one and two. This essay identifies how simplification of

procurement and management processes could make crowdsourcing more attractive to firms as a

means of procuring IT services.

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 Table of Contents
Page
ABSTRACT ................................................................................................................................... iii

LIST OF TABLES .........................................................................................................................vii

LIST OF FIGURES ..................................................................................................................... viii

INTRODUCTION ...........................................................................................................................1

ESSAY ONE: JOINING THE CROWD, FOUR CROWD WORKER ARCHETYPES

DRIVING INFORMATION TECHNOLOGY CROWDSOURCING ..........................................4

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Abstract ........................................................................................................................................4
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Introduction ..................................................................................................................................4
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Theoretical Framework ..............................................................................................................10

Research Methodology ...............................................................................................................12

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Results ........................................................................................................................................20

Discussion ..................................................................................................................................36

Contributions & Limitations ......................................................................................................38

Summary ....................................................................................................................................40

Appendix 1 .................................................................................................................................42

Appendix 2 .................................................................................................................................48

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ESSAY TWO: IT FLEXIBLITY AND THE CHOICE TO USE CROWDSOURCING FOR IT
DELIVERY....................................................................................................................................49

Introduction ................................................................................................................................49

Theoretical Framework ..............................................................................................................54

Research Methodology ...............................................................................................................61

Results ........................................................................................................................................83

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Discussion ..................................................................................................................................85
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Contributions & Limitations ......................................................................................................86
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Summary ....................................................................................................................................87

ESSAY THREE: IT CROWDSOURCING PLATFORMS, BUILDING FOR BUYERS ..........89

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Introduction ................................................................................................................................89

Theoretical Framework ..............................................................................................................94

Research Methodology ...............................................................................................................95

Results ......................................................................................................................................103

Discussion ................................................................................................................................110

Summary ..................................................................................................................................113

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 List of Tables
Characteristics of Sourcing Environments.......................................................................................9

Essay One Sample Demographics .................................................................................................15

Revealed Concepts and Constructs of Information Technology Crowdsourcing ..........................20

Demographic Data by Archetype ..................................................................................................26

Characteristics of Sourcing Environments....................................................................................48

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Essay Two Sample Demographics.................................................................................................62

Summary of Variables ...................................................................................................................63

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CFA Results ..................................................................................................................................68
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Factor Loadings and Reliabilities ..................................................................................................69

Essay Two Descriptive Statistics ...................................................................................................82

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Essay Two Sample Demographics.................................................................................................82

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 List of Figures
Saturation Graph ............................................................................................................................19

Revealed Causal Map of Aggregate Data .....................................................................................19

Identifying the Archetypes ............................................................................................................22

Revealed Causal Maps by Archetype ...........................................................................................27

Model Description ........................................................................................................................83

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Model Results ...............................................................................................................................84

Design Science Review Process ...................................................................................................95

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Generic ITCS Workflow ...............................................................................................................97
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Simplification Recommendations ................................................................................................104

Proposed Platform Alternatives ..................................................................................................105

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 INTRODUCTION
As demands for Information Technology (IT) services continue to escalate companies are

increasingly challenged to meet staffing needs. Decreasing numbers of students studying

technology related fields, coupled with poor career retention, compounded by pending retirements

in the existing technology workforce support a confluence of forces that will continue to spur

headwinds for IT organizations to meet staffing requirements over the next ten years (Bosworth et

al. 2013).

In the face of these headwinds crowdsourcing is an emerging technique for attracting workers.

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Crowdsourcing has been defined in a variety of ways. Common themes among crowdsourcing

definitions include utilizing labor from outside the traditional boundaries of the firm to complete
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a task (Kaganer et al. 2013). Crowdsourcing has been defined as broadly as virtually any type of

internet based collaboration activity for sourcing work (Estellés-Arolas et al. 2012). In some
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instances the contributions of the nontraditional workers are uncompensated, such as contributors

to the Wikipedia website or traditional open source software development projects, and at other
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times the contributions of the nontraditional workers are compensated, such as through Amazon’s

Mechanical Turk (Doan et al. 2011). While crowdsourcing has been seen as a means by which

software development capacity can be managed (Kim et al. 2012), successful use of crowdsourcing

in the delivery of software development may require organizations to think differently about

technology sourcing enablement. In order to support emerging business models in crowdsourcing,

technology is becoming increasingly critical (Majchrzak et al. 2013). Advances in collaborative

technologies have enabled dramatic change not just in business processes, but also in the

underlying business models that firms leverage to bring value to their stakeholders.

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This dissertation proposes a research agenda that seeks to take a multifaceted approach to

examining the role of crowdsourcing in expanding the technology workforce. In order for a vibrant

marketplace to exist three elements must be in place: buyers, sellers and a market to facilitate

transactions. This research will examine the technology crowdsourcing phenomenon from each

of these three perspectives using both multi-method and multi-level techniques. Essay one will

examine the crowdsourcing phenomenon from the perspective of the technology worker, or the

seller of IT services. The research will examine the interests and motivations for technology

workers who participate in crowdsourcing platforms. The first essay will seek to address the

following question from the technology crowdworkers’ perspective, Why do technology workers

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participate in IT crowdsourcing communities? Significant theoretical work has been conducted
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describing the variation that can exist in technology career paths (Lee 2002). The first essay

addresses the role of crowdsourcing as a component of career management by technology workers.

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Essay two will explore the attitudes, usage intentions and usage levels of IT crowdsourcing

services by IT services buyers. Technology standardization driven by industry trends such as cloud
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computing and mobile devices facilitates the creation of common development environments,

making collaboration between loosely knit crowdworkers possible (Doan et al. 2011). Increasing

levels of technology standardization have been found to facilitate the use of third parties in

software development. Industries with higher levels of standards adoption have been found to

have a greater propensity to engage 3rd party contractors in software development (Sahaym et al.

2007). Architecture governance programs, such as service oriented architecture have been found

to assist in the development of enterprise capabilities across business units (Boh et al. 2007). It is

posited that the same architectural standards that facilitate flexibility and distributed intra-firm

development, can be used to support crowdsourcing engagements. I argue that the degree to which

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a firm has adopted standardized infrastructures and flexible architectures will shape a firm’s

interest in and adoption of IT crowdsourcing as a means of IT project delivery. However, as firms

standardize IT practices, rigidity may develop in vendor management practices that decrease a

firm’s ability to take advantage of emerging sourcing techniques such as crowdsourcing. Building

on this thesis, essay two will examine the following research question: What factors shape an

enterprise’s choice to use of IT crowdsourcing services?

While the motivations of crowdworkers and the usage intentions of IT services buyers are

important elements to the growth and stability of the crowdsourcing marketplace, crowdsourcing

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platforms are a critical linchpin that facilitates the interactions between IT services buyers and

services sellers. Essay three will use a design science perspective to retrospectively evaluate
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current crowdsourcing platform designs to assess the viability of these platforms to support the

interests of both services buyers and sellers examined in Essays one and two. Specifically, Essay
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three will address the following question: What are the key design principles that are critical to

building effective IT crowdsourcing platforms.

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 ESSAY ONE
JOINING THE CROWD: FOUR CROW WORKER ARCHETYPES DRIVING
INFORMATION TECHNOLOGY CROWDSOURCING

Abstract

As technology platforms and online communities evolve, the nature of the relationship between

workers and firms is changing. Crowdsourcing is an emerging phenomenon that exemplifies the

changing relationship between workers and firms. Although significant research has been

conducted regarding worker motivation within the traditional firm-worker relationship, relatively

little work has examined motivation in crowdsourcing engagements. This study utilizes revealed

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causal mapping methodology to identify the motivations and career outcomes of technology

workers based in the United States who participate in compensation-based technology

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crowdsourcing platforms such as oDesk or Rent-a-coder. Career anchors are used to examine
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the motivations of different types of crowd workers who participate in online sourcing

marketplaces. Four archetypes of information technology (IT) crowdworkers are identified:

Workforce Survivors, Dream Chasers, Weekend Warriors and Full-time Freelancers. The
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findings identify each archetype’s motivations and extend career anchors theory to address new

types of firm-worker relationships.

Keywords: Crowdsourcing, IT Workforce Development, Career Anchors, Revealed Causal

Mapping

Introduction

The on-demand-labor economy that uses workers from the general public (crowd) to complete a

task is steadily growing (Bergvall-Kåreborn et al. 2013). This economy rests heavily on the

availability of workers (referred to as crowd workers) who willingly participate in this new

work form of open sourcing mediated by digital marketplaces, which I refer to as crowdsourcing

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(CS). The popularity of this form of work is evident from the millions of crowd workers who are

registered to work on various CS platforms (Freelancer 2015; Topcoder 2015). The steady rise

of the on-demand or gig economy is drawing attention to the issues surrounding the crowd

workers who participate in this emerging marketplace (Florentine 2015; Kaganer et al. 2013).

Superficially, the lack of job security, the unpredictable work schedules, the lack of a guarantee

of steady income, the absence of insurance and pension benefits through employment, and the

ambiguity regarding safeguards afforded by key labor laws designed to protect the workers

collectively conspire to characterize this kind of work environment as unattractive at best and as

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a sweat-shop at worst (Kittur et al. 2013). The undesirable attributes of this work environment

prompt a broader question: Why does an individual desire to be a crowd worker? Although this
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question has not been examined through the IT crowd workers’ perspective, recently the scholars

have tried to profile this workforce in an effort to understand the individuals who are willing to
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participate in this seemingly unattractive work option (Brawley et al. 2016; Rogstadius et al.

2011).
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Crowd workers’ willingness, and even eagerness, to participate in crowdsourcing is particularly

perplexing in the IT labor space, where technology workers often enjoy many employment

privileges due to the talent shortage (Amato 2013). Decreasing numbers of students studying

technology-related fields, coupled with poor career retention, compounded by pending

retirements in the existing technology workforce create a confluence of forces that is expected to

make it difficult for IT organizations to meet staffing requirements over the next ten years

(Bosworth et al. 2013). While companies are increasingly challenged to meet their staffing

needs (Khan et al. 2014; Trost 2014), IT workers are likely to benefit from the low IT

unemployment rate (Kolakowski 2015) as employers aggressively compete to attract workers to

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meet the demands for IT services. In spite of the availability of good traditional employment 1

opportunities, a significant number of workers are engaging in non-traditional employment

relationships. Crowdsourcing-based freelancing platforms such as oDesk, eLance (now Upwork),

and Freelancer continue to attract workers, with over eight million crowd worker accounts

established2. In an attempt to understand why these platforms continue to attract participants

even though crowd workers lack many of the protections available through traditional IT

employment, I posit the following research question: Why do crowd workers participate in IT

crowdsourcing?

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I address this research question through the perspective of Schein’s career anchors (Schein
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1990). Using this theoretical perspective, I categorized why workers participate in

crowdsourcing and characterize differences between the types of individuals who choose to
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participate. The career anchors were theorized, in part, to describe worker motivations as

technology diffusion within enterprises began to change work processes. My analysis extends
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career anchors theory to the emerging types of worker relationships supported by crowdsourcing.

The remainder of the paper is organized as follows. I next summarize the existing literature on

crowdsourcing and highlight gaps that are addressed in this research. I then present career

anchors theory and use it to examine and describe the motivations of IT crowdworkers. I next

present my research methodology and results, followed by a discussion of the implications of my

results and my contributions.

1 Employment with a standard recurring paycheck and benefits package

2 http://www.elance-odesk.com/, accessed 8/10/2015

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Research Background - Types of Crowdsourcing

Crowdsourcing has been defined in a variety of ways. Common themes among crowdsourcing

definitions include utilizing labor from the crowd through an open call to complete a task

mediated or enabled by an online platform (Deng et al. 2016). In some instances the

contributions of the crowd are uncompensated, such as contributors to the website Wikipedia,

and at other times the contributions are compensated, such as through Amazon’s Mechanical

Turk (Doan et al. 2011). While some crowdsourcing research focuses on open innovation

(Lichtenthaler 2011), crowdfunding (Belleflamme et al. 2014), or ideas competitions (Leimeister

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et al. 2009), this paper looks specifically at how crowdsourcing may be applied as a means of

outsourcing IT services. Outsourcing-based CS communities provide a mechanism by which

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small IT jobs are conducted through “microsourcing” engagements that afford varying levels of

support, guidance, and compensation to CS participants (Oshri et al. 2011); I refer to such work
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arrangements as IT crowdsourcing (ITCS). Oshri et al. (2011) posited a framework for

organizing these “microsourcing” engagements into three categories: directories, marketplaces,

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and communities. They categorized the types of platforms based on their main focus, structure

of deals, the platform’s role in facilitating buyer-seller interaction, and revenue model (See Table

1).

The “directory” online sourcing environments unite buyers of IT services, or job requestors, and

crowd workers. Directories do not provide transaction processing capabilities, instead serve only

as a virtual job board that facilitates introductions that result in work engagement whose terms

are set outside of the platform. Marketplace environments, which are the focus of this paper,

involve crowd workers’ selecting and finishing posted jobs in exchange for payment.

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Crowdworkers perform and deliver these jobs according to pre-specified work instructions and a

predetermined compensation rate. The marketplace platform provides tools and support for

buyers and workers throughout the transaction. “Community” environments provide a

framework for engagement and development of crowd workers. Community environments often

structure jobs as contests, where not all the participants are financially compensated. Often only

the winning participants receive monitory awards. Therefore, community-based environments

position themselves as wellsprings of learning where the participants’ visibility and growth are

the salient benefits instead of compensation. By focusing this paper on crowdsourcing for

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compensation-based marketplaces within the IT sourcing environment, I are able to isolate the

factors that drive IT crowd workers to purse ITCS as a career (i.e., for monetary reasons.) In
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these work environments, exemplified by platforms such as e-Lance, Rent-a-coder, Freelancer or

oDesk, job requestors contract with IT workers through the online marketplaces and the
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crowdworkers expect to be paid for the delivery of specific services.

While substantial attention has been directed at open innovation contests (e.g., Terwiesch and Xu
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2008, Majchrzak and Malhotra 2013; Nevo and Kotlarsky 2014), marketplace crowdsourcing is

still an emerging phenomenon, and therefore scholarly work on marketplace CS in general is

limited; for ITCS in particular, it is nonexistent. While some work has been done to examine the

viability of marketplace crowdsourcing as a career alternative (Deng et al. 2013), to my

knowledge crowdsourcing as a career pathway specifically within IT has not yet been explored.

We do not know whether IT workers’ perceptions of crowdsourcing opportunities are different

from those of less specialized workers. As a larger share of the workforce begins to participate

in ITCS opportunities (Freelancer 2015), it is critical that we develop our understanding of how

to make crowdsourcing arrangements beneficial for both workers and the companies who utilize

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them. I posit that the implications to workers of crowdsourcing will be particularly acute in

marketplace crowdsourcing work environments, as these workers are participating in jobs for

defined monetary compensation. While the business implications of various forms of

crowdsourcing are beginning to be addressed, questions concerning the worker implications of

crowdsourced environments are growing (Kittur et al. 2013). While business leaders may be

intrigued by the possibilities of crowdsourcing and worker advocates may fear the ramifications

of a crowd-based workforce (Schmidt 2013), little work has been done to find out what

crowdworkers themselves think of ITCS career pathways. Therefore, my study is designed to

capture the crowdworkers’ perspectives regarding their motivations to participate in ITCS.

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Table 1. Characteristics of Sourcing Environments IE
Characteristics Directory Marketplace Community
Main Focus Helps buyers discover Connects buyers and Helps members
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suppliers suppliers of services develop professional
throughout all stages through interaction
of workflow and paid client
engagements
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Structure of Deals are offline, no Deals are done Deals done online
Deals platform involvement online, platform and usually structured
involved in legal and as contests. The
financial aspects of platform is involved
deal in legal and financial
aspects of deal
Platform’s role No buyer-supplier The platform The platform
in facilitating interaction facilitated, facilitates buyer- facilitates buyer-
buyer-seller merely introductions supplier interaction supplier interaction
interaction throughout the with a focus on
project learning and
community building
Revenue Model Advertising, sponsorship Project commission Project commission
paid by suppliers. paid by buyers
Premium
membership fees

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 Platform Infolancer, Chinasourcing Elance, oDesk, Topcoder, Kaggle
Examples Freelancer
Source: Adapted from Oshri et al. 2011

Theoretical Framework: Career Anchors

Significant theoretical studies have examined the stages of careers, beginning with the

pioneering work of Super (Super 1957). Super’s work posited four stages of career

development: 1) establishment, 2) advancement, 3) maintenance, and 4) disengagement. Many

corresponding frameworks have been used to define various career stages, including tenure, age,

and organizational level. Another prominent model for describing career stages, presented by

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Dalton et al., describes four career stages: 1) the apprentice stage, characterized by working

under the supervision of others; 2) the colleague stage, characterized by individual contributions;
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3) the mentor stage, characterized by work that can lead to the develop of junior colleagues; and

4) the sponsor stage, characterized by the ability to set direction for the organization. While all
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of these models provide a means by which to describe the stages of career progression, they

provide little insight into the work values driving individuals’ transitions through the stages.
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Schein's career anchors theory (CAT) (Schein 1990; Schein et al. 1978) provides a theoretical

lens through which to examine motivations that steer individuals’ career pathways. The

overarching thesis underlying the concept of career anchors is that internal values drive an

individual’s career decisions. The types of work values considered career anchors have grown

with additional research regarding worker motivations and interests. In Schein’s early work five

career anchors were defined: 1) technical competence, 2) general managerial competence, 3)

security/stability, 4) autonomy/independence and 5) entrepreneurial creativity (Schein et al.

1978). As the relationship between workers and employers has grown more fluid with the

growth of technology and outsourcing, the following four additional anchors have been

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identified: 6) lifestyle integration, 7) pure challenge, 8) organizational identity and 9)sense of

service (Schein 1990).

While the concepts presented by the career anchors framework are applicable to a broad range of

professional endeavors, the framework has been particularly instructive in the examination of IT

careers. IT careers can be marked by rapidly changing skill requirements, and wide ranging

options for career path development. Career Anchors have been used to examine and explain the

career motivations of IS workers and describe the variability of worker expectations that can be

applied to human resource planning (Crepeau et al. 1992). This variability can lead to changes in

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anchors over time. The age and experience of technology workers has been found to predict a

preference toward security and stability associated with the ability to pursue work opportunities
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within a specific geography (Igbaria et al. 1995). The study by Igbaria et al. (1995) also found

that IS experience was positively associated with the career anchor of autonomy. Technology
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workers have been found to have dual career options, either pursuing managerial or supervisory

positions, or pursing technical roles (Baroudi 1988). The differing nature of available technical
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career paths has led some researchers to propose that workers will align with different anchors at

different stages of their career on different career paths (Agarwal et al. 2000). Chang et al.

(2011) examined how career anchors change over time, finding that technology workers who

remain in technology-related positions at traditional firms become more interested in managerial

positions and in geographic security and value higher levels of autonomy. It is unclear if, and if

so how, these findings apply to ITCS, where the work, career, and organizational boundaries are

more fluid than in traditional employment. By addressing the research question posited in this

study, I extend the application of CAT to the ITCS space.

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Career Anchors and the changing nature of Work

While the phenomenon of crowdsourcing continues to grow and a growing number of studies

have examined the behaviors and motivations of crowd workers (Brabham 2010; Deng et al.

2013; Kaufmann et al. 2011), little is understood regarding how IT focused crowdworkers may

be similar to, or differ from, crowdworkers in other domains or traditional IT workers.

Significant theoretical contributions have been made regarding how workers are motivated in

traditional organizations (Amabile 1993; Feldman et al. 1996). Many of these theories address

worker development from the perspective of the employer (Beecham et al. 2008). However, the

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crowdsourcing work environment puts much greater emphasis on workers managing their own

career development. Career anchors theory provides a lens through which to examine why some
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IT professionals participate in ITCS when traditional employment opportunities are plentiful.

While many crowdworkers on platforms like Mechanical Turk may work for far less than
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minimum wage (Deng et al. 2013), crowdworkers on compensation-based platforms such as

oDesk may have the potential to earn far more than minimum wage rates. Do crowdworkers on
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compensation based platforms see their activities as hobbies or as work? Do they participate in

crowdsourcing to develop skills, for compensation, or both? To the extent that IT crowdworkers

see their involvement in crowdsourcing as “work,” career anchors theory (Schein 1990) can help

uncover the crowd workers’ salient anchors to reveal the work values that motivate their

participation in ITCS in order to provide insight into why they choose to participate in this

seemingly unattractive work environment.

Research Methodology

A qualitative approach, revealed causal mapping, is used to effectively evaluate the emerging

crowdsourcing phenomenon and address the underlying research questions, which center on

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“why” workers participate in ITCS, particularly when traditional employment options are

available. Through the revealed causal mapping approach a robust picture can be developed

of the causes and effects that come through engagement with a phenomena, and the underlying

causes and effects can be analyzed from multiple perspectives. A special issue of

Organizational Science on managerial cognition included examples of causal mapping

methodologies (Laukkanen 1996; Meindl et al. 1996; Priem 1996), and the methodology was

introduced to the Information Systems discipline through the work of Nelson et al. (Nelson et al.

2000), who expanded causal mapping techniques to a method they called “revealed causal

mapping.” The methodology of causal mapping allows a researcher to make inferences

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regarding the true motivations and cognitions instigating actions by the linkages between
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observed causes and effects among study participants (Fahey et al. 1989).

A revealed causal mapping approach utilizes opened ended questions to elicit feedback from
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study participants. While traditional revealed casual mapping is conducted via in-person

interviews, given the distributed nature of technology crowdworkers, I used an online survey that
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gives respondents the opportunity to provide text responses. Once data were collected, causal

maps were constructed through analysis of the raw text of survey responses to identify common

themes and commonly related concepts in crowd work motivation and outcomes. The causal

concepts identified in the first wave of analysis were used to create construct-level causal maps

which identified common themes across participants. Raw data were aggregated based on

common themes and concepts, and the relative frequency of each cause and effect relationship

identified in the raw data was calculated. In the study, participants in multiple crowdsourcing

platforms responded to questions regarding motivations and outcomes. The size of the sample

was determined by reaching saturation of cause and effect relationships. Once the point of

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redundancy in the information was identified, the number of responses was doubled to insure

that full saturation had been reached.

Revealed causal mapping methodology is well suited to this research question because it allows

for exploratory research into crowdworkers’ motivations while providing a measure of reliability

of the results. The model creates a framework that can be applied in future quantitative work to

develop a deeper understanding of the implications of crowdsourcing for worker well-being.

Data Collection

I collected data in two steps. First I conducted a pilot study inviting IT crowd workers to

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complete a survey regarding their work motivations. Invitations to complete the survey were

extended through the online crowdsourcing platforms of oDesk, eLance3 and Rent-a-coder. The
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survey was presented as a task and respondents were compensated $20 for their time to complete
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the survey. After the pilot data were collected, minor modifications were made to the survey to

better focus on revealing workers’ career anchors and a second wave of data collection was

completed. A total of 25 responses was collected. The survey was available by invitation to
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crowd workers, and they were randomly selected from the pool of workers on each platform.

Only workers based in the United States were allowed to take the survey. The online survey

comprised of open ended questions regarding work values and outcomes (such as what types of

jobs they usually take, what they like about doing ITCS, what they dislike, what opportunities

ITCS provides that attracts them to that platform, their career goals, how ITCS helps fulfill their

personal and professional priorities, and whether they would consider doing ITCS as their full

time job) and demographic questions (such as their employment status, age, gender, occupation,

3 The data were collected prior to the announcement that oDesk and eLance would merge.

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