The motivations and experiences of the on-demand mobile workforce

On-demand mobile workforce applications match physical world tasks and willing workers. These systems offer to help conserve resources, streamline courses of action, and increase market efficiency for micro- and mid-level tasks, from verifying the existence of a pothole to walking a neighbor's dog. This study reports on the motivations and experiences of individuals who regularly complete physical world tasks posted in on-demand mobile workforce marketplaces. Data collection included semi-structured interviews with members (workers) of two different services. The analysis revealed the main drivers for participating in an on-demand mobile workforce, including desires for monetary compensation and control over schedules and task selection. We also reveal main reasons for task selection, which involve situational factors, convenient physical locations, and task requester profile information. Finally, we discuss the key characteristics of the most worthwhile tasks and offer implications for novel crowdsourcing systems for physical world tasks.

[1]  Aniket Kittur,et al.  An Assessment of Intrinsic and Extrinsic Motivation on Task Performance in Crowdsourcing Markets , 2011, ICWSM.

[2]  Lorrie Faith Cranor,et al.  Are your participants gaming the system?: screening mechanical turk workers , 2010, CHI.

[3]  Aniket Kittur,et al.  Instrumenting the crowd: using implicit behavioral measures to predict task performance , 2011, UIST.

[4]  Brad J. Sagarin,et al.  A Functional Approach to Volunteerism: Do Volunteer Motives Predict Task Preference? , 2005 .

[5]  Benjamin B. Bederson,et al.  Web workers unite! addressing challenges of online laborers , 2011, CHI Extended Abstracts.

[6]  Nina Mazar,et al.  Large stakes and big mistakes , 2009 .

[7]  Chrysanthos Dellarocas,et al.  Harnessing Crowds: Mapping the Genome of Collective Intelligence , 2009 .

[8]  Jens Riegelsberger,et al.  Face it - photos don't make a web site trustworthy , 2002, CHI Extended Abstracts.

[9]  R. Sugden,et al.  Regret Theory: An alternative theory of rational choice under uncertainty Review of Economic Studies , 1982 .

[10]  E. Fehr,et al.  Psychological Foundations of Incentives , 2002 .

[11]  P. Lawrence,et al.  Industrial Jobs and the Worker , 1966 .

[12]  Aniket Kittur,et al.  CrowdForge: crowdsourcing complex work , 2011, UIST.

[13]  David E. Bell,et al.  Regret in Decision Making under Uncertainty , 1982, Oper. Res..

[14]  Luis von Ahn.  Human Computation , 2008, ICDE.

[15]  S. M. Arnsten.  Intrinsic motivation. , 1990, The American journal of occupational therapy : official publication of the American Occupational Therapy Association.

[16]  A. Kohn.  Why incentive plans cannot work , 1993 .

[17]  E. Deci,et al.  Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. , 2000, The American psychologist.

[18]  Richard,et al.  Motivation through the Design of Work: Test of a Theory. , 1976 .

[19]  Duncan J. Watts,et al.  Financial incentives and the "performance of crowds" , 2009, HCOMP '09.

[20]  R. Gibbons.  Piece-Rate Incentive Schemes , 1987, Journal of Labor Economics.

[21]  Dana Chandler,et al.  Breaking Monotony with Meaning: Motivation in Crowdsourcing Markets , 2012, ArXiv.

[22]  Lydia B. Chilton,et al.  TurKit: human computation algorithms on mechanical turk , 2010, UIST.

[23]  F. Herzberg.  One More Time: How Do You Motivate Employees? , 2008 .

[24]  A. Tenbrunsel,et al.  Organizational Behavior and Human Decision Processes , 2013 .

[25]  Daniel J. Veit,et al.  More than fun and money. Worker Motivation in Crowdsourcing - A Study on Mechanical Turk , 2011, AMCIS.

[26]  Deepak Ganesan,et al.  Labor dynamics in a mobile micro-task market , 2013, CHI.

[27]  Bill Tomlinson,et al.  Sellers' problems in human computation markets , 2010, HCOMP '10.

[28]  I. Ajzen.  The theory of planned behavior , 1991 .

[29]  Laura A. Dabbish,et al.  Social transparency in networked information exchange: a theoretical framework , 2012, CSCW.

[30]  M. Six Silberman,et al.  Turkopticon: interrupting worker invisibility in amazon mechanical turk , 2013, CHI.

[31]  Alireza Sahami Shirazi,et al.  Location-based crowdsourcing: extending crowdsourcing to the real world , 2010, NordiCHI.

[32]  J. van der Pligt,et al.  Anticipated Affect and Behavioral Choice , 1996 .

[33]  A. Rustichini,et al.  Pay Enough or Don't Pay at All , 2000 .

[34]  Panagiotis G. Ipeirotis,et al.  Quality management on Amazon Mechanical Turk , 2010, HCOMP '10.

[35]  Siddharth Suri,et al.  Conducting behavioral research on Amazon’s Mechanical Turk , 2010, Behavior research methods.

[36]  Bill Tomlinson,et al.  Who are the crowdworkers?: shifting demographics in mechanical turk , 2010, CHI Extended Abstracts.

[37]  Heike Schaumburg,et al.  A picture says more than a thousand words: photographs as trust builders in e-commerce websites , 2002, CHI Extended Abstracts.

[38]  Aniket Kittur,et al.  Crowdsourcing user studies with Mechanical Turk , 2008, CHI.

[39]  Michael S. Bernstein,et al.  The future of crowd work , 2013, CSCW.

[40]  Panagiotis G. Ipeirotis.  Demographics of Mechanical Turk , 2010 .

[41]  Benjamin B. Bederson,et al.  Human computation: a survey and taxonomy of a growing field , 2011, CHI.

[42]  A. Tversky,et al.  Rational choice and the framing of decisions , 1990 .

[43]  Hector Garcia-Molina,et al.  Turkalytics: analytics for human computation , 2011, WWW.

[44]  E. Deci.  Effects of Externally Mediated Rewards on Intrinsic Motivation. , 1971 .