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research-article

Analyzing Participant Behaviors in Design Crowdsourcing Contests using Game Theoretic Models and Field Data

[+] Author and Article Information
Ashish M. Chaudhari

Graduate Research Assistant, School of Mechanical Engineering, Purdue University, West Lafayette, Indiana 47907
chaudha5@purdue.edu

Zhenghui Sha

Assistant Professor, Department of Mechanical Engineering, University of Arkansas, Fayetteville, Arkansas 72701
zsha@uark.edu

Jitesh H. Panchal

Associate Professor, School of Mechanical Engineering, Purdue University, West Lafayette, Indiana 47907
panchal@purdue.edu

1Corresponding author.

ASME doi:10.1115/1.4040166 History: Received July 05, 2017; Revised April 25, 2018

Abstract

Crowdsourcing is the practice of getting ideas and solving problems using a large number of people on the Internet. It is gaining popularity for activities in the engineering design process ranging from concept generation to design evaluation. The outcomes of crowdsourcing contests depend on the decisions and actions of participants, which in turn depend on the nature of the problem and the contest. For effective use of crowdsourcing within engineering design, it is to understand how the outcomes of crowdsourcing contests are affected by sponsor-related, contest-related, problem-related, and individual-related factors. To address this need, we employ existing game-theoretic models, empirical studies, and field data in a synergistic way using the theory of causal inference. The results show that participants' decisions to participate are negatively influenced by higher task complexity and lower reputation of sponsors. However, they are positively influenced by the number of prizes, prize amounts, and higher allocation to prizes at higher levels. That is, an amount of money on any following prize generates better participation than the same amount of money on the first prize. The contributions of the paper are: (a) a causal graph that encodes relationships among factors affecting crowdsourcing contests, derived from game-theoretic models and empirical studies, and (b) a quantification of the causal effects of these factors on the outcomes of GrabCAD contests. The implications of these results on the design of future design crowdsourcing contests are discussed.

Copyright (c) 2018 by ASME
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