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Understanding Design Decisions under Competition using Games with Information Acquisition and a Behavioral Experiment

[+] Author and Article Information
Jitesh H. Panchal

School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907
panchal@purdue.edu

Zhenghui Sha

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

Karthik Kannan

Krannert School of Management, Purdue University, West Lafayette, IN 47907
kkarthik@purdue.edu

1Corresponding author.

ASME doi:10.1115/1.4037253 History: Received March 14, 2017; Revised June 23, 2017

Abstract

The primary motivation in this paper is to understand decision-making in design under competition from both prescriptive and descriptive perspectives. Engineering design is often carried out under competition from other designers or firms, where each competitor invests effort with the hope of getting a contract, attracting customers, or winning a prize. One such scenario of design under competition is crowdsourcing where designers compete for monetary prizes. Within existing literature, such competitive scenarios have been studied using models from contest theory, which are based on assumptions of rationality and equilibrium. Although these models are general enough for different types of contests, they do not address the unique characteristics of design decision-making, e.g., strategies related to the design process, the sequential nature of design decisions, the evolution of strategies, and heterogeneity among designers. In this paper, we address these gaps by developing an analytical model for design under competition, and using it in conjunction with a behavioral experiment to gain insights about how individuals actually make decisions in such scenarios. The contributions of the paper are two fold. First, a game-theoretic model is presented for sequential design decisions considering the decisions made by other players. Second, an approach for synergistic integration of analytical models with data from behavioral experiments is presented. The proposed approach provides insights such as shift in participants' strategies from exploration to exploitation as they acquire more information, and how they develop beliefs about the quality of their opponents' solutions.

Copyright (c) 2017 by ASME
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