Understanding crowdsourcing requesters’ wage setting behaviors

• Main Authors: HARA, Kotaro, TANAKA, Yudai
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Human-centered computing; Human computer interaction (HCI); Graphics and Human Computer Interfaces; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/7314; https://ink.library.smu.edu.sg/context/sis_research/article/8317/viewcontent/3491101.3519660.pdf
• Institution: Singapore Management University

Requesters on crowdsourcing platforms like Amazon Mechanical Turk (AMT) compensate workers inadequately. One potential reason for the underpayment is that the AMT’s requester interface provides limited information about estimated wages, preventing requesters from knowing if they are offering a fair...