Unveiling the Inter-Related Preferences of Crowdworkers: Implications for Personalized and Flexible Platform Design

TL;DR

This study explores the interconnected preferences of crowdworkers regarding device usage and work practices, providing insights for designing more personalized and flexible crowdsourcing platforms.

Contribution

It is the first to analyze the interrelated variabilities among crowdworker preferences and device usage, informing platform customization.

Findings

Identified three distinct crowdworker groups based on device preferences and work routines.

Most workers prefer traditional devices with limited interest in smartphones and tablets.

A small group actively uses and prefers mobile devices for crowdwork.

Abstract

Crowdsourcing platforms have traditionally been designed with a focus on workstation interfaces, restricting the flexibility that crowdworkers need. Recognizing this limitation and the need for more adaptable platforms, prior research has highlighted the diverse work processes of crowdworkers, influenced by factors such as device type and work stage. However, these variables have largely been studied in isolation. Our study is the first to explore the interconnected variabilities among these factors within the crowdwork community. Through a survey involving 150 Amazon Mechanical Turk crowdworkers, we uncovered three distinct groups characterized by their interrelated variabilities in key work aspects. The largest group exhibits a reliance on traditional devices, showing limited interest in integrating smartphones and tablets into their work routines. The second-largest group also primarily uses traditional devices but expresses a desire for supportive tools and scripts that enhance productivity across all devices, particularly smartphones and tablets. The smallest group actively uses and strongly prefers non-workstation devices, especially smartphones and tablets, for their crowdworking activities. We translate our findings into design insights for platform developers, discussing the implications for creating more personalized, flexible, and efficient crowdsourcing environments. Additionally, we highlight the unique work practices of these crowdworker clusters, offering a contrast to those of more traditional and established worker groups.