Degree
Doctor of Philosophy (PhD)
Department
Division of Computer Science and Engineering
Document Type
Dissertation
Abstract
Applications (apps) of the Digital Sharing Economy (DSE), such as Uber, Airbnb, and TaskRabbit, have become a main facilitator of economic growth and shared prosperity in modern-day societies. However, recent research has revealed that the participation of minority groups in DSE activities is often hindered by different forms of bias and discrimination. Evidence of such behavior has been documented across almost all domains of DSE, including ridesharing, lodging, and freelancing. However, little is known about the under- lying design decisions of DSE systems which allow certain demographics of the market to gain unfair advantage over others. To bridge this knowledge gap, in this dissertation, we investigate the problem of digital discrimination from a software engineering point of view. To develop an in-depth understanding of the problem, we first synthesize existing evidence on digital discrimination from interdisciplinary literature. We then analyze online user feedback, available on social media channels, to assess end-users’ awareness of discrimination issues affecting their DSE apps. We then introduce a novel protocol for drafting and evaluating nondiscrimination policies (NDPs) in the DSE market. Our objective is to assist DSE developers with drafting high quality and less ambiguous NDPs. Finally, we propose and evaluate a modeling framework for representing discrimination concerns affecting popular DSE apps along with their relations (synergies and tradeoffs) to other system features and user goals. Our objective is to visualize such complex domain knowledge using formal notations that software developers can easily understand, communicate, and utilize as an integral part of their app design process. The impact of the proposed research will extend to the entire population of DSE workers, targeting the deep racial and regional disparities in the DSE market and helping people in resource-constrained communities to overcome key barriers to participation and adaptation in one of the fastest growing software ecosystems in the world.
Date
3-3-2022
Recommended Citation
Tushev, Miroslav, "Digital Discrimination in the Sharing Economy: Evidence, Policy, and Feature Analysis" (2022). LSU Doctoral Dissertations. 5760.
https://repository.lsu.edu/gradschool_dissertations/5760
Committee Chair
Mahmoud, Nash
DOI
10.31390/gradschool_dissertations.5760