From Total Effects to Underlying Mechanisms via Causal Mediation: An Empirical Example from Ride-Hailing Platforms in the United States

30 Pages Posted: 24 Mar 2020 Last revised: 27 Sep 2023

See all articles by Ecem Basak

Ecem Basak

City University of NY, Baruch College, Zicklin School of Business

Ali R. Tafti

University of Illinois at Chicago

Mary Beth Watson-Manheim

University of Illinois at Chicago

Date Written: February 13, 2020

Abstract

For over a decade, IS researchers have explored causal relationships between IT artifacts and various outcomes. They focus on estimating average treatment effects, where IT artifacts cause outcomes. Causal mediation analysis helps identify critical channels and estimate causal mediation effects, revealing the mechanisms behind treatment effects. In this paper, we discuss the benefits and challenges of mediation in causal inference, highlighting differences from previous approaches and offering implementation guidance. We apply causal mediation to investigate an open question in IS literature: How does the demand for public transportation mediate the impact of ride-hailing platforms on US traffic congestion?

Keywords: ride-haling platforms, causal mediation analysis, traffic congestion, public transit ridership

Suggested Citation

Basak, Ecem and Tafti, Ali R. and Watson-Manheim, Mary Beth, From Total Effects to Underlying Mechanisms via Causal Mediation: An Empirical Example from Ride-Hailing Platforms in the United States (February 13, 2020). Available at SSRN: https://ssrn.com/abstract=3544999 or http://dx.doi.org/10.2139/ssrn.3544999

Ecem Basak (Contact Author)

City University of NY, Baruch College, Zicklin School of Business

One Bernard Baruch Way
New York, NY 10010
United States

Ali R. Tafti

University of Illinois at Chicago ( email )

601 S Morgan St, 2403 University Hall, MC 294
Chicago, IL 60607
United States

Mary Beth Watson-Manheim

University of Illinois at Chicago ( email )

1200 W Harrison St
Chicago, IL 60607
United States

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