Disintermediation Evidence From a Cleaning Platform

24 Pages Posted: 28 Sep 2022 Last revised: 21 Oct 2022

Date Written: September 17, 2022

Abstract

We present evidence of disintermediation---a notoriously challenging task---in a European cleaning platform's transaction data between April 2016 and February 2020. In short, we demonstrate that a cleaner's leaving the platform is typically accompanied by unusually many customers' also leaving the platform. This pattern (i) replicates in most cities in our data, (ii) is robust to alternative specifications of the empirical exercise, and (iii) cannot be explained away by bad cleaners driving customers away, cleaners and customers trying out the platform once or twice and then exiting, or customers being unable to find their favorite cleaner on the platform. Further, we project that the platform would enjoy about 24 percent more cleanings if not for disintermediation. Our approach (empirical test plus counterfactual simulation) only requires run-of-the-mill, observational transaction data and can be applied to any similar setting.

Suggested Citation

Karacaoglu, Nil and Li, Simin and Stamatopoulos, Ioannis, Disintermediation Evidence From a Cleaning Platform (September 17, 2022). Available at SSRN: https://ssrn.com/abstract=4222023 or http://dx.doi.org/10.2139/ssrn.4222023

Nil Karacaoglu

Fisher College of Business, The Ohio State University ( email )

2100 Neil Avenue
Columbus, OH 43210
United States

HOME PAGE: http://sites.google.com/view/nilkaracaoglu

Simin Li

Tulane University - A.B. Freeman School of Business ( email )

7 McAlister Drive
New Orleans, LA 70118
United States

Ioannis Stamatopoulos (Contact Author)

The University of Texas at Austin - McCombs School of Business ( email )

2110 Speedway B6000
Austin, TX 78705
United States

HOME PAGE: http://https://sites.utexas.edu/yannis-stamos/

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