Assessing the representativeness of a smartphone-based household travel survey in Dar es Salaam, Tanzania

Abstract The household travel survey (HTS) finds itself in the midst of rapid technological change. Traditional methods are increasingly being sidelined by digital devices and computational power—for tracking movements, automatically detecting modes and activities, facilitating data c...

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Bibliographic Details
Main Authors: Zegras, P. C, Li, Menghan, Kilic, Talip, Lozano-Gracia, Nancy, Ghorpade, Ajinkya, Tiberti, Marco, Aguilera, Ana I, Zhao, Fang
Other Authors: Massachusetts Institute of Technology. Department of Urban Studies and Planning
Format: Article
Language:English
Published: Springer US 2021
Online Access:https://hdl.handle.net/1721.1/131519
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Summary:Abstract The household travel survey (HTS) finds itself in the midst of rapid technological change. Traditional methods are increasingly being sidelined by digital devices and computational power—for tracking movements, automatically detecting modes and activities, facilitating data collection, etc.. Smartphones have recently emerged as the latest technological enhancement. FMS is a smartphone-based prompted-recall HTS platform, consisting of an app for sensor data collection, a backend for data processing and inference, and a user interface for verification of inferences (e.g., modes, activities, times, etc.). FMS, has been deployed in several cities of the global north, including Singapore. This paper assesses the first use of FMS in a city of the global south, Dar es Salaam. FMS in Dar was implemented over a 1-month period, among 581 adults chosen from 300 randomly selected households. Individuals were provided phones with data plans and the FMS app preloaded. Verification of the collected data occurred every 3 days, via a phone interview. The experiment reveals various social and technical challenges. Models of individual likelihood to participate suggest little bias. Several socioeconomic and demographic characteristics apparently do influence, however, the number of days fully verified per individual. Similar apparent biases emerge when predicting the likelihood of a given day being verified. Some risk of non-random, non-response is, thus, evident.