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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 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.

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Acknowledgements

The data collection for this research was supported by an award from the World Bank Group Big Data Innovation Challenge. Additional research support was provided by the Singapore National Research Foundation through the Singapore–MIT Alliance for Research and Technology Center for Future Urban Mobility.

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Correspondence to P. Christopher Zegras.

Appendix

Appendix

Following Filmer and Pritchett (2001), we construct a linear wealth index for the surveyed households using asset ownership indicators. We apply principal components analysis (PCA) and calculate the wealth index based on the normalized variables and their respective loadings (Table 7) on component 1.

Table 7 First nine components from principal components analysis on household durable goods

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Zegras, P.C., Li, M., Kilic, T. et al. Assessing the representativeness of a smartphone-based household travel survey in Dar es Salaam, Tanzania. Transportation 45, 335–363 (2018). https://doi.org/10.1007/s11116-017-9851-6

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Keywords

  • Household travel survey
  • Smartphones
  • Response rates and biases
  • Dar es Salaam
  • Tanzania