Road to a Master’s Thesis: Idealog 4

This is the fourth in a series of posts documenting my journey towards a Masters in Urban Planning research project. This one dives into one idea (exploring the travel demand impact of remote work in the tech industry) more deeply, including some thoughts on potential methodology.

Post-COVID-19 Remote Work Travel Patterns


The COVID-19 pandemic upended typical mobility patterns around the globe from 2020 through 2021, especially for people accustomed to commuting for work. One of the most significant disruptors was the rapid acceleration of what was already a growing trend of remote (or distributed) work. Enabled by videoconferencing and asynchronous collaboration software (e.g., Zoom, Slack, Microsoft/Box/Dropbox/Atlassian solutions, etc.), many so-called “knowledge workers” (a.k.a. the “creative class”) were suddenly granted the ability/mandate to work from anywhere with an internet connection. The quick implementation of new corporate remote work policies and mass closure of traditional offices meant that millions of people no longer had a daily commute longer than the length of their homes.

Source: The Verge

It’s important to note that the luxury of remote work was not accessible to everyone, nor was it universally desirable. Past research has found that only about one-third of all jobs could be done fully remotely – and less than half of those in a recent survey stated they would prefer never going into a physical office location. However, a more significant portion have stated that they would be open to working remotely for two or three days a week. This demonstrates that the flexibility of remote work has broad appeal, but that it may not be something people prefer to do 100% of the time.

Many books have also been written on the topic of remote work. Scott Berkun’s The Year Without Pants and Jason Fried’s REMOTE both evangelized the distributed work revolution and pointed out that there will still be times when people want to congregate for in-person collaboration. The emerging narrative across most knowledge worker industries was that the nature of work would inevitably become more flexible and distributed. Personally, I have also been a huge proponent of this mindset.

Since technology had always been the driver of this paradigm shift, it was natural that software companies were some of the first to go fully remote in the early days of the pandemic. In fact, companies in San Francisco and Silicon Valley announced remote work policies before local governments even began lockdowns, potentially playing a significant role in stemming the spread of COVID-19 early in the San Francisco Bay Area. As the pandemic dragged on through 2020, these same companies began extending their remote work flexibility to extremes – first to the end of the year, then mid-2021, and eventually adopting indefinite (or “virtual-first”) policies that would cement the role of remote work in corporate cultures for years to come.

This came with much buzz about a predicted “tech exodus” out of Silicon Valley, and the rise in prominence of secondary tech hubs such as Austin, Seattle, or Miami (unlikely).

However, early research showed the exodus was more hype than reality – though there were significant numbers of people who left San Francisco city limits for the surrounding counties, perhaps demonstrating the acceleration of a move to suburbs for families who were already planning as such.

Regardless of where these employees moved, the fact remains that remote work is the new normal for most people in the tech industry for the foreseeable future. This means a significant portion of former commuters will no longer be on highways, commuter rail, or even walking downtown on a daily basis. This has profound implications for cities and transportation systems everywhere, but perhaps more pronounced in the San Francisco Bay Area due to the outsized presence of the technology industry.

While tech employees were never the outright majority of commuters in the Bay Area, they had represented the fastest growing industry segment prior to the pandemic (reaching nearly 1 million jobs in 2019) and their working habits arguably presage the behavior of all remote-eligible workers. The Bay Area Council Economic Institute estimates that 1.79 million residents in the region are remote-eligible, meaning even a small percentage of them working from home a few days a week would have significant impacts on traffic congestion and transit agency revenue.

Scope of Research

This research aims to uncover the long-term implications of remote work on travel demand patterns, with a focus on employees in the tech sector. The study will be limited to employees formerly tied to a headquarter office in the San Francisco Bay Area, to derive learnings about what happens when a region has an overweighted sector that suddenly has the option of not commuting.

The intention of the research is to help local governments and public transit agencies better forecast travel demand in the years to come, answering questions such as:

  • For those with the option of remote work, has there been a long-term shift in their preferred modes of travel after COVID-19?
    • Have people bought/sold cars, switched to biking, stopped taking public transit?
    • Will traffic congestion levels be better or worse in the future?
      • Do people use cars more because they perceive there will be less traffic?
      • Will the influx of new cars on the road lead to unmanageable congestion?
  • Given the prevalence of indefinite remote work policies, will public transit ridership levels ever fully recover from pre-pandemic levels?
    • Is this problem unique to the Bay Area given its high concentration of tech workers?


An online survey will be conducted with a sample of people working at technology companies headquartered (or formerly headquartered in 2020) in the San Francisco Bay Area. To establish long-term revealed preference (instead of just stated preference), the survey will be conducted in late 2021 / early 2022 and ask about past behavior starting from the point of COVID-19 vaccination. Topics covered may include:

  • Company attributes (i.e., size) and history/culture around remote work
  • Currently established long-term remote work policy
  • Personal commute patterns before and after the COVID-19 pandemic
    • Modal shifts or change in vehicle ownership
    • Days in the office versus fully remote
  • Travel patterns outside of work purposes

Questions about the future will be limited to the short-term (i.e., speculation on something 5 years out would not be valuable). Analysis would be segmented by demographics (particularly with regards to family size and presence of children) and location if participants end up being in significantly disparate geographic areas.

The survey results can be paired with some external data sources to verify hypothetical patterns. Data sources may include:

  • Car and bicycle sale data
  • National Household Travel Survey
  • Traffic data from Inrix or local road sensors

One thought on “Road to a Master’s Thesis: Idealog 4

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