Which Local Governments Adopt New Technology First?
Ishana Ratan (UC Berkeley), Alison Post (UC Berkeley), Tanu Kumar (Claremont Graduate University), & Mridang Sheth (UC Berkeley)
What shapes transportation technology adoption?
Emerging technologies, including real-time digital tracking systems, AI, and satellite imagery, can enhance public service delivery by enabling real-time performance monitoring, automating routine tasks, and improving the targeting of services. These tools also have the potential to support more responsive and personalized interactions with citizens, increasing both efficiency and trust in government institutions. Under what conditions are new and emerging technologies adopted by local governments?
This article explores the question of technology adoption among local governments through the case of the General Transit Feed Specification (GTFS). GTFS is a standard that allows transportation agency routes and bus times to be displayed on Google Maps, the Transit App, and other trip planning software used by millions of people every day. GTFS is necessary for transit agencies to share this up-to-date route and schedule data, making it an important case of technology adoption.
However, while this standard is necessary for transit agencies to share their information on major trip planning platforms, its adoption has not been universal across agencies in California. Instead, there is considerable variation in the rate of GTFS adoption, and analyzing which agencies adopted GTFS earliest contributes to the understanding of how local governments adopt technology.
Beyond responsiveness: The role of bureaucratic capacity
A common assumption in public administration and political science is that local governments improve service delivery in response to voter pressure, especially in smaller communities where elected officials are more visible. Based on this perspective, smaller towns and cities, where residents can more easily hold officials accountable, should be early adopters of technologies that make public services more transparent and user-friendly.
However, our research into GTFS adoption among transit agencies in California reveals a different dynamic. Instead of a voter-driven patten of technology adoption, which would predict that smaller agencies adopt first, we find that larger agencies are consistently the first to adopt this critical trip planning technology. The figure below shows the adoption curve of large, medium, and small agencies, derived from a survival analysis in the paper.
Figure 1.
This pattern highlights a critical factor in agencies’ adoption of GTFS: bureaucratic capacity. Technology adoption, in the case of public transportation, does not occur solely because of voter pressure. Instead, technology adoption depends upon whether an agency has the internal expertise and resources to adopt and implement a new technology.
In particular, interviews with transit officials across California highlight that the adoption of GTFS was driven not by voter demand but by the efforts of internal champions within transit agencies. GTFS has been championed by employees who recognized the potential benefits for riders and the agency itself. The benefits of GTFS include fewer complaints, better informed riders, and compatibility with widely used third-party apps. These agency staff, then, advocated for adoption and navigated the bureaucratic hurdles necessary to implement GTFS.
Moreover, although variation in the timing of technology adoption is driven by agency size, we find that once GTFS is adopted, size is not a predictor of GTFS feed updating. We find that when small agencies adopt GTFS, they are no less likely to update their feed regularly than larger peers. In sum, the main barrier to the utilization of new transportation technologies is the initial hurdle of adoption, rather than maintenance. When small agencies can overcome obstacles to adoption, they too can benefit from new transportation technologies.
Why larger agencies tend to adopt first
In addition to establishing the pattern that larger agencies adopt GTFS earliest, the paper identifies four key reasons why larger government agencies often adopt new technologies earlier than their smaller counterparts. We emphasize the importance of internal champions for adoption, as discussed in broader smart city technology adoption literature, in addition to highlighting the role of economies of scale, technological compatibilities, and relationships with vendors for GTFS adoption.
First, large agencies often employ dedicated technical staff whose primary responsibility is managing the adoption of new technologies. While small transit agencies may have multiple employees tasked with different roles, larger agencies often have specific information technology departments and data analysts. These subject matter experts are well positioned to evaluate new technologies and understand their benefits.
Second, larger agencies benefit from economies of scale. Investing in a new technical system requires upfront costs like staff time, specialized knowledge, and selecting a vendor. These costs are more easily justified among larger agencies which serve a larger population and cover more service area.
Third, large agencies tend to have existing technologies that allow for a smoother adoption process, integrating new features into legacy systems. For example, large agencies often employ automatic vehicle location for internal operations, which allows them to transmit real time transit data to GTFS feeds. Smaller agencies, however, must set up new vehicle tracking systems from scratch before making use of real-time transit data.
Finally, large agencies are more visible to technology vendors seeking to launch new products. Namely, a contract with a large city’s transportation agency is more attractive than piloting a product with a small rural provider. Vendors often seek out large agencies first, offering demonstrations and pilot programs to high-profile agencies.
Policy implications
The findings from this paper suggest that policy can improve the adoption and utilization of transportation technologies, especially among small agencies that tend to adopt later than their larger counterparts. Namely, small transportation agencies may require technical assistance or collaboration with larger agencies in their region or state in order to learn about the benefits of and adopt new technologies.
Interviews highlight the role of large agencies and regional organizations in promoting technology, and policy could focus on amplifying these efforts to assist smaller agencies. Interviewees mention the role of the California Integrated Transit Project (CalITP), which hosts informational events and leads bulk procurement programs, empowering small agencies to adopt new technologies. These types of collaborative efforts all support the diffusion of technology from large to small agencies and close the gap in adoption.
Ishana Ratan is a PhD candidate in political science at the University of California, Berkeley, and a fellow at the Johns Hopkins Net Zero Industrial Policy Lab. In Fall 2025, she will join the Department of Political Science at the University of Mississippi as an assistant professor. She researches the politics of technology governance, specifically the political economy of green technology, investment, and development.
Alison E. Post is an associate professor of political science and Global Metropolitan Studies at the University of California, Berkeley. Her research focuses on comparative urban politics and policy, and especially topics related to infrastructure. She is the author of Foreign and Direct Investment in Argentina: The Politics of Privatized Infrastructure (Cambridge University Press), as well as numerous articles.
Tanu Kumar is a governance specialist in the Public Institutions Data and Analytics Unit at the World Bank and faculty affiliate at the Center for Effective Global Action at Berkeley. Her academic research focuses on governance, bureaucracy, and how citizens can improve government services in developing countries, particularly India. She holds a PhD in Political Science from the University of California, Berkeley.
Mridang Sheth is a senior software engineer at LinkedIn, where he designs and builds scalable subscription infrastructure, user-facing product flows, and data analytics platforms that power AI-driven recommendations and retention experiments for LinkedIn Premium. He holds a BS in Electrical Engineering and Computer Science from the University of California, Berkeley.