Improving Transit in Small Cities through Collaborative and Data-driven Scenario Planning

Published in Case Studies on Transport Policy, 2023

Recommended citation: Goodspeed, Robert, et al. "Improving Transit in Small Cities through Collaborative and Data-driven Scenario Planning." Case Studies on Transport Policy (2023): 100957. https://www.sciencedirect.com/science/article/pii/S2213624X23000111

Abstract

Small communities often lack effective transit planning methods that can integrate diverse forms of knowledge, foster collaboration, and envision better transit futures. To address these needs, this paper presents a case study of a project conducted in Benton Harbor, Michigan. The case study demonstrates a collaborative and data-driven scenario planning process conducted for a small region, and evaluates it through a mixed-methods research design. Through the use of normative service scenarios and exploratory qualitative scenarios, the project generated financially and operationally feasible proposals that community leaders can implement in the future, and also fostered constructive dialogue among transit stakeholders. Survey data show that participants experienced high levels of learning, engaged in quality deliberation, and are generally optimistic about the potential for improved transit. The project’s approach can be replicated elsewhere through the use of five essential elements: a steering committee, stakeholder analysis, a series of engagement workshops, normative and exploratory scenarios, and interaction between data and modeling. Collaborative planning with scenarios can help the transportation field address the need to foster collaboration and epistemic inclusion in a changing world.

*The scenario planning process was envisioned as the primary link between various smart mobility data collection activities and changes that would improve mobility-related outcomes in the community. *