Evaluation of Bike Network Plan Public Engagement Phase 1

The City of San Antonio is currently updating their Bike Network Plan, initially established in 2011. The plan focuses on improving bicycle safety and creating a more connected and bike-friendly environment throughout San Antonio. This revision addresses evolving requirements and best practices from organizations like the National Association of City Transportation Officials (NACTO), focusing on enhancing bike infrastructure. The goal is to ensure the safety of bikers and create an inviting environment that encourages biking as an alternative mode of transportation.

The need for a new plan for San Antonio's Bike Network, updating from the 2011 version, is driven by the city's dynamic growth and evolution. As San Antonio has developed, with new areas emerging and traffic patterns shifting, the bike network needs to adapt to these changes to remain relevant and efficient. This evolution isn't just physical but also reflects the residents' changing preferences for sustainable and healthier modes of transportation. An updated plan also allows for the incorporation of the latest safety and design standards, ensuring that the network is safe and accessible for all users. Moreover, such a plan is crucial for aligning with broader city goals like reducing carbon emissions, enhancing public transportation, and improving the overall quality of life in San Antonio.

Stated Purpose: To gauge how San Antonians currently ride bikes; their largest concerns with biking; and how their travel patterns would change if biking was feasible.

In their endeavor to revise San Antonio's bike network plan, the COSA Bike Network team's approach exemplified the concepts discussed by Nabatchi and Leighninger (2015) in "Public Participation for 21st Century Democracy." Their strategy was marked by its holistic and inclusive nature, aiming to engage the community comprehensively. By organizing events across all city council districts, the team embraced what Nabatchi and Leighninger (2015) identify as 'thick participation.' This method, centered around small group interactions, enabled in-depth discussions and education about the bike network plan. Such gatherings are vital for fostering community ownership and a deeper understanding among participants, aligning with the book's emphasis on meaningful and deliberative public engagement. Complementing these in-person events, the team's use of online surveys constituted an integration of 'thin participation,' as characterized by Nabatchi and Leighninger (2015). This form of participation, marked by individual and less time-consuming engagements like completing surveys or providing feedback digitally, expanded the scope of participation. It allowed residents unable to attend physical meetings to contribute their perspectives and suggestions for improvements in the bike network. This dual approach in San Antonio reflects what Nabatchi and Leighninger (2015) describe as 'good participation.' The combination of interactive, educational sessions with accessible online feedback channels exemplifies the principle of treating citizens as informed stakeholders. By offering various avenues for input, the initiative ensured a more inclusive participation process and empowered the community, facilitating informed contributions to the decision-making process.

In the process of revising San Antonio's bike network plan, the COSA Bike Network team adopted a survey methodology that effectively merged quantitative and qualitative research techniques. This sophisticated approach is reflective of the principles found in "Planning and Urban Design Standards" authored by the American Planning Association, Steiner, and Butler (2012). The team's method, encompassing a variety of data collection techniques, exhibited a profound understanding of the diverse needs and preferences within the community, a vital component of inclusive urban planning.

The design of the survey, which included the use of visual aids, language that was easy to understand, and availability in Spanish, was a clear demonstration of the team's commitment to inclusivity. This approach made the survey accessible to a broad spectrum of participants, a crucial aspect in urban planning. It particularly resonated with the emphasis placed on acknowledging the varied knowledge and concerns of all community stakeholders, including residents, businesses, and other interest groups, as outlined in the guidebook (American Planning Association, Steiner, & Butler, 2012).

Furthermore, the survey employed closed-ended questions that used scales, such as the Likert scale, to evaluate participants' comfort levels on different types of roads and with various biking facilities. This strategic use of quantitative methods was instrumental in gathering specific, measurable data, essential for making informed decisions in urban design and infrastructure. This technique was directly in line with the guidebook’s recommendation of involving a wide array of interests in conversations about the community's physical, environmental, social, and economic development (American Planning Association, Steiner, & Butler, 2012).

In addition to these quantitative measures, the inclusion of open-ended questions in the survey allowed for the collection of richer, more detailed feedback. This approach not only captured the depth of qualitative data but also provided insights that extended beyond the scope of quantifiable metrics. It echoed the guidebook's advice on the importance of documenting stakeholder interests and the processes of stakeholder involvement in the planning process, ensuring that a variety of perspectives were considered and valued (American Planning Association, Steiner, & Butler, 2012).

The Bike Network Plan's public engagement in San Antonio incorporates elements of PPGIS, utilizing surveys with geographic information, and interactive maps that enable users to pinpoint locations where biking infrastructure requires enhancements for safety, convenience, and comfort. This approach is visualized through maps that display survey data, indicating the origins of comments across the city and ensuring that feedback is gathered from all districts. This method aligns with the principles discussed in the study by Griffin, G. P., & Jiao, J. (2019), which emphasizes the importance of public participation in planning through PPGIS. In the context of San Antonio’s Bike Network Plan, the use of PPGIS tools like interactive maps and geographically-tagged surveys can significantly enhance the understanding of community needs and preferences. It ensures that the infrastructure developments are not just top-down decisions but are informed by the actual users of the bike network, reflecting a diverse range of experiences and requirements.

Through this public engagement process, over 450 location-specific comments were received, and over 1,600 surveys were collected, providing a substantial dataset to work with. By utilizing a manifest approach and conducting a category count (Gaber & Gaber, 2007, pp. 110), the team was able to develop and extract meaningful insights through these qualitative datasets. These category count findings are showcased on Page 24 of the Phase 1 Community Engagement document, and conveniently compiled in a user-friendly interactive dashboard. Outfitted with spatial and temporal data dimension manipulation capabilities, the interactive dashboard provides an opportunity for future investigative research.

The bike network plan in San Antonio has effectively incorporated a mobility working group, consisting of stakeholders from the biking community who bring a blend of technical and practical expertise. This advisory group plays a crucial role in the ongoing development and refinement of the plan. Members are kept abreast of the latest developments, including the results of surveys, which ensures that they are well-informed and actively engaged in the planning process. The group's involvement extends to participating in breakout sessions, where they focus on identifying and reinforcing areas in the bike network that require improvement or highlighting new areas in need of facilities. The inclusion of this working group is vital for several reasons. First, it taps into the wealth of knowledge and experience of community members who are deeply involved in biking, ensuring that the plan is both practical and technically sound. Second, by representing the broader biking community, the plan is more likely to reflect the actual needs and preferences of those who will use the bike network most.

San Antonio's bike network plan demonstrated a comprehensive urban planning approach through its public engagement strategy, which combined community events and online surveys. This approach effectively gathered data on biking habits and educated the public about their impact on cycling infrastructure development. The surveys, notable for their blend of quantitative and qualitative methods, were accessible in multiple languages and employed visual aids, aligning with American Planning Association standards. While quantitative data was effectively collected using tools like the Likert scale, open-ended questions provided deeper insights. The integration of Participatory Planning GIS (PPGIS) allowed for specific geographic feedback, embodying modern inclusive urban planning principles. The involvement of a citizen advisory group, representing a diverse range of stakeholders from the biking community, ensured that the plan was informed by real-world experiences. However, while this approach marked a significant step in community-focused urban planning, it also highlighted areas where further improvements are necessary. Continued efforts to enhance the inclusivity and impact of community feedback, along with a deeper integration of stakeholder suggestions, could further refine and strengthen the cycling infrastructure, making it even more effective and reflective of the community's diverse needs and preferences.

In assessing the public engagement methods utilized in San Antonio's bike network plan, it is pertinent to apply Sherry Arnstein's Ladder of Citizen Participation as a framework. This model classifies the level of citizen power in decision-making processes within public participation models. Arnstein's Ladder comprises eight rungs, categorized into three broad levels: Nonparticipation, Tokenism, and Citizen Power.

Upon examination, San Antonio's approach appears to align with the 'Tokenism' level of Arnstein's Ladder, swaying between Consultation and Placation:

Consultation: This stage involves seeking opinions, holding public meetings, and conducting surveys, albeit with no guarantee that public input will significantly impact decision-making. The San Antonio plan's use of surveys and community events to collect data on biking habits and concerns mirrors this level of participation. It demonstrates an effort to listen to community voices, yet the degree to which this input tangibly influences final decisions remains ambiguous.

Placation: At this level, citizens have some influence, but final decision-making authority still rests with traditional power holders. The incorporation of a citizen advisory group in the San Antonio plan suggests an advancement towards placation. The group, representing diverse stakeholders in the biking community, seems to have a consultative role in the process, reviewing survey results and participating in discussions. However, it is likely that ultimate decision-making power lies with city officials and planners.

While acknowledging the notable successes achieved, it is worthwhile to explore a few areas that might benefit from further consideration. We’ve identified two overarching themes in the approach to public engagement that could be refined and optimized: Communication and Qualitative Data Analysis. Findings from our study suggest that the plan could provide clearer communication about the activities entailed in each phase, thereby improving the public’s understanding of how the engagement process will be structured. Additionally, the  plan does not outline how the public engagement data will be used, nor is there an online archive of past meeting materials provided for reference — both of which are common practice in plans of similar nature. Regarding our concerns focused on qualitative analysis, it may be beneficial to explore potential implications of relying predominantly on public engagement from existing frequent riders. This approach might inadvertently overlook the perspectives of individuals who are not currently frequent cyclists but could become so in the future. Lastly, regarding the location-specific comments (qualitative data), there appears to be an opportunity to advance qualitative research through the implementation of latent trend and pattern content analysis. We suggest incorporating a time variable across the entire dataset, and revisiting the comments to identify underlying themes for a more comprehensive contextual understanding.