Long-term evaluation of individualized marketing programs for travel demand management

Dill, Jennifer; Mohr, Cynthia · 2010 · ROSA P / Oregon Transportation Research and Education Consortium

archive: archived pipeline: cataloged verified

Get this paper ↗ (full text — opens at the source; we link to it, we don't host it)

Summary

This study evaluates the long-term effectiveness of individualized marketing programs for travel demand management (TDM), specifically examining the City of Portland’s SmartTrips program. Motivated by the need to address traffic congestion and environmental concerns without expanding infrastructure, the research addresses two primary gaps in existing literature: the lack of data on whether behavior changes persist beyond the immediate post-intervention period, and the insufficient understanding of the psychological mechanisms driving these changes. While previous evaluations showed short-term reductions in drive-alone trips, few assessed sustainability over one to two years, and traditional microeconomic theories often fail to fully explain travel decision-making. Consequently, this research applies the Theory of Planned Behavior (TPB) to determine if attitudes, social norms, and perceived behavioral control can explain sustained shifts in travel modes. The methodology involved surveying residents in three Portland neighborhoods where SmartTrips was implemented: Southwest (2008), Northeast (2006), and Southeast (2007). For the Southwest area, a panel of residents was surveyed before the program and again one to two years after its conclusion. For the Northeast and Southeast areas, follow-up surveys were conducted one to two years post-intervention. The surveys collected data on daily trip modes, recent use of alternative transportation, and psychological factors including attitudes, norms, and perceived control. The analysis compared pre- and post-survey data to assess behavioral persistence and utilized TPB models to quantify the influence of psychological variables on travel choices. The findings indicate that the benefits of individualized marketing can extend beyond one year, lasting up to at least two years. In the Northeast and Southeast target areas, the share of trips made driving alone remained significantly lower, while walking and bicycling remained significantly higher compared to pre-survey levels, comparable to immediate post-program results. In the Southwest area, there was a significant drop in weekday drive-alone trips, though this may have been partially influenced by rising gas prices. TPB models effectively explained 45–55% of the variance in travel behavior. Attitudes and perceived behavioral control were strong predictors, with attitudes heavily influencing bicycling and perceived control impacting walking. Social norms had a comparatively minor influence. The study also noted that programs were less effective in environments less conducive to active transportation, suggesting that physical infrastructure plays a critical role in perceived behavioral control. The significance of this research lies in its validation of long-term behavior change through individualized marketing and its demonstration of the utility of psychological frameworks in transportation planning. The results suggest that TDM programs are most effective when they target attitudes and perceived behavioral control rather than relying solely on social norms. Furthermore, the findings imply that marketing efforts should be tailored to regional characteristics and specific travel modes, and that their efficacy is enhanced when combined with investments in walkable, bikeable, and transit-friendly infrastructure. This study provides a framework for optimizing future TDM strategies by integrating psychological insights with physical planning.

Key finding

Attitudes, social norms, and perceived behavioral control explain 45-55% of the variance in travel behavior, and SmartTrips benefits persisted for at least two years in some neighborhoods.

Methodology

survey

Sample size: 288

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).

Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• acceptance adoption

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Applied Guidance: countermeasure evaluation
• Empirical Findings: observational prevalence