From Automobiles to Alternatives: Applying Attitude Theory and Information Technologies to Increase Shuttle Use at Rocky Mountain National Park

Abstract

This thesis examines potential strategies for increasing voluntary shuttle use at Rocky Mountain National Park (ROMO) and the gateway community of Estes Park, Colorado. The first chapter of this two-part study evaluates the impact of a pilot intelligent transportation system (ITS) on visitor awareness and use of shuttles during the summer of 2011. Two forms of ITS, dynamic message signs (DMS) and highway advisory radio (HAR), were evaluated. Specifically, the ITS was meant to influence day-visitors to park at a new park-and-ride lot just east of Estes Park where they could then board a connector shuttle and transfer to any of four shuttle routes servicing the town and park. Surveys were administered onboard the park-and-ride shuttle (N = 68) and at two locations in downtown Estes Park (N = 490). Our analysis revealed that the DMS contributed to increased awareness of the shuttles. However, the HAR did not contribute substantially to awareness or use of the visitor shuttles. Our analysis offers additional recommendations for increasing voluntary shuttle use, such as providing direct routes between the park-and-ride and popular park attractions. The results of this study demonstrate the utility of ITS as a transportation management tool in a national park setting, but also highlight the importance of selecting appropriate technologies that meet the needs of park visitors. The second chapter explores strategies for optimizing the use of ITS by applying the theory of planned behavior (Ajzen, 1991) to identify the beliefs that inform choice of travel mode among ROMO and Estes Park visitors. Using results of a mail survey (N = 222), the theory of planned behavior was applied to the prediction of intention and use of visitor shuttles. Perceived behavioral control was found to have a significant influence on intention to use shuttles. Past experience with park shuttles was tested as an additional predictor of behavior and shown to significantly improve the prediction of shuttle use. Past experience with public transit was also added to the model, but with no significant contribution, thereby demonstrating the inherent difference between travel behaviors in everyday settings as opposed to recreation settings. These results were then coupled with segmentation analysis to identify unique segments of visitors. The segments were statistically similar in terms of demographic characteristics, yet heterogeneous in their attitudes, subjective norms, and perceived control regarding shuttle use. Of the three segments identified, Bus Backers were found to hold the most positive beliefs about shuttles and Potential Mode-shifters were identified as the segment offering the most potential for mode change due to their neutral attitudes and beliefs. Strategies were identified to maintain and improve use of shuttles among these segments. Our study broadens the application of segmentation analysis to transportation in a park setting and demonstrates its important contribution

    Similar works