Technology Adoption by Small Urban and Rural Transit Agencies

In this paper, findings from a national survey on technology use by agencies providing transit service to rural areas are presented. The survey collected data on agency use of information and communications technologies, transit-specific technology, as well as characteristics of its manager. The survey targeted organizations that receive Section 5311 funds, a federal grant program, to provide transit service to non-urbanized areas, but that do not provide intercity bus service exclusively. Survey data were joined with financial and operating statistics contained in the recently available Rural National Transit Database (Rural NTD) to allow for further analysis. An econometric analysis to investigate the impact of community, agency, and manager attributes on technology adoption was conducted using discrete choice modeling techniques. The analysis included modeling the individual adoption of four technologies: Automatic Vehicle Location (AVL), Computer-Aided Scheduling and Dispatch software (CASD), Geographic Information Systems (GIS), and Mobile Data Terminals (MDTs) using binary logit techniques. The joint adoption of technology, specifically CASD software in combination with AVL, GIS, or MDTs, was modeled using a multinomial logit framework. Agency size measured by fleet size, budget, and trips delivered are significant factors that impact the adoption of technology by rural transit agencies. Manager education and experience, attendance at national conferences, interaction with technology vendors, and participating in technology training were also found to be significant. Results of the survey and analysis have practical implications for policy and practice. They support participation of agency managers in national conferences and technology-focused training. The results can also be used to determine which agencies might benefit from technology based on community, agency, and manager attributes. Conversely, agencies that do use technology, but are not expected to based on their characteristics, can be identified to determine if and how they benefit from the technologies they use.

• Record URL:
  https://www.ugpti.org/resources/reports/details.php?id=649
• 
• Corporate Authors:

  Upper Great Plains Transportation Institute

  Small Urban and Rural Transit Center, North Dakota State University, P.O. Box 6050
  Fargo, ND  United States  58108-6050

  Federal Transit Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Ripplinger, David
  • Brand-Sargent, Bethany
• Publication Date: 2010-6

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 83p

Subject/Index Terms

• TRT Terms: Automatic vehicle location; Bus transit operations; Econometric models; Geographic information systems; Logits; Rural areas; Scheduling; Small cities; Transit operating agencies
• Uncontrolled Terms: Computer aided dispatch systems; Mobile data terminals
• Subject Areas: Data and Information Technology; Public Transportation; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01173877
• Record Type: Publication
• Files: TRIS, USDOT
• Created Date: Sep 28 2010 2:37PM