SMART operational field test evaluation : public support for bus transit in tri-county area of southeastern Michigan : final report
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SMART operational field test evaluation : public support for bus transit in tri-county area of southeastern Michigan : final report

Filetype[PDF-331.81 KB]


English
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  • Creators:
  • Corporate Creators:
    University of Michigan
  • Subject/TRT Terms:
  • Resource Type:
    Tech Report
  • Geographical Coverage:
    Michigan
  • Corporate Publisher:
    University of Michigan
  • NTL Classification:
    NTL-PUBLIC TRANSPORTATION-Paratransit;NTL-PUBLIC TRANSPORTATION-Advanced Public Transit Systems;NTL-INTELLIGENT TRANSPORTATION SYSTEMS-Transit Management;
  • Abstract:
    Despite ever-decreasing public transit rider-ship in the U.S., public transit continues to enjoy moderate to high amounts of public support, meaning that the public continues to support public expenditures on transit. Indeed, since the 1970s some transit agencies have succeeded in passing dedicated tax millages in support oftransit service. In the spring of 1995, the Suburban Mobility Authority for Regional Transportation (SMART), which provides public transit in the greater Detroit region, became one such agency. Why voters, most of whom do not use public transit, continue to offer political support for transit remains an open question. On November 5, 1996, the authors conducted an exit poll of voters in the SMART region to assess overall levels of support for the SMART millage renewal and to test several hypotheses regarding why voters continue to support public transit. In this study, four alternative hypotheses are tested. These include: (1) voters support transit because they use it, (2) voters support transit so that others will use it and thereby reduce traffic congestion, (3) voters support transit because they view transit as a needed social service, and (4) voters offer greater support for transit as the quality of the service increases. To examine the accuracy of each hypothesis, numerous predictions that derive from each hypothesis were tested using statistical models (logistic regression) built from the voter survey data and census data.
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