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WILLINGNESS TO PAY FOR TRAVEL INFORMATION

WILLINGNESS TO PAY FOR TRAVEL INFORMATION. Asad J. Khattak* Youngbin Yim^ Linda Stalker* *Department of City & Regional Plng. Univ. of North Carolina, Chapel Hill ^California PATH Program University of California at Berkeley. Importance. Incident & recurrent congestion

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WILLINGNESS TO PAY FOR TRAVEL INFORMATION

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  1. WILLINGNESS TO PAY FOR TRAVEL INFORMATION Asad J. Khattak* Youngbin Yim^ Linda Stalker* *Department of City & Regional Plng. Univ. of North Carolina, Chapel Hill ^California PATH Program University of California at Berkeley

  2. Importance • Incident & recurrent congestion • Data collection, processing & dissemination • Are people willing to pay for high quality info? • Public versus private resources • Field Operational Tests & deployment: TravInfo • Traveler Advisory Telephone System

  3. Literature Real-time travel info in large US cities: • Electronic information increases shifting • Information valuable in uncertain travel conditions • Info content, quality and medium • Travelers willing to pay in certain “high benefit” situations • TravInfo, SmartTraveler, Travlink

  4. Gaps In existing studies: • Factors that influence willingness-to-pay for travel info? • What kind of info will users pay for? • Is there demand for transit info? • What can we learn from FOT/implementations in larger cities?

  5. The Survey • CATI: April 1997 of TATS callers • Sample = 511 (quota for traffic & transit calls; gender) • Sample comparisons showed differences--non-generalizable • Information seekers • Focus on trip called (TATS) about: • Different purposes • Skip patterns

  6. Survey Questions Reported & Stated preferences • RP: Last month, how frequently did you call TATS? • SP scenarios: About how many times will you call TATS if per-call charge was 25 cents, 50 cents, 1 dollar? • Give per call or monthly fee preference Other variables: • Travel decisions, socio-economic and context factors

  7. Methodology Random-effects negbin reg. • Dependent variable is • RP: Calling frequency (1) • SP: Calling frequency (6) • Indep. Vars: Per-call fee, individual, household, travel characteristics • Potential biases: • Strategic bias--lose free service • Non-commitment bias--overstate W-T-P • Cognitive dissonance--unable to assess free service’s worth

  8. Methodology - Model Estimated model accounts for: • Serial correlation • Over-dispersion • Heterogeneity (when mean variance ratio grows with higher means) • Does not yield marginal effects Skip patterns: • Missing data problem • Indicator variables

  9. Selected Results

  10. Selected Results

  11. Conclusions • Response reasonable: Higher cost implies less use • Controlling for various factors & combining RP with SP • Information seekers willing to pay • Demand for personalized information • Other info sources complementary • Potential for transit improvement

  12. Policy Implications Commercialization of travel info: • There is demand for TATS • Added benefits of personalization imp. to customers • Advertise TATS on comm. radio • TATS usage may grow (SmartTraveler) • In other areas: • Develop free-of-charge service • Gradually introduce charges: Longer commute routes & improvement potential

  13. Directions for Further Research • Content of information • New media: Internet, PDA • Integration of info • Behavioral change • Network performance

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