Transit Market Research Using Attitudinal Market Segmentation, Structural Equation Modeling and Mode Choice Modeling Yoram Shiftan, The Technion Maren.

Slides:



Advertisements
Similar presentations
Introduction to Transportation Systems. PARTIII: TRAVELER TRANSPORTATION.
Advertisements

Salt Lake City Downtown Transportation Master Plan Light Rail & Bus; Presentation Background and Introduction August 23, 2006.
West Michigan Transit Linkages Study Wednesday, June 4 th, :00 a.m. Grand Valley State University Kirkhof Center Conference Room 2266.
ANYBODY CAN RIDE! Examples of successful rural transit programs and practices elsewhere in the United States.
Travel Survey Components Attitudes and Personalities October 31, 2006.
On-board Survey of Bus and Light Rail Customers May 8, 2006 Transit Marketing, LLC CJI Research Corporation.
Transportation leadership you can trust. presented to Regional Transportation Plan Guidelines Work Group Meeting presented by Christopher Wornum Cambridge.
Measuring and capturing mind share APTA 2013 Marketing & Communications Workshop.
October 4-5, 2010 TCRP H-37: Characteristics of Premium Transit Services that Affect Choice of Mode Prepared for: AMPO Modeling Subcommittee Prepared by:
Demand for bus and Rail Analyzing a corridor with a similar Level Of Service 5 th Israeli-British/Irish Workshop in Regional Science April, 2007.
GREATER NEW YORK A GREENER Travel Demand Modeling for analysis of Congestion Mitigation policies October 24, 2007.
The Current State and Future of the Regional Multi-Modal Travel Demand Forecasting Model.
Presented to presented by Cambridge Systematics, Inc. Transportation leadership you can trust. Comparison of Activity-Based Model Parameters Between Two.
FOCUS MODEL OVERVIEW CLASS THREE Denver Regional Council of Governments July 7, 2011.
Time of day choice models The “weakest link” in our current methods(?) Change the use of network models… Run static assignments for more periods of the.
Presentation to the AMP Leadership Team Moving forward. April 17, 2013.
Lec 3, Ch. 2 Transp Systems & Organization Understand the nation’s transportation system is the result of independent actions (through reading) Understand.
CEE 320 Fall 2008 Mode Choice Survey Results. CEE 320 Fall 2008 Which variables do you think matter? What is your age? How far from campus do you live?
Modelling Service Quality for Public Transport Contracts: Assessing Users’ Perceptions Gabriela Beirão José Sarsfield Cabral 9th Conference on Competition.
Commuting in America Using the ACS to Develop a National Report on Commuting Patterns and Trends Penelope Weinberger, CTPP Program Manager, AASHTO ACS.
May 2009 Evaluation of Time-of- Day Fare Changes for Washington State Ferries Prepared for: TRB Transportation Planning Applications Conference.
1 Using Transit Market Analysis Tools to Evaluate Transit Service Improvements for a Regional Transportation Plan TRB Transportation Applications May 20,
Business Logistics 420 Public Transportation Lectures 8: The Performance and Condition of Transit in the United States.
Transportation Operations/Mobility in the Baltimore Region Customer Satisfaction Survey AMPO Operations Work Group September 28-29, 2006 Las Vegas.
Census Transportation Planning Products (CTPP) Data Products June 18, 2010.
COMMUTING IN AMERICA 2013 ALAN E. PISARSKI PRESERVING THE AMERICAN DREAM Oct 2013.
FOCUS MODEL OVERVIEW CLASS FIVE Denver Regional Council of Governments July27, 2011.
11 May, 2011 Discrete Choice Models and Behavioral Response to Congestion Pricing Strategies Prepared for: The TRB National Transportation Planning Applications.
Auckland’s Travel Demand Initiatives Sustainable Mobility & Healthy Communities Summit 2014.
How Much is Too Much? America’s Addiction to Gasoline and Its Impact on the Workforce June 10, 2008.
Accessibility David Levinson. Why Do Cities Form? Why does the Twin Cities exist? Why are the Twin Cities larger than Duluth or Fargo? Why is Chicago.
The Commute Trip Reduction (CTR) Law.  The CTR Law requires major employers - in Urban Growth Areas throughout Washington - to implement an employee.
Transit Estimation and Mode Split CE 451/551 Source: NHI course on Travel Demand Forecasting (152054A) Session 7.
1 Washington Metropolitan Area Transit Authority Customer Satisfaction Measurement FY 2006 Q3 Comparison April 28, 2006.
Orange County Business Council Infrastructure Committee December 14, 2010 Draft Long-Range Transportation Plan Destination 2035.
January Utah Statewide Household Travel Study Study overview and results.
A New Policy Sensitive Travel Demand Model for Tel Aviv Yoram Shiftan Transportation Research Institute Faculty of Civil and Environmental Engineering.
Transportation leadership you can trust. presented to TRB Planning Applications Conference presented by Vamsee Modugula Cambridge Systematics, Inc. May.
TRANSPORTATION AND TRANSITION Oregon Youth Transition Conference February 19, 2015 Hood River, Oregon.
Materials developed by K. Watkins, J. LaMondia and C. Brakewood Service Planning & Standards Unit 4: Service Planning & Network Design.
Greater Toronto & Hamilton Area School Travel Household Attitudinal Study.
PainsGains Lack of transport Long waiting times Lack of safety Anger & frustration Less waiting times Convenient travelling Ensure more safety Travel.
MOVING TOWARD AN ELDER FRIENDLY MOBILITY FUTURE May 19, 2009 Presented by Marla Turner, Associate State Director AARP Texas.
MIAMI UNIVERSITY BUS SYSTEM IMPROVEMENT PLAN. What’s the problem? ●A current Miami student pays $66 per semester for transit fees that goes towards the.
GNTP Business Forum – The Big Idea – Gary Smerdon-White 18 th September 2012.
VMT Reduction Programs: Time for a Change? Stacey Bricka, PhD, NuStats 12 th TRB Planning Applications Conference Products of Your.
David B. Roden, Senior Consulting Manager Analysis of Transportation Projects in Northern Virginia TRB Transportation Planning Applications Conference.
Cal y Mayor y Asociados, S.C. Atizapan – El Rosario Light Rail Transit Demand Study October th International EMME/2 UGM.
Active Transportation in Action Individualized Marketing.
VALUES WORKSHOP Anne Arundel County | April 26, 2010.
Morgan County Transit Discussion UTA Corporate Staff Presentation November 19, 2013.
Peak Travel in America: Where Are We Going? 12 th Conference on Transportation Planning Applications Houston 2009 Nancy McGuckin, Travel Behavior Analyst.
Journey to Work from 1990 Census and ACS National test (C2SS) Elaine Murakami, USDOT, FHWA Nanda Srinivasan, Cambridge Systematics Inc.
Transportation leadership you can trust. presented to 12th TRB National Transportation Planning Applications Conference presented by Arun Kuppam, Cambridge.
GCAA Feb 17, Results 1.2 million miles of travel 600 tons of air pollution Each day these efforts reduce: Currently partnering with more than 1650.
TPB CLRP Aspirations Scenario 2012 CLRP and Version 2.3 Travel Forecasting Model Update Initial Results Ron Kirby Department of Transportation Planning.
Baseline Scenario Quality Growth Strategy.
FOCUS MODEL OVERVIEW CLASS FOUR Denver Regional Council of Governments July 7, 2011.
Client Name Here - In Title Master Slide 2007/2008 Household Travel Survey Presentation of Findings on Weekday Travel Robert E. Griffiths Technical Services.
Impact of Aging Population on Regional Travel Patterns: The San Diego Experience 14th TRB National Transportation Planning Applications Conference, Columbus.
December 17, 2010 Developing Transit Performance Measures for Integrated Multi-Modal Corridor Management.
Shaping our Future Transportation Transportation trends Influencing trends through land use decisions Alternative futures: Base Case and Scenario Complementary.
Walk Statistics.  The question has been asked: “Is Lomas a better BRT corridor than Central?”  The purpose of this analysis is to compare the two corridors.
RideWise Travel Training
Transportation and transition
Transportation Engineering Mode Choice January 21, 2011
Measuring and capturing mind share
Transit Competitiveness and Market Potential
Lorain County Transit Needs Assessment
Mass Transit Usage According to IBISWorld, the public transportation industry increased 14.3%, from $63 billion during 2013 to $72 billion for 2017,
Presentation transcript:

Transit Market Research Using Attitudinal Market Segmentation, Structural Equation Modeling and Mode Choice Modeling Yoram Shiftan, The Technion Maren Outwater, Cambridge Systematics YuShuang Zhou, Cambridge Systematics 5th Israeli-British/Irish Workshop in Regional Science Ramat Gan, April 2007 2 3 1 3

Building a Competitive Strategy What kinds of strategies can best seize these opportunities? Strategies Which segments in which travel markets should transit services compete for? Competitive Positioning What will be the likely funding and cooperation? Resources What are the market segments and where are they located? Market Segments What are the key attitudes and preferences that drive traveler choices? Travel Behavior

From Market Research to Service Planning Locate Market Segments Competitive Positioning Customer Experience System Performance Network Structure Understand Travel Markets Service Planning Transit Priority Personal Safety Seating Comfort Segment Market

Market Research Analysis Flow Chart Attitude-Based Survey Stated-Preference Survey (WTA) Exploratory Factor Analysis Confirmatory Factor Analysis Structural Equation Modeling Market Segmentation Mode Choice (WTA) Market Segmentation Application

Attitude-Based Survey Results (UTA) 10 9 8 UTA - 38 Statements WTA - 30 Statements 7 Score 6 5 4 3 Attitudinal Statements 1. Driving is the fastest way 9.0 1. Avoid traveling at stressful time 5.1 2. Public transportation help the environment 8.5 2. Need to make trips to various locations 5.1 3. Clean vehicle is important 8.4 3. Don't mind transfers 4.9 4. Like to keep to my schedule when travel 8.0 4. Avoid some areas that are unsafe 4.8 5. Prefer travel options with predicted time 7.8 5. Prefer driving to be alone 4.7 TOP TEN BOTTOM TEN 6. It is imptant to have comfortable seats 7.7 6. Travel mostly during peak time 4.4 7. Like to know the cause of delay 7.6 7. Worry about getting into an accident 4.1 8, Driving should pay more to help Envirenment 8. Feel safe near home or destianton 7.5 4.1 9. Important to change travel plans at a moment 7.5 9. Use Public transportation if it was cheaper 4.0 10. Feel savfe using PT 7.3 10. I am usually anxious when travel 3.1

Confirmatory Factor Analysis (UTA) Desire to Help the Environment Desire for Productivity and Reliability Sensitivity to Time Sensitivity to Safety and Privacy Need for Fixed Schedule Sensitivity to Stress and Comfort Willingness to Use Transit

Desire to Help the Environment I would be willing to pay more when I travel if it would help improve air quality People who drive alone should pay more to help improve air quality (.89) I would switch to a different form of transportation if it would reduce air pollution (.86) Use of public transportation can help improve air quality (.28)

Desire for Productivity and Reliability I would like to make productive use of my time when I travel I would much rather do something else with the time that I spend traveling (.82%) I prefer a travel option that has predictable travel time from day to day (.73%) If my travel option is delayed, I want to know the cause and length of the delay (.68%) When traveling, I like to keep as close as possible to my departure and arrival schedules (.68%)

Sensitivity to Time I am usually in a hurry when I make a trip I would change my form of travel if it would save me some time (.93%) I use the fastest form of transportation regardless of cost (.85) Driving is usually the fastest way to get where I need to go (.52)

Sensitivity to Safety and Privacy I do mind traveling with strangers I do not feel safe using public transportation (.85) Having my privacy is important to me when I travel (.61) I prefer driving because I like to be alone while I travel (.56) I do not feel safe walking both near my home and near my destination (.55) I avoid traveling through certain areas because they are unsafe (.51) When traveling, I do not like to talk and visit with other people (.26) I worry about getting in an accident when I travel (.21)

Need for Fixed Schedule I need to travel mostly during rush hour times I need to make trips according to a fixed schedule (89%)

Sensitivity to Stress and Comfort Having a stress-free trip is more important than reaching my destination quickly I avoid traveling at certain times because it is too stressful (73%) I don’t mind delays as long as I am comfortable (64%) It is important to have comfortable seats when I travel (26%) A clean vehicle is important to me (18%)

Willingness to Use Transit I wouldn’t mind walking a few minutes to get to and from a bus or a TRAX stop I would ride transit if services were available to my destination when I need to travel (88%) If I rode public transportation I wouldn’t mind changing between buses or between bus and TRAX (78%) I know how to reach my destination using public transportation (64%) I would use public transportation more often if it was cheaper to ride (36%)

Attitude Factors (the WTA case) Need for Flexibility Sensitivity to Personal Travel Experience Desire to Help the Environment Need for Time Savings Insensitivity to Transport Costs Sensitivity to Stress

Structural Equation Modeling (UTA) Attitudinal Statements (Endogenous) Attitudinal Factors (Latent) Socioeconomic Status (Exogenous) Environment. Productivity & Reliabiity Sensitivity to Time Privacy & Safety Fixed Schedule Stress & Comfort Willingness to Use transit V1 EV1 EQ1 Q1 Q2 V2 EV2 EQ2 EQ3 Q3 V3 EV3 EQ37 Q37 V27 EV37 EQ38 Q38 V28 EV38 Travel Behaviors

Goals of Market Segmentation to produce distinct groups (i.e., segments) with maximized difference between groups and minimized difference within each group Between Segments The differences among segments are maximized Within Each Segments The differences within each segment are minimized

Market Segmentation (UTA) Sensitivity to Time Low Sensitivity of Time High Sensitivity of Time All Travelers Flexible Schedule Fixed Need for Fixed Schedule No Transit Transit Willingness to Use Transit Anxious Amblers None of These Factors Transit Green Riders Fixed Schedule Productive 9 to 5-ers Fixed Schedule and Transit Routine Riders Time Cautious Flyers Time and Transit Green Flyers Time and Fixed Schedule Cautious 9 to 5-ers Time, Fixed Schedule and Transit Routine Flyers Market Segments Attitudinal Focus

Cautious Flyers Low desire to improve air quality Lowest willingness to use transit High desire for productivity, high sensitivity to safety and privacy, and low sensitivity to stress and comfort. Flexible schedule, yet high sensitivity to time. The majority of this segment is young married female with kids, most of them are in one-worker and two-vehicle household. More than 75% of this segment are homemakers and students. Only 35% of the population in this segment need to travel more than 0.5 mile to work, nobody uses transit as the primary mode for either work or other trips.

Green Riders High desire to improve air quality Segment with highest willingness to use transit Low desire for productivity and reliability, low sensitivity to time, and very flexible schedule. Least sensitive segment to safety and privacy, but highly sensitive to stress and comfort. High share of retired population (50%) and of students (5%) All households own vehicles, most of them own one. 25% of this segment needs to travel more than 0.5 mile to work/school, 6% use transit as the primary mode for work/school trips, and 15% use transit for non-work trips

Number of Workers in the Household 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Anxious Amblers Green Riders Productive 9 to 5-ers Routine Riders Cautious Flyers Green Flyers Cautious 9 to 5-ers Routine Flyers 1 2 >=3

People Who Travel More Than ½ Mile For Work and School Trips Percent 91% 90% 90 87% 85% 75 60 44% 45 35% 30 26% 15 13% 11% 9% 7% 6% 6% 0% 0.0% 1% Anxious Amblers Green Riders Productive 9 to 5-ers Routine Riders Cautious Flyers Green Flyers Cautious 9 to 5-ers Routine Flyers Share using public transit for work/school trips

Market Segmentation Competitive Positioning Tougher Markets Toughest Markets High Desire for Safety and Privacy and Comfort Relatively Low-Hanging Fruit Tough but Possible Low Low High Value of Time

Market Segments 30 25 20 15 10 5 Routine Flyers 33% Anxious Amblers 5 10 15 20 25 30 Anxious Amblers 21% Cautious 9 to 5-ers 20% Percent Routine Riders 9% Green Riders 7% Productive 9 to 5-ers 4% Cautious Flyers 4% Green Flyers 2%

Geogarphic Details of Market Segments One of two PUMA in Salt Lake County Geogarphic Details of Market Segments Block Groups Census Tracts

Market Segmentation (WTA) All Trans-Bay Trippers Factor One Modest Environmental Strong Environmental Factor Two Less Time Savings More Time Factor Four Less Stressed More Less Stressed Joe Six-Pack None of These Factors Market Segment Focus Anxious Ambler Stress Calm Charger Time Frazzled Flyer Time and Stress Environment Green Cruiser Reserved Recycler Environment and Stress Relaxed Runabout Environment and Time Tense Trekker Environment, Time, and Stress

WTA Mode Choice Model Constants Modes HBW HBO/Shop HBRec Carpool Auto -0.21 -0.33 -1.44** BART Transit 1.86** 1.32* 2.17** Other rail 0.59 0.64 1.51 Bus 0.96* -0.11 1.27 Ferry 0.018 0.24 -0.65 Drive access -1.68** 0.015 Transit access/egress -068** -0.29 -0.55* LOS Total cost Rail/bus -0.0038** -0.0027** -0.0063** -0.0032** -0.0013 -0.0026* -0.0013** -0.0007** -0.0015** In vehicle time -0.037** -0.025** -0.046** -0.023** -0.016** -0.039** -0.024** -0.017** -0.029** Walk time -0.030** -0.028** Walk access/egress time -0.060 -0.048** -0.062** Drive access time -0.108** -0.069** -0.061** Out of vehicle time -0.043** -0.039 -0.025 Total travel time Time sensitive MS -0.0078** -0.0094** -0.0056

WTA Mode Choice Model - Continue Socioeconomic Modes HBW HBO/Shop HBRec Household income Drive alone 4.4E-6* -9.2E-7 -6.9E-6** Rail/bus drive access 7.1E-6** 7.1E-6* -1.7** Ferry drive access 1.5E-5** -2.1E-6 -1.2E-5** Rail/bus transit access -2.1E-7 -5.3E-7 -2.4E-5** Ferry walk/tran access 7.4E-6 1.2E-5** -1.5E-5** Vehicle per household 0.136* 0.419** 0.070 Rail/bus walk/tran accss -o.604** -0.346* 0.018 Ferry walk/transit access -0.496** -0.128 -0.083 0.026 0.306** 0.100 -0.281** 0.416** -0.263 Additional Constants Market Segments Auto modes Stress-related MS -0.0031 1.067** 0.574** Ferry modes 0.125 0.757** -- Carpool transit ferry Pro-environment MS 0.720** Summary statistics Final log likelihood -1754.50 -1115.58 -780.32 Rho-Square wrt zero 0.328 0.393 0.458 Rho-Square wrt cons. 0.119 0.093 0.111 Auto VOT $17.07 $21.34 $18.47 Bus/Rail VOT $3.65 $3.49 $3.70 Ferry VOT $4.60 $8.14 $6.82

Conlusions To increase transit market share we need to understand the market place according to the key attitudes potential customers most value. Structural Equation Modeling is a powerful tool to improve our understanding of travel behavior and to improve transit services. This approach can significantly increase out ability to answer important questions for better transit planning such as: What attitudes and preferences drive each market segment’s choice for local travel options? What strategies would be most effective for each market segment? What are the “easy-to-reach” (and “hard to reach”) markets? What strategies are most likely to be effective in different locations?

For Example Market segments with a high value of time and a high need for safety and privacy (such as Cautious 9 to 5-ers in the UTA study) are more difficult to serve with fixed-route transit systems. Market segments with a low value of time and low need to privacy (such as Green Riders in the UTA Study) are more likely served by models improvements to existing transit services.

Thank you for your attention!

Anxious Amblers Low desire to help the environment Low willingness to use transit Low desire for productivity and reliability Low sensitivity to time and flexible schedule High sensitivity to safety and privacy Most sensitive segment to stress and comfort High concentration of old retire female population Low to middle income level (up to $100,000) Only 7% of this segment needs to travel more than 0.5 mile to work, and nobody uses transit as the primary mode for work trips. Only 4% use transit for non-work trips.

Green Flyers Highest desire to help the environment, and high willingness to use transit. High sensitivity to time, but low desire for productivity and reliability, flexible schedule, low sensitivity to safety and privacy, and low sensitivity to stress and comfort. Most of the people in this segment are young and middle aged, employed, and from a one worker household. More than half of this segment have an income below $50,000. Only 44% of this segment need to travel more than 0.5 mile to work/school, 11% of them use transit as primary mode for commute, and 22% uses transit for non-work trips.

Mode Share for Work/School Trips