1. Peter Vovsha, Parsons Brinckerhoff, New York, NY, USA Gaurav Vyas, Parsons Brinckerhoff, New York, NY, USA Danny Givon, Jerusalem Transportation Masterplan Team (JTMT), Jerusalem, Israel Yehoshua Birotker, Jerusalem Transportation Masterplan Team (JTMT), Jerusalem, Israel USUAL WORK ARRANGEMENTS: STATISTICAL ANALYSIS AND MODEL IMPLEMENTATION FOR JERUSALEM 1 TRB Application Conference, May 2013

2.  Commuting to work:  Main traffic component in peak periods  Cornerstone of travel demand modeling  Traditional view on commuters:  Full-time worker  Commuting every regular workday  Commuting in peak hours AM / PM  Inflexible schedule dictated by employer  New tendencies:  Growing number of alternative flexible arrangements  New phenomena like telecommuting Motivation 2 TRB Application Conference, May 2013

3.  Alternative work arrangements affect:  Commuting patterns and frequency  Sensitivity to congestion pricing and other policies  Correspond to policy levers:  Compressed work weeks  Peak spreading for work hours  Incorporation in travel models:  Explicit (sub-model) or implicit (DAP, work trip rates)?  Assumptions for future (fixed or trends?) Implications for Modeling 3 TRB Application Conference, May 2013

4. ArrangementNormalAlternative Job typeFull timePart-time Number of jobs12+ Usual workplace location Out of home - permanent At home Out of home - variable Commuting frequency 5 days a week1-4 days a week (compressed) 6-7 days a week (extended) Telecommuting frequency Low (less than once a week) High (once a week or greater) Schedule flexibilityNo / littleYes / significant Usual scheduleAM / PMSecond shift, other Taxonomy of Usual Work Arrangements 4

5. Population Sector # Households Full-time workers Part-time workers Secular 4,887 5,251 1,277 Ultra Orthodox 2,119 1,162 558 Arab 1,224 1,528 198 Total 8,230 7,941 2,033 Jerusalem Household Travel Survey, 2010 5 TRB Application Conference, May 2013

6. Job Type Full-time Part-time Number of Jobs 1 2+ Empl. Type Hired Self Employed Work Place Home Permanent Work Place Varied Work Location 24 Alternatives If home is not the work place Usual Work Location Model Commuting Frequency and Flexibility Person and Household Characteristics; Occupation Main Work Arrangement (lifestyle)

7. Commuting Frequency and Flexibility 7 Number of Days Working 1/ 7 7/ 7 4/ 7 2/ 7 3/ 7 5/ 7 6/ 7 Telecommuting Frequency (8 categories) Schedule Flexibility: 1) No, 2) Some, 3) High, 4) No schedule Usual Schedule (5 categories) TRB Application Conference, May 2013

8. Usual Schedule Categories TRB Application Conference, May 2013 8 Usual Arrival Time to work Usual Departure Time from work Before NoonNoon-2 PM2 PM-4PM 4 PM - 6 PM 6 PM - 8 PM 8 PM - 10 PM 10 PM - 12 PM After Midnight Before 6 AM113315849181143 6 AM - 8 AM24142670872247391223 8 AM - 10 AM194728811,1825571191832 10 AM - Noon0214339652781 Noon - 2 PM0172514 63 2 PM - 4 PM00151527325 4 PM - 6 PM0003818147 After 6 PM0000211926 Conventional Schedule Early Departure Normal Departure and late arrival Over Workers (early arrival and late departure) Second shift workers

9.  Main Work Arrangement:  2 for Job types  2 for number of jobs  2 for Employment types  3 for Work location  Utility function:  4 parameterized terms by main dimensions:  Job types  Number of jobs  Employment types  Work location  Interaction terms (2-way constants) Choice Model 1 9 TRB Application Conference, May 2013

10.  Work Location  40 TAZs are sampled from the pool of all TAZs  Size variables include inter-sector friction variables  Sampling is based on the employment characteristics and impedance between origin and destination TAZ Choice Model 2 10 TRB Application Conference, May 2013

11.  Commuting Frequency and Flexibility:  7 for number of days working  'n+1' alternatives for telecommuting frequency for ‘n’ number of days at work  4 for schedule flexibility  5 for usual work schedule  Utility function:  4 parameterized terms by main dimensions:  Number of days at work  Telecommuting frequency  Schedule flexibility  Usual work schedule  Interaction terms (2-way constants) Choice Model 3 11 TRB Application Conference, May 2013

12. VariablesPart-time2+ jobsSelf- employed Home as work place Variable work place Age>65 yearsMore Less Young ArabMore Arab MaleLess MoreLess Arab FemaleMoreLess Higher Education MoreLessMoreLess Clerical workerMoreLessMore Less Manufacturing, construction worker Less MoreLessMore Non- professional MoreLess MoreLess Behavioral Insights – Main Work Arrangements TRB Application Conference, May 2013 12

13. Behavioral Insights- Main Work Arrangements TRB Application Conference, May 2013 13 Interaction2+JobsSelf- employed Home as work place Variable work place Part-timePositive Self employed Positive Variable Work place Positive VariablesPart-time2+ jobsSelf- employed Home as work place Variable work place Low IncomeMoreLessMore Female and presence of children MoreLessMore Less Only worker and household size>1 More for Arab Sector More

14. Behavioral Insights – Work Location TRB Application Conference, May 2013 14

15. Behavioral Insights – Work Location (Unique Feature) TRB Application Conference, May 2013 15 Inter-Sector (Social) Friction Residential Sector/Area Employment Sector/Area ArabOrthodoxSecular Arab High OrthodoxVery High SecularVery HighHigh

16. VariablesNumber of days at work Telecommuting frequency Schedule Flexibility Usual Schedule/ duration Part-time workerLess than 5LessMoreLess conventional Self-employedLess than 5More Less duration Multiple jobsMore than 5More Less conventional Variable work place Less than or equal to 5 More More conventional Academic professional More than 5More More conventional Orthodox-femaleLess than 5Less Less conventional Age>65 yearsLess than 5More Less duration Higher EducationLess than 5More More conventional Behavioral Insights – Commuting Frequency Model 16

17. VariablesNumber of days at work Telecommuting frequency Schedule Flexibility Usual Schedule/ work duration Female and presence of children More likely equal to 5 LessLess duration Low IncomeMore likely equal to 5 LessLess duration Female and low income More Behavioral Insights – Commuting Frequency Model 17 InteractionNo-scheduleSome FlexibilityHigh Flexibility TelecommutingPositive Non- conventional schedule Negative

18. Placement in Jerusalem CT-RAMP ABM 18 Population Synthesis Main Long-term Work Arrangements Long-term Location Choices Usual Commuting Freq. & Flexibility Household & Person Mobility Attributes Daily Activity-Travel Pattern Type & Time Allocation Tour Formation Location of Non-Work Act. Tour & Trip Details Traffic &Transit Network Simulations 1 2 3 4 5 TRB Application Conference, May 2013

19.  Evolution of usual work arrangements:  Communication technology revolution (work from home, telecommuting)  Structural shifts in industry & occupation (flexible work hours, self employment)  Consequence of growing congestion (compress work weeks)  Choice Models:  Statistically estimated for base year  Adjustments for future years:  Scenarios and trends (for example, growing telecommuting)  Policy tests (for example, shifted usual work hours) Forecasting 19 TRB Application Conference, May 2013

20.  Understanding principal changes in commuting patterns:  Growing share of alternative work arrangements  Incorporation in travel models:  Policy lever / scenario management  Policy implications of alternative work arranges:  Beneficial for reduction of commuting volumes in peak periods  Demand elasticity to congestion pricing  Impact on total VMT remains unclear Conclusions and Perspectives 20 TRB Application Conference, May 2013