The value of travel time savings and the value of leisure in Zurich: Estimation, decomposition and policy implications

Abstract We use state-of-the art estimation approaches to obtain mode-specific values of travel time savings (VTTS) based on pooled RP/SP travel choice data of Zurich workers. Unlike the large majority of time valuation studies, we also have data on the respondents’ time-use and expenditure allocation, which enables us to estimate their value of leisure (VoL),i.e. the opportunity value of liberated time when the duration of a committed activity, such as travel, is reduced. We use the estimates of the VoL and the VTTS to derive the value of time assigned to travel (VTAT) – the monetary value of the direct (dis-)utility derived from the conditions experienced while traveling. Linking the VTTS and VoL at the individual-level allows for a detailed analysis of VTAT distributions. We obtain median VTTS for car and motorbike (MIV) of 30.6 CHF/h, carpooling (CP) of 27.7 CHF/h, carsharing (CS) of 26.7 CHF/h, walk of 26.7 CHF/h, bike of 18.2 CHF/h and public transportation (PT) of 14.8 CHF/h. The median VoL amounts to 25.2 CHF/h. We find that MIV, CS and CP perform worst in terms of VTAT (as indicated by values smaller than zero), showing that the perceived travel comfort all in car modes (private, shared and pooled) is substantially lower than for PT and bike, where the VTAT are greater than zero. From a transportation policy perspective, our results suggest that travel comfort matters greatly and investing in the quality of travel should therefore obtain more attention. However, from a PT operator’s point of view, our results indicate that in the case of Zurich, investing in faster connections may exhibit a higher marginal impact on user benefits, since the VoL is relatively high, while travel comfort is perceived as high already.

[1]  Kay W. Axhausen,et al.  Advanced continuous-discrete model for joint time-use expenditure and mode choice estimation , 2018 .

[2]  T. Fowkes,et al.  New appraisal values of travel time saving and reliability in Great Britain , 2019 .

[3]  Silvania Avelar Visualizing public transport networks: an experiment in Zurich , 2008 .

[4]  C. A. Guevara,et al.  BEHIND THE SUBJECTIVE VALUE OF TRAVEL TIME SAVINGS: THE PERCEPTION OF WORK, LEISURE AND TRAVEL. , 2001 .

[5]  K. Axhausen,et al.  A joint time-assignment and expenditure-allocation model: value of leisure and value of time assigned to travel for specific population segments , 2019, Transportation.

[6]  J. Shires,et al.  An international meta-analysis of values of travel time savings. , 2009, Evaluation and program planning.

[7]  M. Bierlaire,et al.  ESTIMATION OF VALUE OF TRAVEL-TIME SAVINGS USING MIXED LOGIT MODELS , 2005 .

[8]  S. Shapiro,et al.  An Approximate Analysis of Variance Test for Normality , 1972 .

[9]  Kenneth Train,et al.  Customer-Specific Taste Parameters and Mixed Logit: Households' Choice of Electricity Supplier , 2000 .

[10]  Mark Wardman,et al.  Meta-analysis of UK values of travel time: An update , 2011 .

[11]  Andrew Daly,et al.  Assuring finite moments for willingness to pay in random coefficient models , 2009 .

[12]  Andrew Daly,et al.  Dummy coding vs effects coding for categorical variables: Clarifications and extensions , 2016 .

[13]  M. Wardman,et al.  The digital revolution and worthwhile use of travel time: implications for appraisal and forecasting , 2016 .

[14]  Takayuki Morikawa,et al.  Theoretical analysis on the variation of value of travel time savings , 2004 .

[15]  P. Koster,et al.  Commuters' Preferences for Fast and Reliable Travel: A Semi-Parametric Estimation Approach , 2015 .

[16]  Claude Weis,et al.  Ermittlung von Bewertungsansätzen für Reisezeiten und Zuverlässigkeit auf der Basis eines Modells für modale Verlagerungen im nicht-gewerblichen und gewerblichen Personenverkehr für die Bundesverkehrswegeplanung: FE-Projekt-Nr. 96.996/2011 , 2014 .

[17]  J. Pucher,et al.  Verkehrsverbund: The evolution and spread of fully integrated regional public transport in Germany, Austria, and Switzerland , 2019 .

[18]  Marco Kouwenhoven,et al.  Value of travel time as a function of comfort , 2018, Journal of Choice Modelling.

[19]  Juan de Dios Ortúzar,et al.  Willingness-to-Pay Estimation with Mixed Logit Models: Some New Evidence , 2005 .

[20]  Sergio R. Jara-Díaz,et al.  Beyond transport time: A review of time use modeling , 2017 .

[21]  Paulina Greeven,et al.  Econometric Calibration of the Joint Time Assignment-Mode Choice Model , 2008, Transp. Sci..

[22]  Maria Börjesson,et al.  Experiences from the Swedish Value of Time study , 2011 .

[23]  Kay W. Axhausen Ermittlung von Bewertungsansätzen für Reisezeiten und Zuverlässigkeit auf Basis der Schätzung eines Modells für modale Verlagerungen im nicht-gewerblichen und gewerblichen Personenverkehr für die Bundesverkehrswegeplanung , 2014 .

[24]  J. Drèze,et al.  Specification and estimation of Cobb-Douglas production function models , 1966 .

[25]  Stefan Flügel Accounting for user type and mode effects on the value of travel time savings in project appraisal: Opportunities and challenges , 2014 .

[26]  Sergio R. Jara-Díaz,et al.  Consumer's surplus and the value of travel time savings , 1990 .

[27]  Sergio R. Jara-Díaz,et al.  Transport Economic Theory , 2007 .

[28]  David A. Hensher,et al.  The sensitivity of the valuation of travel time savings to the specification of unobserved effects , 2001 .

[29]  Paul Koster,et al.  Long‐Run Versus Short‐Run Perspectives on Consumer Scheduling: Evidence from a Revealed‐Preference Experiment Among Peak‐Hour Road Commuters , 2015 .

[30]  Chandra R. Bhat,et al.  A multiple discrete–continuous extreme value model: formulation and application to discretionary time-use decisions , 2005 .

[31]  Alejandro Tirachini,et al.  Valuation of sitting and standing in metro trains using revealed preferences , 2016 .

[32]  W. Wien,et al.  Object-oriented Computation of Sandwich Estimators , 2006 .

[33]  Kay W. Axhausen,et al.  Modeling car-sharing membership as a mobility tool: A multivariate Probit approach with latent variables , 2017 .

[34]  K. Axhausen,et al.  Post-Car World: data collection methods and response behavior in a multi-stage travel survey , 2019, Transportation.

[35]  C. Angelo Guevara,et al.  Critical assessment of five methods to correct for endogeneity in discrete-choice models , 2015 .

[36]  Stéphanie Vincent Lyk-Jensen,et al.  Between-mode-differences in the value of travel time: Self-selection or strategic behaviour? , 2010 .

[37]  Achim Zeileis Object-oriented Computation of Sandwich Estimators , 2006 .

[38]  K. Axhausen,et al.  Surveying and analysing mode and route choices in Switzerland 2010–2015 , 2020, Travel Behaviour and Society.

[39]  D. Hensher,et al.  Productivity foregone and leisure time corrections of the value of business travel time savings for land passenger transport in Australia , 2016 .

[40]  Stephane Hess,et al.  On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice , 2006 .

[41]  D. McFadden The Choice Theory Approach to Market Research , 1986 .

[42]  Kay W. Axhausen,et al.  The Multi-Agent Transport Simulation , 2016 .

[43]  Florian Heiss,et al.  Discrete Choice Methods with Simulation , 2016 .

[44]  Kenneth Train,et al.  Discrete Choice Models in Preference Space and Willingness-to Pay Space , 2005 .

[45]  Oded Cats,et al.  Does conducting activities while traveling reduce the value of time? Evidence from a within-subjects choice experiment , 2020 .

[46]  Patricia L. Mokhtarian,et al.  How attractive is it to use the internet while commuting? A work-attitude-based segmentation of Northern California commuters , 2020 .

[47]  Mark Wardman,et al.  Values of Travel Time Savings UK , 2003 .

[48]  Stephane Hess,et al.  Correlation and scale in mixed logit models , 2017 .

[49]  Felix Becker,et al.  mixl: An open-source R package for estimating complex choice models on large datasets , 2021, Journal of Choice Modelling.

[50]  Yhf Cheung,et al.  VALUE OF DUTCH TRAVEL TIME SAVINGS IN 1997 , 1999 .

[51]  J. Ortúzar,et al.  Valuing crowding in public transport: Implications for cost-benefit analysis , 2016 .

[52]  S. Jara-Díaz,et al.  Time use: The role of sleep , 2020, Transportation Research Part A: Policy and Practice.

[53]  Kay W. Axhausen,et al.  mixl: An open-source R package for estimating complex choice models on large datasets , 2021, Journal of Choice Modelling.

[54]  Regine Gerike,et al.  Time use, mobility and expenditure: an innovative survey design for understanding individuals’ trade-off processes , 2019, Transportation.

[55]  Alexandre Mas,et al.  Labor Supply and the Value of Non-Work Time: Experimental Estimates from the Field , 2017, American Economic Review: Insights.

[56]  H. Gunn,et al.  SPATIAL AND TEMPORAL TRANSFERABILITY OF RELATIONSHIPS BETWEEN TRAVEL DEMAND, TRIP COST AND TRAVEL TIME , 2001 .

[57]  S. Jara-Díaz,et al.  The role of gender, age and location in the values of work behind time use patterns in Santiago, Chile , 2011 .

[58]  Feng Zhen,et al.  How do passengers use travel time? A case study of Shanghai–Nanjing high speed rail , 2018 .

[59]  C. Bhat The multiple discrete-continuous extreme value (MDCEV) model : Role of utility function parameters, identification considerations, and model extensions , 2008 .

[60]  E. Verhoef,et al.  Long-Run vs. Short-Run Perspectives on Consumer Scheduling: Evidence from a Revealed-Preference Experiment Among Peak-Hour Road Commuters , 2011 .

[61]  A. Reggiani,et al.  Meta-Analysis and the Value of Travel Time Savings: A Transatlantic Perspective in Passenger Transport , 2007 .

[62]  Sergio R. Jara-Díaz,et al.  Transport and time use: The values of leisure, work and travel , 2020 .

[63]  Kay W. Axhausen,et al.  Implications of survey methods on travel and non-travel activities: A comparison of the Austrian national travel survey and an innovative mobility-activity-expenditure diary (MAED) , 2018 .

[64]  P. Mokhtarian,et al.  TTB or not TTB, that is the question: a review and analysis of the empirical literature on travel time (and money) budgets , 2004 .

[65]  Sergio R. Jara-Díaz,et al.  INTRODUCING THE EXPENDITURE RATE IN THE ESTIMATION OF MODE CHOICE MODELS , 1989 .

[66]  Paul Koster,et al.  Commuters' Preferences for Fast and Reliable Travel: A Semi-Parametric Estimation Approach , 2015 .

[67]  Basil Schmid,et al.  Connecting Time-Use, Travel and Shopping Behavior: Results of a Multi-Stage Household Survey , 2019 .

[68]  Vincent A. C. van den Berg,et al.  New values of time and reliability in passenger transport in The Netherlands , 2014 .

[69]  P. Mackie,et al.  THE VALUE OF TRAVEL TIME SAVINGS IN EVALUATION , 2001 .

[70]  Mark Wardman,et al.  Values of travel time in Europe: Review and meta-analysis , 2016 .

[71]  K. Train,et al.  A Control Function Approach to Endogeneity in Consumer Choice Models , 2010 .

[72]  Sergio R. Jara-Díaz,et al.  Estimating the value of leisure from a time allocation model , 2008 .

[73]  E. Cherchi,et al.  Accounting for inertia in modal choices: some new evidence using a RP/SP dataset , 2011 .

[74]  K. Axhausen,et al.  A pooled RP/SP mode, route and destination choice model to investigate mode and user-type effects in the value of travel time savings , 2019, Transportation Research Part A: Policy and Practice.

[75]  A. Deserpa A Theory of the Economics of Time , 1971 .

[76]  Sergio R. Jara-Díaz,et al.  Understanding time use: Daily or weekly data? , 2015 .