Does the social context help with understanding and predicting the choice of activity type and duration? An application of the Multiple Discrete-Continuous Nested Extreme Value model to activity diary data

An understanding of activity choices and duration is a key requirement for better policy making, in transport and beyond. Previous studies have failed to make the important link with individuals’ social context. In this paper, the Multiple Discrete-Continuous Nested Extreme Value (MDCNEV) model is applied to the choice of activity type and duration over the course of two days, using data from the Chilean city of Concepcion. In common with other studies, heterogeneity across decision makers is accommodated in the model by analysing the impact of different socio-demographic, mobility and residential location variables on both the activity choice and the time allocation decision. In addition, different social network and social capital measures are found to be significantly correlated with the choice and duration of different activities, and we show how these relationships seem to differ from the effects of socio-demographic variables. Finally, we perform a forecasting exercise using the MDCNEV model, highlighting the differences in substitution patterns from a standard MDCEV model.

[1]  Daniel McFadden,et al.  Computing Willingness-to-Pay in Random Utility Models , 1996 .

[2]  Kay W. Axhausen,et al.  Social Networks and Travel Behaviour , 2015 .

[3]  K. Axhausen,et al.  Activity‐based approaches to travel analysis: conceptual frameworks, models, and research problems , 1992 .

[4]  Eric J. Miller,et al.  The social dimension in action : A multilevel, personal networks model of social activity frequency between individuals , 2009 .

[5]  Khandker Nurul Habib,et al.  Social Context of Activity Scheduling , 2008 .

[6]  Chandra R. Bhat,et al.  Joint Model for Perfect and Imperfect Substitute Goods Case: Application to Activity Time-Use Decisions , 2006 .

[7]  K. Train.  Qualitative Choice Analysis: Theory, Econometrics, and an Application to Automobile Demand , 1985 .

[8]  D. Ettema,et al.  Modelling the joint choice of activity timing and duration , 2007 .

[9]  Chandra R. Bhat,et al.  Comprehensive Model of Worker Nonwork-Activity Time Use and Timing Behavior , 2009 .

[10]  Chandra R. Bhat,et al.  A household-level activity pattern generation model with an application for Southern California , 2013 .

[11]  Chandra R. Bhat,et al.  A Multiple Discrete-Continuous Nested Extreme Value (MDCNEV) Model: Formulation and Application to Non-worker Activity Time-Use and Timing Behavior on Weekdays , 2010 .

[12]  Susan Pike,et al.  Travel Mode Choice and Social and Spatial Reference Groups , 2014 .

[13]  Mike Wright,et al.  Qualitative Choice Analysis-Theory, Econometrics and an Application to Automobile Demand , 1987 .

[14]  Matthias Kowald,et al.  Modelling contact mode and frequency of interactions with social network members using the multiple discrete–continuous extreme value model , 2017 .

[15]  J. Tobin.  Estimation of Relationships for Limited Dependent Variables , 1958 .

[16]  Hjp Harry Timmermans,et al.  Modeling Departure Time Choice in the Context of Activity Scheduling Behavior , 2003 .

[17]  C. Bhat,et al.  An Efficient Forecasting Procedure for Kuhn-Tucker Consumer Demand Model Systems , 2010 .

[18]  Alejandro Tudela,et al.  Exploring the links between personal networks, time use, and the spatial distribution of social contacts , 2013 .

[19]  J. Heckman.  Sample Selection Bias as a Specification Error (with an Application to the Estimation of Labor Supply Functions) , 1977 .

[20]  Phyllis Moen,et al.  2. Time Clocks: Work-Hour Strategies , 2019 .

[21]  Chandra R. Bhat,et al.  An empirical investigation into the time-use and activity patterns of dual-earner couples with and without young children , 2015 .

[22]  V. Sivaraman,et al.  Discrete-Continuous Choice Model with Multiple Budget Constraints, Imperfect and Perfect Substitutes, and Price Variation: Application to Household Vacation Travel Behavior , 2013 .

[23]  Chandra Bhat,et al.  Modeling the Commute Activity-Travel Pattern of Workers: Formulation and Empirical Analysis , 2001, Transp. Sci..

[24]  C. Bhat,et al.  Modeling Adults' Weekend Day-Time Use by Activity Purpose and Accompaniment Arrangement , 2007 .

[25]  Sascha Hoogendoorn-Lanser,et al.  On Good Neighbors and Distant Friends in the Online Era , 2016 .

[26]  Ta Theo Arentze,et al.  A Latent Class Accelerated Hazard Model of Social Activity Duration , 2011 .

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

[28]  Leah Ruppanner,et al.  Fairness and Housework: A Cross-National Comparison* , 2008 .

[29]  Chandra R. Bhat.  A New Generalized Gumbel Copula for Multivariate Distributions , 2009 .

[30]  Chandra R. Bhat,et al.  Accommodating Multiple Constraints in the Multiple-Discrete Continuous Extreme Value (MDCEV) Choice Model , 2012 .

[31]  Ryan Peseckas,et al.  Collecting Social Network Data from Mobile Phone SIM Cards , 2016 .

[32]  C. Bhat,et al.  Household Vehicle Type Holdings and Usage: An Application of the Multiple Discrete-Continuous Extreme Value (MDCEV) Model , 2006 .

[33]  K. Axhausen,et al.  Collecting data on leisure travel: The link between leisure contacts and social interactions , 2010 .

[34]  Tommy Gärling,et al.  Computer Simulation of Household Activity Scheduling , 1998 .

[35]  Florencia Torche,et al.  Unequal But Fluid: Social Mobility in Chile in Comparative Perspective , 2005 .

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

[37]  Bob Blakley,et al.  Conceptual Model , 2017, Encyclopedia of GIS.

[38]  Claudia Mora,et al.  The meaning of womanhood in the neoliberal age: Class and age-based narratives of chilean Women , 2006 .

[39]  K. Axhausen,et al.  A CONCEPTUAL MODEL OF THE WEEKLY HOUSEHOLD ACTIVITY/TRAVEL SCHEDULING PROCESS. IN: TRAVEL BEHAVIOUR: SPATIAL PATTERNS, CONGESTION AND MODELLING , 2002 .

[40]  G. Jong.  An indirect utility model of car ownership and private car use , 1990 .

[41]  Kay W. Axhausen,et al.  Distance patterns of personal networks in four countries: a comparative study , 2013 .

[42]  Eric J Miller,et al.  Collecting Social Network Data to Study Social Activity-Travel Behavior: An Egocentric Approach , 2008 .

[43]  Jeffrey A. Dubin,et al.  An Econometric Analysis of Residential Electric Appliance Holdings and Consumption , 1984 .

[44]  K. Campbell,et al.  Name generators in surveys of personal networks , 1991 .

[45]  Geneviève Bouchard,et al.  Why Do Women Do the Lion’s Share of Housework? A Decade of Research , 2010 .