A new concept of accessibility to personal activities: development of theory and application to an empirical study of mobility resource holdings

Abstract The notion of spatio-temporal accessibility to [potential] out-of-home activities is central to transport geography. This paper extends existing theory by proposing a new concept of accessibility, termed the ‘perceived activity set’ (PAS). A person’s PAS is defined as the set of out-of-home activities which they view as encompassing their potential travel needs when making decisions that structurally affect their accessibility. In other words, it is proposed that a person’s mobility-linked choices such as, for instance, where to live or whether to own a car, are a function of how such choices affect their ability to access out-of-home activities they consider relevant. This paper first formalises the PAS and places it in the wider context of accessibility theory. It then presents an empirical study that makes use of the PAS concept, which analyses people’s ownership of several mobility resources that each enable particular forms of travel. The PAS appears promising, as it unlocks a class of flexible techniques that relax restrictive assumptions regarding the drivers behind structural choices related to personal mobility. The techniques were found to be analytically tractable, and the empirical analysis based on the PAS yielded a number of insights. The advantages of using long-duration diaries with PAS-based techniques, rather than more-common one-day diaries, are shown to be large. It was found that the more ‘substantial’ a mobility resource is (in terms of expense and commitment) the better the PAS concept is at explaining patterns of ownership. The paper concludes with suggested directions for research to further develop the PAS concept, which include refinements to the quantitative techniques, extension to other structural mobility choices, and qualitative research into the nature of the relationship between people’s perceived needs for mobility and their expected activity patterns over longer periods than are observed by most activity and travel surveys.

[1]  Kay W. Axhausen,et al.  A Dynamic Understanding of Travel Demand: A Sketch , 2005 .

[2]  Kay W. Axhausen,et al.  Household Mobility Tool Ownership: Modeling Interactions between Cars and Season Tickets , 2006 .

[3]  Torsten Hägerstraand WHAT ABOUT PEOPLE IN REGIONAL SCIENCE , 1970 .

[4]  Harry L. Margulis,et al.  Predicting the Growth and Filtering of At-risk Housing: Structure Ageing, Poverty and Redlining , 1998 .

[5]  H. B. Mann,et al.  On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other , 1947 .

[6]  Tijs Neutens,et al.  My space or your space? Towards a measure of joint accessibility , 2008, Comput. Environ. Urban Syst..

[7]  J. Urry Mobility and Proximity , 2002 .

[8]  F. E. Horton,et al.  Effects of Urban Spatial Structure on Individual Behavior , 1971 .

[9]  H. S. Booker,et al.  Demand for automobiles in the United States , 1957 .

[10]  M. Roorda,et al.  An integrated model of vehicle transactions, activity scheduling and mode choice , 2009 .

[11]  Taha Hossein Rashidi,et al.  A dynamic hazard-based system of equations of vehicle ownership with endogenous long-term decision factors incorporating group decision making , 2011 .

[12]  Scott Le Vine,et al.  Strategies for personal mobility: A study of consumer acceptance of subscription drive-it-yourself car services , 2011 .

[13]  Toshiyuki Yamamoto,et al.  On the formulation of time-space prisms to model constraints on personal activity-travel engagement , 2002 .

[14]  Moshe Ben-Akiva,et al.  Integration of an Activity-based Model System and a Residential Location Model , 1998 .

[15]  P. Vovsha,et al.  Model for Person and Household Mobility Attributes , 2009 .

[16]  J C Tanner CAR OWNERSHIP TRENDS AND FORECASTS , 1977 .

[17]  M. Mogridge The prediction of car ownership and use revisited: the beginning of the end? , 1989 .

[18]  K. Axhausen,et al.  Models of Mode Choice and Mobility Tool Ownership beyond 2008 Fuel Prices , 2010 .

[19]  Kay W. Axhausen,et al.  Estimation of Carsharing Demand Using an Activity-Based Microsimulation Approach: Model Discussion and Some Results , 2013 .

[20]  Harvey J. Miller,et al.  Measuring Space‐Time Accessibility Benefits within Transportation Networks: Basic Theory and Computational Procedures , 1999 .

[21]  D. Dissanayake,et al.  Investigating household vehicle ownership, mode choice and trip sharing decisions using a combined revealed preference/stated preference Nested Logit model: case study in Bangkok Metropolitan Region , 2010 .

[22]  Stefan Schönfelder,et al.  Structure and innovation of human activity spaces , 2004 .

[23]  Mark D. Uncles,et al.  Discrete Choice Analysis: Theory and Application to Travel Demand , 1987 .

[24]  M. Ben-Ariva,et al.  METHODOLOGY FOR SHORT-RANGE TRAVEL DEMAND PREDICTIONS. ANALYSIS OF CARPOOLING INCENTIVES , 1977 .

[25]  John Eliasson,et al.  A model for integrated analysis of household location and travel choices , 2000 .

[26]  D. P. McElroy Integrating Transit Pass Ownership into Mode Choice Modelling , 2009 .

[27]  Chandra R. Bhat,et al.  Modeling the Choice Continuum: Integrated Model of Residential Location, Automobile Ownership, Bicycle Ownership, and Commute Tour Mode Choice Decisions , 2008 .

[28]  K. Axhausen,et al.  Structures of commitment in mode use: a comparison of Switzerland, Germany and Great Britain , 2001 .

[29]  M. Kwan Space-time and integral measures of individual accessibility: a comparative analysis using a point-based framework , 2010 .

[30]  Moshe Ben-Akiva,et al.  Moving from trip-based to activity-based measures of accessibility , 2006 .

[31]  Martin Dijst,et al.  ICTs and Accessibility: An Action Space Perspective on the Impact of New Information and Communication Technologies , 2004 .

[32]  Biao Huang,et al.  The Use of Pseudo Panel Data for Forecasting Car Ownership , 2007 .

[33]  Julian Hine,et al.  Participation index : a measure to identify rural transport disadvantage? , 2011 .

[34]  Andrew Daly,et al.  Audit of Car Ownership Models , 2002 .

[35]  Aruna Sivakumar,et al.  Design of a Strategic-Tactical Stated-Choice Survey Methodology Using a Constructed Avatar , 2011 .

[36]  S. Handy,et al.  Factors associated with bicycle ownership and use: a study of six small U.S. cities , 2010 .

[37]  D. Salon,et al.  Cars and the City: An Investigation of Transportation and Residential Location Choices in New York City , 2006 .

[38]  Colin G. Pooley,et al.  Household decision-making for everyday travel: a case study of walking and cycling in Lancaster (UK) , 2011 .

[39]  K. Train A Structured Logit Model of Auto Ownership and Mode Choice , 1980 .