INTERSHOPPING DURATION: AN ANALYSIS USING MULTIWEEK DATA

This study examines the rhythms in the shopping activity participation of individuals over a multiweek period by modeling the duration between successive shopping participations. A hazard-based duration model is used to model intershopping duration, and a latent segmentation method is applied to distinguish between erratic shoppers and regular shoppers. The paper applies the methodology to examine the regularity and frequency of shopping behavior of individuals using a continuous six-week travel survey collected in the cities of Halle and Karlsruhe in Germany in the fall of 1999. The empirical results underscore the need to adopt a flexible hazard model form for analyzing intershopping durations. The results also provide important insights into the determinants of the regularity and frequency of individuals' shopping activity participation behavior.

[1]  David A. Hensher,et al.  Handbook of Transport Modelling , 2000 .

[2]  Byung-Do Kim,et al.  Studying patterns of consumer's grocery shopping trip , 1997 .

[3]  Chandra R. Bhat,et al.  A comprehensive daily activity-travel generation model system for workers , 2000 .

[4]  Ram M. Pendyala,et al.  Time use and activity perspectives in travel behavior research , 2002 .

[5]  S Gregory Hatcher,et al.  DAILY VARIABILITY OF ROUTE AND TRIP SCHEDULING DECISIONS FOR THE EVENING COMMUTE , 1992 .

[6]  N. Kiefer.  Economic Duration Data and Hazard Functions , 1988 .

[7]  Laurence L. George,et al.  The Statistical Analysis of Failure Time Data , 2003, Technometrics.

[8]  C. Bhat.  An analysis of evening commute stop-making behavior using repeated choice observations from a multi-day survey , 1999 .

[9]  J. O. Huff,et al.  Classification issues in the analysis of complex travel behavior , 1986 .

[10]  Chandra R. Bhat,et al.  An Endogenous Segmentation Mode Choice Model with an Application to Intercity Travel , 1997, Transp. Sci..

[11]  J. Hausman,et al.  Flexible parametric estimation of duration and competing risk models , 1990 .

[12]  F. Koppelman,et al.  Activity-Based Modeling of Travel Demand , 2003 .

[13]  Tony Lancaster,et al.  Generalised residuals and heterogeneous duration models: With applications to the Weilbull model , 1985 .

[14]  M. Clarke,et al.  The significance and measurement of variability in travel behaviour , 1988 .

[15]  Frank S. Koppelman,et al.  ESTIMATION OF DISAGGREGATE REGRESSION MODELS OF PERSON TRIP GENERATION WITH MULTIDAY DATA , 1984 .

[16]  J. Kalbfleisch,et al.  The Statistical Analysis of Failure Time Data , 1980 .

[17]  S. Hanson,et al.  Systematic variability in repetitious travel , 1988 .

[18]  J. Heckman,et al.  A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data , 1984 .

[19]  Randolph W. Hall,et al.  Handbook of transportation science , 1999 .

[20]  Ta Theo Arentze,et al.  Experiences with developing ALBATROSS: a learning-based transportation oriented simulation system , 1998 .

[21]  C. Bhat,et al.  Activity-Travel Patterns of Nonworkers in the San Francisco Bay Area: Exploratory Analysis , 2000 .

[22]  Chandra R. Bhat,et al.  Incorporating Observed and Unobserved Heterogeneity in Urban Work Travel Mode Choice Modeling , 2000, Transp. Sci..

[23]  Satoshi Fujii,et al.  TWO COMPUTATIONAL PROCESS MODELS OF ACTIVITY-TRAVEL BEHAVIOR1 , 1997 .

[24]  T. Garling.  Theoretical Foundations of Travel Choice Modeling , 1998 .

[25]  K. Axhausen,et al.  Observing the rhythms of daily life , 2000 .

[26]  Fred L. Mannering,et al.  HAZARD-BASED DURATION MODELS AND THEIR APPLICATION TO TRANSPORT ANALYSIS. , 1994 .

[27]  R. Schlich,et al.  Analysing intrapersonal variability of travel behaviour using the sequence alignment method , 2001 .

[28]  Hani S. Mahmassani,et al.  DYNAMICS OF COMMUTER BEHAVIOUR: RECENT RESEARCH AND CONTINUING CHALLENGES , 1997 .

[29]  Kay W. Axhausen,et al.  Within household allocation of travel - the case of upper Austria: paper submitted for presentaion at the 80th Annual Meeting of the Transportation Research Board, Washington, D.C., January 2001 , 2002 .

[30]  Chandra R. Bhat,et al.  A hazard-based duration model of shopping activity with nonparametric baseline specification and nonparametric control for unobserved heterogeneity , 1996 .

[31]  Bruce D. Meyer.  Unemployment Insurance and Unemployment Spells , 1988 .

[32]  Frank S. Koppelman,et al.  Integrated Model System of Stop Generation and Tour Formation for Analysis of Activity and Travel Patterns , 1999 .

[33]  E. I. Pas.  Weekly travel-activity behavior , 1988 .

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

[35]  Harry Timmermans,et al.  Albatross version 2: A learning-Based Transportation Oriented Simulation System , 2005 .

[36]  E. I. Pas,et al.  Intrapersonal variability in daily urban travel behavior: Some additional evidence , 1995 .

[37]  Frank S. Koppelman,et al.  An examination of the determinants of day-to-day variability in individuals' urban travel behavior , 1986 .

[38]  Kay W. Axhausen,et al.  Day on day dependencies in travel: first results using ARIMA modelling , 2001 .

[39]  Peter Jones,et al.  Developments in dynamic and activity-based approaches to travel analysis , 1990 .

[40]  Eric I. Pas,et al.  A Flexible and Integrated Methodology for Analytical Classification of Daily Travel-Activity Behavior , 1983 .

[41]  Naufel J. Vilcassim,et al.  Investigating Household Purchase Timing Decisions: A Conditional Hazard Function Approach , 1991 .