Trip chaining of bicycle and car commuters: an empirical analysis of detours to secondary activities
暂无分享,去创建一个
[1] Michael Duncan,et al. How much can trip chaining reduce VMT? A simplified method , 2016 .
[2] Michael G. McNally,et al. On the Structure of Weekly Activity/Travel Patterns , 2003 .
[3] Winnie Daamen,et al. Trip chain complexity: a comparison among latent classes of daily mobility patterns , 2020 .
[4] Jon Wakefield,et al. Bayesian and Frequentist Regression Methods , 2013 .
[5] Arnold van der Valk. Town Planning in the Netherlands Since 1800: Responses to Enlightenment Ideas and Geopolitical Realities , 2015 .
[6] Y. Susilo,et al. The influence of built environment to the trends in commuting journeys in the Netherlands , 2007 .
[7] Khandker Nurul Habib,et al. Unraveling the relationship between trip chaining and mode choice: evidence from a multi-week travel diary , 2012 .
[8] R. Schoot,et al. Bayesian analyses : where to start and what to report , 2014 .
[9] Jonah Gabry,et al. R-squared for Bayesian Regression Models , 2019, The American Statistician.
[10] F. Witlox,et al. Commuting trips within tours: how is commuting related to land use? , 2011 .
[11] M. Kroesen. To what extent do e-bikes substitute travel by other modes? Evidence from the Netherlands , 2017 .
[12] Abolfazl Mohammadian,et al. The validity of using activity type to structure tour-based scheduling models , 2007 .
[13] Maria Börjesson,et al. The value of time and external benefits in bicycle appraisal , 2012 .
[14] Corinne Mulley,et al. Multiple purposes at single destination: a key to a better understanding of the relationship between tour complexity and mode choice , 2013 .
[15] Stephan Brunow,et al. The impact of activity chaining on the duration of daily activities , 2013 .
[16] Ben Pelzer,et al. Weighted Effect Coding for Observational Data with wec , 2017, R J..
[17] N. Gale,et al. Exploring the anchor-point hypothesis of spatial cognition , 1987 .
[18] Harry Timmermans,et al. Capturing tour mode and activity choice interdependencies: A co-evolutionary logit modelling approach , 2007 .
[19] Ryuichi Kitamura,et al. Time-space constraints and the formation of trip chains , 1987 .
[20] S. Hoogendoorn,et al. Latent classes of daily mobility patterns: the relationship with attitudes towards modes , 2020, Transportation.
[21] Ben Pelzer,et al. A novel method for modelling interaction between categorical variables , 2016, International Journal of Public Health.
[22] Sascha Hoogendoorn-Lanser,et al. The Netherlands Mobility Panel: an innovative design approach for web-based longitudinal travel data collection , 2015 .
[23] Torsten Hägerstraand. WHAT ABOUT PEOPLE IN REGIONAL SCIENCE , 1970 .
[24] Michael A. P. Taylor,et al. Defining and understanding trip chaining behaviour , 2007 .
[25] Ben Pelzer,et al. When size matters: advantages of weighted effect coding in observational studies , 2016, International Journal of Public Health.
[26] Steve Melia. Filtered and unfiltered permeability: The European and Anglo-Saxon approaches , 2012 .
[27] M. Legrand,et al. Major 20th century changes of the content and chemical speciation of organic carbon archived in Alpine ice cores: Implications for the long‐term change of organic aerosol over Europe , 2013 .
[28] Sean T. Doherty. Should we abandon activity type analysis? Redefining activities by their salient attributes , 2006 .
[29] Peter R. Stopher,et al. Travel time budgets: new evidence from multi-year, multi-day data , 2016, Transportation.
[30] Hussain Alkharusi,et al. Categorical Variables in Regression Analysis: A Comparison of Dummy and Effect Coding , 2012 .
[31] Ming Lee,et al. An empirical investigation on the dynamic processes of activity scheduling and trip chaining , 2004 .
[32] M. Dijst,et al. Travel-time ratios for visits to the workplace: the relationship between commuting time and work duration , 2002 .
[33] P. Nijkamp,et al. The attraction force of out‐of‐town shopping malls: a case study on run‐fun shopping in the Netherlands , 2003 .
[34] Danilo Bzdok,et al. Points of Significance: Statistics versus machine learning , 2018, Nature Methods.
[35] M. Dijst,et al. Travel time ratio: the key factor of spatial reach , 2000 .