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An Exploration of the Characteristics of Excess Travel Within Commuting

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An Exploration of the Characteristics of Excess Travel Within Commuting An exploration of the characteristics of excess travel within commuting By: Anna Fraszczyk A thesis submitted for the degree of Doctor of Philosophy School of Civil Engineering and Geosciences Newcastle University The United Kingdom May 2014 Abstract Travel behaviour research aims to inform and provide evidence for sound transport policy. Excess travel, where individuals demonstrate excessive use of for example time or distance, challenges assumptions underpinning fundamental beliefs of travel behaviour research where travel should be minimised in order to get to the destination. This thesis explores the phenomenon of excess travel and the characteristics of people exhibiting excess travel within a commuting context, using Tyne and Wear as a case study. Building on existing definitions of excess commuting, which include time and distance, this study gradually adds additional parameters of cost, effort, and many other parameters (e.g. value of time, weights for walking and waiting) in the generalised cost formula, and the final sample is analysed to identify similarities and differences between excess commuters (EC) and not excess commuters (NEC). The methodology uses a GIS technique for sampling and a questionnaire approach for data collection. The final sample includes origin-based (home) commuters who completed a questionnaire delivered to their home addresses, and destination-based (work) commuters who completed an online version of the same questionnaire. Analytical methods are used to identify EC and NEC based on self-reported (‘pure’) values of the four key parameters of time, cost, distance and effort while commuting and using a generalised cost approach. For the parameters of time and cost as well as for the generalised cost results seven saving options are considered, where 5% savings is the lowest option and 50% or more savings is the highest option. An analysis of various attributes and their differences in medians together with a series of socio-economic characteristics are used to distinguish between EC and NEC within the four groups in total (time, cost, effort, generalised cost). The results show that within the collected sample EC make up between 32% (in the cost group) and 78% (in the effort group) of the total sample (depending on the parameter/group considered), and that there are some statistically significant differences at the 95% level between EC and NEC within the groups. The fact that the number of EC varies between the groups is to be expected, as the literature review suggested that taking different parameters into account produces different results. Generally, EC seem to behave in a similar manner to the rest of the sample, in terms of most of the factors tested, when making choices about commuting, but for example 41% of the respondents i drive to work and within this driving group there are more EC than NEC (for example 44% of EC versus 37% of NEC within the time group or 52% of EC versus 36% of NEC within the cost group). More importantly, the median values for the four key parameters of travel to work (actual commute time, ideal one-way commute time, commute cost, commute distance) are higher in majority of the cases for EC than for NEC within the four groups. Attitudes and preferences also play a role, demonstrating that the most frequent trip purpose, the commute, can provide some benefit to travellers. The results also show that in terms of the activities such as listening to music/radio, reading book/newspapers, exercising or concentrating on the road a majority of statistically significant differences between EC and NEC occur within the cost and the effort groups only. The demand for more direct routes and cheaper fares on public transport is emphasised by the majority of the sample. The respondents tend to be well informed about their travel to work alternative transport modes and different transport planning tools available, and the Internet stands out as a primary source of information employed by majority of both EC and NEC. In exploring the characteristics of EC and NEC in more depth, recommendations are identified for public transport providers to improve their services and encourage more commuters to transfer travel time into activity time. ii Acknowledgement When I started my PhD I was introduced to the motto: “It is about the journey, not the destination”. My journey took me nearly 8 years (part-time) and it has been a wonderful, most challenging, hated and loved period in my life. I have spent a quarter of my life on the excess commuting research project and still feel I do not know much about the topic. But at least I know enough to earn a PhD title. Yes, it is about the journey, but I am extremely happy and grateful that I managed to reach the desired destination. Finally! I would like to thank a number of people who helped me with this journey and who contributed to the final success of this PhD project. Thanks to my supervisors Dr Stuart Barr and Dr Neil Thorpe for their constructive criticism, advice and precious time spent on reading and commenting on my endless chapters. Thanks to Professor Corinne Mulley, my former supervisor, for her faith (in me) and time (for me) – You are a true inspiration for your students! Thanks to my examiners: Professor Glenn Lyons for his thoughtful comments and Professor Margaret Bell for her positive attitude and attention to detail. Thanks to my family and friends for helping me to reach my dream. Special thanks to: my parents Danuta and Jerzy for their great support, my brother Marcin for being my BIG brother, my beloved grandma Kazia for her enormous love and sacrifice, and to Amelia for being a patient and good kid. Also, great thanks to a small group of my very close friends who offered me their time and support during this PhD journey: Ewa and Mario for their love and various (including listening) skills; Lena for her child-friendly attitude; Danka for her friendship and for “2B”; Kasia for being a true friend with a different perspective; and Marta for her enthusiasm and passion for community engagement activities. And finally, I would like to thank my colleagues from NewRail, especially Dr Marin Marinov, for their time, understanding and priceless moral support during the last two years of my ups and downs on the PhD journey. Thank you. iii Table of Contents Abstract i Acknowledgements iii Table of Contents iv List of Tables vi ii List of Figures xi Chapter 1. Introduction 1 1.1 Background 1 1.2 The UK context 2 1.3 Aims and objectives of the study 4 1.4 Structure of the thesis 5 Chapter 2. Critical review of literature on the excess travel phenomenon 6 2.1 Introduction 6 2.2 The evolution of the travel behaviour literature 7 2.3 Simple models of excess commuting 11 2.3.1 Monocetric model in excess commuting 11 2.3.2 Linear programming approach to excess commuting 12 2.4 The main issues concerning excess commuting 14 2.4.1 Methodological issues 17 2.4.1.1 Geographical boundaries 17 2.4.1.2 Different measures of excess commuting 20 2.4.1.3 Spatial structure 23 2.4.2 Contextual issues 25 2.4.2.1 Social factors 25 2.4.2.2 Physical factors 28 2.4.2.3 Psychological factors 30 2.4.3 Policy issues 34 2.5 Summary 37 2.6 Research gaps 38 2.6.1 A UK case study 38 2.6.2 Individual approach 39 2.6.3 Transport mode 40 2.6.4 A clear methodology 40 2.7 Conclusions 41 Chapter 3. Methodology 43 3.1 Introduction 43 3.2 Hypotheses 43 3.3 Design of a method for data collection 46 3.3.1 Choice of a method for data collection 46 3.3.2 Questionnaire design and mapping questions to hypotheses 48 3.3.2.1 Part one – daily travel 48 3.3.2.2 Part two – attitudinal statements towards commuting 49 3.3.2.3 Part three – geographical data 53 3.3.2.4 Part four – socio-economic characteristics 54 3.3.3 Survey delivery methods 55 iv 3.3.3.1 Paper based delivery to respondent’s home 56 3.3.3.2 Online workplace questionnaire 56 3.3.4 Incentive 56 3.4 Design of a method for measuring excess commuting 57 3.4.1 Pure time, cost and effort 57 3.4.1.1 Pure time 58 3.4.1.2 Cost excess commuters 59 3.4.1.3 Effort excess commuters 59 3.4.2 Generalised cost 61 3.5 Sampling process 62 3.5.1 The choice of Tyne and Wear as a case study area 63 3.5.2 Public transport in Tyne and Wear 65 3.5.3 Identification of the study’s sample 67 3.5.3.1 GIS as a tool for selection of ’hotspots’ by origin of commute 68 3.5.4 Sampling at the destination of commute 72 3.6 Testing the questionnaire and sampling methodology in a pilot study 73 3.6.1 Delivery methodology 74 3.6.2 Gender bias 75 3.6.3 Effort 75 3.6.4 Car availability 77 3.6.5 Focus on travel to work 77 3.6.6 Delivery Process 77 3.6.7 Questionnaire re-design 78 3.7 The main survey 80 3.7.1 Main sample – paper questionnaires 81 3.7.2 Main sample – online questionnaire 82 3.7.3 Final sample size 83 3.8 Summary 83 Chapter 4. Analysis of Results 85 4.1 Introduction 85 4.2 Analysis of Hypothesis One 85 4.2.1 Time excess commuters 86 4.2.2 Cost excess commuters 87 4.2.3 Effort excess commuters 88 4.2.4 Generalised cost excess commuters 90 4.3 Analysis of Hypothesis Two 93 4.3.1 Socio-economic characteristics 93 4.3.2 Preferences and opinions when commuting 94 4.3.3 Daily travel 98 4.3.4 Activities conducted while commuting 100 4.3.5 Teleportation test 101 4.3.6 Money and time savings results 102 4.3.7 Summary 104 4.4 Analysis of the Third Hypothesis 105 4.4.1 Alternative commute journeys 105 4.4.2 Time and cost savings 107 v 4.4.3 Physical effort spent when commuting 108 4.4.4 Cognitive effort 109 4.4.5 Affective effort 109 4.4.6 Perceived self-reported versus ideal commute time 110 4.4.7 Transport planning tools 112 4.4.8 Summary 113 4.5 Commuters opinions about public transport 116 4.6 Conclusions 118 Chapter 5.
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