https://hdl.handle.net/2123/29795 2026-06-09T18:23:41Z https://hdl.handle.net/2123/32011 Parking Preferences of Tourists in Sun Moon Lake National Scenic Area, Taiwan Jou, R.C.; Lin, Ying-Chun; Hensher, David A. Sun Moon Lake is a famous tourist attraction in Taiwan and abroad. However, as Sun Moon Lake is surrounded by mountains and has limited land to develop, traffic congestion around the lake area is commonplace during peak holiday hours. This study focusses on the parking choices of visitors to Sun Moon Lake and develops a stated preference (SP) instrument with multiple scenarios to evaluate parking preferences under various financial and service level scenarios. We estimate Multinomial Logit (MNL) and Mixed Logit (ML) models, accounting for the panel nature of the data (PDML)to identify preferences for parking choices of visitors to Sun Moon Lake. The focus is on understanding how parking price, travel time, walking time, scenery, and transfers between public transport affect visitors' parking choices. Unlike the findings of studies in metropolitan areas, which often find that parking price was the deciding factor, visitors' parking decisions in the tourist area were more concerned with time factors, such as the time to search for places to park and traffic congestion, possibly due to the less frequent use of tourist venues. Although raising parking price can suppress parking demand in the scenic area, other parking management mechanisms work better, such as the construction of new and suitable outer parking lots with transfer buses to relieve the heavily congested traffic in the scenic area. In addition we find that using the parking space in the area can be improved by beautifying the landscaping between the parking lots and the tourist spots, enhancing the pleasure of traveling along the routes, introducing multiple transfer modes, and providing real-time traffic information to tourists. 2023-12-19T00:00:00Z https://hdl.handle.net/2123/32005 Who stays and who plays? Participant retention and smartphone app usage in a longitudinal travel survey. Greaves, Stephen P.; Cobbold, Alec; Stanesby, Oli; Sharman, Mel; Jose, Kim; Evans, Jack; Cleland, Verity Longitudinal studies have become increasingly popular for investigating changes in behaviour, but present additional challenges around participant recruitment, retention, compliance, and ultimately data quality. Personal technologies, particularly smartphones, have become integral to tackling these challenges but come with their own caveats around user acceptance and compliance. The current paper investigates these issues in the context of a longitudinal investigation of interventions designed to encourage use of public transport and increase associated physical activity in Tasmania, Australia. The study comprises multiple waves of data collection over a seven-month period in which travel data were collected using a smartphone app and supplemented with user experience surveys. Evidently attrition is lower for older participants, those engaging with the app more, and those responding to the research/environmental/health messaging of the survey as well as the potential for financial gain. App usage is lower among older participants while app engagement is stronger for males, those recording less travel and those indicating environmental reasons as a motivator for completing the study. Experiences with the app were mixed, participants reported positive sentiments about the ease of use, hedonic motivation, and help in recalling travel; however, concerns were raised over the accuracy of trip recording, the associated burden of correcting trips, and reductions in smartphone battery-life. Despite the unplanned coincidence with the COVID-19 restrictions, outcomes provide important guidance around recruitment, retention and post-hoc analysis of results from longitudinal studies. 2023-12-18T00:00:00Z https://hdl.handle.net/2123/31827.2 Learning from the Evidence: Insights for Regulating E-scooters Zhang, Yuting; Nelson, John D.; Mulley, Corinne As a trending mobility choice, e-scooters have become popular in many cities. Many authorities have initiated shared e-scooter trial schemes to assess the feasibility of the vehicles prior to enacting official legalisation. This paper aims to provide an evidence review of shared e-scooters and investigate how existing evidence may inform long-term policies. This carries significant relevance for jurisdictions that are in a conflicting position with e-scooters, such as New South Wales (NSW), Australia whose context motivates this study. The evidence review focuses on three themes derived from experience with shared e-scooters within the broader micromobility landscape, namely: safety; where shared e-scooters fit into the modal landscape; and the environmental impacts. Findings confirm that ensuring the safety of shared e-scooters requires complex solutions, which may include a clear regulatory framework for e-scooters, safety education and skill training, innovative data collection and analysis methods, and an approach to safety management that is user-based, location-based, and time-based. In terms of modal fit policymakers should encourage first and last-mile combinations with public transport, with consideration of user characteristics; while environmental impact is strongly correlated to the mode replaced by e-scooter trips. The paper provides insights for policymakers on the regulation and positioning of shared e-scooters. 2023-11-02T00:00:00Z https://hdl.handle.net/2123/31826 Barriers towards enhancing mobility through MaaS in a Regional and Rural context: insights from suppliers and organisers Xi, Haoning; Nelson, John D.; Mulley, Corinne; Hensher, David A.; Ho, Chinh Q.; Balbontin, Camila This study explores the potential of a mobility framework for MaaS in a regional and rural context. In-depth interviews of stakeholders, including Non-Transport Providers and Transport Providers, were conducted in three regional locations in New South Wales, Australia, and their attitudes towards MaaS analysed. Findings revealed that the majority had a positive attitude towards MaaS; while those who expressed negative attitudes commonly had concerns about subscription fees, the underlying reliance on private cars in rural areas, and the digital usage by older people. The paper discusses the government's role in improving travel options which ensure equitable access to both local and regional transport services. Policy implications for necessary adjustments to the modal landscape and the design of a digital App and payment methods are drawn. The results provide insights into the features of mobility services, which could include alternative uses for the private car, provided by various stakeholders and their fit within the mobility framework. 2023-11-02T00:00:00Z https://hdl.handle.net/2123/31785 A latent-based segmentation framework for the investigation of charging behaviour of electric vehicle users Pellegrini, Andrea; Diana, Marco; Rose, John Electrification of transport is deemed by many countries worldwide as one of the key strategies to mitigate C02 emissions, yet the availability of reliable public charging infrastructure systems represents a potential serious bottleneck to such endeavours. Existing studies exploring battery electric vehicle (BEV) charging behaviour are typically based on either non-representative samples or stated choices experiments. This paper analyses observational data from a representative sample of German BEV owners who provided information on mileage and charging activities over a timeframe of eight weeks. BEV charging patterns, related vehicles kilometres travelled (VKT) and battery charging behaviour are assessed via a multifaceted empirical framework that pairs a hazard survival-based model with a log linear regression approach. A latent class method is also employed to segment BEV owners into different charging segments. The model suggests two types of charging behaviour exist, consisting of regular and irregular chargers. Charging frequencies and patterns are found to be radically different between the two groups under study, with regular chargers estimated to charge their vehicles 1.5 times more than irregular chargers. Lastly, the framework proposed is used to explore how charging behaviour will mutate due to both technology advancements (BEV driving range improvements) and user-centric factors (VKT variations). Neither technological or user factors are predicted to substantially affect the inter-charging duration of irregular chargers, whereas both increasing BEV driving ranges and reducing VKT results in a longer elapsed time between two consecutive charges for regular users. 2023-10-19T00:00:00Z https://hdl.handle.net/2123/31664 Development and Application of a State-wide Transport Model System in Australia Hensher, David A.; Ho, Chinh Q. This paper develops a regional travel demand model system, called R-Tresis, with the capability to predict expected changes in public transport patronage under service scenarios up to 2056. Taking 2016 as the base year, this paper sets out the approach undertaken to develop the key network performance variables (travel times, fares and other costs, and service frequency) for four linehaul modes – train, coach, car, and plane. An aggregate modal share logit model for three trip purposes is estimated to identify the role of various trip attributes and socioeconomic characteristics to forecast modal shares in the base year 2016. The resulting models produce an accessibility index, as a derivative of a logit model that captures the role of each mode in defining the accessibility to each and every other location in NSW and the Australian Capital Territory. The accessibility index is used in a residential population model to identify the relationship between population and accessibility, which is important in identifying the potential growth in population as a result of improvements in the transport network. The estimated base year relationship between population and accessibility is then linked to a total travel demand model (i.e., one-way daily trips expanded up to a year) to obtain a relationship between changes in the population levels and travel. In addition, a total trips model for the existing population (under a business-as-usual scenario) identifies the relationship between existing resident’s trip activity and accessibility, which used in application to predict changes in travel (or induced trips) of the population associated with business as usual. We have chosen a corridor between Sydney and Newcastle and beyond to illustrate the application of the model system. 2023-09-14T00:00:00Z https://hdl.handle.net/2123/31575 Evaluating Travel Behavior Resilience across Urban and Rural Areas during the COVID-19 Pandemic: Contributions of Vaccination and Epidemiological Indicators Xi, Haoning; Nelson, John D.; Hensher, David A.; Hu, Songhua; Shao, Xuefeng; Xie, Chi The COVID-19 pandemic has severely disrupted travel behavior across diverse socio-economic areas, with a significant impact on transportation systems, public health, and the economy. As countries both recover and plan for future virus-driven stresses, it is crucial to identify the drivers of building travel behavior resilience, such as vaccination. Using an integrated dataset with over 150 million US county-level mobile device data from 01/01/2020 to 20/04/2021, we employ Bayesian structural time series (BSTS) models to infer the relative impact of the vaccination intervention on five types of travel behavior across Metropolitan, Micropolitan and Rural areas. Further, we develop partial least squares regression (PLSR) models to accurately estimate how COVID-19 vaccination rates, epidemiological indicators (i.e., COVID-19 incidence rates, death rates, and testing rates) and weather conditions (i.e., temperature, rain, and snow) would impact various travel behaviors across the diverse areas during the recovery period of the pandemic. The model results shed light on the positive role of vaccinations in fostering the recovery of travel behaviors and reveal the disparities in travel behavior resilience in response to vaccination rates, epidemiological indicators, and weather conditions across diverse areas. Our findings can offer evidential insights for policymakers, transport planners, and public health officials, guiding the development of equitable, sustainable, and resilient transportation systems prepared to adapt to future pandemics. 2023-08-22T00:00:00Z https://hdl.handle.net/2123/31553 An Alternative Scoring Approach for Best-Worst Scaling (BWS) Wei, Edward; Burke, Paul F. The paper proposes an alternative scoring approach for the Best-Worst scaling (BWS) Object Case to capture both preference heterogeneity and experimental design differences to improve the prediction accuracy at the individual level. The unduplicated and highly unique scores across individuals also provide helpful input for further analysis, such as hybrid models to help understand people’s preferences in other tasks. Whilst the existing BWS scoring methods, including the most commonly used best-minus-worst and the best-over-worst ratio scores, have been applied primarily to elicit preference and ranking at both aggregate and individual levels, there are limitations such as equally scored items when we predict choices and order. We propose an alternative approach to target several limitations of existing methods. The proposed scoring approach can make several contributions: 1) it breaks equality in scores; 2) it introduces instruments to minimise design-induced effects such as different item co-occurrences in different balanced incomplete block designs (BIBD); and 3) it introduces a risk-averse instrument to lower the impact of incorrect predictions. We used seven empirical BWS Case I data sets with respondents completing full BIBD designs varied to test the new scoring against the current scoring. Results show a universal improvement in prediction accuracy. Compared to the present method, generating a limited set of discrete scores, the new approach generates almost unduplicated scores for object items across individuals with continuous distributions. 2023-08-10T00:00:00Z https://hdl.handle.net/2123/31466 Improving Transportation Project Evaluation by Recognizing the Role of Spatial Scale and Context in Measuring Non-User Economic Benefits Weisbrod, Glen; Hensher, David A. The usefulness of transportation project evaluation depends on the completeness of its benefit measures. Since transportation networks are intrinsically spatial, transportation improvement projects have spatial access and location characteristics that can lead to a variety of non-user economic benefits. Recent research has enabled us to better understand how spatial context and spatial heterogeneity play further roles in generating efficiency gains for non-users, in the form of productivity, income, and cost savings for both private and public sectors of the economy. This paper draws upon that body of research to expand our understanding of the means by which transportation projects can generate economic efficiency gains, and approaches needed to measure them. It covers topics beyond those captured by current definitions of “wider economic benefits,” including additional sources of scale economies associated with freight distribution and connectivity, and further public and private sector economic gains enabled by environmental and social inclusion improvement. It points to ways that non-user economic benefits can be more comprehensively defined and better measured by recognizing their spatial scale, context, and threshold effects. It also identifies ways that current benefit measurement methods introduce unintended bias into transportation investment decision-making through omission and mismeasurement. The result is a case for a refresh of thinking about how we classify and recognize non-user economic benefits in transportation evaluation, and how we apply transportation planning and economic models to support their measurement. 2023-07-13T00:00:00Z https://hdl.handle.net/2123/31453 A novel mobility consumption theory for road user charging Bliemer, Michiel C.J.; Loder, Allister; Zheng, Zuduo Building on the analogy between electrical energy and mobility, we propose a novel mobility consumption theory based on the idea of the required reserved space headway of vehicles while driving. In this theory, mobility is ``produced'' by road infrastructure and is ``consumed'' by drivers in a similar fashion to power that is produced in power plants and consumed by electrical devices. The computation of mobility consumption only requires travel distance and travel time as input, as well as two physical parameters that are readily available, namely vehicle length and reaction time. We argue that mobility consumption is a more comprehensive measure for road use than travel distance (or travel time) alone as it captures road use over both space and time. One application area for our mobility consumption theory that we look at in this study is road user charging. We use mobility consumption theory to develop a mobility-based charging scheme as a novel road pricing approach and compare it to distance-based charging in two case studies. When considering only departure time choice in a simple bottleneck model, we show that mobility-based charging can reduce congestion akin a congestion pricing scheme, unlike distance-based charging. Further, when considering route choice, we show that distance-based charging can increase congestion as it encourages drivers to take shortcuts through routes with low capacity, while mobility-based charging mitigates this effect. The proposed mobility-based charging scheme is further capable of considering technological innovation in vehicle automation and carbon charging. 2023-07-11T00:00:00Z https://hdl.handle.net/2123/31368.2 The Digital Freight Forwarder and the Incumbent: A Predictive Framework to Examine Disruptive Potentials of Digital Platforms Herold, David; Fahimnia, Ben Digital platforms play an increasing role in the logistics industry. In this space, new start-ups have been challenging the traditional logistics providers with new business models. It is, however, not clear whether these digital platforms have the potential to truly ‘disrupt’ the current industries. In this paper, we debate a holistic view on the notion of disruption and disruptive innovation in the context of digital platform start-ups. To distinguish between disruptive and sustained innovations, we propose a Digital Start-up Disruption (DSD) framework – grounded on the existing literature – that allows characterizing digital platforms and their disruptive potential, the ecosystem network, the value creation, and the regulatory agenda. Applying the framework of the four antecedents to a case study of a digital freight forwarder arrives at important insights pertaining to the dynamics of disruptive and sustaining technologies. This framework and methodology can help investors and funding organisations identify the opportunities for potential disruptive innovations. 2023-06-21T00:00:00Z https://hdl.handle.net/2123/31324 A data-driven conceptual framework for understanding the nature of hazards in railway accidents Hong, Wei-Ting; Clifton, Geoffrey; Nelson, John D. Hazards threaten railway safety by their potential to trigger railway accidents. Whilst there are a considerable number of prior works investigating railway hazards, few offer a holistic view of hazards across jurisdictions and time and demonstrate policy implementation due to the inability to analyse a large amount of safety-related textual data. The conceptual framework HazardMap is developed to overcome this gap, employing open-sourced Natural Language Processing topic model BERTopic for the automated analysis of textual data from Rail Accident Investigation Branch (RAIB), Australian Transport Safety Bureau (ATSB), National Transportation Safety Board (NTSB) and Transportation Safety Board of Canada (TSB) railway accident reports. The topic modelling depicts the relationships between hazards, railway accidents and investigator recommendations and is further extended and integrated with the existing risk theory and epidemiological accident models. Results show that each hazard in the railway system has different aspects and could trigger a railway accident when combined with other hazards. Each aspect can be partially or fully addressed by implementing hazard mitigation policies such as introducing new technologies or regulations. A case study of the application to the risk at level crossings is provided to illustrate how HazardMap works with real-world data. This demonstrates a high degree of coverage within the existing risk management system, indicating the capability of helping policymaking for managing risks with adequate accuracy. The primary contributions of the framework proposed are to enable a huge amount of knowledge accumulated for an intuitive policymaking process to be summarised, and to allow other railway investigators to leverage lessons learnt across jurisdictions and time with limited human intervention. Future research could incorporate data from road, aviation or maritime accidents. 2023-06-07T00:00:00Z https://hdl.handle.net/2123/31323 RecoMap - a semi-automated tool for analysing railway accident recommendations across jurisdictions and over time Hong, Wei-Ting; Clifton, Geoffrey; Nelson, John D. To maintain a safer railway operational environment, recommendations are proposed by independent investigators after accidents. Despite a considerable number of (sometimes similar) recommendations made across jurisdictions, practitioners suffer from a lack of synthesised recommendations made across jurisdictions and time due to the high complexity of analysing textual data. To fulfil the gap, an auto mated tool for the analysis of accident report recommendations is developed, allowing the railway industry to learn from other countries. The Structural Topic Model (STM) is used to extract critical insights from recommendations to depict how independent railway accident investigators mitigate risks observed. Empirical data is retrieved from official railway accident reports published by Rail Accident Investigation Branch (RAIB), Australian Transport Safety Bureau (ATSB), National Transportation Safety Board (NTSB) and Transportation Safety Board of Canada (TSB). The resulting RecoMap is developed as a framework to help practitioners learn across jurisdictions and time. The study also identifies a transition from making interfering recommendations addressing operational issues to making supportive recommendations addressing organisational issues in the railway industry across countries. Additionally, the concept of triple-loop learning is insufficient in the railway industry of the investigated jurisdictions, implying that current practices might result in railway accidents that could have been prevented by learning from other jurisdictions and implementing corresponding mitigation measures in advance. 2023-06-07T00:00:00Z https://hdl.handle.net/2123/31309 Exploring stability in travel attitudes: Evidence from a repeated cross-sectional study in Sydney, Australia Van Acker, Veronique; Mulley, Corinne Many travel behaviour studies focus on the interaction between attitudes and travel behaviour, but in doing so have used a multitude of attitude measurements. These studies often use surveys where respondents are asked to indicate their level of agreement with a set of attitudinal statements. However, this set of statements sometimes varies very widely between studies, making it difficult to compare results across studies as well as complicating a thorough understanding of the motivations underlying travel. This paper therefore uses a repeated cross-sectional approach where the same set of attitudinal statements was asked in an online survey organized in 2016 and 2020 in the Greater Metropolitan Area of Sydney, NSW, Australia. Findings indicate that the same type of travel attitudes persist over time (in this study: a negative attitude towards travel in general, and a positive attitude towards cars). Moreover, these travel attitudes remain characterized by (largely) the same set of attitudinal statements, indicating at least some stability in the measurement of travel attitudes. Findings of this paper can thus be helpful in reducing the heterogeneity of attitudinal statements included in travel surveys. 2023-01-01T00:00:00Z https://hdl.handle.net/2123/31294 The impact of the pandemic on logistics and supply chain digitalization Bhattacharjya, Jyotirmoyee; Tripathi, Sonali; Gezdur, Arda; Sutton-Brady, Catherine; Bell, Michael The coronavirus pandemic led to supply chain disruptions resulting in adverse economic impacts on global supply chains. Nationwide lockdowns in countries that play key roles in global manufacturing restricted freight movements through air, ocean, and land routes resulting in delivery delays, higher freight rates, and congestion. At the same time, the pandemic has accelerated the growth of the e-commerce sector. Concern around infections has led to a surge in first-time online consumers for categories such as health and pharmaceuticals and fast-moving consumer goods. Companies have had to rethink their approaches to optimizing warehouse locations and inventory to meet customer demand. From a freight perspective, the focus has shifted from a single-mode model towards multi-modal logistics to reduce costs and dependence on any one mode. This chapter will review recent developments, long term impacts and opportunities for growth in the context of this important sector and illustrate some of the key impacts of the pandemic using the example of the emerging economy in India. It concludes by synthesising key takeaways and conclude by reflecting on the future of the sector. 2022-01-01T00:00:00Z https://hdl.handle.net/2123/31255 Travel time reliability, urban form, decision making under uncertainty and smart urban development Li, Zheng; Zeng, Jingjing; Hensher, David A.; Wu, Chenyang Within a land use-transportation interaction model, this study embeds a behavioral framework which accommodates travel decision making under uncertainty into a spatial general equilibrium model to understand the interplay between individuals’ mode choices and urban form. Special attention is paid to demonstrating the multifold role of ambiguity attitude, a behavioral mechanism existing in real-market decisions but largely overlooked in urban models. Our baseline model outputs are consistent with the market evidence, which reinforces the rationality of the proposed model with a focus on behavioral realism. We also simulate the possible impacts of improved travel time reliability on system behavior and urban form, and the results suggest it is possible to realize smart development in terms of sustainable travel and city growth. 2023-05-22T00:00:00Z https://hdl.handle.net/2123/31108 Travel Decision Making Under Uncertainty and Road Traffic Behavior: The Multifold Role of Ambiguity Attitude Zeng, Jingjing; Li, Zheng; Hensher, David A. To aggregate commuters’ mode choices to traffic behavior in the presence of travel time uncertainty, we develop a dynamic traffic simulation in terms of an agent-based model, which consists of two sub-models, the mode choice model and the traffic flow simulation model. The modeling framework accommodates the interplay between the two models and their co-evolution over time. We embed an extended list of empirical parameters including ambiguity/risk attitudes and heterogeneity , and time-money trade-offs within a rank-dependent and source-dependent utility framework to imitate commuters’ daily mode choice behaviors. The improved behavioral realism at the micro-level results in an improved understanding of traffic flow in terms of modal split and average speed at equilibrium, compared to a conventional model which assumes risk neutrality and ambiguity neutrality. A novel finding is that ambiguity seeking, a typical behavior in the loss domain but largely ignored in the transport literature, acts as an important driver that shifts commuters from cars to public transport. 2023-04-18T00:00:00Z https://hdl.handle.net/2123/31089 An autoregressive spatial stochastic frontier analysis for quantifying the sales efficiency of the electric vehicle market: An application to 88 pilot cities in China Pellegrini, Andrea; Yao, Xusheng; Rose, John; Ma, Shoufeng This paper proposes the use of an autoregressive spatial stochastic frontier model to measure the sales efficiency of the electric vehicle (EV) market in 88 Chinese cities for the period 2016 to 2021. In contrast to previous research on this topic, the adoption of a stochastic frontier model allows for computing the maximum level of EV sales (i.e., frontier) that each city could have potentially achieved in the timeframe under scrutiny given a certain set of inputs (e.g., central and local purchase subsidies, subsidies for the construction/operation of electric vehicle chargers, average petrol prices, purchase restrictions on conventional vehicles, among others). Further, the spatial-based structure of the model proposed enables the assessment of the impact of similar policy interventions implemented in neighbouring cities on EV sales frontier estimated within the city. The empirical evidence suggests that as the provision of EV charging stations around and within the city increases, so does the maximum number of sellable electric cars. A further interesting finding is that the frontier for EV sales is positively influenced by the electric cars purchased in the previous month in neighbouring areas, revealing the presence of a strong spatial dependency. Finally, this study conducts a simulation exercise wherein three hypothetical scenarios are explored: 1) the implementation of a ten percent tax on petrol, 2) a ten percent increase in the number of public chargers available, and 3) the introduction of policies to improve the air quality of all 88 cities. The results from the simulation analysis suggests that introducing a 10 percent environmental tax on petrol would have resulted in the sales of around 71,000 EVs more across the 88 cities over six years. 2023-04-12T00:00:00Z https://hdl.handle.net/2123/30276 The Greening of the passenger car might not deliver such positive sustainability news – so what do we have to do? Hensher, David A. As we promote the need to reduce emissions at the tailpipe for cars, trucks, and buses, we may be neglecting the full story on what this might mean for achieving a broad set of sustainability goals. While not denying the merits of reducing tailpipe emissions, there are many unresolved questions about the indirect emission impacts as well as other sustainability impacts such as traffic congestion. This short paper attempts to place the debate within a wider setting if only to achieve more than what we see government myopically focusing on. 2023-03-23T00:00:00Z https://hdl.handle.net/2123/30212 No Accounting for Government: Applying Corporate Governance Principles to Elected Officials Day, Christopher To address the agency problem, corporate governance legislation has placed stringent requirements on the behaviour of individuals appointed to company boardrooms and senior management positions. In contrast, there is an absence of robust governance frameworks for politicians and their advisors. This is problematic given the delegation of decisions making authority by the public and the adverse consequences of poor decisions and unscrupulous behaviour on societal well-being. Accordingly, this paper draws on the tenets of corporate governance legislation and outlines how application of a similar framework within government has the potential to improve the efficacy and transparency of its decisions. 2023-03-15T00:00:00Z https://hdl.handle.net/2123/29971 Two Mobility as a Service (MaaS) paradigms: Private Assets as a Service (PAaaS) with reference to the Private Car as a Service (PCaaS) and Corporate MaaS (C-MaaS) Hensher, David A. Mobility as Service (MaaS) continues to garner significant interest and yet we still appear to be a long way from any signs of a product profile that has the merit of a business case let alone a commercial case. We continue, however, to explore ways in which MaaS may eventually deliver societal outcomes that make it an appealing contribution to delivering improved mobility aligned with sustainability objectives. This note proposes a focus on ways to make better use of the private car and a corporate commitment model as offering real potential if behaviourally achievable to deliver an appealing MaaS offering. 2023-02-06T00:00:00Z https://hdl.handle.net/2123/29970 What have we learned about long term structural change brought about by COVID-19 and working from home? Hensher, David A.; Beck, Matthew J.; Nelson, John D. March 2020 will forever be etched in our minds as the beginning of what has become the most concerning health pandemic faced by all generations of the living population. Almost two-and-three quarter years on, we are starting to see a number of signs for what the future might evolve into through structural change brought about by many events, and no more so than the burgeoning growth in working from home (WFH). No longer associated with negative stigma, working from home, or remote working more generally, has become almost folklore with all elements of society slowly recognising that it is to some extent here to stay, and we should start rethinking how this non-marginal change in the way we live, and work will be used to restructure the fabric of society. In this paper, we draw on the research undertaken as part of an ongoing project on WFH and its relationship to travel and work, since March 2020 to summarise the main evidence that we use to speculate on what we think are likely to be the big changes in the land transport sector that would not have been considered, at least to the same extent, pre-COVID-19. 2023-02-06T00:00:00Z https://hdl.handle.net/2123/29969 Slow recognition of seminal papers and fast growth of author connectivity in economics Haghani, Milad; Hensher, David A.; Greene, William A bird’s-eye view of the economics literature and its temporal evolution during the last three decades is provided by analysing titles, abstracts, keywords, reference lists and author affiliations of nearly 204,000 economics papers. Major divisions of the literature are objectively identified through exploring patterns of term co-mention in their titles and abstracts. Temporal research trends are also quantified, and influential references are determined through patterns of co-citation of references in the reference lists of these papers. Analyses show that the literature of economics tends to lag in the adoption of emerging research and is reliant on a traditional knowledge base. Of more than 1,250 references that have had a local burst of citation, the average and maximum gap between their publication year and the onset of recognition has been respectively 10 and 47 years. Influential economics papers typically have to wait for a decade before their recognition comes along, and this phenomenon has intensified over the last three decades. Another observation is the sharp rise in author connectivity and globalisation in economics research. International collaboration in the field of economics shows a distinct acceleration since 2013. If current trend continues, in few years, the number of internationally collaborated economics papers published each year will surpass that of domestically produced papers. Economists may be traditionalists, in that, they are hesitant in giving recognition to new research or creating new research trends, but they cannot be considered insular, as they have become notably well-connected and collaborative. 2023-02-06T00:00:00Z https://hdl.handle.net/2123/29876 Vehicle choice and use under alternative policy scenarios: What needs to be done to promote electric vehicle uptake and usage Pellegrini, Andrea; Rose, John The aim of this study is to evaluate the determinants affecting two interrelated discrete and continuous decisions that households typically make when purchasing a new vehicle, consisting of vehicle type choice and their usage. To this end, we develop a double hurdle model that explicitly accounts for mixed nature of the choices under investigation. The proposed methodological approach is applied to a discrete choice experiment primarily designed to elicit New South Wales (Australia) residents’ preferences for alternative fuelled vehicles. Evidence from the empirical analysis suggests that respondents are more inclined to acquire fuel efficient automobiles relative to passenger vehicles powered by petrol, with battery electric cars being the most preferable purchase option. Nevertheless, the model shows that respondents still prefer driving conventional vehicles longer, with petrol automobiles being the fuel type car associated with the highest kilometres driven. Finally, given the model parameter estimates, this study undertakes a simulation exercise to explore how the New South Wales automobile market will evolve under different policy settings. The modelling predictions suggest that lowering the purchase price of plug-in hybrid-electric and battery electric vehicles below that of all other vehicle fuel types will give rise to more electric vehicles on roads compared to a faster charging time of home stations. 2023-01-12T00:00:00Z