Stated Preference Survey Research Articles

Assessment of the environmental impact and policy responses for urban air mobility: A case study of Seoul metropolitan area

Urban air mobility (UAM) is expected to be a new alternative future transportation system to overcome the limitations of infrastructure investment and resolve traffic congestion cost issues in urban areas. This study aims to estimate the parameters of the mode choice model incorporating the cleaner transportation mode and evaluate the environmental impact by calculating the reduction of greenhouse gas emissions from ground traffic. A stated preference survey is employed to estimate the parameters for each travel mode, including the emerging travel mode. The awareness and experience of the air travel modes remove the hesitation concerning travel mode choice having positive values, but concerns about taking new types of air mobility reduce the probability of choosing urban air mobility. The macroscopic travel demand forecasting program simulates the travel demand of urban air mobility to calculate the reduction of CO2 emissions between before and after the introduction. While about 30 thousand of urban air mobility travel demand are generated after the introduction of urban air mobility in the urban area, it reduces about 90 thousand tons of CO2 emissions from the ground traffic. The introduction of urban air mobility causes modal shifts from ground traffic, reducing climate change and global warming. Policymakers should evaluate the feasibility of introducing urban air mobility, including environmental impact assessment, and an appropriate transit fare policy is required for the proliferation of urban air mobility.

Connected automated vehicle impacts in Southern California part-I: Travel behavior and demand analysis

Connected and automated vehicle (CAV) technologies attracted extensive attention in the past decade. As CAV brings convenience to travel, people's travel behaviors and patterns might change significantly. Existing models, however, cannot comprehensively evaluate the impacts on transportation systems. This study adopted an activity-based approach to evaluate the comprehensive CAV impacts on the transportation system in Southern California. A stated-preference survey was conducted, and captured people's behavior changes associated with CAV deployment. The model prediction demonstrated that the total trip number increased by 9%, with an 13% growth in total car-like mode travel distance. Among all trip purposes, work trips contributed to 49% of total trip number growth and 75% of the increased car-like mode travel distance. The advanced CAV technology alone wouldn’t directly benefit future transportation systems and it is still critical to have appropriate policy interventions in place.

Public managers’ trust in citizens and their preferences for behavioral policy instruments: evidence from a mixed-methods study

AbstractLocal public managers increasingly use behavioral policy instruments to influence the behavior of citizens. However, despite their increased reliance on these instruments, there is little evidence on why local public manager would prefer behavioral instruments over classic stick, carrot or sermon-type instruments. We conduct a mixed-methods study, combining a stated-preference survey and two focus groups, to examine whether senior local public managers (directors and deputy directors) in Flanders prefer behavioral policy instruments over classic stick, carrot and sermon-type instruments, and explore whether their trust in citizens (perceptions of citizen's ability, benevolence and integrity) affects these preferences for policy instruments. The results indicate that in some policy areas, such as health, public nuisance and road safety, public managers appear more willing to use behavioral policy instruments than classic sticks and carrots, but not sermons. Furthermore, we find that public managers’ trust in citizens does not appear to significantly affect their preferences for policy instruments, but that political and economic motives do play a role in their preferences for behavioral policy instruments. Finally, the results also indicate that the simultaneous use of behavioral and classic policy instruments (packaging) can help mediate the perceived risks of citizens’ non-compliance with behavioral policy instruments.

Exploring the Role of Shared Mobility in Alleviating Private Car Dependence and On-Road Carbon Emissions in the Context of COVID-19

Shared mobility is becoming increasingly popular worldwide, and travelers show more complex choice preferences during the post-pandemic era. This study explored the role of shared mobility in the context of coronavirus disease (COVID-19) by comparing the travel mode choice behavior with and without shared mobility. Considering the shared mobility services of ride-hailing, ride-sharing, car-sharing, and bike-sharing, the stated preference survey was designed, and the mixed logit model with panel data was applied. The results show that if shared mobility is absent, approximately 50% of motorized mobility users and 84.62% of bike-sharing adopters will switch to using private car and public transport, respectively. The perceived pandemic severity positively affects the usage of car-sharing and bike-sharing, while it negatively affects the ride-sharing usage. Under different pandemic severity levels, the average probabilities of private car choice with and without shared mobility are 38.70 and 57.77%, respectively; thus, shared mobility would alleviate the dependence on private car in post-pandemic future. It also helps to decrease the on-road carbon emissions when the pandemic severity is lower than 53. These findings suggest policymakers to maintain the shared mobility ridership and simultaneously contain the pandemic. Additionally, pricing discount and safety enhancement are more effective than reducing detour time to protect ride-sharing against COVID-19.

Inferring Community Resilience through the Accessibility of Goods Delivery

This study analyzed community resiliency by evaluating access to essential delivery services before and during the COVID-19 pandemic. Data were collected from October 2020 to September 2021 in a stated-preference survey about delivery services in Southwest Virginia. A significantly larger proportion of respondents without vehicle access relied on third-party restaurant app delivery use than those with a vehicle. Compared to more urban areas, respondents who lived in rural locations were three times more unsatisfied with delivery services due to a lack of accessibility to stores and delivery options.

Intrinsic motivation for reducing single-use plastics: The compensation effects of basic psychological needs

Increasing single-use plastic consumption has caused tremendous consequences for the ecosystem; therefore, consumers are being encouraged to reduce this. Despite numerous research about single-use plastics, we still have little understanding into how individuals’ intrinsic motivation for less single-use plastics can be developed. This study extends the self-determination theory about human motivation and the functioning of basic psychological needs which are essential for behavior change to study how three basic psychological needs can influence intrinsic motivation for reducing single-use plastics. Also, the negative interaction effects of each pair of basic psychological needs on intrinsic motivation were examined in this study. A sample of 468 responses collected in a stated preference survey was used to test the theoretical framework. Findings reveal that intrinsic motivation for reducing single-use plastics can be influenced by the satisfaction of basic psychological needs. Interestingly, the research has extended the self-determination theory by highlighting compensation effects among the fulfillment of basic psychological needs on intrinsic motivation for reducing single-use plastics.

The effect of online meeting and health screening on business travel: A stated preference case study in Hong Kong

This study quantifies the effects of health control measures at the airport on passenger behaviour related to business travel. A stated preference survey was conducted over potential air travellers in Hong Kong in the context of COVID-19 pandemic. Panel latent class models were estimated to understand passenger preference toward new travel requirements given the applicability of online meeting. Online meeting is applicable in cases where it is a good substitute of air travel and achieves the same outcomes of a trip, and inapplicable otherwise. Empirical results indicate that traveller subgroups are affected in different ways. When an online meeting is inapplicable, nearly 75% of the respondents prefer to travel for business and undertake health screenings. These passengers (identified as “captive” business travellers) perceive such measures necessary to lower health related risks during air travel. As such, they are willing to spend up to 21 to 38 min on the health control measures such as vaccination record requirements and test involving sample collection. When an online meeting is applicable, the share of “choice” business travellers is about 45%, among whom the attitudes towards health control measures become more averse. The average weighted willingness-to-pay for the time saved at health checkpoints increase significantly. The aviation industry thus faces a “double-hit” problem: operation costs will increase due to pandemic control measures, and the resultant inconvenience, extra time and costs further reduces travel demand. Unlike previous short pandemics, business travel is likely to suffer with an extended decline until the pandemic is fully controlled. These identified challenges call for financial and operational support to help the aviation industry reach a sustainable “new normal”. The high value of time saved at check points also justifies investments that make the pandemic control and health measures efficient and smooth. Travellers’ time spent on airport health control should be within 20 min to avoid substantial negative impacts on business travel demand.

Political relations and sports: exploring the demand for relocated soccer games

ABSTRACT Research question In recent years, European soccer leagues have strengthened their internationalization efforts by relocating games abroad. In this context, we empirically investigate the impact of the political relations between the importing and the exporting countries on on-site demand for such games. While there is a rich literature addressing this issue in more general settings, it has never been explored in sports. Research methods We use a stated-preference approach and survey data of a representative sample of soccer-interested US residents, which we combine with data from the American Community Survey. The effects are estimated using Tobit regressions and an instrumental variable approach. Results and findings We find that the willingness-to-pay for admission to relocated games is higher if the country where the competing teams come from is perceived as friendly. Implications We provide preliminary empirical evidence that the political relations between importing and exporting countries may be important for international demand of spectator sports. As such, the public perception about political relations between countries may constitute a crucial component for sport leagues’ expansion strategies.

Individual-level exit choice behaviour under uncertain risk

Understanding human decision making during emergency evacuations is important. It is because decision making is crucial at each stage of the evacuation (e.g. route choice, exit choice, path finding, etc.). Previous studies have examined the influence of social interaction and environmental factors on exit choice. However, researches on the decision-making behaviour and risk attitude towards such selection at the individual level is still limited. To fill this knowledge gap, we designed a series of virtual evacuation scenarios to examine the exit choice behaviour and decision-making attitude in uncertainty risk scenarios in different smoke conditions. Data collection was implemented by an online stated preference survey. The results revealed a systematic and pattern preference in exit choice regardless of the decisions made by experienced evacuees. The weighted uncertainty risk for individuals was determined by considering the smoke height and smoke appearance frequency. The weighting function between the subjective and objective entities exhibited an S shape. In addition, the function was estimated using an empirical equation. A decision maker’s attitude towards uncertain risk in evacuation scenarios was observed to be a rank- and reference-dependent preference rather than being fully rational. The results of the experiments conducted in virtual environment well agreed with the cumulative prospect theory. This research demonstrates the feasibility of using virtual environment for evacuation experiment which can total avoid the risk of stampede while the individual decision-making behaviours can still be captured.

P53 Patient Preferences for Multiple Myeloma Treatment: A Stated Preference Survey Using Discrete Choice Experiment and Swing Weighting

Patient preferences have become an important focus for inclusion in drug development and evaluation. Understanding patient preferences is especially valuable in Multiple Myeloma (MM), where the rapid development of treatments with diverging benefit-risk profiles raises uncertainty about what matters most to patients. This study aimed to investigate which treatment attributes (side-effects, symptoms, efficacy outcomes, uncertainties) are most important to MM patients.

Autonomous Vehicles Acceptance: A Perceived Risk Extension of Unified Theory of Acceptance and Use of Technology and Diffusion of Innovation, Evidence from Tehran, Iran

This research integrates Unified Theory of Acceptance and Use of Technology (UTAUT) (Performance Expectancy [PE], Effort Expectancy [EE], and Social Influence) with Diffusion of Innovation Theory (TRialability [TR] and OBservability [OB]) as well as Perceived Risk (PR) to identify a wider set of latent factors affecting acceptance of fully automated AVs. Although research on AVs acceptance has been conducted in developed countries, it is a rather new topic in developing countries, where it has only been introduced as a promising technology to come. Structural equation modeling on stated preference surveys data of 641 Tehran residents in 2019 justifies the proposed integration of two theories and PR. Only PR shows an expected negative sign (−0.2); Among UTAUT variables, PE (0.33) and EE (0.25) were the most and least influential factors, respectively. Regression weights of DOI-related variables show that TR (0.17) and OB (0.16) have almost equal effect.

The Impact of COVID-19 on Travel Mode Choice Behavior in Terms of Shared Mobility: A Case Study in Beijing, China.

Shared mobility is growing rapidly and changing the mobility landscape. The COVID-19 pandemic has complicated travel mode choice behavior in terms of shared mobility, but the evidence on this impact is limited. To fill this gap, this paper first designs a stated preference survey to collect mode choice data before and during the pandemic. Different shared mobility services are considered, including ride hailing, ride sharing, car sharing, and bike sharing. Then, latent class analysis is used to divide the population in terms of their attitudes toward shared mobility. Nested logit models are applied to compare travel mode choice behavior during the two periods. The results suggest that shared mobility has the potential to avoid the high transmission risk of public transport and alleviate the intensity of private car use in the COVID-19 context, but this is limited by anxiety about shared spaces. As the perceived severity of the pandemic increases, preference for ride hailing and ride sharing decreases, and a price discount for ride hailing is more effective than that for ride sharing at maintaining the ridership despite the impact of COVID-19. These findings contribute to understanding the change in travel demand and developing appropriate strategies for shared mobility services to adapt to the pandemic.

Modal Choice for the Driverless City: Scenario Simulation Based on a Stated Preference Survey

The possible future introduction of Autonomous Vehicles (AVs) and Shared Autonomous Vehicles (SAVs) raises questions about how they might affect the demand for transport and especially modal choice. In this research, a stated preference (SP) survey and a modelling process using Mixed Logit are proposed to simulate the future market share of AVs/SAVs and how their introduction into the system could change the modal choice, especially in relation to active and public transport modes. An efficient SP survey design has been developed based on the state-of-the-art information and carried out in 2020 among citizens of two medium-sized Southern European cities within a car-intensive region. The design considered different trip purposes (compulsory, leisure), different trip distances, and attributes not taken into account before, such as comfort and the physical characteristics of the terrain for the active modes. The model results suggest that AVs and SAVs were the preferred transport modes for most respondents, accounting for more than 58% of the market share in the scenarios presented. Also, we detected some socioeconomic differences in the propensity to use this mode of transport showing that men living in high-income households and car users were more prone to use autonomous alternatives. The models allowed us to simulate different scenarios, such as experiencing higher costs for using the AV alternative. Policies imposing a higher cost for the AV alternative but lower costs and waiting times for the SAV and public transport alternatives could decrease the AV’s market share favouring more sustainable modes. The above scenario showed that achieving a more sustainable future mobility system considering AVs requires an in-depth transport demand knowledge and adequate transport policies.

The Attitudes towards Autonomous Vehicles in a Medium-Sized Academic-Dominated U.S. Metropolitan Area With Cold Winters

Autonomous vehicles, AVs, as an emerging technology will contribute to fundamental changes in the transportation of cities. Medium-sized academic-dominated U.S. towns with cold winters and a large proportion of college students and employees are some of the regions with special travel patterns that may potentially contribute to a different perception of AVs. Using a stated preference survey in the two main universities in the Fargo-Moorhead area, perceived usefulness, perceived risk, and a winter-related variable defined as transportation safety improvement by AVs in inclement weather were simultaneously modeled. Given that the respondents agreed with the stated usefulness and risks of AVs, not being single was associated with an increased likelihood of agreeing with the winter-related variable for the respondents above 25. Low income households were associated with a 25% increase in the likelihood of agreeing with the winter-related variable for the respondents in the non-student model.

A tale of two modes: Who will use single user and shared autonomous vehicles

The two most traditional and conventional transportation modes, private vehicles, and public transit, may be disrupted due to the advent of shared autonomous vehicles (SAVs), which can offer affordable on-demand mobility solutions leading to a transformed transportation system. However, little is known about the attributes affecting mode choice decisions and the impacts of the emergence of SAVs on travel behavior. A stated preference survey consisting of choice experiments, distributed online in October and November 2017 to residents of the Chicago-Naperville-Elgin, IL-IN-WI metropolitan statistical area, is used to determine the perceived impacts that SAVs may have on mode choice decisions and the corresponding value of travel time savings. Based on a representative sample (in terms of age and gender) of 400 responses, random parameter (mixed) logit models are developed to investigate the factors that affect mode choice decisions in short- and long-term scenarios. Value of travel time savings (VTTS) is calculated using the marginal rate of substitution derived from the mixed logit models. The results indicate that the option of sharing the AV ride is not as preferable as single occupant AVs across all market segments, which may challenge the benefits that this emerging technology can bring to shared transportation modes. Further, it was found that VTTS is lower for SAVs compared to single occupancy AVs regardless of the time horizon.

Effects of trip-level characteristics on autonomous vehicle ownership: A U.S. analysis

We examined how trip-level characteristics may influence autonomous vehicle ownership decisions. Using 639 stated preference survey responses in the US, we developed an integrated choice and latent variable model linking trip- and consumer-level characteristics to AV ownership choices. Results suggested parking cost, travel cost and travel time are important predictors for vehicle ownership at the trip-level; and monthly payment, car ownership importance and autonomous vehicle safety perceptions are significant predictors at the consumer-level. By examining elasticities of vehicle ownership market shares, we found while consumer-level characteristics have the most prominent effect on vehicle ownership decisions, trip-level characteristics have a small but measurable effect. Among trip-level characteristics, parking cost has the largest impact on vehicle ownership decisions, followed by travel cost of ridehailing (both conventional and autonomous), and transit travel time. Finally, we simulated future vehicle ownership decisions under three policy scenarios by leveraging trip- and consumer-level characteristics.

Willingness-to-relocate: Examining preferences for parking relocation of privately-owned automated vehicles

Privately-owned automated vehicles (PAVs) can relocate themselves elsewhere after arriving at destinations, thereby inducing empty vehicle mile traveled (VMT) and more greenhouse gas emissions. This paper examines travelers’ preferences for PAV relocation, using stated preference surveys distributed in the Seattle and Kansas City regions in the U.S. Model results suggest that trip purpose, individual socio-economic and household characteristics, and local contexts influence PAV relocation decisions. Additionally, a willingness-to-relocate (WTR) metric is defined to represent how much time travelers would be willing to spend to relocate PAVs to save $1 in parking costs. The WTR estimates in both regions indicate the potential of induced VMT due to PAV parking relocation. Furthermore, travelers’ awareness of fuel/energy costs associated with PAV relocation does not necessarily relate to a lower WTR, depending on the region. To curb excessive empty VMT from PAV relocation, explicit disincentives, such as a VMT fee, may be needed.

Evaluating the Impact of Urban Consolidation Center and Off-Hour Deliveries on Freight Flows to a Retail District Using Agent-Based Simulation

With rapid ongoing urbanization, cities across the world face a multitude of challenges in urban logistics. Delivery of goods to retail districts is particularly challenging as these places are typically located in congested urban centers. In response, policy makers have explored various freight management initiatives, including urban consolidation centers (UCC) and off-hour deliveries (OHD). This study examines the impact of these initiatives on freight flows to a retail district in Singapore. The study approach pairs empirical behavioral models and an agent-based simulation. First, using results from a stated preference survey, the choice behavior of two relevant actors—establishments that ship goods and establishments that receive goods within a retail district—and their likelihood of participating in UCC or OHD are analyzed. Then, the resulting behavioral models are incorporated into a city-scale agent-based simulator to evaluate the impact of these initiatives on freight flows, tracking multiple logistics-related performance indicators. The results show that the likelihood of participating in UCC and OHD declines when multiple actors are involved in the participation decision. Both UCC and OHD have the potential to reduce freight traffic and parking demand, although in different ways. For UCC, a minimum level of participation must be achieved to guarantee increase in vehicle load factors. OHD decreases load factors as well as the required number of dedicated trips to the retail district.

Risk perception of earthquakes: Modeling conception of willingness to pay and prospect theory

Natural disasters have greatly threatened people's lives and properties. In recent years, disaster management has become a key issue for the sustainable development of a society. In this regard, understanding how people perceive disasters is needed to formulate better disaster management strategies and enhance the resilience of the society. This research seeks to study risk perception and relevant attitudes, which are the fundamental factors of human behavior under the threat of disaster impact. A stated preference survey is conducted to investigate people's willingness to pay for earthquake risk reduction, where the effect of information is also the concern and incorporated in survey design. Thereupon, a multiple-bounded dichotomous choice model and an ordered probit model are estimated to quantify risk attitudes toward earthquakes as the monetary value. Results suggest that factors, such as higher socioeconomic status, more family members, and the residence aged above 40 years old, have positive effects on risk perception. In addition, presenting previous earthquake disaster damage information may increase individuals' risk perception. The prospect theory is employed in the study to establish a theoretical model to capture people's risk-seeking and/or risk-averse behavior, thereby more sophisticatedly reflecting the behavioral realism related to disaster preparedness. Based on the improved understanding of risk perception and relevant attitudes, the associated authorities may be able to develop solid resilience-enhancement programs and more effectively strengthen disaster response efficiency, thereby minimizing the damages and injuries caused by earthquakes.

Impact of High-speed rail on air travel demand between Dallas and Houston applying Monte Carlo simulation

High-speed rails (HSR) are common in Europe and Asia, but the U.S. still does not have an operational HSR network. Subsequently, literature on HSR in the U.S. socio-spatial context is very limited. To address this gap in the literature, we focus on the Dallas-Houston HSR project, planned to provide service in 2026, to investigate the critical attributes travelers consider when choosing between air and HSR. This study also explores the potential impacts HSR would have on airlines sharing this route. To examine these attributes and the potential effects of this HSR, we performed a stated preference survey, discrete choice analysis, and applied Monte Carlo simulation. Our results show that service frequency is an essential factor for travelers choosing a mode of transportation between Dallas and Houston. A potential competition and cooperation opportunity exist between airlines and HSR on this corridor.