Stated Preference Survey Research Articles

Patients' Preferences for Dosing Frequency and out-of-Pocket Cost Associated with Iron Chelators: A Mixed-Methods Pilot Study in the United States

Patients with sickle cell disease, thalassemia, and other anemias who require regular red blood cell transfusions are at risk of developing iron overload. Excess iron accumulates in tissues and vital organs, such as the liver, heart, and pancreas, causing end organ damage with significant morbidity and higher risk of early mortality. To offset the negative impacts of iron overload, patients are often prescribed iron chelators; however, little is known about what is important to patients when choosing between therapies, including the impact of dosing frequency or cost. The primary objective of our study was to develop and examine the comprehension of a patients' health preference survey regarding the dosing frequency of hypothetical oral iron chelators and the impact of the associated out-of-pocket costs. We hypothesized that patients would prefer iron chelators administered less frequently with some tradeoffs related to cost. The secondary objective was to explore potential reasons for preferring a less frequent dosing schedule to inform a larger-scale online preference study. A stated-preference survey using a direct elicitation approach was developed and tested in one-on-one, semistructured cognitive interviews with eight adults recruited through L&E Research, a market research firm specializing in healthcare. Patients with sickle cell disease, thalassemia major, or other anemias requiring frequent blood transfusions and who have experience with an iron chelator were invited to participate in an online interview. The survey instrument included a trade-off scenario involving a choice between two hypothetical oral iron chelators. Participants were told to assume that the medicines were just as safe and effective as their current iron chelator and could be taken either twice a day or three times a day. The survey also included questions to help explain preferences and understand the impact of out-of-pocket costs on treatment choice. During the interviews, we followed the “think aloud” approach where participants were asked to read the draft survey aloud, provide answers to the questions, and discuss or explain their interpretations of the information and the motivation behind their answers to selected questions. Open-ended, probing interview questions were used to explore participants' responses further. Qualitative data were generated through interview participants' verbatim accounts of their decision-making. The interviewer and the research team interpreted the qualitative data and made notes and observations to refine the survey instrument between interviews in an iterative process of updating and retesting. Quantitative data were generated through responses to the survey questions and were summarized using descriptive statistics. The median age of participants was 39 years old (25th percentile: 37 years; 75th percentile: 44 years), and most identified as female (n=7, 87.5%). Five participants were currently taking an oral iron chelator at the time of the interview, but the length of time on treatment varied from less than 6 months (n=2) to 2-5 years (n=3). When asked to choose a hypothetical oral iron chelator, all participants chose oral tablets that would be taken twice daily. The most common reasons for choosing a less frequent dosing schedule included dislike of taking a lot of pills (n=6), not having to remember to take pills (n=5), and not having to carry as many pills with them (n=4). When asked whether they would still choose oral tablets taken twice daily when the monthly out-of-pocket cost was $50, all but one participant switched to oral tablets taken three times a day. Qualitative data suggested participants accepted the hypothetical context of the preference scenarios, and the survey instrument was generally well understood. Participants also reported several other reasons for preferring a less frequent dosing schedule, which will all be included as response options in the final survey. Although patients indicated a preference for an iron chelator administered less frequently two times a day versus three times a day, choice was affected by the out-of-pocket cost of treatment. The results of our pilot mixed-methods interview study supported patients' comprehension of the health preference survey, which will be administered online to a larger sample to further explore preferences for dosing frequency and out-of-pocket costs of oral iron chelators.

The role of travel satisfaction and attitudes toward travel modes in the prospect of adoption of urban air taxis: Evidence from a stated preference survey in Tehran

Urban air mobility (UAM) is a new mode of transportation which has the potential to curb congestion in urban areas by providing a fast alternative that bypasses surface-level traffic by employing low altitude urban airspace. However, the successful adoption of this innovation among other modes of transportation remains a critical challenge, as public acceptance plays a pivotal role in the uptake of any emerging technology or service. To transcend traditional ground transportation, it is imperative to investigate the factors that drive a transition from current modes, particularly private cars, to the utilization of urban air taxis (UATs). While prior research has explored different aspects of UAM adoption, there is a notable dearth of studies examining the influence of travel satisfaction and attitudes towards travel modes on the preference for UAM. Notably, existing transportation literature has established that both satisfaction and attitudes significantly shape travel behavior. To achieve this, a stated preference survey was conducted in the Tehran metropolitan area, and a multinomial logit model incorporating latent variables was developed to assess the influence of socio-demographic and psychological factors on UAM adoption in hypothetical scenarios with predetermined travel times and costs. The findings highlight the pivotal role of service cost and affordability, with individuals of higher incomes exhibiting a significant inclination toward UAT adoption. The adoption of UAT is significantly higher when the cost is comparable to the existing modes. Moreover, satisfaction components, specifically enjoyment and time-saving benefits, exert a significant influence on UAT preference. Unfavorable perceptions towards private cars and ride-hailing services positively contribute to the likelihood of preferring UAT, with a greater impact observed for negative attitudes towards ride-hailing. The study explicitly underscores the influence of travel satisfaction and attitudes towards conventional modes of transportation on the adoption of innovative alternatives such as air taxis within the context of mode choice scenarios.

Effects of proactive and reactive health control measures on public transport preferences of passengers – A stated preference study during the COVID-19 pandemic

The outbreak of COVID-19 has caused unprecedented disruptions to public transportation services, passengers' mode choice preferences, and their behavioral pattern. Recent studies have updated the systemic shift from shared travel to private mode due to the perceived higher health risk of shared mobility. However, findings from these studies may not be applicable to public transport-oriented cities with very low rate of private car ownership. In the long term when we arrive at a stabilized ‘New Normal’, the need to promote public transport is likely to be re-emphasized with high priority. This study presents insights into the factors affecting public transport (PT) preferences and potential modal shifts within various modes of PT when proactive and reactive health control measures are implemented. An online stated preference survey was conducted in Hong Kong, where public buses, public light buses, MTR, and taxis are the popular modes of public transport. The regret-based panel mixed multinomial logit model was applied in this study, aiming to capture individual’s regret aversion psychology in the context of the COVID-19 pandemic. The results of our random regret model suggest that travelers generally have lower regrets for the chosen mode when having passenger temperature screening, COVID tracing app, and more frequent disinfection, while seem to be unaware of the in-vehicle air quality. Interaction effects between health control measures and personal characteristics (e.g., age and risk attitudes) were also considered. Trip characteristics, including in-vehicle crowding level, fares, in-vehicle travel time, waiting time at a station, walking time, and trip purpose, were found to influence passengers' choices of travel modes. Policy simulations of possible changes in public transport modal preferences in the presence of various health control measures have also been undertaken. The findings suggest that overall health control measures are appreciated by passengers and do align with promotion of a return to public transport use. However, their effects are quite moderate and should be selectively used for different transport modes. Increasing service frequency can be a promising solution, which reduces crowding and waiting time of passengers using public transport modes, and reduces virus transmission risk. This study contributes to a better understanding of public acceptance and preference toward health control measures in public transport, and call for in-depth cost-benefit analysis in the related fields so that better response can be made in possible future public health crisis.

잠재선호 조사를 이용한 자율주행 수요대응형 대중교통 서비스 수락률에 관한 연구

잠재선호 조사를 이용한 자율주행 수요대응형 대중교통 서비스 수락률에 관한 연구

Evaluation of Stated Preference Surveys with Statistical Methods

In this paper, the author investigated the stated preference survey in transport modelling. The research was conducted to ensure that the best fractional orthogonal design of stated preference paired comparison survey would not increase the error or uncertainty in transport-related decision modelling. The research was conducted based on artificial Monte Carlo simulated respondents, and the results were assessed with standard mathematical-statistical tools. Although the assessment should have resulted in 0% errors, according to our 2,000 sample, a minor 5% of errors occurred. The problem to be investigated in this paper is that the best-designed survey could have some errors.

Influence of Psychological and Socioeconomic Factors on Purchase Likelihood for Autonomous Vehicles: A Hybrid Choice Modeling Approach

This study looks into how psychological and socioeconomic factors interact to affect people’s propensity to purchase autonomous vehicles (AVs). Inspired by the Technology Acceptance Model, six psychological variables—social influence, convenience, perceived utility, perceived ease of use, perceived risk, and usage attitude—are proposed. Twenty-two measurement variables are introduced because it is difficult to measure these latent factors directly. To understand the link between the latent variables and calculate their factor scores, a structural equation model is created. The latent variables, along with observable socioeconomic attributes, are included as explanatory variables in a mixed logit model to estimate the purchase likelihood for AVs on different levels. A stated preference survey is conducted for data collection. We obtained 302 effective samples. The experiment results demonstrate that perceived usefulness has the most significant positive impact on purchase likelihood, followed by social influence and perceived ease of use. However, perceived risk has a significant negative impact on the purchase likelihood. Individuals with less driving experience and those without a motor vehicle driving license are more inclined to adopt autonomous vehicles. Additionally, there is a substantial correlation between the frequency of car use and the propensity to support the deployment of autonomous vehicles.

How consequential is policy consequentiality? Evidence from online discrete choice experiment with ornamental plants

Stated preference surveys often employ policy consequentiality scripts to examine respondents’ concern for the policy in question and their belief in the impact of their responses on the provision of the respective good. In this study, we used an online choice experiment to investigate how perceptions of policy consequentiality influence individual preferences regarding ornamental plants cultivated with or without neonicotinoid insecticides. The role of policy consequentiality was examined between the control and treatment group and by levels of ex-post perceived consequentiality groups. Our findings indicate limited support for the notion that ex-ante consequentiality treatment mitigates hypothetical bias and choices to opt out. However, participants exhibiting higher levels of ex-post consequentiality perceptions displayed a reduced likelihood of opting out compared to those with lower levels. Furthermore, we found a sharp distinction in plant choice outcomes and elicited willingness-to-pay (WTP) between those who believed their responses were consequential and those who did not, in line with the predictions of the knife-edge effects. In contrast, participants attributing some degree of consequentiality to the survey results exhibited comparable behavior. These results suggested that the effects of policy consequentiality on consumer choices and WTP can be mixed in choice experiments involving private goods.

Road crossing behavior and preferences among pedestrians: From the lens of the theory of interpersonal behavior

Objective As a major safety intervention, infrastructural facilities such as footbridges, underpasses or signals are provided for pedestrians to remove their direct interactions with vehicles and consequently ensure safe crossing as they attempt to cross roadways. Interestingly, it is evident that even within the proximity of footbridges or underpasses, some individuals are more willing to take the risk of crossing at-grade even where there are no signals or crosswalk markings to separate their movement from vehicles. These crossing alternatives may have different utilization depending on location and road user types. Therefore, sustainable crossing facilities are needed to meet pedestrian needs. This study attempts to investigate the factors that influence pedestrians to avoid provided footbridges and engage in at-grade crossing behaviors. Methods The crossing point preference is an interpersonal behavior which is a multifaceted and complex phenomenon involving conscious (intentions) and subconscious (habits) factors. This study employs Triandis’ Theory of Interpersonal Behavior (TIB) as a theoretical framework and structural equation modeling to achieve study objectives. Pedestrians were intercepted randomly and socio-demographics, trip characteristics and perceptions data collected through a stated preference survey. Results Perceived consequence, affect, and social factors were found as significant antecedents of at-grade crossing intentions. Habits and facilitating conditions significantly moderate the impact of crossing intentions on actual at-grading crossing behavior. Pedestrians’ perceived consequence was found to significantly mediate the impact of social factors and affective factors on intention to cross at-grade. Apart from gender, age, satisfaction with footbridge features, work trips, and crossing frequency were all significant determinants of actual crossing at-grade behavior. Conclusions The study findings can help road safety agencies provide acceptable sustainable facilities that will be used by pedestrians to ensure that the purpose of investments toward pedestrian crossing safety is achieved. Effective road safety education and awareness campaigns on negative consequences of crossing at-grade, while highlighting the benefits of using provided footbridges are suggested to be undertaken by government agencies.

The application potential of Mobility as a Service (MaaS) at mega events: A case study of Hangzhou 2022 Asian Games

The hosting of mega sporting events will cause an ample increase in travel demand, causing an imbalance between supply and demand, so effective mobility management is essential. Mobility as a Service (MaaS) embodies a novel sustainable mobility paradigm and breathes fresh blood into mobility management. This work aims to reveal the potential acceptance of MaaS in the spectating context as well as the factors influencing the subscription of MaaS bundles, and to discuss the application of MaaS for mobility management at mega events. In the setting of the Hangzhou 2022 Asian Games, an online stated preference survey was conducted in mainland China regarding the entire travel process during the spectating period. Two mixed logit models were employed to analyze the choices of MaaS bundles in Airport/High-Speed Rail Station pick-up and drop-off (APD) scenario and Hotel-Venue (HV) scenario, respectively. Estimation results indicate that about 80% of the respondents are willing to subscribe to MaaS bundles and MaaS is capable of being used for mobility management. Household structure and income, as well as modality styles in daily and tourism, have significant impacts on the subscription intention of MaaS bundles. The results also show that respondents are sensitive to the subscription fees of MaaS bundles. Behavioral inertia is clearly demonstrated in the choice of APD MaaS bundles and obvious preference heterogeneity exists among respondents concerning the travel modes included in HV MaaS bundles. The findings from this study provide valuable information and strategies for transportation planners, event organizers, and those involved in the tourism sector. These insights can facilitate the implementation of personalized and sustainable smart mobility services during events or in tourism, enhancing the overall mobility experience.

Proactive Coordination of Traffic Guidance and Signal Control for a Divergent Network

In the realm of transportation system optimization, enhancing overall performance through the proactive coordination of traffic guidance and signal control in a divergent network can tackle the challenges posed by traffic congestion and inefficiency. Thus, we propose an innovative approach to first allow the information on variable message signs (VMS) that deviates from estimated travel times. This proactive approach guides drivers towards optimal routes from a system-wide perspective, such as minimizing vehicle hours traveled. The deviation is constrained both by the lower bound of drivers’ long-term compliance rate and the upper bound of the favored traffic signal operation. The proposed approach coordinates the traffic guidance system with the signal control system. The traffic signal control system sets the upper limit for information deviation in the traffic guidance system, while the traffic guidance system provides demand predictions for the traffic signal control system. Overall, the objective function of the approach is the network-level performance of all users. We gauge traveler satisfaction as a measure of system credibility, using both a route choice module and a satisfaction degree module established through stated preference surveys. Numerical results demonstrate that proactive-coordinated (PC) strategies outperform reactive-coordinated (RC), proactive-independent (PI), and reactive-independent (RI) strategies by improving the system performance, meanwhile keeping the system trustworthy. Under the normal traffic scenario, the PC strategy reduces total travel time by approximately 10%. Driver satisfaction with the PC strategy increases from a baseline of 76% to 95%. Moreover, in scenarios with sudden changes in either traffic demand or supply, e.g., accidents or large events, the proactive guidance strategy is more flexible and can potentially improve more from the system perspective.

Adoption of electric vehicles by young adults in an emerging market: a case study from Argentina

ABSTRACT The destiny of the electric vehicle (EV) marketplace will depend upon the behaviour of potential buyers and on how emerging markets allow EVs to be perceived as a mobility solution to the externalities generated by internal combustion (IC) vehicles. To this end it is important to ascertain the role played by psychological factors, along with instrumental attributes, especially among younger adults (future purchasers) in not yet mature markets. Our paper analyses and models the propensity to purchase an EV with respect to an equivalent IC vehicle. It contributes to the existing literature investigating younger adults’ behaviour in an emerging market, focusing on the role of attitudes and perceptions. A stated preferences survey, built on real commercial scenarios (Renault ZOE vs Renault Clio), was designed and disseminated at the University of Cordoba (Argentina). Respondent behaviour was modelled within the random utility paradigm. First, heterogeneity among users was investigated through mixed multinomial logit formulation; The role of psycho-attitudinal factors was then explored through the specification of hybrid choice models with latent variables. Estimation results indicate the significant role of attitudes and perceptions in emerging markets.

Pre-peak fare discount policy for managing morning peak demand of interregional bus travel: a case study in Seoul metropolitan area

ABSTRACT Pre-peak fare discount policies have become increasingly common in urban transit services and show potential to spread morning peak-hour demand. This study analyzes the departure time choice behavior of interregional bus passengers during morning hours. A mixed logit model is applied to estimate the probability of shifting departure time as a function of fare discount rate, in-vehicle congestion, and other influential factors, accommodating heterogeneity of passenger preferences. The analysis data are obtained through a stated preference survey, which is conducted to passengers who regularly use the interregional bus in Seoul metropolitan area. Choice models are segmented by departure time periods (peak, pre-peak, and post-peak) and occupation types (fixed time worker, flexible time worker, and student). Marginal utilities of the unobserved preferences are estimated to suggest policy implications. From the experimental analysis, target passengers for shifting departure time during peak hour are suggested as flexible time workers and students.

How will China–Singapore International Land–Sea Trade Corridor affect route choice behaviour? A discrete choice model

Under the government-to-government cooperation framework, the Memorandum of Understanding (MoU) on China–Singapore International Land–Sea Trade Corridor (C–S-ILSTC) between Singapore and Chongqing has been signed in 2018, with the objective to improve the connectivity between Southeast Asia and Western China region via the Beibu Gulf port. C–S-ILSTC provides a new and efficient intermodal freight transportation route choice, which is expected to reconstruct the regional intermodal container transportation network. In this study, we formulate a discrete route choice model based on stated preference survey to analyse the route choice behaviour between Southeast Asia and western China region under the intermodal container transport network with C–S-ILSTC. Based on the modelling results, we further discuss the impact of significant route choice influential factors, such as transit time, shipping fee, cargo type, historical experience of using the route, company size, annual throughput, and business area. In addition, descriptive statistics and word cloud analysis are provided to investigate respondents’ underlying attitudes on the most important route choice influential factors. Scenario analysis is further conducted to demonstrate the impact of subsidy on respondents’ willingness to switch to the newly introduced C–S-ILSTC for freight transportation. The results provide policy implications on improving the utilisation rate of C–S-ILSTC.

Determinants behind the acceptance of autonomous vehicles in mandatory and optional trips

Due to the potential of automated vehicles (AVs) to change the transportation system radically, it is essential to investigate the factors affecting users’ intention to use them. Although previous studies have mostly focused on the latent variables of the internal schema of beliefs, this paper aims to examine the impact of internal and external factors by integrating the variables of the unified theory of acceptance and use of technology along with environmental concerns and perceived risk. Moreover, the effects of latent variables are also compared for different trip purposes (mandatory and optional), which have received less attention in previous studies. Using a stated-preference survey, 641 valid responses from citizens of Tehran, Iran have been collected. The estimation results of structural equation modelling show a significant difference between the determinants of AV acceptance across mandatory and optional trips. The estimated coefficients indicate that social influence and performance expectancy are the strongest explanatory factors in the intention to use AVs in optional and mandatory trips, respectively. However, no significant difference is observed for the impact of environmental concerns on the intention to use AVs across both trip types.

Stated Preference Approach for Measuring the Perceived Benefit to Drive-Alone Users If They Switch to Park and Ride: An Indian Perspective

Park and ride facilities can be a potential instrument for addressing the rising congestion problems and ensuring sustainable urban mobility in major Indian cities, equipped with fast and excellent metro systems. The present study attempts to understand the travel behavior of commuters (four-wheeled private vehicle users only) in relation to the introduction of park and ride as a sustainable and economical alternative mode of travel to driving alone in a private vehicle in the context of Delhi, India. The present study measures the perceived benefit to drive-alone users in Delhi with regard to their willingness to pay (WTP) for switching to a better-quality park and ride service instead of using their private vehicles. Choice-based responses along with socioeconomic and travel information were collected from 559 drive-alone users using a tablet-based stated preference survey instrument. The responses were then analyzed using a multinomial logit (MNL) model. Further, WTP estimates of the noncost attributes were calculated to derive the perceived benefit to drive-alone users if they were to switch to using a park and ride service. The study also developed a generalized cost (GC) equation using the parameter and WTP estimates derived from the MNL model. Finally, the study conducted a post-estimation analysis using the GC equation to examine the influences of identified explanatory attributes on the GC for drive-alone users who switched to park and ride. “Trip length,”“parking cost,” and “parking type” exerted a significant influence on the generalized cost, indicating that drive-alone users could expect considerable savings (perceived benefit with regard to utility gain) if they were to choose park and ride.

Visitors’ willingness to pay for ecosystem conservation in Grenada

Understanding visitors’ willingness to pay (WTP) for natural ecosystems can assist policymakers in managing the environmental assets that form the foundation of nature-based tourism. To earn the highest economic return from limited budgetary resources, tourist-dependent destinations must identify sustainable sources of conservation funding and prioritize spending across ecosystems and initiatives. The purpose of this study is to assess the potential for visitor donations to serve as a source of conservation funding and investigate preferences and willingness to pay for multiple ecosystems concurrently, using data from a stated preference survey administered in Grenada, a small island state in the southern Caribbean that relies on nature-based tourism. Results from a discrete choice experiment and a contingent valuation exercise reveal a reluctance to donate to conservation initiatives by more than half of respondents. Visitors place the highest value on improvements to coral reefs, followed by rainforests, mangroves, and beaches. Average willingness to donate to a conservation trust fund ranged from US $8.00 to US $15.00, and from US $17.00 to US $52.00 for conservation plans targeting improvements to specific ecosystems. Few factors are found to be associated with willingness to pay. Scale heterogeneity may be a more significant source of variation than preference heterogeneity.

Quantifying perceived social benefit of bicycle-friendly infrastructure in Indian cities: Patna as a case study

The Indian central government has been trying to promote the use of bicycles in the Indian cities acknowledging its potential as a sustainable mode of transport. At the urban administrative level, however, there seems to be skepticism in accepting bicycle infrastructure development as an objective to be invested in. To overcome this, the urban local bodies need to be informed of the perceived social benefits of bicycle infrastructure as a rationale for investing in it. This study identifies the commuters’ idea of favourable cycling conditions through a discrete choice experiment conducted in Patna. Different sets of choice alternatives based on different levels of the six identified factors are presented to the commuters using a Stated Preference survey, and their choice data is collected. Using the Multinomial Logit Model, the coefficients and the willingness-to-pay (WTP) values for different levels of factors are determined. The WTP values depict the quantified perceived social benefit of bicycle-infrastructure development in Patna. Findings from the present study show that a reduction in Trip Length has the highest WTP, followed by better route visibility, segregation from motorized vehicles, improvement in road surface quality, and integration with Public Transport.

Are consumers no longer willing to pay more for local foods? A field experiment

AbstractGovernment programs promoting locally produced foods have risen dramatically. But are these programs actually convincing consumers to pay more for locally produced food? Studies to date, which have mostly relied on hypothetical stated preference surveys, suggest that consumers will pay premiums for various local foods and that the premiums vary with the product and presence of any geographic identity. This study reports results from a large field experiment involving 1,050 adult consumers to reveal consumers’ willingness to pay (WTP) premiums for “locally produced” foods – mushrooms and oysters. Despite strong statistical power, this study reveals no positive effect of the locally produced label on consumer WTP. These null results are contrary to most of the existing literature on this topic. The finding that consumers are not willing to pay more for local foods has important implications for state and federal agencies that promote labeling campaigns that seek to increase demand and generate premiums for locally produced foods.

A study on the factors influencing the adoption of urban air mobility and the future demand: Using the stated preference survey for three UAM operational scenarios in South Korea

This study analyzed commuters’ intention to use urban air mobility (UAM) and the future demand for UAM based on its service characteristics and the personal characteristics of the potential users. The Seoul Metropolitan Area (SMA) was selected as the study area as it is expected to have the highest demand for UAM in South Korea. Three UAM operation scenarios were set: short-distance intra-city trips, long-distance intra-city trips, and inter-city trips. Five alternatives were assumed for the stated preference (SP) survey: bus, subway, taxi, private car, and UAM. Six alternative-specific variables were selected: access time, waiting time, boarding time, cost, autonomous mode, and the presence of other passengers. An online survey of 300 residents of SMA was conducted with 100 residents for each scenario. The residents were briefed on the modes of transportation and service characteristic of alternatives. The analysis results were as follows: (1) cost and access time significantly influenced the intention to use UAM in all scenarios. However, the effects of waiting time, boarding time, and autonomous driving on intention to use UAM differed based on the scenarios; (2) the individual characteristics of potential users had varying effects on their preference for UAM depending on the scenarios and the means of transportation, which was a counterpart to UAM. (3) The probability of choosing UAM for commuting was expected to be 10–20%, with the highest modal split for long-distance intra-city trips and the lowest modal split for short-distance intra-city trips. Among the six alternative-specific variables, autonomous driving and cost had the most significant effect on the change of the probability for using UAM. The results of this study are expected to be used as basic data for designing an effective strategy for the introduction of UAM in South Korea.

Modeling Choice Behaviors for Ridesplitting under a Carbon Credit Scheme

Ridesplitting, a form of shared ridesourcing service, has the potential to significantly reduce emissions. However, its current adoption rate among users remains relatively low. Policies such as carbon credit schemes, which offer rewards for emission reduction, hold great promise in promoting ridesplitting. This study aimed to quantitatively analyze the choice behaviors for ridesplitting under a carbon credit scheme. First, both the socio-demographic and psychological factors that may influence the ridesplitting behavioral intention were identified based on the theory of planned behavior, technology acceptance model, and perceived risk theory. Then, a hybrid choice model of ridesplitting was established to model choice behaviors for ridesplitting under a carbon credit scheme by integrating both structural equation modeling and discrete choice modeling. Meanwhile, a stated preference survey was conducted to collect the socio-demographic and psychological information and ridesplitting behavioral intentions of transportation network company (TNC) users in 12 hypothetical scenarios with different travel distances and carbon credit prices. Finally, the model was evaluated based on the survey data. The results show that attitudes, subjective norms, perceived behavioral control, low-carbon values, and carbon credit prices have significant positive effects on the choice behavior for ridesplitting. Specifically, increasing the carbon credit price could raise the probability of travelers choosing ridesplitting. In addition, travelers with higher low-carbon values are usually more willing to choose ridesplitting and are less sensitive to carbon credit prices. The findings of this study indicate that a carbon credit scheme is an effective means to incentivize TNC users to choose ridesplitting.