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• A behavior intervention architecture was applied in the traffic safety field. • The concept was explored by conducting a survey with 1054 respondents in Japan. • Nudge Theory could effectively nudge drivers to use driving tracking. • Different demographic groups should be nudged with different nudge techniques. Driver tracking has the potential to improve driving skills and reduce traffic accidents. Nudging drivers toward the widespread utilization of driver tracking holds significant potential for enhancing traffic safety. Nudge approach gained popularity by changing environmental factors through careful design and guiding people to make certain choices under non-mandatory conditions. This research is dedicated to examines the impact of nudge approach on driver's willingness to use driver tracking across different age, marital, and income groups. Survey data were collected from a sample of 1054 respondents throughout Japan in 2020. Together with the PLS-SEM model and multigroup analysis, results reveal that (1) natural consequences, comparison of behavior, shaping knowledge, covert learning, identity nudge approaches could all have positive impact on driver's willingness to use driver tracking; (2) it is significantly effective to deploy shaping knowledge nudge approach for the drivers under 50 years old to encourage them to use driver tracking; (3) natural consequence nudge approach is more suitable for drivers older than 50 years old, while the convert learning nudge approach is more appropriate for drivers younger than 50 years old; (4) natural consequences nudge approach is more effective in influencing the willingness of unmarried respondents to use driver tracking, while the covert learning nudge approach is more effective in influencing the willingness of married respondents; (5) comparison of behavior nudge approach is 2 times more effective at persuading drivers to use driver tracking for the higher income group, while driver's identity nudge approach is 2 times more effective for the lower income group. These findings provide valuable insights for drivers, companies, and governments with a superior nudge approach to enhance driving skills, which is beneficial for improving traffic safety. [ABSTRACT FROM AUTHOR]

The built environment is a structural determinant of health. Here we reveal spatially heterogeneous associations of built environment indicators with objective health outcomes (morbidity) by combining a random forest (RF) approach and a multiscale geographically weighted (MGWR) regression method. Using data from six Japanese cities, we found that the ratio of morbidity has obvious spatial agglomerations. The mixed land-use diversity with 1000 m buffer, distance to hospital, proportion of park area with 300 m buffer, and house price with 2000 m buffer, negatively affect health outcomes at all locations. For most locations, high PM2.5 or high floor area ratio with 2000 m buffer are linked to a high ratio of morbidity. Our findings support the use of such data for long-term urban and health planning. We expect our study to be a starting point for further research on spatially heterogeneous associations of the built environment with comprehensive health outcomes. [ABSTRACT FROM AUTHOR]

This paper compares the energy consumption of elderly and non-elderly households, recognizing the ever-increasing importance of the aging population for energy policy. Decisions of the domestic (in-home) and transport (out-of-home) sectors at the household level are jointly incorporated by building a multivariate Hierarchical Archimedean Copula model with intra-sector and inter-sector dependencies. Data from a life-oriented behavioral survey in Japan are used, which includes 532 elderly households and 340 non-elderly households. A variety of life-related factors, together with built environment factors, are introduced into the above model. Modeling analysis results show that inter- and intra-sector dependencies are heterogeneous across households in terms of these factors. It is found that almost equal numbers of influential factors are sensitive and insensitive to age-based sample segmentation. Various similarities and dissimilarities across energy types between elderly and non-elderly households are revealed. The paper concludes with a discussion of the policy implications of the results. [ABSTRACT FROM AUTHOR]

To design effective policies against COVID-19, there is a need for more evidence-based research. However, associations between actual policies and temporal behavior changes have remained underexplored. To fill this important research gap, a nationwide retrospective life-oriented panel survey on individuals' behavior changes from April to September 2020 was implemented in Japan. Reliability of information sources, risk perceptions, and attitudes toward policymaking were also investigated. Valid data were collected from 2643 respondents residing in different parts of the country. Risks were reported about general infections and public transport use. Attitudes toward policymaking were mainly about policymaking capacity and PASS-LASTING based policy measures. A dynamic structural equation model (DSEM) was developed to quantify dynamic associations between individuals' behavior changes over time and subjective assessments (i.e., attitudes) of policymaking. Survey results revealed that behavior changes are mostly characterized by avoidance behaviors. Modeling estimation results showed a statistically-significant sequential cause-effect relationship between accumulated behavior changes in the past, subjective factors, and the most recent behavior changes. The most recent behavior changes are mostly affected by accumulated behavior changes in the past. Effects of subjective assessments of policymaking on the most recent behavior changes are significant but moderate. Among attitudes toward policymaking, attitudes toward policymaking capacity are more influential than willingness to follow PASS-LASTING based policy measures. High risks of using public transport are found to significantly influence the most recent behavior changes, together with other risk perception factors. Insights into effective COVID-19 policymaking are summarized. [Display omitted] • A nationwide life-oriented panel survey was implemented online in Japan in 2020. • Various behavior changes are mostly characterized by avoidance behaviors in Japan. • Impacts of risk perception during the use of public transport are revealed. • Impacts of policymaking capability on activity-travel behaviors are confirmed. • Impacts of PASS-LASTING policies on activity-travel behaviors are confirmed. [ABSTRACT FROM AUTHOR]

This study evaluated the characteristics of individuals with voluntary behavioural changes (cancellation and postponement of bookings) during the early stages of the coronavirus disease 2019 (COVID-19) outbreak in Japan. In addition, the temporal trends of these changes were captured. A cross-sectional analysis and a time series analysis were conducted. A nation-wide retrospective panel survey was conducted at the end of March 2020 (n = 1052). Odds ratios for cancellations/postponements with respect to individual characteristics were calculated in the analysis. To determine the temporal trend, the incidence ratios were compared throughout the time series analysis for four time periods: period 1, before the announcement of the Public Health Emergency of International Concern (PHEIC) from the World Health Organisation (WHO) (January 1–31); period 2, after the announcement of PHEIC (February 1–26); period 3, after the announcement of school closures by the Japanese government (February 27 – March 11); and period 4, after the announcement of the pandemic by the WHO (March 12–31). In total, 72% of respondents cancelled or postponed their bookings at least once, and about half of the changes occurred in period 3. Elderly individuals' changes in gatherings were, on average, 5.9 times (95% confidence interval [CI] 1.9 – 17.9) higher than those of young individuals. The incidence rate of change in gatherings during period 3 was 7.11 times (95% CI: 5.16 – 9.81) higher than in period 2 and 3.15 times (95% CI: 2.25 – 4.43) higher than in period 4. Significant interaction terms were observed in age and residential city size, but not sex, of the respondents. A significant proportion of the Japanese population voluntarily changed their behaviour during the early stages of the COVID-19 outbreak, and the government's announcement of school closures was a key trigger during this time. [Display omitted] • Temporal behavioural changes for the coronavirus disease 2019 outbreak in Japan were evaluated. • A high percentage of the population had voluntarily initiated behavioural changes. • Differences in behavioural changes were observed across individual characteristics. • The government announcement for school closures was a key trigger for behavioural change across all ages. • Significant interaction effects between time periods and characteristics were observed. [ABSTRACT FROM AUTHOR]

Use of smartphone apps to detect driving risks and/or provide warning information to drivers is a hot topic in traffic safety research. However, scientific evidence on the effectiveness of such apps to reduce dangerous driving is still limited. To provide additional insights, this study examines whether and how driving risks diagnoses and real-time warning information provided through a smartphone app could assist drivers to control their vehicles on expressways safely. For this research purpose, a 3-month driving experiment was conducted in Japan, where the different combination and utilization of app functions were investigated. During the experiment, a series of questionnaire surveys were also carried out in response to six different app versions. A bivariate ordered probit model was estimated to jointly represent speed limit compliance and acceleration/deceleration simultaneously. Model estimation results show that with the warning information provided via the smartphone app, it is more effective to improve drivers' performance on speed limit compliance than on acceleration/deceleration control. The app improves speed limit compliance and acceleration/deceleration control of careless drivers but only improves speed limit compliance of irritable and excessively confident drivers and acceleration/deceleration control of aggressive drivers. Finally, implications of analysis results to traffic safety measures are discussed. [ABSTRACT FROM AUTHOR]

As an additional effort for exploring the unknowns about the ownership behavior of autonomous vehicles (AVs), we implemented an online stated preference (SP) survey in Japan and collected 1728 responses from car users across the whole country in 2016. The SP choice set included three types of AVs (conditional, high, and full automation) and a conventional vehicle. Each respondent answered three SP profiles. SP Attributes of AVs (additional purchase cost, reduction rate of insurance, reduction rate of permanent parking cost, penetration rate in the market, and release timing to the market) were defined relative to the conventional vehicle. Changes in future income were assumed based on each respondent's historical trend for assisting him/her to show more realistic responses. It was found that on average, respondents are willing to pay an additional 402,233 to 793,611 JPY to purchase an AV in the future. Estimating a mixed logit model with repeated choices and correlations between random-effect parameters following a normal distribution confirmed the significant influence of unobserved and correlated heterogeneities with respect to SP attributes. Both expected and unexpected results with respect to the random-effect variables are observed. Policy implications of analysis results are discussed. [ABSTRACT FROM AUTHOR]

Abstract It is essential to better understand the opinions and behaviors of various stakeholders (e.g., persons in companies, customers, government, and local community) when taking effective traffic management and operation measures. Existing studies have examined the interactions between companies and customers in the context of distribution chains; however, even though the importance of other inter-agent interactions is recognized, no efforts have been made, at least in the context of inter-city truck transport routes on expressways. To fill this research gap, this study implemented a stated preference (SP) survey to managers and drivers of transport companies along the expressways in the western part of Japan in 2014–2015, where some new traffic management measures encouraging behavioral changes are investigated. As a result, we obtained 525 valid SP responses from 52 companies (one manager and several drivers from each company). Our survey results first revealed that about 60% of truck transport routes were decided by company managers, and decisions by drivers are minor. A modeling analysis based on a path-size bivariate probit model is further conducted to explicitly represent the interaction between company managers and drivers. The existence of the interaction is statistically supported. We further revealed the similarities and dissimilarities of factors affecting managers' and drivers' decisions, together with the relative importance of measures encouraging behavioral changes. Finally, we made extensive discussions about the implications of analysis results. Graphical abstract Image 1 Highlights • Interpersonal interaction (InIn) within transport company is focused on. • A path-size bivariate probit model with InIn and route-overlapping and is built. • Inter-city truck route choices are investigated using an SP data. • About 60% of truck transport routes are decided by company managers. • The roles of monetary incentives to behavioral changes are identified to be limited. [ABSTRACT FROM AUTHOR]

This study explores the direct rebound effect, which indicates the degree of increase in travel demand caused by the increasing vehicle efficiency in the private passenger transport sector. Different from the usual effect, here the direct rebound effect is not assumed to be the same for the entire population. To determine when rebound occurs and who is suffering, two types of triggers, which may lead to different rebound effects among the population, are investigated: vehicle efficiency and travel demand. The quantile regression method is adopted to measure the rebound effect and differentiate it with respect to vehicle efficiency and travel demand. Considering that the rebound effect might have diverse performance in different cities, a comparative analysis between Beijing and Tokyo is conducted. Drawing on the data collected in a household energy consumption survey in Beijing and Tokyo in 2009, the models are estimated and the results reveal significant heterogeneity of the direct rebound effect both in Beijing and Tokyo, but with a much more complicated form in Beijing. For travelers in Beijing, rebound only occurs to those people whose cars are less efficient than 15–18 km/L, and the magnitude of the rebound effect is between 31.8% and 60.2%, varying across travelers with different travel demands. In comparison, in Tokyo, only travelers with low and medium kilometers traveled have the rebound effect, and the effect is inversely related to their travel demand, ranging between 17.1% and 92.3%. The above-identified inter-city and intra-city difference in the rebound effect could contribute to the population and a spatially specific policy scheme in practice. [ABSTRACT FROM AUTHOR]

Highlights: [•] A life history survey of Japanese’s four types of biographies is implemented. [•] Residence, household structure, job/education and car ownership are targeted. [•] An exhaustive CHAID analysis is done to capture biographical interdependences. [•] Both intra-domain and inter-domain biographical interdependences are observed. [•] Both short- and long-term state dependence and future expectations are identified. [ABSTRACT FROM AUTHOR]

Highlights: [•] Direct and indirect rebound effects for private vehicle in Japan are investigated. [•] SP-off-RP method is used to identify the existence and distribution of rebounds. [•] 34% of respondents have the reallocation choices which cause rebound effect. [•] Rebound effects from vehicles are more possible to occur in domestic sector. [ABSTRACT FROM AUTHOR]

This study attempts to clarify differences in Japanese time use behaviour for people with/without responsibility for nursing care of family members by comparing the behaviour of three population groups: in-home caregivers, out-of-home caregivers and non-caregivers. The analysis is also conducted with respect to the behaviour on weekdays and weekends. After examining the differences of time use behaviour based on simple statistical tests, we develop a multilevel multiple discrete-continuous extreme value model, which simultaneously represents activity participation and time allocation. In the model, observed variations, unobserved inter-individual variations and unobserved spatial variations are distinguished. Using large-scale national time use data collected in Japan, the analysis confirms various differences of time use behaviour across the three groups, especially between in-home caregivers and non-caregivers. [ABSTRACT FROM AUTHOR]

Abstract: This paper attempts to evaluate the effects of in-vehicle warning information on drivers’ decelerating and accelerating behavior when approaching an intersection near an arch-shaped bridge, where traffic accidents have often occurred due to poor visibility. The warning information was provided with images and/or voice, triggered by the actual presence of a stopped vehicle at the downhill road section of the intersection. An on-site driving experiment was conducted on a national highway in Hiroshima City, Japan, by involving 14 university students, and it was demonstrated that dynamic information seems more effective for drivers to avoid dangerous driving situations than static information. It was also found that having only the voice-based warning information may be as effective as having both the voice and image warning information. [Copyright &y& Elsevier]

Abstract: To represent heterogeneous group decision-making mechanisms in choice behavior, this paper attempts to develop a new household discrete choice model by integrating different types of household choice models based on latent class modeling approach under the principle of random utility maximization, where household utility function at each model is defined to theoretically reflect its members’ preferences and intra-household interaction. A latent class corresponds to a particular group decision-making mechanism. The proposed model can deal with not only the choice situations where multiple household members involved in joint decision are known a priori, but also the situations where the involved members are unknown. As a case study, three types of household utility functions are dealt with: multi-linear, maximum and minimum types, in the context of couples’ car ownership behaviors. Due to the limited sample size, paired combinations of the three utilities are examined and compared. Using the data collected in two Japanese cities in 2004, the effectiveness of the proposed household decision model is empirically confirmed. It is found that changes of utility combinations result in very complicated variations in both signs and values of the model parameters and choice probabilities by multi-linear utility show small variations across different combinations. [Copyright &y& Elsevier]

Abstract: Travel behavior models assuming individual decision-making processes have been a dominant theme in transportation studies. While the assumption that an individual can decide on all relevant aspects of some types of travel behavior may be reasonable, in many other aspects household members interact before making decisions about different activities that they perform and the time that is involved. On the other hand, different types of households may show different group decision-making mechanisms. In other words, there might exist diverse intra-household interactions during joint decision-making processes. To reflect this point, this paper aims to develop a new household time allocation model based on the iso-elastic class of social welfare function, which can include different types of household utility functions as special cases (e.g., Nash, utilitarianism, autocratic and max–min types). Throughout this empirical analysis, which uses an activity diary data collected in a depopulated region of Japan, the effectiveness of the proposed model is confirmed. Furthermore, the model’s applicability in evaluating transportation policies for elderly people is examined based on a simulation analysis. [Copyright &y& Elsevier]

Autonomous vehicles (AVs) are expected to bring various changes in people's lives. Such expected changes in life may affect people's decisions on the ownership of privately-owned AVs (PAVs) and even future travel demand structure. However, such effects remained unclear due to the lack of relevant studies. By targeting young people, this study fills this research gap by implementing a nation-wide expectation and stated preference (SP) survey in Japan, by comparing with older people. In the survey, respondents first reported their expected changes in life caused by AVs and then chose the most preferred vehicle from a choice set with three types of PAVs (conditional, high, and full automation) and a conventional car. The survey was implemented in 2016 and 3,006 valid SP responses were collected from 1,002 respondents (417 are young people). It is found that young people expected more changes in life and are more likely to choose PAVs with high and full automation than older people, which is consistent with the reported willingness-to-pay. By estimating a mixed logit model with panel data, it is revealed that expected changes in life affect the two age groups' choices of PAVs. There are more inconsistent influences of expected changes in life between the two groups than consistent influences, suggesting the presence of age-related structural differences of responses to future expectations. Diverse responses to future expectations are revealed, which policy implications are discussed. The findings support a life-oriented paradigm shift of travel behavior research and cross-sectoral transport policymaking and future sustainable society design. • Young and older people respond to expected changes in life in an opposite way, mostly. • Expected increases in in-vehicle activities could promote the ownership of AVs. • Influences of young people's expected changes in life differ across types of AVs. • Expected relocation to suburbs does not necessarily encourage the ownership of AVs. • Using AV as a moving home/office/hotel does not affect the ownership of advanced AVs. [ABSTRACT FROM AUTHOR]

Aim: This study developed a risk scoring tool and examined its applicability using data from the Kihon Checklist cohort dataset for 19 months to predict the transition from no certification for long‐term care to long‐term care level 3 or above. Methods: Data were collected from 26 357 functionally independent, community‐dwelling older adults in a Japanese city who answered the Checklist in 2014 and were followed for 19 months. Individuals certified for long‐term care during the follow‐up period were classified into three levels depending on their certification status: low, moderate, and high long‐term care levels. Relationships between the Kihon Checklist domains and high long‐term care levels were examined using the logistic regression model. A score chart predicting incidents of high long‐term care levels was created to facilitate its applicability. Results: As of 2016, 971 participants were certified for long‐term care (3.7%), of which 168 (0.6%), 357 (1.4%), and 446 (1.7%) were certified as high, moderate, and low long‐term care levels, respectively. Variables associated with the certification of high long‐term care level included difficulties in activities of daily living, a decline in locomotor and cognitive function in the Kihon Checklist domains, and age. The score chart was created based on these variables and demonstrated excellent discriminatory ability, with an area under curve of 0.817 (95% confidence interval: 0.785–0.849). Conclusions: The Kihon Checklist can predict the future development of a high degree of dependency. The score chart we developed can be easily implemented to identify older adults at high risk with reasonable accuracy. Geriatr Gerontol Int 2022; 22: 797–802. [ABSTRACT FROM AUTHOR]