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Population aging is happening in many places, such as on the Chinese mainland and in Hong Kong. Hong Kong, with the second-highest percentage of older adults in Asia, is among the world's fastest-aging societies. Moreover, the city has very high transit patronage: transit trips constitute approximately 90% of all trips. Given the significance of transit in Hong Kong, improving transit services for older adults is of substantial importance. In light of this, based on the data of transit satisfaction (or perception) collected by a questionnaire survey in March 2015 (N=613), this study adopts the entropy weight method to determine the importance weights of an array of transit service quality attributes (e.g., seat availability and travel stability). Then, it performs an index-based importance-satisfaction (I-S) analysis using the outcome of the previous step as a basis to determine priorities for transit service improvement. The results show that in the view of older adults, three service quality attributes in need of improvement are seat availability, waiting conditions, and service frequency. Accordingly, the paper puts forward policy implications for further implementation. [ABSTRACT FROM AUTHOR]

Taxis provide a personalized, door-to-door, and demand-responsive service, and are an attractive transport mode for accommodating the needs of an aging population. Accessible taxis further enhance the level of comfort and accessibility by providing a larger compartment and a mechanical ramp to facilitate the boarding and alighting of wheelchairs. At present, however, both ordinary and accessible taxis are infrequently used by elderly passengers in Hong Kong, due in part to high fares and long walking and wait times. Because of these limitations, taxis cannot effectively cater for the travel demands of the elderly and hence cannot improve their mobility. In this study, 580 residents of Hong Kong aged 60 or above were interviewed regarding their decision to whether to make a trip by an ordinary/accessible taxi to attend a non-compulsory social activity in hypothetical scenarios. A total of 2320 observations were obtained and a series of binary logistic regression models were calibrated to identify the significant factors influencing the elderly's willingness-to-travel. The model results show that the older elderly and those with a lower monthly expenditure were more reluctant to travel by taxi and preferred staying home. The elderly using crutches or a wheelchair had a stronger preference for accessible taxis rather than the non-walking aid users. The findings also indicate that the elderly were more sensitive to a taxi fare subsidy based on a percentage discount than one based on a fixed discount. Policy measures related to providing an accessible taxi service and taxi fare subsidy scheme to improve the mobility of the elderly are discussed: A step-wise taxi fare subsidy scheme is recommended to integrate with current transport policy measures to look after the needs of the elderly at different ages, and a supply-side subsidy is also recommended to support local taxi operators to purchase accessible taxis and increase the fleet size to minimize the wait time of users. • Identify the factors influencing the elderly's willingness-to-travel by an ordinary/accessible taxi for social activities. • Study the heterogeneous responses of the elderly with different socio-demographic characteristics. • Investigate whether the taxi fare subsidy should be a fixed amount or a discount of a certain percentage of the fare. • Recommend an operation mechanism for the proposed taxi fare subsidy scheme. • Suggest policy measures related to an accessible taxi service and taxi fare subsidy scheme to improve the elderly mobility. [ABSTRACT FROM AUTHOR]

Numerous cities are undergoing the ageing of populations. Developing a transport system that incorporates mobility needs, preferences, and demands of elderly people is crucial to such a demographic shift. Understanding the travel behavior and characteristics of elderly people is the first and foremost step towards this goal. In stark contrast with Western car-dominant places, numerous East Asian modern cities (e.g., Hong Kong, Beijing, and Shanghai) have high levels of public transportation use. Experience gained from existing studies in the West cannot be applied to Hong Kong, a typical transit-dependent city. In light of this, based on the 2011 Travel Characteristic Survey data and Poisson and negative binomial regression models, this study identifies factors that significantly affect the number of daily trips taken by (or trip frequency of) elderly people in Hong Kong. The paper finds that both socio-demographic (e.g., age and housing type) and built environment characteristics significantly affect the trip number of elderly people. Interestingly, it is determined that car availability does not play a significant role in the trip generation process, but public transportation accessibility truly matters. This outcome remarkably differs from findings in Western car-dominant cities. Moreover, to discern whether the elderly are a homogenous group, this study estimates separate models for the young elderly (aged between 60 and 74) and the very old (aged 75 or above). It is observed that the effect of public transportation accessibility on elderly mobility varies among elderly subgroups: public transportation accessibility significantly affects the trip frequency of the young elderly, but not that of the very old. Finally, a multitude of policy measures with the aim of upgrading elderly mobility is proposed. [ABSTRACT FROM AUTHOR]

Hong Kong is a transit-oriented city with an extremely high public transportation share (approximately 90%). Additionally, in this city, the percentage of older people aged 60 or above is predicted to reach 38.0% in 2064. Thus, the provision of age-friendly public transportation is timely and enormously significant. Only with a better understanding of mobility behaviors of older people, it is possible to tailor transportation systems and optimize market strategies to cater to their actual needs and preferences. Based on the 2011 Travel Characteristic Survey data, this paper calibrates a mixed binary logit model and a conditional logit model to uncover older people's travel propensity, as well as destination and departure time choices. The findings include: (1) a host of socio-demographic variables and land-use attributes affect travel propensity; (2) owning an automobile and driving license are too weak to exert significant influence on travel propensity. This finding is in contrast with the conventional wisdom in car-dominant cities where car ownership and license-holding status are significant predictors of mobility; (3) there are random taste variations among respondents regarding travel propensity; and (4) time-constant destination and time-variant origin-destination pair characteristics influence older people's destination and departure time decisions. Based on the results, a few policy suggestions (e.g., reducing the actual and perceived costs associated with interchanges, time-varying public transport service) are discussed. We believe that these policy sights can act as a valuable reference to transportation planning which addresses the mobility of older people, especially in the metropolitan cities which provide similar public transport services. [ABSTRACT FROM AUTHOR]

• Effects of future climatic uncertainties on building retrofit decisions are estimated. • Life-cycle economics and carbon emissions are selected as the multiple objectives. • Future climatic uncertainties alter optimal values of some building retrofit measures. • Optimal infiltration standard and insulation options are susceptible to future climate. • Optimal glazing materials and shading options are not susceptible to future climate. Energy consumption of and carbon emissions from buildings, which substantially depend on outdoor climate conditions, may be susceptible to future climate change. However, how future climatic uncertainties affect decision-making regarding building energy retrofits is unclear from the life-cycle analysis perspective. This study used typical high-rise public rental housing buildings in subtropical Hong Kong as a case study to consider future climatic uncertainties under representative concentration pathway scenarios and in different general circulation models to estimate their effect on multi-objective building retrofit decisions considering trade-offs among different objectives, namely, life-cycle economics, life-cycle carbon emissions, and operational energy use impacts. The results indicate the significant influence of future climatic uncertainties on the optimal values of building energy retrofit measures. The passive house infiltration standard and thick (0.06–0.1 m) polyurethane foam insulation can be recommended for long-term future climatic conditions (RCP8.5–2065s). By contrast, optimal values of glazing materials, horizontal shading projection factors, and window-to-wall ratio are not susceptible to future climatic uncertainties. Uncertainties from different general circulation models are another notable factor affecting optimal values and retrofit options. This study reveals the importance of considering future climatic uncertainties when deciding optimal values and selecting building energy retrofit options. [ABSTRACT FROM AUTHOR]

Population aging has become a notable and enduring demographic phenomenon worldwide. Older adults' walking behavior is determined by many factors, such as socioeconomic attributes and the built environment. Although a handful of recent studies have examined the influence of street greenery (a built environment variable readily estimated by big data) on older adults' walking behavior, they have not focused on the spatial heterogeneity in the influence. To this end, this study extracts the socioeconomic and walking behavior data from the Travel Characteristic Survey 2011 of Hong Kong and estimates street greenery (the green view index) based on Google Street View imagery. It then develops global models (linear regression and Box–Cox transformed models) and local models (geographically weighted regression models) to scrutinize the average (global) and location-specific (local) relationships, respectively, between street greenery and older adults' walking time. Notably, green view indices in three neighborhoods with different sizes are estimated for robustness checks. The results show that (1) street greenery has consistent and significant effects on walking time; (2) the influence of street greenery varies across space—specifically, it is greater in the suburban area; and (3) the performance of different green view indices is highly consistent. [ABSTRACT FROM AUTHOR]

Population aging is a conspicuous demographic trend shaping the world profoundly. Walking is a critical travel mode and physical activity for older adults. As such, there is a need to determine the factors influencing the walking behavior of older people in the era of population aging. Streetscape greenery is an easily perceived built-environment attribute and can promote walking behavior, but it has received insufficient attention. More importantly, the non-linear effects of streetscape greenery on the walking behavior of older adults have not been examined. We therefore use readily available Google Street View imagery and a fully convolutional neural network to evaluate human-scale, eye-level streetscape greenery. Using data from the Hong Kong Travel Characteristic Survey, we adopt a machine learning technique, namely random forest modeling, to scrutinize the non-linear effects of streetscape greenery on the walking propensity of older adults. The results show that streetscape greenery has a positive effect on walking propensity within a certain range, but outside the range, the positive association no longer holds. The non-linear associations of other built-environment attributes are also examined. [ABSTRACT FROM AUTHOR]

Rental and vacancy dynamics in real estate markets have elicited substantial scholarly attention. Previous studies primarily focused on offices and paid much less emphasis on retail properties. Moreover, nearly all research fails to explore the causes of differences in rental and vacancy adjustment speeds. To this end, retail property rental and vacancy dynamics (1991–2017) in tourist- and local-dominant areas in Hong Kong are examined using error correction models. This study is the first to use information asymmetry theory to explain rent/vacancy adjustment speed differentials in the retail property market and investigate the change of the adjustment speeds accruing to a policy shock. The results show that both supply and demand factors influence retail property rentals. Rental adjustment is quicker in tourist-dominant areas than in local-dominant counterparts, which agrees with information asymmetry theory. The implementation of the Individual Visit Scheme hastens the rental adjustment process of tourist-dominant areas but not that of local-dominant counterparts. Finally, policy implications (e.g., adjusting the one-size-fits-all maximum loan-to-value ratio policy and enhancing tourists' accessibility to non-tourist-dominant areas) are discussed. [ABSTRACT FROM AUTHOR]

A significant increase in the older population has been observed in numerous cities. Understanding the correlates of older adults' mobility is, therefore, of critical importance to meet their needs and preferences. Based on multisource data, including Google Street View street images and Hong Kong Travel Characteristics Survey 2011 data, we developed a series of multilevel and geographically weighted logistic regression models to scrutinize the global and local associations between urban greenery (eye-level street greenery, the number of parks, and the normalized difference vegetation index (NDVI)) and the travel propensity of older adults. Notably, eye-level street greenery was assessed by using readily available street images and machine learning techniques. The modeling results reveal that eye-level street greenery has a positive effect on older adults' mobility, but the number of parks and the NDVI do not significantly affect the mobility. Robustness checks verified the plausibility of these findings. Furthermore, the effect of street greenery varies over space, larger in suburban areas than in urban areas. This study advances the understanding of relationships between urban greenery and travel behavior. [ABSTRACT FROM AUTHOR]

Population aging is happening in most of the world's metropolitan cities, and the proportion of elderly adults is predicted to increase significantly in the coming decades. This rapid growth of elderly populations may lead to serious transport issues when their mobility is compromised by the unavailability of public transport services. Public transport concession fare schemes are commonly implemented in many cities to encourage the elderly's participation in social activities. However, these policies emphasize the role of money (i.e., travel fares) in determining willingness to travel. Other possible factors, such as walking distance to and from stops and stations, wait times for public transport services, and seat availability, have not been considered by transport operators and policy makers. In this study, we interviewed 613 elderly Hong Kong residents aged 60 or above regarding their travel decisions using designated modes of public transport to attend social activities in four hypothetical games. A total of 2452 observations were collected for model development. Binary logistic regression models were calibrated to determine which factors significantly influenced the elderly's travel decisions. Based on the model results, this paper suggests policy measures to strengthen public transport planning in Hong Kong with the goal of improving elderly mobility. The findings provide policy insights that can also be applied to other metropolitan cities with similar traffic conditions. [ABSTRACT FROM AUTHOR]

Urban resilience studies often prioritize the investigation of sudden and short-lived natural disasters, while overlooking the gradual emergence and enduring nature of pandemics. The COVID-19 crisis, a quintessential example of such a challenge, has elicited significant but underexplored shifts in the landscape of urban public events. This research, drawing on social sensing geospatial datasets, aims to examine the changes in public events prior to, during, and after the fifth wave of COVID-19 in Hong Kong. Employing a dynamic time warping-based clustering algorithm alongside multiple linear regression analysis, we endeavor to address two pivotal questions: (1) How have the patterns of public events transformed in response to the pandemic? (2) What factors significantly influence these changes? The findings reveal that: Temporally, the implementation of social distancing measures is correlated with a marked reduction in public event frequency, reflecting the extensive impact of the COVID-19 crisis. Spatial analysis reveals that while public events are concentrated in Hong Kong's central areas, the spread of confirmed COVID-19 cases is more evenly distributed, with only a weak correlation observed between event hotspots and case distributions. Furthermore, our analysis identifies three distinct temporal patterns of public event changes, underscoring a higher resilience of events in urban centers against pandemic-induced disruptions. Additionally, built environment factors are found to be positively correlated with the decline in events as per the impact ratio, while socio-demographic factors more significantly affect the recovery ratio of events post-pandemic. This study not only pioneers in providing a comprehensive framework for monitoring urban events during a pandemic but also offers crucial insights into urban dynamics and vitality. These findings are invaluable for shaping more effective public health policies and crisis management strategies, enhancing urban resilience in face of future pandemics. • This study addresses resilience from a slow-onset and long-standing pandemic perspective. • Social sensing geospatial datasets enhance fine-grained tracking of public activities. • Activity resilience is defined by COVID-19's impact and the recovery extent after COVID-19. • The driving mechanism of activity resilience is explored from the built environment and socio-demographic aspects. • The research framework provides insights into urban dynamics and allows policymakers to introduce better policies. [ABSTRACT FROM AUTHOR]

Highlights • A driving simulator experiment and a questionnaire survey are designed. • Self-reported serious fatigue is related to worse driving performance. • Temporal patterns of driving fatigue and performance follow quadratic forms. • A recovery effect and a lagging effect are found in the temporal patterns. • Policies to solve high work intensity during rush hours are suggested. Abstract This study uses a questionnaire survey and a driving simulator test to investigate the temporal patterns of variations in driving fatigue and driving performance in 50 male taxi drivers in Hong Kong. Each driver visited the laboratory three times: before, during, and after a working shift. The survey contained a demographic questionnaire and the Brief Fatigue Inventory. A following-braking simulator test session was conducted at two speeds (50 and 80 km/h) by each driver at each of his three visits, and the driver's performance in brake reaction, lane control, speed control, and steering control were recorded. A random-effects modeling approach was incorporated to address the unobserved heterogeneity caused by the repeated measures. In the results, a recovery effect and a lagging effect were defined for the driving fatigue and performance measures because their temporal patterns were concavely quadratic and had a 1-hour delay compared to the temporal patterns of occupied taxi trips and taxi crash risk in Hong Kong. Demographic variables, such as net income and driver age, also had significant effects on the measured driving fatigue and performance. Policies regarding taxi management and operation based on the modeling results are proposed to alleviate the taxi safety situation in Hong Kong and worldwide. [ABSTRACT FROM AUTHOR]

It has been well established that the infrastructural development for rail transit stimulates rail transit use. However, there is little agreement about the source of the increased rail transit use. Using data from two repeated cross-sectional surveys, we examine changes in individual travel behavior resulting from the introduction of a rail transit line in Hong Kong. To address some methodological limitations inherent to repeated cross-sectional research design (e.g., selection bias and longitudinal incomparability), a two-dimensional propensity score matching method (2DPSM) is adopted to pair samples between the treatment and control groups in both cross-sectional and longitudinal dimensions. Paired t -tests are used to compare the longitudinal changes in travel behavior between the treatment and control groups of the matched samples. To get a more comprehensive understanding of the net treatment effects of the new rail line on travel behavior, we examined its impacts on both home-based trips (trips originating or terminating at home) and all trips for both treatment and control group. For home-based trips, the opening of the new rail line increased the rail mode share by 10.4%, and rail trip number by 0.126 (in terms of net effect, i.e., difference in the change between treatment and control group). It reduced the bus mode share by 17.1% and bus trip number by 0.208, showing a significant bus-to-rail modal shift. For all trips, the new rail line increased rail mode share by 9.5% and total trip number by 0.189. It also decreased bus mode share by 13.2%, and bus trip number by 0.191. Hence, the source of the increased rail transit use came from both the modal shift from bus and the increased travel demand induced by the new transit infrastructure. For both home-based trip and all trips, there was no significant influence on car use and total trip distance. Our findings provide new evidence that the development of rail transit in a high-density urban setting encourages a modal shift from bus to rail transit and stimulates flexible travel behaviors, but fails to control private vehicle use. • We applied a 2DPSM approach combined with paired t -tests to identify the influence of a rail transit line on travel behavior (including both home-based trips and all trips) by using data from repeated cross-sectional surveys in Hong Kong. • For both home-based trip and all trips, the new rail line had a positive effect on rail transit use, and had a negative influence on bus use. • There was a positive relationship with the total number of all trips, but non-significant association with that of home-base trips, which indicated that the increase in rail transit ridership may partly come from increased non-home-based travel demand created by the new rail line. • The development of rail transit in a high-density urban setting encourages a modal shift from bus to rail transit and stimulates flexible travel behavior, but fails to control private vehicle use. [ABSTRACT FROM AUTHOR]