Spatial and temporal analysis of shared bicycle use in Limassol,Cyprus

Cities around the world are moving away from the car-centric infrastructure, urban design and planning policies prevalent since the 1950s and promoting sustainable mobility as an alternative, including cycling. As such, Bicycle Sharing Systems (BSS) have emerged as a transport innovation across the globe. Cycling modal share however remains low in most Southern European island cities. These cities exhibit certain characteristics considered as barriers to cycling, such as hot summers and high humidity, hilliness, and car-oriented culture and infrastructure. Despite this, BSS and policies promoting cycling have emerged in this region as well. These have the potential to provide alternatives for those marginalized by car-based mobility and to reduce traffic related diseases and injuries, noise and air pollution, which can contribute to an improved quality of life for all citizens. Using the Mediterranean island city of Limassol (Cyprus) as a case study, the utilization of bicycle sharing is investigated by constructing regression models to assess the influence of spatial and temporal factors on the demand for BSS use at stations. From the regression models it appears that land use factors such as residential, commercial and park land use, as well as the presence of the beach and cycling paths positively influences frequency of use, as does higher network connectivity. While higher tourist arrivals have a positive effect, the presence of hotels in a 300 m buffer around the stations does not. Higher rainfall, as well as higher temperatures, are associated with a decrease in BSS use. Explicitly incorporating spatial dependence, in Spatial Auto-Regressive (SAR) models, led to the formulation of models with comparable or better explanatory power, when compared to the Ordinary Least Squares (OLS) models. The insights from the regression models can be used to inform policies promoting cycling and the design and planning of BSS (expansion) in Limassol and other cities.     

Public bicycle as a feeder mode to rail transit in China: The role of gender,age, income,trip purpose,and bicycle theft experience

A marriage between public bicycle and rail transit presents new opportunities for sustainable transportation in Chinese cities. To examine determinants of public bicycle usage for rail transit access, an intercept survey of feeder mode choice among rail transit users was conducted near rail stations in Nanjing, China. Mode choice models were estimated with five feeder mode alternatives, including car, bus, walk, private bike, and public bike. By differentiating between public and private bicycle modes in the mode choice models, the study reveals the effects of personal demographics, trip characteristics, and station environments on public bicycle usage for rail transit access. Results show that female, older, and low-income rail commuters are less likely to use public bicycle to access rail transit. Rail commuters with bicycle theft experience and making school- or work-related trips are more likely to use public bicycle to access rail transit. Land use variables are largely insignificant in this study except that density shows a positive relationship with walking to rail transit. The results on demographic differences raise equity concerns when it comes to investing in public bicycle systems. Policy implications are discussed for Chinese cities to equitably boost public bicycle integration with rail transit.     

Spatial variation in shared ride-hail trip demand and factors contributing to sharing: Lessons from Chicago

As ride-hailing becomes more common in cities, public agencies increasingly seek transportation network company (TNC) service data to understand (and potentially regulate) demand and service response. Despite the increase in ride-hailing or TNC demand and subsequent research into its determinants, there remains little research on shared TNC trips and the spatial distribution of trip demand across demographic and land use variables. Using Chicago as a case study, shared TNC trip data from 2019 was used to estimate the count and ratio of shared ride services, based on built environment, demographic, location, time of day, and trip details. Findings reveal that trip length, day of week designation, density of pedestrian and multi-modal infrastructure, and underlying socioeconomic characteristics of the origin zones influence the proportion and count of shared ride-hail trips. Of concern is that those using transit or active modes may be taking more ride-hailing trips, but these Chicago-region results indicate that the provision of pedestrian infrastructure and remoteness to transit stops result in fewer shared trips.     

Inferring the trip purposes and uncovering spatio-temporal activity patterns from dockless shared bike dataset in Shenzhen,China

Trip purpose is closely related to travel patterns and plays an important role in urban planning and transportation management. Recently, there has been a growing interest in investigating the spatio-temporal patterns of dockless shared-bike usage and its influencing mechanisms. Few, however, have focused on revealing the travel patterns by inferring the purpose of dockless shared-bike trips at the individual level. We present a framework for inferring the purpose of dockless shared-bike users, based on gravity model and Bayesian rules, and conduct it in Shenzhen, China. We consider the comprehensive factors including distance, time, environment, activity type proportion, and service capacity of points of interest (POIs), the last two factors of which were usually neglected in previous transport studies. Especially, we integrated areas of interest (AOIs) and Tencent User density (TUD) social media data characterize the service capacity of POIs, which reflect the area and scale differences of different POI categories. Through the comparison between two improved models and the basic model, it is demonstrated that the introduction of activity type proportion and service capacity of POIs can improve the effectiveness of model for inferring the purposes of dockless shared-bike trips. Based on the obtained trip purposes, we further explore the spatio-temporal patterns of different activities and gain some insights into bike travel demand, which can inform scientific decisions for bicycle infrastructure planning and dockless shared- bike management.     

Space-time demand cube for spatial-temporal coverage optimization model of shared bicycle system: A study using big bike GPS data

As a sustainable transport mode, bicycle sharing is increasingly popular and the number of bike-sharing services has grown significantly worldwide in recent years. The locational configuration of bike-sharing stations is a basic issue and an accurate assessment of demand for service is a fundamental element in location modeling. However, demand in conventional location-based models is often treated as temporally invariant or originated from spatially fixed population centers. The neglect of the temporal and spatial dynamics in current demand representations may lead to considerable discrepancies between actual and modeled demand, which may in turn lead to solutions that are far from optimal. Bike demand distribution varies in space and time in a highly complex manner due to the complexity of urban travel. To generate better results, this study proposed a space-time demand cube framework to represent and capture the fine-grained spatiotemporal variations in bike demand using a large shared bicycle GPS dataset in the “China Optics Valley” in Wuhan, China. Then, a more spatially and temporally accurate coverage model that maximizes the space-time demand coverage and minimizes the distance between riders and bike stations is built for facilitating bike stations location optimization. The results show that the space-time demand cube framework can finely represent the spatiotemporal dynamics of user demand. Compared with conventional models, the proposed model can better cover the dynamic needs of users and yields ‘better’ configuration in meeting real-world bike riding needs.     

Systematic comparison of trip distribution laws and models

Trip distribution laws are basic for the travel demand characterization needed in transport and urban planning. Several approaches have been considered in the last years. One of them is the so-called gravity law, in which the number of trips is assumed to be related to the population at origin and destination and to decrease with the distance. The mathematical expression of this law resembles Newton's law of gravity, which explains its name. Another popular approach is inspired by the theory of intervening opportunities which argues that the distance has no effect on the destination choice, playing only the role of a surrogate for the number of intervening opportunities between them. In this paper, we perform a thorough comparison between these two approaches in their ability at estimating commuting flows by testing them against empirical trip data at different scales and coming from different countries. Different versions of the gravity and the intervening opportunities laws, including the recently proposed radiation law, are used to estimate the probability that an individual has to commute from one unit to another, called trip distribution law. Based on these probability distribution laws, the commuting networks are simulated with different trip distribution models. We show that the gravity law performs better than the intervening opportunities laws to estimate the commuting flows, to preserve the structure of the network and to fit the commuting distance distribution although it fails at predicting commuting flows at large distances. Finally, we show that the different approaches can be used in the absence of detailed data for calibration since their only parameter depends only on the scale of the geographic unit.     

A consolidated model of trip distribution

This work analyzes and compares various trip distribution models with spatial aggregation within a common theoretical framework for formulating and solving multi-objective optimization problems. A new model is designed that incorporates the main characteristics of existing ones. These models are then calibrated with a single database at different spatial aggregation levels using maximum likelihood. The results show that with aggregated data the various models differ little, but with disaggregated data the differences are considerable. It is also demonstrated that changing the level of data aggregation can significantly alter the models’ parameter values.     

Factors influencing motivations and expectations of field trip attendance

This paper examines students’ motivations for participating in field trips and analyses students’ expectations in an attempt to identify the influence of three variables: age, level of education, and previous work experience. Results demonstrate that students’ reasons for participation are diverse, and while the results are specific for the case analysed, they support prior research, suggesting that students develop very positive attitudes and perceptions towards field trips.     

Measuring the sustainability of Cuban tourism destinations considering stakeholders' perceptions

The aim of this research consists of measuring the sustainability degree for tourism destinations considering the stakeholder's preferences. Their opinions were included in the overall process during the choice of the initial indicators and determining the weights. Additionally, in the aggregation process, a sustainability index was calculated with a multiple criteria decision theory methodology, according to its ability to embrace the participant opinions in the decision‐making process. Results allows determining the sustainability degree and the identification of strengths and weaknesses in terms of goals attainment. To corroborate the robustness of the index, an analysis of the rankings was performed.     

Determinants hindering the intention of tourists to visit disaster-hit destinations

The purpose of this study is to propose and examine a new research model that is able to capture both the cognitive and affective components influencing potential tourists' behavioural intentions to visit a disaster-hit destination, which have negatively affected their perceived destination image. A survey of 357 participants provides strong support for the model. The results indicate that participants' perceptions of destination image are a strong predictor of their travel intentions. Factors relating to cognitive appraisals (e.g. perceived equipment risk, perceived natural risk and perceived social risk) as well as affective evaluations (e.g. perceived fear of ghosts, perceived unpleasantness, etc.) were found to be critical components that significantly, and negatively, influence potential tourists' perceptions of a destination image. Theoretical and practical implications of the results are discussed herein.     

Catalysts and magnets: Built environment and bicycle commuting

What effects do bicycle infrastructure and the built environment have on people’s decisions to commute by bicycle? While many studies have considered this question, commonly employed methodologies fail to address the unique statistical challenge of modeling modes with small mode shares. Additionally, personal characteristics that are not adequately accounted for may lead to overestimation of built environment impacts.This study addresses these two key issues by using an ordered probit Heckman selection model to jointly estimate participation in and frequency of commuting by bicycle, controlling for demographics, residential preferences, and travel attitudes. The findings suggest a strong influence of attitudinal factors, with modest contributions of bicycle accessibility. Bicycle lanes act as “magnets” to attract bicyclists to a neighborhood, rather than being the “catalyst” that encourages non-bikers to shift modes. The results have implications for planners and policymakers attempting to increase bicycling mode share via the strategic infrastructure development.     

A global comparison of bicycle sharing systems

Increasing urban populations have created pressures on the transportation networks that serve them. Bicycle sharing systems (BSS) have seen a dramatic increase in popularity as cities around the world begin to implement and see significant use and benefit from this growing mode of urban micro-mobility. As a result, the research surrounding bicycle sharing systems has also increased, although this has been primarily focused on the analysis of individual systems. There is therefore a need for a global comparison of systems, particularly given that prior research often omits China, which is currently the largest BSS market in the world. This paper therefore marks a major step forward through its analysis of data from 322 schemes situated on all major continents. Conducting such analysis, there appear to be 5 main types of BSS: very large, high use BSS, large BSS in major cities, medium BSS with extensive cycling infrastructure, small to medium efficient BSS and small to medium inefficient BSS. From these major cluster groups, we are able to group schemes by usage, contextual indicators and the behavioural characteristics of their users. This not only facilitates a global comparison of scheme performance, but also offers a basis to new schemes to identify established BSS with similar characteristics that can be used as a template for anticipating the likely demand from users.     

Air transport and tourism—Perspectives and challenges for destinations,airlines and governments

Air transport and tourism are interlinked. Tourism is a driving factor for and, in some cases, a stimulator of change in air transport; most notably the development of new business models such as charter airlines. On the other hand, air transport opened new destinations and tourism forms such as long-haul excursions. Here these interlinks are analyzed in a system model. For the strategic development of destinations, a clear airline policy and air access strategy seems to be necessary. For airlines an assessment and understanding of the business models of destinations is essential. By shaping the external regulative environment of air traffic, government may influence air traffic as well as tourism.     

Revealing travel patterns and city structure with taxi trip data

Delineating travel patterns and city structure has long been a core research topic in transport geography. Different from the physical structure, the city structure beneath the complex travel-flow system shows the inherent connection patterns within the city. On the basis of taxi-trip data from Shanghai, we built spatially embedded networks to model intra-city spatial interactions and to introduce network science methods into the analysis. The community detection method is applied to reveal sub-regional structures, and several network measures are used to examine the properties of sub-regions. Considering the differences between long- and short-distance trips, we reveal a two-level hierarchical polycentric city structure in Shanghai. Further explorations of sub-network structures demonstrate that urban sub-regions have broader internal spatial interactions, while suburban centers are more influential on local traffic. By incorporating the land use of centers from a travel-pattern perspective, we investigate sub-region formation and the interaction patterns of center–local places. This study provides insights into using emerging data sources to reveal travel patterns and city structures, which could potentially aid in developing and applying urban transportation policies. The sub-regional structures revealed in this study are more easily interpreted for transportation-related issues than for other structures, such as administrative divisions.     

Prioritizing low-stress and equitable bicycle networks using neighborhood-based accessibility measures

As cities across the United States strive to create comfortable bicycle networks for mainstream users, three topics have garnered attention: project prioritization criteria, accessibility to everyday destinations, and social equity. However, these topics have not often been integrated in research or practice. This paper introduces a method to assess the extent to which reductions in “Bicycle Level of Traffic Stress” (LTS) on segments of a citywide bicycle network increase accessibility to supermarkets, pharmacies, banks, and public libraries. Six accessibility performance measures are developed and evaluated for 278 neighborhoods in Baltimore, Maryland using a GIS-based approach. The demographic distributions of accessibility results are further analyzed, focusing on disadvantaged populations. Using a set of 106 proposed bicycle projects, the marginal accessibility gains and cumulative demographic impact across affected neighborhoods are assessed for each project. These results are ranked and crosslisted to identify a set of projects that balance accessibility gains with equity objectives. The prioritization results demonstrate some overlap with the short-term priorities embodied in City of Baltimore's 2015 Bike Master Plan, but they also highlight projects in other areas, specifically those that would serve neighborhoods most disadvantaged in terms of racial segregation, high poverty rates, and low rates of vehicle ownership.     

The effectiveness of environmental interpretation at resource‐Sensitive tourism destinations

The process of appropriate visitor management is an integral part of sound tourism management. Visitor management includes the development and implementation of rules and regulations with respect to visitor activity, which in turn provides the guidelines for visitors. On the other hand, it also aims to create enjoyable visitor experiences in the hope that visitors will appreciate the value of the site. Environmental interpretation in a resource‐sensitive tourism destination is considered to be an effective visitor management strategy that helps to encourage visitors to adopt more appropriate behaviour in order to sustain the development of tourism. This paper aims to examine the processes and purposes of visitor management and environmental interpretation, including relevant definitions and functions. The characteristics of visitor management and environmental interpretation, and how to increase their effectiveness, also are addressed. Copyright © 2002 John Wiley & Sons, Ltd.     

An examination of the role of domestic destinations in satisfying holiday demands

The role of domestic destinations in satisfying demand for holidays has received less attention than research which outlines the challenges associated with long haul travel, particularly within the United Kingdom context. This paper examines the role of domestic holidays in satisfying demand in relation to international holidays, in the context of providing a better understanding of the environmental impacts of tourism. This is achieved through analysis of a household survey and a series of interviews with family groups of holiday-makers. The data was collected in the East Midlands region of the United Kingdom. Most respondents prefer domestic holidays in attractive coastal and rural destinations; they often take place in the summer and for shorter periods than overseas trips. Yet once at the destination there is commonality between tourism practices in domestic and international destinations. Socio-cultural aspects, life stage and financial considerations prove much more influential than environmental concerns in influencing choice. In response, the main policy recommendation would be to raise the relative cost of travelling abroad. The primary research recommendation would be to deepen the understanding of how substitution between destinations can occur.     

The evolution of backpacker destinations: the case of Zipolite,Mexico

Despite the growing literature on backpacker tourism, little is known about the evolutionary patterns of the places that cater to such travellers. This paper analyses, first, the way in which established and current models of tourist development conceptualise backpackers and their destinations. In addition, it offers some specific suggestions that will allow them to explain the evolution of backpacker destinations in a more detailed manner. Then, results of field research conducted at Mexico's largest backpacker resort are presented, to illustrate its particular socio‐spatial evolution. The paper concludes that, when fuelled by an increasing number of arrivals and a growing demand for comforts, what were once drifter‐dominated peripheral places may evolve gradually into well‐established ‘resorts’ that satisfy contemporary backpackers' demands for infrastructure, natural settings and ambience. Developer‐tourists with an affinity to backpacker culture are likely to become key actors as they come to gain control over land use and local economic development. Copyright © 2007 John Wiley & Sons, Ltd.