Recreational Trips Research Articles

Sea‐Level Rise, Drinking Water Quality and the Economic Value of Coastal Tourism in North Carolina

AbstractWe estimate the economic benefits of avoiding reductions in drinking water quality due to sea level rise accruing to North Carolina (NC) coastal tourists. Using stated preference methods and responses from recent coastal visitors, we find that tourists are 2%, 8%, and 11% less likely to take an overnight trip if drinking water tastes slightly, moderately, or very salty at their chosen destination. The majority of those who decline a trip would take a trip to another NC beach without water quality issues, others would take another type of recreational trip, with a minority opting to stay home. Willingness to pay for an overnight beach trip declines with the salty taste of drinking water. We find evidence of attribute non‐attendance in the stated preference data, which impacts the regression model and estimates of the willingness to pay for trips. Combining economic and hydrological models, annual aggregate benefit losses due to low drinking water quality could be as high as $232 million by 2040.

Understanding the urban mobility challenge: Why shared mobility providers fail to attract car drivers

Reducing urban car traffic has become a global policy objective. A vital element in achieving this objective is the availability of shared mobility providers offering sustainable alternative travel modes such as micromobility, carsharing, and ridehailing. Despite policy and industry efforts, shared mobility options have failed to change the travel patterns of current car users. We explore this urban mobility challenge through an empirical study of 807 urban travelers. Our results show that car drivers estimate travel costs conceptually rather than rationally and consider both trip purpose and length. In particular, car users perceive longer and recreational trips as cheaper per distance driven than shorter and work-related trips. A segmentation analysis reveals that habitual and technology-averse car drivers are particularly susceptible to this skewed cost perception, unlike more frequent transit users. Embedding these results in a case study of current shared mobility options shows that these options are ill-adjusted to the preferences of car travelers but more attractive to current transit users, potentially leading to cannibalization. Based on these findings, we outline several strategies for mobility providers and policymakers to attract car drivers to shared mobility options, thereby contributing to solving the urban mobility challenge.

Acceptance and demand of autonomous vehicles for long-distance recreational travel: An investigation based on a survey of visitors to US national parks

The study of anticipated changes in travel behavior that could be brought by autonomous vehicles (AVs) has been widespread for commuting and short-distance daily travel, yet little attention has been given to long-distance travel. To address this research gap, this paper presents an analytical model for estimating public preference towards the adoption and use (in terms of frequency and length of trips) of AVs, focusing on long-distance recreational travel (LDRT). The model considers socio-demographics, trip-specific characteristics, in-vehicle time use-related factors, and attitudinal latent variables (AV usefulness, AV concern, driving enjoyment) as potential influencers of AV acceptance and demand. To analyze the proposed model, data were collected from a survey of visitors to US national parks conducted in Summer 2022, and the structural equation modeling (SEM) technique was employed. The results indicate that the frequency and length of long-distance recreational trips will likely be higher in the AV era. This draws attention to tourism destination managers not only to manage the tourists’ demand at destinations but also to manage traffic on the roads leading to the destinations. Additionally, the results show that the LDRT demand will continue to rise with the increase in AV acceptance due to the usefulness and potential for several in-vehicle activities offered by vehicle automation, despite concerns about system safety, data privacy, and legal liability. The study also reveals that some travelers will likely miss manual driving enjoyment in AV driving, particularly in unique travel settings like tourism travel, and thus might opt for manual driving options. Based on these findings, we advocate for the timely consideration of induced LDRT, and tourism travel demand generated by AVs—such as provisioning sustainable public transport options to recreational and tourism destinations.

Exploring pedestrian thermal risk exposure and its determinants among various types of walking trips: A gendered examination from a GPS-based study in Nanjing

Previous research has found that components of the natural and built environment play an important role in regulating ambient temperature. However, existing research regarding the association between these environmental characteristics and thermal exposure has focused mainly at the macro level, leaving this relationship at the individual level underexplored. It remains unknown how the environment functions differently in determining thermal exposure among various types of trips and how this mechanism differs by gender. Using GPS walking trajectory data collected in Nanjing, China, this study examines the extent to which male and female pedestrians experience different levels of thermal exposure, and how the thermal exposure determinants work differently between utilitarian and recreational trips. Descriptive analysis shows that men experience higher per-minute thermal exposure than women, and both male and female pedestrians face higher thermal exposure per minute during utilitarian walks compared to recreational walks. Generalized linear mixed model results indicate that green spaces significantly reduce thermal exposure for both male and female pedestrians during utilitarian walking trips, but this effect only works among women regarding recreational walking. We also identified a negative relationship between water bodies and thermal exposure during recreational walks, but this correlation only occurs among women. Our study suggests that the natural environment’s mitigating effect on thermal exposure differs by gender among different types of walking trips. Policymakers should consider these disparities to avoid exacerbating gender inequality in the arena of thermal exposure and health.

The Role of Recreational Trips in Providing Educational Values for Female Elementary School Students

This research shed light upon the various recreational values involved and how recreational trips matter in the growth and development of students. The primary school students, specifically the female students, were targeted here, and the discussions were carried out regarding how these recreational trips influenced the performance of the various candidates. This descriptive research was conducted on a group of 797 participants from the government and private schools. The findings of the study indicate that a majority of 51.7% members were found to opt for five or less training courses. And 44.8% of all the members were among those who were interested in Educational courses.

The influence of working from home and underlying attitudes on the number of commuting and non-commuting trips by workers during 2020 and 2021 pre- and post-lockdown in Australia

Since the start of 2020, we have seen major changes in the way communities operate. Mobility behaviour has been drastically impacted by work from home (WFH) and by lockdowns and restrictions in different jurisdictions. This study investigates the influence of WFH and different lockdown patterns on commuting and non-commuting trips in Australia by workers between early 2020 and late 2021. The data includes three waves of data collection to represent different lockdown periods. A multiple discrete–continuous extreme value (MDCEV) model is estimated to represent the number of one-way trips undertaken weekly with different purposes (commuting, work-related, education, shopping, personal business/social recreation), and by different modes (car, public transport, active modes). Explanatory variables include socioeconomic characteristics, location, the time period during the pandemic (i.e., waves). In addition, latent variables were included representing underlying attitudes such as satisfaction towards life or concern about the use of public transport – which might certainly play an important role in understanding individual weekly travel behaviour decisions. The model structure has the advantage that it estimates commuting and non-commuting activity together, allowing for a substitution effect between them. The results suggest that across all waves and jurisdictions, respondents who WFH more are more likely to have a higher number of shopping trips and personal business/social recreation trips, perhaps substituting these trips in replacement of their lesser commuting trips. Interestingly, all other influences held constant, individuals who are more concerned about the use of public transport are more likely to undertake commuting trips by all modes, more likely to do shopping trips, and less likely to undertake personal business/social recreation trips – suggesting they are prioritising essential trips rather than social/personal trips and perceive the risk of COVID-19 to be higher due to this travel.

Na nás venkovské působí každá návštěva Prahy přímo posvátně. Imaginace a politika v rekreaci zemědělců na přelomu 40. a 50. let 20. století

This study deals with the overnight tourist trips that the United Union of Czech Agricultural Workers organized for agricultural workers in the late 1940s and the early 1950s. It examines how two groups of ideas influenced how such recreational trips unfolded. The first centered around the effects of organizers’ efforts to make recreation a social-constructive tool of the Czechoslovak state and an ideological tool of the Communist regime. Imaginaries of the countryside and its inhabitants also influenced the planning of these trips. This study understands both groups of ideas as a part of the period under study’s social imagination, which according to Charles Taylor encompasses ideas about the arrangement of society and expectations about how it functions. The view from the other side, that is, how the vacationers experienced their holidays, demonstrates how successful the organizers were in meeting their goals and also reveals the sources of contemporary imaginaries of the countryside and its inhabitants.

Perspectives on e-scooters use: A multi-year cross-sectional approach to understanding e-scooter travel behavior in Portland, Oregon

Unique travel behavior patterns are observed as shared electric scooters (e-scooters) provided by private operators expand into U.S. cities. Three separate years of e-scooter ridership survey data from the Portland Bureau of Transportation’s E-scooter Pilot Programs were analyzed to ascertain the multi-year cross-sectional and demographic characteristics of e-scooter riders. A binary logistic regression model, descriptive statistics, and multiple regression model are used to analyze e-scooter mode substitution, trip purposes, and travel distance from 2018 to 2020 in Portland, Oregon. Since the introduction of e-scooter in 2018, respondents have been less likely to use their previous transportation, and especially vehicle trips were consistently replaced with e-scooter trips during three different periods of analysis. In 2020, utilitarian trips, work/school trips, and trips for accessing transit stops replaced recreation trips as the primary trip purpose. The travel distance model shows that e-scooters can help to reduce vehicle miles traveled (VMT) by replacing car and ride-hail/taxis trips. With the result of this research, this study supports shared e-scooters as a viable transportation mode in the future that can achieve several policy goals, such as climate change, congestion, first/last mile connector to transit, and equity.

Investigating the changes in travel behaviour during an economic crisis in a developing country: A case study of the Greater Beirut Area, Lebanon

Lebanon is currently facing one of the worst economic crises in its history, which has been compounded by the economic consequences of the COVID-19 pandemic and the devastating explosion at the Port of Beirut in August 2020. This research focuses on the Greater Beirut area in Lebanon, aiming to examine the impact of the ongoing economic crisis on travel behavior. The study analyzes changes in travel behavior before and during the crisis for various trip purposes, including the number of trips and modes of transportation used. Socio-economic factors that may have influenced these changes are also considered. Descriptive analyses and multivariate statistics reveal that the economic crisis had a significant influence on people's travel behavior. Multinomial logistic regression models highlight the impact of factors such as age, nationality, occupation, household size, income, and spending fluctuations on trip frequency changes during the crisis. The analysis of the data indicates a decrease in all trip types during the crisis, partly due to the adoption of online study and work, resulting in fewer commuting trips. Private car usage declined for shopping trips, while motorcycles and public transport witnessed an increase. Recreational trips reduced significantly, with more respondents opting for fewer trips per year, showing a noticeable preference for buses. Despite the shift away from private cars, the adoption of public transport remains modest, partly due to limited accessibility, safety concerns, and unreliable services.

Exploring constraints and coping strategies of outdoor recreation trips accessible by public transport: A walk-along and ride-along study in Austria

Exploring constraints and coping strategies of outdoor recreation trips accessible by public transport: A walk-along and ride-along study in Austria

The effects of climate change on outdoor recreation participation in the United States: Projections for the 21st century.

Climate change is expected to impact individuals' recreational choices, as changing temperatures and precipitation patterns influence participation in outdoor recreation and alternative activities. This paper empirically investigates the relationship between weather and outdoor recreation using nationally representative data from the contiguous United States. We find that across most outdoor recreational activities, participation is lowest on the coldest days (<35 degrees Fahrenheit) and highest at moderately high temperatures (80 to 90 degrees). Notable exceptions to this trend include water sports and snow and ice sports, for which participation peaks at the highest and lowest temperatures, respectively. If individuals continue to respond to temperature changes the same way that they have in the recent past, in a future climate that has fewer cool days and more moderate and hot days, our model anticipates net participation across all outdoor recreation activities will increase by 88 million trips annually at 1 degree Celsius of warming (CONUS) and up to 401 million trips at 6 degrees of warming, valued between $3.2 billion and $15.6 billion in consumer surplus annually (2010 population). The increase in trips is driven by participation in water sports; excluding water sports from future projections decreases the consumer surplus gains by approximately 75 percent across all modeled degrees of warming. If individuals in northern regions respond to temperature like people in southern regions currently do (a proxy for adaptation), total outdoor recreation trips will increase by an additional 17 percent compared to no adaptation at 6 degrees of warming. This benefit is generally not seen at lower degrees of warming.

Benchmarking ecosystem performance using index numbers: A case study of the northeast large marine ecosystem

Ecosystem indicators provide important information to managers about the results of their efforts to provide goods and services from marine ecosystems, along with the environmental condition of the ecosystem. Often, multiple indicators are of interest, which represent a cross-section of goods and services provided through ecosystem based management (EBM). This can make evaluation of whether ecosystem managers are improving their stewardship of marine ecosystems challenging because multiple indicators may give conflicting signals about management success. In order to overcome this problem, we develop an environmental output and input quantity index that collapses multiple ecosystem indicators into two composite indices. Our indices are based on distance functions constructed using Data Envelopment Analysis (DEA), a linear programming technique. We construct an output quantity index with data on fishery revenue, right whale populations and recreational trips from the northwest Atlantic Large Marine Ecosystem (LME) for the years 1998–2019. This is combined with an environmental quantity index using data on zooplankton abundance, chlorophyll-A, and aggregate fishery biomass. Both indices use 1998 as a benchmark year. Results from the combined output quantity-environmental quantity index show that relative to 1998, ecosystem performance generally improved before declining after 2016. Environmental conditions substantially improved, but outputs from the system declined in recent years. Although outputs are greater than in 1998, the system should be able to produce more given the environmental quality. Reasons for lower outputs could be due to exogenous factors beyond the control of managers.

Estimation of trip purposes in public transport during the COVID-19 pandemic: The case of Santiago, Chile.

The COVID-19 pandemic strongly affected the mobility of people. Several studies have quantified these changes, for example, measuring the effectiveness of quarantine measures and calculating the decrease in the use of public transport. Regarding the latter, however, a low level of understanding persists as to how the pandemic affected the distribution of trip purposes, hindering the design of policies aimed at increasing the demand for public transport in a post-pandemic era. To address this gap, in this article, we study how the purposes of trips made by public transport evolved during the COVID-19 pandemic in the city of Santiago, Chile. For this, we develop an XGBoost model using the latest available origin-destination survey as input. The calibrated model is applied to the information from smart payment cards during one week in 2018, 2020, and 2021. The results show that during the week of maximum restriction, that is, during 2020, the distribution of trips by purpose varied considerably, with the proportion of trips to work increasing, recreational trips decreasing, and trips for health purposes remaining unchanged. In sociodemographic terms, in the higher-income communes, the decrease in the proportion of trips for work purposes was much greater than that in the communes with lower income. Finally, with the gradual return to in-person activities in 2021, the distribution of trip purposes returned to values similar to those before the pandemic, although with a lower total amount, which suggests that unless relevant measures are taken, the low use of public transportation could be permanent.

Ethnographic Study of the Tourists' Motivation for Recreational Trip to Mazandaran Province Through the Lens of Rite of Passage Theory

Ethnographic Study of the Tourists' Motivation for Recreational Trip to Mazandaran Province Through the Lens of Rite of Passage Theory

Parking Charges: Ingeniously Effective and Publicly Accepted in Riyadh?

The background of this study is relevant to parking facilities at shopping malls in the Kingdom of Saudi Arabia (KSA), where all parking services are mostly free, with very few exceptions. Demand on parking places at shopping malls and recreational areas in Saudi cities are generally very high. This is partly because most of the entertaining, shopping, and recreational areas are indoors and are typically located at shopping malls with huge parking provision. With the vast increase in car ownership and use in the country over the past few decades, a consequent increase in demand on roads and parking facilities has been observed, which has no doubt resulted in further congestion. This study aims to investigate the willingness to pay to save time searching for a parking place at shopping malls in Riyadh city in the KSA. The methodology includes interviewing shoppers in shopping mall car parks and asking about their search time for a parking space and their willingness to pay to save search time, as well as to report on their socio-economic characteristics including age, gender, employment, education, car ownership, and income. The outcome of this study shows that on average, shoppers spend about 9 min searching for a parking place for their shopping and recreational trips. The results also show that, on average, shoppers reported that they go shopping, eating out, etc., about three times per week, and the average willingness to pay to save time searching for parking space is about 10 Saudi Riyal (about 2.7 USD) per visit. The modelling results show that there is a higher willingness to pay from the middle income and car-ownership categories of the population than from the highest income and car ownership groups. This might reflect the fact that the middle-income groups are much more dependent on themselves to drive their cars and search for a parking space every time, while those of higher incomes could possibly rely on their private drivers most of the times to drive them and park their cars. This paper contributes to the literature by providing a first understanding on how demand for parking facilities is affected by various socio-economic factors and the willingness to pay to save search time at these parking locations. The implications of the outcome of this research will be of use for decision makers and city authorities in planning travel demand management policies and programs that aim at reducing demand on private cars and achieving sustainability.

Reprint of: Exploring tourists' motivations, constraints, and negotiations regarding outdoor recreation trips during COVID-19 through a focus group study.

Understanding of tourists' motivations, constraints, and negotiation strategies-relevant to outdoor recreation trips-provides several managerial implications to destination managers and marketers, as outlined below:•Lack of centralized and reliable information was frequently cited as a constraint in the focus group discussions. In order to provide adequate and timely information to potential participations, we proposed a novel website template including details about information to be presented.•As our study sheds light on tourists' companionship preferences, activity choice, and evaluation of a destination's COVID-related operational practices, we propose several advertising strategies and destination operational guidelines to attract tourists.

Comparing E-Bike Users’ Perceptions of Safety: The Case of Lausanne, Switzerland

Electrically-assisted bicycles (E-bikes) may broaden cycling to a wider spectrum of users, territories, and trips. But what are e-bike users’ experiences of safety in a low-cycling city, and how do they vary among different users? This paper conceptualizes perceived safety based on vélomobility as the meeting point between users with specific characteristics (age, gender, etc.) and an environment more or less amenable to cycling. It is based on data from a survey of 1260 e-bike users who received a subsidy in Lausanne, Switzerland. We use 13 variables to measure perceived safety, finding 3 components: comfort for cycling in different situations, satisfaction with cycling conditions, and barriers to e-bike use. Based on these components, we identify four groups of e-bike users: (1) confident all-rounders, (2) recreational on-roaders, (3) worried traffic-avoiders and (4) unconfident path-users. We find gender and age to be the main factors associated with being a member of a group with lower perceived safety. Low weekly frequency of e-bike use, reduced winter e-bike use, and cycling for recreational trips exclusively also reduce perceived safety. Despite the benefits of electrical assistance compared to conventional bicycles, low safety due to unwelcoming road conditions remains a major concern for many e-bike users.

Spatial and temporal responses to incentives: An application to wildlife disease management

When participating in recreation individuals decide on where to go (locations) and when to participate (which time periods), and they respond to changes in external factors (e.g., environmental quality changes, provision of incentives). In examining economic decision-making, economists focus mostly on location choices, thus the behavioral and welfare impacts of the incentives associated with time choices are largely unknown. In this paper, we develop and estimate a flexible econometric model that combines spatial and temporal choices. The model is applied to examine individuals’ location and time choices of their recreation trips in response to extended recreation seasons that are proposed to encourage hunting for wildlife disease management. The data are from an online revealed and stated preference survey of recreational hunters in Alberta, Canada. We find that individuals substitute activities spatially and temporally, take more hunting trips, and gain welfare benefits when they can more flexibly choose the time of activities. Our findings show that increases in time flexibility can be used as an incentive to encourage beneficial outcomes.

Sistem Pendukung Keputusan Pemilihan Siswa Study Tour Menggunakan Metode TOPSIS

Study tour activities are as a means of learning while recreation for teachers, students and course administrators. This recreational trip while studying is held every year and requires good preparation. For students who wish to take part in the study tour, a selection stage is carried out. In this study, the selection used a decision support system using the TOPSIS method (Technique For Others Reference by Similarity to Ideal Solution). This method consists of several steps that are easy to implement. In this method, there is no special calculation for weights. The weight is determined based on the analysis of all parties involved in developing the system. This system is expected to be able to select students properly through the attributes used, namely achievement, health, files and budget capabilities. Some assessments are carried out by interviews conducted by the course admin. The data is then processed as input to a decision support system. The system was developed using the PHP programming language and MySQL database. Some of the features or menus contained in it are home, alternative data, ratings, rankings and weights. These features are designed so that the system is easy to use. This research resulted in a selection system that makes it easier for administrators to determine students who take part in the study tour. Decision support systems simplify student data collection and topsis method calculations. The value of each criterion can be calculated quickly by the system. The weight used can be changed through the system. Recommendations for students to take part in the study tour can be seen in the ranking menu in the system in order. The system can be used annually in selecting study tour students

Assessing the factors affecting the perceived crossing speed of pedestrians and investigating the direct and indirect effects of crash risk perception on perceived crossing speed

Walking is the primary means of transportation. For assessing individual's health, travel behaviour and benchmarking service levels of pedestrian infrastructure, walking/crossing speed acts as a relevant indicator. In spite of this, there is a paucity of literature that has focused on the evaluation of the individual's perceived crossing speed and the factors that influence it. Based on the responses collected from 616 pedestrians, the present study adopts an exploratory approach to identify the factors that influence an individual's perception of crossing speed. Five different types of classification-based machine learning methods (decision trees, boosting, K-nearest neighbour, random forest, and support vector machine) are employed to study the influence of selected factors of an individual's perceived crossing speed at mid-block crossings. Furthermore, using mediation analysis, it was analyzed if the crash risk perception (CRP) of an individual had a significant effect on their perceived crossing speed (PCS) directly and indirectly through their discrete crossing pattern (CP). Study findings indicate that crossing pattern (frequency of crossing/walking for recreational trips per week), crash risk perception, and age were the three most factors influencing the respondent's perceived crossing speed (PCS). In comparison to other four classification-based machine learning methods, random forest proved to be the most accurate method. Mediation analysis indicated that crash risk perception (CRP) directly affects the perceived crossing speed of individuals (individuals tend to cross slowly if they perceive a high risk of crashes) as well as indirectly influences crossing speed through their crossing pattern (CP). This study contributes to the growing body of research in investigating relationship between crossing pattern, perceived safety, and walking speed of pedestrians. The results of the present study will be the basis for advocating the need to pay more attention to pedestrian safety perception, since perceived crossing speed and crossing pattern are directly related to it.