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Suburban areas have lower density development than urban areas, which may make them less accessible for the growingpopulation of low- and moderate-income suburban residents, particularly those without a personal vehicle. This research examines factors that lead these households to move to suburban areas and identifies accessibility barriers they face. We use a mixed-methods approach with Public Use Microdata Sample (PUMS) data from the U.S. Census, online/in-person surveys (n=208), and interviews conducted in English and Spanish (n=25) with households in Contra Costa County with an income of less than $75,000. To understand key differences in housing and transportation choices between urban and suburban residents, these data were compared to survey and interview data from low-income Oakland residents from 2020-2021. We found that low- and moderate-income households choose to live in suburbs due to rising rents and otherrequirements (e.g., credit score, rental history) in urban areas, and a desire for home ownership and safer environment for children. Yet lack of tenant protections is leaving them vulnerable to rising rents in suburban areas. Transportation costs are higher in suburbs due to longer commutes and higher reliance on personal vehicles. Despite higher levels of carownership in the suburbs, households often go without a car due to maintenance issues or inability to make car payments. When faced with the lack of an automobile, suburban households have few quality transportation alternatives.

In an abstract sense, researchers have assumed that a population‐based centroid better represents a given polygon than a purely geometric centroid (GC) because it accounts for the internal distribution of the local population. In specific application contexts, when measuring place‐based spatial accessibility, for example, using a GC might be misleading because this practice could overestimate travel costs in large polygons; however, this assumption has not been quantitatively tested. In this article, we examine the role of centroid definition types by comparing the accessibility values of three different centroid estimation approaches. The analysis indicated that, in comparison to population‐based centroids, the GC typically underestimated accessibility values, particularly in sparsely populated polygons, and accentuated spatial disparities. The findings suggest that researchers need to pay more cautious attention to the potential impact of centroid methods when measuring spatial accessibility. [ABSTRACT FROM AUTHOR]

Background: In consideration of patient out-of-pocket costs in low- and middle-income countries, this observational cohort study sought to quantify the travel expenses associated with receiving free cardiac services in India and create a point-of-care ultrasound (POCUS) referral model. Methods: In a tertiary hospital that offers free services in Bangalore, India, we interviewed outpatients awaiting cardiac evaluation regarding their out-of-pocket expenses. A subgroup underwent POCUS for signs of left atrial enlargement, inferior vena cava plethora, and extravascular lung water, and subsequent chart review for significant findings on echocardiography or need for immediate care. A model was tested in which a normal POCUS would negate the requirement for referral. Results: Patients (N = 219), of age (mean ± SD) 49.0 ± 12.9 y, traveled [median (IQR)] 1178 miles (248–1240), spent $104 ($26-$195), and lost 4.5 (0–10) days of work at a daily wage of $3.90 ($1.95-$6.50). The one-way travel cost equated to 27 days of daily pay. In the POCUS subgroup, symptoms were commonly chest pain (57%) and dyspnea (48%) and were less than moderate in severity (71%). Abnormal echo findings were present in 54% of patients, of whom 29% needed immediate care, and 71% were dismissed without follow-up. POCUS signs were related to an abnormal echo (p < 0.001), but not immediate care (p = 0.50). POCUS-based referral would have prevented 51% (35/68) of unnecessary referrals and missed 13% (9/68) of cases that required immediate care. Conclusions: Out-of-pocket costs, relative to income, can be significant for those seeking free cardiac care. POCUS performed locally could potentially reduce the costs of travel but would risk missing cases, depending on symptom type. [ABSTRACT FROM AUTHOR]

In urban metro systems, unexpected events often occur to cause discordance in the planned timetable and delay in passenger travel. Therefore, this study focuses on the timetable rescheduling problem by adopting a stop-skipping strategy during the off-peak period. In addition, there are a number of existing optimization models that minimize the total passenger waiting time, which can cause fairness issues for a small group of passengers having longer waiting time at some stations. In this study, a rescheduling model is proposed to consider passenger waiting time fairness and train travel time cost. This model is tested with a randomly designed delay scenario of Nanjing Metro Line 2, which can be efficiently solved by a designed iterative algorithm based on decomposition method. Compared to the standard stop pattern, the result shows that the stop-skipping pattern can better alleviate the impact of sudden delays, while simultaneously ensuring the passenger waiting time fairness. [ABSTRACT FROM AUTHOR]

Based on an unedited hieratic docket from the tomb of Tutankhamun, this article determines financial aspects of royal funeral processions in ancient Egypt. With reference to written sources from the Middle Kingdom, it is concluded that mechanics to safeguard the ritual's safety included en route cash payments during the 18th Dynasty. As a result, this study advocates caution when it comes to the assessment of looting activities soon after Tutankhamun's interment in KV 62. [ABSTRACT FROM AUTHOR]

This study aims to comprehensively identify the contributing factors affecting the adoption of flex route transit. A survey was conducted in 2019, and a multiple indicators multiple causes (MIMIC) model was utilized to capture individuals' preferences toward car, fixed route, and flex route transit. Subsequently, the multinomial logit model with attitudinal features is employed to identify the key factors influencing the shift from car or fixed route to flex route transit. Results indicate that several factors contribute to flex route transit adoption, with the top three being car restriction, travel cost, and age groups. Car restriction is positively associated with flex route transit adoption (marginal effects 11.67%). Travel costs (≥1.49 US$) and elderly groups also contribute to an increase in flex route transit adoption, with marginal effects of 9.18% and 8.01%, respectively. These findings provide insightful implications for decision-makers in identifying potential adopters and improving flex route transit adoption. [ABSTRACT FROM AUTHOR]

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. • Car users perceive trip costs differently based on trip length and purpose (work versus leisure). • Longer and recreational trips are perceived as cheaper per distance driven than shorter and work-related trips. • Habitual and technology-averse car drivers are more susceptible to skewed cost perception compared to frequent transit users. • Current shared mobility offers are more attractive to transit users than car drivers, potentially leading to cannibalization. [ABSTRACT FROM AUTHOR]

Customized bus services typically focus on single‐trip requests, which often struggle to accommodate the growing needs for varied multiple trips in urban daily travel. This paper addresses the customized bus routing problem for passengers with multiple trips. A bi‐objective mathematical model is established for maximizing the operational profit and minimizing the travel costs by considering the characteristics of the multi‐trip requests and time‐dependent travel time. Besides, a novel profit objective function is proposed considering the service's completion status and the starting price. Since the proposed mixed integer linear programming model is an NP‐hard problem, a non‐dominated sorting genetic algorithm II‐based method is proposed to handle different sizes of instances. Finally, the instances with multi‐trip requests are carried out to test the accuracy of the model and the effectiveness of our method compared with Gurobi and the local search‐based multi‐objective algorithm approach. [ABSTRACT FROM AUTHOR]

Despite the availability of electronic navigators and automated vehicles, static wayfinding instructions remain widely used due to their resistance to signal disturbances, as well as their economic and environmental advantages over electronic signs. To investigate the impact of static wayfinding on the network cost and flow distribution, this paper presents an efficient method for updating the incident matrix and extends the stochastic user equilibrium (SUE) framework to incorporate static wayfinding instructions by using the generalized nested logit (GNL) choice model to represent user behavior. The SUE principle relaxes the assumption that users possess perfect knowledge of traffic conditions and always choose the optimal link to minimize their costs. The GNL model improves generalization performance of the cross-nested logit (CNL) model while solving the overlap problem of the multinomial logit (MNL) model. The disaggregate simplicial decomposition (DSD) algorithm is applied to solve proposed user equilibrium by iteratively finding decent directions through an auxiliary solution and determining step size using different methods. The results indicate that the self-regulated averaging (SRA) method can solve the proposed model efficiently. Additionally, increasing travel time cost on guided links and even outer links can be potential influences caused by static wayfinding instructions. The study results can assist decision-makers in quantitatively assessing the value of placing static wayfinding instructions at certain locations and choosing effective layout information. [ABSTRACT FROM AUTHOR]

We collect data on prices, travel costs, and farmer decisions to quantify market access for chemical fertilizer and its impact on agricultural productivity in 1,180 villages in Northern Tanzania. Villages at the bottom of the travel cost-adjusted input price distribution face 40%–55% less favorable prices than those at the top. A standard deviation increase in village-level remoteness is associated with 20%–25% lower input adoption. A spatial model of input adoption conservatively estimates that total trade costs are 4 times pecuniary travel costs. Counterfactuals suggest that halving travel costs would more than double adoption and reduce the adoption-remoteness gradient by 63%. [ABSTRACT FROM AUTHOR]

Background: Drug-resistant (DR) tuberculosis (TB) is typically characterized by resistance to a single or combination of first- and/or second-line anti-TB agents and commonly includes rifampicin-resistant (RR)-TB, multidrug-resistant (MDR)-TB, pre-extensively drug-resistant (pre-XDR)-TB and XDR-TB. Historically, all variations of DR-TB required treatment with second-line drugs which are less effective and more toxic than first-line options, have a longer treatment duration and are more expensive to both patients and providers. The World Health Organization (WHO) now recommends a new second-line 3-drug 6-month all-oral regimen consisting of bedaquiline, pretomanid, and linezolid referred to as BPaL. We estimate patient and provider costs of DR-TB treatment with BPaL compared to the current standard of care in South Africa. Methods and findings: In coordination with South Africa's BPaL clinical access programme (CAP) we conducted an economic evaluation of A) patient costs through a cross-sectional patient cost survey and B) provider costs through a bottom-up costing analysis consisting of a retrospective medical record review (patient resource-use) and top-down financial record review (fixed/shared costs such as overhead). Across both costing perspectives, we compare costs of 1) BPaL, to current standard of care options including the 2) 9-11-month standard short oral regimen (SSOR) and 3) 18-21-month standard long oral regimen (SLOR). Eligible patients included those ≥14 years old with confirmed sputum pulmonary RR/MDR-TB, pre-XDR or XDR-TB. All costs are reported in 2022 United States Dollar (US$). A total of 72 patients were enrolled and completed the patient cost survey (41.7% on BPaL, 16.7% on the SSOR and 41.7% on the SLOR). Mean on-treatment patient costs were lowest among those on BPaL ($56.6) and increased four-fold among those on the SSOR ($228.1) and SLOR ($224.7). Direct medical patient costs were negligible across all treatment regimens, while direct non-medical patient and guardian costs for travel, food and nutritional supplementation accounted for the largest proportion of total costs ($54.6, $227.8 and $224.3 for BPaL, the SSOR and SLOR respectively). In assessing provider costs, a total of 112 medical records were reviewed (37.5%, 41.1% and 21.4% on BPaL, the SSOR and SLOR respectively). Total provider costs for producing a favorable treatment outcome (cured/completed treatment) were similar among those on BPaL ($4,948.7 per patient) and the SSOR ($4,905.6 per patient) with costs increasing substantially among those on the SLOR ($8,919.9 per patient). Based on incremental cost-effectiveness ratios (ICERs), at even the lowest willingness to pay (WTP) threshold, treatment with the new BPaL regimen was more cost-effective than current standard of care treatment options (ICER: $311.4 < WTP: $3,341). Conclusions: When using the newly recommended BPaL regimen, cost to patients decreased by 75% compared to current standard of care treatment options in South Africa. Due in part to higher resource-use within the BPaL CAP offsetting the shorter treatment duration, cost of treatment provision through BPaL and the 9-11-month SSOR were similar. However, when considering cost and treatment outcomes, BPaL was more cost-effective than other standard of care regimens currently available for DR-TB in South Africa. [ABSTRACT FROM AUTHOR]

This study investigates the optimization of taxi-pooling operations using the M/M/1/m queuing model, aiming to enhance efficiency and revenue for taxi service platforms. Traditional taxi operations face challenges during peak periods, including inefficiency and increased operational costs. Taxi-pooling, by accommodating multiple passengers with similar travel demands, offers a solution that reduces travel costs, operational expenses, and urban congestion. The study develops an optimization model to balance operational costs and passenger waiting times, identifying the utilization rate of taxis as a critical factor in platform revenue. By modeling the taxi-pooling service as a queuing system, we derive mathematical expressions for passenger waiting times and platform revenue under varying conditions. Our findings highlight the importance of optimal vehicle investment strategies and pricing decisions to maximize revenue. The study provides theoretical support for improving taxi-pooling platforms' efficiency and competitiveness, contributing to better urban transportation solutions. [ABSTRACT FROM AUTHOR]

Purpose Methods Results Conclusion To analyse the impact on cost if faricimab is used as the first‐line treatment for neovascular age‐related macular degeneration (nAMD) compared to standard treatment with bevacizumab.Retrospective registry study including real‐world data from the Swedish Macula Registry between 2017 and 2022. The observed number of injections and visits for bevacizumab during the first two years of treatment was used (n = 437 patients). Number of faricimab injections was obtained from published clinical trial data and unit costs mostly from publicly available Swedish sources. The provider cost included medication and visit cost and societal cost included additionally patient travel cost. Costs are presented in 2023 EUR.The incremental societal cost of faricimab was 277 EUR per patient compared to bevacizumab in the base case. Medication cost was higher (1516 EUR) while visit cost (−1183 EUR) and patient travel cost (−56 EUR) were lower due to longer injection intervals. Faricimab was of similar cost as bevacizumab for patients residing far from the clinic. The faricimab injection interval and the number of bevacizumab injections were major drivers of uncertainty in the results.Faricimab represents a cost‐effective alternative to bevacizumab for patients with nAMD in Sweden. Its extended treatment interval is particularly beneficial for patients living far from clinics, and if the real‐life faricimab injection interval extends beyond 12 weeks. Our findings emphasize faricimab's potential to free up healthcare staff to treat a larger patient population with existing clinic resources. [ABSTRACT FROM AUTHOR]

Background: The worldwide market for continuing medical education (CME) was severely affected by the COVID-19 pandemic, which precipitated an increase in web-based CME course attendance. Virtual education methods may be effective for engaging learners and changing behaviors. However, more information is needed about physician preferences for in-person vs. livestreamed CME courses in the postpandemic era. Because of the paucity of data regarding this topic, the current study was designed to evaluate CME participant characteristics, preferences, engagement, and satisfaction with traditional in-person vs. virtual educational methods. Methods: A cross-sectional study was performed of attendees of two large internal medicine CME courses held in 2021. Both CME courses were offered via in-person and livestream options, and were taught by Mayo Clinic content experts. Participants, who consisted of practicing physicians seeking CME, completed a 41-question survey after CME course completion. Statistical comparisons were performed by using Fisher exact tests for all survey items, except for those with ordinal response sets, which were compared with Cochran-Armitage trend tests. Results: A total of 146 participants completed the survey (response rate, 30.2%). Among the 77 respondents who attended in-person courses, the most frequent reasons indicated were the opportunity to travel (66%) and collaboration/networking with others (25%). Among the 68 respondents who attended the livestream courses, the most frequent reasons indicated included COVID-19–related concerns (65%), convenience (46%), and travel costs (34%). The percentage of respondents who indicated that they would choose the same mode of attendance if given the option again was higher for those who attended in person than for those who attended via livestream (91% vs. 65%, P <.001). Conclusions: These data suggest that in-person course offerings will continue to be a preferred learning method for some physicians. However, most respondents who attended virtually preferred that method. Therefore, hybrid CME models offering both in-person and virtual options may be most beneficial for meeting the needs of all CME learners. [ABSTRACT FROM AUTHOR]

The rapid development of high-speed railways (HSR) worldwide has provided a fast, convenient, safe, and comfortable mode of transportation. It is also an important public transportation tool for green travel, contributing to the reduction of carbon emissions. HSR has a strong competitive advantage in long-distance passenger transportation, but it faces significant competition from the aviation industry. Airlines attract passengers with discounted fares and differentiated pricing strategies, apart from shorter travel times. Therefore, it is necessary for railway enterprises to enhance their competitiveness through differentiated pricing methods for HSR. In this study, we focus on optimizing a long-distance origin-destination (OD) pair and creating a competitive market environment by considering all operating trains and flights for the selected OD pair. We aim to improve the realism of the study by considering passengers' fully rational travel choice behavior. To reduce the complexity of variables, passengers are grouped based on their expected departure time and income level. A mixed integer linear programing model is developed to address the problem, aiming to minimize overall travel costs for passengers while ensuring that the income of the railway enterprise does not fall below a specified value. By setting this specific value, the maximum revenue of HSR train tickets can be obtained. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate out-of-pocket non-medical expenses and employment-related outcomes in families of children with life-limiting conditions, specifically, to quantify the financial and employment implications of two events: a child's hospitalization and death. This cohort study used panel data collected prospectively for a larger study investigating the effectiveness of specialized pediatric palliative care. Participants were recruited by medical professionals between November 2019 and May 2022 at four Swiss children's hospitals. The care follow-up and bereavement follow-up assessments were 330 and 300 days, respectively. We measured out-of-pocket non-medical expenses, individual full-time equivalent units, and personal income, as well as sick leave and vacation days taken. Analyses included descriptive statistics and two-way linear fixed-effects regressions. The analysis included 110 parents (mothers n = 59, fathers n = 51) of 61 children. Children were hospitalized for a median of 7 days (interquartile range 0–21, range 0–227). The fixed-effects models found a positive association between hospitalization, i.e., length of stay, and travel and accommodation expenses (coefficient 4.18, 95% confidence interval 2.20–6.16). On average, for each week of hospitalization, parents spent an additional 29 Swiss francs on travel and accommodation. During the 300-day bereavement follow-up, six (26%) of 23 parents increased their work commitments, while one reported a decrease. Conclusions: Families incur higher travel and accommodation expenses during hospitalization than during non-hospitalized periods. Instrumental support, e.g., parking vouchers, can help families minimize these costs. Future studies should investigate whether early return to work during bereavement is driven by economic considerations or a desire for distraction. Clinical trial registration: Data analyzed in this study were collected as part of a clinical trial, registered on ClinicalTrials.gov, No. NCT04236180, 15 March 2019 What Is Known: • Families of children with life-limiting conditions are at risk of substantial financial burden from high out-of-pocket medical expenses. • It is also known that parents often have to incur out-of-pocket non-medical expenses and reduce their work commitments. Little is known about the economic consequences of losing a child to a life-limiting condition. What Is New: • We provide new longitudinal evidence on the hospitalization- and death-related financial and employment implications for families of children with life-limiting conditions. • Child hospitalizations add to families' financial burden through increased travel and accommodation expenses. Work commitments rose during early bereavement. [ABSTRACT FROM AUTHOR]

This study focuses on solving the problem of metro first/last mile, studying the method for designing microcirculation bus routes and coordinating schedules considering the impact of shared bicycles. First, we propose a bilevel mixed-integer programming model for designing microcirculation bus routes and coordinating schedules considering the impact of shared bicycles. The upper-level model minimizes the weighted sum of the travel time cost of passengers and the operating cost of public transport enterprises, and the lower-level model maximizes the number of passengers served by microcirculation bus routes. Then, an improved genetic algorithm is developed to solve the model, called the Monte Carlo adaptive genetic algorithm (M-GAI). Finally, the proposed model and algorithm are evaluated using the case study in the area near the Fubao metro station of Shenzhen Metro Line 3. Results show that if the impact of shared bicycles is not considered, the passenger demand will be greater than the actual value, and the operating cost of public transport enterprises will be increased by 36%. Compared with GAI, the average number of iterations of M-GAI is reduced by 31%, and the objective function value is decreased by 4%. In addition, when the number of routes increases, the average waiting time of passengers is shortened, the average attendance rate of microcirculation buses increases, and the average empty distance of each vehicle is shortened. However, the operating cost of public transport enterprises will increase with the number of routes. Finally, when weight factors α and β are 0.6 and 0.4, respectively, and the sum of the travel time cost of passengers and the operating cost of public transport enterprises reach optimal. [ABSTRACT FROM AUTHOR]

The remote and iconic Kimberley region, in northern Western Australia, is a contested landscape with growing pressure for different types of land use and development. The region has high biodiversity values and impressive scenery that provide attractive recreation experiences for visitors. We estimate the value of domestic recreation to the region using a travel cost model. Analysis includes two approaches for accounting for multi‐destination trips (MDTs) given travel to remote sites are more likely to include these than shorter trips, and four specifications for the value of travel time. We estimate a total consumer surplus of A$110.34 million annually and find that adjusting travel costs for MDTs using stated survey information produces a better fitting model than using revealed travel information. These findings highlight both the importance of estimating recreation values for use in land use planning in the Kimberley and for improving the travel cost method for remote sites where per‐trip travel costs are high. [ABSTRACT FROM AUTHOR]

The primary objective of this paper is to minimize the overall travel costs for passengers while simultaneously maximizing the operational revenue for the transportation company. This is achieved through the optimization and adjustment of various factors, such as the intervals between regular bus and subway services, the duration of vehicle stops at each station, and the pricing structure for subway and shared bicycle usage. By enhancing the efficiency of passenger travel, we have successfully bolstered the company's operational profits. In contrast to prior research, this paper comprehensively considers the dual uncertainties associated with both bus operations and shared bicycle operations within a cooperative system. By establishing a coordinated dual‐level optimization model for regular bus, subway, and bike‐sharing networks under dual uncertainty conditions, we employed convex combination techniques to unify the dual uncertain variables into a single objective, which was then incorporated into a chance‐constrained bilevel programming model. Ultimately, we utilized KKT conditions to transform the model from a bilevel to a single level for resolution. This paper centers its research on the collaborative system comprising the Nanchang Metro Line 1, Bus Route 520, Bus Route 211, and the adjacent region hosting a cluster of shared bicycles. By leveraging Python programming, optimization models, empirical data on traffic flow and stoppage times, and OD data, we conducted an optimization analysis to solve the problem at hand. According to the optimization results, passenger waiting time, passenger transfer time, and passenger on board time are effectively reduced by 6.81%, 18.29%, and 23.92%. At a confidence level of 95%, the resulting time level results in a 12.44% reduction in total travel time. The average subway fare increased by 18.12%, the average shared bicycle fare decreased by 19.12%, and the total cost of travel expenses increased by 16.68%. The final total cost of travel was reduced by 4.06%, and the business operating income was increased by 13.10%. The comprehensive optimization results have effectively fulfilled the objectives of the bilevel optimization model, thereby confirming the rationality and practicality of the optimization approach. The research outcomes hold significant practical implications for facilitating the efficient and cooperative development of urban transportation networks, ultimately enhancing the convenience of residents' travel experiences. [ABSTRACT FROM AUTHOR]

Car-sharing is a travel mode that can serve as an alternative to private cars, helping to reduce urban pollution. However, currently, there is a low willingness among travelers to use car-sharing, which is reflected in both low market penetration and user frequency. Therefore, it is essential for the government to encourage the use of car-sharing by providing subsidies. To better encourage the usage of car-sharing, this paper applies a two-fold evolutionary game model involving travelers and the government to explore the impact of subsidies on travelers' choices, and the factors that could affect the subsidies' efficiency. A simulation, using data from Beijing, was conducted to determine the implications of subsidy policies. The results show that a mileage-based subsidy and a fixed subsidy are applicable to travel of high and low mileages respectively, and under both subsidy modes, subsidies for trips with short duration or short pick-up and return time are more effective. Furthermore, we find that the efficiency of subsidies increases as the scale of car-sharing users, demand elasticity, or total number of travelers increases. Additionally, the subsidy levels should be lower than the environmental benefits of car-sharing but higher than the difference in travel costs between private cars and car-sharing. Future work will involve other game players such as car-sharing operators in order to draw deeper conclusions, and will involve the collection of data from more countries and cities to develop the robustness of the conclusions. [ABSTRACT FROM AUTHOR]

This study proposes a framework of an urban passenger-and-package sharing (PPS) system that utilizes e-hailing taxis to transport packages in addition to passengers. We examine the interactions between stakeholders and highlight the role of the pricing strategy in the system, including passenger fare discounts and driver incentives for PPS trips. Higher discounts and incentives stimulate more passengers and taxi drivers, respectively, to participate in the PPS system but possibly limit the profit of the service provider. A multi-agent simulation model is developed to analyze the influences of the pricing strategy on the behaviors of the service provider, passengers, and taxi drivers. The real-world case study demonstrates that the service provider, passengers, and taxi drivers benefit from different combinations of the passenger fare discounts and driver incentives. The pricing strategy could be set up to produce the system optimal (SO) situation that maximizes the total benefit, or win-win situations that simultaneously benefit all stakeholders—the service provider gains a higher profit, passengers enjoy lower travel costs, and taxi drivers have higher incomes when compared to the traditional e-hailing taxi system. The public authority is suggested to provide a subsidy to expand the domain of win-win situations to cover the SO situation, such that the system benefits all stakeholders and obtains the maximum total benefit. • Envisions a multi-stakeholder framework for PPS system based on e-hailing taxis. • Pricing concerns passenger fare discount and driver incentive for PPS service. • Analyzes the impact of pricing on system profit, passenger cost and driver income. • Optimal pricing maximizes the total benefit but may distract some stakeholders. • Evaluates the effectiveness of subsidy in coordinating win-win and SO situations. [ABSTRACT FROM AUTHOR]

Taking bus and subway into account, an asymmetric polycentric urban system equilibrium model is constructed to explore the impacts of rail transit on the distribution of residents and labor force in a linear polycentric urban system. By comparing the urban system equilibria before and after the introduction of rail transit, the influence of rail transit on urban performance is analyzed. The results show that the introduction of rail transit makes the advantaged center more attractive for the labor force, and further widens the economic level gap between the two business centers. Specifically, larger distance between the two commercial centers and the higher subway travel cost would strengthen the polarization effect caused by rail transit investment. Since the improvement of transportation makes it easier for residents to accept long-distance commuting and they are more willing to choose the jobs in the advanced center. [ABSTRACT FROM AUTHOR]

New energy vehicles (NEVs) are considered a crucial means of reducing travel costs, enhancing consumer experiences, and innovating services. This paper aims to categorize the functional experiences of NEVs into two types: intelligent experience and eco-friendly experience, using a dual-path model. By analyzing 118,648 text data from automotive information and service platforms, the relevant factors influencing consumer satisfaction are explored. The research findings reveal that intelligent experience has a significantly positive impact on consumer satisfaction, whereas eco-friendly experience has a significantly negative impact on consumer satisfaction. This suggests that new energy vehicle companies need technological innovation in infrastructure and range to enhance consumer satisfaction. Furthermore, the research confirms that, when facing the intelligent experience of new energy vehicles, consumers' "rational" thinking plays a dominant role, and efficacy is an intermediate variable to enhance consumer satisfaction. On the other hand, when facing the ecofriendly experience of new energy vehicles, consumers' "emotional" thinking predominates, and identity is an intermediate variable to enhance consumer satisfaction. Additionally, the moderating effect of perceived usability is examined. When faced with the intelligent experience of NEVs, consumers with high perceived usability are more likely to generate a sense of efficiency. In the case of the eco-friendly experience of NEVs, consumers with low perceived usability are more likely to experience a sense of identity. [ABSTRACT FROM AUTHOR]

In recent years, problems related to the adequacy of existing water resources have arisen due to issues such as population growth, rapid urbanization, industrialization, and climate change. Especially in agricultural production where water is used the most, the use of wastewater has become widespread as a solution to this problem. Considering that wastewater may harm the environment due to the substances it contains, it is aimed to make an environmental valuation in this study. In this context, by using the travel cost method used in the valuation of goods without a market, a different approach was brought to this method, as agricultural production is concerned, and an evaluation was made based on producer surplus. In the study, by comparing the agricultural productions with wastewater and well water, 2 hypotheses have been developed about the environmental valuation of wastewater; First, if the producer surplus of agricultural production with wastewater is lower than that of production with well water, there is environmental pollution, and its value is the difference between the two rents. The second hypothesis is that if the producer's surplus with wastewater is high, positive externality will occur as a hypothesis against the negative effects of environmental pollution. By conducting a survey with 125 producers in the research area, the data of 314 parcels in total were included in the analysis, and the producer surplus was calculated by creating the supply function with the regression analysis. As a result of the research, the producer surplus (584.40$) obtained from the agricultural production made by irrigating with wastewater was found to be higher than the producer surplus (553.44$) of the production made by irrigating with well water. In this case, it was concluded that the wastewater irrigated did not affect the environmental pollution, but the positive externality. Although the use of wastewater in agricultural production has made a positive contribution to the economy, it will be beneficial to use it after the necessary treatment processes, considering its harmful effects on human health. [ABSTRACT FROM AUTHOR]

The split delivery vehicle routing problem (SDVRP) is a relaxed variant of the capacitated vehicle routing problem (CVRP) where the restriction that each customer is visited precisely once is removed. Compared with CVRP, the SDVRP allows a reduction in the total cost of the routes traveled by vehicles. The exact methods to solve the SDVRP are computationally expensive. Moreover, the complexity and difficult implementation of the state-of-the-art heuristic approaches hinder their application in real-life scenarios of the SDVRP. In this paper, we propose an easily understandable and effective approach to solve the SDVPR based on an a priori adaptive splitting algorithm (AASA) that improves the existing state of the art on a priori split strategy in terms of both solution accuracy and time complexity. In this approach, the demand of the customers is split into smaller demand values using a splitting rule in advance. Consequently, the original SDVRP instance is converted to a CVRP instance which is solved using an existing CVRP solver. While the proposed a priori splitting rule in the literature is fixed for all customers regardless of their demand and location, we suggest an adaptive splitting rule that takes into account the distance of the customers to the depot and their demand values. Our experiments show that AASA can generate solutions comparable to the state of the art, but much faster. [ABSTRACT FROM AUTHOR]

We study how the buying purpose affects the trade-off between time and money. We consider the case of buying something for ourselves versus buying a gift and the decision whether to spend time traveling to a cheaper store to save money. We hypothesized that when purchasing a gift, people make less effort to save money, and therefore will be less willing to spend time traveling to a cheaper store when they buy a gift. In experiments with several scenarios, we fail to find support for this hypothesis. We also explore the impact of telling subjects that the purchase is made abroad. This is hypothesized to increase the valuation of the buyer's time. We also hypothesize that the interaction of being abroad and buying a gift will be negative. The data support both hypotheses. Subjects answered 15 questions about their decision-making style (rational, intuitive, and spontaneous). Subjects with more rational decision-making exhibit lower time value, which is likely to be closer to the real one. Subjects with more rational decision-making also show more strongly that time abroad is more valuable. These results suggest that questions about decision-making style are correlated with decision-making in scenarios of realistic purchase decisions. [ABSTRACT FROM AUTHOR]

Males of the endangered northern quoll (Dasyurus hallucatus) are facultatively semelparous, often dying following their first breeding season. This is often driven by high breeding costs: males travel and mate extensively in breeding season, resulting in reduced body condition. Annual post‐breeding survival rates for male northern quolls have been recorded between 0% and 12.5% across their range in northern Australia. We highlight an observed 50% survival rate of male northern quolls (3 of 6) living into their second year in a Pilbara mining landscape. High male survival here may be attributed to above average rainfall in the landscape and reduced breeding opportunities, due to low female abundance—likely driven by large amounts of unfavourable mining land. This likely led to lower hormonal stress associated with breeding for males, as well as increased resource availability. Given northern quoll population persistence is highly dependent on breeding success, high survival of male northern quolls may inadvertently stabilize populations if they can breed again in a second year, though this is yet to be observed in the Pilbara region. Nevertheless, semelparity of male northern quolls likely varies with environmental and demographic factors, demonstrating that northern quoll populations may be resilient to disturbance in an unpredictable semi‐arid environment. [ABSTRACT FROM AUTHOR]

To mitigate the negative effects of freight vehicles on urban areas, many cities have implemented road accessibility restrictions, including limited traffic zones, which restrict access to specific areas during certain times of the day. Implementing these zones creates a tradeoff between the delivery cost and time, even under the assumption of equal traversal time and travel cost. Consequently, the planners in charge of vehicle routing need to work with graphs containing information on all Pareto-optimal paths. Inspired by these changes in city logistics and the resulting computational challenges, we study the vehicle routing problem with access restrictions, where some streets are closed to traffic within a given time period. We formulate this problem using workday variables and propose two branch and price algorithms based on the underlying road network and multigraph. The results of our computational experiments demonstrate the effectiveness of the proposed algorithms, solving instances with up to 100 nodes and 33 customers, and underline the importance of considering alternative paths in reducing costs. Funding: This work was supported by KU Leuven [C14/22/026]. [ABSTRACT FROM AUTHOR]

The real-time dynamic coupling under the virtual-coupling technology guarantees running multi-group trains in different sections based on passenger flow's spatial and temporal distribution characteristics. It enables more flexible transport organization modes such as full-length and short-turn routing and the express/local stop mode. Utilizing the redundant capacity of the airport line to carry out coordinated transportation of passengers and goods is an essential means of relieving urban traffic pressure, saving energy, and protecting the environment. To promote urban rail transit to achieve the goal of "double-carbon," the optimization of passenger and freight cooperative transport schemes based on the virtual coupling technology for the airport line of the rail transit is investigated. Based on the train operation of full-length and short-turn routing under the virtual-coupling technology, according to the unbalanced distribution characteristics of passenger and freight flows in urban rail transit, this paper constructs an optimization model of urban rail transit capacity allocation to minimize passenger travel costs, enterprise operation costs, and carbon emission costs, and considering the constraints of the carbon emission policy, with the constraints such as the train operation safety, the constraints of the balance of the passenger flow and freight flow loading. The multi-objective model to solve the optimization problem has been designed. Given the complexity of the multi-objective model solution, an improved nondominated sorting genetic algorithm is designed, and the algorithm makes use of the screening function of the constraints during the initial population generation process, which effectively balances the relationship between the whole process of screening and time-consumption of the NSGA-II algorithm. Taking Wuxi Metro Line 3 as an example, the results show that: (i) Compared with the traditionally large and small crossing mode, full-length and short-turn routing of virtual coupling Trains proposed in this paper can reduce the average waiting time of passengers by about 2.01min, the cost of carbon emission by 15.7% and the cost of enterprise operation by 20.2%, and at the same time, improve the average total rate by about 50%, which verifies that the virtual formation technology is conducive to improving the efficiency of passenger travel and reducing the operating cost and the carbon cost. It is also beneficial for improving passenger traveling efficiency. (ii)The single-alignment fixed configuration mode, compared with the single-flow mode, can increase the average full-load rate by 26.6% while increasing the passenger travel cost by only 0.98% and reducing the carbon emission cost by a small margin; the virtual configuration technology based-on the large and smallalignment operation and transport scheme increases the passenger travel cost by about 0.3% and further reduces the carbon emission cost by 1.9%. They further reduced the carbon emission cost by 1.9% while increasing the average total occupancy rate by about 5.8%. The proposed models and algorithms provide some decision support for urban rail transit operators to optimize transport schemes under different carbon emission policies and the virtual coupling operation mode. [ABSTRACT FROM AUTHOR]

To solve the problem of passenger travel cost and full load rate balance before and after the implementation of cross-line operation in the peak period of urban rail transit (URT) passenger flow. This paper introduces the concept of section full load rate balance. According to the division of different types of passenger flow in the intersection mode of "X" and "Y" lines, based on the characteristics of passenger flow in peak passenger flow period, a mathematical model with cross-line operation mode turn-back station and operation frequency of train as decision variables is constructed to minimize passenger travel cost, full load rate balance objective function and enterprise operation cost. Taking the Changping Line and Line 8 in the Beijing URT system as examples, the validity of the model is verified. The results show that the operation mode of the cross-line train can alleviate the passenger flow pressure of the transfer station, reduce the overload of the original train on the line, improve the full load rate balance of the train, make the utilization of the transport capacity more balanced, and optimize the passenger ride experience. In addition, considering the operation of cross-line trains may increase the operating costs of enterprises. [ABSTRACT FROM AUTHOR]

This paper focuses on the joint optimization of the charging station location problem (CSLP) and discrete network design problem (DNDP) in a transportation network. We present a variational inequality (VI) formulation to describe the user equilibrium (UE) state of gasoline vehicles (GVs) and electric vehicles (EVs). Based on the mixed-UE model, a mathematical program with equilibrium constraints (MPEC) model is formulated for integrating the decisions of deploying EV charging stations (EVCSs) and adding new links to minimize the total travel cost (TTC) of all vehicles. A modified genetic algorithm is developed to tackle the MPEC model with an adaptive path generation procedure to address the mixed-UE model. Finally, we conduct numerical experiments to identify the efficacy of the proposed models and algorithms. Specifically, we propose a two-step optimization model and explore a performance comparison between the joint and two-step optimization approaches, while the joint optimization exhibits superiority in minimizing the TTC. [ABSTRACT FROM AUTHOR]

Archaeological investigations worldwide have focused on when and how humans permanently settled in high-altitude environments. Recent evidence from Xiada Co, Qusongguo, and Dingzhonghuzhuzi in western Tibet, where lithic artifacts and radiocarbon dates with original deposits were first accessed, provides new insights into human activities in this extreme environment during the early Holocene. This paper examines the mobility and land-use patterns of foragers in western Tibet from the perspectives of lithic analysis. Assemblages from three sites suggest homogenous technologies and raw material use, as well as potential interaction network of hunter-gatherers within the plateau during the early Holocene. It further argues that the material exponents and travel cost models of site location supported permanent occupation of the western Tibetan Plateau in this period. [ABSTRACT FROM AUTHOR]

Local search (LS) algorithms are efficient metaheuristics to solve combinatorial problems. The performance of LS highly depends on the neighborhood exploration of solutions. Many methods have been developed over the years to improve the efficiency of LS on different problems of operations research. In particular, the exploration strategy of the neighborhood and the exclusion of irrelevant neighboring solutions are design mechanisms that have to be carefully considered when tackling NP‐hard optimization problems. An MOEA/D framework including an LS‐based mutation and knowledge discovery mechanisms is the core algorithm used to solve a bi‐objective vehicle routing problem with time windows (bVRPTW) where the total traveling cost and the total waiting time of drivers have to be minimized. We enhance the classical LS exploration strategy of the neighborhood from the literature of scheduling and propose new metrics based on customer distances and waiting times to reduce the neighborhood size. We conduct a deep analysis of the parameters to give a fine tuning of the MOEA/D framework adapted to the LS variants and to the bVRPTW. Experiments show that the proposed neighborhood strategies lead to better performance on both Solomon's and Gehring and Homberger's benchmarks. [ABSTRACT FROM AUTHOR]

We investigate the impact of COVID-19 on tourism expenditures by analyzing survey data collected from participants of one of the major amateur cycling races in Italy—the Nove Colli. We gathered information from different types of participants (tourists, residents, day-trippers) about their travel expenses, accommodation, food and beverage, and side goods such as sports equipment. The survey covers three race editions: pre-COVID-19 in 2016, post-lockdown in 2021, and post-COVID-19 in 2022, for a total of 2734 respondents. Using a quasi-difference-in-differences approach, we find a significant increase in total tourism expenditures due to COVID-19, primarily driven by a substantial increase in side goods expenses, which more than doubled the rise in food and beverage expenses. This result can be partly explained through revenge spending as a form of compensatory consumption behavior and inform policy-makers on how individuals' spending patterns may change in the aftermath of an exogenous shock. [ABSTRACT FROM AUTHOR]

Road travel cost can be defined as a function of condition and volume-capacity factors. Asset managers intervene on heavily trafficked and poor condition roads based on criteria to optimize network travel and intervention (social) costs. These criteria may involve a trade-off between improving the road condition or capacity. Road performance is known through periodic inspection and stochastic modeling to estimate a deteriorated future condition. The predicted future condition and traffic growth rates change pavement section intervention (capacity or condition improvement) priority over time. The optimal road intervention choice can be determined using algorithms, including the greedy algorithm and Monte Carlo simulations. Greedy algorithms search through the entire sample space locally and stepwise to approximate global optima, whereas Monte Carlo simulations randomly sample candidate sections to generate more globally optimum interventions. This study proposes a road asset management model using Monte Carlo methods to optimally choose road network interventions considering condition and traffic changes over a planning horizon. The study includes an empirical application using real world data and compares the proposed Monte Carlo simulations approach to the greedy algorithm. [ABSTRACT FROM AUTHOR]

Incentive travel tourists generally come in large groups and travel at the full expense of their company. Their expenditure is greater than ordinary tourists, but they receive less attention in Indonesia’s marketing strategy as quality tourists. This condition occurs due to a lack of understanding of the incentive travel business process. This lack of understanding is because research on the MICE industry is more concerned with meetings/conferences or exhibitions than incentive travel. Also, a reference book that discusses incentive travel and its relation to the choice of destination processes or destination marketing strategy is limited. This study aims to determine who is involved in the destination selection process and their relationships. The research method used is a qualitative method using desk research for data collection and content analysis for analytical methods. The research method used is a qualitative method using desk research for data collection and content analysis for the analysis method. Desk research was carried out by reviewing literature related to travel incentives and research report documents conducted by research institutions related to incentive travel. The result shows several parties’ engagement and role in the incentive travel destination selection process. [ABSTRACT FROM AUTHOR]

AbstractPublic transport inherently involves encounters with other people. For women, negotiating everyday overcrowded, unsafe, and unreliable conditions is a major barrier to accessing public transport mobility that triggers emotions. Using qualitative research methods – in-depth interviews and visual surveys – this study delves beyond understanding the barriers and looks at the affective realm to comprehend how affects and emotions shape accessibility, acceptability, and affordability of public transport for women in Kolkata. The disruptive affects of overcrowded, unsafe, and unreliable conditions produce emotional ordeals, increase travel time and costs, and restrict mobility. The sense of despair that emerges compels women to adjust, accept, and even opt out of overcrowded, unsafe, and unreliable public transport more often than not. This paper argues that affects, emotions, reactions, and consequences are entangled and impact the accessibility, acceptability, and affordability of public transport. The contribution of this paper lies in bringing to the fore the need for feminist inquiries into gendered mobility inequalities and the role of affects and emotions therein. [ABSTRACT FROM AUTHOR]

To quantify the travel time and cost characteristics of mixed traffic involving electric vehicles (EVs) and fuel-powered vehicles on roads, in this paper, we comprehensively consider three factors affecting road impedance: queue length, waiting time, and service rate. Initially, a time characteristic function and a cost characteristic function for mixed traffic impedance are constructed. From the perspective of travel time, we consider the impact of EV penetration on the actual road capacity and introduce a capacity coefficient to modify the BPR (Bureau of Public Roads) road impedance function. Given that different types of vehicles might need to wait at charging stations, we employ queuing theory to calculate the queuing time at these stations and construct an impedance model that considers travel time. From the perspective of travel costs, we account for the energy consumption costs and road usage fees for different types of vehicles. The energy consumption cost for travel mileage is obtained by multiplying the unit mileage energy consumption cost of mixed traffic by the travel mileage. For road usage fees, we adopt the conventional method of multiplying the per-kilometer rate for each vehicle type by the travel mileage, thus constructing an impedance model that incorporates travel costs. Finally, in the numerical analysis section, based on the vehicle travel mileage, we categorize travel into short-, medium-, and long-distance trips for analysis. With the constructed mixed traffic impedance model, we conduct a detailed analysis of the travel time and cost characteristics of mixed traffic over different travel distances. We explore the specific impacts of the electric vehicle penetration rate, traffic flow volume, and travel mileage on road impedance. The results indicate that as the penetration rate of electric vehicles increases, the total energy consumption of the transportation system significantly decreases. Moreover, at high electric vehicle penetration rates, although an increase in traffic flow leads to higher traffic impedance and longer travel times, the overall travel costs are reduced. This demonstrates that increasing the penetration rate of electric vehicles positively contributes to reducing the energy consumption and costs of transportation systems. [ABSTRACT FROM AUTHOR]

The design of transportation networks is generally performed on the basis of the division of a metropolitan region into communities. With the combination of the scale, population density, and travel characteristics of each community, the transportation routes and stations can be more precisely determined to meet the travel demand of residents within each of the communities as well as the transportation links among communities. To accurately divide urban communities, the original word vector sampling method is improved on the classic Deepwalk model, proposing a Random Walk (RW) algorithm in which the sampling is modified with the generalized travel cost and improved logit model. Urban spatial community detection is realized with the K-means algorithm, building the F-Deepwalk model. Using the basic road network as an example, the experimental results show that the Deepwalk model, which considers the generalized travel cost of residents, has a higher profile coefficient, and the performance of the model improves with the reduction of random walk length. At the same time, taking the Shijiazhuang urban rail transit network as an example, the accuracy of the model is further verified. [ABSTRACT FROM AUTHOR]

In this study, a tripartite decision-making parking pricing model was developed based on Game Theory to comprehensively reflect the impact of parking pricing on private car travelers, parking lot operators, and traffic managers. Utility theory is introduced to analyze the behavioral characteristics of the tripartite participants in parking pricing. A parking behavior model for private car travelers, an operating profit model for parking lot operators, and a social negative utility model for traffic managers are established. This article presents an analysis of the mutual influence between them based on a game theory perspective and introduces parking saturation and road saturation as new factors influencing parking pricing to address the interactive relationship among the tripartite participants. A parking pricing model based on tripartite games is established, and a solution algorithm is designed. The results indicate that when the parking fee rates for the two public parking lots in the scenario are 8.5 CNY/h and 9 CNY/h, respectively, the parking demand is 300, and the sum of the total travel costs of private car travelers and the total operating profits are CNY 20,589 and 2187.9, respectively. The parking saturation of the public parking lot and the difference between the expected value is minimized to 0.25, and the road saturation and the difference between the expected value are minimized to 1.48, which is the parking pricing plan that minimizes the conflicts of interest among the tripartite stakeholders in the tripartite game. The parking pricing model of a public parking lot provides a reference for formulating parking fee strategies that comprehensively reflect the needs of the three parties involved in the public parking lot. [ABSTRACT FROM AUTHOR]

Air transport networks play a significant role in the modern tourism industry, and their operational performance and stability can be measured by reliability analysis. This study, from the perspective of a travel agency, attempts to assess the reliability of a stochastic air transport network (SATN) by considering multiple passenger demands generated by both the starting airport and several connection airports. The SATN is modeled as a stochastic flow network comprised of several nodes and arcs where nodes represent airports, and arcs represent flights connecting two airports. Each flight is associated with a predetermined stochastic capacity following a specific probability distribution, departure time, arrival time, and discount fare. Accordingly, network reliability refers to the probability that the network can successfully transport passengers from their respective source airports to the destination airport within the given travel time and travel cost limit. An algorithm in terms of the concept of lower boundary point is developed to compute network reliability. Furthermore, a simple example and a case study are presented to demonstrate the proposed reliability method and the managerial implications of reliability for travel agencies. [ABSTRACT FROM AUTHOR]

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Introduction: Telehealth is becoming an increasingly common presence in health care, particularly amidst the coronavirus disease 2019 pandemic. We aimed to investigate ways in which telehealth has been implemented in pediatric surgical specialties, as well as the success and satisfaction rates of these interventions. Methods: A systematic review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines using PubMed, Scopus, and CINAHL databases for telehealth and pediatric surgical specialties on August 20th, 2021. There were 1227 studies screened and 17 studies met final inclusion criteria for patient, parent/guardian, or physician satisfaction measures of a telehealth intervention in the United States. Results: Studies implementing telehealth interventions included all major pediatric surgical subspecialties with a total of 2926 patients. Of the 17 studies, common themes were the use of telehealth for synchronous video and/or telephone virtual visits, including comparing virtual visits to in-person clinic visits (nine studies) and postoperative virtual visits (six studies). Telehealth was also used in the perioperative setting to deliver care instructions via mobile application or text message (two studies). Telehealth interventions had a high rate of parent satisfaction (75%–98%), and 57%–75% of parents stated they would choose or prefer virtual appointments in the future, often citing travel and cost savings as benefits. Provider satisfaction was also high with satisfaction scores ranging from 7.5 to 9.4/10. Discussion: This systematic review suggests that both parent and physician satisfaction with telehealth in pediatric surgical specialties is generally high. Expanding telehealth applications allow greater access to care, particularly for specialized surgical services which often pose significant costs and travel burdens. [ABSTRACT FROM AUTHOR]

Rainforests, as invaluable natural resources, play a pivotal role globally, offering many ecosystem services such as recreation. This study aims to quantify the value of Brunei's rainforest assets (specifically recreational areas and national parks) utilizing the Travel Cost Method (TCM), a prevalent approach for ascertaining the worth of natural sites. The tourism use of Brunei's rainforests holds a high value, estimated at over $300,000 USD per square kilometer, which supports the argument for resource allocation towards their protection not only for ecological reasons but also for their recreational benefits. The authors posit that nature-based ecotourism can be a sustainable and protective mechanism for tropical rainforests. Practical recommendations for ecotourism include a minimalist approach to visitor regulation, limiting access to a small percentage of large recreational areas and national parks to protect flora and fauna, and possibly implementing entry or service fees. [ABSTRACT FROM AUTHOR]

Green travel is a special type of pro-environmental behavior, which requires people to pay a time cost to reduce carbon emissions. This study explored the impact of the cost of travel time and feedback types on green travel. To verify the change of travel choice under different time costs, experiment 1 explored the impact of different costs of travel time on green travel. The results showed that with the increase in time cost, green travel behavior gradually decreased. This suggests that time costs can hinder green travel behavior. To intervene in this negative effect, experiment 2 explored the effects of different types of feedback intervention. The results showed that both environmental and health feedback could only intervene with green travel behavior when the time costs were low. This indicates that health and environmental feedback can intervene in the negative effects of travel time cost, but the cost range of the intervention is limited. This study has implications for promoting green travel behavior. [ABSTRACT FROM AUTHOR]

Broadcast control (BC) is a bio-inspired coordination technique for a swarm of agents in which a single coordinator broadcasts an identical scalar signal to all performing agents without discrimination, and the agents make appropriate moves towards the agents' collective optimal state without communicating with one another. The BC technique aims to accomplish a globally assigned task for which BC utilizes a stochastic optimization algorithm to coordinate a group of agents. However, the challenge intensifies as the system becomes larger: it requires a larger number of agents, which protracts the converging time for a single coordinator-based BC model. This paper proposes a revamped version of BC model, which assimilates distributed multiple coordinators to control a larger multi-agent system efficiently in a pragmatic manner. Precisely, in this hierarchical BC scheme, the distributed multiple sub-coordinators broadcast the identical feedback signal to the agents, which they receive from the global coordinator to accomplish the coverage control task of the ordinary agents. The dual role of sub-coordinators is manipulated by introducing weighted averaging of the gradient estimation under the stochastic optimization mechanism. The potency of the proposed model is analyzed with numerical simulation for a coverage control task, and various performance aspects are compared with the typical BC schemes to demonstrate its practicability and performance improvement. Particularly, the proposed scheme shows the same convergence with about 30% less traveling costs, and the near convergence is reached by only about one-third of iteration steps compared to the typical BC. [ABSTRACT FROM AUTHOR]

The rapid evolution of educational and professional training methods has ignited a pivotal debate between traditional classroom training and the increasingly prevalent virtual training paradigm. This research paper delves into the heart of this discourse, presenting a comparative study focused on unraveling the conundrum of cost-effectiveness. As institutions and organizations grapple with decisions regarding resource allocation, our study seeks to provide a nuanced analysis, examining both quantitative and qualitative dimensions. The investigation encompasses diverse facets of cost, including infrastructure expenses, training material outlays, and ancillary costs such as travel and accommodation. Beyond financial metrics, we explore the impact on productivity, learner engagement, and knowledge retention. By adopting a holistic approach, we aim to offer comprehensive insights into which training method--classroom or virtual--proves more economically viable. Acknowledging the dynamic nature of industries and the evolving preferences of learners, our research strives to contribute a balanced perspective. The methodology involves a thorough review of existing literature, case studies, and empirical data to inform a comprehensive understanding of the cost-effectiveness associated with each training modality. Ultimately, this research aspires to empower educational institutions, corporate entities, and policymakers with evidence-based insights, facilitating informed decisions in the evershifting landscape of training and development. Through the exploration of tangible and intangible aspects, we aim to contribute a valuable resource for stakeholders seeking clarity in the perpetual dilemma of Classroom Training Vs. Virtual Training: Which is more Cost-Effective? [ABSTRACT FROM AUTHOR]