Search Results (419)

The 15 min city concept seeks to promote health, well-being, and quality of life by ensuring that essential services are located within a 15 min walking or cycling distance from housing and are accessible through sustainable modes of transportation. This study aims to evaluate the compliance of this concept in a developing country context and provide supporting evidence by examining if residing within the 15 min reach to basic services affects perceived health, perceived accessibility, and life satisfaction. To assess pedestrian accessibility in Lahore, Pakistan, we adapted the NEXT proximity index—originally developed as part of the Landscape Metropolis Project in Italy—which scores 15 min access using open data sources. A network analysis was conducted to determine the shortest travel times to various points of interest, including education, transportation, healthcare, shops, restaurants, leisure spaces, places of worship, and financial services. Each hexagonal unit in the study area was assigned an access score proportional to its proximity to these facilities. These access scores were then analyzed using multiple regression models, based on survey data collected from 519 university students regarding their perceived health, perceived accessibility, and life satisfaction. According to the network analysis conducted using WorldPop estimates of Lahore’s population, only up to 30% of the population resides in areas that qualify as a 15 min city for each facility type. Moreover, access to bus stops significantly enhances both perceived accessibility and life satisfaction, while proximity to healthcare services shows the strongest positive association with life satisfaction. Full article

Tourism enterprises are increasingly pressured to align competitiveness with sustainability, yet limited evidence exists from Central and Eastern Europe. This study investigates the role of eco-friendly orientation as a determinant of customer satisfaction and perceived competitiveness in the Visegrad Four (Slovakia, Czech Republic, Poland, and Hungary). Empirical research was conducted on a sample of 478 enterprises, including hotels, guesthouses, spas, agritourist facilities, and travel agencies. Data were collected between January and June 2025 using a standardized questionnaire and analyzed through descriptive statistics, factor analysis, Pearson correlation, multiple regression, and ANOVA. The findings demonstrate that enterprises adopting more extensive environmental practices report significantly higher customer satisfaction (r = 0.43, p < 0.01) and perceived competitiveness (r = 0.38, p < 0.01). Factor analysis identified three key dimensions of environmental orientation: ecological operations, ecological innovations, and ecological marketing. Regression analysis highlighted ecological marketing, particularly the adoption of certifications and eco-labels, as the strongest predictor of competitiveness. ANOVA revealed significant cross-country differences, with Slovak and Czech enterprises outperforming Polish and Hungarian counterparts. The results suggest that ecological initiatives are essential for long-term competitiveness, providing both strategic guidance for managers and policy implications for fostering supportive regulatory and financial frameworks across the region. This study makes a novel contribution by offering one of the first large-scale empirical analyses of the link between sustainability and competitiveness in Central and Eastern Europe, a region where such research is still scarce. Theoretically, it extends the application of Ecological Modernization Theory to the tourism sector, while practically it provides actionable recommendations for managers and policymakers on integrating eco-certification and ecological marketing into their strategies. These insights underline the dual role of environmental orientation as a driver of both customer satisfaction and competitive advantage. Full article

The 15-minute city (15MC) model has gained increasing attention as a framework for promoting sustainable urban living by ensuring that essential services, including urban green spaces (UGSs), are accessible within short walking or cycling distances. UGSs play a vital role in public health, social interaction, and environmental resilience, yet questions remain about how equitably they are distributed and accessed in cities. This study assesses proximity and accessibility to UGSs in Porto, Portugal, through the lens of the 15MC. The methodology combined a GIS-based spatial analysis of walking and cycling catchments with a complementary questionnaire to capture user perceptions and travel behaviors. Results show that, while 84% and 100% of residents live within a 15-minute walking and cycling distance of a UGS, respectively, accessibility remains uneven, particularly for walking. Large peripheral parks contribute significantly to provision but remain less accessible to central neighborhoods, and cycling to UGSs is marginal due to fragmented and insufficient infrastructure, and residual cycling use. Subjective findings mirrored the spatial analysis, highlighting dissatisfaction with cycling conditions and only moderate satisfaction with pedestrian environments. The study emphasizes the need for integrated planning that improves local connectivity, infrastructure quality, and spatial equity to fully realize the 15MC vision. Full article

The rapid adoption of electric vehicles (EVs) requires efficient charging infrastructure planning. This study proposes a multi-objective optimization model for siting and capacity planning of EV charging stations, distinguishing between fast and slow chargers. The model integrates investment, dynamic electricity costs, and user experience, factoring in congestion-adjusted travel distances, time-of-use pricing, and queuing delays using an enhanced M/M/c approach. A comparison of algorithm reveals that the simulated annealing (SA) algorithm outperforms the genetic algorithm (GA) and ant colony optimization (ACO) in minimizing total costs. A case study in Changchun’s urban core demonstrates the model’s applicability, resulting in an optimal plan of 15 stations with 110 fast and 40 slow chargers, providing 11,544 kVA capacity at an annual cost of 38.2651 million yuan. Compared to traditional models that ignore charger types and simplify delays, the proposed model reduces total system costs by 4.31%, investment costs by 5.31%, and user costs by 3%, while easing delays in high-demand areas. This framework provides practical insights for urban planners and policymakers, helping balance investment and user satisfaction, and promoting sustainable EV mobility. Full article

To overcome the limitations of traditional methods in emergency response scenarios—such as limited adaptability during the search process and a tendency to fall into local optima, which reduce the overall efficiency of emergency supply distribution—this study develops a Vehicle Routing Problem (VRP) model that incorporates multiple constraints, including service time windows, demand satisfaction, and fleet size. A multi-objective optimization function is formulated to minimize the total travel time, reduce distribution imbalances, and maximize demand satisfaction. To solve this problem, a hybrid deep reinforcement learning framework is proposed that integrates an Adaptive Large Neighborhood Search (ALNS) with Proximal Policy Optimization (PPO). In this framework, ALNS provides the baseline search, whereas the PPO policy network dynamically adjusts the operator weights, acceptance criteria, and perturbation intensities to achieve adaptive search optimization, thereby improving global solution quality. Experimental validation of benchmark instances of different scales shows that, compared with two baseline methods—the traditional Adaptive Large Neighborhood Search (ALNS) and the Improved Ant Colony Algorithm (IACA)—the proposed algorithm reduces the average objective function value by approximately 23.6% and 25.9%, shortens the average route length by 7.8% and 11.2%, and achieves notable improvements across multiple performance indicators. Full article

Rural tourism is a significant driver of socio-economic development in rural areas. However, current offerings are often characterized by monotonous experiences, homogenized products, and a lack of cultural depth, failing to meet tourists’ growing demand for immersive engagement. While some scholars have adopted a spatial perception perspective, a visitor-centered approach remains scarce, with limited focus on methods for analyzing cultural perception. This study takes Dangjia Village, a renowned cultural tourism destination in Hancheng, China, as a case study. By scraping online reviews from travel and social platforms, we employ LDA topic modeling, textual semantic analysis, and IPA to investigate the characteristics and preferences of tourists’ cultural perception. The findings reveal that: (1) Tourists’ cultural perception of Dangjia Village includes three dimensions: History and Culture, Architecture and Culture, and Local Products and Culture. (2) Positive sentiments outweigh negative ones in tourist evaluations. (3) The History and Culture dimension received the highest levels of both attention and satisfaction. Architecture and Culture attracted the least attention but relatively high satisfaction, while Local Products and Culture garnered considerable attention yet the lowest satisfaction. Originating from a visitor perception perspective, this study explores cultural perception characteristics, providing insights for the high-quality utilization and optimization of cultural tourism resources in such villages. Full article

Background: Direct clinical training on real patients is essential in dental education. However, the declining patient inflow increasingly challenges this objective. This cross-sectional study aimed to assess patients’ experiences and preferences to derive recommendations for improving patient recruitment. Material and Methods: Over a period of one year, patients treated by students in the courses and final examinations at the dental school of conservative dentistry were questioned using a specially designed questionnaire and reviewed using their medical records. They were asked about their complete treatment process, and patient files were used to record socio-demographic as well as economic and appointment-specific data. Results: We analysed 297 patients (142 women, 47.8%; 155 men, 52.2%) treated by undergraduates across two semesters (four courses) and two final examinations. Median age was 57.0 years (IQR 46–67; mean 55.2, SD 15.2; range 14–85) with no sex-based difference (p > 0.05). Arrival was predominantly by car (72.7%, n = 216); median one-way distance was 20.5 km (IQR 11.2–32.1); and 58.4% were employed, while 41.6% were not employed (33.7% retired, 7.9% unemployed). The leading reason for course attendance was “satisfaction with previous treatments” (65.32%). Information sources were reported by 290/297 (98%); the most common was already being a course patient (143, 48.1%). Most patients attended one appointment (109, 36.7%). Median travel cost per appointment (including parking) was €17.0 (typically €10.0–€23.5). Of 285 respondents, 93.68% answered “Yes” to satisfaction with student treatment. Conclusions: Important steps include enhancing parking facilities, optimizing recall systems and appointment accessibility, and strengthening relationships with regular patients to encourage word-of-mouth referrals. The main focus is to maintain high clinical quality, ensure affordability, and further reduce patient copayments where possible. Full article

Accessible tourism is a critical aspect of sustainable development, yet many Southeast Asian destinations lack sufficient infrastructure and services for elderly and disabled travelers. This study develops a Mixed-Integer Linear Programming (MILP) framework to optimize travel itineraries, balancing cost, accessibility, and cultural–environmental priorities. A national accessibility database for Thailand was created, encompassing airports, hospitals, public transport nodes, cultural landmarks, and natural attractions. Compared to baseline conventional itineraries—defined as standard travel routes planned without specific accessibility considerations or optimization techniques—the MILP-optimized routes reduce average travel time by 15–20% and improve accessibility scores by 25%. Sensitivity analyses reveal trade-offs between economic efficiency, inclusivity, and infrastructure capacity, while a schematic accessibility network highlights structural fragmentation among airports, hospitals, and secondary attractions. Scenario analyses show that stricter accessibility thresholds improve inclusivity (index: 0.65 to 0.80) but restrict destination options, whereas high-demand scenarios increase costs and reduce inclusivity. A survey of 30 smart wheelchair users indicates high satisfaction with individualized programs and GPS connectivity. These findings underscore the need for investment in multimodal integration, accessibility upgrades, and a national database to enhance inclusive tourism planning. The framework is transferable to other ASEAN countries, contributing to SDG 3, 8, and 11. Overall, this study should be viewed as a prototype or exploratory contribution, with limitations in real-time applicability, generalizability, and implementation of environmental and ethical aspects. Full article

This study explores older passengers’ attitudes, behavior, and evaluations of digital air travel, as well as the impact of digital technologies on this demographic, using China as a case study. The findings of this study offer valuable insights for air transport companies to develop sustainable operational strategies, increase passenger satisfaction, and potentially achieve long-term viability. A structured questionnaire survey was conducted targeting this subgroup, applying the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB) as the primary analytical frameworks. While the study’s sample is skewed towards digitally literate individuals, this subgroup remains highly relevant for analyzing digital impact trends, as they are the most likely to interact with and be influenced by digital air travel tools. This study suggests that older passengers, particularly young-old passengers, in China have a generally positive attitude towards the use of digital air travel tools, with time saving, convenience, and cost saving identified as the top three perceived benefits. Over 80% of participants indicated that digital technology influenced their decision to continue choosing air travel, highlighting a link between digital engagement and sustainable passenger behavior. However, as this study is limited to digitally literate “young-old” passengers in China, the findings should be interpreted as exploratory and context-specific rather than globally generalizable. Future studies are needed with broader age groups and mixed methods to verify these results. Full article

This study investigates the influence of driver-related factors on on-street parking choice by integrating stated preference (SP) and revealed preference (RP) survey methods. A hybrid SP–RP survey was designed to simulate realistic parking scenarios, and 423 valid questionnaires were collected online and offline. Key factors affecting parking choice were identified through descriptive analysis, including user acceptance of differentiated pricing and satisfaction with existing policies. The Kaiser–Meyer–Olkin (KMO = 0.904) and Bartlett’s test (p < 0.001) confirmed data suitability for factor analysis. A binary logistic regression model was developed to quantify variable effects under different travel purposes. Key findings include the following: monthly parking fee had the strongest effect (OR = 6.691, p = 0.010) on parking choice for shopping/entertainment trips; model prediction accuracy ranged from 80.87% to 83.56% across travel purposes; and goodness-of-fit metrics were strong (McFadden R² = 0.630, Nagelkerke R² = 0.772). The results provide empirical evidence on parking choice determinants and support the design of demand-responsive parking policies through dynamic and differentiated pricing strategies. Full article

This study focuses on the challenges of resident mobility in low-density areas. Amid China’s rapid urbanization, rural landscapes and travel patterns are undergoing significant transformation. Using Lanzhou’s rural areas as a representative case study, this research employs questionnaire surveys to collect data. It applies a multi-nominal logit (MNL) model to examine factors influencing travel mode choices and utilizes structural equation modeling (SEM) to assess travel satisfaction—a composite metric derived from residents’ subjective evaluations of convenience, cost, time, and comfort. Findings indicate that private cars and public transportation are the primary travel modes. The MNL model reveals that age and destination accessibility significantly influence travel choices. SEM path analysis further shows that annual household income has a direct positive effect on satisfaction, while age exerts an indirect negative influence through mediating variables. Female satisfaction levels were significantly lower than those of males. Both road density and perceived infrastructure quality significantly enhanced satisfaction, while destination accessibility may exert a slight negative indirect effect by increasing travel expectations. The study theoretically enriches research on rural travel patterns and provides practical insights into rural transportation planning and infrastructure development. Full article

Cultural heritage tourism is a vital part of Malaysia’s tourism sector, attracting visitors to iconic UNESCO sites like George Town and Melaka. However, these heritage sites face growing challenges from overcrowding and environmental degradation, which accelerate the deterioration of historic architecture and cultural artifacts. Preservation efforts often require site closures, which negatively impact tourist experiences and satisfaction. Thus, augmented reality (AR) offers a solution by supporting heritage management and preservation, allowing visitors to engage with virtual representations via mobile AR apps, thereby enhancing visitor engagement and travel experience. Despite global adoption, mobile AR apps often suffer from low user retention, with many users abandoning them shortly after downloading them. Understanding what drives continued usage is crucial for successful AR implementation. This study integrates the expectation confirmation model (ECM) and the unified theory of acceptance and use of technology 2 (UTAUT2) to examine the determinants affecting user’s experiential satisfaction and continued usage intention of mobile AR apps. An online survey of 450 domestic tourists in George Town and Melaka was conducted. Data analysis using structural equation modeling with SmartPLS 4.0 revealed that the integrated model offers a stronger predictive power and significantly outperforms ECM and UTAUT2 individually. The findings contribute valuable insights for researchers, app developers, tourism stakeholders, and policymakers. Full article

With the rapid expansion of the electric vehicle (EV) market, optimizing the distribution of charging stations has attracted increasing attention. Unlike internal combustion engine vehicles, EVs are typically charged at the end of a trip rather than during transit. Therefore, analyzing EV users’ charging preferences based on their activity–travel patterns is essential. This study seeks to improve the operational efficiency and accessibility of EV charging stations in Lanzhou City by optimizing their spatial distribution. To achieve this, a novel multi-objective optimization model integrating NSGA-III and TOPSIS is proposed. The methodology consists of two key steps. First, the NSGA-III algorithm is applied to optimize three objective functions: minimizing construction costs, maximizing user satisfaction, and maximizing user convenience, thereby identifying charging station locations that address diverse needs. Second, the TOPSIS method is employed to rank and evaluate various location solutions, ultimately determining the final sitting strategy. The results show that the 232 locations obtained by the optimization model are reasonably distributed, with good operational efficiency and convenience. Most of them are distributed in urban centers and commercial areas, which is consistent with the usage scenarios of EV users. In addition, this study demonstrates the superiority in determining the distribution of charging station locations of the proposed method. In summary, this study determined the optimal distribution of 232 EV charging stations in Lanzhou City using multi-objective optimization and ranking methods. The results are of great significance for improving the operational efficiency and convenience of charging station location optimization and offer valuable insights for other cities in northwestern China in planning their charging infrastructure. Full article

The COVID-19 pandemic reshaped travel patterns and customer expectations, generating profound challenges for the hotel industry. This study analyzes 50,000 TripAdvisor reviews of New York hotels to examine how customer satisfaction with hotel selection attributes shifted before and during the pandemic. BERTopic was applied to extract eight key attributes, while VADER, PRCA, and Asymmetric Impact–Performance Analysis (AIPA) were used to capture asymmetric effects and prioritize improvements. Comparative analyses by hotel classification, travel type, and customer residence reveal significant shifts in food and beverage, location, and staff, particularly among lower-tier hotels, business travelers, and international guests. The novelty of this study lies in integrating BERTopic and AIPA to overcome survey-based limitations and provide a robust, data-driven view of COVID-19’s impact on hotel satisfaction. Theoretically, it advances asymmetric satisfaction research by linking text-derived attributes with AIPA. Practically, it offers actionable guidance for hotel managers to strengthen hygiene, expand contactless services, and reallocate resources effectively in preparation for future crises. In addition, this study contributes to sustainability by showing how data-driven analysis can enhance service resilience and support the long-term socio-economic viability of the hotel industry under global crises. Full article

This paper proposes a mixed-integer linear programming (MILP) model for the consistent vehicle routing problem with time windows (ConVRPTW), motivated by the need to enhance customer satisfaction in the last-mile logistics industry. The problem involves designing a set of consistent routes for a group of customers whose demand fluctuates from one period to another within a specified planning horizon. The objective is to minimize the cost associated with the number of vehicles used and the total travel time while satisfying service consistency constraints. A tabu search (TS) metaheuristic is implemented to solve the proposed model, and its performance is compared with the optimal solutions. Instances of 10 and 20 customers are designed based on the well-known Solomon instances for VRPTW. Finally, the solutions obtained from the ConVRPTW model are compared with those of a traditional VRPTW model using some key performance indicators (KPIs) to measure the contribution of service consistency to route design. Full article