Search Results (356)

Compared to commuting, grocery shopping trips, despite their profound implications for mixed land use and transportation planning, have received limited attention in travel behavior research. Drawing upon a travel diary survey conducted in a fast-growing metropolitan region of the United States, i.e., Salt Lake County, UT, this research investigated a variety of influential factors affecting mode choices associated with grocery shopping. We analyze how built environment (BE) characteristics, measured at seven spatial scales or different ways of aggregating spatial data—including straight-line buffers, network buffers, and census units—affect travel mode decisions. Key predictors of choosing walking, biking, or transit over driving include age, household size, vehicle ownership, income, land use mix, street density, and distance to the central business district (CBD). Notably, the influence of BE factors on mode choice is sensitive to different spatial aggregation methods and locations of origins and destinations. The straight-line buffer was a good indicator for the influence of store sales amount on mode choices; the network buffer was more suitable for the household built environment factors, whereas the measurement at the census block and block group levels was more effective for store-area characteristics. These findings underscore the importance of considering both the spatial analysis method and the location (home vs. store) when modeling non-work travel. A multi-scalar approach can enhance the accuracy of travel demand models and inform more effective land use and transportation planning strategies. Full article

With the arrival of an aging society and the continuous extension of the human lifespan, the quality of life has not improved in a corresponding manner. People’s demand for happiness and health is increasing. As a result, a model emerged that integrates tourism and medical services, which is health tourism. This growing demand has prompted many service providers to see it as a business opportunity and enter the market. Tourism can help travelers release work stress and restore physical and mental balance; meanwhile, health check-ups and disease treatment can help them regain health. Consumers have long favored health and medical tourism because it helps relieve stress and promotes overall well-being. As people age, some consumers experience a gradual decline in physical functions, making it difficult for them to participate in regular travel services provided by traditional travel agencies. Therefore, this study aims to explore the service needs of health and medical tourism customers (tourists/patients) and the interrelationships among these service needs, so that health and medical tourism service providers can develop more customized and diversified services. This study identifies four key drivers of medical tourism services: medical services, medical facilities, tour planning, and hospitality facilities. This study uses the APA (attention and performance analysis) method to assess each dimension and criterion and utilizes the DEMATEL method with the NRM (network relationship map) to identify network relationships. By combining APA and NRM techniques, this study develops the APA-NRM technique to evaluate adoption strategies and identify suitable paths for health tourism services, providing tailored development strategies and recommendations for service providers to enhance the service experience. Full article

The sharing economy is considered to be a potentially efficacious approach for promoting sustainable production and consumption (SPC). This study utilizes dockless bike sharing (DBS) in Beijing as a case study to examine how sharing economy policies and business practices advance SPC. It also dynamically quantifies the environmental and economic performance of DBS practices from a life cycle perspective. The findings indicate that effective SPC practices can be achieved through the collaborative efforts of multiple stakeholders, including the government, operators, manufacturers, consumers, recycling agencies, and other business partners, supported by regulatory systems and advanced technologies. The SPC practices markedly improved the sustainability of DBS promotion in Beijing. This is evidenced by the increase in greenhouse gas (GHG) emission reduction benefits, which have risen from approximately 35.81 g CO₂-eq to 124.40 g CO₂-eq per kilometer of DBS travel. Considering changes in private bicycle ownership, this value could reach approximately 150.60 g CO₂-eq. Although the economic performance of DBS operators has also improved, it remains challenging to achieve profitability, even when considering the economic value of the emission reduction benefits. In certain scenarios, DBS can maximize profits by optimizing fleet size and efficiency, without compromising the benefits of emission reductions. The framework of stakeholder interaction proposed in this study and the results of empirical analysis not only assist regulators, businesses, and the public in better understanding and promoting sustainable production and consumption practices in the sharing economy but also provide valuable insights for achieving a win-win situation of platform profitability and environmental benefits in the SPC practice process. Full article

Understanding the carbon emissions of multimodal travel—comprising walking, metro, bus, cycling, and ride-hailing—is essential for promoting sustainable urban mobility. However, most existing studies focus on single-mode travel, while underlying spatiotemporal and behavioral determinants remain insufficiently explored due to the lack of fine-grained data and interpretable analytical frameworks. This study proposes a novel integration of high-frequency, real-world mobility trajectory data with interpretable machine learning to systematically identify the key drivers of carbon emissions at the individual trip level. Firstly, multimodal travel chains are reconstructed using continuous GPS trajectory data collected in Beijing. Secondly, a model based on Calculate Emissions from Road Transport (COPERT) is developed to quantify trip-level CO₂ emissions. Thirdly, four interpretable machine learning models based on gradient boosting—XGBoost, GBDT, LightGBM, and CatBoost—are trained using transportation and built environment features to model the relationship between CO₂ emissions and a set of explanatory variables; finally, Shapley Additive exPlanations (SHAP) and partial dependence plots (PDPs) are used to interpret the model outputs, revealing key determinants and their non-linear interaction effects. The results show that transportation-related features account for 75.1% of the explained variance in emissions, with bus usage being the most influential single factor (contributing 22.6%). Built environment features explain the remaining 24.9%. The PDP analysis reveals that substantial emission reductions occur only when the shares of bus, metro, and cycling surpass threshold levels of approximately 40%, 40%, and 30%, respectively. Additionally, travel carbon emissions are minimized when trip origins and destinations are located within a 10 to 11 km radius of the central business district (CBD). This study advances the field by establishing a scalable, interpretable, and behaviorally grounded framework to assess carbon emissions from multimodal travel, providing actionable insights for low-carbon transport planning and policy design. Full article

Online reviews play a critical role in shaping consumer decisions and providing valuable insights to enhance the products and services for businesses. As visual content becomes increasingly prevalent in reviews, it is essential to understand how image complexity influences review helpfulness. Despite the growing importance of images, the impact of color diversity and texture homogeneity on review helpfulness remains underexplored. Grounded in Information Diagnosticity Theory and Dual Coding Theory, this study investigates the relationship between image complexity and review helpfulness, as well as the moderating role of review text readability. Using a large-scale dataset from the hotel and travel sectors, the findings reveal that color diversity has a positive effect on review helpfulness, while texture homogeneity follows an inverted U-shaped relationship with helpfulness. Furthermore, text readability strengthens the positive impact of texture homogeneity, making moderately homogeneous images more effective when paired with clear and well-structured text. Heterogeneity analysis demonstrates that these effects vary across product categories. The results advance the understanding of multimodal information processing in online reviews, providing actionable guidance for platforms and businesses to refine the review systems. Full article

Sustainable tourism has become a strategic imperative, particularly in Bali Island, where tourism drives regional economic growth. In this study, we investigate the mediating role of green service innovation in the relationship between the marketing mix and business performance among small and medium-sized enterprises (SMEs) in Bali Island’s tour and travel sector. We seek to understand how sustainability-oriented innovation contributes to enhancing SME competitiveness and long-term performance. A quantitative approach was adopted, using structured survey data from 387 tour and travel business owners registered with the Bali Provincial Tourism Office. Structural Equation Modeling (SEM) was employed to assess both the direct effects of the marketing mix on business performance and the indirect effects mediated by green service innovation. The findings indicate that the marketing mix does not directly influence green service innovation or business performance. However, green service innovation significantly enhances business performance, confirming its mediating role. This suggests that traditional marketing strategies are insufficient unless aligned with sustainability-driven innovation. Green service innovation acts as a strategic resource that strengthens business performance in tourism SMEs. We provide theoretical and practical insights into how integrating sustainability into marketing and operational strategies can enhance SMEs’ competitiveness and support sustainable tourism development. Full article

This study explores the intersection of virtual reality tourism, digital innovation in digital transformation and corporate sustainability-driven business transformations in tourism strategies, and sustainability-driven business transformations in tourism. By reducing the environmental footprint associated with traditional travel, VR-based tourism presents an innovative solution to promote sustainable tourism. Through three empirical studies, we investigate how immersive 360-degree VR experiences influence psychological well-being and meaning in life as influenced by sustainable VR experiences. Our findings reveal that VR travel enhances engagement, fosters cultural appreciation, and provides an alternative to high-emission tourism, thus contributing to environmental sustainability-driven business transformations in tourism. The study offers managerial and policy implications for tourism stakeholders seeking to integrate digital transformation strategies into sustainable tourism development. Full article

Rural tourism is growing as travelers seek authentic experiences with local traditions, culture, and heritage. This form of tourism plays a key role in the sustainable development of rural areas by effectively utilizing rural resources. To ensure its continued success, best practices must be adopted to enhance the visitor experience while ensuring long-term viability. Research on rural tourism in the villages of Sremski Karlovci, Irig, and Vrdnik in Fruška Gora (Serbia) and Pienza, Montalcino, and San Gimignano in Tuscany (Italy), involving 357 tourists, identified four key factors influencing their experiences: ‘Organic Heritage’, ‘Authentic Comfort’, ‘Authentic Flavors’, and ‘Warm Farmstead’. These factors show that the motivations driving tourists to rural destinations and village accommodations are universal. However, Tuscan villages attract more tourists due to their superior infrastructure, diversified offerings, and strong international promotion, attracting wealthier tourists who tend to stay longer and spend more. Stakeholder research (58 participants) confirmed that Fruška Gora must improve infrastructure, diversify experiences, and strengthen promotional efforts to enhance sustainability and competitiveness. These changes are essential for the long-term success of rural tourism businesses in the future. Full article

Telework emerged in the 1970s with the advent of Information and Communication Technologies (ICT) as a potential substitute for commuting trips and an answer to avoid congestion. While early studies supported this substitution effect, subsequent research has presented contradictory findings, with some studies demonstrating complementary effects and increased travel distances, while others show a reduction in travel or mixed results. These discrepancies may arise from methodological differences in study design, sampling, and modeling approaches. To analyze these factors, a systematic literature review complemented by three meta-analyses was developed. OLS and GLS-RE models were built to measure telework impacts on the number of trips (total and by purpose), commuting distance, and total distance traveled. Our research suggests that while telework reduces commuting and business trips, particularly for full-time teleworkers, it may increase commuting distances. Total distance traveled presents mixed results, heavily dependent on research design. By identifying these patterns, we outline methodological directions for future research, including improved sampling strategies, advanced modeling techniques, and rigorous control variable selection. Full article

Background: Logistics and transport, core of many business processes, are continuously optimized to improve efficiency and market competitiveness. The paper describes a modular coordination of vehicle routing and bin packing problems that enables independent instances of the problems to be joined together, with the aim that the vehicle routing solution satisfies all the constraints from real-world applications. Methods: The vehicle routing algorithm is based on an adaptive memory procedure that also incorporates a simple, one-dimensional bin packing problem. This preliminary packing solution is refined by a complex, three dimensional bin packing for each vehicle to identify the infeasible packages. The method iteratively adjusts virtual volumes until reaching near-optimal routes that respect bin-packing constraints. Results: The coordination enables independent applications of an adaptive memory procedure to vehicle routing and a genetic algorithm approach to bin packing while joining them in a computationally tractable way. Such a coordinated approach is applied to a frequently used public benchmark and proven to provide commensurate costs while significantly lowering algorithm complexity. Conclusions: The proposed method is further validated on a real industrial case study and provided additional savings of 14.48% in average daily distance traveled compared to the current industrial standard. Full article

This study introduces a novel forecast combination method for monthly Japanese tourism demand, analyzed at both aggregated and disaggregated levels, including tourist, business, and other travel purposes. The sample period spans from January 1996 to December 2018. Initially, the time series data were decomposed into high and low frequencies using the Ensemble Empirical Mode Decomposition (EEMD) technique. Following this, Autoregressive Integrated Moving Average (ARIMA), Neural Network (NN), and Support Vector Machine (SVM) forecasting models were applied to each decomposed component individually. The forecasts from these models were then combined to produce the final predictions. Our findings indicate that the two-stage forecast combination method significantly enhances forecasting accuracy in most cases. Consequently, the combined forecasts utilizing EEMD outperform those generated by individual models. Full article

The COVID-19 pandemic severely affected Japan’s tourism-related industries, leading to significant revenue losses in the accommodation, restaurant, and tourist facility sectors. Many businesses experienced difficult situations, resulting in closures and layoffs as a result of the prolonged decline in tourism demand. Focusing on the first half of the pandemic (2020–2021), this study analyzes the loss of sales and the influencing factors among tourism-related businesses in the Nishimikawa region of Aichi Prefecture. A questionnaire survey was conducted in November 2021, and changes in sales from April 2020 to September 2021 were estimated to assess the economic impact across different sectors. A quantitative analysis was also performed to examine the relationship between sales and the state of emergency, the domestic travel subsidy program Go To Travel campaign, and business attributes. The results indicate that COVID-19 severely impacted business sales, especially in the accommodation and food service sectors, while the tourism facility and retail sectors were less affected. In the Nishimikawa region, popular for day trips from nearby areas, the Go To Travel campaign had a limited effect, highlighting the need for region-specific support measures. Full article

In the digital era, user-generated online reviews serve as a valuable resource for understanding visitor experiences in cultural institutions. This study analyses sentiments and thematic trends in TripAdvisor reviews of mountain museums, using Latent Dirichlet Allocation topic modelling and sentiment analysis. A dataset of 2157 reviews from ten museums was classified into local and non-local perspectives, revealing significant differences in visitor expectations. Findings indicate that local visitors prioritize historical authenticity and educational value, whereas non-local visitors emphasize aesthetic appeal, interactivity, and cultural immersion. Sentiment analysis highlights generally positive perceptions, with business travellers and groups of friends reporting the highest satisfaction levels. Comparative analysis across visitor types reveals distinct engagement patterns, with families valuing child-friendly exhibits, couples seeking cultural enrichment, and solo travellers focusing on intellectual depth. These insights inform strategic recommendations for museum management, including multilingual content, interactive elements, and guided tours dedicated to specific visitor profiles. Despite limitations related to lack of real-time feedback, this research demonstrates the potential of sentiment analysis in enhancing museum experiences. Future studies should integrate multimodal analysis and real-time tracking to further refine visitor experience evaluation. Full article

Travel and tourism are essential to global economies, generating social, economic, and environmental impacts. However, there is a lack of standardized methodologies to assess the environmental footprint of tourist destinations beyond carbon footprint analysis. This study introduces the Greentour tool, the first of its kind to evaluate the environmental impact of accommodation, restaurants, and tourism activities using nine environmental indicators from a life cycle assessment (LCA) perspective. The tool applies a hybrid bottom-up and top-down approach, integrating data from tourist establishments and destination managers. The tool was tested in four tourist destinations in Spain and Portugal (Rías Baixas, Camino Lebaniego, Lloret de Mar, and Guimarães), revealing that transportation is the primary contributor to environmental impacts, ranging from 60% to 96% of total emissions, particularly in air-travel-dependent destinations. Food and beverage services are the second-largest contributor, accounting for up to 26% of emissions, while accommodation ranks third (1–14%). This study highlights the significant role of electricity consumption and food choices (e.g., red meat and dairy) in greenhouse gas (GHG) emissions, emphasizing the need for sustainable alternatives. Despite challenges in data collection, particularly for food and transport statistics, the Greentour tool has demonstrated robustness and adaptability across diverse destinations, making it applicable worldwide. This tool provides key insights for policymakers, tourism stakeholders, and businesses, supporting the integration of sustainability strategies into public policies and industry best practices. Future research should focus on expanding its use to additional destinations to foster science-based decision-making and promote more sustainable tourism practices globally. Full article

This study examines how economic growth, travel, global connection, and changes in population impact the environmental footprint in seven countries, including Russia, the US, China, France, the UK, Pakistan, and India, from 1995 to 2023. The results show a significant link between Granger’s environmental impact and some economic, non-economic, and population factors in these countries. According to the study, environmental impacts result primarily from economic expansion and tourism revenue generation. The essential activities in economic development frequently result in significant ecological deficits through natural resource depletion, land alterations, and environmental releases. Business enlargement and tourism income commonly bring about deforestation while causing both pollution and habitat damage, thus showing why sustainable practices must exist to protect nature during economic development. We also have to consider factors other than economics, such as total income from natural resources and using nuclear power early. Additionally, how many people live in a particular area and the number of children born contribute to these footprints. Also, this study shows how economic, non-economic and demographic issues can indicate what harm the environment might face later. This is especially important in countries that use nuclear energy extensively. The report suggests different ways to solve this problem. These include advocating for sustainable tourism practices, directing research efforts towards nuclear energy, supporting renewable energy initiatives, promoting family planning and education, and raising public awareness. The aim is to reduce the environmental harm caused by nuclear energy and promote a more sustainable future. Full article