Tourism Revenue Research Articles

Policy Effect and Mechanism of China’s MSRI on Inbound Tourism Along the Route

ABSTRACT This paper adopted a difference-in-differences method and panel datasets were divided into 20 MSR countries and 60 non-MSR countries between 2010 and 2019 to identify the MSRI’s effects and mechanisms behind on inbound tourism. Results show that the MSRI had a significant and direct positive effect on inbound tourism among associated countries. Compared with the tourist arrivals (ITN), the positive effect on the inbound tourism revenue (ITR) was stronger. The MSRI increased these countries’ ITR and ITN by 27.4% and 15.0%. The positive effect on ITR demonstrated a fluctuating but rising trend. The MSRI had boosted inbound tourism by reducing social risk, enhancing infrastructure, and facilitating trade among associated countries. The MSRI had a higher inbound tourism promotion effect on countries in South Asia, West Asia and North Africa, high-income countries, lower-middle-income countries and countries with low tourism resource endowment.

A Review Geospatial Artificial Intelligence (GEO-AI): Implementation Of Machine Learning On Urban Planning

Geospatial Artificial Intelligence (Geo-AI) is an interesting topic in its development and application in our lives. One of them is spatial planning, which contributes to the economic and social development of a region or country. Spatial data is the main thing in this research, which maximizes the effectiveness of land use spatial data on the area as upstream data and develops GIS-based urban planning applications to display the results of analysis and predictions of urban objects automatically. On the other hand, to maximize tourism revenue, the government plans urban areas for both spatial and land use and makes a lot of spatial data based on geographical and environmental conditions. This study will analyze the benefits of Geo-AI in urban planning and the tourism sector. The method used in this study is the Systematic Literature Review (SLR), where the search for the required articles comes from electronic databases obtained using the NVivo software with article sources from Publish or Perish. This study discusses the main steps for the analysis of geospatial data that have been successful in the main areas, namely the development of applications and models, including visualization. By treating issues in geospatial artificial intelligence, the overall aim of the research is to improve the quality of life for Indonesia's growing urban population. The results of the study with the systematic literature review of Geo-AI found a gap in the research implementation of the machine learning model used where five models were compared and relevant to the geospatial dataset displayed in the form of a literature review matrix and visually included in the relevant keywords in the bibliometric analysis. Interdisciplinary results are developing and are urgently needed by both government and private stakeholders in the development of smart cities to prepare spatial planning in urban areas and strategies in optimizing technology in the field of spatial planning in implementing systems based on Geo-AI.

DAMPAK INDIKATOR PARIWISATA TERHADAP PERTUMBUHAN EKONOMI REGIONAL (STUDI PANEL PROVINSI-PROVINSI INDONESIA)

Tourism in Indonesia is still regarded as an ordinary industry. However, it has the potential to drive economic growth. This paper uses panel data regression to investigate how several tourism indicators, like tourist expenditure, accommodation availability, and number of workers, affect regional tourism revenue in Indonesia and how regional tourism revenue affects GRDP. Results show that domestic tourist expenditure and accommodation availability positively impact regional tourism revenue and are statistically significant. It was also found that the effect of regional tourism revenue on GRDP is positive and significant. It is recommended that the local government improve the quality and increase the quantity of accommodation.
 
 Keywords: Tourism Revenue, Tourism Labor, Tourist Expenditure, Accommodation, GRDP

Ticket Pricing and Spatial Heterogeneity of Scenic Spots in China: A Spatial Hedonic Pricing Approach

ABSTRACT Ticket pricing and tourism revenue are crucial to scenic spots. In China, pricing strategies for scenic spots differ due to regional differences. This paper aims to identify the pricing mechanism and spatial effects of ticket pricing across regions from a macro perspective. We employ a spatial hedonic pricing approach, including the spatial lag model (SLM), the spatial error model (SEM) and geography weighted regressions (GWR) to investigate the spatial dependence and heterogeneity of ticket pricing by using data from national-level scenic spots in China. The empirical results based on the spatial hedonic model suggest that the pricing mechanism varies in space and is influenced by the combination of government-pay and user-pay. The semiparametric geographically weighted regressions further show the spatial heterogeneity of ticket prices, indicating regional differences in the pricing mechanism. Specifically, tourists would pay more for tourism resources in peripheral regions; scenic spots in less developed regions usually implement high ticket price strategies. Our study provides a new approach to exploring the spatial effects of ticket pricing. Knowledge about the differentiated pricing mechanism across regions not only sheds light on ticket revenues of tourist destinations in the Chinese context but also contributes insights to address similar issues better elsewhere in the world.

How air pollution affects tourism revenue: evidence from China

ABSTRACT It is acknowledged that air pollution has a detrimental impact on tourism revenue, but the mechanisms behind this impact remain unknown. Previous studies have merely assumed that air pollution affects tourism revenue through the number of tourists. Based on the inbound tourism data of 47 major tourist cities in China from 2005 to 2017, this study reveals that in addition to lowering the number of tourists, air pollution also reduces tourist expenditure per capita by shortening their length of stay, ultimately leading to a decrease in tourism revenue. The finding is robust even when the endogeneity of air pollution is considered. Moreover, the results also show that the impact of air pollution on tourism revenue, tourist flow, tourist expenditure per capita, and length of stay is nonlinear. The findings of this paper contribute to an accurate assessment of the economic consequences of air pollution on tourism.

Digital financial inclusion and domestic tourism demand: Through the lens of spatial spillover

Domestic tourism demand has dominated the global tourism market and has been more resilient during the COVID-19 pandemic; yet, it is under-studied compared to international tourism demand. Digital financial inclusion (DFI) enables the provision of formal financial products and services to small and medium-sized tourism enterprises and tourists through cost-effective digital means, potentially boosting domestic tourism demand. Integrating micro- and macro-level data from 335 prefecture-level regions in China, we investigate the impact of DFI on domestic tourism demand using spatial panel models. Our analysis reveals significant and positive effects, both direct and spillover, of DFI on domestic tourism demand within a region and across regions. Notably, among the three dimensions of DFI, the usage depth exhibits the most substantial spillover effects. Furthermore, our findings also highlight the crucial role of DFI in internalizing domestic tourism revenues. Our study provides practical implications for sustainable domestic tourism development in the digital era.

Research on the Integration and Development of Intangible Cultural Heritage and Tourism Management Industry in the Context of Digitization

Abstract This study employs the entropy power method to disaggregate the development potential of intangible cultural tourism resources in Area Z, further analyzing these resources via the RMP model. This model comprehensively evaluates the quantity and categorical structure of Area Z’s intangible tourism resources. Additionally, this research explores the dynamics of intangible tourism product design, focusing on the interplay between intangible tourism resources and products, herein referred to as the R-P relationship. The Herfindahl index serves as the primary analytical tool in this paper to assess and quantify the degree of integration between the tourism and cultural industries in Area Z. The findings reveal that the most significant developmental potential lies in the appeal of non-heritage resources and products, which score 50.8 in terms of development value. Intangible tourism resources in Area Z are abundant and diverse, with skill-based resources constituting 50% of the total. From 2014 to 2023, tourism revenue in Area Z surged from 28.046 billion yuan to 69.915 billion yuan, indicating substantial market potential. The design of non-heritage tourism products should, therefore, prioritize items with significant collectible and cultural heritage value. The integration index between the cultural industry and the tourism management industry in Area Z is measured at HI=0.6058, while the core product index for non-heritage and tourism stands at HI=0.2604. This paper underscores the critical role of strategic resource allocation and product design in maximizing the economic impact and cultural preservation of intangible tourism resources.

Exploring the High-Quality Development of Smart City Tourism in the Information Age

Abstract This article discusses the high-level guidance strategy and deep-level value embodiment of tourism informatization construction for smart city tourism. Based on the existing evaluation system of intelligent city tourism development, the article utilizes BP neural network for data screening. It combines the entropy weight method to complete the index assignment, and evaluates and analyzes the development of innovative tourism services in six intelligent cities. In the area of brilliant tourism information service, Beijing scored 94%. In clever catering and accommodation services, Beijing leads with a score of 90%, while Nanjing and Chengdu rank second and third with scores of 81% and 80% respectively. Regarding overall innovative tourism development, Beijing scored 0.4731, 0.1762, and 0.1168 in terms of scientific and technological innovation, economic development, and general development security, respectively. In addition, the intelligent tourism development trend from 2018 to 2022 shows that Beijing’s tourism revenue will reach 622.46 billion yuan in 2022, which is 30.36 billion yuan more than the previous year. By evaluating the development of intelligent city tourism services through BP neural network, this paper effectively identifies the critical factors for developing clever tourism construction. It puts forward effective strategies to improve the level of intelligent services. These findings have important theoretical and practical significance for the development of intellectual city tourism field, and provide an essential reference for the further optimization of smart city tourism services.

ЕФЕКТИВНІСТЬ ТА ПРІОРИТЕТНІ НАПРЯМИ РОЗВИТКУ СТРАТЕГІЧНОГО УПРАВЛІННЯ ТУРИСТИЧНОЮ ДЕСТИНАЦІЄЮ МІСТОМ КИЄВОМ В УМОВАХ ПАНДЕМІЇ COVID-19 ТА ВОЄННОГО СТАНУ

The main purpose of this study is to develop a mechanism for strategic management of the tourist destination of Kyiv in the context of the COVID-19 pandemic and martial law. The methodology involves a mixed approach that combines the collection and analysis of qualitative and quantitative data to assess the impact of these conditions on tourism and develop recommendations for strategic management. The results showed a significant decline in tourism revenues, shifts in the demographic structure of tourists, and changes in travel behavior. Strategic management measures, such as strengthening digital marketing, diversifying tourism products, and strengthening local partnerships, were identified as crucial for the recovery and sustainability of Kyiv’s tourism sector. The study offers practical recommendations for improving strategic tourism management, ensuring sustainability and resilience to future challenges.

Optimization study of tourism total revenue prediction model based on the Grey Markov chain: a case study of Macau

<abstract> <p>The GM (1, 1) model, grounded in gray system theory, utilizes first-order cumulative data for forecasting. While offering simplicity and efficiency, its applicability is confined to such data. In light of the constraints inherent in the conventional gray GM (1, 1) prediction model when confronted with stochastic data fluctuations, the residual correction methodology was deployed to enhance the predictive efficacy of the GM (1, 1) model. Subsequently, an augmented model underwent refinement through the application of the Markov chain, giving rise to a sophisticated and optimized gray Markov chain prediction model. The efficacy of this novel model was substantiated through a case study involving the prediction of Macao's aggregate tourism revenue. A comparative analysis was conducted between the outcomes generated by the traditional gray prediction model, those of the refined prediction model, and the empirical data pertaining to tourism. This scrutiny validated the proficiency and precision of the optimized prediction model. The process of model optimization manifested a discernible enhancement in both predictive accuracy and stability, thereby broadening the prospective applications of gray prediction models. This endeavor aspired to furnish a scientifically grounded point of reference for the advancement of tourism within the Guangdong-Hong Kong-Macao Greater Bay Area and, indeed, throughout China. Moreover, it introduced a fresh methodology that held promise as a decision-making support mechanism for the developmental trajectory of Macao's tourism industry.</p> </abstract>

An Exploration of Tourism Marketing Strategies of “Ethnicity + Folklore + Folk Lodging” in Guizhou Province Based on Echo State Network Modeling

Abstract Due to the improvement of national consumption levels, the Guizhou tourism industry plays an increasingly important role in the economy of Guizhou province, and the proportion of tourism revenue to GDP is increasing. We combine the improved FOA algorithm with an echo-state network, taking into account the characteristics of Guizhou tourism demand, to construct an AFOA-ESN prediction model for Guizhou tourism demand. The new algorithm fixes the problems with the old Drosophila algorithm by changing the number of Drosophila populations, the size of the search step, and the best place for the first iteration. This makes the new algorithm better at local searches and more efficient. We select the annual data on the number of travelers to Guizhou from ten provinces as the dataset and apply the simulation analysis method to test the effectiveness of the previously mentioned prediction model. The data show that among the ten sets of experiments, the AFOA-ESN prediction model has seven times the smallest MAPE value, while the AFOA-ESN model has six times the smallest MSE value. In addition, the consumption structure of Guizhou tourism tourists from 2010 to 2022 did not change much in this stage, showing the development of shock, sensitivity, and vulnerability. Based on the analysis results, we propose the tourism marketing strategy of “Ethnicity + Folklore + Folk Lodging.” This study selects forecast information suitable for the tourism industry and provides the necessary reference for decision-making in tourism-related departments.

A Logical Rationale for Sports Tourism to Help Rural Revitalization under Integrated Transfer Learning Strategy

Abstract As an emerging driving force to promote rural revitalization, sports tourism provides tourists with rich experiences and effectively promotes the development of local sports industry and economy. In this study, an integrated transfer learning model is constructed to assess the development level of rural revitalization by combining a constrained LightGBM-based learner, a Gaussian distribution and an optimized sampling function. Applying this model, this paper calculates the integrated development index of rural revitalization for 21 provinces, municipalities and autonomous regions in China between 2019 and 2023. Particularly for Tianjin, the study finds that its comprehensive development index for rural revitalization is relatively low, only 0.244 in 2023. Analyzing the cases of six typical villages in Tianjin, the study finds that sports tourism significantly impacts rural revitalization. During the five years, the average annual growth of tourist arrivals amounted to 125,400 visitors, and the average tourism revenue in 2023 reached 9.686 billion yuan. Meanwhile, these villages had an average of 3.79 points in the development level of living affluence, which is a high level. The study provides empirical support for sports tourism to help rural revitalization. It provides practical references for the future development direction and planning of rural sports tourism, emphasizing the critical role of sports tourism in promoting the comprehensive development of villages.

Research on passenger flow prediction of tourist attractions by integrating differential evolution and GWO optimization

Abstract With the rapid development of tourism, the rapid growth in the number of tourists caused by the imbalance of the passenger flow carrying capacity of tourist attractions, tourist crowding, overloading, and other problems caused by the frequent occurrence of safety accidents, to the tourist attractions has caused a huge negative impact. For this reason, this paper constructs a model for predicting passenger flows at tourist attractions based on the GWO algorithm. Optimizing the model involves using a differential evolutionary algorithm following a feature study with the Gray Wolf Optimization (GWO) algorithm. Then, for the problems that are prone to occur in the fusion of the GWO algorithm and DE algorithm for solving nonlinear systems of equations, a combined GWO-DE-SVM model is proposed to realize the accurate prediction of tourist attractions’ passenger flow. On this basis, the prediction effect of the GWO-DE-SVM combination model is examined. The loss values of the model in the training set and test set of this paper are around 0.034 and 0.029, respectively, with the lowest average error of 2.524% among all the models. The passenger flow and the total tourism revenue of W tourist attraction in the coming year are successfully predicted in the practical application, which is estimated to be 681 million and 106.88 million yuan, respectively. Million and 106.88 million yuan are the respective amounts. And two peaks of tourist attractions in W were predicted in May and October. This study provides a scientific basis for the management of scenic spots to prevent tourist crowding.

The Impact of Tourists' Misbehavior on the Tourism Economy in Bali: A Case Study and Economic Analysis

The portrayal of tourists' misbehavior via social media and news channels has emerged as a significant factor shaping Bali's tourism economy. Predominantly fueled by these digital platforms, negative depictions of tourists' misconduct influence perceptions and potentially disrupt Bali's tourism landscape. This study explores the intricate interplay between these portrayals and their tangible effects on the island's economic sustainability. The impact of negative portrayals manifests in various dimensions within Bali's tourism economy. Firstly, these depictions wield the potential to dissuade potential tourists, resulting in a decline in tourist arrivals. Consequently, a reduction in visitor numbers directly impacts the island's tourism revenue, affecting diverse sectors reliant on tourism expenditure, such as hospitality, accommodations, local businesses, and employment opportunities. An in-depth economic analysis reveals the consequential aftermath of decreased tourism revenue. Bali's economy faces challenges encompassing diminished government income, reduced investments, and the potential destabilization of livelihoods for communities dependent on the tourism sector. Strategic mitigation strategies emerge as imperative in addressing these economic implications. The study advocates for the adoption of responsible tourism practices, the restoration of Bali's positive image, economic diversification initiatives, and investments in alternative income sources beyond tourism. In conclusion, the abstract underscores the profound influence of negative portrayals of tourists' misbehavior on Bali's tourism economy. By analyzing the tangible economic consequences and advocating for sustainable strategies, Bali aspires to mitigate the adverse effects, fostering a resilient and diversified economy capable of withstanding disruptions in the tourism sector while ensuring sustainable growth and prosperity

Viability Measurement of Hydropower Projects

Evaluating the viability of hydropower projects involves a comprehensive examination of costs and benefits. Economic analysis extends to broader impacts, such as fuel diversification, market advantages, production cost savings, job creation, and improved reliability. Benefit-cost analysis compares monetary costs and benefits, including direct and indirect community effects. This study has used literature survey method to provide insights into projected and actual outcomes, supported by guidelines from institutions like ADB, UNIDO, and the World Bank. Financial benefits of hydropower projects involve optimizing energy output and revenue from Power Purchase Agreements. Economic benefits include fuel diversification, market impacts, navigation, tourism, water supply, and tax revenues. Costs related to physical properties, structures, and resettlement are evaluated using the Price Quantity (PQ) method, while rental income and business losses are assessed through opportunity cost analysis. The loss of crops and trees is evaluated based on expected yields. This approach ensures a thorough understanding of both financial viability and broader economic impacts.

Analysis of Amenities in Increasing Tourism Revenue at Curug Cigentis Karawang

This research aims to find out about the state of amenities at one of the tourist attractions in the southern area of Karawang Regency, namely Curug Cigentis which is at the foot of Mount Sanggabuana. Amenities consist of health hygiene facilities, security, communications, amusement rides, accommodation, souvenir shop, prayer room, parking area, toilet, restaurant. From several amenity components in this tour, can we determine changes in tourist attractions. This research uses a qualitative descriptive method where data collection is carried out using interviews with 82 visitors. Business managers and owners at the Curug Cigentis tourist location, and secondary and primary data needed in this research. The results of this research show that the amenities owned and prepared by the management of Curug Cigentis really help tourist activities. Because there is cleanliness, health, security, communication, amusement rides, souvenir shops, prayer rooms, parking lots, toilets, restaurants. However, there are differences in rates for car parking fees, you have to add costs for communication availability by purchasing WiFi, and paying for the swimming pool at the Curug Cigentis tourist location. Meanwhile, MCK is available for free and for food and drink prices there is equal price, if you want to buy it at any stall along Curug Cigentis the price is the same. Good handling of amenities will increase income because visitors will want to visit the tourist location because they feel that supporting facilities are available, providing a sense of security and comfort.

Historical Nostalgia and Destination Loyalty Intention: Mediating Role of Perceived Value and Satisfaction among Visitors of Cultural Heritage Sites of Nepal

Background: Heritage sites of Nepal are the center of attraction for national and international visitors. It is essential to delve into the factors that drive visitors to these destinations, which are influenced by the narratives and cultural significance associated with Nepal's heritage sites. Objective: The purpose of this paper is to examine the mediating role of Perceived Value (PV) and Satisfaction (SAT) in the relationship between Historical Nostalgia (HN) and Destination Loyalty Intention (DLI) among visitors of cultural heritage sites of Nepal. Methods: The research applied a cross-sectional survey research design to collect data from 256 domestic tourists. The purposive sampling method was used to reach the respondents. Partial Least Squares Structural Equation (PLS-SEM) was applied to test hypotheses. Results: The paper findings showed that perceived values do not mediate the relationship between historical nostalgia and destination loyalty intention but show a direct effect between historical nostalgia and destination loyalty intention whereas satisfaction displays the role of mediation between historical nostalgia and destination loyalty intention. Further, historical nostalgia positively influences perceived value and satisfaction, leading to increased destination loyalty intention. Moreover, the impact of perceived value on destination loyalty intention was not supported. Conclusions: This paper can help destination managers design marketing strategies to evoke historic nostalgia and improve visitor experiences at Nepal's heritage sites. The tourism board can apply the findings to enhance destination loyalty and increase the tourism revenue of Nepal.

Interdependence in Coastal Tourist Territories between Marine Litter and Immediate Tourist Zoning Density: Methodological Approach for Urban Sustainable Development

The coastal strip, characterized by the urbanization of coastal tourist territories (CTTs), has expanded over decades through civil engineering, altering the shoreline dynamics and creating artificial beaches crucial for tourism. To examine the relationship between extensive land use in CTTs for tourism and residences and the presence of marine litter, a specific parametric study was conducted along the coast of Tenerife, the largest island in the Canary Islands. Due to Tenerife’s geographical location and exposure to the descending Gulf Stream flow, the coastal waters in the selected zone experience waste impact at both local and global scales. However, the presence of marine litter deposited by ocean currents is at a micro level and falls outside the scope of this report. This study parameterised urban reality in study areas, and the presence of macro waste has been parameterised using standardised units of measurement. This enables the establishment of source measurements that will contribute to preventative measures against this type of coastal pollution. The interdependence between tourist zoning, civil seafront engineering works along the seafront, and marine litter presence in inaccessible and visible areas for tourists requires a methodology to better understand waste origin and loading areas. This knowledge is crucial for an effective local monitoring system. A quantitative overlay reading methodology has been designed in the urban setting through calculations of urban densities, while examining the waste in these areas’ immediate infralittoral flooring through the use of visual underwater extraction. Anticipating the type and quantity of waste in each area will allow for the implementation of effective awareness, promoting action for preventative and corrective measures at the urban level. The results show a direct dependence between urban density and the presence of waste, as well as an equation that makes it possible to anticipate the amount of waste according to urban density and its relational vector. There is no discontinuity between them, as each area is affected by others to the extent that they establish the parametric continuity conditions determining each field. Therefore, it is possible to relate them beyond a one-on-one relationship. This approach fosters sustainable tourism development, reducing pressure on the sea and enhancing the utilisation of tourism revenues in measures to address waste-related challenges and promotes sustainable tourism development in Europe’s coastal regions.

PANEL ANALYSIS ON THE TOURISM SECTOR OF SELECTED MEDITERRANEAN COUNTRIES

The tourism industry is a dynamic sector for the economies of Mediterranean countries. The aim of this study is to investigate the relationships between tourism revenues, employment rates and economic growth of two selected Mediterranean countries in the 1997-2020 period. In this study, panel data analysis method was used. In the analysis of panel data regression models, it was seen that the random effects model was appropriate. The model was estimated with Driscoll/Kraay resistant standard estimators developed against deviations from the assumptions. The results show that there is a positive relationship between tourism revenues, employment rates and economic growth in the two Mediterranean countries. Accordingly, an 1% increase in tourism revenues increases economic growth by 0.54%, while a 1% increase in employment rates increases economic growth approximately 1.5 times.

THE ENVIRONMENTAL EFFECTS OF TOURISM: ANALYZING THE IMPACT OF TOURISM, GLOBAL TRADE, CONSUMPTION EXPENDITURE, ELECTRICITY, AND POPULATION ON ENVIRONMENT IN LEADING GLOBAL TOURIST DESTINATIONS

The study analysed the impact of tourism, trade, consumption expenditure, electricity usage, and population on carbon dioxide emissions (CO2) in leading tourist destinations. The study uses a panel dataset of 32 countries from different continents between 2001 and 2020 and applies the generalized method of moments (GMM) and Quantile Regression approaches. The results suggest that tourism (arrivals and revenues) can reduce environmental degradation, and that CO2 emissions increase due to factors such as GDP per capita, electricity consumption, and population growth. Trade openness can reduce CO2 emissions, and controlling for final consumption also indicates a decrease in CO2 emissions. The study suggests that sustainable tourism practices, responsible consumption, and larger international integration may play a role in mitigating CO2 emissions. Leading tourist destinations should develop sustainable urban areas to accommodate population growth, and embrace eco-friendly technologies, infrastructure, and consumption patterns to promote sustainable economic growth while reducing CO2 emissions.