Private management of African protected areas improves wildlife and tourism outcomes but with security concerns in conflict regions.

Protected areas can conserve wildlife and benefit people when managed effectively. African governments increasingly delegate the management of protected areas to private, nongovernmental organizations, hoping that private organizations' significant resources and technical capacities actualize protected areas' potential. Does private sector management improve outcomes compared to a counterfactual of government management? We leverage the transfer of management authority from governments to African Parks (AP)-the largest private manager of protected areas in Africa-to show that private management significantly improves wildlife outcomes via reduced elephant poaching and increased bird abundances. Our results also suggest that AP's management augments tourism, while the effect on rural wealth is inconclusive. However, AP's management increases the risk of armed groups targeting civilians, which could be an unintended outcome of AP's improved monitoring and enforcement systems. These findings reveal an intricate interplay between conservation, economic development, and security under privately managed protected areas in Africa.

Evaluation model of urban tourism competitiveness in the context of sustainable development.

In the contemporary context marked by globalization and the growing prominence of sustainable development, assessing urban tourism competitiveness has emerged as a crucial research domain. This paper aims to develop a comprehensive model for evaluating city tourism competitiveness, grounded in the principles of sustainable development. The model incorporates factors such as city tourism resources, environmental considerations, economic aspects, and societal factors. This holistic approach seeks to offer valuable insights for the city tourism industry. The study conducts a thorough analysis of current research both domestically and internationally, highlighting gaps and articulating the objectives and significance of the research. Employing a machine learning-based empowerment method, the paper determines the significance of evaluation indices and utilizes the Topsis method for assessing urban tourism competitiveness. Distinguishing itself from traditional evaluation methods, this model integrates the principles of sustainable development throughout the evaluation process, with environmental, social, and economic sustainability serving as pivotal evaluation indicators. Empirical analysis involves the evaluation of tourism competitiveness for select cities, facilitating inter-city comparisons. Results from empirical studies demonstrate the model's effectiveness in evaluating urban tourism competitiveness, providing targeted developmental recommendations for urban tourism.

Unique attributes of official endorsers in destination marketing.

Along with the digital transformation of the administrative environment and the end of the COVID-19 pandemic, official endorsers have nurtured a new channel for tourism destination marketing, which is of great significance to local economic recovery. However, less attention has been paid to the different effects of endorsement between ordinary endorsers and official endorsers, mainly due to their contrasting social statuses. To bridge the research gap, the source credibility model and social identity theory are integrated to construct the distinctive attributes of officials, as well as structural equation model is utilized to explore the underlying mechanism of official endorsement. Findings indicate that trustworthiness, the sense of authority, expertise, and attractiveness have direct positive effects on official identification, while also indirectly influencing tourists' attitudes toward the destination through official identification. These findings provide theoretical and managerial implications for the local government managers involved in tourism destination marketing.

The macroeconomic impact of a dengue outbreak: Case studies from Thailand and Brazil.

BACKGROUND: Dengue is spreading in (sub)tropical areas, and half of the global population is at risk. The macroeconomic impact of dengue extends beyond healthcare costs. This study evaluated the impact of dengue on gross domestic product (GDP) based on approaches tailored to two dengue-endemic countries, Thailand and Brazil, from the tourism and workforce perspectives, respectively. FINDINGS: Because the tourism industry is a critical economic sector for Thailand, lost tourism revenues were estimated to analyze the impact of a dengue outbreak. An input-output model estimated that the direct effects (on international tourism) and indirect effects (on suppliers) of dengue on tourism reduced overall GDP by 1.43 billion US dollars (USD) (0.26%) in the outbreak year 2019. The induced effect (reduced employee income/spending) reduced Thailand's GDP by 375 million USD (0.07%). Overall, lost tourism revenues reduced Thailand's GDP by an estimated 1.81 billion USD (0.33%) in 2019 (3% of annual tourism revenue). An inoperability input-output model was used to analyze the effect of workforce absenteeism on GDP due to a dengue outbreak in Brazil. This model calculates the number of lost workdays associated with ambulatory and hospitalized dengue. Input was collected from state-level epidemiological and economic data for 2019. An estimated 22.4 million workdays were lost in the employed population; 39% associated with the informal sector. Lost workdays due to dengue reduced Brazil's GDP by 876 million USD (0.05%). CONCLUSIONS: The economic costs of dengue outbreaks far surpass the direct medical costs. Dengue reduces overall GDP and inflicts national economic losses. With a high proportion of the population lacking formal employment in both countries and low income being a barrier to seeking care, dengue also poses an equity challenge. A combination of public health measures, like vector control and vaccination, against dengue is recommended to mitigate the broader economic impact of dengue.

Does the selection of high-quality scenic spots promote the growth of tourism economy? evidence from China's 5A-rated tourist attractions.

To stimulate the regional tourism economy, local governments often seek to increase the number of 5A-rated tourist attractions. However, there have been few analyses examining the economic benefits and influence mechanisms of 5A-rated attraction selection. Using the quality signaling theory and data from 282 prefecture-level cities spanning 2002 to 2019, this study examines the impact of 5A-rated attraction selection on the local tourism economy with the difference-in-differences method. This study's results demonstrate that the selection of 5A-rated attractions significantly contributes to the growth of the local tourism economy. The robustness test results confirm the validity of this conclusion. A mechanism analysis reveals that 5A-rated attractions positively impact the tourism economy via investments in infrastructure, popularization of informatization, and increased external openness. Furthermore, the study suggests that the effect of 5A-rated attractions is more pronounced in economically underdeveloped regions and low-level cities. The results of this study contribute to the sustainable development of China's tourism economy and may provide guidance for the establishment of tourism evaluation systems in other international locations in order to foster economic growth.

How far can air pollution affect tourism in China? Evidence from panel unconditional quantile regressions.

Previous studies provide empirical evidence for the connection between air pollution and tourism. However, many of them take the nexus as a linear one. It remains unexplored whether any thresholds are required for the nexus to materialize. This study systematically investigates whether PM2.5 concentrations-an essential indicator of air pollution-affect tourism in China at various tourism development levels. We analyze 284 Chinese cities from 2008 to 2018 using the Unconditional Quantile Regression method. Our statistical results reveal that air pollution positively influences tourism (regarding tourist visits and tourism revenue) in areas with low tourism development levels. However, a complex correlation between air pollution and tourism emerges when tourism development has reached a certain level. The correlation is initially negative, then positive, and finally disappears. But, the overall correlation remains negative. The effects of the interaction between air pollution and tourism resources on tourism are inverted U-shaped, implying that tourism resources can mitigate the negative effects of air pollution on tourism only when tourism development has reached a certain level. Based on the above findings, the associated policy implications are discussed.

Intervention for work-family conflict and work deviance behavior among female workers in Tourism, Museum, Art Gallery Exhibition Centers: Implications for sustainable Tourism development intervention study.

BACKGROUND: This study was motivated due to psychological exhaustion, demands, and conflict degenerating from the work environment and family responsibilities facing career female workers. These roles and expectations have posed serious dilemmas to female populations in workplaces. Leaving them untreated is risky and could lead to severe psychological disturbances. Based on these, this study investigated the effect of the occupation health model of Rational Emotive Behaviour Therapy on work-family conflict and work-deviant behavior among female workers in Tourism, Museum, Art Gallery and Exhibition Centers in Enugu State. METHODS: A randomized control design was used. A total of 119 female workers were randomized into intervention and control groups, measured at 3 points (pretest, posttest, and follow-up test), and the data collected were analyzed using repeated measure statistics. RESULTS: The finding showed that the intervention is significantly effective in reducing the work-family conflict and work deviance behavior among female workers in Tourism, Museum, and Art Gallery Exhibition Centers. Nonetheless, the findings show that the gender and time interaction effects did not significantly affect the work-family conflict and work deviance behavior scores of the workers. The follow-up stage improved the intervention's favorable impact on the reduction of work-family conflict and work-deviant behaviors. CONCLUSION: This suggest that occupation health model of Rational Emotive Behaviour Therapy has significant impact in reducing and changing female workers' perceptions of work-family conflict and work deviant behaviors.

Measuring intangible cultural heritage image: A scale development.

Although an increasing number of studies have examined issues relating to the preservation and development of intangible cultural heritage (ICH), there has been limited research on how tourists perceive ICH. Moreover, UNESCO asserts that the concept of "authenticity" is not applicable to ICH, and so far, no valid instrument for measuring tourists' subjective perceptions of ICH has been developed, even though their perceptions play a very important role in the preservation and development of ICH. Therefore, this paper aims to develop a measurement scale for ICH image, using both qualitative and quantitative research methods. Participant observation, semi-structured in-depth interviews, secondary data collection, and a literature review were conducted to generate the initial scale items, and then the main surveys were conducted to collect data for the model tests. Four dimensions were extracted by exploratory factor analysis: transmission, localization, vitality, and association. The reliability and validity of the measurement model were demonstrated through confirmatory factor analysis. We further determined that the transmission, vitality, and association of ICH image have a positive impact on tourists' revisit intention. The paper highlights the crucial role of ICH image in sustainable tourism development. The theoretical and managerial implications of the study are discussed, followed by suggestions for future research.

Biomonitoring of human activities recovery following lockdown in a highly touristic Mediterranean Island using Mytilus galloprovincialis.

Coastal waters face significant anthropogenic stress, particularly from tourism, exacerbating pollution, especially in areas like touristic islands. Ischia, the largest island in the Gulf of Naples and part of the Regno di Nettuno Marine Protected Area, suffers from pollution due to tourism and maritime traffic. During the initial SARS-CoV-2 lockdown from March to June 2020, Ischia was isolated, providing a unique opportunity to study pollutant release and its impact on coastal ecosystems. Adult Mytilus galloprovincialis mussels were transplanted to three sites on the island for active biomonitoring. Accumulation of chemicals in tissues and biomarkers related to metabolism, detoxification, and oxidative stress were measured. Results indicated that pollutants from daily activities entered the sea, affecting filter feeders. Translocated organisms showed modulated metabolic functions and biochemical changes, highlighting coastal vulnerability and calling for conservation efforts.

Green sustainability in the hotel sector: The role of CSR, intrinsic green motivation, and personal environmental norms.

In the context of the United Nations Sustainable Development Goals (UN-SDGs), this study accentuates the role of the tourism and hospitality sector in promoting sustainability. The primary purpose is to unravel the relationship between corporate social responsibility (CSR) and energy-specific sustainable behavior of employees (ESBE), with particular emphasis on the mediating roles of green intrinsic motivation and personal environmental norms. Utilizing a three-wave data collection approach, we secured 325 valid responses from sector employees at various levels (manager-non managers) and applied Structural Equation Modeling through the SMART-PLS tool to assess the hypothesized relationships. The findings highlight a pronounced interconnection between CSR, ESBE, and the designated mediating variables. These results not only augment the academic literature by illustrating the psychological underpinnings bridging CSR to ESBE, but also equip the tourism and hospitality industry with actionable insights. Through informed CSR initiatives aligned with employee values, the sector can galvanize sustainable behaviors and create business models that resonate with the aspirations of the UN-SDGs, pointing the way to a more sustainable industry.

Not only in the crowd: Benthic litter characterization in a low population density area still reveals widespread pollution and local malpractices.

Various anthropogenic activities affect marine coastal habitats, leading to heavy litter pollution. However, whilst high litter concentrations are nowadays common in the proximity of metropolises, few studies investigated the magnitude of this phenomenon around coastal villages and small towns. We hereby characterized the benthic litter occurring in the trawlable grounds of the Gulf of Policastro (Tyrrhenian Sea, central-western Mediterranean), a low population density area that becomes a popular tourist destination during summer. We furthermore tested differences between two depths (∼100-200 and ∼500-600 m) and the impact of tourism on the shallower waters. The area was characterized by a litter abundance of 651.12 ± 130.61 item/km2, with plastic being almost totalitarian (93%). The shallower waters hosted two-thirds of the litter found. Almost all (∼95%) the litter items had a land-based origin, while the sea-based litter was mostly found at higher depths. About 14% of the litter was found to be fouled, with the development of litter-associated communities that somehow mimic the natural ones living on hard substrates. The higher litter presence noticed during the touristic peak (July-August) suggests that tourism is an important source of local litter, although it contributed to the local accumulation in a synergic way with other factors. The majority of the litter items presumably originated from the nearby coastline, while the deeper waters were or are used as a dumping site by the local trawling fleet. The discovery of such a critical waste accumulation and management in a somehow remote area contributes to widen the perspectives on the presence of benthic litter mostly in territories characterized by wide anthropization. Moreover, it confirms that appropriate local policies and communication plans are urged even at a regional level to stimulate citizen consciousness and mitigate the ever growing litter pollution.

Tourism cooperation in the Belt and Road Initiative from economic and spatial insights.

This study examines the potential benefits of cooperation among Belt and Road Initiative (BRI) countries in achieving common goals within the international tourism cooperation network. Despite its significance, limited research has been conducted on this topic in terms of economic and spatial insights. To address this gap, we utilized the gravity model, social network, and quadratic regression. The revealed findings suggest that while the intermediary function among BRI countries is declining, the tourism cooperation network is gradually strengthening. Furthermore, reducing the gap between the governance and consumption levels of BRI countries can improve the network. The study offers new insights into the BRI tourism cooperation network, which could be critical for the future growth of regional tourism.

Exploring the dual impact: Dissecting the impact of tourism agglomeration on low-carbon agriculture.

Despite extensive research on the relationship between tourism and agriculture, the specific impact of tourism on agriculture's low-carbon transition has not been thoroughly investigated. This study analyzes the effects of tourism agglomeration on agricultural carbon intensity across 30 Chinese provinces from 2001 to 2020. It is framed within the context of rural digitalization, with a particular emphasis on the integration of agro-tourism and the total factor productivity of agriculture. Utilizing spatial econometric models, we find that tourism agglomeration hinders the low-carbon transition in agriculture by influencing carbon intensity both directly and indirectly. At the national level, the impact of tourism agglomeration follows an inverted-U curve with respect to agro-tourism integration and carbon intensity. At the regional level, the effects vary, with weaker indirect influences in major grain-producing areas. Furthermore, rural digitalization appears to lessen the adverse impacts of tourism on carbon intensity. This study also identifies significant spatial spillover effects from tourism agglomeration. The findings suggest that provinces with high tourist influx should enhance investments in climate-smart agricultural practices and technologies to counteract these negative impacts. Moreover, integrated governance of tourism and agriculture is essential for achieving carbon neutrality in both sectors.

Netographic narratives of user-generated travelogues on tourist destination image of Thailand.

The image of a tourist destination is considered a vital aspect of international travel experiences, yet research in this area remains limited. Adopting a combination of netography and qualitative research methodology, this study aims to contribute to the scientific knowledge of destination image development in Thailand by analysing online travelogues to evaluate how Chinese tourists interpret the idea of destination image. To achieve this goal, 146,641 words of Chinese internet comments containing the keyword "Thailand" from four major media sources and Chinese bloggers were gathered and analysed using netography methodology. The findings showed that there was a rise in public interest, in public forums, in the destination image of Thailand among Chinese outbound tourists. The study's results may provide important fundamental theoretical insights and inspire further investigation into the issue of destination image construction.

Is the digital economy empowering high-quality tourism development? A theoretical and empirical research from China.

How digital economy (DE) empowers high-quality development of tourism (HQDT) has become a common concern among scholars. Given this, this study clarifies the theoretical connotation of DE enabling HQDT,and finds that: Micro, DE promotes efficiency improvements in tourism enterprises, with its economies of scale and Matthew effect reducing average costs, its economies of scope meeting diversified demand, and its long-tail effect improving supply-demand matching mechanism. Meso, DE can transform and upgrade tourism industry structure through industrial digitization and digital industrialization, and also form a new tourist industry form and value chain through cross-border integration. Macro, DE can stimulate innovation and flexibility of market players, increase new factor inputs in tourism, improve factor allocation efficiency, and advance macro regulation of the tourism market. Accordingly, the study conducts an empirical test based on panel data for 31 provinces in mainland China during 2011-2020. Results show that: ① DE positively influences HQDT, and the sub-dimensions all positively influence HQDT. ② DE has a heterogeneous impact on HQDT and shows spatial spillover effects. Finally, the study concludes with effective paths for DE promoting HQDT: "Promote digital infrastructure construction, accelerate tourism digital transformation, strengthen integration and innovation development, and overcome the challenges of tourism enterprises".

Differences in tourism economic development and its influencing factors among three major city clusters along the middle reaches of the Yangtze River.

An in-depth study of the mechanisms governing the generation, evolution, and regulation of differences in tourism economics holds significant value for the rational utilization of tourism resources and the promotion of synergistic tourism economic development. This study utilizes mathematical statistical analysis and GIS spatial analysis to construct a single indicator measure and a comprehensive indicator measure to analyze tourism-related data in the research area from 2004 to 2019. The main factors influencing the spatial and temporal differences in the tourism economy are analyzed using two methods, namely, multiple linear regression and geodetector. The temporal evolution, overall differences and differences within each city group fluctuate downwards, while the differences between groups fluctuate upwards. Domestic tourism economic differences contribute to over 90% of the overall tourism economic differences. Spatial divergence, the proportion of the tourism economy accounted for by spatial differences is obvious, the comprehensive level of the tourism economy can be divided into five levels. The dominant factors in the formation of the pattern of spatial and temporal differences in the tourism economy are the conditions of tourism resources based on class-A tourist attractions and the level of tourism industry and services based on star hotels and travel agencies. This study addresses the regional imbalance of tourism economic development in city clusters and with the intent of promoting balanced and high-quality development of regional tourism economies.

Analyzing the tourism efficiency and its influencing factors of China's coastal provinces.

Tourism efficiency has become an important role in promoting tourism competitiveness and driving sustainable development. It is particularly important to identify and agnalyze the factors and mechanisms that affect efficiency. This paper firstly evaluates the tourism efficiency of 11 coastal provinces regions in China from 2010 to 2020 by using the DEA-BBC model that includes undesirable outputs. After that, it investigates the internal driving mechanism of the efficiency change through the Malmquist index and its decomposition. Finally, it analyzes the external influencing elements of tourist efficiency by the Tobit model. The results show that: (1) Although the average value of the tourism efficiency was changed from 0.727 to 0.707, it does not achieve the target. Its trend shows fluctuating from 2010-2020, which indicates that the tourism efficiency of most provincial regions is not optimal. The main factor that restricts tourism efficiency is scale efficiency. (2) By analyzing the dynamic trend, it is found that the average increase of technical efficiency is 14.0%, the average increase of technical change is 9.5%, and the average increase of MI index is 25.4%. It indicates that the overall tourism efficiency of 11 coastal provinces region in China is on the rise. (3) The spatial difference of tourism efficiency is significant, but there is no obvious spatial correlation. (4) The influencing factors of tourism efficiency are consumer demand, industrial structure, labor force and urbanization.

Spatiotemporal differentiation and driving mechanisms of high-level Grade A tourist attractions in the Yangtze River Delta City Cluster.

Herein, the spatial evolution characteristics of high-level Grade A tourist attractions in the Yangtze River Delta (YRD) urban agglomeration, from 2001 to 2021, are studied by comprehensively applying the nearest neighbor index, kernel density analysis, standard deviation ellipse, and spatial autocorrelation. High-level Grade A tourist attractions are investigated using the random forest model as the driving mechanism of the spatial pattern. Results show that 1) the spatial distribution of high-level Class A tourist attractions in the YRD city cluster has grown to be an agglomeration, and the high-density areas have evolved from "point-like dispersion to regiment-like combination," gradually forming a B-shaped core density structure. 2) The spatial distribution comprises an overall "northwest-southeast" direction, a small counterclockwise rotation, the distribution of the center of gravity to the southwest migration, and the center of gravity from the territory of Suzhou City to the territory of Huzhou City. 3) The high-level Class A tourist attractions in the YRD city cluster as a whole show a strong positive spatial correlation, and the significantly clustered areas include three types: high-high (H-H), low-low (L-L), and low-high (L-H). 4) The spatial distribution of high, A-level tourist attractions in the YRD city cluster results from the combined action of the natural environment, resource endowment, socioeconomy, and policy background. Each element has a nonlinear and complex influence on the distribution of scenic spots.

A time-varying analysis between economic uncertainty and tourism development in Singapore.

Tourism development (TO) is seen as a viable solution to address economic policy uncertainty (EPU) risks. However, previous studies have largely ignored the relationship between short, medium, and long term by decomposing TO and EPU index at different time-frequency scales, especially in Singapore. In this study, the Wavelet tools analysis and a rolling window algorithm are employed to re-visit the causal relationship between EPU, industrial production index (IPI), government revenue (GR), and tourism development (TO) in Singapore from January 2003 to February 2022. The findings revealed the heterogeneous effects of EPU on TO at different time horizons in terms of importance and magnitude over time. A rise in EPU results in a decline in TO at the low frequencies, indicating that EPU has a detrimental effect on TO over the short term. Conversely, in the long term, an increase in TO results in a decrease in EPU. Furthermore, the outcome also indicated that there is a uni-directional causality running from TO to EPU, GR and IPI. Expressly, we confirm that the negative co-movement is more pronounced in the aftermath of the COVID-19 crisis, particularly for EPU, and GR at low-medium frequencies throughout the research period. The findings provide tourism policymakers with insight to develop strategic plans for tourism development that consider the effects of economic policy uncertainty. By understanding how uncertainty impacts tourism, governments can tailor development strategies to mitigate risks and capitalize on opportunities.

Segmentation by motivations in religious tourism: A study of the Christ of Miracles Pilgrimage, Peru.

The present study, focused on pilgrimages as part of religious tourism, aimed to achieve the following objectives: Identify the motivations of the demand for religious tourism focused on pilgrimages; analyze the segmentation of the demand; identify the relationship between demand segments with satisfaction and loyalty; and establish the sociodemographic aspects that characterize demand segments. The study was conducted during the Pilgrimage of the Christ of Miracles in Lima, Peru. The sample was taken on-site from 384 tourists. The statistical techniques used were factor analysis and the k-means clustering method. The results reveal five motivational dimensions: Religious Experience, Belief Experience, Escape, Touristic Experience, and Shopping. Three attendee segments were also identified: Believers, related to belief experience; Religious, related to religious experience; and Passive, tourists with low motivations. The Religious segment had the highest satisfaction and loyalty levels among these groups. Sociodemographic differences were also found in the demand segments. The findings will contribute to management guidelines for destination administrators with religious events and provide insights into academic literature.