Project description:The aim of this study is to examine the effect that visitor satisfaction with traditional restaurants has on perceptions of the local gastronomy, the overall image of a city and loyalty to that destination. Fieldwork has been carried out in Córdoba, a city in southern Spain famous for being a UNESCO World Heritage city and for its traditional gastronomy. The methodology used is based on structural equation modeling (PLS-SEM). This paper makes a novel contribution in that no previous studies to date have explored satisfaction with traditional restaurants, with respect to the food, the service and the atmosphere. To achieve the proposed objective, a structured questionnaire has been used to find out the opinions of diners in renowned restaurants that base their cuisine on traditional dishes made with quality local ingredients. The results obtained confirm that a satisfactory experience with the food of a traditional restaurant has a positive effect on the image of the destination and the gastronomy of the place, as well as on visitors' intentions to recommend and repeat the visit to said destination. Based on the analysis carried out, effective strategies are suggested to help manage these types of restaurants. The study provides theoretical and practical implications from a gastronomic perspective, which can enable tourism managers to employ new strategies to retain tourists visiting a city, based on increasing their post-experience satisfaction with restaurants featuring local cuisine.
Project description:The tourist experience is a core indicator of destination management for the comprehensive evaluation of destination value. Tourist experience and tourist inspiration are important concepts in the stream of research on destination marketing and management. However, these relationships remained under-explored in the extant literature. This study examined the impact of tourist experience on tourist inspiration under the moderating impact of destination familiarity. To achieve the objective of this study, data were collected online from 622 Chinese tourists. We employed partial least squares structural equation modeling (PLS-SEM) to statistically analyze the gathered data. Findings show that four types of tourist experiences, namely education, esthetics, entertainment, and escapism, significantly and positively influenced the inspired-by state of tourist inspiration, which further influenced the inspired-to-state of tourist inspiration. Destination familiarity exerted a significantly negative moderating impact on the relationship between education experience and inspired-by state of tourist inspiration. Sensitivity analysis presents that education experience was the strongest predictor of the inspired-by state followed by aesthetics, escapism, and entertainment facets of the tourist experience. Findings contribute to the theory and practice of tourism management with a robust interpretation of tourist experience, tourist inspiration, and destination familiarity to solidify the effective management of tourist destinations. Limitations and future research directions are noted.
Project description:BackgroundThe factors influencing tourist loyalty are widely highlighted in the literature. However, we find that the relationship between some influencing factors and loyalty is still inconsistent, and we don't yet know the strength and magnitude of the relationships. To address this issue, this study examined a meta-analysis of the five factors (satisfaction, motivation, perceived value, perceived quality, and experience quality) influencing tourist loyalty and its sub-dimensions.MethodsThe samples included articles from major academic databases, including Web of Science, Wiley Online, EBSCO, SAGE, Taylor and Francis, and Elsevier. Studies written in Chinese were retrieved from CNKI.com. We used the following keywords for retrieval: loyalty, behavioral intention, recommendation intention, word-of-mouth, revisit intentions, intention to revisit, willingness to recommend, and similar related terms. Conceptual and empirical studies published between January 1989 and September 2021 were extracted. To test whether there was publication bias, we used Fail-Safe-Number (FSN) to verify the stability of the results. The homogeneity test of the selected statistical model was based on the Q test and I2. The results were obtained by combining multiple single effect values into the combined effect value.ResultsWe developed 21 hypotheses and proposed a theoretical framework and analyzed 114650 accumulated sample sizes from 242 independent empirical studies. Among the 21 hypotheses proposed in this paper, the remaining 20 hypotheses have been proved except for hypothesis H6.ConclusionsThe findings showed that the five factors had varying degrees of positive and significant relationships with tourist loyalty and its sub-dimensions. In the descending order of effects, the five factors are degree of satisfaction, quality of experience, perceived value, perceived quality and motivation. We discussed the significance of the meta-analysis, theoretical and practical implications for destination marketing.
Project description:User-generated content (UGC) is an important data source for tourism GIScience research. However, no effective approach exists for identifying hidden spatiotemporal patterns within multi-scale unstructured UGC. Therefore, we developed an algorithm to measure the tourist destination popularity (TDP) based on a multi-spatiotemporal text granular computing model, called TDPMTGC. To accurately granulate the spatial and temporal information of tourism text, tourism text data granules are used to represent landscape objects. These granules are unified objects that possess multiple attributes, such as spatial and temporal dimensions. The multi-spatiotemporal scales are characterized by the multi-hierarchical structure of granular computing, and transformations of granular layers and data granule size are achieved by scale selection in the spatial and temporal dimensions. Therefore, all scales between the spatial and temporal dimension are related, which allows for the comparability of the data granules of all spatial-spatial, temporal-temporal and spatial-temporal layers. This approach achieves a quantitative description and comparison of the popularity value of granules between adjacent scales and cross-scales. Therefore, the TDP with multi-spatiotemporal scales can be deduced and calculated in a systematic framework. We first introduce the conceptual framework of TDPMTGC to construct a quantitative measurement model of TDP at multi-spatiotemporal scales. Then, we present a dataset construction approach to support multi-spatiotemporal scale granular reorganization. Finally, TDPMTGC is derived to describe both the TDP at a single spatial or temporal scale and the patterns and processes of the TDP at multi-spatiotemporal scales. A case study from Jiuzhaigou shows that the TDP derived using TDPMTGC is consistent with the conclusions of existing studies. More importantly, TDPMTGC provides additional detailed characteristics, such as the contributions of different scenic spots in a tourist route or scenic area, the monthly anomalies and daily contributions of TDP in a specific year, the distinct weakening of tourist route scale in tourist cognition, and the daily variations of TDP during in-season and off-season times. This is the first time that a granular computing model has been introduced to tourism GIScience that provides a feasible scheme for reorganizing large-scale unstructured text and constructing public spatiotemporal UGC tourism datasets. TDPMTGC constitutes a new approach for exploring tourist behaviors and the driving mechanisms of tourism patterns and processes.
Project description:Loyalty is important in the tourism sector since tourists are the key to returning to a destination or recommending it, which is a determining factor in the management of tourist sites. The tourism of Mosques, is a contextualized tourism within religious and cultural tourism. This research aims to analyze the loyalty of tourists of Islamic origin in the Cathedral Mosque of Cordoba. Unlike previous studies, this research adopts a comprehensive approach by considering cultural factors in the analysis of loyalty of Islamic tourists in mosque tourism. The methodology used in this study was a structural equation model with a partial least squares (PLS) analysis. The sample is made up of 262 tourists of Islamic origin at Cordoba Cathedral Mosque. This model does not correspond to factors identified by the previous literature, which adopts an religious perspective of Islamic tourists in mosque tourism. The methodology used in this study was a structural equation model with a partial least squares (PLS) analysis. The sample is made up of 262 tourists of Islamic origin in Cordoba Cathedral Mosque. This model does not correspond to factors identified by the previous literature, which adopts an religious perspective.
Project description:This study addresses the critical need for regional tourism integration and sustainable development by identifying cooperation opportunities among tourist attractions within a region. We introduce a novel methodology that combines association rule mining with complex network analysis and utilizes search index data as a dynamic and contemporary data source to reveal cooperative patterns among tourist attractions. Our approach delineates a potential cooperative network within the destination ecosystem, categorizing tourist attractions into three distinct communities: core, intermediary, and periphery. These communities correspond to high, medium, and low tourist demand scales, respectively. The study uncovers a self-organizing network structure, driven by congruences in internal tourist demand and variances in external tourist experiences. Functionally, there is a directed continuum of cooperation prospects among these communities. The core community, characterized by significant tourist demand, acts as a catalyst, boosting demand for other attractions. The intermediary community, central in the network, links the core and periphery, enhancing cooperative ties and influence. Peripheral attractions, representing latent growth areas within the destination matrix, benefit from associations with the core and intermediary communities. Our findings provide vital insights into the dynamics, systemic characteristics, and fundamental mechanisms of potential cooperation networks among tourist attractions. They enable tourism management organizations to employ our analytical framework for real-time monitoring of tourism demand and flow trends. Additionally, the study guides the macro-control of tourism flows based on the tourism network, thereby improving the tourist experience and promoting coordinated development among inter-regional tourist attractions.
Project description:The consumption of raw fish has increased considerably in the West, since it is said to be potentially healthier than processed fish (for containing omega 3 and 6, essential amino acids and vitamins). However this potential benefit, as well as the taste, value and even the risk of extinction are not the same for all species of fish, constituting grounds for fraud. Using the principles of the DNA barcode we revealed mislabelling of fish in Japanese restaurants and fishmarkets in Florianópolis, a popular tourist capital in Brazil. We sequenced the COI gene of 65 samples from fisheries and 80 from restaurants and diagnosed 30% of mislabeled samples in fisheries and 26% in restaurants. We discussed that frauds may have occurred for different reasons: to circumvent surveillance on threatened species; to sell fish with sizes smaller than allowed or abundant species as being a much rarer species (law of supply); to induce product consumption using species with better taste. It should be noted that some substitutions are derived from incorrect identification and are not a fraud per se; they are due to confusion of popular names or misunderstanding by the sellers. Therefore, we suggest the implementation of a systematic regulatory program conducted by governmental agencies to reduce mislabelling in order to avoid further damage to the community (in health and financial issues) and fish stocks.
Project description:Advanced mobile functions and empowered smartphones have provided tourists with various location-based service apps that reshaped the business model of the tourism sector. Despite their importance to tourists, l-apps still have limitations, such as ignorance of tourist preferences and the mismatch between app introduction and tourist experience, therefore affecting tourist loyalty to destinations. Understanding tourist-oriented factors thus becomes critical for l-app designers and service providers. This study integrates the technology-acceptance model (TAM) into a unique context to examine the roles of digital literacy, perceived ease of use, perceived autonomy, virtual-content congruence, and tourist engagement on tourist loyalty. Our empirical test of a structural equation model based on a randomly recruited 319 customers found that tourists' digital literacy influences their engagement and perceived ease of use, which mediates the relationship between digital literacy and engagement; tourists' perceived autonomy influences their engagement. Moreover, we found the moderating role of information-experience congruency between digital literacy, perceived ease of use, and perceived autonomy and tourist engagement, thus contributing to the boundary conditions of the TAM model. Finally, tourist engagement contributes to tourist loyalty. The study contributes to the integration of the technology acceptance model with a tourist orientation. The findings also offer meaningful, practical implications and recommendations on l-app design to stakeholders of tourist destinations.
Project description:This paper aims to contribute to the knowledge on how the Smart Tourism Destination (STD) might enhance the Tourist Shopping Journey (TSJ) through offering information sources that meet visitors' needs and preferences. The CAN (Cognitive-Affective-Normative) model was employed to explore the antecedents of using information sources for purchases made in destinations. The importance of the cognitive variables performance and effort expectancy in the purchasing process are highlighted: tourists are pragmatic when consulting information sources in destinations. This study contributes to the knowledge of the role of information sources in TSJ behaviour, and can help managers in the development of STD strategies and services. It also opens new research lines by considering the TSJ as a hitherto unexamined holistic process.
Project description:An upsurge of fever cases of unknown origin, but resembling dengue and leptospirosis was reported in Havelock, Andaman & Nicobar Islands, an important tourism spot, during May 2014. Investigations were carried out to determine the aetiology, and to describe the epidemiology of the outbreak. The data on fever cases attending Primary Health Centre (PHC), Havelock showed that the average number of cases reporting per week over the last 2 years was 46·1 (95% confidence interval 19·4-72·9). A total of 27 (43·5%) patients out of the 62 suspected cases were diagnosed as having DENV infection based on a positive enzyme immunoassay or reverse transcriptase-polymerase chain reaction. The overall attack rate was 9·4 cases/1000 population and it ranged between 2·8 and 18·8/1000 in different villages. The nucleotide sequencing showed that the virus responsible was DENV-3. DENV-3 was first detected in the Andaman & Nicobar Islands in 2013 among wharf workers in Port Blair and within a year it has spread to Havelock Island which is separated from South Andaman by 36 nautical miles.