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This paper aims to analyse the changes in the extent of the green space in the city of Srinagar, a unique urban Himalayan destination, and examine whether the difference in the green space has a significant effect on the destination business performance measured in terms of loss of ecological attractiveness.

This study was carried out in two phases in the study area. In phase I, the changes in the extent of the green space area were analysed using Landsat TM and Sentinel Images for classification. The study has used the period from 2001 to 2018 to understand changes in the green space. The Post-Classification Comparison technique was used to investigate the variation in the green space zones in the city of Srinagar. In phase II, the paper evaluated the impact of change in the green space on the destination business performance. The data was collected from the tour operation companies through a questionnaire survey, and the impact path was examined using structural equation modelling.

Results reveal that the green space in the city of Srinagar has decreased over the past 18 years, and the decreasing green space has a significant effect on the destination business performance.

Identifying the impact of decreasing green space on the destination business performance of the study area under investigation is essential for tourism development both in terms of new product development and resource preservation. Developing a measurement scale showing the impact of decreasing green space on destination business performance could offer destination managers a means of identifying the essence of the green space in the destination regions. These findings add to the growing literature on the attributes of tourism destinations, providing scholars with new insights into the role of green space in destination performance. The current study offers evidence of the impact of decreasing green space on the destination's performance. This provides a new perspective for future studies on visitor satisfaction as a potential mediator of the relationship between reducing greenspace and destination business performance. The main limitation of this study is that the researchers have only analysed the impact of decreasing green space on the destination business performance in terms of its ecological competitiveness. Other destinations business performance verticals, such as hotels, restaurants and grocery stores were not considered by this study and can be taken up for future investigation.

This study provides empirical insights that can have significant implications for researchers, policymakers, destination management organizations, academia and practitioners and further enrich the existing literature by establishing an empirical argument in the context of urban destinations positioned with a fragile Himalayan ecosystem.

This study aims to assist the urban administrators in improving the green space ecosystem in the region, which can help attain the sustainability of the city environment and assist in economic regeneration in urban settings.

This study aims to examine the relationships between tourism destination competitiveness (TDC) determinants and tourism performance. This study specifically assessed the soundness of the TDC attributes and evaluated their ability in explaining tourism performance.

The Dwyer and Kim’s (2003) destination competitiveness integrated model (IM) was used. Secondary data of 115 nations available from the Travel and Tourism Competitiveness Index (TTCI) and other international reports were also used. The hypothesised relationships were tested via partial least square-structural equation modelling (PLS-SEM).

This study confirms that the core resources, complementary condition, globalisation and tourism price significantly explain tourism performance. Results have shown differences in the competitiveness level and actual performance among nations, highlighting specific limitations of the current TDC model and TTCI report reliability.

Future study could segment the sample base on destinations characteristic and then analyse it based on smaller sub-samples of similar destinations. Moreover, drivers of destination performance in developed and less develop destinations are quite diverse.

The incorrect competitiveness ranking evaluation will affect inward investment decisions. This study framework enables policymakers to arrive at more informed decisions than merely relying on the original competitiveness rankings.

The widespread acknowledgment of the importance of competitiveness for a tourism destination's success suggests that there is a crucial need for sound benchmarking of countries’ competitive capabilities. The proposed competitiveness determinants aid the policymakers in identifying the best competitiveness and tourism performance predictors, as well as how to identify crucial factors affecting the rankings.

The purpose of this paper is to address a new method to evaluate the competitiveness of tourist destinations based on competitive performance from the consumers’ perspective. The main objective is to assess the sources of relative strength and weakness perceived in a destination, and to evaluate its performance vis-à-vis to the main competitors identified by tourists through measurement indexes.

The strengths and weaknesses of the focal destination were identified by plotting 12 tourism-specific variables (attractors) and 12 business-related variables in importance-performance matrix (IPA) grids. The set of destinations identified as “the main competitors” were built according to the frequency they were mentioned, and the indicators of competitiveness were estimated by averaging variables representing dimensions identified by exploratory-confirmatory factor analysis. The variables were aggregated into dimensions to permit comparisons in relation to the main competitors.

The results suggest that tourism-specific variables converge to “tourist attractions” and “conviviality,” and that business-related variables converge into “accessibility,” “infrastructure” and “macrostructure.” The competitiveness against competition was evaluated twice: by using an IPA grid to evaluate competition against “all others,” and by comparing the factors of performance across the most cited competitors. The results show that the focal destination surpasses most of its main competitors in conviviality, but has some deficiencies in tourist attractions, and that dimensions representing the business-related variables fit in the middle.

The authors acknowledge that competitive performance, used as surrogate for competitiveness, is fairly limited once it does not consider the supply side potential forces that also influence the destination competitiveness (DC) at large. But although limited to the demand side, the proxy used to assess (DC) is in accordance with previous literature.

The results have high value to DMO managers, especially to those ones involved in developing tourism attractions.

This research advances over previous works: by identifying the nearest competitors of a destination; and by representing the competitive distance between the focal destination and its main competitors.

Destination marketing systems (DMS) represent a vital inter-organisational information system (IOIS) for supporting the collaborative e-marketing strategies of tourism firms and the competitiveness of tourism destinations. However, many DMS have failed to deliver the expected outcomes, while the performance measurement of DMS has not been thoroughly investigated in the literature so far. The study synthesises research from the fields of DMS, IOIS and collaborative practices for investigating the perceptions of various tourism DMS stakeholders about the evaluation of DMS performance. The paper aims to discuss these issues.

The study conducted a nation-wide survey for measuring the perceptions of various tourism DMS stakeholders in Greece about the importance of the roles that DMS should serve as well as the items that should be used for measuring the performance of these DMS’ roles.

The findings showed that the public and private stakeholders held different perceptions about the roles of DMS as well as about the metrics that need to be used for evaluating DMS performance. The findings also showed that the perceptions that stakeholders hold about the roles of the DMS influence their perceptions about the performance evaluation of DMS.

The findings are based on evaluating a specific type of IOIS and sector/context. Thus, caution is required in generalising the results to other types of IOIS and social/environmental contexts.

The study highlighted that the performance and success of DMS, and of IOIS projects in general, require the nurturing of a collaborative culture and the co-ordination of the various stakeholders’ perceptions and interests.

The study addresses the gap in DMS performance evaluation and it contributes to the literature about IOIS evaluation by adopting a stakeholders approach.

The present work assesses destination and service quality attributes, in terms of exploring the stronger and weaker points within these entities. In addition, it explores the relative effect of holistic experiences of destinations and the service-specific attributes on tourists’ overall satisfaction with destinations. Building on the perception, performance, and service quality literature a survey is carried out at 5 different tourist attractions among 701 tourists from over 15 countries worldwide visiting Northern Norway. The results divulge that many destination attributes are important; however, tourists find that the destination performs correspondingly with the perceived importance of destinations. The service quality attributes are also important, but reveal a perceptual gap between importance and performance. The study finds that Northern Norway as a tourist destination should concentrate on “uniqueness” and “novelty” to enhance tourist satisfaction. Service providers are advised to keep up the good work on “giving a good impression and a nice welcome” to enhance tourist satisfaction.

Importance-performance analysis (IPA) remains one of the lesser used quantitative techniques to analyze cultural differences in image perceptions. Therefore, this chapter analyzes differences in international visitors' image perceptions for the island of Mauritius in its key generating markets. Using the mixed method, the study identifies image attributes in a qualitative phase initially, followed by the administration of a survey instrument to a quota sample of 1,000 visitors, resulting in 705 useable questionnaires. IPA reveals the existence of significant differences between importance and performance scores on image for the whole sample as well as significant differences by nationality sub-groups. For example, Germans on average have the lowest importance scores, whereas Indians have the highest in comparison with other nationalities. For each market, the study also identifies the influence of fluency levels in main languages spoken on importance and performance scores. Using IPA, the gaps in scores reflect degrees of product customization and re-positioning that is needed for the different markets of Mauritius. Similarities in scores across nationalities suggest the universal importance of some image attributes in destination selection. The chapter contributes to the dearth of literature on cultural differences in image perceptions for island destinations.

Destination competitiveness is a significant contributor to tourism growth, performance and development. The current research intends to test the effect of the dimensions of the Travel and Tourism Competitiveness Index (TTCI) on destination competitiveness in the United Arab Emirates (UAE), Egypt and Oman and how competitiveness influences tourism performance and development.

The perspectives of 460 responses were collected from the UAE, 457 from Egypt and 301 responses from Oman. Partial least squares structural equation modelling (PLS-SEM) was utilised to measure the research model relationships.

The results showed that the competitiveness index components are significantly contributing to destination competitiveness and that this competitiveness is predicting both tourism performance and development.

This study developed and empirically tested the effect of an integrative model of the competitiveness index on destination competitiveness from the perspective of local visitors in three Muslim and Arab nations. This study gives scholars valuable perceptions into how socio-cultural variations between residents and locals in various nations might result in significantly diverse behaviours.

The paper aims to analyze cognitive attributes affecting the overall destination image perception of British, German and Russian tourists toward Antalya, a well-positioned mass tourism destination in the East Mediterranean region dominated by an all-inclusive (AI) system.

The paper is an empirical study using a structured questionnaire conducted in the summer of 2018 with 274 British, 179 German and 231 Russian tourists departing to their respective source markets from Antalya International Airport. The mean values are used as performance and correlation coefficients of the relationship between each cognitive image dimension and overall image evaluation is used to express importance.

The paper provides empirical insights that these three nationalities prefer Antalya as an AI holiday destination for different reasons and that each nationality demands attention to different factors of the destination for improvement or preservation.

This study provides specific recommendations for AI destinations such as Antalya for the German, British and Russian source markets. When other source markets or types of destinations are considered, the findings of this study should be re-considered. Utilization of the original and modernized importance performance analysis (IPA) plot interpretations in this research reveals a deeper understanding of current findings and provides a new perspective for further research and guidance for destination managers and marketers.

Utilization of both original and modernized IPA plot interpretation in this research not only reveals a deeper understanding of current findings but also provides a new perspective for future studies and guidance for destination managers and marketers.

Unlike the majority of destination image research, this study of destination image based on individual nationalities enables tailor-made destination image development according to diversified importance and performance of destination attributes affecting the overall destination image for each nationality.

This study aims to find a dynamic model in an effort to optimize tourism performance in ecotourism destinations. The model structure is built based on competitive performance in geographic areas and the application of ecotourism elements that are integrated with big data innovation through artificial intelligence technology.

Data analysis is performed through dynamic system modeling. Simulations are carried out in three models: First, existing simulation models. Second, Scenario 1 is carried out by utilizing a causal loop through innovation of big data-based artificial intelligence technology to ecotourism elements. Third, Scenario 2 is carried out by utilizing a causal loop through big data-based artificial intelligence technology on aspects of ecotourism elements and destination competitiveness.

This study provides empirical insight into the competitiveness performance of destinations and the performance of implementing ecotourism elements if integrated with big data innovations that will be able to massively demonstrate the growth of sustainable tourism performance.

This study does not use a primary database, but uses secondary data from official sources that can be accessed by the public.

The paper includes implications for the development of intelligent technology based on big data and also requires policy innovation.

Sustainable tourism development.

This study finds the expansion of new theory competitiveness of ecotourism destinations.

This paper seeks to demonstrate the critical importance of the destination's decisions made in relation to market positioning in understanding the competitive performance achieved by local businesses.

The aim of the empirical research was to check the following hypotheses: clear positioning on longer‐stay customers makes it more likely that the conduct of ski corporations and hotel businesses will complement each other; clear positioning on longer‐stay customers improves the competitive performance of ski corporations; and clear positioning on longer‐stay customers improves the competitive performance of tourist hospitality businesses. The multiple case study methodology was adopted as a means of refuting or confirming these hypotheses, with the use of a combination of qualitative and quantitative data, although giving greater weight to the quantitative sources.

Two dimensions are of decisive importance: the commercial mix of customers attracted to the destination (distinguishing between day‐trippers and longer‐stay customers), and the structural mix of plant capacity and high turnover tourist accommodation facilities.

The case studies chosen have made it possible to test three hypotheses according to which a clear positioning on longer‐stay customers: increases the extent to which the behaviour of ski corporations and hotel structures complement each other; improves the competitive performance of the ski corporations; and improves the competitive performance of the businesses offering tourist accommodation.