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This study aims to present diverse proposals for the measurement of tourism destination competitiveness that serve as alternatives to the travel and tourism competitiveness index (TTCI).

The proposal includes principal component analysis, the DP2-distance method, goal programming, data envelopment analysis and the Borda count. The study evaluates 17 destinations from Central America and the Caribbean.

These include the feasibility that the methodologies provide reliable competitiveness rankings and the possibility of using less information due to the strength of the statistical methodologies. International tourist arrivals, income from international tourism and travel and tourism contribution to the gross domestic product could be used as approximations of tourism destination competitiveness.

The main limitation is the absence of major destinations from the region that constitutes fierce competitors.

New aggregation methods can build composite indicators for competitiveness measurement and their presentation in a more comprehensible way.

The results serve as an alternative for countries that have yet to be considered in international tourism competitiveness comparisons.

A better explanatory power of the proposed index is given, thanks to their decomposition capacity and the reduction of the limitations of the original TTCI. Moreover, the proposals facilitate the inclusion of external information or the execution of a completely objective methodology.

本研究旨在为衡量旅游目的地竞争力提出多样化的建议, 并作为旅行和旅游竞争力指数的替代方案。

该提案包括主成分分析、DP₂ 距离方法、目标规划、数据包络分析和 Borda 计数。 该研究评估了中美洲和加勒比地区的 17 个目的地。

结果包括这些方法提供可靠的竞争力排名的可行性, 以及由于统计方法的优势而使用较少信息的可能性。 国际旅游人数、国际旅游收入以及旅行和旅游对 GDP 的贡献可以用作旅游目的地竞争力的近似值。

主要局限是该地区没有竞争激烈的主要目的地。

新的聚合方法可以为竞争力测量建立综合指标, 并以更易于理解的方式呈现。

结果可作为国际旅游竞争力比较中, 衡量尚未考虑国家的替代方案。

由于其分解能力和原始 TTCI 限制的减少, 所提出的指数具有更好的解释力。 此外, 这些建议有助于纳入外部信息及执行完全客观的方法。

El presente estudio busca presentar diversas metodologías para medir la competitividad de los destinos turísticos, de modo que sirvan como alternativa al Índice de Competitividad de Viajes y Turismo.

La propuesta incluye Análisis de Componentes Principales, el método de distancia DP₂, Programación por Metas, Análisis Envolvente de Datos y el Recuento de Borda. Se analizan 17 destinos de Centro América y el Caribe.

Estos incluyen la validez de las metodologías para obtener rankings de competitividad fiables y la posibilidad de emplear menor cantidad de información, dadas las fortalezas de los procedimientos estadísticos propuestos. Las Llegadas de Turistas Internacionales, los Ingresos por Turismo Internacional, y la Contribución del Turismo al PIB podrían ser buenas aproximaciones para medir competitividad turística

La principal limitación es la ausencia de destinos importantes de la región, que se consideran importantes competidores.

Novedosos procedimientos de agregación para crear indicadores sintéticos para medir la competitividad turística y su presentación de un modo más comprensible.

Los resultados sirven como alternativa para otros destinos que aún no han sido considerados en comparaciones internacionales de competitividad turística.

Un mejor poder explicativo de los índices propuestos, gracias a su capacidad de descomposición, y la reducción de las limitaciones del índice del WEF. Además, las propuestas facilitan la inclusión de información externa o la ejecución de un método completamente objetivo.

Urban MICE competitiveness research consists of two clusters, one that is public-statistics-based and another that is questionnaire-based. Supply-side research on urban MICE competitiveness is rare. Based on the findings of Chen (2014) and other scholars, the purpose of this paper is to design counterpart statistical indicators to empirically analyze CMCA member cities.

After calculating the standardized Z value of the original statistical data for 17 CMCA member cities, the authors conducted confirmatory factor analysis for the first-level principal components, based on which hierarchical clustering was performed; then, regression analysis was conducted with the MICE profit factor as the dependent variable and the cost factor, tight support factor and facilitating factor as the independent variables to support publishing articles.

The confirmatory factor analysis showed that the urban MICE competitiveness indicators from the supply-side perspective include the profit factor, cost factor, tight support factor and facilitating factor.

On the basis of research findings from the demand perspective and the literature review, the authors constructed an urban MICE competitiveness indicator system from the perspective of the supply side and conducted principal component analysis. However, because of the inaccessibility of panel data, the current data were only sufficient to conduct the research. If panel data could be acquired, further research could be conducted to perfect the current indicator system for urban MICE competitiveness.

The findings suggest that tourism total income, tourism foreign exchange income, inbound tourist number, number of exhibitions, exhibition area, number of UFI member cities and number of ICCA member cities were the main reason for the gap between different cities’ competitiveness and the reform focus for improving urban MICE competitiveness. The cost factor had a significantly negative influence on urban MICE competitiveness, implying that the higher the average hotel room price and revenue per available room, the less competitive the MICE host city is.

The tight support factor exerts a significant positive influence on urban MICE competitiveness from the supply-side perspective, while the cost factor exerts a significant negative influence. The findings suggest that the tourism total income, tourism foreign exchange income, inbound tourist number, number of exhibitions, exhibition area, number of UFI member cities and number of ICCA member cities were the main reason for the gap between different cities’ competitiveness and the reform focus for improving urban MICE competitiveness. The cost factor had a significantly negative influence on urban MICE competitiveness, implying that the higher the average hotel room price and revenue per available room, the less competitive the MICE host city is.

The research bridge the empirical statistics and the questionnaire-based perception study on urban MICE tourism image, and advance to construct an empirical statistics based indicator system for urban MICE tourism image.

This research paper aim at providing a new approach of calculating the destinations competitiveness index. How can these variables been aggregated in other to reflect the realities of very distinct productive environments? We assume that: The weighting of variables provides a better measure of destinations competitiveness. Base on the Neo-Technological theory, after a life cycle differentiation, we used a panel data approach to calculate the weight of each variable as the spearman correlation coefficient of its contribution to tourism inflows growth. After integrating these weights, we came to the point that by applying an appropriate weight to its components, we end up having a competitiveness index that significantly improve the correlation between competitiveness and tourism inflows growth.

The purpose of this paper is to demonstrate the relevance of business intelligence (BI) in businesses in general and tourism firms in particular. BI has been hailed as an innovation that can propel businesses that adopt the system to high productivity and efficiency. This paper confirms that view but further adds that BI also enhances a business’s competitiveness.

This paper reviews literature on the use of BI in tourism. Although current literature is largely fragmented, focusing on BI, the tourism industry and the notion of competitiveness separately, this paper makes an attempt to bring the three sub-themes in the same study and highlights their interconnectedness. The study adopts two environmental analysis models to better analyze this matter. First is the environmental analysis model as based on Downes’s modification of Porter’s five forces framework. The second model used is the resource-based view approach to business environmental analysis.

This paper affirms that the tourism industry is one of those industries that continue to benefit from the advantages that come with the adoption of a BI system. Literature shows that the tourism industry was one of those that first adopted BI in order to benefit from the benefits that come with its adoption. Such advantages include flexible and user friendly tourists’ data capture, storage, retrieval, processing and analytical capabilities.

This was a largely literature review-based study. There is, therefore, room for strengthening its findings by conducting field work and mixed methods research for more robust results.

This study will surely benefit the tourism industry and business in general from its highly favorable conclusions to the benefits that come with the adoption of a BI system. It can also be used as a reference in to the tourism field, especially aggregating important concepts and literature that can help future practical studies.

Society will also benefit from this study in terms of the new knowledge that has been generated. Members of society will then be in a position to demand products and services that are a result of innovation and informed decision making.

Although this paper is largely based on literature, the conclusions reached are those of the authors. A close assessment of the literature in BI and the tourism industry was done, resulting in the conclusions reached by the authors.

Nation branding strategies are gaining priority as an area of research because of increasing market complexities and the rising importance of national competitiveness ranking. The sustainable development of a nation brand, when properly managed, will provide the economic incentive to attract investors, tourists and generate income for local communities. Therefore, this paper aims to focus on delineating the strategic imperatives for sustainable market competitiveness of nation brands.

The research adopts an eclectic approach in examining a wider range of factors such as sustainability and market competitiveness to develop a synergistic nation brand.

For nation brands to remain competitive, it is essential to understand the key determinants of market competitiveness. These determinants include sustainable tourism factors such as culture, heritage, environmental and integration of internal and external stakeholder groups from the public and private sectors.

This paper provides a framework for the analysis of sustainable market competitiveness factors of the nation brand. It also provides implications for nation branding and future research agenda.

The purpose of this paper is to provide a comprehensive review of the literature and develop a model of the determinants, indicators and effects of destination competitiveness (DC), as well as several propositions.

This study thoroughly reviewed extant literature to develop a conceptual model and propositions.

Two key findings are listed below. First, 12 different environmental factors are identified and 12 propositions are developed linking these environmental factors to DC. Second, a new indicator of DC is developed, namely, Tourism Attractions-Basics-Context (TABC) model. The TABC model is simple and directly taps into the benefits tourists seek in a destination.

Directions for future research are discussed in detail in the paper.

Managerial implications are discussed in detail in the paper.

The extant research on the topic of DC has been rather fragmented and incomplete in scope. The research presented in this paper addresses these limitations.

Accessible tourism is evolving as a field of academic research and industry practice, set within a dynamic social context. The field is interdisciplinary, multidisciplinary and transdisciplinary. The purpose of this paper is to examine key concepts and global initiatives that will shape accessible tourism futures.

Three of the authors have extensive academic experience in the area and the fourth author is the Managing Director of the pre-eminent European Network for Accessible Tourism. In taking a limited Delphi approach to canvassing key areas likely to shape accessible tourism futures, the following concepts and policy initiatives were examined: motivations, dreams and aspirations of people with disability; demography; UN Convention on the Rights of Persons with Disabilities; destination competitiveness; universal design (UD); and the UN Sustainable Development Goals for 2030.

A discussion of each of the above areas was placed in context to accessible tourism futures and to contextualise the papers that were selected for the special issue. The latter part of the paper outlines the contribution of each empirical paper to the issue discussing the approach, findings and implications. Stakeholder collaboration was identified as the key common theme of the papers and the factor for developing accessible tourism solutions, recognising the value of the market and capitalising on it. A collaborative approach is required to recognise the complementary nature of the different paradigms; to re-shape and transform the future of the accessible tourism industry. To assist in the development of accessible tourism futures, UD principles should provide a foundation to enhance the future competitiveness of tourism destinations and organisations.

The paper’s examination of the concepts and global policy considerations provides a strong academic and practitioner foundation for considering accessible tourism futures. In doing so, accessible tourism futures are shown to be affected by key concepts related to core tourism considerations and major policy initiatives on accessibility and sustainability. Yet, accessible tourism futures also have the potential to create their own momentum and contribute unique learnings on the diversity of tourism markets that will shape tourism concepts and global policy initiatives in their own right.

This article intends to analyse the explanatory power of the Travel and Tourism Competitiveness Index (TTCI) and some of its constituent factors on national success metrics in managing the initial surge of the COVID-19 pandemic.

The authors study the outbreak control effectiveness of 132 countries during the first semester of 2020. The authors apply generalized linear regression models and weighted least squares models using 6 COVID-19-related dependent variables, 9 TTCI-related independent variables and 12 control variables.

The results suggest that countries with superior TTCI values and selected constituent factors have the highest daily averages of coronavirus infections and fatalities per million and the highest speed rates of COVID-19 spread. The authors also find that these countries have the shortest government response time, the lowest daily average of the social restrictions index and the shortest time from the first case reported in China to the first case reported nationally.

To the best of the authors' awareness, no previous study exists analysing the statistical relationship between the TTCIB and some of its constituent factors with the selected metrics of national success at managing the initial surge of the COVID-19 pandemic. This fact represents the primary evidence of this article's unique contribution.

本文擬分析旅行及觀光競爭力指數、以及其部份構成因素，如何影響有關國家在新型冠狀病毒肺炎大爆發初期控制病毒傳播方面的成功指標。

我們就132個國家於2020年上半年控制肺炎爆發方面的表現進行研究。我們以廣義線性回歸模型和加權最小平方法進行分析研究，當中使用了六個與新型冠狀病毒肺炎有關的因變數、九個與旅行及觀光競爭力指數有關的自變數、和12個控制變量。

研究結果暗示、在擁有優越的旅行及觀光競爭力指數值和選定的構成因素的國家，以百萬人來計算，每日冠狀病毒感染及死亡的平均數字是最高的; 而且，新型冠狀病毒肺炎的傳播速度也是最高的。研究結果亦顯示、在這些國家，政府反應所需的時間是最短的，社會限制指數的日均值是最低的，以及首宗在中國被報導的個案與首宗在有關的國家被全國性地報導的個案之間的時間距是最短的。

盡作者們所知，從前似沒有相關的研究、以國家在新型冠狀病毒肺炎大爆發初期成功控制病毒傳播的選定指數、來分析旅行及觀光競爭力指數與其部分構成因素之間的統計關係; 這正是本文所作獨特貢獻的基本證據。

This paper aims to discuss the evolution of tourism data and critically debates future perspective for producers and users of tourism data.

This paper provides a perspective on tourism data based on selected literature.

Industry developments, technological changes and novel methodologies have influenced tourism data sources. Closer attention to new data collection methods and novel analytics is required.

A considerate and integrated system of tourism data (statistics, indicators, and big data) shall remain a priority for scholars and practitioners alike.

The thoughtful merging of tourists’ digital traces with industry data, the competences of data analysts and the theoretical strengths of tourism scholars will result in a redesign of the tourism data landscape.

This perspective article provides a brief overview of the development and challenges related to the future use of tourism statistics, indicators and big data.

The paper offers a novel vision of tourism data by combining three different but complementary aspects of tourism data.