travel & tourism competitiveness index 2022

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Leading countries in the Travel & Tourism Development Index 2021

The economic contribution of travel and tourism, impact of covid-19 on international tourism arrivals worldwide, leading countries and territories in the travel & tourism development index (ttdi) in 2021.

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The Travel & Tourism Development Index (TTDI) is an evolution of the Travel and Tourism Competitiveness Index (TTCI). The source specifies that it "measures the set of factors and policies that enable the sustainable and resilient development of the Travel & Tourism (T&T) sector, which in turn contributes to the development of a country". The index covers 117 countries and is made up of five sub-indexes: Enabling Environment, Travel and Tourism Policy and Enabling Conditions, Infrastructure, Travel and Tourism Demand Drivers, and Travel and Tourism Sustainability. The index scores range from one to seven, with one being the worst rating and seven the best rating.

Statistics on " Travel and tourism in Malta "

Travel and tourism's total contribution to GDP in Malta 2019-2022
Distribution of travel and tourism expenditure in Malta 2019-2022, by type
Distribution of travel and tourism expenditure in Malta 2019-2022, by tourist type
Travel and tourism revenue in Malta 2019-2028, by segment
Leading countries in the Travel & Tourism Development Index 2021
Key data on travel agencies in Malta 2024
Number of inbound tourists in Malta 2001-2023
Number of inbound tourists in Malta 2019-2023, by age group
Leading inbound travel markets in Malta 2019-2023, by number of nights
Inbound tourist expenditure in Malta 2010-2023
Contribution of inbound visitor spending to Maltese exports 2010-2021
Leading inbound travel markets in Malta 2023, by Google travel demand growth
Number of outbound tourists from Malta 2010-2023
Number of nights spent by outbound tourists from Malta 2019-2023, by country
Spending of outbound tourists from Malta 2010-2023
Expenditure of outbound tourists from Malta 2019-2023, by destination
Leading outbound travel markets in Malta 2023, by Google travel demand growth
Number of domestic tourists in Malta 2016-2022
Number of domestic tourists in Malta 2022, by age
Number of domestic tourists in Malta 2015-2022, by destination
Domestic tourism spending in Malta 2016-2022
Cruise passenger movements in Mediterranean ports 2019-2022, by country
Number of cruise passengers arriving in Malta 2011-2023
Number of cruise passengers arriving in Malta 2019-2023, by age
Cruise calls at Mediterranean ports 2019-2022, by country
Number of cruise liner calls in Malta 2008-2023
Number of tourist accommodation establishments in Malta 2022, by type
Key data on the hotel industry in Malta 2022
Number of hotels and similar accommodation in Malta 2013-2022
Number of hotel rooms in Malta 2013-2022
Hotel bedroom occupancy rate in Malta 2013-2022

Other statistics that may interest you Travel and tourism in Malta

Basic Statistic Travel and tourism's total contribution to GDP in Malta 2019-2022
Basic Statistic Distribution of travel and tourism expenditure in Malta 2019-2022, by type
Basic Statistic Distribution of travel and tourism expenditure in Malta 2019-2022, by tourist type
Premium Statistic Travel and tourism revenue in Malta 2019-2028, by segment
Basic Statistic Travel and tourism's total contribution to employment in Malta 2019-2022
Premium Statistic Leading countries in the Travel & Tourism Development Index 2021
Basic Statistic Best-rated countries in the Gay Travel Index 2023
Premium Statistic Key data on travel agencies in Malta 2024

Inbound tourism

Premium Statistic Number of inbound tourists in Malta 2001-2023
Premium Statistic Number of inbound tourists in Malta 2010-2023, by travel mode
Premium Statistic Number of inbound tourists in Malta 2019-2023, by age group
Premium Statistic Leading inbound travel markets in Malta 2019-2023, by number of nights
Premium Statistic Inbound tourist expenditure in Malta 2010-2023
Premium Statistic Leading inbound travel markets in Malta 2019-2023, by tourist expenditure
Premium Statistic Contribution of inbound visitor spending to Maltese exports 2010-2021
Premium Statistic Leading inbound travel markets in Malta 2023, by Google travel demand growth

Outbound tourism

Premium Statistic Number of outbound tourists from Malta 2010-2023
Premium Statistic Number of nights spent by outbound tourists from Malta 2019-2023, by country
Premium Statistic Spending of outbound tourists from Malta 2010-2023
Basic Statistic Expenditure of outbound tourists from Malta 2019-2023, by destination
Premium Statistic Leading outbound travel markets in Malta 2023, by Google travel demand growth

Domestic tourism

Premium Statistic Number of domestic tourists in Malta 2016-2022
Premium Statistic Number of domestic tourists in Malta 2022, by age
Premium Statistic Number of domestic tourists in Malta 2015-2022, by destination
Premium Statistic Domestic tourism spending in Malta 2016-2022

Cruise tourism

Premium Statistic Cruise passenger movements in Mediterranean ports 2019-2022, by country
Premium Statistic Number of cruise passengers arriving in Malta 2011-2023
Premium Statistic Number of cruise passengers arriving in Malta 2019-2023, by age
Premium Statistic Cruise calls at Mediterranean ports 2019-2022, by country
Premium Statistic Number of cruise liner calls in Malta 2008-2023

Accommodation

Basic Statistic Number of tourist accommodation establishments in Malta 2022, by type
Premium Statistic Key data on the hotel industry in Malta 2022
Premium Statistic Number of hotels and similar accommodation in Malta 2013-2022
Premium Statistic Number of hotel rooms in Malta 2013-2022
Premium Statistic Hotel bedroom occupancy rate in Malta 2013-2022

Further related statistics

Premium Statistic Leading European countries in the Travel & Tourism Development Index 2021
Premium Statistic Leading countries in the MEA in the Travel & Tourism Competitiveness Index 2018
Premium Statistic Sub-Saharan African countries in the Travel & Tourism Competitiveness Index 2019
Premium Statistic Inbound tourism of visitors from India to the Netherlands 2012-2017
Basic Statistic Forecast: economic contribution of travel and tourism to GDP worldwide 2020-2029
Basic Statistic Global travel and tourism expenditure 2019-2022, by type
Premium Statistic Travel and tourism competitiveness index score APAC 2019 by segment
Premium Statistic Overnight guests from Canada in the Netherlands 2018, by city
Premium Statistic Inbound tourism of visitors from Denmark to the Netherlands 2013-2019
Premium Statistic Number of hotel bed-places in Saudi Arabia 2008-2022
Premium Statistic Tourism establishments Saudi Arabia 2007-2020
Premium Statistic Average length of hotel stay Saudi Arabia 2004-2022
Basic Statistic Flyer usage before travel and tourism shopping in Canada 2014
Basic Statistic Opinions on EU Digital COVID certificates aiding travel planning in Europe 2021

Further Content: You might find this interesting as well

Leading European countries in the Travel & Tourism Development Index 2021
Leading countries in the MEA in the Travel & Tourism Competitiveness Index 2018
Sub-Saharan African countries in the Travel & Tourism Competitiveness Index 2019
Inbound tourism of visitors from India to the Netherlands 2012-2017
Forecast: economic contribution of travel and tourism to GDP worldwide 2020-2029
Global travel and tourism expenditure 2019-2022, by type
Travel and tourism competitiveness index score APAC 2019 by segment
Overnight guests from Canada in the Netherlands 2018, by city
Inbound tourism of visitors from Denmark to the Netherlands 2013-2019
Number of hotel bed-places in Saudi Arabia 2008-2022
Tourism establishments Saudi Arabia 2007-2020
Average length of hotel stay Saudi Arabia 2004-2022
Flyer usage before travel and tourism shopping in Canada 2014
Opinions on EU Digital COVID certificates aiding travel planning in Europe 2021

travel & tourism competitiveness index 2022

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WEF Travel & Tourism Development Index (TTDI) published today

by Bloom Consulting

The findings of the Travel & Tourism Development Index (TTDI) which measures 117 economies on a range of tourism and travel related indicators and policies, has been published by the World Economic Forum today. The WEF describes this addition as an “evolution” to the previous Tourism and Travel Competitiveness Index .

Every two years, the WEF publishes in-depth analysis as well as an index that gives countries a score and overall ranking and serves as a critical benchmarking tool for the T&T sector. Japan topped the ranking this year, with the United States coming in second; Spain third, and the United Kingdom in eighth position.

Bloom Consulting , a member of an advisory and data partner for the report, believes the outcomes will be highly anticipated by the industry because tourism and travel has changed in unprecedented ways since the publication of the TTDI’s predecessor, the Travel & Tourism Competitiveness Index (TTCI) 2019.

“The climate crisis, the pandemic and now the outbreak of war in Europe continues to disrupt and impact the recovery of the industry. What made an economy competitive in the past, isn’t necessarily what will make it competitive and sustainable for the future. As such, policies and strategies need to evolve and this report provides much needed direction,” said Jose Torres, CEO of Bloom Consulting.

See which countries scored in the top 10 of the WEF TTDI.

New criteria for a new era

Economies are measured using five subindexes and 112 individual indicators which covers a range of criteria that takes into account “business, safety and health conditions, infrastructure and natural resources as well as, environmental, socioeconomic and demand pressures”.

This year, criteria used to measure the long-term development drivers of tourism and travel in economies has been updated to reflect the changing market conditions and include a greater focus on sustainability and resilience. SOCIOECONOMIC RESILIENCE AND CONDITIONS, NON-LEISURE RESOURCES AND T&T DEMAND PRESSURE & IMPACT pillars are all new to the 2021 edition of the TTDI.

“The need for T&T development has never been greater as it plays a critical role in helping the global economic recovery by supporting the livelihoods of some of the populations hardest hit by the pandemic.”

Key outcomes

Uneven t&t recovery .

With the accessibility of vaccines in Western countries, strong government spending and an easing of travel restrictions amongst many Western countries, the T&T industry in the developed world is on the road to recovery.

Whilst international arrivals were still 67 per cent below pre-pandemic levels according to the latest outlook from the United Nations World Tourism Organization (UNWTO), tourist arrivals increased by 4.0 percent in 2021 and numbers in January 2022 rose even further.

While momentum is gathering pace with tourists eager to travel once again, experts say that international arrivals may not return to pre-pandemic levels until 2024 at the earliest. Countries, for instance, like Australia and New Zealand announced only recently that borders were reopening to international travellers. Further, the unprecedented war in Ukraine has led to increased uncertainty and a rise in the cost of living which may lead to less demand for the travel sector.

On a global perspective the recovery of the T&T sector “remains slow, uneven and fragile” due to many factors including the limited access to vaccines in emerging and developing economies and an inclination by some tourists to be more sensitive to health and safety conditions, sticking with destinations with widespread vaccination rates and better healthcare services. In many parts of the world, many Covid-related travel restrictions and mask mandates are still in place.

The World Bank predicts that emerging markets and developing economies (EMDEs) will not return to pre-pandemic tourism activity until after 2023, and 80 percent of tourism reliant EMDEs were below their 2019 economic output at the end of 2021.

Tourism reliant EMDEs face a significant and urgent need to close this gap because their entire economy depends on it. “Investing in T&T could not only mitigate the impact of the pandemic but also improve socioeconomic progress and resilience,” the report said.

Going forward, the T&T sector must work to improve “ the distribution and promotion of natural, cultural and non-leisure assets and activities; the availability of quality transport and tourist service infrastructure; the degree of international openness; and favourable factors such as (increasingly important) ICT readiness and health and hygiene,” the report stressed.

As a result of changing market conditions and increased uncertainty, the public and private sectors are “continuously reviewing their tourism strategies and policies to bolster recovery” whilst the industry overall remains “vulnerable to socioeconomic conditions and global risks”.

Sustainability and resilience

Climate and other environmental issues are a growing risk for many T&T economies with the report warning the sector is “increasingly tied to their ability to manage and operate under ever greater ecological and environmental threats.” Further, results captured from The World Economic Forum’s Global Risks Report 2022 survey confirmed environmental risks represent half of the top 10 global risks.

Even before the pandemic, sustainability issues such as overcrowding, environmental degradation caused by mass tourism, and the liveability for residents in highly visited cities like Amsterdam or Barcelona were mounting.

Whilst the initial lockdowns in 2020 forced a complete stop to the actions causing environmental pressures, new smarter ways of approaching sustainable growth are needed as the global industry works to recover.

“Economies that have sustainable tourism strategies such as the protection of natural assets, longer stays for tourists and the promotion of less populated areas will have long-term competitive advantages because the whole world is moving, slowly but surely, into more sustainable, less carbon intensive ways of operating. Some of the trends we saw during the pandemic, like the shift to nature trips over cities, we think will stay for the long-term,” Torres said.

Changing dynamics of tourism

The pandemic has created new opportunities and shifted consumer preferences - many economies will notice and adapt accordingly. According to the UNWTO Panel of Experts, the major trends driving the T&T recovery include “domestic tourism, travel close to home, open-air activities, nature-based products and rural tourism”.

Over the last two years, nature-related segments saw a 20.8 percent average growth in Digital Demand as people flocked to nature destinations, such as parks and mountains, that were safer and more accessible during the pandemic. In fact, some countries in nature-based and rural tourism markets have been able to grow beyond pre-pandemic levels.

Influenced by the restrictions and travel policies during the pandemic domestic travel rose which saw an average spending increase from 50.8 per cent in 2019 to 62.6 per cent in 2020 among economies ranked in the TTDI. Conversely, the business travel segment declined as people moved to zoom and remote work.

“Reading this report demonstrates that the world has changed and what consumers wanted in the past, will not be what they want in the future. It has been a hugely unsettling time but the industry can also look to the opportunities and the new sources of growth that are starting to take shape as outlined in this report. Nation Brands need to focus on these opportunities whilst realising that uncertainty right now is the norm,” Torres said.

To read the full report, visit www.weforum.org .

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Fact sheet: 2022 national travel and tourism strategy, office of public affairs.

The 2022 National Travel and Tourism Strategy was released on June 6, 2022, by U.S. Secretary of Commerce Gina M. Raimondo on behalf of the Tourism Policy Council (TPC). The new strategy focuses the full efforts of the federal government to promote the United States as a premier destination grounded in the breadth and diversity of our communities, and to foster a sector that drives economic growth, creates good jobs, and bolsters conservation and sustainability. Drawing on engagement and capabilities from across the federal government, the strategy aims to support broad-based economic growth in travel and tourism across the United States, its territories, and the District of Columbia.

Key points of the 2022 National Travel and Tourism Strategy

The federal government will work to implement the strategy under the leadership of the TPC and in partnership with the private sector, aiming toward an ambitious five-year goal of increasing American jobs by attracting and welcoming 90 million international visitors, who we estimate will spend $279 billion, annually by 2027.

The new National Travel and Tourism Strategy supports growth and competitiveness for an industry that, prior to the COVID-19 pandemic, generated $1.9 trillion in economic output and supported 9.5 million American jobs. Also, in 2019, nearly 80 million international travelers visited the United States and contributed nearly $240 billion to the U.S. economy, making the United States the global leader in revenue from international travel and tourism. As the top services export for the United States that year, travel and tourism generated a $53.4 billion trade surplus and supported 1 million jobs in the United States.

The strategy follows a four-point approach:

Promoting the United States as a Travel Destination Goal : Leverage existing programs and assets to promote the United States to international visitors and broaden marketing efforts to encourage visitation to underserved communities.
Facilitating Travel to and Within the United States Goal : Reduce barriers to trade in travel services and make it safer and more efficient for visitors to enter and travel within the United States.
Ensuring Diverse, Inclusive, and Accessible Tourism Experiences Goal : Extend the benefits of travel and tourism by supporting the development of diverse tourism products, focusing on under-served communities and populations. Address the financial and workplace needs of travel and tourism businesses, supporting destination communities as they grow their tourism economies. Deliver world-class experiences and customer service at federal lands and waters that showcase the nation’s assets while protecting them for future generations.
Fostering Resilient and Sustainable Travel and Tourism Goal : Reduce travel and tourism’s contributions to climate change and build a travel and tourism sector that is resilient to natural disasters, public health threats, and the impacts of climate change. Build a sustainable sector that integrates protecting natural resources, supporting the tourism economy, and ensuring equitable development.

Travel and Tourism Fast Facts

The travel and tourism industry supported 9.5 million American jobs through $1.9 trillion of economic activity in 2019. In fact, 1 in every 20 jobs in the United States was either directly or indirectly supported by travel and tourism. These jobs can be found in industries like lodging, food services, arts, entertainment, recreation, transportation, and education.
Travel and tourism was the top services export for the United States in 2019, generating a $53.4 billion trade surplus.
The travel and tourism industry was one of the U.S. business sectors hardest hit by the COVID-19 pandemic and subsequent health and travel restrictions, with travel exports decreasing nearly 65% from 2019 to 2020.
The decline in travel and tourism contributed heavily to unemployment; leisure and hospitality lost 8.2 million jobs between February and April 2020 alone, accounting for 37% of the decline in overall nonfarm employment during that time.
By 2021, the rollout of vaccines and lifting of international and domestic restrictions allowed travel and tourism to begin its recovery. International arrivals to the United States grew to 22.1 million in 2021, up from 19.2 million in 2020. Spending by international visitors also grew, reaching $81.0 billion, or 34 percent of 2019’s total.

More about the Tourism Policy Council and the 2022 National Travel and Tourism Strategy

Created by Congress and chaired by Secretary Raimondo, the Tourism Policy Council (TPC) is the interagency council charged with coordinating national policies and programs relating to travel and tourism. At the direction of Secretary Raimondo, the TPC created a new five-year strategy to focus U.S. government efforts in support of the travel and tourism sector which has been deeply and disproportionately affected by the COVID-19 pandemic.

Read the full strategy here

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Smart destination competitiveness: underscoring its impact on economic growth

Journal of Tourism Futures

ISSN : 2055-5911

Article publication date: 29 June 2023

The current study is designed to investigate the factors that foster the framing of destination competitiveness and establish the factors that drive the contribution of tourism innovations to economic growth in smart tourism destinations.

Design/methodology/approach

A four-year panel data were extracted from the World Economic Forum's travel and tourism competitiveness index and data were analysed using Poisson Pseudo Maximum Likelihood regression model.

The findings demonstrate that both the enabling environment and airport infrastructure significantly affect tourism's impact on the economy of the selected smart European tourism destinations. Conversely, human resources and general infrastructure display a negative correlation with tourism's contribution to the economy. However, no data in the sample support the idea that tourism policies, government prioritization or readiness of tourism information and communication technologies impact tourism's contribution to the economy. Additionally, the marginal effects indicate that improving the enabling environment and airport infrastructure can generate additional benefits for the economy through tourism.

Originality/value

The uniqueness of this study is the integration of smart tourism destinations with the measure of destination competitiveness to provide an empirical bridge that links tourism competitiveness to economic growth.

Economic growth
Tourism competitiveness
Smart destination

Lasisi, T.T. , Odei, S.A. and Eluwole, K.K. (2023), "Smart destination competitiveness: underscoring its impact on economic growth", Journal of Tourism Futures , Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JTF-09-2022-0243

Emerald Publishing Limited

Published in Journal of Tourism Futures . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

Introduction

After several decades of research on tourism destination competitiveness, there is a consensus in academic scholarship that the tourism destination competitiveness index or measure is a necessary tool in stimulating destination growth but more importantly, measuring destination performance. Understandably, the tourism destination competitiveness index objectively balanced both the subjective demands of tourists and the objective industry measures ( Enright and Newton, 2004 ). In other words, destination competitiveness measures both the demand and supply aspects of tourism production and delivery in destination locations.

More recently, the integration of technological advances into the production and consumption of tourism products has seen the introduction of concepts such as Smart tourism destination – a tourism destination that has incorporated information and communication technologies (ICTs) in their tourism services to improve visitor experiences and overall destination performance through co-creation of vales ( Errichiello and Micera, 2021 ). Without a doubt, interest in smart tourism destinations has been increasing among tourists, industry, and academics ( Del Chiappa and Baggio, 2015 ). However, the major focus on smart tourism destination studies has revolved around conceptualization and definitions ( Boes et al. , 2015 ; Buhalis and Amaranggana, 2013 ); co-creation capabilities ( Boes et al ., 2016 ; Buonincontri and Micera, 2016 ), the ecosystem ( Del Chiappa and Baggio, 2015 ) amongst others.

Despite the understanding by practitioners about the importance of destination competitiveness to the attractiveness and performance of tourism destinations, the smart tourism destination research domain is still lacking in the subject of competitiveness measures. Academic scholarships have acknowledged the role of tourism/destination competitiveness in driving economic growth and performance ( Zadeh Bazargani and Kiliç, 2021 ) in developed, developing, and emerging economies, the focus of scholars has been on uncovering the viable models for competitiveness ( Pérez León et al. , 2021 ). Yet, a gulf exists between the understanding of the impacts of tourism competitiveness and the knowledge of the enabling factors for its development.

To the best of our knowledge, Koo et al. (2016) conceptualized the competitiveness measure of smart tourism destinations, Cimbaljević et al. (2019) reviewed extant literature on smart tourism destinations, and Cavalheiro et al. (2020) proposed the developmental model for smart tourism destinations. As such, the current study is designed to investigate the enabling conditions that foster the framing of destination competitiveness in the EU-6 smart tourism destinations. Specifically, the study intends to answer the question of whether or not factors such as government prioritization of tourism, tourism ICT readiness, airport infrastructure, policies, enabling conditions, and visitors' contribution to GDP contribute to destination competitiveness in the case of the EU-6 smart tourism destinations.

Given the above background, concerns, and motivations, the current study holds several contributions. First, the uniqueness of integrating smart tourism destinations with the measure of destination competitiveness provides an empirical bridge that links tourism competitiveness to tourism innovation for the selected European destinations. This presents some advantages to examining competitiveness at a subregional and or country level. In other words, the geographically dispersed nature of the selected European countries supports the extension of the findings across both homogenous and heterogeneous regional settings.

Further, the regional perspective of this study enables the understanding of critical stakeholders in the important factors for region-specific policy generations that are not only effective but appropriate for the contextual composition of the region. Specifically, while other studies have established some important indicator of tourism competitiveness and its linkages to economic performance, to the best of our knowledge, no such study exist with smart tourism destinations in Europe. Hence, the findings of this study can be instrumental in designing policies that are context-specific and useable for the intended stakeholders. Also, the result of this study will be of importance to countries, especially developing nations looking to use tourism development to diversify their economy.

Literature review

Smart tourism destinations.

Some earlier conceptualizations, such as “eDestinations,” have served as inspiration for smart tourism destinations. However, while eDestinations focused on the use of ICTs to deliver information and to play a crucial role in all operations ( Novianti et al ., 2022 ), smart tourism destinations technology is prominently entrenched in all aspects due to new advances like the Internet of Things ( Elkhwesky and Elkhwesky, 2022 ). The topic of smart tourism destinations emerged to explain how the idea of smart cities is applied to tourism destinations ( Coca-Stefaniak, 2020 ). In addition to outlining the components of a smart tourism system, the concept of smart tourism destinations has since been clarified ( Shafiee et al ., 2019 ). Although there is no consensus on a definition for smart tourist destinations yet ( Gelter et al ., 2021 ). de Avila (2015) in Gretzel et al . (2015) defines smart tourism as the utilization of advanced technology infrastructure within an innovative tourist destination to ensure the sustainable development of tourist regions that are accessible to all. This technology also fosters interaction and integration between visitors and their surroundings, enhancing their overall experience while also improving the quality of life for residents. Also, the Spanish innovation-fostering organization SEGITTUR and AENOR, a standardization agency has established one of the most widely used definitions. According to ( SEGITTUR, 2022 ), a smart tourism destination is defined as an innovative tourist destination that relies on advanced technology to facilitate sustainable development and improve the quality of life for both visitors and residents while encouraging interaction with the environment. However, scholars such as Errichiello and Micera (2021) , Gomez-Oliva et al . (2019) , and Özen (2020) , have come up with other definitions.

Smart tourism destinations seek to enhance visitor experiences and doing so requires combining ICTs with the real world. This is in accordance with Errichiello and Micera (2021) , who define smart tourism destinations as locations that use ICTs to improve visitor experiences and organizational performance through increased co-creation of value. The fundamental goal of smart tourism destinations is to enhance visitor experiences by utilizing cutting-edge smart devices and ICTs. Theoretically, this may be accomplished by creating a central technological interface that connects all the stakeholders, incorporates required data from many sources, and facilitates real-time and dynamic information exchange. This would increase productivity, facilitate decision-making, and improve visitor experiences ( Jeong and Shin, 2019 ; Zhang et al ., 2022 ) in a context in which destinations must foster deeper relationships and smarter knowledge sharing among stakeholders to stay innovative and competitive ( Valeri and Baggio, 2021 ). However, in places that promote smart tourism, general technical improvements must be tailored to specific smart technologies, which are specialized tools made for predetermined goals that offer value to the tourism industry by encouraging greater participation, experience personalization, and co-creation ( Zhang et al ., 2022 ). The robust interactions and personalized experiences in smart cities have the potential to benefit all and increase the destination's competitiveness for smart tourism ( Boes et al ., 2016 ).

Travel and tourism competitiveness index

The travel and tourism competitiveness index (TTCI) is a measure of the relative performance of a country's travel and tourism industry ( Rodríguez-Díaz and Pulido-Fernández, 2020a ). It is used to assess the performance of a country's travel and tourism industry in comparison to other countries. The TTCI is based on a range of factors, including the quality of infrastructure, the cost of doing business, the availability of human resources, the level of safety and security, the quality of the environment, and the level of government support. It has been used to identify areas of strength and weakness in a country's travel and tourism industry and to compare the performance of different countries ( Agustin and Martini, 2022 ). The TTCI has also been used to inform policy decisions and assess the impact of policy changes on the travel and tourism industry. The current literature on the TTCI is largely focused on the development and application of the index. Studies have examined the factors that influence the TTCI, the impact of policy changes on the TTCI, and the use of the TTCI to inform policy decisions.

There are two distinct categories of models and studies on the determinants of competitiveness in tourism destinations in the literature: those created by institutions with a high reputation and those created by researchers or authors ( Chin et al ., 2015 ). According to Martínez-gonzález et al . (2021) , the World Economic Forum (WEF) model is highlighted in the literature. The annual Travel and Tourism Competitiveness Report (TTCR-2019) is periodically prepared by WEF and included in this report is the TTCI ( Gómez-Vega and Picazo-Tadeo, 2019 ; Rodríguez-Díaz and Pulido-Fernández, 2019 ). Both the index and report accelerate policy development, decision-making process, and tourism competitiveness evaluation in tourism that makes a destination appealing for international tourism ( Rodríguez-Díaz and Pulido-Fernández, 2020b ; Streimikiene et al ., 2021 ). Furthermore, the TTCI and TTCR-2019 are useful resources for examining destinations' competitiveness from a benchmarking and macro-level approach ( Andrades and Dimanche, 2017 ). A key component of the WEF model is the TTCI which measures a combination of policies and factors that enables sustainable development within the travel and tourism industry, which ultimately contributes to a country's competitiveness and development ( Woyo and Slabbert, 2021 ). The TTCI consistently employs the same factors and metrics, and comparisons between countries using this index are made easier. TTCI enables the adoption of a longitudinal paradigm due to its continuous formulation and structure over time ( Nazmfar et al ., 2019 ; Salinas Fernández et al ., 2020 ). The structure of the TCCI consists of 90 indicators distributed across 14 pillars that are further divided into four subindexes: natural and cultural resources; infrastructure; travel policies and conducive conditions; conducive environment.

The TTCI is used to identify areas of strength and weakness in a country's travel and tourism industry and to compare the performance of different countries. The TTCI has also been used to inform policy decisions and assess the impact of policy changes on the travel and tourism industry. The current literature on the TTCI is largely focused on the development and application of the index. Studies have examined the factors that influence the TTCI, the impact of policy changes on the TTCI, and the use of the TTCI to inform policy decisions.

Hypotheses development

Tourism policies are a government-driven set of discourses, practices, and decisions (often in collaboration with social or private actors) to advance tourism ( Velasco, 2016 ). Policies and enabling conditions can increase the economic growth of smart tourism destinations by proving incentives for businesses to invest in the destinations, such as tax breaks, grants, and other financial support. Additionally, it creates a favourable environment for businesses to operate in, such as providing access to infrastructure, technology, and other resources. This can help businesses expand their operations and create more jobs, which in turn can lead to more innovations and economic growth. Furthermore, with policies and enabling conditions, destinations remain well-maintained and attractive to visitors, which can help increase the number of tourists and their expenditures. Through the development of policies and regulations, the adoption of smart tourism technologies and strategies can be encouraged. This can include tax incentives for tourism businesses that invest in technology, funding for research and development, and collaboration between government and private sector stakeholders. Additionally, governments must create an enabling environment that supports the development and implementation of smart tourism initiatives, including a strong legal and regulatory framework, open data policies, and supportive institutional arrangements.

Policies and enabling conditions in the travel and tourism industry will lead to economic growth in smart tourism destinations.

An enabling environment is critical for the success of smart tourism initiatives. This includes a robust telecommunications infrastructure, reliable electricity supply, and strong cybersecurity measures. Additionally, access to capital, supportive legal and regulatory frameworks, and favourable macroeconomic conditions are important for the development of a thriving smart tourism industry. According to the World Intellectual Property Organization (WIPO), the institution index consists of the business, regulatory, and political environment ( WIPO, 2020 ). The business environment entails the ease of resolving insolvency and private entrepreneurial endeavours while the regulatory environment captures the perception of the government's ability to devise and effect cohesive policies in promoting the private sector, evaluating the cost of redundancy dismissal and the rule of law. The political environment considers the security, operational, or political risk and quality of civil and public services, policy creation, and enactment. A study on tourism innovation and tourism entrepreneurship ( Montañés-Del-Río and Medina-Garrido, 2020 ) considered social capital, intellectual capital, perceptual, sociodemographic, and economic factors that determine innovation propensity among tourism entrepreneurs. Findings from their study suggest that informal investment, level of education, age, and gender of tourism entrepreneurs determine their propensity to innovate. Tourism innovation in the business environment is also related to safe and sustainable transport within a smart approach to transport and mobility at regional and national levels ( Kelemen et al ., 2018 ), which will impact the economy.

Enabling environment will facilitate tourism innovation, which will positively affect economic growth in smart tourism destinations.

The government is essential in shaping competitiveness and the degree to which the government emphasizes that sector can be viewed as the prioritizing of the tourism industry. Governments that prioritize the tourist industry and take action to create an effective destination-marketing strategy for the industry foster innovation. However, government-sponsored destination marketing initiatives strengthen the demand side of the tourism industry while its supply side remains unchanged. Under this circumstance, innovation prioritization switches traditional tourism to a sector that is far more strategically important. Barriers to innovation in tourism strategy and policy include a paucity of strategic vision and minimal emphasis on innovation. This is related to policy actors' limited awareness of tourism innovation and perceptions of the industry as a non-innovative sector. A government can direct funds to crucial development initiatives by stating that the tourism industry is one of its top priorities and by mirroring this in its budget priorities. Other ways that the government prioritizes the industry include establishing exceptional destination-marketing initiatives and striving to timely collect and make travel and tourism data available ( Blanke et al ., 2011 ).

The government's prioritization of tourism will facilitate tourism innovation, which will positively affect economic growth in smart tourism destinations.

The availability of a skilled workforce with expertise in areas such as data analytics, digital marketing, and software development is critical for the development of a successful smart tourism industry. The Human Capital and Research (HCR) index consists of the education, research, development (R&D), and tertiary education subindex ( Shen and Zhao, 2022 ). The education subindex captures education and school life expectancy, achievements at both elementary and secondary levels, as well as government funding for these levels. The R&D subpillar captures the quality and level of research and development activities by researchers, and expenditures on R&D, to mention a few, while the tertiary education subindex captures the coverage (tertiary enrolment); sectors typically linked with innovation are given precedence, as evidenced by the proportion of tertiary graduates in fields such as science, engineering, manufacturing, and construction ( WIPO, 2020 ) as mobility and inbound of tertiary students are important for skill and idea exchange needed for innovation.

Human resources and the labour market will expedite tourism innovation, which will positively affect economic growth in smart tourism destinations.

The infrastructure index consists of ecological sustainability, information, and communication technologies (ICTs), and general infrastructure. Ecological sustainability includes efficiency of energy use, quality certifications, and environmental performance index. The general infrastructure subindex includes but is not limited to equipment and machinery, industrial, commercial, and residential buildings, schools, railways, and so on, while the ICTs subindex includes online participation of citizens, online services by the government, ICT use, and access ( WIPO, 2020 ). The adoption of ICTs is a critical component of smart tourism. This includes the use of mobile apps, digital signage, and social media platforms to enhance the tourism experience. Most studies on tourism innovation- and the innovation–environment nexus have often considered the business environment in relation to innovation (e.g. Madanaguli et al ., 2021 ; Prajogo, 2016 ). According to ( OECD/Eurostat, 2019 ), the natural environment through firms' decisions influences innovation, and likely environmental factors include air, water, and soil pollution, climate change, epidemics, and pandemics. Jacomossi et al . (2021) used regression analysis and mediation techniques to determine the role of ecological sustainability in the innovation–competitiveness nexus in 119 countries. Findings suggest that ecological sustainability significantly mediates the positive relationship between the two variables.

Infrastructure is considered to be an important factor that collaborative business innovation that facilitates local and regional innovation ( Kringelum et al ., 2021 ). Launonen and Viitanen (2011) created a pyramid for innovation, similar to Maslow's hierarchy of needs, and physical infrastructure and service structures are considered to be vital and the bedrock of innovation. Roche (2020) in her study analysed the effect of cities' physical layouts affect innovation. The author theorized that when there is more physically connected infrastructure, there will be a more interpersonal exchange, and this will lead to a more serendipitous exchange of knowledge which will increase innovation. The result of the study revealed that regional innovation differentials may be explained by variations in street network density rather than conventional location. According to Ratten et al . (2019) , tourism innovation is effective innovation that takes into account the existing resources, therefore existing infrastructure will determine the level of tourism innovation, which in turn affects the national/regional economic growth.

Infrastructure/airport transport infrastructure will aid the movement and transfer of knowledge which will encourage tourism innovation, thereby positively affecting economic growth

The relationship between the variables is depicted in the research model as shown in Figure 1 .

Research context

Based on de Avila's (2015) in Gretzel et al . (2015) definition of a smart tourism destination, the study considers the six smart tourist destinations (France, Ireland, Italy, Slovenia, Spain, and the Czech Republic) to determine the impact of the travel and tourism competitive index on economic growth. According to the European Commission's initiative – European Capitals of Smart Tourism (ECST) (2022) , cities with outstanding achievements in smart destinations were shortlisted in the ECST competition. Consequently, the top countries with smart cities were included in the current study. The analysis also focused on these countries because they are among the most popular tourist destinations in Europe, and therefore analysing their tourism industry could provide valuable insights into the potential benefits and challenges of developing smart tourism initiatives in other high-traffic destinations. Furthermore, this study also focused solely on these countries because it is part of a larger research project that focuses specifically on these selected countries. Ensuing, this section will discuss the World Economic Forum's TCCI of the research contexts.

Regarding Travel and Tourism (T&T) policy and enabling conditions, which capture the specific strategies or policies that directly impact the T&T industry, Figure 2 reveals that for the years 2015–2019, France recorded an average annual growth rate of 6.17%. Ireland has the lowest average annual growth rate of 1.83%, and Italy is performing below the European median between 2015 and 2019. The enabling environment subindex denotes the general condition to operate in a country. Figure 2 indicates that France experienced an average annual growth rate of 1.84% for the time. Of the countries under consideration, the Czech Republic has the highest average annual growth rate at 2.5%, while Ireland has the lowest average annual growth rate at 0.37%. Furthermore, with the government's prioritization of tourism, Spain experienced an annual average growth rate of 2.2% for the period 2015–2019 as shown in Figure 3 . Of the countries under consideration, Ireland has the highest average annual growth rate at 9.19%, while Slovenia has the lowest average annual growth rate at −1.22%. For the enabling environment, from 2015 through 2019, the Czech Republic experienced an average annual growth rate of 2.5%. The highest average annual growth rate among the selected countries is 2.5% in the Czech Republic, while the lowest average annual growth rate is 0.37% in Ireland. For the human capital and research subindex, as shown in Figure 4 , the Czech Republic experienced an average annual growth rate of 1.53% for the period 2015-2019. Of the countries under consideration, Slovenia has the highest average annual growth rate at 2.75%, while Ireland has the lowest average annual growth rate at 0.7%.

As shown in Figure 4 , for the infrastructure subindex, the Czech Republic experienced an average annual growth rate of −0.71% for the period 2015–2019. Of the countries under consideration, Spain has the highest average annual growth rate at −0.53%, while France has the lowest average annual growth rate at −2.5%. All countries performed above the region median except Slovenia, which was just on the mark between 2017 and 2019. For the airport transport infrastructure, the Czech Republic experienced an average annual growth rate of 3.71% for the period from 2015 to 2019. Of the countries under consideration, Ireland has the highest average annual growth rate at 4.21%, while France has the lowest average annual growth rate at −1.31%.

Data and methodology

The TTCI was the source of data used for the empirical estimation and the data used spanned between 1995 and 2021. Data used for the empirical analysis were based on a sample of 162 observations from six smart tourist destinations (France, Ireland, Italy, Slovenia, Spain, and the Czech Republic). This included 27 observations from each country. The TTCI is a biennial report issued by the World Bank Group's Macroeconomics, Trade and Investment Global Practice. The TTCI aims to provide accessible data on countries' trade and competitiveness. It currently compares the competitiveness of 140 economies in the travel and tourism industry. The TTCI is perhaps the most used dataset for assessing the competitiveness of travel and tourism. According to Iunius et al . (2015) , the TTCI measures a set of policies and factors that facilitate sustainable development in the T&T sector and also enhance a country's competitiveness and development. It is made up of four subindices, 14 pillars, and 90 individual indicators that are dispersed across the pillars. In this study, the enabling environment, Tourism Policy, Enabling Conditions, and Infrastructure indices were used for institutions, human capital and research, and infrastructure pillars of the Global Innovation Index (GII) and expressed as scores on a 1–7 scale, with 7 being the most desirable outcome. There are two main reasons why the TTCI framework is adopted by this study. TTC, for beginners, is built on a modern framework that is regularly updated. This implies that when analysing competitiveness, current changes in the travel and tourism industry are considered. Second, in recent tourist destination competitiveness studies, scholars have used TTCI in their studies (e.g. Fernández et al ., 2020 ; Perez Leon et al ., 2021 ; Zaroki and Owliaaynasab, 2018 ). This research shows that the TTCI can be used in similar studies.

For the methodological approach, we used the Poisson Pseudo Maximum Likelihood regression model technique with high-dimensional fixed effects (PPMLHDFE). This was the model of choice because our dependent variable is count data with no negative values. The PPML regression is a suitable model that has the natural ability to analyse count data with zero values in dependent variables. According to Correia et al . (2020) , the PPMLHDFE considers the advantages of the Poisson estimator (PPML) as well as having the ability to control individual fixed effects. It is known to provide a more robust technique to examine the presence of (pseudo) maximum likelihood estimates. In addition, it is able to manage multiple sources of heterogeneity in comparison to other high-dimensional fixed effect non-linear algorithm estimators. It also provides quick estimation of the parameters as it can eliminate the unnecessary number of iterations. The PPML regression was preferred to other log-linear regressions because, in the existence of heteroskedasticity, the estimations of log-linearized models fit by for instance the Ordinary Least Square (OLS) will be inconsistent ( Correia et al ., 2020 ; Martin and Pham, 2020 ). We used the PPML model applied to tourism's contributions to gross domestic product (GDP); this allowed us to account for zero values. We believe that not all firms can make profits from the sale of new products, and there will be firms that can break even. So, the PPML regression can be the solution to the zero values in GDP problems that can exist in our data helping us to avoid dropping such observations. This regression model helps us to overcome selection bias, which will not be in the case of the OLS model. Following the literature, see Larch et al. (2019) , we provide the model to capture tourism contributions to GDP in these countries as (1) T C i j t = exp ( λ i t + ϕ j t + Ε j t + Ρ ′ Χ i j t ) + ε i j t where TC is tourism contribution to GDP; λ it and ϕ j t are variables enhancing tourism contributions to GDP in smart tourism destinations; Ε jt refers to fixed effects of smart tourism destinations; Χ ijt denotes common variables between smart tourism destinations that vary over time; ε ijt denotes the error term. Substituting our explanatory variables into equation (1) , we provide our proposed structural gravity equation as (2) T C i j t = exp ( α + β 1 P o l i c y a n d e n a b l i n g c o n d i t i o n i t + β 2 E n a b l i n g e n v i r o n m e n t i t + β 3 G o v e r n m e n t p r i o r i t i z a t i o n i t + β 4 H u m a n r e s o u r c e i t + β 5 I C T r e a d i n e s s i t + β 6 i n f r a s t r u c t u r e i t + β 7 A i r t r a n s p o r t i n f r a s t r u c t u r e i t + β 8 c o u n t r y d u m m i e s i j t ) + ε i j In the field of economics and other social sciences, the marginal effect has become widely embraced. Marginal effects analysis provides good and consistent estimates of the magnitude of changes in the dependent variable when there is a marginal change in the covariates ( Ai and Norton, 2003 ). Using marginal effects estimations allows researchers to express how the predicted probabilities of explanatory outcomes change with its associated risk factors ( Norton et al ., 2019 ). In addition, the marginal effects allow for easy comparison that allows researchers to know what happens when there are any additional changes in the independent variables. Table 1 describes the variables used for the empirical estimations.

We begin the results with the descriptive statistics in Table 1 to provide a general overview of the sample population. The average contribution of tourism to GDP is about $41.613 as shown in Table 1 . The average of the policies and enabling environment was about 0.512. When it comes to enabling environment, the average contribution is about 0.605. The average of the government prioritization variable is 0.576. The variable on human capital or resources has an average of 0.552. Tourism ICT readiness also has an average of 0.613 while the maximum for that variable is 5.92. The general infrastructure component has an average score of about 0.558 with a maximum value of 5.68. Finally, the variable on air transport infrastructure has a mean value of 0.451. The mean results show that they are all far less than one.

The predictive power of our model as shown by the coefficient of determination score ( R 2 ) is 0.894 as shown in Table 2 , meaning that the combined effect of the endogenous variables on exogenous variables was high predictive accuracy of about 89%. We now test the various hypotheses using the poison pseudo maximum estimator.

Table 3 shows the average marginal effects of tourism contributions to economic growth, indicating the result hypothesized relationships. Regarding the first hypothesis focuses on policies and enabling conditions that impact economic growth in smart tourism destinations, we find no statistically significant evidence in the sample supporting this relationship ( β = 0.180, p > 0.293), so we reject this hypothesis. Hypothesis 2 also focuses on establishing the relationship between enabling environment's role in facilitating tourism innovations as expected. We find a positive and statistically significant relationship with the sample ( β = 0.742, p < 0.007). We, therefore, accept hypothesis 2 . Our hypothesis three is not supported. We find no positive and statistically significant correlation between government prioritization and economic growth ( β = 0.020, p > 0.832). The results show that when government prioritizes tourism and focuses resources in that sector, it does not potentially contribute to economic growth. The fourth hypothesis stating that human resources and the labour market could contribute to positively affecting economic growth in smart tourism destinations is not supported. We find a statistically significant but negative relationship in the sample supporting this ( β = −0.533, p < 0.001). This negative relationship means that we reject hypothesis 4 .

Finally, hypothesis 5 which sort to establish the nexus between infrastructure and knowledge transfers is partially supported. We find evidence positively supporting air transport infrastructure ( β = 0.222, p < 0.002), while we find a negative correlation between general infrastructure probability to influence tourism's contributions to GDP ( β = −0.341, p > 0.001). The results on the country dummies also point to the expected benefits of tourism's contributions to these countries' growth. We find that in all the sampled countries, tourism demonstrates to have a positive and statistically significant contribution to GDP. However, the expected benefits were lower for the Cech Republic, and Ireland as shown by the lowest coefficient ( β = 1.254, p < 0.001) and ( β = 1.060 p > 0.001). France, Italy, and Spain demonstrated to have the highest contributions from Tourism to GDP. France was probable to have the highest tourism contribution based on the highest coefficient ( β = 4.115, p < 0.001) followed by Italy ( β = 4.148, p < 0.001).

Discussions

Every economic activity is aiming to employ innovative approaches that can help provide a competitive advantage over market rivals, and the tourism sector is no exception. The economies of these countries support the tourism-led growth hypothesis, and the economic growth of these economies is dependent on tourism. An increase in tourism positively leads to increased growth. Most of these tourist countries have applied the concept of innovations with varying degrees of success over the past years ( WIPO, 2020 ). But existing research has not highlighted the importance of innovation adoption in the tourism sector. This means that the factors capable of inducing tourism innovations need to be examined to influence tourism innovation policies. This paper has focused on analysing the key determinants that can enhance innovations in this vital sector in these six important tourist destinations in the European Union. Our results have surprisingly demonstrated that policies and enabling conditions in these countries are not statistically significant factors capable of driving improved tourism's contributions to economic wealth. This insignificant result means that we reject hypothesis 1 . The marginal effect results show that existing policies and enabling conditions in these countries do not marginally influence GDP. This can be because the policies that focus on the specific policies or strategic characteristics impacting the tourism industries directly in these countries are not effective in achieving their intended objectives of boosting tourism. This result calls for comprehensive reviews of various country-specific policies to assess their effectiveness or otherwise and find ways to improve upon them. The ineffectiveness of Italy's tourism policymakers has also been acknowledged by a study by Iș;ik et al . (2020) who called for a comprehensive review country's tourism policy to make them more sustainable. Niavis et al . (2022) found that intervention policies in most Mediterranean countries are ineffective in boosting tourism activities.

Our result on the enabling environment's positive role in influencing tourism's contributions to GDP is as expected and supports hypothesis 2 . The results show that when the enabling conditions improve, it can contribute to improved tourism contributions to GDP. As shown by the marginal effects results, any improvements in enabling conditions in these countries could potentially increase tourism's contribution to GDP marginally by US$ 31.055. This result signifies that these countries must work on improving upon the enabling conditions such as specific policies capable of directly impacting the tourism sector. These countries should enhance tourism activities by diversifying individual markets and also by supporting promotion bodies such as travel and tour organizations. Policies on the enabling conditions should focus on the international openness of these countries to make them more attractive to future tourists. The regulation of travel and tourism sector business operations to ensure they do not distort the prevailing prices of tourism products among others. Our result is comparable to the findings of a similar by Goral (2016) conducted in eight Mediterranean tourist destinations that included Spain, France, Italy, Greece, and so on. They also find that enabling conditions in these popular tourist destinations significantly influence tourism income.

Furthermore, the study did not find any statistical significance in the government prioritization variable. Due to the insufficient compelling evidence in the sample supporting this relationship, we reject hypothesis 3 . The countries are expected to benefit from a clear prioritization of the tourism sector with high government investments to support tourism activities and promotions. What this means is that when governments in these popular tourist destinations put tourism high on their agenda and promote it, the expected benefits from the priority do not impact the returns to tourism. However, the results should be interpreted with caution as the countries are not homogenous in terms of their abilities to attract tourists. The results could be impacted by the countries such as Ireland that are not bigger in terms of attracting tourists in relation to the other countries. Despite the insignificant relationship, we believe the government of these countries where tourism is the backbone of economic growth should focus on promoting and prioritizing tourism development to continuously provide the needed economic benefits. The prioritization can be in the form of supportive policies and infrastructure to ensure becomes beneficial to economic and regional growth ( Lee and Brahmasrene, 2013 ).

The results point to a negative correlation between human resources and their ability to contribute to economic growth (GDP). This negative relationship implies that we did not find compelling evidence in the sample supporting hypothesis 4 . This inverse relationship means that the human resources in the tourism sector do not make a significant impact on its ability to drive economic growth. We did not find causality buttressing the economic-motivated tourism growth, meaning that tourism development is not a product of human resources. The results could mean that levels of training received by tourism staff do not lead to satisfaction with tourism services hence their ineffectiveness in promoting tourism. As shown by the marginal effects results, whenever there is an increase in human resources in tourism, it rather exerts a negative influence on the expected contributions to GDP, reducing it by US$ 22.332. The results could mean that the human resources in tourism in these countries might not have the necessary skills that could help them to contribute better to tourism activities which can influence GDP. This calls for these countries to upgrade their human resource with the requisite skills that will make them contribute better to improving tourism services. Our result differs from the findings of a related study ( Rivera, 2017 ), which found that human development promotes tourism by creating an unbalanced connection. Fahimi et al . (2018) also find that human capital development positively contributes to economic growth.

We did not find compelling evidence in our sample to support the relationship between ICTs readiness and tourism contributions to economic growth. This result means that tourism’ ICT readiness does not significantly impact tourism's contribution to economic growth implying they do not promote tourism competitiveness. The marginal effect result has proven that tourism ICT readiness in these countries reduces tourism-related GDP by US$ 10.310. This is result surprising because ICT infrastructure is anticipated to positively impact the tourism sector and accelerate smart tourism ( Park et al ., 2016 ). This result means that the use of ICT in the tourism sectors in these countries does not result in any changes in expected tourism outcomes. This result is a bit surprising as the tourism sector has become ICT-based, and tourists require information to help with the planning of their trips, for flight and hotel reservations. Internet penetration through the Internet and smartphone technologies are expected to bring positive gains to tourism promotion, but our results confirm otherwise. For these tourism destinations, ICT helps in the promotion of their various attractions that can help attract people. However, we find that the adoption of ICT in these tourist destinations does not help to drive tourism activities. This result calls for these countries to examine their ICT infrastructure for possible improvements to make the significant promotion of tourism. Our results differ from the findings of a related study by Pierdicca et al . (2019) who find that innovative ICT infrastructure facilitates tourist attractions to regions that further contribute to overall territorial economic growth.

Finally, we find mixed results on the role of infrastructure in promoting tourism contributions to economic growth. These results partially supported our hypothesis 5 . Regarding the general infrastructure, we witnessed a negative relationship, implying that general infrastructure negatively influences tourism's contribution to GDP. The results on the marginal effects show that any increase in infrastructure leads to a reduction in tourism's contribution to GDP by about US$ 14.272. However, when we consider airport infrastructure, we find that it significantly and positively contributes to increasing GDP growth marginally by US$ 9.296. This is an expected finding because airport infrastructure facilitates the swift movement of people, goods, and services, so when there is the availability of such infrastructure, it can attract more people to these destinations. Adequate airport infrastructure can promote the tourism drive of these countries and make them preferred destinations. Where these airport infrastructures are inadequate, it leads to higher transport fares which will make these destinations unattractive. It is therefore expected that the marginal effects results show that airport infrastructure marginally contributes to the GDP of these countries. The results also suggest that investment in airport infrastructure in these countries can promote tourism and its spillover effects on regional economic growth. Our results on the significance of airport infrastructure in promoting tourism are supported by a study by Doerr et al . (2020) , who also find that airport infrastructure promotes tourism in German regions.

This paper aimed at analysing the factors driving tourism's contributions to the economies of six smart tourist destinations across the European Union. The analysis of the tourism competitiveness of these countries based on tourism-related data has provided interesting results. The study finds among others that tourism competitiveness in these countries is significantly and positively influenced by enabling environment and airport infrastructure. These significant results supported our hypotheses 2 and 5 . Contrarily, our hypothesis four was not supported, as the study revealed that determinants such as human resources (labour market) and general infrastructure in these countries exert a negative influence on tourism contributions to economic growth. Other factors such as policies and enabling conditions, government prioritizations, tourism ICT readiness, and general infrastructure were not statistically significant factors capable of driving tourism's ability to contribute to economic growth in these smart tourist destinations. These insignificant results led to the rejection of hypotheses 1 and 3 .

This study contributes to literature in several ways. Firstly, academic scholarships have acknowledged the role of tourism/destination competitiveness in driving economic growth and performance ( Zadeh Bazargani and Kiliç, 2021 ) in developed, developing, and emerging economies, the focus of scholars has been on uncovering the viable models for competitiveness ( Pérez León et al. , 2021 ). Yet, a gulf exists between the understanding of the impacts of tourism competitiveness and the knowledge of the enabling factors for its development, which this study bridges. Secondly, our result gave empirical evidence that government prioritization of tourism, policies, enabling conditions, ICT readiness, and general infrastructure does not have any significant effect that leads to economic growth. This begs the question and the need for further research to understand if pre-existing conditions and the state of these countries need to be improved even though technology helps in achieving the smartness of the cities but does not reflect in its tourism sector. Lastly, as most of these hypotheses were rejected, and further empirical and comparative investigations can be carried out for top tourist destinations, as this will further shed light on tourism competitiveness in this comparative model, thereby improving literature.

This study has managerial and policy implications. Our results also make significant contributions to gaining a better understanding of the benefits countries could derive from tourism and the travel sector. First, we have shown that enabling the environment is a vital driver of tourism's impact on economic growth. This result calls for policymakers and stakeholders in these countries to pay attention to specific policies that aim at facilitating tourism activities. The calls for strong political will and commitments of various respective governments will in providing and supporting the enabling environment tourism needs to thrive. Various levels of government in these countries need to collaborate and coordinate their activities to create this enabling environment. The second significant finding of this research is that airport infrastructure significantly contributes to sustainable tourism contribution to economic growth. This result calls for these destinations to improve upon their existing airport infrastructure to be able to accommodate the numerous tourists. This investment can help reduce transportation costs and make them more attractive to tourism. Policymakers also need to consider the cost and benefits of such airport infrastructure projects and make commitments to improve them. Lastly, these countries should enhance their international competitiveness through bilateral agreements which could be enhanced by including various consulates and embassies.

Few limitations have been recognized in this research, which could provide further directions for future research. First, the study was based on the empirical analysis of TTCI data involving just six smart tourist destinations. To fully understand and generalize our results on whether the outlined factors influence tourism contributions to GDP, will require more studies to be replicated in other well-known tourist destinations. The study was based on four-year panel data, we recommend further studies use longer panel data to comprehensively capture the trends, changes, and long-run effects of tourism's contribution to economic growth.

Research model

Travel and tourism policy and enabling conditions and enabling environment subindex

Government prioritization of tourism and human resource and labour market subindex

Infrastructure and airport transport infrastructure subindex

Descriptive statistics of the variables

Note(s): dy/dx is marginal effect coefficients, Std. Err. represent standard errors estimated with the Delta-method

*The coefficients are significant at 10%

**The coefficients are significant at 5%

***The coefficients are significant at 1%

Source(s): Authors' estimations

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Acknowledgements

Taiwo Temitope Lasisi gratefully acknowledges the financial support of the Faculty of Informatics and Management of the University of Hradec Králové (FIM UHK) within the framework of the Specific Research Project “Information and knowledge management and cognitive science in tourism”. The authors wish to express their thanks to Zuzana Kroulíkova and Ondřej Tázlar, FIM UHK students, who assisted with the graphical elements of this study.

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Travel & Tourism Development Index 2021: Rebuilding for a Sustainable and Resilient Future

Executive summary

Embeddinginclusivity, sustainability, and resilience into the Travel and Tourism sectors as it recovers will ensure it can continue to be a driver of global connectivity, peace, and economic and social progress.

The Travel & Tourism Development Index (TTDI) 2021 is an evolution of the 15-year-old Travel & Tourism Competitiveness Index (TTCI) series, a flagship index of the World Economic Forum’s Platform for Shaping the Future of Mobility. This revised index serves as a strategic benchmarking tool for policy-makers, companies and complementary sectors to advance the future development of the Travel and Tourism (T&T) sector by providing unique insights into the strengths and development areas of each country/economy to enhance the realization of sector potential and growth. Furthermore, it serves as a platform for multistakeholder dialogue to understand and anticipate emerging trends and risks in global T&T, direct policies, practices and investment decisions, and accelerate new models that ensure the longevity of this important sector. The publication’s theme is “Rebuilding for a Sustainable and Resilient Future”. The COVID-19 pandemic has been one of the greatest challenges the T&T sector has faced, undermining not only the prosperity of businesses within the sector but also the well-being of tens of millions of employees, local communities and entire economies around the world. At the time of writing, the sector, and the world at large, is starting to assess the impact of the war in Ukraine. Global shocks such as this bring additional instability and economic disruption to the sector and could have long-term impacts on T&T development, as has happened with the pandemic. As the sector slowly recovers, it will be crucial that lessons are learned from recent and current crises and that steps are taken to embed long-term inclusivity, sustainability and resilience into the T&T sector as it faces evolving challenges and risks. In doing so, the sector can continue to be a driver of global connectivity, peace and economic and social progress. T&T development strategies will play an important role in accomplishing this. Accordingly, important changes have been made between the TTCI and the TTDI.

The TTDI benchmarks and measures “the set of factors and policies that enable the sustainable and resilient development of the T&T sector, which in turn contributes to the development of a country”. The transformation of the TTCI into the TTDI reflects the index’s increased coverage of T&T development concepts, including sustainability and resilience impact, on T&T growth and is designed to highlight the sector’s role in broader economic and social development as well as the need for T&T stakeholder collaboration to mitigate the impact of the pandemic, bolster the recovery and deal with future challenges and risks. Some of the most notable framework and methodology differences between the TTCI and TTDI include the additions of new pillars, including Non-Leisure Resources, Socioeconomic Resilience and Conditions, and T&T Demand Pressure and Impact.

The index is comprised of five subindexes (used for presentation and categorization purposes only), 17 pillars, and 112 individual indicators, distributed among the different pillars.

Top-line results

Relatively stagnant TTDI results reinforce the difficult situation the T&T sector faces. On average, TTDI scores increased by just 0.1% between 2019 and 2021, with only 39 out of 117 economies covered by the index improving by more than 1.0%, 51 increasing or decreasing within a 1.0% range and 27 declining by over 1.0%.

Aside from the United States (2nd), the top 10 scoring countries are high-income economies in the Europe and Eurasia or Asia-Pacific regions. Japan tops the ranking, with fellow regional economies Australia and Singapore coming in 7th and 9th, respectively. Meanwhile, Italy joined the top 10 (up from 12th in 2019) in 2021, while Canada slid out (10th to 13th). The remaining top 10 TTDI performers are Spain (3rd), France (4th), Germany (5th), Switzerland (6th) and the United Kingdom (8th). Viet Nam experienced the greatest improvement in score (+4.7%, 60th to 52nd) on the overall index, while Indonesia (+3.4%, 44th to 32nd) and Saudi Arabia (+2.3%, 43rd to 33rd) had the greatest improvement in rank. Meanwhile, Malaysia (-3.0%, 29th to 38th), India (-2.6%, 46th to 54th) and Mongolia (-2.1%, 76th to 84th) had the largest declines in ranking.

The key findings of the index show the following:

The need for T&T development has never been greater: The T&T sector is a major driver of economic development, global connectivity and the livelihood of some of the populations and businesses most vulnerable to, and hardest hit by, the pandemic. Therefore, supporting T&T development and recovery – which in turn will help the global recovery, build resilience and support all of those who depend on the sector for work – will be critical.

The T&T sector has faced difficult operating conditions, but shifting demand dynamics have created opportunities and a need for adaptation: In the shorter term, challenges such as reduced capacity, geopolitical tensions and labour shortages are slowing recovery. However, opportunities have been created in markets such as domestic and nature-based tourism, the rise of digital nomads and “bleisure”. 1 The T&T sector stakeholders’ ability to adapt under these conditions highlights its capacity for adaptation and flexibility.

T&T development strategies can be employed to help the sector build back better: Amid the current challenges, shifting demand dynamics and future opportunities and risks, a more inclusive, sustainable and resilient sector can be – and needs to be – built. However, this calls for thoughtful and effective consideration. It also requires leveraging development drivers and strategies, including: restoring and accelerating international openness and consumer confidence, via, for example, improved health and security; building favourable and inclusive labour, business and socioeconomic conditions; focusing more on environmental sustainability; strengthening the management of tourism demand and impact; and investment in digital technology.

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Travel & Tourism Development Index 2021: Rebuilding for a Sustainable and Resilient Future

5. Regional results

The Europe and Eurasia and Asia-Pacific regions dominate the index ranking, while sub-Saharan Africa showed the greatest improvement in performance.

Figure 13: Regional TTDI 2021 performance distribution

Overall, the Europe and Eurasia (Europe) and Asia-Pacific (APAC) regions dominate the TTDI ranking (9.0% and 4.9% above the TTDI average, respectively). However, Europe is the only region to have decreased its average score since 2019 (just -0.5%), very slightly eroding its considerable lead. On the other hand, the sub-Saharan Africa (Africa) region had the greatest improvement in performance (+1.1%), but far more needs to be done for economies in the region to catch up with the global average (-18.4% below TTDI average). The Americas and the Middle East and North Africa (MENA) regions also underperform the global average (-3.1% and -2.8% below TTDI average). Nonetheless, the Americas region has marginally gained in its score (+0.6%), while MENA has remained relatively stable as its improvement (+0.1%) was in line with overall global performance.

The section below provides additional analysis of each region and highlights the top performers or interesting results. It is important to note that regions are often composed of a wide variety of economies at different levels of development. Therefore, the quantitative results may not reflect some of these more nuanced realities. For a more in-depth visualization of regional data, please click here .

The Americas

While 13 out of the 21 Americas economies covered in the TTDI have improved their score since 2019, the region as a whole still performs below the TTDI average, with just under half of the 21 economies scoring above the mean. One of the most defining aspects of the region’s T&T is its rich endowment of nature. More than half of its economies score above the TTDI average for the Natural Resources pillar, nine are in the top 20 performers and five (in order of pillar scoring, Mexico, Brazil, the United States, Canada and Colombia) among the top 10. These five, and a few others, also possess above-average cultural and non-leisure resources. On average, the region’s economies also have above-average tourist service infrastructure, price competitiveness and prioritization of T&T, although this varies greatly between constituent countries.

On the other hand, the region’s T&T sector faces many challenges, not least unfavourable enabling environments and, in particular, often poor business (especially outside of high-income economies) and safety and security conditions. In fact, half of the 20 lowest-ranking economies for safety and security globally come from Latin America. The region’s less developed economies require significant investment in mobility services and infrastructure, especially for ground transport, and a noticeable need to enhance international openness. The majority of economies in the Americas also need to tackle socioeconomic resilience and environmental sustainability issues.

The United States is the region’s top TTDI scorer (2nd) and accounts for the vast majority of the region’s T&T GDP. Outside of the United States, Canada (13th), Mexico (40th), Brazil (49th) and Argentina (59th) account for much of the remaining T&T GDP. Chile (34th) stands out as the top performer in South America, while Uruguay , which was the most T&T-dependent economy in the region in 2020, experienced the fastest rate of improvement (+3.6%, 61st to 55th).

Asia-Pacific

The APAC region is the second-highest performer in the ranking. Of its 20 constituent economies, 12 score above the TTDI average and 13 have improved their score since 2019.

The region is large and diverse. It is home to some of the best combinations of natural, cultural and non-leisure resources, but environmental sustainability challenges threaten its lead in the former. Many of the more developed economies in APAC have world-class transport, tourism, healthcare and ICT infrastructure, high levels of international openness and investment in T&T, conducive business environments, high performance for socioeconomic resilience and qualified and productive workforces. On the other hand, the region’s less developed economies’ advantage in price competitiveness and rich natural assets are often offset by gaps in the aforementioned factors such as tourism, healthcare and ICT infrastructure, international openness and socioeconomic resilience. However, these gaps are being bridged somewhat as APAC’s lower- middle-income economies have improved their performance, with particularly strong growth in areas such as ICT readiness.

As mentioned, Japan is the top performer in both the APAC region and globally, with Australia (7th) and Singapore (9th) ranking in the global top 10. However, it is lower-middle-income economies such as Viet Nam (+4.7%, 60th to 52nd), Indonesia (+3.4%, 44th to 32nd) and Pakistan (+2.9%, 89th to 83rd) that have improved their TTDI scores the most since 2019. China, which ranks 12th on the TTDI, has the region’s largest T&T economy, while the Philippines, which depended the most on T&T for its GDP in 2020, ranks 75th. Although Japan and Singapore lead the ranking in the Eastern APAC and South-East Asia subregions, respectively, India (54th) is the top scorer in South Asia.

Europe and Eurasia

Europe remains the TTDI’s top-performing region, surpassing the global average in most pillars and being among the best positioned to grow in the coming years. Of the 43 regional economies covered in the index, 32 score above the global average and 18 have improved their score since 2019.

As a global economic and cultural centre, the region boasts some of the highest scores for cultural and non-leisure resources, travel to which is bolstered by, on average, a high degree of international openness and quality infrastructure, including the best ground and tourist service infrastructure. Operating in the region is also made easier by leading ICT and healthcare infrastructure and favourable business, security, human resource and labour markets, and socioeconomic conditions. Advantages in many of these categories are especially concentrated in the more economically developed Western, Southern and Northern Europe subregions. Moreover, the region’s international openness is based around members of the European Union and Schengen Area (the 26 European countries that have abolished passport control etc. on their mutual borders).

Countries in the Eurasia and Balkans and Eastern Europe subregions tend to be more price- competitive compared to their expensive western neighbours, while more tourism-dependent southern European states stand out for their prioritization of T&T, tourism infrastructure and natural resources. Overall, European economies do better than most in environmental sustainability, but they often have more limited natural resources, resulting in some of the lower marks for the T&T Demand Pressure and Impact pillar, which includes signs of unsustainable demand such as high rates of seasonality and shorter visitor stays.

Spain ranks highest in the region (3rd). However, France (4th), Germany (5th), Switzerland (6th), the United Kingdom (8th) and Italy (10th) all rank among the top 10 on the index. In 2020, Croatia (46th) and Albania (72nd) were most dependent on T&T for GDP, while Germany has the largest T&T economy.

Middle East and North Africa

While the MENA region underperforms the global TTDI average, results vary greatly based on the subregion and economic level of development. Overall, the region scores above average in eight pillars, with half of the dozen economies covered by the index scoring above average.

MENA’s high-income economies, all of which are based in the Middle East subregion, are typically defined by top-notch air transport, a significant presence of non-leisure resources such as major corporations, and overall favourable enabling environments, including business and human resource and labour markets and good ICT-readiness. On the other hand, North African economies, all of which are lower-middle- income, have gaps in air, tourist, health and ICT infrastructure and access to qualified labour. Yet they lead the region in price competitiveness and tend to prioritize and devote relatively more resources to T&T. To further develop their T&T sector, many MENA countries need to increase their international openness, invest more in ground services and tourist infrastructure and focus on promoting and establishing cultural and, in particular, natural attractions. The latter task will be hard to achieve without improving the region’s challenging environmental sustainability situation. Moreover, the region can significantly improve its skilled labour availability and resilience by addressing socioeconomic issues such as lagging social protection coverage, youth employment and training, workers’ rights and opportunities for women and minority groups.

The United Arab Emirates (25th) is the best TTDI performer in the region. However, since 2019, Saudi Arabia , which has the largest T&T economy in the region, has had the biggest leap in the rankings (+2.3%, 43rd to 33rd), while Egypt has had the second greatest percentage improvement (+4.3%, 57th to 51st) in the entire index. The United Arab Emirates is top scorer in the Middle East subregion, while Egypt is the top scorer in North Africa. In 2020, Qatar (43rd) and Tunisia (80th) were most dependent on T&T for GDP.

Sub-Saharan Africa

Sub-Saharan Africa (Africa) has had the greatest improvement in TTDI performance since 2019, with 17 out of the 21 regional countries covered by the index increasing their TTDI scores. Nevertheless, the region still lags behind other regions, undermining its great potential as a T&T economy.

Africa’s opportunity for tourism lies in several factors, not least of which are its price competitiveness and potential for nature tourism. However, several obstacles undermine T&T in the region. Government support for the sector could be improved via better data collection and marketing. In particular, nature tourism can be bolstered by higher-quality online promotion and increased focus on environmental sustainability. Additionally, travel to and within the region is hampered by underdeveloped infrastructure and limited international openness. Visitors might also be concerned by the region’s, on average, low health, hygiene, safety and security conditions. Lastly, unfavourable business, human resource and labour markets, and socioeconomic conditions all make T&T operations less viable.

Nevertheless, as already mentioned, many economies in the region are bridging these gaps. For instance, hard transport infrastructure continues to improve as indicated by the more positive perceptions of roads, railways and airports. Additionally, the region’s travel market is bound to benefit from improving international openness, which is bolstered by increasing intra-regional trade integration efforts such as the African Continental Free Trade Area. Africa also had the index’s fastest improvement in ICT readiness, making it easier to provide digital T&T services.

Mauritius (62nd) ranks the highest in the region. However, South Africa (68th) is the largest T&T economy in Africa. Meanwhile, Benin had the greatest improvement in TTDI score (+4.0%, 106th to 103rd) and Tanzania the greatest improvement in ranking (+2.6%, 86th to 81st). The top scorers in Eastern, Southern and Western Africa are Mauritius, South Africa and Cape Verde (82nd), respectively. The latter was also the most dependent of T&T for GDP in 2020.

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Travel & Tourism Development Index 2021: Rebuilding for a Sustainable and Resilient Future

5. Regional results

The Americas

Asia-Pacific

Europe and Eurasia

Middle East and North Africa

Sub-Saharan Africa

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