Using Big Data to measure tourist sustainability: myth or reality?

sustainability Review Using Big Data to Measure Tourist Sustainability: Myth or Reality? YamiléPérez Guilarte 1,* and Daniel Barreiro Quintáns 2 1Institute for Studies and Development of Galicia, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain 2Department of Geography, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain; d.barreir[email protected] *Correspondence: yamile.per[email protected] Received: 25 July 2019; Accepted: 10 October 2019; Published: 13 October 2019   Abstract: The concern about the production of international standards to measure the sustainability of tourism is present today, especially the discourse on the introduction of new sources. This article aims to survey and describe the main approaches and methodologies to use big data to measure tourism sustainability. Successful cases are addressed by explaining the main opportunities and challenges for the creation of official tourist statistics. A comprehensive review of publications regarding this field was carried out by applying the systematic literature review technique. This contributes a knowledge base to destination management organisations to encourage the implementation of official tourism statistics systems using big data. Keywords: big data; tourism sustainability; official statistics; indicators 1. Introduction Sustainability constitutes a key element in the tourism industry’s competitiveness, as destinations are appreciated according to the quality of their environment, including the local communities’ attitudes. For tourist historic cities, this is a real challenge considering that the flows of visitors are continuously growing [ 1 ]. As a result, some destinations or significant tourist attractions suffer from overtourism, which not only makes the resident’s quality of life worse, but also the visitors’ experience. In order to prevent such conditions in historic cities, tourism practices should follow integral sustainable models, instead of only guaranteeing heritage protection [2]. Today, in the discussion about the role of natural and social resources to increase economic benefits, sustainable development and sustainability are fundamental [ 3 ]. In this context, various initiatives have emerged at different territorial scales to establish systems to measure tourism sustainability. However, there is not an international and generally accepted statistical framework, including social and environmental dimensions for the measurement of tourism sustainability [ 4 ]. The initiative, “Measuring Sustainable Tourism (MST)”, is currently under development by the United Nations World Tourism Organisation (UNWTO) with the aim of publishing a global procedure to measure tourism’s effect on sustainability. It asks for a framework based not on the use of traditional data sources, but capable of using and integrating all possible sources to provide the richest picture possible. In this context, new sources have emerged from the use of big data technologies in the tourism sector, with real potentialities to improve the relevance and quality standards of official statistics [ 5 ]. Some examples of these new data sources include: store cashiers, mobile network operators, social media, web activity, flight reservation systems, smart mobile devices, financial transactions, traffic loops, satellite images, Wikimedia content and image collections, among others [6]. Sustainability 2019,11, 5641; doi:10.3390/su11205641 www.mdpi.com/journal/sustainability Sustainability 2019,11, 5641 2 of 19 Most tourist applications have focused on recommender systems, which are software-based tools to personalise tourist products based on visitors’ interests. This is to propose the model experience according to the visitors’ desires [ 7 ]. However, the exploitation potential to support destination management organisation’s strategic decisions has only received little consideration [ 8 , 9 ]. The application of big data technologies to tourism planning and managing is complex as it requires technological expertise [ 10 ]. Nevertheless, this is not the only factor determining its application. Important and coordinated efforts have to be made by statistical authorities and data providers to obtain results with the quality standards actually achieved by current official statistics [ 5 ]. Furthermore, for the integration of private and public stakeholders, the organisational learning processes are fundamental, allowing them to define their specific knowledge requirements [11,12]. From the above-mentioned, two gaps can be identified: On the one hand, the lack of an up-to-date international and generally accepted statistical framework to measure tourist sustainability; on the other, the underexploited application of big data by official statistical agencies. Therefore, this study considers two hypotheses: (1) Official tourism statistical systems are not including specific indicators to measure tourist sustainability (economic, social, environmental) because of the absence of practical guidelines and tools; (2) they are still generally based on the use of traditional sources, especially due to the lack of collaboration among tourism authorities, data providers, big data experts and academia. This article aims to survey and describe the approaches and methodologies for big data to generate official tourism statistics that support destination management organisations. A special focus is placed on measuring social, economic, and environmental sustainability. The research sets out to study to the extent to which big data potentialities are exploited in the generation of official tourism statistics, as well as in the design of tourist intelligence information systems. According to the authors’ knowledge, this is the first systematic review of literature in the field of hospitality and tourism that focuses on the use of big data in official tourism statistics. The management of the main opportunities and challenges addressed in this study could encourage destination manager organisations to use it to optimise competitiveness and sustainability, especially in tourist historic cities. 2. Literature Background 2.1. Measuring Tourism Sustainability Sustainability applied to tourism refers to a type of tourism that satisfies the current public’s necessities without risking the possibility of future generations satisfying their own needs [ 13 ]. For the European Association of Historic Cities and Regions, sustainability encompasses social, environmental and economic issues, and in the case of cultural tourism, this means taking into account each of the components through [14]: •Visitors: Their requirements, desires and comfort; • Industry: The obligation for tourist companies to achieve profitability and a long-standing future; • Community: Being respectful towards local communities in matters such as values, necessities or quality of life; • Environment: The need to preserve physical and cultural environments, local traditions and a sense of place. Sustainable tourism has been included in the agenda of some of the most important global institutions in the sector. This is the case of the Global Sustainable Tourism Council (GSTC) ( https://www.gstcouncil.org/ ). It started in 2007 as a partnership among international institutions to promote knowledge on tourist sustainability and to agree on common rules for sustainable tourism, and became an organisation in 2010 supported by the United Nations Environment Programme, United Nations Foundation and the United Nations World Tourism Organisation (UNWTO). The latter, launched the Guide, “Indicators of Sustainable Development for Tourist Destinations”, intended to use indicators as a main tool to optimise tourism planning and management [ 13 ]. However, Sustainability 2019,11, 5641 3 of 19 since its release in 2004, new formulas have emerged to support local authorities to guarantee the destination’s sustainability. Furthermore,in2015,allmembersoftheUnitedNationsadoptedtheSustainableDevelopmentGoals (SDGs). Thisconstitutesasetof17goalstoencouragesustainabilityata globallevelbysettingtargetstobe fulfilled by 2030 in issues such as the environment, health, poverty, social rights, innovationand education (https://www.un.org/sustainabledevelopment/sustainable-development-goals/). In addition, in 2017, the International Year of Sustainable Tourism for Development was nominated by the 70th General Assembly of the United Nations. In this favorable context, multiple initiatives have emerged. A relevant example is the UNWTO International Network of Sustainable Tourism Observatories (INSTO). It is a network of tourism observatories that, through the regular use of monitoring, assessment and information administration, provide significant instruments to support the design and application of policies on sustainable tourism [15]. In Europe, several initiatives have been promoted by the European Commission, the European Environment Agency, or the Council of Europe among other organisations. In 2010, a group of actions included in the communication, “Europe, the World’s No. 1 Tourist Destination—A New Political Framework for Tourism in Europe”, were launched to encourage sustainable tourism in Europe and promote competitiveness and visibility on a global scale [ 16 ]. The European Tourism Indicator System for sustainable management at a destination level (ETIS) is one of these actions. It was initiated in 2013 by the European Commission as an easy and useful toolkit for tourism stakeholders to improve sustainable tourism management. The ETIS results are supported by self-assessment, observation, data gathering and analysis, which allow the destinations to collect the necessary information to supervise sustainability and effectively manage tourism activities. The ETIS includes 43 indicators that have been divided into four categories: destination management, social and cultural impact, economic value and environmental impact. The ETIS tries to respond to the need to protect and enhance cultural heritage, local identity and resources to avoid the phenomenon of banalisation and the residents’ discontent [3]. It is also worth mentioning the Barcelona Declaration, “Better Places to Live, Better Places to Visit” launched in April 2018 aiming to deliver a legacy for Europe beyond the 2018 European Year of Cultural Heritage (EYCH 2018). This was an action initiated by the Network of European Regions for Sustainable and Competitive Tourism (NECSTouR), in collaboration with the European Cultural Tourism Network, the European Travel Commission and Europa Nostra, and supported by the European Heritage Alliance 3.3. Its main objective is to show the synergies between tourism and cultural heritage to benefit European citizens, cultural heritage, companies, visitors and destinations. In addition, it parts from assuming a collective responsibility of all involved sectors to achieve SDGs. Principle 4 “Balancing Place, People and Business” of the Declaration clearly mentions the need for efficient tools to measure tourism impacts [17]. The need to introduce new tools to measure tourism sustainability is present in several projects and actions that have been implemented worldwide. For example, the project “Models of Integrated Tourism in the MEDiterranean Plus (MITOMED+)” (https://mitomed-plus.interreg-med.eu/) financed by the Interreg Mediterranean Programme, focuses on public policies for the sustainable development of maritime and coastal tourism. It develops evaluation and planning tools to help tourist destinations to improve their sustainability levels. In Asia, for instance, some projects have been developed through the involvement of small and medium-sized enterprises (SMEs) as part of the SWITCH-Asia programme ( https://www.switch-asia.eu/ ). This initiative is based on the possibilities SMEs can offer in terms of innovation management, uniqueness of services, and practical solutions in the implementation of sustainable measures in the tourism industry [ 18 ]. In Latin America, or more specifically in Honduras, Bolivia, Peru, M é xico and Costa Rica, some projects are responsible for improving the locals’ quality of life, including indigenous communities from the development of sustainable tourism both in urban and rural areas [ 19 ]. It is also worth mentioning some initiatives in Sustainability 2019,11, 5641 4 of 19 African countries such as Kenya, Zimbabwe, Egypt, Burkina Faso, South Africa and Mozambique (https://sustainabletourism.net/case-studies/austrailianz/africa/). These actions focus on eco-efficient accommodation, ecotourism, wildlife tourism regulations, instruments for economic development, and initiatives to preserve the communities’ culture and the environment. Several studies have been carried out worldwide to assess the importance of sustainable tourism in the promotion of well-being and local development due to the use of indicators [ 20 – 22 ]. Indeed, the indicators to monitor tourist sustainability have been accepted as valid tools for: (1) The assessment of policies and the monitorisation of destination performances [ 23 – 25 ]; (2) the definition of development plans and establishment of quantitative objectives [ 26 – 29 ]; (3) easy communication to destination stakeholders about the present situation and upcoming scenarios [ 30 ]. In more exact terms, the problems regarding the practical application of sustainability are understood by all stakeholders, including policymakers, local communities, entrepreneurs, Non-Governmental Organisations (NGOs), and visitors. Hence, it still remains a challenging concept [3]. The need to measure both the performance of tourism and its impacts has led the tourism sector to focus, for the past 15 years, on the sustainability indicator-based case studies [ 28 ]. However, some issues make it difficult to implement actions to measure and manage tourism, thus creating a gap [ 31 – 33 ]. The handling of the large number of indicators that are generally included in measuring tourism impacts, the data availability at a local level, and the incomplete quantification of indicators are some of the difficulties [ 26 , 28 , 34 ]. In addition, there are a few studies especially oriented to the use of sustainable tourism indicators at heritage destinations [26,35]. The discussion on the synergies between science and policy in choosing a set of indicators to properly monitor sustainability [ 34 , 35 ] expresses the relevance of incorporating both scientific principles and participatory planning processes [ 36 – 40 ]. Therefore, this is a political as well as a technical choice that must focus on establishing significant indicators to assess sustainability in the social, economic and environmental dimensions [41–43]. In addition, there are recurring criticisms which sustain that academics and public organisations have manifested great enthusiasm towards sustainable tourism, but without achieving any major results. [ 36 ]. While academia is criticised for concentrating their efforts on the production of literature instead of the production of practical tools, public agencies are accused of misusing the concept to justify tourism development. In spite of these criticisms, there is a recognition of the need to move towards a more sustainable horizon, as well as the important role that the business sector will play in its effective implementation [18,37,38]. The concern about the production of practical international standards to measure the sustainability of tourism activity is very present today. The UNWTO has been working on a draft framework through the initiative “Measuring Sustainable Tourism” (MST). It was presented at the 6th International Conference on Tourism Statistics held in Manila in June 2017. The Secretary-General of the UNWTO expressed the relevance of the MST initiative as a framework of meaningful and feasible indicators for a real contribution of tourism to SDGs, the 2030 Development Agenda, and a new era of sustainable and inclusive development. It also highlighted the need to collect more data sources, developing clear and unified concepts, and building technical capacity. More precisely, in the conference Session 5, “Producing Data on Sustainable Tourism”, the potential to use various data sources, particularly big data, for the measurement of sustainable tourism was addressed. It was concluded that it is essential that statisticians find opportunities to access and utilise new data sources to improve and extend current tourism datasets [4]. 2.2. Big Data: A New Source for Official Tourist Statistics Big data can be defined as a set of data collected from various sources with diverse formats, including texts, images, voices or rasters. They may be extracted from Instagram, Facebook, Twitter, blogs, videos and voice recordings, and also, from communication systems, business databases and sensors. Apart from the large volume of information, there are other features that characterise big data. Sustainability 2019,11, 5641 5 of 19 The five main properties of big data are well-known as the 5V: variety, velocity, volume, veracity and value [39]. In exact terms, the report “Tourism Statistics: Early Adopters of Big Data?” states that big data in a gradual but persistent manner will partially take the place of traditional sources or surveys [ 6 ]. It also highlights the relevant role tourism statisticians should have in rethinking the statistics systems through the integration of big data. It allows the measurement of not only an individual’s physical movements, but also monetary transactions, thereby becoming an indispensable tool for designing, implementing and disseminating innovation systems within the field of tourism. Figure 1shows the most generally considered sources of big data. As in other categorisations, some elements may be subjectively identified within different groups. For example, publications on social networks can be classified either as communication systems or world wide web, while Wikipedia can be considered web-based and crowd sourced at the same time [6]. Sustainability 2019, 11, x FOR PEER REVIEW 5 of 20 It also highlights the relevant role tourism statisticians should have in rethinking the statistics systems through the integration of big data. It allows the measurement of not only an individual’s physical movements, but also monetary transactions, thereby becoming an indispensable tool for designing, implementing and disseminating innovation systems within the field of tourism. Figure 1 shows the most generally considered sources of big data. As in other categorisations, some elements may be subjectively identified within different groups. For example, publications on social networks can be classified either as communication systems or world wide web, while Wikipedia can be considered web-based and crowd sourced at the same time [6]. Figure 1. Sources of big data [6]. Recently, the amount of available public data has increased exponentially due to: The implementation of open data initiatives worldwide by public sectors; the popularisation of collaborative tools, such as Open Street Maps or social networks like Twitter or Instagram, that provide data generated by users without the need of governmental or central institutions; and also the broad usage or tools like TripAdvisor or Booking.com. Accordingly, this circumstance represents a new paradigm of communication and knowledge sharing between citizens, companies and public institutions. However, they are not being fully exploited [9]. As part of the current data revolution, the concept of a smart tourism destination has gained relevance. It has been defined as the product of the interconnection between a tourist destination and the various stakeholders through dynamic platforms and knowledge-intensive communication flows, as well as with improved support systems for decision-making [40–43]. The final purpose of an intelligent tourist destination must be the improvement of the tourist experience, the maximisation of competitiveness and consumer satisfaction based on sustainability [44]. However, although sustainability is supposed to be a fundamental pillar in the smart tourism destinations or smart cities approaches, the models integrating smartness and sustainability are still dealing with some gaps [45–50]. The situation is particularly acute in tourist destinations, because reaching sustainability is, in general, an unsolved issue which still lacks practical actions [51]. In this context, and in order to reinforce the sustainable dimension, terms such smart sustainability [51] and smart sustainable cities have emerged [48]. Smart sustainability is based on a governance framework that applies technology to five fundamental pillars [51]: i) long-term planning, the efficient management of resources; ii) monitoring, transparency and participation, public-private cooperation, knowledge, innovation; iii) communication, iv) awareness raising; v) the improvement of the tourist experience. The intensive use of technology by smart tourism destinations plays a key role through the potential interactions that may arise between the technologies and the basic elements of sustainability, which could accelerate the process of achieving it. Nevertheless, the relevant modifications in the business sector at different territorial scales are required to exploit the potential of information technologies to Figure 1. Sources of big data [6]. Recently, the amount of available public data has increased exponentially due to: The implementation of open data initiatives worldwide by public sectors; the popularisation of collaborative tools, such as Open Street Maps or social networks like Twitter or Instagram, that provide data generated by users without the need of governmental or central institutions; and also the broad usage or tools like TripAdvisor or Booking.com. Accordingly, this circumstance represents a new paradigm of communication and knowledge sharing between citizens, companies and public institutions. However, they are not being fully exploited [9]. As part of the current data revolution, the concept of a smart tourism destination has gained relevance. It has been defined as the product of the interconnection between a tourist destination and the various stakeholders through dynamic platforms and knowledge-intensive communication flows, as well as with improved support systems for decision-making [ 40 – 43 ]. The final purpose of an intelligent tourist destination must be the improvement of the tourist experience, the maximisation of competitiveness and consumer satisfaction based on sustainability [44]. However, although sustainability is supposed to be a fundamental pillar in the smart tourism destinations or smart cities approaches, the models integrating smartness and sustainability are still dealing with some gaps [ 45 – 50 ]. The situation is particularly acute in tourist destinations, because reaching sustainability is, in general, an unsolved issue which still lacks practical actions [ 51 ]. In this context, and in order to reinforce the sustainable dimension, terms such smart sustainability [ 51 ] and smart sustainable cities have emerged [48]. Smart sustainability is based on a governance framework that applies technology to five fundamental pillars [ 51 ]: (i) long-term planning, the efficient management of resources; (ii) monitoring, transparency and participation, public-private cooperation, knowledge, innovation; Sustainability 2019,11, 5641 6 of 19 (iii) communication, (iv) awareness raising; (v) the improvement of the tourist experience. The intensive use of technology by smart tourism destinations plays a key role through the potential interactions that may arise between the technologies and the basic elements of sustainability, which could accelerate the process of achieving it. Nevertheless, the relevant modifications in the business sector at different territorial scales are required to exploit the potential of information technologies to support sustainable tourism, as well as more innovative models developed by tourism academics and solid interactions with public authorities in tourism [52]. Big data includes, on one hand information collected from the sensorisation of the destination from different subsystems, such as those to monitor water consumption, waste volume, energy usage, urban mobility, etc. On the other hand, it encompasses new and relevant data sources to support sustainable tourist models. This is the case of the information regarding the spatial and temporal concentration of visitors compiled from online booking [ 53 ] or from social networks [ 54 ]. A deep understanding of visitors’ movements at the destination and the factors influencing them allows tourism managers to solve or prevent overcrowding situations that affect the tourist’s experience and the residents’ quality of life, particularly in historic centres. As part of the expansion of the use of big data in the tourism sector, different applications have arisen, such as destination management systems (DMS) or tourist information systems (TIS), which integrate relevant statistical data collected from traditional sources or big data. They cover the demand side, as for example: the visitor’s profile, behaviour and opinions, the supply side (expenditure, overnight stay, seasonality), and the residents’ perspective (satisfaction, involvement). The data can be accessed through platforms, which generally allows for the easy visualisation and understanding of the information, chart data, keyword graphs, trend charts, tag cloud, etc. Furthermore, if the DMS or TIS incorporates the data about environmental indicators, they will contribute not only towards reaching economic and social sustainability of the destination, but also environmental [ 55 , 56 ]. Unfortunately, this integration is too far in the future to be in widespread use at this time [51]. The use of intelligent systems in tourism is widely used as a support for destination management. For example, in Spain, the State Society for the Management of Innovation and Tourism Technologies, A. S. (SEGITTUR, by its Spanish acronym) is leading initiatives to use the latest technologies (big data and business intelligence) to measure and analyse the real behaviour of the consumption of the city by its visitors and tourists. This is the case of the Tourism Intelligence System (SIT, by its Spanish acronym), a technological platform based on the exhaustive analysis of different sources of information selected according to the needs and idiosyncrasies of the territory and the priorities that are marked by its managers. The system has been implemented in the cities of Las Palmas de Gran Canarias, Palma de Mallorca, and Badajoz. In the latter, the system is shared with the city of Elvas (Portugal) framed in a project financed by the European program of Cross-Border Cooperation Spain-Portugal (POCTEP) [ 57 ]. The Tourist Intelligence System of Buenos Aires (https://turismo.buenosaires.gob.ar/es/ observatorio) also exploits big data to generate information about the visitors’ volume, origin, stay, expense, booking preferences, as well as the data from the accommodation industry and aviation connection competitiveness. It also provides information about the visitors’ movements in the city by neighbourhood, day and even by hours. This indicator is significant enough to ensure the social and environmental sustainability of the destination. As overcrowded areas and tourist attractions can be identified, the adoption of measures to ensure a quality tourist experience and the preservation of the local environment and communities can be adopted in real time. Sustainable tourism can benefit from the application of technologies on at least three levels. At a destination level, they provide stakeholders with a global understanding of the tourist phenomenon and its economic, social and environmental impacts, which can encourage them to adopt a responsible and proactive attitude towards sustainable goals [ 58 ]. At the visitors’ level, as they can access these platforms, be informed about the sustainability levels of the destination, and as a prosumer, they can choose one place or another to travel, while more responsible behaviour at the destination is encouraged. Sustainability 2019,11, 5641 7 of 19 At the local communities’ level, as residents are interviewed, they participate in tourism planning, and as a result, engage in more actions supporting sustainable tourism [51]. 3. Materials and Methods The establishment of a strong theoretical frame was the base to survey and describe approaches and methodologies for using big data in the generation of tourism statistics, with a special focus on measuring sustainability. For this purpose, a comprehensive review of publications regarding this field was carried out by applying the systematic literature review (SLR), widely used in social sciences [ 59 – 62 ]. The SLR allows studies to be weighed against each other in terms of the confidence with which their findings can be accepted, while data integration makes it possible to reach an overall judgement from all studies. Both contribute to the communication between researchers and practitioners. They also reduce the effort required by practitioners and other service decision-makers in finding and evaluating research evidence to make their decisions [59]. According to this research objective, the systematic literature review was oriented to answer the following questions: 1. What are the motives for using big data in tourism statistics? 2. What are the main types of big data used? And why are they the most used? 3. Which actors are involved in studying and applying big data to generate tourism statistics? Are they implementing Tourist Information Systems? 4. Which are the approaches and methodologies to use big data to measure tourism sustainability? In order to locate high-quality studies for the research topic, databases from the Web of Science (WOS) and SCOPUS were examined. The search encompassed different types of publications, such as articles from peer-review journals, books, proceedings or reviews. Furthermore, relevant publications from international organisations such as the World Tourism Organisation, UNESCO or the European Commission related to the use of big data in tourist statistics were consulted. In order to ensure the inclusion of all significant studies needed to give a response to the research questions, several criteria were established. Firstly, both databases were searched using the following keywords: “big data & tourism”, “big data & tourism & sustainability”, “big data & tourism & indicators”, “big data & tourism statistics”. Secondly, papers were selected between the years 1999 and 2019, thus guaranteeing a wide period to observe tendencies and changes. Thirdly, both theoretical and case studies within the social science, arts and humanities fields were included. The process of selection and exclusion of articles is shown in Figure 2. After removing duplicate articles, a total of 180 abstracts were read. However, 108 were excluded because they did not respond to the research objective and questions. Next, the full texts of the remaining 72 selected were read, which allowed a final selection of 10 articles to be analysed, representing only 15% of the 72 full texts. The criteria to select them was the presence of a clear intention to use the information gathered with big data technologies to generate official statistics in tourism or to create tourist information systems to promote sustainable tourism planning. Therefore, the remaining 85% of articles were rejected for not matching this essential condition, which is the main purpose of this research. Most of the refused articles (58%) cover interesting aspects of the application of big data in tourism, but the information is not used to generate official tourist statistics. They deal with understanding the visitors’ profile, opinion and behaviour through user generated content as a tool to study specific issues such as the destination image, tourist movement patterns and preferences, and visitors’ satisfaction [ 9 , 59 – 63 ]. Furthermore, tourist companies’ interests were present in 17% of the papers. They use big data to follow online consumers’ reviews, to predict hotel demands, as well as to co-create new tourist products together with visitors [64–68]. Sustainability 2019,11, 5641 8 of 19 Sustainability 2019, 11, x FOR PEER REVIEW 8 of 20 However, using these databases guaranteed the selection of the ones with the highest research quality. Figure 2. Flowchart of the inclusion and exclusion of studies [62]. Once selected, the studies were evaluated to identify the kinds of theoretical and conceptual contributions and advances made, the array and nature of empirical situations investigated, the methodological approaches adopted, the conclusions and recommendations outlined, and the tools, guidelines and regulations produced in reports. The synthesis was done based on a descriptive approach through registering, tabulating and integrating all of the articles’ contributions. 4. Results and Discussions This section presents the results and discussions of the information gathered from the selected papers. For the integration of the data, the following parameters had previously been defined and extracted from the papers: title, authors, year of publication, journal or editorial, objectives, methodology (research technique, setting, type of data and source, tools for collection processing and visualising data), sustainability approach, stakeholders involved, big data opportunities and challenges. 4.1. Publications on Tourism Statistics and Sustainability: General Remarks Table 1 shows the list of the selected publications that were analysed in depth in order to identify the approaches and methodologies to use big data to generate tourism statistics, especially indicators that measure tourism sustainability. The selection includes 8 articles from journals, Tourism Management being the only journal with 2 articles [63,64]. Furthermore, a chapter of a book [65] and a report based on a keynote prepared by EUROSTAT were included [6]. Figure 2. Flowchart of the inclusion and exclusion of studies [62]. In addition, four papers (6%) related to the development of methodologies to measure tourism sustainability were identified [ 69 – 72 ]. However, they were not included because they did not consider big data as a source to measure tourism sustainability. Finally, three theoretical works (4%) were not included either, as they had a general approach on the use of big data in tourism [ 73 , 74 ] or addressed a different perspective in relation to this research [ 75 ]. In terms of research bias, there is one issue that should be taken into account. Some publications related to the research topic could have been left out of the literature review, because they are not included in Scopus or Web of Science. However, using these databases guaranteed the selection of the ones with the highest research quality. Once selected, the studies were evaluated to identify the kinds of theoretical and conceptual contributions and advances made, the array and nature of empirical situations investigated, the methodological approaches adopted, the conclusions and recommendations outlined, and the tools, guidelines and regulations produced in reports. The synthesis was done based on a descriptive approach through registering, tabulating and integrating all of the articles’ contributions. 4. Results and Discussions This section presents the results and discussions of the information gathered from the selected papers. For the integration of the data, the following parameters had previously been defined and extracted from the papers: title, authors, year of publication, journal or editorial, objectives, methodology (research technique, setting, type of data and source, tools for collection processing and visualising data), sustainability approach, stakeholders involved, big data opportunities and challenges. 4.1. Publications on Tourism Statistics and Sustainability: General Remarks Table 1shows the list of the selected publications that were analysed in depth in order to identify the approaches and methodologies to use big data to generate tourism statistics, especially indicators that measure tourism sustainability. The selection includes 8 articles from journals, Tourism Management Sustainability 2019,11, 5641 9 of 19 being the only journal with 2 articles [ 63 , 64 ]. Furthermore, a chapter of a book [ 65 ] and a report based on a keynote prepared by EUROSTAT were included [6]. Table 1. List of publications on tourism statistics and sustainability. Authors and Years of Publication Title Journal or Editorial Fuchs, Höpken and Lexhagen (2014) Bigdata analytics for knowledge generation in tourism destinations—A case from Sweden Journal of Destination Marketing & Management Raun, Ahas, and Tiru (2016) Measuring tourism destinations using mobile tracking data Tourism Management Cortina, Izquierdo, Prado and Velasco (2016) Quality implications of the use of big data in tourism statistics: three exploratory examples European Conference on Quality in Official Statistics Miah, Huy, Gammack and McGrath (2017) A Big Data Analytics Method for Tourist Behaviour Analysis Information & Management Peng and Huang (2017) A Novel Popular Tourist Attraction Discovering Approach Based on Geo-Tagged Social Media Big Data ISPRS International Journal of Geo-Information Scharl, Lalicic and Onder (2017) Tourism Intelligence and Visual Media Analytics for Destination Management Organizations Springer Demunter (2017) Tourism statistics: Early adopters of big data? Publications Office of the European Union Donovan, Flaherty and Healy (2017) Using big data from Wikipedia page views for official tourism statistics Statistical Journal of the IAOS Batista e Silva, Herrera, Rosina, Barranco, Freire and Schiavina (2018) Analysing spatiotemporal patterns of tourism in Europe at high-resolution with conventional and big data sources Tourism Management Del Vecchio, Mele, Ndou and Secundo (2018) Open Innovation and Social Big Data for Sustainability: Evidence from the Tourism Industry Sustainability In relation to the research objectives, all papers are oriented to the use of big data technologies to develop tools and methods to support strategic decision-making in tourism destination management. In particular, the incorporation of big data to official tourism statistical systems was addressed in four papers [ 5 , 6 , 12 , 53 ]. They all highlighted the potential relevance of big data in gathering tourism statistics, as well as its opportunities and challenges, which is further discussed in the following sections. In spite of the fact that the research period was set in the last 10 years, between 1999 and 2019, the first publication addressing the subject of interest of this paper was published in 2014 [ 11 ]. As shown in Figure 3, in 2017 and 2018 the number of papers increased, totalling 70% of the total papers. This is a result of the growing recognition of big data as a complementary source for the generation of official tourism statistics [ 5 , 12 ]. However, if compared with the rest of articles being published on the use of big data in the tourism sector, the number of papers on this particular topic still remains low, as explained above. Sustainability 2019,11, 5641 16 of 19 have been developed within the academic environment [ 11 , 65 ], however an example of transference to the business world could be appreciated [65]. The measurement of sustainable tourism is perhaps one of the most under researched subjects in tourism statistics, because it lacks the practical tools to guide the implementation and systematicity. Nevertheless, big data can cover this gap by proposing indicators, especially those contributing with geographical and temporal granularity, as used by Batista et al. [ 53 ] and Cortina et al. [ 5 ]. Apart from this, some interesting initiatives, such as the ones developed by WebLyzard Technology, are examples of the potentialities of social and news media to encourage integral sustainable practices and open innovation [ 9 ]. These cases prove that integration among indicators to measure tourist sustainability and big data really is possible, it is not a myth, and it also shows its potential to destination management organisations. Unfortunately, this is not expansive enough. For this reason, future research should be oriented towards creating mechanisms to coordinate tourism authorities with data providers, data experts, academia and business communities. On the condition that all these actors understand and believe in big data as a complementary data source, they will be able to face the challenges and build official tourist statistics. Author Contributions: Introduction, Y.P.G.; literature review, Y.P.G.; materials and methods, Y.P.G. and D.B.Q.; results and discussions, Y.P.G. and D.B.Q.; conclusions, Y.P.G.; references, Y.P.G. and D.B.Q. Funding: This research was funded by the Xunta de Galicia and the European Union (European Social Fund—FSE) through predoctoral stage grants to universties and public research organisations in Galicia and other organisations of the Galician R+D+I System (2017), grant number ED481A-2017/230. Conflicts of Interest: The authors declare no conflicts of interest. References 1. Timothy, D.J. Cultural Heritage and Tourism: An Introduction; Channel View Publications: Bristol, UK, 2011; ISBN 978-1-84541-178-7. 2. Cohen-Hattab, K. Public involvement and tourism planning in a historic city: The case of the Old City of Jerusalem. J. Herit. Tour. 2013,8, 320–336. [CrossRef] 3. European Commission European Tourism Indicators System for Sustainable Destination Management. ETIS Toolkit for Sustainable Destination Management. Available online: /growth/sectors/tourism/offer/ sustainable/indicators_en (accessed on 29 August 2018). 4. UNWTO. 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