Big data represents an actual field of study both for the agenda of researchers and practitioners. Although it is a common trend for all industries, big data assumes a critical relevance in the information intensive ones, such as tourism (Law et al., 2014; Vargo et al., 2009) where it is assumed as pillar of the smart growth and competitiveness of tourism destinations and companies in the global market (Alcántara-Pilar et al., 2017; Gretzel, Sigala et al., 2015; Fuchs et al., 2014; Jackson, 2016). Big data has the potential for changing the global travel and tourism industries and create significant opportunity for incumbents as well as new entrants. Information Technology (IT) innovations have allowed the growth of multiple online marketplaces, hospitality and accommodation sharing services as Airbnb, TripAdvisor, Online Travel Agencies as Booking.com, and Uber. All these companies get valuable information on big data for managing the interaction with customers by providing the best service to customers in the right time at the right place.
It is in this venue, that the recent debate on smart tourism has attempted to demonstrate the several areas of implications and challenges that big data can offer to the competitiveness of tourism destinations and companies (Jackson, 2016). Characterized by advanced services, high degree of innovation and the presence of open, integrated and shared processes for enhancing the quality of life for both residents and tourists (Presenza et al., 2014), the notion of a smart tourist destination is the result of the interconnection of tourism destinations with multiple stakeholders’ communities through dynamic platforms and knowledge intensive flows of communication and enhanced decision support systems (Buhalis and Amaranggana, 2015; Jovicic, 2017).
Due at the large diffusion of social networks and digital applications, tourism is more and more configurable as an experience (Aarikka-Steroos and Jaakkala, 2012; Lu et al., 2015) resulting from collaboration, co-creation and digitalization (Neuhofer et al., 2013). During their journeys and in their decision-making and communication processes tourists contribute to the creation of a massive flow of data generated by sensors, micro-devices and cameras distributed on the urban and extra-urban areas of interest for tourists. All these data are a promising basis for making smart destinations as well as for enhancing the satisfaction of tourists through a personalized offering of products and services. However, in tourism destinations, these data typically remain unused.
Despite the actuality of the term and its large recurrence in the work of scholars and practitioners, smart tourism remains an ill-defined concept and a field of investigation that calls for closer examination and theorization (Gretzel, Sigala et al., 2015) from a wide range of disciplines and research approaches. Thus, we encourage papers that examine novel phenomena, employ original methodologies, and offer interesting theoretical and empirical contributions to this research theme.
Topics of interest include but are not limited to the following:
- Data-driven decision-making in tourism management
- Challenges and opportunities from big data exploitation
- Smart technologies for the tourism sector
- Digital local experiences and destination competitiveness
- Big data and knowledge management in tourism
- Big data and business model innovation for tourism
- Big data and technology-driven entrepreneurship in tourism
- Big data analytics for extracting value in tourism
- Big data impacts on services co-creation tourism services and products
- Big data for improving the quality of destination services
- Computer-enabled sentimental analysis or content analysis approaches for smart tourism
- Evaluation of guest satisfaction using big data analytics
- Issues of privacy and security in the management of tourist big data
Alcántara-Pilar, J. M., del Barrio-García, S., Crespo-Almendros, E., & Porcu, L. (2017). Toward an understanding of online information processing in e-tourism: does national culture matter?. Journal of Travel & Tourism Marketing, http://dx.doi.org/10.1080/10548408.2017.1326363.
Buhalis, D., & Amaranggana, A. (2015). Smart tourism destinations enhancing tourism experience through personalisation of services. In Information and Communication Technologies in Tourism 2015 (pp. 377-389). Springer, Cham.
Fuchs, M., Höpken, W., & Lexhagen, M. (2014). Big data analytics for knowledge generation in tourism destinations–A case from Sweden. Journal of Destination Marketing & Management, 3(4), 198-209.
Gretzel, U., Sigala, M., Xiang, Z., & Koo, C. (2015). Smart tourism: foundations and developments. Electronic Markets, 25(3), 179-188.
Jackson, S. (2016). Prediction, explanation and big(ger) data: a middle way to measuring and modelling the perceived success of a volunteer tourism sustainability campaign based on ‘nudging’. Current Issues in Tourism, 19, 643-658.
Jovicic, D.Z., (2017). From the traditional understanding of tourism destination to the smart tourism destination. Current Issues in Tourism, http://dx.doi.org/10.1080/13683500.2017.1313203.
Law, R., Buhalis, D., & Cobanoglu, C. (2014). Progress on information and communication technologies in hospitality and tourism. International Journal of Contemporary Hospitality Management, 26(5), 727-750.
Lu, J., Mao, Z., Wang, M., & Hu, L., (2015). Goodbye maps, hello apps? Exploring the influential determinants of travel app adoption. Current Issues in Tourism, 18, 1059-1079.
Presenza, A., Micera, R., Splendiani, S., & Del Chiappa, G. (2014). Stakeholder e-involvement and participatory tourism planning: analysis of an Italian case study. International Journal of Knowledge-Based Development, 5(3), 311-328.
Vargo, S. L., & Akaka, M. A. (2009). Service-dominant logic as a foundation for service science: clarifications. Service Science, 1(1), 32-41.
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