Call for Papers

CfP special issue on "Smart Tourism 2.0: Perspectives with geospatial data and AI"

Submission deadline: October 31, 2024

Guest editors

* Jinwon Kim, University of Florida, USA, jinwonkim(at)
* Seongsoo (Simon) Jang, Cardiff University, UK, jangs(at)
* Ulrike Gretzel, University of Southern California, USA, ugretzel(at)
* Chulmo Koo, Kyung Hee University, South Korea, helmetgu(at)


This special issue seeks to offer comprehensive insights into tourism supply, demand, and markets, through a spatial-temporal-psychological (STP) lens in the digital era. Smart tourism refers to tourism supported by integrated efforts at an ICT-enabled destination (smart destination). It involves the collection, exchange, and processing of data, offering technology-mediated tourism experiences (smart experience), and interconnecting stakeholders in the business ecosystem (smart business) (Gretzel et al., 2015). As tourism involves visitors' spatial movements between places, geospatial technologies (e.g., GPS-equipped smartphones) can gather data about tourists, firms, and their spatial interactions. A clear understanding of the geospatial aspects of smart tourism activities will provide vital insights for destination planning, marketing, and management (Yang et al., 2023). In smart destinations, various actors, such as tourism firms (e.g.,, Airbnb), tourists, and natural or constructed environments engage in immersive interactions, which can be monitored through the use of geospatial technologies, personal digital gadgets, and digital/social networking platforms (e.g., Google, Facebook).

This special issue aims to advance the field of geospatial smart tourism by making new insights and methodological contributions on how and why ICT mediation affects or changes spatio-temporal patterns in smart tourism contexts. As spatial configurations can significantly influence perceptions, decisions, and behaviors (Ebert et al., 2022), we encourage researchers to enhance their understanding of tourism suppliers and buyers by integrating spatio-temporal data from location-aware devices with qualitative and experimental data (Koo et al., 2021; Tilly et al., 2015). Furthermore, researchers can explore the root causes of spatially heterogeneous visitor behaviors by incorporating relevant psychological mechanisms (Jang & Kim, 2022) and conducting experimental studies (Jang et al., 2021), alongside utilizing geospatial data. In addition to established tools like Geographic Information Systems (GIS) and spatial econometrics (Koo et al., 2023), this issue delves into the potential of Geospatial Artificial Intelligence (GeoAI), which refers to spatially explicit AI techniques used for geographic knowledge discovery and beyond (Janowicz et al., 2020). Applications of GeoAI can accelerate the real-world understanding of the smart tourism field by integrating spatio-temporal data with AI techniques (e.g., machine learning & deep learning) to extract valuable geographical insights (Gao, 2021; VoPham et al., 2018). Consequently, both theoretical frameworks and practical applications necessitate novel insights into the spatio-temporal ("where and when"), geo-psychological ("where and why"), and geoAI ("where and so what") approaches within the realm of smart tourism.

Central issues and topics

Please note that all submissions should fall into the scope of Electronic Markets ( Otherwise, they cannot start the review process.

Possible topics of submissions include, but are not limited to:

  • Conceptualizations of tourists' spatio-temporal-psychological dimensions in smart tourism
  • Spatio-temporal tourism service design and implementation
  • Contributions of spatio-temporal service offerings to tourism firms' performance
  • Recommended roles of search engines (e.g., Google), conversational generative AI (e.g., Bard), online travel agency platforms (e.g.,, social networking platforms (e.g., Facebook), and peer-to-peer home rental platforms (e.g., Airbnb) for reducing tourists' search costs
  • Contributions of spatio-temporal-psychological service offerings to tourist outcomes
  • The role of spatio-temporal social networking in enhancing tourist engagement and satisfaction in smart destinations
  • Impacts of government actions during disasters (e.g., earthquakes) or crises (e.g., COVID-19) on tourists' spatio-temporal patterns and behavioral engagement
  • Appropriate instruments to measure and model spatio-temporal tourist engagement
  • Combined use of secondary data (e.g., location and time) and primary data (e.g., survey, experiments) for a better understanding spatio-temporal patterns in smart destinations
  • Improving the interpretability of GeoAI models in spatio-temporal tourist behaviors


Electronic Markets is a Social Science Citation Index (SSCI)-listed journal (IF 8.5 in 2022) in the area of information management and information systems. Submissions should be original, unpublished, and not under consideration at any other journal. Both quantitative and qualitative research methods are welcome, provided the research exhibits strong methodological rigor. Contributions can take the form of conceptual and theoretical development papers, empirical hypothesis testing, position papers, case-based studies, and more. All papers which pass the desk-reject phase will undergo a double-blind peer-review process. Submissions must be made via the journal's submission system ( and comply with the journal's formatting standards. Authors should clearly indicate that their submission is intended for the special issue on Smart Tourism. The preferred average article length is approximately 10,000 words, excluding references. Instructions, templates, and general information are available at If you would like to discuss any aspect of this special issue, you may either contact the guest editors or the Editorial Office.


Smart tourism, geospatial data, spatio-temporality, geo-psychology, GeoAI

Important deadline

* Submission deadline: October 31, 2024


Ebert, T., Mewes, L., Götz, F. M., & Brenner, T. (2022). Effective maps, easily done: visualizing geo-psychological differences using distance weights. Advances in Methods and Practices in Psychological Science, 5(3),

Gao, S. (2021). Geospatial artificial intelligence (GeoAI). New York: Oxford University Press.

Gretzel, U., Sigala, M., Xiang, Z., & Koo, C. (2015). Smart tourism: foundations and developments. Electronic Markets, 25(3), 179-188.

Jang, S., & Kim, J. (2022). Enhancing exercise visitors' behavioral engagement through gamified experiences: A spatial approach. Tourism Management, 93, 104576.

Jang, S., Kim, J., Kim, J., & Kim, S. S. (2021). Spatial and experimental analysis of peer-to-peer accommodation consumption during COVID-19. Journal of Destination Marketing & Management, 20, 100563.

Janowicz, K., Gao, S., McKenzie, G., Hug, Y., & Bhaduri, B. (2020). GeoAI: Spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond. International Journal of Geographical Information Sciences, 34(4), 625-636.

Koo, C., Kim, J., & Alt, R. (2023). Spatial is special: Exploration for spatial approach in smart tourism cities. Information Processing and Management, 60(4), 103401.

Koo, C., Xiang, Z., Gretzel, U., & Sigala, M. (2021). Artificial intelligence (AI) and robotics in travel, hospitality and leisure. Electronic Markets, 31(3), 473-476.

Tilly, R., Fischbach, K., & Schoder, D. (2015). Mineable or messy? Assessing the quality of macro-level tourism information derived from social media. Electronic Markets, 25, 227-241.

VoPham, T., Hart, J. E., Laden, F., & Chiang, Y. Y. (2018). Emerging trends in geospatial aritifical intelligence (geoAI): Potential applications for environmental epidemiology. Environmental Health, 17(1), 1-6.

Yang, Y., Chen, X., Gao, S., Li, Z., Zhang, Z., & Zhao, B. (2023). Embracing geospatial analytical technologies in tourism studies. Information Technology & Tourism, 1-14.