Abstract
Digital transformation and technological advances are causing a radical change in communication structures and in the way information is consumed. With rapid development of computing and the Internet, data is generated, recorded, stored and accumulated on a large scale, making it necessary for economic sectors to act quickly in order to adapt their businesses to the online environment and thus, ensure their own survival. The application of Big Data in tourism enables to transform all this data into useful information, so that companies in the sector can define and optimize their strategies in order to increase their profits. This article performs a comparative bibliometric analysis of the presence and impact of scientific production related to Big Data within the area of tourism research indexed in the WoS and Scopus databases. The aim is to know key aspects such as its growth, correlation, citation, coverage, overlap, dispersion or concentration that will support future researchers when they start their work in this emerging field. From the analysis of the 113 articles selected between the two bases through an advanced search for terms with a time limit set in 2019, it can be concluded that this is a new field of knowledge, which has aroused great interest since 2017, publishing about two thirds of the articles during the period 2017–2019. Although WoS and Scopus differ in general terms in scope and coverage policies, both systems are complementary and not exclusive. In the specific area of Big Data and Tourism Research, Scopus is the base that provides better coverage by collecting a higher number of articles and receiving more citations.
Similar content being viewed by others
References
Álvarez-García, J., Durán-Sánchez, A., Río-Rama, D., De la Cruz, M.: Scientific coverage in community-based tourism: sustainable tourism and strategy for social development. Sustainability 10(4), 1158 (2018a). https://doi.org/10.3390/su10041158
Álvarez-García, J., Durán-Sánchez, A., del Río-Rama, M., García-Vélez, D.: Active ageing: mapping of scientific coverage. Int. J. Env. Res. Publ. Health 15(12), 2727 (2018b). https://doi.org/10.3390/ijerph15122727
Baggio, R. (2016). Big data, business intelligence and tourism: a brief analysis of the literature. Paper presented at the IFITTtalk@Östersund: Big Data & Business Intelligence in the Travel & Tourism Domain, Östersund (SE), 11-12 April.
Bearman, T.C., Kunberger, W.A.: A Study of Coverage Overlap Among Fourteen Major Science and Technology Abstracting and Indexing Services. National Federation of Abstracting and Indexing Services, Philadelphia (1977)
Benavides-Velasco, C.A., Guzmán-Parra, V., Quintana-García, C.: Evolución de la literatura sobre empresa familiar como disciplina científica. Cuadernos de Economía y Dirección de la Empresa 14(2), 78–90 (2011)
Beyer, M.A., Laney, D.: The Importance of ‘Big Data’: a Definition. Stamford, CT, Gartner (2012)
Bollier, D., Firestone, C.M.: The Promise and Peril of Big Data. Aspen Institute, Washington (2010)
Bourne, C.P., Kasson, M.S., North, J.B.: Overlappig Coverage of Bibliography of Agricultura by Fifteen Other Secondary Sources. Goverment Research and Develpment Report, U.S (1969)
Bradford, S.C.: Sources of information on specific subjects. Engineering 137, 85–86 (1934)
Broadus, R.: Toward a definition of “bibliometrics”. Scientometrics 12(5–6), 373–379 (1987)
Cancino, C.A., Merigo, J.M., Torres, J.P., Diaz, D.: A bibliometric analysis of venture capital research. J. Econ. Finan. Adm. Sci. 23(45), 182–195 (2018). https://doi.org/10.1108/JEFAS-01-2018-0016
Chen, M., Mao, S., Liu, Y.: Big data: a survey. Mob. Netw. Appl. 19(2), 171–209 (2014a). https://doi.org/10.1007/s11036-013-0489-0
Chen, M., Mao, S., Zhang, Y., Leung, V.C.M.: Big Data: Related Technologies, Challenges and Future Prospects. Springer, Heidelberg (2014b)
Chou, M.C.: Does tourism development promote economic growth in transition countries? a panel data analysis. Econ. Model. 33, 226–232 (2013). https://doi.org/10.1016/j.econmod.2013.04.024
Choudhury, M.M., Harrigan, P.: CRM to social CRM: the integration of new technologies into customer relationship management. J. Strateg. Mark. 22(2), 149–176 (2014). https://doi.org/10.1080/0965254X.2013.876069
Corral, J.A., Canoves, G.: La investigación turística publicada en revistas turísticas y no turísticas: análisis bibliométrico de la producción de las universidades catalanas. Cuadernos de Turismo 31(1), 55–81 (2013)
Costas, R., Moreno, L., Bordons, M.: Solapamiento y singularidad de MEDLINE, WoS e IME para el análisis de la actividad científica de una región en Ciencias de la Salud. Revista Española de Documentación Científica 31(3), 327–343 (2008)
De Mauro, A., Greco, M., Grimaldi, M.: A formal definition of Big Data based on its essential features. Libr. Rev. 65(3), 122–135 (2016). https://doi.org/10.1108/LR-06-2015-0061
Durán-Sánchez, A., Álvarez-García, J., Río-Rama, D., De la Cruz, M.: Sustainable water resources management: a bibliometric overview. Water 10(9), 1191 (2018). https://doi.org/10.3390/w10091191
Eilat, Y., Einav, L.: Determinants of international tourism: a three-dimensional panel data analysis. Appl. Econ. 36(12), 1315–1327 (2004). https://doi.org/10.1080/000368404000180897
Falk, M.: A dynamic panel data analysis of snow depth and winter tourism. Tour Manag. 31(6), 912–924 (2010). https://doi.org/10.1016/j.tourman.2009.11.010
Frederiksen, L.: Big data. Public Serv. Q. 8(4), 345–349 (2012)
Fuchs, M., Höpken, W., Lexhagen, M.: Big data analytics for knowledge generation in tourism destinations–a case from Sweden. J. Desti. Mark. Manag. 3(4), 198–209 (2014). https://doi.org/10.1016/j.jdmm.2014.08.002
Gandomi, A., Haider, M.: Beyond the hype: big data concepts, methods, and analytics. Int. J. Inf. Manag. 35(2), 137–144 (2015). https://doi.org/10.1016/j.ijinfomgt.2014.10.007
Gluck, M.: A review of journal coverage overlap with an extension to the definition of overlap. J. Am. Soc. Inf. Sci. 41(1), 43–60 (1990). https://doi.org/10.1002/(SICI)1097-4571(199001)41:1%3C43:AID-ASI4%3E3.0.CO;2-P
Hall, M.C., Williams, A.: Tourism and Innovation. Routledge, UK (2008)
Hashem, I.A.T., Yaqoob, I., Anuar, N.B., Mokhtar, S., Gani, A., Khan, S.U.: The rise of “big data” on cloud computing: review and open research issues. Inf. Syst. 47, 98–115 (2015). https://doi.org/10.1016/j.is.2014.07.006
Hirsch, J.E.: An index to quantify and individual’s scientific research output. Proceedings of the National Academy of Sciences. United States America 102(46), 16569–16572 (2005). doi: 10.1073/pnas.0507655102
Hjalager, A.M., Nordin, S.: User-driven innovation in tourism—A review of methodologies. J. Qual. Assur. Hosp. Tour 12(4), 289–315 (2011). https://doi.org/10.1080/1528008X.2011.541837
Irudeen, R., Samaraweera, S.: Big data solution for Sri Lankan development: a case study from travel and tourism. In: 2013 international conference on advances in ICT for emerging regions (ICTer) (pp. 207–216). IEEE (2013).
Kambatla, K., Kollias, G., Kumar, V., Grama, A.: Trends in big data analytics. J. Parallel. Distrib. Comput. 74(7), 2561–2573 (2014). https://doi.org/10.1016/j.jpdc.2014.01.003
Keum, K.: Tourism flows and trade theory: a panel data analysis with the gravity model. Ann. Reg. Sci. 44(3), 541–557 (2010). https://doi.org/10.1007/s00168-008-0275-2
Kitchin, R.: Big data and human geography: opportunities, challenges and risks. Dialog. Hum. Geogr. 3(3), 262–267 (2013). https://doi.org/10.1177/2043820613513388
Koo, C., Gretzel, U., Hunter, W.C., Chung, N.: The role of IT in tourism. Asia Pac. J. Inf. Syst. 25(1), 99–104 (2015). https://doi.org/10.14329/apjis.2015.25.1.099
Laney, D.: 3D data management: controlling data volume, velocity and variety. META Group Res. Note 6, 70 (2001)
Li, X., Pan, B., Law, R., Huang, X.: Forecasting tourism demand with composite search index. Tour Manag. 59, 57–66 (2017). https://doi.org/10.1016/j.tourman.2016.07.005
Li, J., Xu, L., Tang, L., Wang, S., Li, L.: Big data in tourism research: a literature review. Tour Manag. 68, 301–323 (2018). https://doi.org/10.1016/j.tourman.2018.03.009
Lotka, A.J.: The frequency distribution of scientific productivity. J. Wash. Acad. Sci. 16(12), 317–323 (1926)
Mariani, M., Baggio, R., Fuchs, M., Höepken, W.: Business intelligence and big data in hospitality and tourism: a systematic literature review. Int. J. Contemp. Hosp. Manag. 30(12), 3514–3554 (2018). https://doi.org/10.1108/IJCHM-07-2017-0461
Marine-Roig, E., Clavé, S.A.: Tourism analytics with massive user-generated content: a case study of Barcelona. J. Dest. Mark. Manag. 4(3), 162–172 (2015). https://doi.org/10.1016/j.jdmm.2015.06.004
Martyn, J.: Tests on abstracts journals: coverage overlap and indexing. J. Doc. 23(1), 45–70 (1967)
Martyn, J., Slater, M.: Tests on abstracts journals. J. Doc. 20(4), 212–235 (1964)
Massidda, C., Etzo, I.: The determinants of Italian domestic tourism: a panel data analysis. Tour Manag. 33(3), 603–610 (2012). https://doi.org/10.1016/j.tourman.2011.06.017
Mayer-Schönberger, V., Cukier, K.: Big Data: a Revolution that Will Transform How We Live, Work, and Think. Houghton Mifflin Harcourt, New York (2013)
Meeker, W.Q., Hong, Y.: Reliability meets big data: opportunities and challenges. Qual. Eng. 26(1), 102–116 (2014). https://doi.org/10.1080/08982112.2014.846119
Meho, L.I., Rogers, Y.: Citation counting, citation ranking, and h-index of human-computer interaction researchers: a comparison of Scopus and web of science. J. Am. Soc. Inf. Sci. Technol. 59(11), 1711–1726 (2008). https://doi.org/10.1002/asi.20874
Merigó, J.M., Mas-Tur, A., Roig-Tierno, N., Ribeiro-Soriano, D.: A bibliometric overview of the journal of business research between 1973 and 2014. J. Bus. Res. 68(12), 2645–2653 (2015). https://doi.org/10.1016/j.jbusres.2015.04.006
Meyer, D.E., Mehlman, D.W., Reeves, E.S., Origoni, R.B., Evans, D., Sellers, D.W.: Comparison study of overlap among 21 scientific databases in searching pesticide information. Online Rev. 7(1), 33–43 (1983)
Miah, S.J., Vu, H.Q., Gammack, J., McGrath, M.: A big data analytics method for tourist behaviour analysis. Inf. Manag. 54(6), 771–785 (2017). https://doi.org/10.1016/j.im.2016.11.011
Mingers, J., Lipitakis, E.: Counting the citations: a comparison of web of science and google scholar in the field of business and management. Scientometrics 85(2), 613–625 (2010). https://doi.org/10.1007/s11192-010-0270-0
Morabito, V.: Big Data and Analytics: Strategic and Organizational Impacts. Springer, US (2015)
Narayan, P.K., Narayan, S., Prasad, A., Prasad, B.C.: Tourism and economic growth: a panel data analysis for Pacific Island countries. Tour Econ. 16(1), 169–183 (2010). https://doi.org/10.5367/000000010790872006
Neuhaus, C., Daniel, H.D.: Data sources for performing citation analysis: an overview. J. Doc. 64(2), 193–210 (2008). https://doi.org/10.1108/00220410810858010
Nicholas, D., Ritchie, M.: Literature and Bibliometrics. Clive Bingley, London (1978)
Norris, M., Oppenheim, C.: Comparing alternatives to the web of science for coverage of the social sciences’ literature. J. Inf. 1(2), 161–169 (2007). https://doi.org/10.1016/j.joi.2006.12.001
Phillips-Wren, G., Hoskisson, A.: An analytical journey towards big data. J. Decis. Syst. 24(1), 87–102 (2015). https://doi.org/10.1080/12460125.2015.994333
Poon, A.: Tourism and information technologies. Ann. Tour Res. 15(4), 531–549 (1988)
Poyer, R.K.: Journal article overlap among index medicus, science citation index, biological abstracts, and chemical abstracts. Bull. Med. Libr. Assoc. 72(4), 353–357 (1984)
Price, D.J.S.: The exponential curve of science. Discovery 17(6), 240–243 (1956)
Pries, K.H., Dunnigan, R.: Big Data Analytics: a Practical Guide for Managers. CRC Press, Boca Raton (2015)
Pulgarín, A., Escalona, M.A.: Medida del solapamiento en tres bases de datos con información sobre Ingeniería. Anales de Documentación 10, 335–344 (2007)
Rowley, J., Slack, F.: Conducting a literature review. Manag. Res. News 27(6), 31–39 (2004)
Rueda, G., Gerdsri, P., Kocaoglu, D.F.: Bibliometrics and social network analysis of the nanotechnology field. In: Portland international conference on management of engineering & technology (PICMET), Portland, USA, July 2007; IEEE; (pp. 2905–2911) (2007).
Shoval, N., Ahas, R.: The use of tracking technologies in tourism research: the first decade. Tour Geogr. 18(5), 587–606 (2016). https://doi.org/10.1080/14616688.2016.1214977
Song, H., Liu, H.: Predicting tourist demand using big data. Analytics in Smart Tourism Design, pp. 13–29. Springer, Cham (2017)
Soukiazis, E., Proença, S.: Tourism as an alternative source of regional growth in Portugal: a panel data analysis at NUTS II and III levels. Port. Econ. J. 7(1), 43–61 (2008). https://doi.org/10.1007/s10258-007-0022-0
Tranfield, D., Denyer, D., Smart, P.: Towards a methodology for developing evidence-informed management knowledge by means of systematic review. Br. J. Manag. 14(3), 207–222 (2003). https://doi.org/10.1111/1467-8551.00375
Verhoef, P.C., Kooge, E., Walk, N.: Creating Value with Big Data Analytics: Making Smarter Marketing Decisions. Routledge, London (2016)
Xiang, Z., Schwartz, Z., Gerdes Jr., J.H., Uysal, M.: What can big data and text analytics tell us about hotel guest experience and satisfaction? Int. J. Hosp. Manag. 44, 120–130 (2015). https://doi.org/10.1016/j.ijhm.2014.10.013
Xiang, Z., Du, Q., Ma, Y., Fan, W.: A comparative analysis of major online review platforms: implications for social media analytics in hospitality and tourism. Tour Manag. 58, 51–65 (2017). https://doi.org/10.1016/j.tourman.2016.10.001
Yang, X., Pan, B., Evans, J.A., Lv, B.: Forecasting Chinese tourist volume with search engine data. Tour Manag. 46, 386–397 (2015). https://doi.org/10.1016/j.tourman.2014.07.019
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Álvarez-García, J., Durán-Sánchez, A., del Río-Rama, M.d.C. et al. Big data and tourism research: measuring research impact. Qual Quant 57 (Suppl 3), 271–292 (2023). https://doi.org/10.1007/s11135-020-01044-z
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11135-020-01044-z