Tecnologías disruptivas y sostenibilidad turística

  1. Luis Moreno Izquierdo 1
  2. María Núñez Romero 1
  3. Aimée Torres Penalva 1
  1. 1 Universitat d'Alacant
    info

    Universitat d'Alacant

    Alicante, España

    ROR https://ror.org/05t8bcz72

Revista:
Economía industrial

ISSN: 0422-2784

Año de publicación: 2022

Título del ejemplar: Sostenibilidad, Innovación y Competitividad Turística

Número: 426

Páginas: 117-122

Tipo: Artículo

Otras publicaciones en: Economía industrial

Resumen

Las tecnologías de la cuarta revolución industrial están conduciendo a una renovación trascendental de todos los sectores productivos; también de los tradicionales como el turístico. Dentro de estos procesos de renovación, la innovación más disruptiva ha puesto el foco sobre las cuestiones de sostenibilidad a nivel productivo y medioambiental. En este artículo se analiza cómo avances en inteligencia artificial, blockchain o en el internet de las cosas están llevando a los destinos y la gestión turística a buenas prácticas internacionales que pueden ser la base de la competitividad futura de un sector clave para la economía española

Referencias bibliográficas

  • Asín, A. (2018). Fomento de la sostenibilidad en destinos turísticos gracias a proyectos reales de IoT. En el IV Congreso de Ciudades Inteligentes. https://www.esmartcity.es/comunicaciones/fomento-sostenibilidad-destinos-turisticos-gracias-proyectos-reales-iot.
  • Abbruzzo, A., Brida, J. G. y Scuderi, R. (2014). Scad-elastic net and the estimation of individual tourism expenditure determinants. Decision support systems, 66, 52-60. https://doi. org/10.1016/j.dss.2014.06.003.
  • Avelar, S. (2020). From a smart city to a smart destination: a case study. In Strategic innovative marketing and tourism, 7-14. Springer, Cham. https://doi.org/10.1007/978-3-030- 36126-6_2.
  • Bai, C. A., Cordeiro, J. y Sarkis, J. (2020). Blockchain technology: Business, strategy, the environment, and sustainability. Business Strategy and the Environment, 29(1), 321-322. https:// doi.org/10.1002/bse.2431.
  • Bano, S., Liu, L., Khan, A. (2022). Dynamic influence of aging, industrial innovations, and ICT on tourism development and renewable energy consumption in BRICS economies. Renewable energy, vol. 192, pp. 431-442. https://doi.org/10.1016/j.renene.2022.04.134.
  • Baum, S. D. y Owe, A. (2022). Artificial Intelligence Needs Environmental Ethics. Ethics, Policy & Environment, 1-5. https://doi.org/10.1080/21550085.2022.2076538.
  • Bongomin, O., Gilibrays-Ocen, G., Oyondi-Nganyi, E., Musinguzi, A. y Omara, T. (2020). Exponential disruptive technologies and the required skills of industry 4.0. Journal of Engineering, 2020(4280156). https://doi.org/10.1155/2020/4280156.
  • Bughin, J., Hazan, E., Ramaswamy, S., Chui, M., Allas, T., Dahlström, P., Henke N. y Trench, M. (2017). Artificial intelligence: the next digital frontier? McKinsey Global Institute. https:// apo.org.au/node/210501.
  • Caddeo, F., & Pinna, A. (2021, May). Opportunities and challenges of Blockchain-Oriented systems in the tourism industry. In 2021 IEEE/ACM 4th International Workshop on Emerging Trends in Software Engineering for Blockchain (WETSEB) (pp. 9-16).
  • Car, T., Stifanich, L. P. y Å imunić, M. (2019). Internet of things (iot) in tourism and hospitality: Opportunities and challenges. Tourism in South East Europe..., 5, 163-175. https://doi. org/10.20867/tosee.05.42.
  • Carabin, G., Wehrle, E. y Vidoni, R. (2017). A review on energy-saving optimization methods for robotic and automatic systems. Robotics, 6(4), 39. https://doi.org/10.3390/robotics6040039.
  • Chen, Y., Cheng, L. y Lee, C. C. (2022). How does the use of industrial robots affect the ecological footprint? International evidence. Ecological Economics, 198, 107483. https://doi.org/10.1016/j.ecolecon.2022.107483.
  • Christensen, C., Raynor, M.E. y McDonald, R. (2013). Disruptive innovation. Harvard Business Review.
  • Comisión Europea (2014). Addressing the Challenge of Energy Efficiency through Information and Communication Technologies. https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2008:0241:FIN:EN:PDF.
  • Cook, G., Lee, J., Tsai, T., Kong, A., Deans, J., Johnson, B. y Jardim, E. (2017). Clicking clean: who is winning the race to build a green internet?. Greenpeace Inc.
  • Cooper, C. (2006). Knowledge management and tourism. Annals of Tourism Research, 33(1), 47-64. https://doi.org/10.1016/j.annals.2005.04.005
  • Crafts, N. (2021). Artificial intelligence as a general-purpose technology: an historical perspective. Oxford Review of Economic Policy, 37(3), 521-536. https://doi.org/10.1093/oxrep/ grab012.
  • Dauvergne, P. (2020). Is artificial intelligence greening global supply chains? Exposing the political economy of environmental costs. Review of International Political Economy, 696-718. https://doi.org/10.1080/09692290.2020.1814381.
  • Etihad Airways (2020). Etihad Airways se asocia con Lumitics para reducir el desperdicio de alimentos en vuelo. https://www.etihad.com/en/news/etihad-airways-teams-up-with-lumit ics-to-reduce-inflight-food-wastage.
  • Gebler, M., Uiterkamp, A. J. S. y Visser, C. (2014). A global sustainability perspective on 3D printing technologies. Energy Policy, 74, 158-167. https://doi.org/10.1016/j.enpol.2014.08.033.
  • Gholamhosseinian, A. y Khalifeh, A. (2012). Cloud compu- ting and sustainability: Energy efficiency aspects. Tesis doctoral. Halmstad University, Halmstad, Suecia. https://www.diva-portal.org/smash/record.jsf?dswid=6556.
  • Gregorutti, B., Lupu, A., y Line, S. Optimisation et apprentissage statistique pour la réduction de la consommation de carburant. http://papersjds16.sfds.asso.fr/submission_119 .
  • Hacklin, F., Raurich, V. y Marxt, C. (2004). How incremental innovation becomes disruptive: the case of technology convergence. IEEE International Engineering Management Conference. 1, 32-36. https://doi.org/10.1109/IEMC.2004.1407070.
  • Honeywell. (2021). Multiple Airlines Select Honeywell Forge Flight Data Analytics Platform To Save On Fuel.
  • https://www.honeywell.com/us/en/press/2021/1/multiple-airlines-select-honeywell-forge-flight-data-analytics-platform-to-save-on-fuel.
  • ICEX. (2019). Meliá usará ‘blockchain’ para compensar emisiones. https://www.icex.es/icex/es/navegacion-principal/ todos-nuestros-servicios/informacion-de-mercados/paises/ navegacion-principal/noticias/NEW2019839162.html?idPais=US>.
  • Ivars-Baidal, J. A., Celdrán-Bernabeu, M. A., Femenia-Serra, F., Perles-Ribes, J. F. y Giner-Sánchez, D. (2021). Measuring the progress of smart destinations: The use of indicators as a management tool. Journal of Destination Marketing & Management, 19, 100531. https://doi.org/10.1016/j.jdmm.2020.100531.
  • Komsary, K. C., Ernawati, T., Hodijah, A. y Wardiana, D. (2020). Internet of Things (IoT) for Energy Efficiency in Tourism-Related Industry. Pertanika Journal of Social Sciences & Humanities, 28.
  • http://www.pertanika.upm.edu.my/pjssh/browse/special-issue?decade=2020&year=2020&journal=JSSH-28-S1/.
  • Liu, J., Liu, L., Qian, Y. y Song, S. (2021). The effect of artificial intelligence on carbon intensity: Evidence from China’s industrial sector. Socio-Economic Planning Sciences, 101002. https://doi.org/10.1016/j.seps.2020.101002.
  • MacArthur, E., y Waughray, D. (2016). Intelligent Assets: Unlocking the circular economy potential. Foundation Ellen MacArthur Foundation.
  • Melander, L. y Lingegård, S. (2018). Is the pace of technology development a threat or opportunity for sustainability? The case of remanufactured industrial robots. Procedia CIRP, 73, 247-252. https://doi.org/10.1016/j.procir.2018.03.313.
  • Moreno-Izquierdo, L., Egorova, G., Peretó-Rovira, A. y Más-Ferrando, A. (2018). Exploring the use of artificial intelligence in price maximisation in the tourism sector: its application in the case of Airbnb in the Valencian Community. Investigaciones Regionales, (42), 113-128. http://hdl.handle. net/10045/86772.
  • Moreno-Izquierdo, L. y A. Pedreño-Muñoz (2020). «Europa frente a EE. UU. y China. Prevenir el declive en la era de la inteligencia artificial».
  • Nishant, R., Kennedy, M. y Corbett, J. (2020). Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda. International Journal of Information Management, 53, 102104. https://doi.org/10.1016/j.ijinfomgt.2020.102104.
  • Pons-Pons, M., Johnson, P. A., Rosas-Casals, M., Sureda, B. y Jover, È. (2012). Modeling climate change effects on winter ski tourism in Andorra. Climate research, 54(3), 197-207. https:// doi.org/10.3354/cr01117.
  • Rejeb, A., Suhaiza, Z., Rejeb, K., Seuring, S. y Treiblmaier, H. (2022). The Internet of Things and the circular economy: A systematic literature review and research agenda. Journal of Cleaner Production, 131439. https://doi.org/10.1016/j.jclepro.2022.131439.
  • Rejeb, A. y Rejeb, K. (2020). Blockchain and supply chain sustainability. Logforum, 16(3), 363-372. https://doi.org/10.17270/J.LOG.2020.467.
  • Rucci, A. C., Moreno-Izquierdo, L., Perles-Ribes, J. F., & Porto, N. (2022). Smart or partly smart? Accessibility and innovation policies to assess smartness and competitiveness of destinations. Current Issues in Tourism, 25(8), 1270-1288. https://doi.or g/10.1080/13683500.2021.1914005.
  • Salam, A. (2020). Internet of things for water sustainability. In Internet of Things for sustainable community development 113-145. https://doi.org/10.1007/978-3-030-35291-2_4.
  • Samala, N., Katkam, B. S., Bellamkonda, R. S. y Rodriguez, R.V. (2020). «Impact of AI and robotics in the tourism sector: a critical insight». Journal of tourism futures, 8(1), 73-87. https:// doi.org/10.1108/JTF-07-2019-0065.
  • Satta, G., Spinelli, R. y Parola, F. (2019). Is tourism going green? A literature review on green innovation for sustainable tourism. Tourism Analysis, 24(3), 265-280. https://doi.org/10.372 7/108354219X15511864843803.
  • Scott, D., Steiger, R., Rutty, M., Pons, M. y Johnson, P. (2020). Climate change and ski tourism sustainability: An integrated model of the adaptive dynamics between ski area operations and skier demand. Sustainability, 12(24), 10617. https://doi. org/10.3390/su122410617.
  • Tian, F., Yang, Y., Mao, Z. y Tang, W. (2021). Forecasting daily attraction demand using big data from search engines and social media. International Journal of Contemporary Hospitality Management. https://doi.org/10.1108/ IJCHM-06-2020-063.
  • Tussyadiah, I. (2020). A review of research into automation in tourism: Launching the Annals of Tourism Research Curated Collection on Artificial Intelligence and Robotics in Tourism. Annals of Tourism Research, 81, 102883. https://doi.org/10.1016/j. annals.2020.102883.
  • UNWTO. (2015). EL TURISMO EN LA AGENDA 2030. https:// www.unwto.org/es/turismo-agenda-2030.
  • Verma, Amit y Shukla, Vinod. (2019). Analyzing the Influence of IoT in Tourism Industry. SSRN Electronic Journal. http://doi. org/10.2139/ssrn.3358168.
  • Vinuesa, R., Azizpour, H., Leite, I. et al.. (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. Nature communications, 11(1), 1-10. https://doi. org/10.1038/s41467-019-14108-y.
  • Zlatanov y Popesku, J. (2019). Current applications of artificial intelligence in tourism and hospitality. In Sinteza 2019-International Scientific Conference on Information Technology and Data Related Research, 84-90. https://doi.org/10.15308/ Sinteza-2019-84-90.