Skip to main content
SpringerLink
Log in

Digital Transformation in Tourism: An Intelligent Information System Proposition for Hotel Organizations

  • Chapter
  • First Online:
Intelligent Systems in Digital Transformation

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 549))

Abstract

The digital transformation process in the tourism industry has been developing further in recent years. In addition to the active use of traditional information technologies, access to data has become relatively easy thanks to the use of smart technologies in this sector, and it has become even more important to interpret this data and improve visitor experiences in line with visitors’ expectations. In this study, which is based on the digitalized tourism perspective called Tourism 4.0 and Smart Tourism, following the Industry 4.0 prospect, digital transformation and the role of digital tools in the accommodation dimension of the tourism sector is discussed and it is aimed to propose an end-to-end smart management system. Thanks to this system which is composed of multiple data collection tools, a relational database for data storage, and interspersed information system modules including a recommendation system, the preferences of the users could be examined to achieve maximum customer satisfaction, and it could be possible to make suggestions for better spending their time in their current visits in line with their preferences. The uniqueness of the chapter is that it simulates the end-to-end digitalization process of accommodation businesses, which is an aspect that has not been discussed in the literature before.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    Illustrations are designed by the authors. Source of thumbnails: https://www.shutterstock.com/tr/category/illustrations-clip-art.

References

  1. Abbasi-Moud Z, Vahdat-Nejad H, Sadri J (2021) Tourism recommendation system based on semantic clustering and sentiment analysis. Expert Syst Appl 167:114324

    Article  Google Scholar 

  2. Adeyinka-Ojo S (2018) A strategic framework for analysing employability skills deficits in rural hospitality and tourism destinations. Tour Manag Perspect 27:47–54

    Article  Google Scholar 

  3. Adeyinka-Ojo S, Abdullah SK (2019) Disruptive digital innovation and sharing economy in hospitality and tourism destination. In: IOP conference series: materials science and engineering, vol 495, no 1. IOP Publishing p 012006

    Google Scholar 

  4. Afsahhosseini F, Al-Mulla Y (2020) Machine learning in tourism. In: Proceedings of the 3rd international conference on machine learning and machine intelligence, pp 53–57. https://doi.org/10.1145/3426826.3426837

  5. Agag G, El-Masry AA (2016) Understanding the determinants of hotel booking intentions and moderating role of habit. Int J Hosp Manag 54:52–67

    Article  Google Scholar 

  6. Aggarwal CC (2015) Data mining: the textbook, vol 1. Springer, New York

    MATH  Google Scholar 

  7. Alotaibi E (2020) Application of machine learning in the hotel industry: a critical review. J Assoc Arab Univ Tour Hosp 18(3):78–96

    MathSciNet  Google Scholar 

  8. Bangare ML, Bangare PM, Ramirez-Asis E, Jamanca-Anaya R, Phoemchalard C, Bhat DAR (2022) Role of machine learning in improving tourism and education sector. Mater Today Proc 51:2457–2461

    Article  Google Scholar 

  9. Benckendorff PJ, Xiang Z, Sheldon PJ (2019) Tourism information technology. Cabi.

    Google Scholar 

  10. Bilgili B, Koc E (2021) Digital transformation in tourism. In: Emerging transformations in tourism and hospitality. Routledge, pp 53–65

    Google Scholar 

  11. Bouneffouf D, Bouzeghoub A, Gancarski A (2013) Risk-aware recommender systems. In: Lecture notes in computer science, vol 8226, Springer

    Google Scholar 

  12. Bower LJ, Christensen MC (1995) Disruptive technologies: catching the wave. Harward Bus Rev 73:43–53

    Google Scholar 

  13. Buhalis D (2020) Technology in tourism-from information communication technologies to eTourism and smart tourism towards ambient intelligence tourism: a perspective article. Tour Rev 75(1):267–272

    Article  Google Scholar 

  14. Buhalis D, Law R (2008) Progress in information technology and tourism management: 20 years on and 10 years after the internet—the state of eTourism research. Tour Manag 29(4):609–623

    Article  Google Scholar 

  15. Büyükuslu AR (2018) Dijital dönüşüm, Der yayınları, İstanbul

    Google Scholar 

  16. Cai W, Richter S, McKenna B (2019) Progress on technology use in tourism. J Hosp Tour Technol 10:651–672

    Google Scholar 

  17. Chanias S, Myers MD, Hess T (2019) Digital transformation strategy making in pre-digital organizations: the case of a financial services provider. J Strateg Inf Syst 28(1):17–33

    Article  Google Scholar 

  18. Cuomo MT, Tortora D, Foroudi P, Giordano A, Festa G, Metallo G (2021) Digital transformation and tourist experience co-design: big social data for planning cultural tourism. Technol Forecast Soc Chang 162:120345

    Article  Google Scholar 

  19. Doğru NB, Meçik O (2018) Türkiye’de endüstri 4. 0’ın işgücü piyasalarına etkileri: Firma beklentileri, Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 23, (Endüstri 4. 0 ve Örgütsel Değişim Özel Sayısı), pp 1581–1606

    Google Scholar 

  20. Egger R (2022) Machine learning in tourism. Springer, Cham

    Google Scholar 

  21. Furr N, Shipilov A (2019) Digital doesn’t have to be disruptive. Harvard Bus Rev. https://hbr.org/2019/07/digital-doesnt-have-to-be-disruptive

  22. Gartner (2022) Top Strategic Technology Trends for 2022. https://www.gartner.com/en/information-technology/insights/top-technology-trends/top-technology-trends-ebook. Accessed 21 June 2022

  23. Gretzel U (2022) The Smart DMO: a new step in the digital transformation of destination management organizations. Eur J Tour Res 30:3002–3002

    Article  Google Scholar 

  24. Gretzel U, Sigala M, Xiang Z, Koo C (2015) Smart tourism: foundations and developments. Electron Mark 3(25):179–188

    Article  Google Scholar 

  25. Gupta M (2019) Deep learning. In: Essentials of business analytics,. Springer, Cham, pp 569–595

    Google Scholar 

  26. Guo R, Wu Y (2021) Research on the Construction path of smart hotel in the era of artificial intelligence. In: 2021 international conference on intelligent computing, automation and applications (ICAA). IEEE, pp 199–202

    Google Scholar 

  27. Gustavo N, Mbunge E, Belo M, Fashoto SG, Pronto JM, Metfula AS, Chiremba TR (2022) Emphasizing the digital shift of hospitality towards hyper-personalization: application of machine learning clustering algorithms to analyze travelers. In: Optimizing digital solutions for hyper-personalization in tourism and hospitality, pp 1–19. IGI Global

    Google Scholar 

  28. Han J, Kamber M, Pei J (2011) Data mining: concepts and techniques, 3rd edn. Morgan Kaufmann, Waltham

    MATH  Google Scholar 

  29. Hand DJ, Till RJ (2001) A simple generalization of the area under the ROC curve for multiple class classification problems. Mach Learn 45(2):171–186

    Article  MATH  Google Scholar 

  30. Hu YH, Chen YL, Chou HL (2017) Opinion mining from online hotel reviews: a text summarization approach. Inf Process Manag 53(2):436–449

    Article  Google Scholar 

  31. Huang A, Chao Y, de la Mora Velasco E, Bilgihan A, Wei W (2021) When artificial intelligence meets the hospitality and tourism industry: an assessment framework to inform theory and management. J Hosp Tour Insights. https://doi.org/10.1108/JHTI-01-2021-0021

  32. IERC (2020) Internet of Things – The Call of the Edge - Everything Intelligent Everywhere - IERC Cluster Book 2020. http://www.internet-of-things-research.eu/pdf/IoT_The_Call_of_the_Edge-Everything_Intelligent_Everywhere_E9788770221955.pdf

  33. Isinkaye FO, Folajimi YO, Ojokoh BA (2015) Recommendation systems: principles, methods and evaluation. Egypt Inf J 16(3):261–273

    Google Scholar 

  34. Ismail MH, Khater M, Zaki M (2017) Digital business transformation and strategy: what do we know so far. Cambridge Serv Allia 10:1–35

    Google Scholar 

  35. Ivanov S (2019) Ultimate transformation: how will automation technologies disrupt the travel, tourism and hospitality industries? Zeitschrift für Tourismuswissenschaft 11(1):25–43

    Article  Google Scholar 

  36. Kelm O, Gerl K, Meißner F (2020) Machine learning. In: Borucki I, Kleinen-von Königslöw K, Marschall S, Zerback T (eds) Handbuch Politische Kommunikation. Springer Fachmedien Wiesbaden, pp 1–9

    Google Scholar 

  37. Kim J, Song C, Kim T, Rim K, Lee J (2009) Secure and efficient recommendation service of RFID system using authenticated key management. In: Proceedings of the 4th international conference on ubiquitous information technologies & applications. IEEE, pp 1–5

    Google Scholar 

  38. Konstantinova S (2019) Digital transformation in tourism. Knowl-Int J 35(1):188–193

    Google Scholar 

  39. Koo C, Shin S, Gretzel U, Hunter WC, Chung N (2016) Conceptualization of smart tourism destination competitiveness. Asia Pac J Inf Syst 26(4):561–576

    Google Scholar 

  40. Koushik AN, Manoj M, Nezamuddin N (2020) Machine learning applications in activity-travel behaviour research: a review. Transp Rev 40(3):288–311

    Article  Google Scholar 

  41. KPMG (2018) The Changing Landscape of Disruptive Technologies. https://assets.kpmg/content/dam/kpmg/pl/pdf/2018/06/pl-The-Changing-Landscape-of-Disruptive-Technologies-2018.pdf

  42. Kumar S (2019) Machine learning (supervised). In: Essentials of business analytics. Springer, Cham, pp. 507–568

    Google Scholar 

  43. Küpeli TŞ, Ünlüönen K (2021) Veri Madenciliği ve Turizmde Veri Madenciliği Çalışmaları. J Tour Gastronomy Stud 9(1):275–298

    Article  Google Scholar 

  44. Le TH, Arcodia C, Novais MA, Kralj A (2021) Proposing a systematic approach for integrating traditional research methods into machine learning in text analytics in tourism and hospitality. Curr Issue Tour 24(12):1640–1655

    Article  Google Scholar 

  45. Leung D, Law R, Van Hoof H, Buhalis D (2013) Social media in tourism and hospitality: a literature review. J Travel Tour Mark 30(1–2):3–22

    Article  Google Scholar 

  46. Li J, Xu L, Tang L, Wang S, Li L (2018) Big data in tourism research: a literature review. Tour Manag 68:301–323

    Article  Google Scholar 

  47. Li Q, Li S, Zhang S, Hu J, Hu J (2019) A review of text corpus-based tourism big data mining. Appl Sci 9(16):3300

    Article  Google Scholar 

  48. Li X, Law R, Xie G, Wang S (2021) Review of tourism forecasting research with internet data. Tour Manag 83:104245

    Article  Google Scholar 

  49. Liu DY, Chen SW, Chou TC (2011) Resource fit in digital transformation: lessons learned from the CBC Bank global e-banking project. Manag Decis 49:1728

    Article  Google Scholar 

  50. Lu D, Wu R, Sang J (2017) Overlapped user-based comparative study on photo- sharing websites. Inf Sci 376:54–70

    Article  Google Scholar 

  51. Lu J, Wu D, Mao M, Wang W, Zhang G (2015) Recommender system application developments: a survey. Decis Support Syst 74:12–32

    Article  Google Scholar 

  52. Luberg A, Granitzer M, Wu H, Järv P, Tammet T (2012) Information retrieval and deduplication for tourism recommender sights planner. In: Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics, pp 1–11

    Google Scholar 

  53. Malcienė Z, Skauronė L (2019) Application of information systems in tourism and leisure sector. Int J Social Sci Human Invent 6(02):5341–5346

    Article  Google Scholar 

  54. Matt C, Hess T, Benlian A (2015) Digital transformation strategies. Bus Inf Syst Eng 57(5):339–343

    Article  Google Scholar 

  55. Mbunge E, Muchemwa B (2022) Deep learning and machine learning techniques for analyzing travelers' online reviews: a review. In: Optimizing digital solutions for hyper-personalization in tourism and hospitality. IGI Global, pp 20–39

    Google Scholar 

  56. Mich L (2020) Artificial intelligence and machine learning. In: Xiang Z, Fuchs M, Gretzel U, Höpken W (eds) Handbook of e-Tourism. Springer, Cham. https://doi.org/10.1007/978-3-030-05324-6_25-1

  57. Nagar R, Singh Y, Jaglan V (2021) A review on machine learning applications in medical tourism. In:2021 fourth international conference on computational intelligence and communication technologies (CCICT). IEEE, pp 208–215

    Google Scholar 

  58. Newman D (2020) Top 10 digital transformation trends for 2021. Forbes. https://www.forbes.com/sites/danielnewman/2020/09/21/top-10-digital-transformation-trends-for-2021/?sh=42fe961fc6f4

  59. Nilashi M, Bagherifard K, Rahmani M, Rafe V (2017) A recommender system for tourism industry using cluster ensemble and prediction machine learning techniques. Comput Ind Eng 109:357–368

    Article  Google Scholar 

  60. Palácios H, de Almeida MH, Sousa MJ (2021) A bibliometric analysis of trust in the field of hospitality and tourism. Int J Hosp Manag 95:102944

    Article  Google Scholar 

  61. Pan B, Yang Y (2017) Forecasting destination weekly hotel occupancy with big data. J Travel Res 56(7):957–970

    Article  Google Scholar 

  62. Panfiluk E, Godlewska M, Heksel Ż, Dubilewska I (2019) Innovative tourist products during the industrial revolution 4.0. Acad Manag 3(2):92–102

    Google Scholar 

  63. Parviainen P, Tihinen M, Kääriäinen J, Teppola S (2017) Tackling the digitalization challenge: how to benefit from digitalization in practice. Int J Inf Syst Proj Manag 5(1):63–77

    Google Scholar 

  64. Pelet JE, Lick E, Taieb B (2019) Internet of Things and artificial intelligence in the hotel industry: which opportunities and threats for sensory marketing? In: Martínez-López F, Gázquez-Abad J, Roggeveen A (eds) Advances in national brand and private label marketing. NB&PL 2019. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-18911-2_20.

  65. Pencarelli T (2020) The digital revolution in the travel and tourism industry. Inf Technol Tour 22(3):455–476

    Article  Google Scholar 

  66. Peng R, Lou Y, Kadoch M, Cheriet M (2020) A human-guided machine learning approach for 5G smart tourism IoT. Electronics (Switzerland) 9(6):1–14

    Google Scholar 

  67. Phillips P, Zigan K, Silva MMS, Schegg R (2015) The interactive effects of online reviews on the determinants of Swiss hotel performance: a neural network analysis. Tour Manag 50:130–141

    Article  Google Scholar 

  68. Piccinini E, Gregory RW, Kolbe LM (2015) Changes in the producer-consumer relationship-towards digital transformation. Wirtschaftsinformatik Proceedings, 1634–1648. https://aisel.aisnet.org/wi2015/109

  69. Pindžo R, Brjaktarović L (2018) Digital transformation of tourism. In Tourism international scientific conference Vrnjačka Banja-TISC, vol 3, no 1, pp 340–355

    Google Scholar 

  70. Pineda-Jaramillo JD (2019) A review of Machine Learning (ML) algorithms used for modeling travel mode choice. Dynamics 86(211):32–41

    Google Scholar 

  71. Portugal I, Alencar P, Cowan D (2018) The use of machine learning algorithms in recommender systems: a systematic review. Expert Syst Appl 97:205–227

    Article  Google Scholar 

  72. Pumaleque AAP, Fernandez IR, Perez DDI, Bedriñana MAA (2021) Digital transformation model for the development of tourism companies. 3c Empresa: investigación y pensamiento crítico (1), 47–61

    Google Scholar 

  73. Samuel AL (1959) Some studies in machine learning using the game of checkers. IBM J Res Dev 3(3):210–229

    Article  MathSciNet  Google Scholar 

  74. Schuchmann D, Seufert S (2015) Corporate learning in times of digital transformation: a conceptual framework and service portfolio for the learning function in banking organisations. Int J Corpor Learn (IJAC) 8(1):31–39

    Article  Google Scholar 

  75. Schwertner K (2017) Digital transformation of business. Trakia J Sci 15(1):388–393

    Article  Google Scholar 

  76. Shalev-Shwartz S, Ben-David S (2014) Understanding machine learning: from theory to algorithms. Cambridge University Press, Cambridge

    Book  MATH  Google Scholar 

  77. Shi Y, Serdyukov P, Hanjalic A, Larson M (2011) Personalized landmark recommendation based on geotags from photo sharing sites. In: Proceedings of the 5th international AAAI conference on weblogs and social media, Barcelona, Spain

    Google Scholar 

  78. Shibata N, Shinoda H, Nanba H, Ishino A, Takezawa T (2020) Classification and visualization of travel blog entries based on types of tourism. In: Neidhardt J, Wörndl W (eds) Information and communication technologies in tourism. Springer, Cham

    Google Scholar 

  79. Sintala SK (2019) Information and communication technology in hotel industry [Master's thesis, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1554496660762962

  80. Snijders C, Matzat U (2012) ‘Big Data’: big gaps of knowledge in the field of internet. Int J Internet Sci 7:1–5

    Google Scholar 

  81. Solakis K, Katsoni V, Mahmoud AB, Grigoriou N (2022) "Factors affecting value co-creation through artificial intelligence in tourism: a general literature review. J Tour Fut. https://doi.org/10.1108/JTF-06-2021-0157

  82. Sousa MJ, Rocha A (2018) Skills for disruptive digital business. J Bus Res 17

    Google Scholar 

  83. Statista (2022) Digital 2022. https://wearesocial.com/uk/blog/2022/01/digital-2022/

  84. Statista (2022). Spending on digital transformation technologies and services worldwide from 2017 to 2025. https://www.statista.com/statistics/870924/worldwide-digital-transformation-market-size/

  85. Uzan ŞB, Özüçağlıyan MÖ (2020) Turizm Sektöründe Veri Madenciliği. Türk Turizm Araştırmaları Dergisi 4(4):3465–3485

    Google Scholar 

  86. Visa S, Ramsay B, Ralescu AL, Van Der Knaap E (2011) Confusion matrix-based feature selection. MAICS 710:120–127

    Google Scholar 

  87. Volo S (2020) Tourism statistics, indicators and big data: a perspective article. Tour Rev 75(1):304–309

    Article  Google Scholar 

  88. Wainwright D, Waring T (2004) Three domains for implementing integrated information systems: redressing the balance between technology, strategic and organisational analysis. Int J Inf Manag 24(4):329–346

    Article  Google Scholar 

  89. Wong BKM, Hazley SAS (2021) The future of health tourism in the industrial revolution 4.0 era. J Tour Fut 7(2):267–272

    Google Scholar 

  90. Xiang Z, Du Q, Ma Y, Fan W (2017) A comparative analysis of major online review platforms: implications for social media analytics in hospitality and tourism. Tour Manag 58:51–65

    Article  Google Scholar 

  91. Yankın FB (2019) Dijital dönüşüm sürecinde çalışma yaşamı. Trakya Üniversitesi İktisadi ve İdari Bilimler Fakültesi 7(2):1–38

    Google Scholar 

  92. Zaki MJ, Meira W Jr, Meira W (2014) Data mining and analysis: fundamental concepts and algorithms. Cambridge University Press, Cambridge

    Book  MATH  Google Scholar 

  93. Zaoui F, Souissi N (2020) Roadmap for digital transformation: a literature review. Procedia Comput Sci 175:621–628

    Article  Google Scholar 

  94. Zhang L, Sun Z (2019) The application of artificial intelligence technology in the tourism industry of Jinan. In: Journal of physics: conference series, vol 1302, no 3. IOP Publishing, p 032005

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Management Information Systems, Marmara University, Istanbul, Turkey

    Tutku Tuncalı Yaman

  2. Department of Management Information Systems, Beykent University, Istanbul, Turkey

    Hülya Başeğmez

Authors
  1. Tutku Tuncalı Yaman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hülya Başeğmez
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tutku Tuncalı Yaman .

Editor information

Editors and Affiliations

  1. Department of Industrial Engineering, Istanbul Technical University, Maçka, Turkey

    Cengiz Kahraman

  2. Department of Industrial Engineering, Bahcesehir University, Besiktas, Istanbul, Turkey

    Elif Haktanır

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Tuncalı Yaman, T., Başeğmez, H. (2023). Digital Transformation in Tourism: An Intelligent Information System Proposition for Hotel Organizations. In: Kahraman, C., Haktanır, E. (eds) Intelligent Systems in Digital Transformation. Lecture Notes in Networks and Systems, vol 549. Springer, Cham. https://doi.org/10.1007/978-3-031-16598-6_15

Download citation

Publish with us

Policies and ethics

Search

Navigation