FORMATION OF NEW SERVICE ECONOMY DIRECTIONS BASED ON DIGITAL SOLUTIONS IN THE HOSPITALITY INDUSTRY AND SPECIALIZED TYPES OF TOURISM USING THE EXAMPLE OF MEDICAL ONE

One of the directions of research among Russian and foreign scholars is identifying and studying the impact of digital transformation on the formation of a new service economy in the hospitality, tourism, and medical tourism industries. Despite rapid progress in digitization, there remains a pressing need to thoroughly investigate the mechanisms through which businesses adapt to dynamic and challenging environments (VUCA), as well as understand the role of artificial intelligence and machine learning technologies in ensuring sustainable development of these sectors. The author has conducted a review and analysis of different approaches to defining the functionalities of digital platforms, such as data integration, process automation, improving customer experience, and risk management. Illustrations are provided using examples of applying artificial intelligence and machine learning in the hospitality and tourism industries, including robotic systems, biometric technologies, and smart assistants. Special attention is drawn to the importance of medical tourism as a driver of economic growth, contributing to job creation and attracting investments. Additionally, a comparative analysis of international and Russian experience in the digitalization of the tourism and hospitality industries was performed. Although the article carries an overview and analytical character, its relevance for Russian researchers and professionals in the fields of tourism, hospitality, and medical tourism is emphasized.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-16
DOI
https://doi.org/10.5281/zenodo.17130418
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
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article

FORMATION OF NEW SERVICE ECONOMY DIRECTIONS BASED ON DIGITAL SOLUTIONS IN THE HOSPITALITY INDUSTRY AND SPECIALIZED TYPES OF TOURISM USING THE EXAMPLE OF MEDICAL ONE

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

FORMATION OF NEW SERVICE ECONOMY DIRECTIONS BASED ON DIGITAL SOLUTIONS IN THE HOSPITALITY INDUSTRY AND SPECIALIZED TYPES OF TOURISM USING THE EXAMPLE OF MEDICAL ONE

article en

Abstract

One of the directions of research among Russian and foreign scholars is identifying and studying the impact of digital transformation on the formation of a new service economy in the hospitality, tourism, and medical tourism industries. Despite rapid progress in digitization, there remains a pressing need to thoroughly investigate the mechanisms through which businesses adapt to dynamic and challenging environments (VUCA), as well as understand the role of artificial intelligence and machine learning technologies in ensuring sustainable development of these sectors. The author has conducted a review and analysis of different approaches to defining the functionalities of digital platforms, such as data integration, process automation, improving customer experience, and risk management. Illustrations are provided using examples of applying artificial intelligence and machine learning in the hospitality and tourism industries, including robotic systems, biometric technologies, and smart assistants. Special attention is drawn to the importance of medical tourism as a driver of economic growth, contributing to job creation and attracting investments. Additionally, a comparative analysis of international and Russian experience in the digitalization of the tourism and hospitality industries was performed. Although the article carries an overview and analytical character, its relevance for Russian researchers and professionals in the fields of tourism, hospitality, and medical tourism is emphasized.

Zenodo (CERN European Organization for Nuclear Research)
Plekhanov Russian University of Economics (RU), Financial University (RU)
Decent work and economic growth
Openalex Percentile: Top 27%
Geochemistry and Geologic Mapping
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