Artificial intelligence for innovative service design and guest experience : case: Hotels in Germany
Shvaikovskaia, Elizaveta (2022)
2022
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2022120927567
https://urn.fi/URN:NBN:fi:amk-2022120927567
Tiivistelmä
The purpose of the thesis was to find out the critical role of artificial intelligence in service design and guest experience in the hotel industry in Germany.
To appeal to the topic and answer the core research questions, the thesis applies the literature review of AI, IoT, big data, service design grounds, and the current condition of intelligent technologies in the industry. Based on the analysis of machine intelligence’s practical implications among global leading hotels, the ideas are tested on the German market throughout the interview and survey implementation. The findings specify critical success factors for the proper adoption of artificial intelligence, robots, and service automation at each customer touchpoint with assessed potential factors. Moreover, the investigation depicts actual challenges according to technological, organizational, and environmental elements, along with future perspectives for the German hotel sector.
In conclusion, the study report confirms the hypothesis of potential market resilience, and simultaneously, it shows evaluated substantial future development and industry empowerment by artificial intelligence and machine learning towards personalization, improved guest experience, unique service, and increased satisfaction.
To appeal to the topic and answer the core research questions, the thesis applies the literature review of AI, IoT, big data, service design grounds, and the current condition of intelligent technologies in the industry. Based on the analysis of machine intelligence’s practical implications among global leading hotels, the ideas are tested on the German market throughout the interview and survey implementation. The findings specify critical success factors for the proper adoption of artificial intelligence, robots, and service automation at each customer touchpoint with assessed potential factors. Moreover, the investigation depicts actual challenges according to technological, organizational, and environmental elements, along with future perspectives for the German hotel sector.
In conclusion, the study report confirms the hypothesis of potential market resilience, and simultaneously, it shows evaluated substantial future development and industry empowerment by artificial intelligence and machine learning towards personalization, improved guest experience, unique service, and increased satisfaction.