Quantum Computing Applications in Data Analytics for Improving Sustainable Tourism Management

Authors:
Ni Made Eka Mahadewi

Addresses:
Department of Tourism, Bali Tourism Polytechnic, Kampial, Nusadua, Badung-Bali, Indonesia.

Abstract:

This is one of the world's largest growth drivers but faces some challenges in terms of sustainability. The use of quantum computing, which represents an unparalleled computing ability, is a revolutionary approach to managing data for tourism applications. This paper will discuss the area where quantum computing can help promote sustainable management through data analytics applications in tourism, thereby improving resource use efficiency, reducing environmental impacts, and enhancing tourist experiences. Here, data clustering, optimization, and predictive analytics are presented in several quantum algorithms applicable to resource allocation improvement, reducing the environmental impacts of tourism, and optimizing the tourist experience. The theoretical underpinning of quantum computing, with a few examples of practical applications in data analytics and implications for sustainable tourism, are presented. Huge improvements in prediction accuracy and operational efficiency suggest a revolution in tourism management may be on the horizon. The proposed architecture will integrate analytics from quantum into decision-making frameworks that can provide actionable insights to policymakers as well as operators in the tourism sector. Finally, the study will conclude with a discussion of limitations and potential further research paths that may promote sustainable practices within the tourism sector.

Keywords: Behavioural Quantum Computing; Data Analytics; Sustainable Tourism; Predictive Modelling; Resource Optimization; Theoretical Underpinning; Quantum Algorithms.

Received on: 16/04/2024, Revised on: 22/06/2024, Accepted on: 29/08/2024, Published on: 09/09/2024

DOI: 10.69888/FTSTPL.2024.000331

FMDB Transactions on Sustainable Technoprise Letters, 2024 Vol. 2 No. 3, Pages: 161-170

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