利用在线平台数据衡量可持续旅游业。

Measuring sustainable tourism with online platform data.

作者信息

Hoffmann Felix J, Braesemann Fabian, Teubner Timm

机构信息

Trust in Digital Services, Technische Universität Berlin, 10623 Berlin, Germany.

Oxford Internet Institute, University of Oxford, OX1 3JS Oxford, UK.

出版信息

EPJ Data Sci. 2022;11(1):41. doi: 10.1140/epjds/s13688-022-00354-6. Epub 2022 Jul 18.

DOI:10.1140/epjds/s13688-022-00354-6

PMID:35873664

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9289659/

Abstract

UNLABELLED

Sustainability in tourism is a topic of global relevance, finding multiple mentions in the United Nations Sustainable Development Goals. The complex task of balancing tourism's economic, environmental, and social effects requires detailed and up-to-date data. This paper investigates whether online platform data can be employed as an alternative data source in sustainable tourism statistics. Using a web-scraped dataset from a large online tourism platform, a sustainability label for accommodations can be predicted reasonably well with machine learning techniques. The algorithmic prediction of accommodations' sustainability using online data can provide a cost-effective and accurate measure that allows to track developments of tourism sustainability across the globe with high spatial and temporal granularity.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1140/epjds/s13688-022-00354-6.

摘要

未标注

旅游业的可持续性是一个具有全球相关性的话题，在联合国可持续发展目标中被多次提及。平衡旅游业的经济、环境和社会影响这一复杂任务需要详细且最新的数据。本文研究在线平台数据是否可以作为可持续旅游统计中的替代数据源。使用从一个大型在线旅游平台抓取的网络数据集，借助机器学习技术能够较好地预测住宿的可持续性标签。利用在线数据对住宿的可持续性进行算法预测，可以提供一种经济高效且准确的衡量方法，从而能够以高时空粒度追踪全球旅游业可持续性的发展情况。