How Can We Improve Hospitality Excellence for Sustainable Development Using Machine Learning

被引:2
|
作者
Gupta, Shashank [1 ]
Jaiswal, Rachana [2 ]
机构
[1] Morgan Stanley Advantage India Pvt Ltd, Nirlon Knowledge Pk, Mumbai, India
[2] HNB Garhwal A Cent Univ, Dept Business Management, Srinagar, India
关键词
Conscious consumerism; hospitality industry; sentiment analysis; signaling theory; stakeholder theory; sustainable development goals; MEDIA;
D O I
10.1080/10963758.2024.2420267
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
This study uncovers a significant shift in the hospitality landscape by acknowledging users as stakeholders, transcending traditional consumer-business interactions. It investigates how sentiment analysis and topic modeling of hotel reviews can guide sustainable practices, leveraging stakeholder and signaling theories. It analyzes a large dataset from online travel platforms; the research identifies six key themes closely linked to SDGs, offering actionable insights for aligning hotel operations with sustainability objectives. Predominantly positive guest sentiments reflect favorable experiences, highlighting the potential to enhance customer satisfaction through sustainability. The study demonstrates the effectiveness of machine learning models, particularly Random forest, in sentiment classification, while LDA effectively uncovers relevant themes. Despite limitations such as data source constraints, this research pioneers a new approach to integrating user feedback into sustainable business practices, contributing valuable insights for managers, policymakers, and the evolving landscape of conscious consumerism in the hospitality industry.
引用
收藏
页数:13
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