Multi‐horizon accommodation demand forecasting: A New Zealand case study-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Multi‐horizon accommodation demand forecasting: A New Zealand case study

Published:2020-10-05 Issue:3 Volume:23 Page:442-453
ISSN:1099-2340
Container-title:International Journal of Tourism Research
language:en
Short-container-title:Int J Tourism Res

Author:

Zhu Min¹,Wu Jinran²^ORCID,Wang You‐Gan²^ORCID

Affiliation:

1. Business School The University of Queensland St Lucia Queensland Australia

2. School of Mathematical Sciences Queensland University of Technology Brisbane Queensland Australia

Publisher

Wiley

Subject

Nature and Landscape Conservation,Tourism, Leisure and Hospitality Management,Transportation,Geography, Planning and Development

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jtr.2416

Reference55 articles.

1. An Empirical Comparison of Machine Learning Models for Time Series Forecasting

2. Forecasting Hotel Occupancy Rates with Time Series Models: An Empirical Analysis

3. Modeling and Forecasting Regional Tourism Demand Using the Bayesian Global Vector Autoregressive (BGVAR) Model

4. Hierarchical forecasts for Australian domestic tourism

5. A Comparative Analysis of Three Types of Tourism Demand Forecasting Models: Individual, Linear Combination and Non-linear Combination

Cited by 15 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Hotel demand forecasting with multi-scale spatiotemporal features;International Journal of Hospitality Management;2024-10

2. Decoding the future: Proposing an interpretable machine learning model for hotel occupancy forecasting using principal component analysis;International Journal of Hospitality Management;2024-08

3. Forecasting of Indian and foreign tourist arrivals to Himachal Pradesh using Decomposition, Box–Jenkins, and Holt–Winters exponential smoothing methods;Asia-Pacific Journal of Regional Science;2024-07-23

4. Machine learning applied to tourism: A systematic review;WIREs Data Mining and Knowledge Discovery;2024-07-04

5. Augmented support vector regression with an autoregressive process via an iterative procedure;Applied Soft Computing;2024-06

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3