SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Multi-step ahead tourism demand forecasting: The perspective of the learning using privileged information paradigm
16 references·0 citing·46 second hopsampled
Multi-step ahead tourism demand forecasting: The perspective of the learning using privileged information paradigm (2022)Multi-step ahead tourism demand forecasti…Tourism Demand Forecasting: A Decomposed Deep Learning Approach (2020)Tourism Demand Forecasting: A…Daily tourism volume forecasting for tourist attractions (2020)Daily tourism volume forecast…Coronavirus pandemic and tourism: Dynamic stochastic general equilibrium modeling of infectious disease outbreak (2020)Coronavirus pandemic and tour…Bayesian BILSTM approach for tourism demand forecasting (2020)Bayesian BILSTM approach for …Using social network and semantic analysis to analyze online travel forums and forecast tourism demand (2019)Using social network and sema…Tourism demand forecasting: A deep learning approach (2019)Tourism demand forecasting: A…Forecasting tourist arrivals with machine learning and internet search index (2018)Forecasting tourist arrivals …Big data in tourism research: A literature review (2018)Big data in tourism research:…Forecasting tourism demand with composite search index (2016)Forecasting tourism demand wi…Forecasting Destination Weekly Hotel Occupancy with Big Data (2016)Forecasting Destination Weekl…Forecasting city arrivals with Google Analytics (2016)Forecasting city arrivals wit…Forecasting Chinese tourist volume with search engine data (2014)Forecasting Chinese tourist v…Forecasting tourism demand with ARMA-based methods (2008)Forecasting tourism demand wi…A Test for Superior Predictive Ability (2005)A Test for Superior Predictiv…Univariate versus multivariate time series forecasting: an application to international tourism demand (2003)Univariate versus multivariat…Time series forecasts of international travel demand for Australia (2002)Time series forecasts of inte…Applied Economic Forecasting (1967)Book Review: Time Series Analysis: Forecasting and Control (1977)Seasonal integration and cointegration (1990)Determinants of Tourist Arrivals in Africa: A Panel Data Regression Analysis (2005)Forecasting tourism recovery amid COVID-19 (2021)Comparing Predictive Accuracy (1994)Testing the equality of prediction mean squared errors (1997)A forecast comparison of volatility models: does anything beat a GARCH(1,1)? (2005)Forecasting the Equity Risk Premium: The Role of Technical Indicators (2011)Forecasting: theory and practice (2022)Tourism demand modelling and forecasting—A review of recent research (2007)The impact of financial development on carbon emissions: An empirical analysis in China (2011)Predicting the Present with Google Trends (2012)A Big Data Analytics Method for Tourist Behaviour Analysis (2016)In Search of Attention (2011)Business Intelligence and Analytics: From Big Data to Big Impact (2012)Big data: a revolution that will transform how we live, work, and think (2013)Effective tourist volume forecasting supported by PCA and improved BPNN using Baidu index (2018)Progress in information technology and tourism management: 30 years on and 20 years after the internet - Revisiting Buhalis & Law's landmark study about eTourism (2018)Forecasting tourism demand with multisource big data (2020)Forecasting, Structural Time Series Models and the Kalman Filter (1990)Twitter mood predicts the stock market (2011)Predicting overall customer satisfaction: Big data evidence from hotel online textual reviews (2018)Forecasting Chinese cruise tourism demand with big data: An optimized machine learning approach (2020)Review of tourism forecasting research with internet data (2020)Beyond the hype: Big data concepts, methods, and analytics (2014)Discovering the tourists' behaviors and perceptions in a tourism destination by analyzing photos' visual content with a computer deep learning model: The case of Beijing (2019)Asymmetric role of tourism development and technology innovation on carbon dioxide emission reduction in the Chinese economy: Fresh insights from QARDL approach (2020)Changes in air passenger demand as a result of the COVID-19 crisis: using Big Data to inform tourism policy (2020)Numerical distribution functions of likelihood ratio tests for cointegration (1999)Time Series Analysis: Forecasting and Control. (1978)Time series analysis forecasting and control (2009)Antecedents of Trust and Adoption Intention toward Artificially Intelligent Recommendation Systems in Travel Planning: A Heuristic–Systematic Model (2020)The good, the bad and the ugly on COVID-19 tourism recovery (2020)Rare Disasters and Asset Markets in the Twentieth Century* (2006)Disaster Risk and Business Cycles (2012)Impact of the COVID-19 pandemic: Evidence from the U.S. restaurant industry (2020)Social costs of tourism during the COVID-19 pandemic (2020)The SARS, MERS and novel coronavirus (COVID-19) epidemics, the newest and biggest global health threats: what lessons have we learned? (2020)Understanding the COVID-19 tourist psyche: The Evolutionary Tourism Paradigm (2020)Distribution of the Estimators for Autoregressive Time Series With a Unit Root (1979)Distribution of the Estimators for Autoregressive Time Series With a Unit Root (1979)Testing the null hypothesis of stationarity against the alternative of a unit root (1992)Forecasting Daily Tourism Demand for Tourist Attractions with Big Data: An Ensemble Deep Learning Method (2021)Tourism demand forecasting with time series imaging: A deep learning model (2021)Forecasting crude oil futures prices using BiLSTM-Attention-CNN model with Wavelet transform (2022)
this work references cited by second hop· second hop is a sample of the most-cited connections

References

  • 2005A Test for Superior Predictive Ability1,227 cited
  • 2018Big data in tourism research: A literature review1,073 cited
  • 2020Coronavirus pandemic and tourism: Dynamic stochastic general equilibrium modeling of infectious disease outbreak524 cited
  • 2019Tourism demand forecasting: A deep learning approach451 cited
  • 2014Forecasting Chinese tourist volume with search engine data432 cited
  • 2018Forecasting tourist arrivals with machine learning and internet search index381 cited
  • 2016Forecasting tourism demand with composite search index369 cited
  • 2002Time series forecasts of international travel demand for Australia279 cited
  • 2020Bayesian BILSTM approach for tourism demand forecasting235 cited
  • 2016Forecasting Destination Weekly Hotel Occupancy with Big Data229 cited
  • 2003Univariate versus multivariate time series forecasting: an application to international tourism demand227 cited
  • 2008Forecasting tourism demand with ARMA-based methods208 cited
  • 2016Forecasting city arrivals with Google Analytics187 cited
  • 2020Daily tourism volume forecasting for tourist attractions183 cited
  • 2020Tourism Demand Forecasting: A Decomposed Deep Learning Approach

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

179 cited
  • 2019Using social network and semantic analysis to analyze online travel forums and forecast tourism demand156 cited
  • Cited by

    No citing works inside the corpus for this window.