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Ulrich Gunter

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Tröster, Bernhard & Gunter, Ulrich, 2022. "Trading for speculators: The role of physical actors in the financialization of coffee, cocoa and cotton value chains," Working Papers 68, Austrian Foundation for Development Research (ÖFSE).

    Cited by:

    1. Algirdas Justinas Staugaitis & Bernardas Vaznonis, 2022. "Financial Speculation Impact on Agricultural and Other Commodity Return Volatility: Implications for Sustainable Development and Food Security," Agriculture, MDPI, vol. 12(11), pages 1-27, November.
    2. Pantoja-Robayo, Javier & Rodriguez-Guevara, David, 2023. "The Climate Effect on Colombian Coffee Prices and Quantities Based on Risk Analysis and the Hedging Strategy in Discrete Setting Approach," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 15(4), December.

  2. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.

    Cited by:

    1. Nie, Yan & Zhang, Guoxing & Zhong, Luhao & Su, Bin & Xi, Xi, 2024. "Urban‒rural disparities in household energy and electricity consumption under the influence of electricity price reform policies," Energy Policy, Elsevier, vol. 184(C).
    2. Yu Jeffrey Hu & Jeroen Rombouts & Ines Wilms, 2025. "Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms," Information Systems Research, INFORMS, vol. 36(1), pages 552-571, March.
    3. Julia Eichholz & Thorsten Knauer & Sandra Winkelmann, 2023. "Digital Maturity of Forecasting and its Impact in Times of Crisis," Schmalenbach Journal of Business Research, Springer, vol. 75(4), pages 443-481, December.
    4. Said Rosli & Sulaimi Mardhiati & Majid Rohayu Ab & Aini Ainoriza Mohd & Olanrele Olusegun Olaopin & Akinsomi Omokolade, 2024. "Evaluating Market Attributes and Housing Affordability: Gaining Perspective on Future Value Trends," Real Estate Management and Valuation, Paradigm, vol. 32(3), pages 87-100.
    5. Xing, Xiaoxuan & Gong, Dunwei & Wang, Yan & Sun, Xiaoyan & Zhang, Yong, 2025. "Acceptable cost-driven multivariate load forecasting for integrated coal mine energy systems," Applied Energy, Elsevier, vol. 397(C).
    6. Afif Zuhri Muhammad Khodri Harahap & Mohd Kamarul Irwan Abdul Rahim & Noor Malinjasari & Suzila Mat Salleh & Rabiatul Adawiyah Ma'arof, 2025. "Enhancing the Inventory Management through Demand Forecasting," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(1), pages 2737-2744, January.
    7. Pei, Ming & Gong, Ruqing & Ye, Lin & Chen, Lei & Sun, Yihui & Tang, Yong, 2026. "Spatiotemporal sparse autoregressive distributed lag model with extended Regressors for regional wind power forecasting," Applied Energy, Elsevier, vol. 404(C).
    8. Zin Mar Oo & Ching‐Yang Lin & Makoto Kakinaka, 2025. "Deciphering Long‐Term Economic Growth: An Exploration With Leading Machine Learning Techniques," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(4), pages 1531-1562, July.
    9. Martin McCarthy, Stephen Snudden, 2024. "Forecasts of Period-Average Exchange Rates: New Insights from Real-Time Daily Data," LCERPA Working Papers jc0148, Laurier Centre for Economic Research and Policy Analysis, revised Oct 2024.
    10. Raja, Aitazaz Ali & Pinson, Pierre & Kazempour, Jalal & Grammatico, Sergio, 2024. "A market for trading forecasts: A wagering mechanism," International Journal of Forecasting, Elsevier, vol. 40(1), pages 142-159.
    11. Marco Zanotti, 2025. "On the stability of global forecasting models," Working Papers 553, University of Milano-Bicocca, Department of Economics.
    12. Qi Zheng & Yunwei Cui & Rongning Wu, 2024. "On estimation of nonparametric regression models with autoregressive and moving average errors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 76(2), pages 235-262, April.
    13. Karamolegkos, Spyridon & Koulouriotis, Dimitrios E., 2025. "Advancing short-term load forecasting with decomposed Fourier ARIMA: A case study on the Greek energy market," Energy, Elsevier, vol. 325(C).
    14. Caljon, Daan & Vercauteren, Jeff & De Vos, Simon & Verbeke, Wouter & Van Belle, Jente, 2026. "Using dynamic loss weighting to boost improvements in forecast stability," International Journal of Forecasting, Elsevier, vol. 42(2), pages 344-358.
    15. Simon Hirsch & Jonathan Berrisch & Florian Ziel, 2024. "Online Distributional Regression," Papers 2407.08750, arXiv.org, revised Apr 2026.
    16. Amjad Almusaed & Ibrahim Yitmen & Asaad Almssad, 2023. "Enhancing Smart Home Design with AI Models: A Case Study of Living Spaces Implementation Review," Energies, MDPI, vol. 16(6), pages 1-23, March.
    17. Cheng Zhang, 2026. "A Nontrivial Upper Bound on the Out-of-Sample $R^2$ in Return Forecasting," Papers 2602.07841, arXiv.org, revised Apr 2026.
    18. Jozef Barunik & Lubos Hanus, 2023. "Learning the Probability Distributions of Day-Ahead Electricity Prices," Papers 2310.02867, arXiv.org, revised Jul 2025.
    19. Ghelasi, Paul & Ziel, Florian, 2026. "A data-driven merit order: Learning a fundamental electricity price model," Energy Economics, Elsevier, vol. 154(C).
    20. Diego Zappa & Gian Paolo Clemente & Francesco Della Corte & Nino Savelli, 2023. "Editorial on the Special Issue on Insurance: complexity, risks and its connection with social sciences," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 125-130, December.
    21. Yi Ding & Peng Wu & Jie Zhao & Ligang Zhou, 2025. "Forecasting product sales using text mining: a case study in new energy vehicle," Electronic Commerce Research, Springer, vol. 25(1), pages 495-527, February.
    22. Ricardo Caetano & José Manuel Oliveira & Patrícia Ramos, 2025. "Transformer-Based Models for Probabilistic Time Series Forecasting with Explanatory Variables," Mathematics, MDPI, vol. 13(5), pages 1-29, February.
    23. Ca’ Zorzi, Michele & Rubaszek, Michał, 2023. "How many fundamentals should we include in the behavioral equilibrium exchange rate model?," Economic Modelling, Elsevier, vol. 118(C).
    24. Kafa, Nadine & Babai, M. Zied & Klibi, Walid, 2025. "Forecasting mail flow: A hierarchical approach for enhanced societal wellbeing," International Journal of Forecasting, Elsevier, vol. 41(1), pages 51-65.
    25. Racek, Daniel & Thurner, Paul W. & Davidson, Brittany I. & Zhu, Xiao Xiang & Kauermann, Göran, 2024. "Conflict forecasting using remote sensing data: An application to the Syrian civil war," International Journal of Forecasting, Elsevier, vol. 40(1), pages 373-391.
    26. Huang, Congzhi & Yang, Mengyuan, 2023. "Memory long and short term time series network for ultra-short-term photovoltaic power forecasting," Energy, Elsevier, vol. 279(C).
    27. Marco Zanotti, 2025. "Do global forecasting models require frequent retraining?," Working Papers 551, University of Milano-Bicocca, Department of Economics.
    28. Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024. "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
    29. Wesley Marcos Almeida & Claudimar Pereira Veiga, 2023. "Does demand forecasting matter to retailing?," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(2), pages 219-232, June.
    30. Anna Sznajderska & Alfred A. Haug, 2023. "Bayesian VARs of the U.S. economy before and during the pandemic," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(2), pages 211-236, June.
    31. Coleen Tala & Romeo T. Quintos Jr, 2025. "Sipnayan sa Tambakan: Mathematical Ethnomodels Through the Lens of the Scrap Merchants," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(9), pages 3934-3957, September.
    32. Babai, M. Zied & Syntetos, Aris A. & Teunter, Ruud H., 2026. "Fifty years of inventory research from a forecasting perspective," European Journal of Operational Research, Elsevier, vol. 331(1), pages 1-20.
    33. Li, Xiaoyuan & Tian, Zhe & Wu, Xia & Feng, Wei & Niu, Jide, 2024. "Optimal planning for hybrid renewable energy systems under limited information based on uncertainty quantification," Renewable Energy, Elsevier, vol. 237(PD).
    34. Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022. "Distributional neural networks for electricity price forecasting," Papers 2207.02832, arXiv.org, revised Dec 2022.
    35. Minghao Ran & Yingchao Wang & Qilu Qin & Jindi Huang & Jiading Jiang, 2025. "An Improved Grey Prediction Model Integrating Periodic Decomposition and Aggregation for Renewable Energy Forecasting: Case Studies of Solar and Wind Power," Sustainability, MDPI, vol. 17(11), pages 1-31, May.
    36. Bernhard Tröster & Ulrich Gunter, 2023. "The Financialization of Coffee, Cocoa and Cotton Value Chains: The Role of Physical Actors," Development and Change, International Institute of Social Studies, vol. 54(6), pages 1550-1574, November.
    37. Tetiana Zatonatska & Olena Liashenko & Yana Fareniuk & Oleksandr Dluhopolskyi & Artur Dmowski & Marzena Cichorzewska, 2022. "The Migration Influence on the Forecasting of Health Care Budget Expenditures in the Direction of Sustainability: Case of Ukraine," Sustainability, MDPI, vol. 14(21), pages 1-17, November.
    38. Chȩć, Katarzyna & Uniejewski, Bartosz & Weron, Rafał, 2025. "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," Journal of Commodity Markets, Elsevier, vol. 37(C).
    39. Marc Wildi, 2026. "Forecasting on the Accuracy-Timeliness Frontier: Two Novel `Look Ahead' Predictors," Papers 2602.23087, arXiv.org.
    40. Singhal, Shakshi & Bano, Yasmeen & Gautam, Prerna, 2026. "Changepoint model for energy-efficient technology diffusion: A comparative evaluation of empirical models," Technovation, Elsevier, vol. 149(C).
    41. Jeroen Rombouts & Marie Ternes & Ines Wilms, 2024. "Cross-Temporal Forecast Reconciliation at Digital Platforms with Machine Learning," Papers 2402.09033, arXiv.org, revised May 2024.
    42. Jonathan Berrisch & Florian Ziel, 2022. "Distributional modeling and forecasting of natural gas prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1065-1086, September.
    43. Oscar Espinosa & Valeria Bejarano & Jeferson Ramos & Boris Martínez, 2023. "Statistical actuarial estimation of the Capitation Payment Unit from copula functions and deep learning: historical comparability analysis for the Colombian health system, 2015–2021," Health Economics Review, Springer, vol. 13(1), pages 1-20, December.
    44. Wang, Lu & Wang, Xing & Liang, Chao, 2024. "Natural gas volatility prediction via a novel combination of GARCH-MIDAS and one-class SVM," The Quarterly Review of Economics and Finance, Elsevier, vol. 98(C).
    45. Meisenbacher, Stefan & Phipps, Kaleb & Taubert, Oskar & Weiel, Marie & Götz, Markus & Mikut, Ralf & Hagenmeyer, Veit, 2025. "AutoPQ: Automating quantile estimation from point forecasts in the context of sustainability," Applied Energy, Elsevier, vol. 392(C).
    46. Shanshan Wang & Shih‐Chih Chen & Mohd Helmi Ali & Ming‐Lang Tseng, 2024. "Nexus of environmental, social, and governance performance in China‐listed companies: Disclosure and green bond issuance," Business Strategy and the Environment, Wiley Blackwell, vol. 33(3), pages 1647-1660, March.
    47. Alroomi, Azzam & Karamatzanis, Georgios & Nikolopoulos, Konstantinos & Tilba, Anna & Xiao, Shujun, 2022. "Fathoming empirical forecasting competitions’ winners," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1519-1525.
    48. Rai, Amit & Shrivastava, Ashish & Jana, Kartick C., 2023. "Differential attention net: Multi-directed differential attention based hybrid deep learning model for solar power forecasting," Energy, Elsevier, vol. 263(PC).
    49. Marco Zanotti, 2025. "The cost of ensembling: is it always worth combining?," Working Papers 554, University of Milano-Bicocca, Department of Economics.
    50. Anita M. Bunea & Mariangela Guidolin & Piero Manfredi & Pompeo Della Posta, 2022. "Diffusion of Solar PV Energy in the UK: A Comparison of Sectoral Patterns," Forecasting, MDPI, vol. 4(2), pages 1-21, April.
    51. Zheng, Zhuang & Shafique, Muhammad & Luo, Xiaowei & Wang, Shengwei, 2024. "A systematic review towards integrative energy management of smart grids and urban energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    52. Fernández, Joaquín Delgado & Menci, Sergio Potenciano & Lee, Chul Min & Rieger, Alexander & Fridgen, Gilbert, 2022. "Privacy-preserving federated learning for residential short-term load forecasting," Applied Energy, Elsevier, vol. 326(C).
    53. Lesia Korolchuk, 2023. "Application of forecasting methods in harmonising strategic planning for sustainable development of the state," E-Forum Working Papers, Economic Forum, vol. 14(1), pages 50-61, December.
    54. Singhal, Shakshi & Bano, Yasmeen & Singh, Ompal, 2025. "Investigating the role of customer's disadoption and dynamic shifts in mobile cellular diffusion: Evidence from emerging economies," Technological Forecasting and Social Change, Elsevier, vol. 219(C).
    55. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 308-321.
    56. Li, Xin & Xu, Yechi & Law, Rob & Wang, Shouyang, 2024. "Enhancing tourism demand forecasting with a transformer-based framework," Annals of Tourism Research, Elsevier, vol. 107(C).
    57. Paul Ghelasi & Florian Ziel, 2023. "Hierarchical forecasting for aggregated curves with an application to day-ahead electricity price auctions," Papers 2305.16255, arXiv.org.
    58. Augusto Cerqua & Marco Letta & Gabriele Pinto, 2024. "On the (Mis)Use of Machine Learning with Panel Data," Papers 2411.09218, arXiv.org, revised May 2025.
    59. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    60. Allen, Sam & Koh, Jonathan & Segers, Johan & Ziegel, Johanna, 2024. "Tail calibration of probabilistic forecasts," LIDAM Discussion Papers ISBA 2024018, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    61. Jan Čapek & Jakub Chalmovianský & Vlastimil Reichel, 2026. "Macroeconomic forecasting during recessions and expansions in the US and the euro area," Economic Inquiry, Western Economic Association International, vol. 64(3), pages 1055-1078, July.
    62. Janczura, Joanna & Wójcik, Edyta, 2022. "Dynamic short-term risk management strategies for the choice of electricity market based on probabilistic forecasts of profit and risk measures. The German and the Polish market case study," Energy Economics, Elsevier, vol. 110(C).
    63. Heymann, Fabian & Milojevic, Tatjana & Covatariu, Andrei & Verma, Piyush, 2023. "Digitalization in decarbonizing electricity systems – Phenomena, regional aspects, stakeholders, use cases, challenges and policy options," Energy, Elsevier, vol. 262(PB).
    64. Spiliotis, Evangelos & Petropoulos, Fotios, 2024. "On the update frequency of univariate forecasting models," European Journal of Operational Research, Elsevier, vol. 314(1), pages 111-121.
    65. Cakici, Nusret & Zaremba, Adam, 2025. "Accounting vs technical information: what matters more for stock return predictability?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 104(C).
    66. Entezari, Negin & Fuinhas, José Alberto, 2024. "Measuring wholesale electricity price risk from climate change: Evidence from Portugal," Utilities Policy, Elsevier, vol. 91(C).
    67. Chen Chuanglian & Lin Huanheng & Lin Yuting, 2026. "Deep Learning‐Based Network Relationship Construction Method and Its Impact on Futures Risk Premiums," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 46(1), pages 175-196, January.
    68. Ramos, Paulo Vitor B. & Villela, Saulo Moraes & Silva, Walquiria N. & Dias, Bruno H., 2023. "Residential energy consumption forecasting using deep learning models," Applied Energy, Elsevier, vol. 350(C).
    69. Ghelasi, Paul & Ziel, Florian, 2024. "Hierarchical forecasting for aggregated curves with an application to day-ahead electricity price auctions," International Journal of Forecasting, Elsevier, vol. 40(2), pages 581-596.
    70. Samartzis, Panagiotis, 2025. "Predicting the relative performance among financial assets: A comparative analysis of different approaches," International Journal of Forecasting, Elsevier, vol. 41(4), pages 1428-1449.
    71. Pedersen, Michael, 2025. "Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence," International Journal of Forecasting, Elsevier, vol. 41(2), pages 475-486.
    72. Jacek Batóg & Barbara Batóg & Magdalena Mojsiewicz & Przemysław Pluskota, 2024. "Electrification of Public Urban Transport: Funding Opportunities, Bus Fleet, and Energy Use Forecasts for Poland," Energies, MDPI, vol. 17(23), pages 1-20, December.
    73. Matthias Hertel & Sebastian Pütz & Ralf Mikut & Veit Hagenmeyer & Benjamin Schäfer, 2026. "Explainable time-series forecasting with sampling-free SHAP for Transformers," Nature Communications, Nature, vol. 17(1), pages 1-16, December.
    74. Katarzyna Chec & Bartosz Uniejewski & Rafal Weron, 2026. "From biased point forecasts of electricity demand to accurate predictive distributions: Using LASSO and GAMLSS," WORking papers in Management Science (WORMS) WORMS/26/01, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    75. Mascarenhas, Maria Margarida & De Blauwe, Jilles & Amelin, Mikael & Kazmi, Hussain, 2026. "Leveraging asynchronous cross-border market data for improved day-ahead electricity price forecasting in European markets," Applied Energy, Elsevier, vol. 404(C).
    76. Wang, Shengjie & Kang, Yanfei & Petropoulos, Fotios, 2024. "Combining probabilistic forecasts of intermittent demand," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1038-1048.
    77. Caravaggio, Nicola & Resce, Giuliano & Vaquero-Piñeiro, Cristina, 2025. "Predicting policy funding allocation with Machine Learning," Socio-Economic Planning Sciences, Elsevier, vol. 98(C).
    78. Victoria A Bensel & Kelsey Corcoran & Anthony J Lisi, 2025. "Forecasting the use of chiropractic services within the Veterans Health Administration," PLOS ONE, Public Library of Science, vol. 20(1), pages 1-8, January.
    79. Katarzyna Maciejowska & Weronika Nitka, 2024. "Multiple split approach -- multidimensional probabilistic forecasting of electricity markets," Papers 2407.07795, arXiv.org.
    80. Divya Aggarwal & Sougata Banerjee, 2025. "Forecasting of S&P 500 ESG Index by Using CEEMDAN and LSTM Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 339-355, March.
    81. Bergsteinsson, Hjörleifur G. & Sørensen, Mikkel Lindstrøm & Møller, Jan Kloppenborg & Madsen, Henrik, 2023. "Heat load forecasting using adaptive spatial hierarchies," Applied Energy, Elsevier, vol. 350(C).
    82. Malte C. Tichy & Illia Babounikau & Nikolas Wolke & Stefan Ulbrich & Michael Feindt, 2026. "Scaling‐Aware Rating of Poisson‐Limited Demand Forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 45(2), pages 787-805, March.
    83. Lv, Yichen & Gao, Mingyun & Xiao, Xinping, 2026. "Unbiased forecasting of seasonal wind power generation based on a novel seasonal multivariable grey model," Renewable Energy, Elsevier, vol. 258(C).
    84. Nghia Chu & Binh Dao & Nga Pham & Huy Nguyen & Hien Tran, 2022. "Predicting Mutual Funds' Performance using Deep Learning and Ensemble Techniques," Papers 2209.09649, arXiv.org, revised Jul 2023.
    85. Mutele, Litshedzani & Carranza, Emmanuel John M., 2024. "Statistical analysis of gold production in South Africa using ARIMA, VAR and ARNN modelling techniques: Extrapolating future gold production, Resources–Reserves depletion, and Implication on South Africa's gold exploration," Resources Policy, Elsevier, vol. 93(C).
    86. Takahashi, Carlos Kazunari & Figueiredo, Júlio César Bastos de & Scornavacca, Eusebio, 2024. "Investigating the diffusion of innovation: A comprehensive study of successive diffusion processes through analysis of search trends, patent records, and academic publications," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    87. Li, Xishu & Zuidwijk, Rob & de Koster, M.B.M, 2023. "Optimal competitive capacity strategies: Evidence from the container shipping market," Omega, Elsevier, vol. 115(C).
    88. Pan Tang & Yuwei Zhang, 2024. "China's business cycle forecasting: a machine learning approach," Computational Economics, Springer;Society for Computational Economics, vol. 64(5), pages 2783-2811, November.
    89. Shi, Qi, 2025. "Technical indicators and aggregate stock returns: An updated look," Journal of Multinational Financial Management, Elsevier, vol. 77(C).
    90. Richard Bean, 2023. "Forecasting the Monash Microgrid for the IEEE-CIS Technical Challenge," Energies, MDPI, vol. 16(3), pages 1-23, January.
    91. Alex Tschan & Lars Hetzel & Ralf Eisinger & Carolin Eggen & Claudia Heuser & Victoria Fritz, 2025. "Data-Driven Inventory Control and Integrated Employee Involvement for Special Buys at ALDI SÜD Germany," Interfaces, INFORMS, vol. 55(1), pages 22-35, January.
    92. Shafie Bahman & Hamidreza Zareipour, 2025. "Long-Term Multi-Resolution Probabilistic Load Forecasting Using Temporal Hierarchies," Energies, MDPI, vol. 18(11), pages 1-30, June.
    93. Emmanuel Senyo Fianu, 2022. "Analyzing and Forecasting Multi-Commodity Prices Using Variants of Mode Decomposition-Based Extreme Learning Machine Hybridization Approach," Forecasting, MDPI, vol. 4(2), pages 1-27, June.
    94. Safdar, Muhammad & Zhong, Ming & Ren, Zhi & Li, Linfeng & Raza, Asif & Hunt, John Douglas, 2026. "An integrated spatial economic modeling framework for forecasting inland waterway freight demand," Transport Policy, Elsevier, vol. 176(C).
    95. Mingzhe Shi & Bahman Rostami-Tabar & Daniel Gartner, 2025. "Looking for the crystal ball in unscheduled care: a systematic literature review of the forecasting process," Health Care Management Science, Springer, vol. 28(3), pages 548-564, September.
    96. Cristiana Tudor & Robert Sova, 2025. "An automated adaptive trading system for enhanced performance of emerging market portfolios," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-39, December.
    97. Joanna Janczura & Andrzej Puć, 2023. "ARX-GARCH Probabilistic Price Forecasts for Diversification of Trade in Electricity Markets—Variance Stabilizing Transformation and Financial Risk-Minimizing Portfolio Allocation," Energies, MDPI, vol. 16(2), pages 1-28, January.
    98. Elalem, Yara Kayyali & Maier, Sebastian & Seifert, Ralf W., 2023. "A machine learning-based framework for forecasting sales of new products with short life cycles using deep neural networks," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1874-1894.
    99. Brown, David P. & Cajueiro, Daniel O. & Eckert, Andrew & Silveira, Douglas, 2025. "Evaluating the role of information disclosure on bidding behavior in wholesale electricity markets," Energy Economics, Elsevier, vol. 146(C).
    100. Theodorou, Evangelos & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2025. "Forecast accuracy and inventory performance: Insights on their relationship from the M5 competition data," European Journal of Operational Research, Elsevier, vol. 322(2), pages 414-426.
    101. Jun Meng & Jingfang Fan & Uma S. Bhatt & Jürgen Kurths, 2023. "Arctic weather variability and connectivity," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    102. Emanuela Raffinetti, 2023. "A Rank Graduation Accuracy measure to mitigate Artificial Intelligence risks," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 131-150, December.
    103. Marta Crispino & Vincenzo Mariani, 2025. "A Tool to Nowcast Tourist Overnight Stays with Payment Data and Complementary Indicators," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 11(1), pages 285-312, March.
    104. Aitazaz Ali Raja & Pierre Pinson & Jalal Kazempour & Sergio Grammatico, 2022. "A Market for Trading Forecasts: A Wagering Mechanism," Papers 2205.02668, arXiv.org, revised Oct 2022.
    105. Conigliani, Caterina & Costantini, Valeria & Paglialunga, Elena & Tancredi, Andrea, 2024. "Forecasting the climate-conflict risk in Africa along climate-related scenarios and multiple socio-economic drivers," Economic Modelling, Elsevier, vol. 141(C).
    106. Wang, Xiaoqian & Kang, Yanfei & Hyndman, Rob J. & Li, Feng, 2023. "Distributed ARIMA models for ultra-long time series," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1163-1184.
    107. Katarzyna Chk{e}'c & Bartosz Uniejewski & Rafa{l} Weron, 2025. "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," Papers 2503.02518, arXiv.org.
    108. Robinson Kruse‐Becher, 2025. "Adaptive Now‐ and Forecasting of Global Temperatures Under Smooth Structural Changes," Environmetrics, John Wiley & Sons, Ltd., vol. 36(6), September.
    109. Abdelfatah, Omar Sharafeldin Mohamed, 2026. "Machine Learning Approaches for Improving Demand Forecasting Accuracy in Retail Supply Chains," SocArXiv 4z9be_v1, Center for Open Science.
    110. Bogdan Oancea & Mihaela Simionescu & Richard Pospisil, 2025. "Do Machine Learning Techniques Outperform Autoregressive Distributed Lag Models in Inflation Forecasting?," Prague Economic Papers, Prague University of Economics and Business, vol. 2025(4), pages 495-558.
    111. Filipe R. Ramos & Luisa M. Martinez & Luis F. Martinez & Ricardo Abreu & Lihki Rubio, 2025. "Mapping e-commerce trends in the USA: a time series and deep learning approach," Journal of Marketing Analytics, Palgrave Macmillan, vol. 13(3), pages 606-634, September.
    112. Ye, Wenxin & An, Kangxin & Zhang, Shihui & Zhen, Zihan & Cai, Wenjia & Wang, Can, 2026. "Probabilistic analysis of tripling global renewables based on Bayesian-inferred growth dynamics model," Renewable Energy, Elsevier, vol. 256(PG).
    113. An, Min Jeong & Jung, Seung Hwan & Lee, Dong Hee, 2025. "Demand forecasting in micro-fulfillment centers using association rule-based machine learning," International Journal of Production Economics, Elsevier, vol. 290(C).
    114. Agakishiev, Ilyas & Härdle, Wolfgang Karl & Kopa, Milos & Kozmik, Karel & Petukhina, Alla, 2025. "Multivariate probabilistic forecasting of electricity prices with trading applications," Energy Economics, Elsevier, vol. 141(C).
    115. Paul Ghelasi & Florian Ziel, 2025. "A data-driven merit order: Learning a fundamental electricity price model," Papers 2501.02963, arXiv.org, revised Nov 2025.
    116. Niklas Valentin Lehmann, 2023. "Forecasting skill of a crowd-prediction platform: A comparison of exchange rate forecasts," Papers 2312.09081, arXiv.org, revised May 2025.
    117. Silvia Golia & Luigi Grossi & Matteo Pelagatti, 2022. "Machine Learning Models and Intra-Daily Market Information for the Prediction of Italian Electricity Prices," Forecasting, MDPI, vol. 5(1), pages 1-21, December.
    118. Li, Xin & Xu, Yechi & Law, Rob & Wang, Shouyang, 2024. "Enhancing Tourism Demand Forecasting with a Transformer-based Framework," SocArXiv 5ezn3_v1, Center for Open Science.
    119. Fałdziński, Marcin & Fiszeder, Piotr & Molnár, Peter, 2024. "Improving volatility forecasts: Evidence from range-based models," The North American Journal of Economics and Finance, Elsevier, vol. 69(PB).
    120. Qi, Lingzhi & Li, Xixi & Wang, Qiang & Jia, Suling, 2023. "fETSmcs: Feature-based ETS model component selection," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1303-1317.
    121. Kwas, Marek & Paccagnini, Alessia & Rubaszek, Michał, 2022. "Common factors and the dynamics of cereal prices. A forecasting perspective," Journal of Commodity Markets, Elsevier, vol. 28(C).
    122. Guo, Su & Zheng, Kun & He, Yi & Kurban, Aynur, 2023. "The artificial intelligence-assisted short-term optimal scheduling of a cascade hydro-photovoltaic complementary system with hybrid time steps," Renewable Energy, Elsevier, vol. 202(C), pages 1169-1189.
    123. Walaa M. Rezk, 2025. "The Impact of Digital Economy Development on Total Factor Productivity in Saudi Arabia: A Panel Data Analysis," SAGE Open, , vol. 15(4), pages 21582440251, November.
    124. Swaminathan, Kritika & Venkitasubramony, Rakesh, 2024. "Demand forecasting for fashion products: A systematic review," International Journal of Forecasting, Elsevier, vol. 40(1), pages 247-267.
    125. Andrea Savio & Luigi De Giovanni & Mariangela Guidolin, 2022. "Modelling Energy Transition in Germany: An Analysis through Ordinary Differential Equations and System Dynamics," Forecasting, MDPI, vol. 4(2), pages 1-18, April.
    126. Radovan Šomplák & Veronika Smejkalová & Martin Rosecký & Lenka Szásziová & Vlastimír Nevrlý & Dušan Hrabec & Martin Pavlas, 2023. "Comprehensive Review on Waste Generation Modeling," Sustainability, MDPI, vol. 15(4), pages 1-29, February.
    127. Easton Huch & Candace Berrett & Mason Ferlic & Kimberly F. Sellers, 2026. "Forecasting Count Data With Varying Dispersion: A Latent‐Variable Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 45(4), pages 1985-2000, July.
    128. Ye, Lili & Xie, Naiming & Boylan, John E. & Shang, Zhongju, 2024. "Forecasting seasonal demand for retail: A Fourier time-varying grey model," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1467-1485.
    129. Pierre Pinson & Mikkel Bjørn & Simon Kristiansen & Claus B. Nielsen & Lasse Janerka & Jesper Skovgaard & Kristian Durhuus, 2025. "Data-Driven at Sea: Forecasting and Revenue Management at Molslinjen," Interfaces, INFORMS, vol. 55(1), pages 5-21, January.

  3. Costantini, Mauro & Gunter, Ulrich & Kunst, Robert M., 2014. "Forecast combinations in a DSGE-VAR lab," Economics Series 309, Institute for Advanced Studies.

    Cited by:

    1. Bingzi Jin & Xiaojie Xu, 2025. "Predicting open interest in thermal coal futures using machine learning," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 38(4), pages 795-809, December.
    2. Bingzi Jin & Xiaojie Xu, 2026. "Employing Gaussian process regression with Bayesian inference to predict the living-materials producer price index in China," Quality & Quantity: International Journal of Methodology, Springer, vol. 60(2), pages 4091-4129, April.
    3. Bingzi Jin & Xiaojie Xu, 2026. "Machine learning wholesale white wheat price index forecasts," Quality & Quantity: International Journal of Methodology, Springer, vol. 60(1), pages 277-305, February.
    4. Timo Dimitriadis & Xiaochun Liu & Julie Schnaitmann, 2020. "Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary," Papers 2009.07341, arXiv.org.
    5. Bingzi Jin & Xiaojie Xu, 2025. "Predictions of residential property price indices for China via machine learning models," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(2), pages 1481-1513, April.
    6. Ulrich Gunter, 2021. "Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests," Forecasting, MDPI, vol. 3(4), pages 1-36, November.
    7. Bingzi Jin & Xiaojie Xu, 2025. "Machine learning price index forecasts of flat steel products," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 38(1), pages 97-117, March.
    8. Bingzi Jin & Xiaojie Xu, 2025. "Steel price index forecasts through machine learning for northwest China," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 38(4), pages 811-833, December.
    9. Ulrich Gunter & Irem Önder & Egon Smeral, 2020. "Are Combined Tourism Forecasts Better at Minimizing Forecasting Errors?," Forecasting, MDPI, vol. 2(3), pages 1-19, June.

Articles

  1. Bernhard Tröster & Ulrich Gunter, 2023. "The Financialization of Coffee, Cocoa and Cotton Value Chains: The Role of Physical Actors," Development and Change, International Institute of Social Studies, vol. 54(6), pages 1550-1574, November.

    Cited by:

    1. Cristian Camilo Ordoñez & Mario Muñoz Organero & Gustavo Ramirez-Gonzalez & Juan Carlos Corrales, 2024. "Smart Contracts as a Tool to Support the Challenges of Buying and Selling Coffee Futures Contracts in Colombia," Agriculture, MDPI, vol. 14(6), pages 1-20, May.

  2. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    See citations under working paper version above.
  3. Irem Önder & Ulrich Gunter, 2022. "Blockchain: Is it the future for the tourism and hospitality industry?," Tourism Economics, , vol. 28(2), pages 291-299, March.

    Cited by:

    1. Ram Narayan & Anita Gehlot & Rajesh Singh & Shaik Vaseem Akram & Neeraj Priyadarshi & Bhekisipho Twala, 2022. "Hospitality Feedback System 4.0: Digitalization of Feedback System with Integration of Industry 4.0 Enabling Technologies," Sustainability, MDPI, vol. 14(19), pages 1-18, September.
    2. Richard Carey & Claire G. Coleman & Tim M. White, 2024. "The Impact of Blockchain on Logistics and Supply Chain Management: A Review," Journal of Procurement and Supply Chain Management, Global Peer Reviewed Journals, vol. 3(1), pages 1-11.
    3. Yassine Mountije & Dora Agapito & Celia Ramos, 2025. "Reshaping the future of tourism & hospitality industry through blockchain technology: a systematic literature review," Information Technology & Tourism, Springer, vol. 27(2), pages 317-343, June.
    4. Liping Fu & Jie Yang & Yongqing Dong & Tong Pei, 2025. "How does information and communication technology promote tourism development? Evidence from the e-commerce pilot city policy in China," Tourism Economics, , vol. 31(2), pages 332-358, March.
    5. T. D. Dang & M. T. Nguyen, 2023. "Systematic review and research agenda for the tourism and hospitality sector: co-creation of customer value in the digital age," Future Business Journal, Springer, vol. 9(1), pages 1-14, December.
    6. Valentina Ndou & Gioconda Mele & Eglantina Hysa & Otilia Manta, 2022. "Exploiting Technology to Deal with the COVID-19 Challenges in Travel & Tourism: A Bibliometric Analysis," Sustainability, MDPI, vol. 14(10), pages 1-25, May.
    7. Li Zhou & Chunqiao Tan & Huimin Zhao, 2022. "Information Disclosure Decision for Tourism O2O Supply Chain Based on Blockchain Technology," Mathematics, MDPI, vol. 10(12), pages 1-21, June.
    8. Alina Petronela Pricope Vancia & Codruța Adina Băltescu & Gabriel Brătucu & Alina Simona Tecău & Ioana Bianca Chițu & Liliana Duguleană, 2023. "Examining the Disruptive Potential of Generation Z Tourists on the Travel Industry in the Digital Age," Sustainability, MDPI, vol. 15(11), pages 1-19, May.
    9. Tarik Dogru & Nathana Line & Lydia Hanks & Fulya Acikgoz & Je’Anna Abbott & Selim Bakir & Adiyukh Berbekova & Anil Bilgihan & Ali Iskender & Murat Kizildag & Minwoo Lee & Woojin Lee & Sean McGinley , 2024. "The implications of generative artificial intelligence in academic research and higher education in tourism and hospitality," Tourism Economics, , vol. 30(5), pages 1083-1094, August.
    10. Raffaella Folgieri & Sergej Gričar & Tea Baldigara, 2025. "Methodological Framework as a Decision-Support Tool in Addressing NFTs and Blockchain Projects in the Tourism Industry," Administrative Sciences, MDPI, vol. 15(6), pages 1-16, June.
    11. Albert Fornells Herrera & Agustina Paradela Morgan & Jordi Ficapal Mestres, 2024. "Navigating the Technological Landscape in Hospitality: Added Values and Entry Barriers of Technologies 4.0," SAGE Open, , vol. 14(4), pages 21582440241, November.
    12. Ana María García-López & Luis Galindo-Pérez-de-Azpillaga & Concepción Foronda-Robles, 2025. "The Flow of Digital Transition: The Challenges of Technological Solutions for Hotels," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 178(3), pages 1323-1346, July.

  4. Bozana Zekan & Ulrich Gunter, 2022. "Zooming into Airbnb listings of European cities: Further investigation of the sector’s competitiveness," Tourism Economics, , vol. 28(3), pages 772-794, May.

    Cited by:

    1. Ulrich Gunter & Bozana Zekan & Francesco Luigi Milone, 2025. "Modelling and forecasting European Airbnb occupancy during the pandemic: The specific merits of panel-data and Markov-switching models," Tourism Economics, , vol. 31(4), pages 695-713, June.
    2. Jorge V Pérez-Rodríguez & Juan M Hernández & Julián Andrada-Félix, 2024. "Modelling prices and volatilities in the sharing economy," Tourism Economics, , vol. 30(5), pages 1189-1215, August.

  5. Baldwin Tong & Ulrich Gunter, 2022. "Hedonic pricing and the sharing economy: how profile characteristics affect Airbnb accommodation prices in Barcelona, Madrid, and Seville," Current Issues in Tourism, Taylor & Francis Journals, vol. 25(20), pages 3309-3328, October.

    Cited by:

    1. Mohamed Amr Sultan & Tomaž Kramberger & Mahmoud Barakat & Ahmed Hussein Ali, 2023. "Barriers to Applying Last-Mile Logistics in the Egyptian Market: An Extension of the Technology Acceptance Model," Sustainability, MDPI, vol. 15(17), pages 1-25, August.
    2. Trinath Sai Subhash Reddy Pittala & Uma Maheswara R Meleti & Hemanth Vasireddy, 2024. "Unveiling Patterns in European Airbnb Prices: A Comprehensive Analytical Study Using Machine Learning Techniques," Papers 2407.01555, arXiv.org.
    3. Marius-Ionuț Gordan & Valentina Constanța Tudor & Cosmin Alin Popescu & Tabita Cornelia Adamov & Elena Peț & Ioana Anda Milin & Tiberiu Iancu, 2024. "Hedonic Pricing Models in Rural Tourism: Analyzing Factors Influencing Accommodation Pricing in Romania Using Geographically Weighted Regression," Agriculture, MDPI, vol. 14(8), pages 1-22, July.
    4. Vargas-Pérez, Víctor A. & Cordón, Oscar & Chica, Manuel & Hernández, Juan M., 2025. "Social network of peer-to-peer accommodations for a visual decision support system in tourism: The case of the Canary Islands," Socio-Economic Planning Sciences, Elsevier, vol. 98(C).
    5. Lin, Wenzhen & Yang, Fan, 2024. "The price of short-term housing: A study of Airbnb on 26 regions in the United States," Journal of Housing Economics, Elsevier, vol. 65(C).
    6. Chaang-Iuan Ho & Tzong-Shyuan Chen & Chin-Pei Li, 2023. "Airbnb’s Negative Externalities from the Consumer’s Perspective: How the Effects Influence the Booking Intention of Potential Guests," Sustainability, MDPI, vol. 15(11), pages 1-28, May.
    7. Lee, Hanna & Jang, Seongsoo & Kim, Jinwon, 2024. "Spatial coopetition and peer-to-peer accommodation price," Annals of Tourism Research, Elsevier, vol. 109(C).
    8. Hongbo Tan & Tian Su & Xusheng Wu & Pengzhan Cheng & Tianxiang Zheng, 2024. "A Sustainable Rental Price Prediction Model Based on Multimodal Input and Deep Learning—Evidence from Airbnb," Sustainability, MDPI, vol. 16(15), pages 1-22, July.

  6. Weismayer, Christian & Gunter, Ulrich & Önder, Irem, 2021. "Temporal variability of emotions in social media posts," Technological Forecasting and Social Change, Elsevier, vol. 167(C).

    Cited by:

    1. Xi Wang & Liang Tang & Linan Zhang & Jie Zheng, 2022. "Initial Stage of the COVID-19 Pandemic: A Perspective on Health Risk Communications in the Restaurant Industry," IJERPH, MDPI, vol. 19(19), pages 1-20, September.
    2. Gavurova, Beata & Skare, Marinko & Belas, Jaroslav & Rigelsky, Martin & Ivankova, Viera, 2023. "The relationship between destination image and destination safety during technological and social changes COVID-19 pandemic," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    3. Baudier, Patricia & de Boissieu, Elodie & Duchemin, Marie-Hélène, 2023. "Source Credibility and Emotions generated by Robot and Human Influencers: The perception of luxury brand representatives," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    4. Giganti, Patrizio & Errichiello, Grazia & Falcone, Pasquale Marcello, 2025. "Exploring public discourse on green hydrogen via YouTube comments: A comparative sentiment analysis using VADER and ChatGPT," Economic Analysis and Policy, Elsevier, vol. 88(C), pages 2012-2030.
    5. Sakshi Kathuria & Urvashi Tandon & Vasundhra, 2026. "Unpacking the drivers of tourists’ social media content creation: an empirical investigation," Quality & Quantity: International Journal of Methodology, Springer, vol. 60(2), pages 6525-6547, April.

  7. Gunter, Ulrich & Zekan, Bozana, 2021. "Forecasting air passenger numbers with a GVAR model," Annals of Tourism Research, Elsevier, vol. 89(C).

    Cited by:

    1. Ari, Didem & Mizrak Ozfirat, Pinar, 2024. "Comparison of artificial neural networks and regression analysis for airway passenger estimation," Journal of Air Transport Management, Elsevier, vol. 115(C).
    2. Hoai Nguyen Huynh & Kuan Luen Ng & Roy Toh & Ling Feng, 2024. "Understanding the impact of network structure on air travel pattern at different scales," PLOS ONE, Public Library of Science, vol. 19(3), pages 1-20, March.
    3. Huidan Xue & Chenguang Li & Liming Wang & Wen-Hao Su, 2021. "Spatial Price Transmission and Price Dynamics of Global Butter Export Market under Economic Shocks," Sustainability, MDPI, vol. 13(16), pages 1-24, August.
    4. Haodong Sun & Yang Yang & Yanyan Chen & Xiaoming Liu & Jiachen Wang, 2023. "Tourism demand forecasting of multi-attractions with spatiotemporal grid: a convolutional block attention module model," Information Technology & Tourism, Springer, vol. 25(2), pages 205-233, June.
    5. Xufang Zheng & Qilei Zhang & Victoria Cobb & Max Z. Li, 2025. "Examining the Dynamics of Local and Transfer Passenger Share Patterns in Air Transportation," Papers 2503.05754, arXiv.org.
    6. Xu, Shilin & Liu, Yang & Jin, Chun, 2023. "Forecasting daily tourism demand with multiple factors," Annals of Tourism Research, Elsevier, vol. 103(C).
    7. Li, Xin & Xu, Yechi & Law, Rob & Wang, Shouyang, 2024. "Enhancing tourism demand forecasting with a transformer-based framework," Annals of Tourism Research, Elsevier, vol. 107(C).
    8. Li, Cheng & Zheng, Weimin & Ge, Peng, 2022. "Tourism demand forecasting with spatiotemporal features," Annals of Tourism Research, Elsevier, vol. 94(C).
    9. Yong Liu & Xiang-jie Fu & Jeffrey Lin Yi Forrest, 2025. "Forecasting tourism demand with pre-holiday attribute," Information Technology & Tourism, Springer, vol. 27(3), pages 613-648, September.
    10. Yi-Chung Hu & Geng Wu & Mei-Ling Wu, 2025. "Generation of ensemble forecasts using functional-link net for decomposition ensemble learning to forecast tourist arrivals," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(5), pages 4159-4184, October.
    11. Abdelghany, Ahmed & Abdelghany, Khaled & Guzhva, Vitaly S. & Kai, Mary, 2025. "Unraveling endogeneity in seat capacity and Fares: Time series econometric models for airline origin-destination passengers forecasting," Journal of Air Transport Management, Elsevier, vol. 128(C).
    12. Li, Xin & Xu, Yechi & Law, Rob & Wang, Shouyang, 2024. "Enhancing Tourism Demand Forecasting with a Transformer-based Framework," SocArXiv 5ezn3_v1, Center for Open Science.

  8. Ulrich Gunter, 2021. "Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests," Forecasting, MDPI, vol. 3(4), pages 1-36, November.

    Cited by:

    1. João Paulo Teixeira & Ulrich Gunter, 2023. "Editorial for Special Issue: “Tourism Forecasting: Time-Series Analysis of World and Regional Data”," Forecasting, MDPI, vol. 5(1), pages 1-3, February.
    2. Yuruixian Zhang & Wei Chong Choo & Yuhanis Abdul Aziz & Choy Leong Yee & Jen Sim Ho, 2022. "Go Wild for a While? A Bibliometric Analysis of Two Themes in Tourism Demand Forecasting from 1980 to 2021: Current Status and Development," Data, MDPI, vol. 7(8), pages 1-38, July.
    3. Ahmed Shoukry Rashad, 2022. "The Power of Travel Search Data in Forecasting the Tourism Demand in Dubai," Forecasting, MDPI, vol. 4(3), pages 1-11, July.
    4. El houssin Ouassou & Hafsa Taya, 2022. "Forecasting Regional Tourism Demand in Morocco from Traditional and AI-Based Methods to Ensemble Modeling," Forecasting, MDPI, vol. 4(2), pages 1-18, April.
    5. Keerti Manisha & Inderpal Singh, 2024. "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, Springer, vol. 8(3), pages 879-909, September.

  9. Ulrich Gunter & Irem Önder & Egon Smeral, 2020. "Are Combined Tourism Forecasts Better at Minimizing Forecasting Errors?," Forecasting, MDPI, vol. 2(3), pages 1-19, June.

    Cited by:

    1. Natalia Świdyńska & Mirosława Witkowska-Dąbrowska, 2021. "Indicators of the Tourist Attractiveness of Urban–Rural Communes and Sustainability of Peripheral Areas," Sustainability, MDPI, vol. 13(12), pages 1-24, June.
    2. Yuruixian Zhang & Wei Chong Choo & Yuhanis Abdul Aziz & Choy Leong Yee & Jen Sim Ho, 2022. "Go Wild for a While? A Bibliometric Analysis of Two Themes in Tourism Demand Forecasting from 1980 to 2021: Current Status and Development," Data, MDPI, vol. 7(8), pages 1-38, July.

  10. Frank Wogbe Agbola & Tarik Dogru & Ulrich Gunter, 2020. "Tourism Demand: Emerging Theoretical and Empirical Issues," Tourism Economics, , vol. 26(8), pages 1307-1310, December.

    Cited by:

    1. Di Lu & Hongxia Gao & Yonglian Wang & Peng Su, 2025. "How does network infrastructure construction affect household tourism expenditures? An empirical analysis from rural China," Tourism Economics, , vol. 31(2), pages 183-200, March.
    2. Canh Phuc Nguyen & Binh Quang Nguyen, 2023. "Does the shadow economy matter for tourism consumption? New global evidence," Empirical Economics, Springer, vol. 65(2), pages 729-773, August.
    3. Wenmin Wu & Chien-Chiang Lee & Wenwu Xing & Shan-Ju Ho, 2021. "The impact of the COVID-19 outbreak on Chinese-listed tourism stocks," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-18, December.
    4. Umberto Minora & Stefano Maria Iacus & Filipe Batista e Silva & Francesco Sermi & Spyridon Spyratos, 2023. "Nowcasting tourist nights spent using innovative human mobility data," PLOS ONE, Public Library of Science, vol. 18(10), pages 1-17, October.

  11. Ulrich Gunter, 2019. "Estimating and forecasting with a two-country DSGE model of the Euro area and the USA: the merits of diverging interest-rate rules," Empirical Economics, Springer, vol. 56(4), pages 1283-1323, April.

    Cited by:

    1. Hsiao, Cody Yu-Ling & Jin, Tao & Kwok, Simon & Wang, Xi & Zheng, Xin, 2023. "Entrepreneurial risk shocks and financial acceleration asymmetry in a two-country DSGE model," China Economic Review, Elsevier, vol. 81(C).
    2. Van Robays, Ine & Stracca, Livio, 2020. "How much does aggregate demand travel across the Atlantic?," Working Paper Series 2430, European Central Bank.

  12. Irem Önder & Christian Weismayer & Ulrich Gunter, 2019. "Spatial price dependencies between the traditional accommodation sector and the sharing economy," Tourism Economics, , vol. 25(8), pages 1150-1166, December.

    Cited by:

    1. David Boto-García, 2023. "Methods to examine omitted variable bias in hedonic price studies," Tourism Economics, , vol. 29(6), pages 1598-1623, September.
    2. Chunfang Zhao & Yingliang Wu & Yunfeng Chen & Guohua Chen, 2023. "Multiscale Effects of Hedonic Attributes on Airbnb Listing Prices Based on MGWR: A Case Study of Beijing, China," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
    3. Shohei Kurata & Yasuo Ohe, 2020. "Competitive Structure of Accommodations in a Traditional Japanese Hot Springs Tourism Area," Sustainability, MDPI, vol. 12(7), pages 1-15, April.
    4. Juan L Eugenio-Martin & José M Cazorla-Artiles & Christian González-Martel, 2019. "On the determinants of Airbnb location and its spatial distribution," Tourism Economics, , vol. 25(8), pages 1224-1244, December.
    5. Bozana Zekan & Ulrich Gunter, 2022. "Zooming into Airbnb listings of European cities: Further investigation of the sector’s competitiveness," Tourism Economics, , vol. 28(3), pages 772-794, May.
    6. Sainaghi, Ruggero & Chica-Olmo, Jorge, 2022. "The effects of location before and during COVID-19," Annals of Tourism Research, Elsevier, vol. 96(C).
    7. Jorge V. Pérez-Rodríguez & Heiko Rachinger & Rafael Suárez-Vega, 2024. "Is peer-to-peer demand cointegrated at the listing level?," Empirical Economics, Springer, vol. 66(5), pages 2249-2275, May.
    8. Giulia Contu & Luca Frigau & Claudio Conversano, 2023. "Price indicators for Airbnb accommodations," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(5), pages 4779-4802, October.
    9. Lim, Weng Marc & Yap, Sheau-Fen & Makkar, Marian, 2021. "Home sharing in marketing and tourism at a tipping point: What do we know, how do we know, and where should we be heading?," Journal of Business Research, Elsevier, vol. 122(C), pages 534-566.
    10. Yuting Chen & Rong Zhang & Bin Liu, 2021. "Fixed, flexible, and dynamics pricing decisions of Airbnb mode with social learning," Tourism Economics, , vol. 27(5), pages 893-914, August.
    11. Türk, Umut & Östh, John & Kourtit, Karima & Nijkamp, Peter, 2021. "The path of least resistance explaining tourist mobility patterns in destination areas using Airbnb data," Journal of Transport Geography, Elsevier, vol. 94(C).
    12. Lee, Yong-Jin Alex & Jang, Seongsoo & Kim, Jinwon, 2020. "Tourism clusters and peer-to-peer accommodation," Annals of Tourism Research, Elsevier, vol. 83(C).
    13. Josep Lladós-Masllorens & Antoni Meseguer-Artola & Inma Rodríguez-Ardura, 2020. "Understanding Peer-to-Peer, Two-Sided Digital Marketplaces: Pricing Lessons from Airbnb in Barcelona," Sustainability, MDPI, vol. 12(13), pages 1-19, June.

  13. Gunter, Ulrich & Önder, Irem & Smeral, Egon, 2019. "Scientific value of econometric tourism demand studies," Annals of Tourism Research, Elsevier, vol. 78(C), pages 1-1.

    Cited by:

    1. Ulrich Gunter & Egon Smeral, 2025. "A novel suggestion on how to adequately treat stochastic non-stationary seasonality in tourism export forecasting," Tourism Economics, , vol. 31(4), pages 579-592, June.
    2. José Alberto Martínez-González & Vidina Tais Díaz-Padilla & Eduardo Parra-López, 2021. "Study of the Tourism Competitiveness Model of the World Economic Forum Using Rasch’s Mathematical Model: The Case of Portugal," Sustainability, MDPI, vol. 13(13), pages 1-20, June.
    3. Yuruixian Zhang & Wei Chong Choo & Yuhanis Abdul Aziz & Choy Leong Yee & Jen Sim Ho, 2022. "Go Wild for a While? A Bibliometric Analysis of Two Themes in Tourism Demand Forecasting from 1980 to 2021: Current Status and Development," Data, MDPI, vol. 7(8), pages 1-38, July.
    4. Li, Cheng & Zheng, Weimin & Ge, Peng, 2022. "Tourism demand forecasting with spatiotemporal features," Annals of Tourism Research, Elsevier, vol. 94(C).
    5. Frank Wogbe Agbola & Tarik Dogru & Ulrich Gunter, 2020. "Tourism Demand: Emerging Theoretical and Empirical Issues," Tourism Economics, , vol. 26(8), pages 1307-1310, December.
    6. Anca-Gabriela Turtureanu & Rodica Pripoaie & Carmen-Mihaela Cretu & Carmen-Gabriela Sirbu & Emanuel Ştefan Marinescu & Laurentiu-Gabriel Talaghir & Florentina Chițu, 2022. "A Projection Approach of Tourist Circulation under Conditions of Uncertainty," Sustainability, MDPI, vol. 14(4), pages 1-21, February.
    7. Yanzhao Li & Ju-e Guo & Wenjun Zhu, 2024. "Digital financial inclusion and domestic tourism demand: Through the lens of spatial spillover," Tourism Economics, , vol. 30(7), pages 1680-1703, November.
    8. Demiralay, Sercan, 2020. "Political uncertainty and the us tourism index returns," Annals of Tourism Research, Elsevier, vol. 84(C).
    9. Gunter, Ulrich & Zekan, Bozana, 2021. "Forecasting air passenger numbers with a GVAR model," Annals of Tourism Research, Elsevier, vol. 89(C).
    10. Zhang, Yishuo & Li, Gang & Muskat, Birgit & Law, Rob & Yang, Yating, 2020. "Group pooling for deep tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 82(C).
    11. Ulrich Gunter & Irem Önder & Egon Smeral, 2020. "Are Combined Tourism Forecasts Better at Minimizing Forecasting Errors?," Forecasting, MDPI, vol. 2(3), pages 1-19, June.
    12. Rockie U Kei Kuok & Tay T.R. Koo & Christine Lim, 2024. "Air transport capacity and tourism demand: A panel cointegration approach with cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model," Tourism Economics, , vol. 30(3), pages 702-727, May.
    13. Lee, Seonjin & Pennington-Gray, Lori, 2025. "Metatheorizing tourist flow at macro-level: Universal forces theory and herding among tourists," Annals of Tourism Research, Elsevier, vol. 113(C).

  14. Bozana Zekan & Irem Önder & Ulrich Gunter, 2019. "Benchmarking of Airbnb listings: How competitive is the sharing economy sector of European cities?," Tourism Economics, , vol. 25(7), pages 1029-1046, November.

    Cited by:

    1. Yifei Jiang & Honglei Zhang & Xianting Cao & Ge Wei & Yang Yang, 2023. "How to better incorporate geographic variation in Airbnb price modeling?," Tourism Economics, , vol. 29(5), pages 1181-1203, August.
    2. Yoo Ri Kim & Anyu Liu & Allan M Williams, 2022. "Competitiveness in the visitor economy: A systematic literature review," Tourism Economics, , vol. 28(3), pages 817-842, May.
    3. Trinath Sai Subhash Reddy Pittala & Uma Maheswara R Meleti & Hemanth Vasireddy, 2024. "Unveiling Patterns in European Airbnb Prices: A Comprehensive Analytical Study Using Machine Learning Techniques," Papers 2407.01555, arXiv.org.
    4. Juan L Eugenio-Martin & José M Cazorla-Artiles & Christian González-Martel, 2019. "On the determinants of Airbnb location and its spatial distribution," Tourism Economics, , vol. 25(8), pages 1224-1244, December.
    5. Bozana Zekan & Ulrich Gunter, 2022. "Zooming into Airbnb listings of European cities: Further investigation of the sector’s competitiveness," Tourism Economics, , vol. 28(3), pages 772-794, May.
    6. Schmücker Dirk & Reif Julian, 2023. "Geht Tourismus alle an? Teilnahme der deutschen Gemeinden am Übernachtungstourismus," Zeitschrift für Tourismuswissenschaft, De Gruyter, vol. 15(1), pages 4-26, March.
    7. Reif, Julian, 2022. "Hot or not? Räumliche Analyse von Airbnb-Listings in Deutschland, Berlin, Hamburg, München und Köln," Working Paper Series 3, Deutsches Institut für Tourismusforschung, Fachhochschule Westküste.
    8. Jorge V Pérez-Rodríguez & Juan M Hernández, 2023. "The effect of type of lodging and professionalism on the efficiency of P2P accommodation," Tourism Economics, , vol. 29(6), pages 1624-1642, September.
    9. Jorge V Pérez-Rodríguez & Juan M Hernández & Julián Andrada-Félix, 2024. "Modelling prices and volatilities in the sharing economy," Tourism Economics, , vol. 30(5), pages 1189-1215, August.
    10. Wei Guo & Jing Wang & Yue Kang, 2024. "Internet use and inverted U-shaped employment polarization in tourism occupations," Tourism Economics, , vol. 30(2), pages 457-476, March.
    11. Yuting Chen & Rong Zhang & Bin Liu, 2021. "Fixed, flexible, and dynamics pricing decisions of Airbnb mode with social learning," Tourism Economics, , vol. 27(5), pages 893-914, August.
    12. Martin Thomas Falk & Yang Yang, 2021. "Hotels benefit from stricter regulations on short-term rentals in European cities," Tourism Economics, , vol. 27(7), pages 1526-1539, November.
    13. Francesco Angelini & Paolo Figini & Veronica Leoni, 2024. "High tide, low price? Flooding alerts and hotel prices in Venice," Tourism Economics, , vol. 30(4), pages 876-899, June.

  15. Ulrich Gunter & Irem Önder & Stefan Gindl, 2019. "Exploring the predictive ability of LIKES of posts on the Facebook pages of four major city DMOs in Austria," Tourism Economics, , vol. 25(3), pages 375-401, May.

    Cited by:

    1. Gunter, Ulrich & Önder, Irem & Smeral, Egon, 2019. "Scientific value of econometric tourism demand studies," Annals of Tourism Research, Elsevier, vol. 78(C), pages 1-1.
    2. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    3. Park, Eunhye & Park, Jinah & Hu, Mingming, 2021. "Tourism demand forecasting with online news data mining," Annals of Tourism Research, Elsevier, vol. 90(C).
    4. Doris Chenguang Wu & Shiteng Zhong & Richard T R Qiu & Ji Wu, 2022. "Are customer reviews just reviews? Hotel forecasting using sentiment analysis," Tourism Economics, , vol. 28(3), pages 795-816, May.
    5. Cebrián, Eduardo & Domenech, Josep, 2024. "Addressing Google Trends inconsistencies," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    6. Ulrich Gunter, 2021. "Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests," Forecasting, MDPI, vol. 3(4), pages 1-36, November.
    7. Jun (Justin) Li & Woo Gon Kim & Hyung Min Choi, 2021. "Effectiveness of social media marketing on enhancing performance: Evidence from a casual-dining restaurant setting," Tourism Economics, , vol. 27(1), pages 3-22, February.
    8. Li, Hengyun & Hu, Mingming & Li, Gang, 2020. "Forecasting tourism demand with multisource big data," Annals of Tourism Research, Elsevier, vol. 83(C).
    9. Huizi Zeng & Chengjun Tang & Chen Zhou & Peng Zhou, 2025. "Spatial Analysis of Network Attention on Tourism Resources for Sustainable Tourism Development in Western Hunan, China: A Multi-Source Data Approach," Sustainability, MDPI, vol. 17(2), pages 1-20, January.
    10. Hu, Mingming & Dong, Na & Hu, Fang, 2024. "Tourism demand forecasting using short video information," Annals of Tourism Research, Elsevier, vol. 109(C).
    11. Tomas Havranek & Ayaz Zeynalov, 2021. "Forecasting tourist arrivals: Google Trends meets mixed-frequency data," Tourism Economics, , vol. 27(1), pages 129-148, February.
    12. Li, Hengyun & Gao, Huicai & Song, Haiyan, 2023. "Tourism forecasting with granular sentiment analysis," Annals of Tourism Research, Elsevier, vol. 103(C).
    13. Gang Xie & Xin Li & Yatong Qian & Shouyang Wang, 2021. "Forecasting tourism demand with KPCA-based web search indexes," Tourism Economics, , vol. 27(4), pages 721-743, June.

  16. Ceddia, Michele Graziano & Gunter, Ulrich & Pazienza, Pasquale, 2019. "Indigenous peoples' land rights and agricultural expansion in Latin America: A dynamic panel data approach," Forest Policy and Economics, Elsevier, vol. 109(C).

    Cited by:

    1. Cappelli, Federica & Caravaggio, Nicola & Vaquero-Piñeiro, Cristina, 2022. "Buen Vivir and forest conservation in Bolivia: False promises or effective change?," Forest Policy and Economics, Elsevier, vol. 137(C).
    2. Catacora-Vargas, Georgina & Alvarado, Víctor & Rankovic, Aleksandar & Tambutti, Marcia, 2022. "Governance approaches and practices in Latin America and the Caribbean for transformative change for biodiversity," Documentos de Proyectos 48542, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    3. Correa, Alicia & Forero, Jorge & Marco Renau, Jorge & Lizarazo, Ivan & Mulligan, Mark & Codato, Daniele, 2023. "Advancing spatial decision-making in a transboundary catchment through multidimensional ecosystem services assessment," Ecosystem Services, Elsevier, vol. 64(C).
    4. Mueller, Bernardo, 2022. "Property rights and violence in indigenous land in Brazil," Land Use Policy, Elsevier, vol. 116(C).
    5. Elena Zepharovich & Michele Graziano Ceddia & Stephan Rist, 2020. "Land-Use Conflict in the Gran Chaco: Finding Common Ground through Use of the Q Method," Sustainability, MDPI, vol. 12(18), pages 1-16, September.

  17. Ulrich Gunter & Irem Önder, 2018. "Determinants of Airbnb demand in Vienna and their implications for the traditional accommodation industry," Tourism Economics, , vol. 24(3), pages 270-293, May.

    Cited by:

    1. Giulia Contu & Luca Frigau & Marco Ortu, 2023. "VGLM proportional odds model to infer hosts’ Airbnb performance," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(5), pages 4069-4094, October.
    2. Shujia Wang & Minmin Zu & Jiana Yuan & Huizi Xie, 2025. "A Multi-Platform Online Data-Driven Diagnostic Approach for Macro-Level Sustainability of Homestays," Sustainability, MDPI, vol. 17(18), pages 1-28, September.
    3. Juan Luis Jiménez & Armando Ortuño & Jorge V. Pérez-Rodríguez, 2022. "How does AirBnb affect local Spanish tourism markets?," Empirical Economics, Springer, vol. 62(5), pages 2515-2545, May.
    4. Wrede, Matthias, 2021. "How short-term rentals are changing the neighborhood," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242409, Verein für Socialpolitik / German Economic Association.
    5. He, Jiaxiu & Li, Bingqing & Wang, Xin (Shane), 2023. "Image features and demand in the sharing economy: A study of Airbnb," International Journal of Research in Marketing, Elsevier, vol. 40(4), pages 760-780.
    6. Ulrich Gunter & Bozana Zekan & Francesco Luigi Milone, 2025. "Modelling and forecasting European Airbnb occupancy during the pandemic: The specific merits of panel-data and Markov-switching models," Tourism Economics, , vol. 31(4), pages 695-713, June.
    7. Juan L Eugenio-Martin & José M Cazorla-Artiles & Christian González-Martel, 2019. "On the determinants of Airbnb location and its spatial distribution," Tourism Economics, , vol. 25(8), pages 1224-1244, December.
    8. Bozana Zekan & Ulrich Gunter, 2022. "Zooming into Airbnb listings of European cities: Further investigation of the sector’s competitiveness," Tourism Economics, , vol. 28(3), pages 772-794, May.
    9. Patricia Valenzuela & Armando Ortuño & María Flor & Begoña Guirao, 2024. "Analysis of the Location Factors Affecting the Price of Tourist Houses: The Role of Accessibility to Public Transport Stations in Madrid," Sustainability, MDPI, vol. 16(11), pages 1-15, June.
    10. Lin, Wenzhen & Yang, Fan, 2024. "The price of short-term housing: A study of Airbnb on 26 regions in the United States," Journal of Housing Economics, Elsevier, vol. 65(C).
    11. Ti-An Chen, 2022. "Business Performance Evaluation for Tourism Factory: Using DEA Approach and Delphi Method," Sustainability, MDPI, vol. 14(15), pages 1-19, July.
    12. Sainaghi, Ruggero & Chica-Olmo, Jorge, 2022. "The effects of location before and during COVID-19," Annals of Tourism Research, Elsevier, vol. 96(C).
    13. Irem Önder & Christian Weismayer & Ulrich Gunter, 2019. "Spatial price dependencies between the traditional accommodation sector and the sharing economy," Tourism Economics, , vol. 25(8), pages 1150-1166, December.
    14. Jorge V Pérez-Rodríguez & Juan M Hernández, 2023. "The effect of type of lodging and professionalism on the efficiency of P2P accommodation," Tourism Economics, , vol. 29(6), pages 1624-1642, September.
    15. Jorge V. Pérez-Rodríguez & Heiko Rachinger & Rafael Suárez-Vega, 2024. "Is peer-to-peer demand cointegrated at the listing level?," Empirical Economics, Springer, vol. 66(5), pages 2249-2275, May.
    16. Miguel Ángel Solano-Sánchez & José António C. Santos & Margarida Custódio Santos & Manuel Ángel Fernández-Gámez, 2021. "Holiday Rentals in Cultural Tourism Destinations: A Comparison of Booking.com-Based Daily Rate Estimation for Seville and Porto," Economies, MDPI, vol. 9(4), pages 1-16, October.
    17. Birgit Leick & Bjørnar Karlsen Kivedal & Mehtap Aldogan Eklund & Evgueni Vinogradov, 2022. "Exploring the relationship between Airbnb and traditional accommodation for regional variations of tourism markets," Tourism Economics, , vol. 28(5), pages 1258-1279, August.
    18. Nicola Camatti & Giacomo Tollo & Gianni Filograsso & Sara Ghilardi, 2024. "Predicting Airbnb pricing: a comparative analysis of artificial intelligence and traditional approaches," Computational Management Science, Springer, vol. 21(1), pages 1-25, June.
    19. Dolnicar, Sara, 2019. "A review of research into paid online peer-to-peer accommodation," Annals of Tourism Research, Elsevier, vol. 75(C), pages 248-264.
    20. Hongbo Tan & Tian Su & Xusheng Wu & Pengzhan Cheng & Tianxiang Zheng, 2024. "A Sustainable Rental Price Prediction Model Based on Multimodal Input and Deep Learning—Evidence from Airbnb," Sustainability, MDPI, vol. 16(15), pages 1-22, July.
    21. Taehyee Um & Yejin Lee & Jakeun Koo, 2025. "Economic impacts of digital home-sharing platform: Creative destruction in the hospitality industry," Tourism Economics, , vol. 31(2), pages 201-220, March.
    22. Ulrich Gunter, 2021. "Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests," Forecasting, MDPI, vol. 3(4), pages 1-36, November.
    23. Bozana Zekan & Irem Önder & Ulrich Gunter, 2019. "Benchmarking of Airbnb listings: How competitive is the sharing economy sector of European cities?," Tourism Economics, , vol. 25(7), pages 1029-1046, November.
    24. Yuting Chen & Rong Zhang & Bin Liu, 2021. "Fixed, flexible, and dynamics pricing decisions of Airbnb mode with social learning," Tourism Economics, , vol. 27(5), pages 893-914, August.
    25. Beatriz Benítez-Aurioles, 2022. "The exhaustion of the herding effect in peer-to-peer accommodation," Tourism Economics, , vol. 28(1), pages 27-43, February.
    26. Martin Thomas Falk & Yang Yang, 2021. "Hotels benefit from stricter regulations on short-term rentals in European cities," Tourism Economics, , vol. 27(7), pages 1526-1539, November.
    27. Bobrovskaya, EV. & Polbin, A., 2023. "Econometric modeling of the demand for short-term rental housing: The case of Airbnb in Moscow," Journal of the New Economic Association, New Economic Association, vol. 59(2), pages 64-84.
    28. Augusto Voltes-Dorta & Federico Inchausti-Sintes, 2021. "The spatial and quality dimensions of Airbnb markets," Tourism Economics, , vol. 27(4), pages 688-702, June.
    29. Türk, Umut & Östh, John & Kourtit, Karima & Nijkamp, Peter, 2021. "The path of least resistance explaining tourist mobility patterns in destination areas using Airbnb data," Journal of Transport Geography, Elsevier, vol. 94(C).
    30. Lee, Yong-Jin Alex & Jang, Seongsoo & Kim, Jinwon, 2020. "Tourism clusters and peer-to-peer accommodation," Annals of Tourism Research, Elsevier, vol. 83(C).
    31. Laura Abrardi & Elisabetta Raguseo & Laura Rondi, 2026. "Sellers’ behavior and online rating bias: A sentiment analysis on airbnb reviews," Tourism Economics, , vol. 32(2), pages 276-299, March.
    32. Jinwen Tang & Jinlin Cheng & Min Zhang, 2024. "Forecasting Airbnb prices through machine learning," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 45(1), pages 148-160, January.
    33. R. Filieri & E. Raguseo & F. Galati, 2023. "Negative signals on Peer-to-Peer platforms: The impact of cancellations on host performance across different property types," Post-Print hal-04779130, HAL.

  18. Ulrich Gunter & M. Graziano Ceddia & David Leonard & Bernhard Tröster, 2018. "Contribution of international ecotourism to comprehensive economic development and convergence in the Central American and Caribbean region," Applied Economics, Taylor & Francis Journals, vol. 50(33), pages 3614-3629, July.

    Cited by:

    1. Valentina Della Corte & Giovanna Del Gaudio & Fabiana Sepe & Fabiana Sciarelli, 2019. "Sustainable Tourism in the Open Innovation Realm: A Bibliometric Analysis," Sustainability, MDPI, vol. 11(21), pages 1-18, November.
    2. Simplice A. Asongu & Mushfiqur Rahman & Joseph Nnanna, 2022. "Law, Political Stability, Tourism Management and Economic Development in Sub-Saharan Africa," Journal of Africa SEER Centre(ASC) 22/023, Africa SEER Centre(ASC).
    3. Pablo Juan Cárdenas-García & Juan Gabriel Brida & Verónica Segarra, 2024. "Modeling the link between tourism and economic development: evidence from homogeneous panels of countries," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    4. Colin Cannonier & Monica Galloway Burke, 2019. "The economic growth impact of tourism in Small Island Developing States—evidence from the Caribbean," Tourism Economics, , vol. 25(1), pages 85-108, February.
    5. Wanjun Xia & Buhari Doğan & Umer Shahzad & Festus Fatai Adedoyin & Abiodun Popoola & Muhammad Adnan Bashir, 2022. "An empirical investigation of tourism-led growth hypothesis in the European countries: evidence from augmented mean group estimator," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 21(2), pages 239-266, May.
    6. Alejandro Alcalá-Ordóñez & Verónica Segarra, 2025. "Tourism and economic development: A literature review to highlight main empirical findings," Tourism Economics, , vol. 31(1), pages 76-103, February.
    7. Marzieh Fallah & Lanndon Ocampo, 2021. "The use of the Delphi method with non-parametric analysis for identifying sustainability criteria and indicators in evaluating ecotourism management: the case of Penang National Park (Malaysia)," Environment Systems and Decisions, Springer, vol. 41(1), pages 45-62, March.
    8. Kai-di Liu & Minghui Jin & Liang Cheng, 2025. "County green transformation: how does gross ecosystem product assessment promote common prosperity?," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-15, December.

  19. Mauro Costantini & Ulrich Gunter & Robert M. Kunst, 2017. "Forecast Combinations in a DSGE‐VAR Lab," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(3), pages 305-324, April.
    See citations under working paper version above.
  20. Marcello Pagnini & Paola Rossi & Valerio Vacca & Michael Sigmund & Ulrich Gunter & Gerald Krenn, 2017. "How Do Macroeconomic and Bank-specific Variables Influence Profitability in the Austrian Banking Sector? Evidence from a Panel Vector Autoregression Analysis," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 46(3), pages 555-586, November.

    Cited by:

    1. Michael Sigmund, 2021. "Assessing macro-prudential policies: the case of FX lending," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(2), pages 316-359, April.
    2. Alessandra Agati & Michael Sigmund, 2025. "Banking in the Negative: A Vector Error Correction Analysis of Bank-Specific Lending and Deposit Rates (Alessandra Agati, Michael Sigmund)," Working Papers 261, Oesterreichische Nationalbank (Austrian Central Bank).
    3. Sigmund, Michael & Agati, Alessandra, 2025. "Banking in the negative: a vector error correction analysis of bank-specific lending and deposit rates," Working Paper Series 3039, European Central Bank.
    4. Esteban Miguélez & Jonathan Spiteri & Simon Grima, 2019. "Establishing the Contributing Factors to the Resurrection of PIIGS Banks Following the Crisis: A Panel Data Analysis," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(1), pages 3-34.
    5. Martin Feldkircher & Michael Sigmund, 2017. "Comparing market power at home and abroad: evidence from Austrian banks and their subsidiaries in CESEE," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q3/17, pages 59-77.
    6. Jabir Esmaeil & Husam Rjoub & Wing-Keung Wong, 2020. "Do Oil Price Shocks and Other Factors Create Bigger Impacts on Islamic Banks than Conventional Banks?," Energies, MDPI, vol. 13(12), pages 1-16, June.
    7. Ozcan, Burcu & Tzeremes, Panayiotis G. & Tzeremes, Nickolaos G., 2020. "Energy consumption, economic growth and environmental degradation in OECD countries," Economic Modelling, Elsevier, vol. 84(C), pages 203-213.
    8. Sigmund, Michael & Siebenbrunner, Christoph, 2024. "Do interbank markets price systemic risk?," Journal of Financial Stability, Elsevier, vol. 71(C).

  21. Gunter, Ulrich & Önder, Irem, 2016. "Forecasting city arrivals with Google Analytics," Annals of Tourism Research, Elsevier, vol. 61(C), pages 199-212.

    Cited by:

    1. Roy, Gobinda & Sharma, Swati, 2021. "Measuring the role of factors on website effectiveness using vector autoregressive model," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    2. Bi, Jian-Wu & Liu, Yang & Li, Hui, 2020. "Daily tourism volume forecasting for tourist attractions," Annals of Tourism Research, Elsevier, vol. 83(C).
    3. Ling Tang & Chengyuan Zhang & Tingfei Li & Ling Li, 2021. "A novel BEMD-based method for forecasting tourist volume with search engine data," Tourism Economics, , vol. 27(5), pages 1015-1038, August.
    4. Xiao-Bing Feng, 2025. "Spatio-temporal Characterization of Potential Demand for Tourist Attractions Based on Internet Search," SAGE Open, , vol. 15(1), pages 21582440251, February.
    5. Yi-Chung Hu, 2023. "Tourism combination forecasting using a dynamic weighting strategy with change-point analysis," Current Issues in Tourism, Taylor & Francis Journals, vol. 26(14), pages 2357-2374, July.
    6. Jiao, Xiaoying & Chen, Jason Li & Li, Gang, 2021. "Forecasting tourism demand: Developing a general nesting spatiotemporal model," Annals of Tourism Research, Elsevier, vol. 90(C).
    7. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    8. Thomas J. Lampoltshammer & Stefanie Wallinger & Johannes Scholz, 2023. "Bridging Disciplinary Divides through Computational Social Sciences and Transdisciplinarity in Tourism Education in Higher Educational Institutions: An Austrian Case Study," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    9. Wanhai You & Yuming Huang & Chien‐Chiang Lee, 2024. "Forecasting tourist flows in the COVID‐19 era using nonparametric mixed‐frequency VARs," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 473-489, March.
    10. Haodong Sun & Yang Yang & Yanyan Chen & Xiaoming Liu & Jiachen Wang, 2023. "Tourism demand forecasting of multi-attractions with spatiotemporal grid: a convolutional block attention module model," Information Technology & Tourism, Springer, vol. 25(2), pages 205-233, June.
    11. F. Antolini & L. Grassini, 2019. "Foreign arrivals nowcasting in Italy with Google Trends data," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2385-2401, September.
    12. Georgios Giotis & Evangelia Papadionysiou, 2022. "The Role of Managerial and Technological Innovations in the Tourism Industry: A Review of the Empirical Literature," Sustainability, MDPI, vol. 14(9), pages 1-20, April.
    13. Purva Grover & Arpan Kumar Kar, 2017. "Big Data Analytics: A Review on Theoretical Contributions and Tools Used in Literature," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(3), pages 203-229, September.
    14. Eden Xiaoying Jiao & Jason Li Chen, 2019. "Tourism forecasting: A review of methodological developments over the last decade," Tourism Economics, , vol. 25(3), pages 469-492, May.
    15. Muralidharan Ramakrishnan & Shirley Gregor & Anup Shrestha & Jeffrey Soar, 2025. "Addressing Knowledge Gaps in ITSM Practice with “Learning Digital Commons”: A Case Study," Information Systems Frontiers, Springer, vol. 27(3), pages 965-989, June.
    16. Wai Kit Tsang & Dries F. Benoit, 2020. "Gaussian processes for daily demand prediction in tourism planning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 551-568, April.
    17. Yuruixian Zhang & Wei Chong Choo & Yuhanis Abdul Aziz & Choy Leong Yee & Jen Sim Ho, 2022. "Go Wild for a While? A Bibliometric Analysis of Two Themes in Tourism Demand Forecasting from 1980 to 2021: Current Status and Development," Data, MDPI, vol. 7(8), pages 1-38, July.
    18. Liu, Han & Chen, Yuxiu & Hu, Mingming & Chen, Jason Li, 2025. "Forecast by mixed-frequency dynamic panel model," Annals of Tourism Research, Elsevier, vol. 110(C).
    19. Buda Baji'c & Sr{dj}an Mili'cevi'c & Aleksandar Anti'c & Slobodan Markovi'c & Nemanja Tomi'c, 2024. "Neural Network Modeling for Forecasting Tourism Demand in Stopi\'{c}a Cave: A Serbian Cave Tourism Study," Papers 2404.04974, arXiv.org.
    20. Assaf, A. George & Tsionas, Mike G., 2019. "Forecasting occupancy rate with Bayesian compression methods," Annals of Tourism Research, Elsevier, vol. 75(C), pages 439-449.
    21. Pan, Mengqiang & Liao, Zhixue & Wang, Zhouyiying & Ren, Chi & Xing, Zhibin & Li, Wenyong, 2025. "Tourism forecasting: A dynamic spatiotemporal model," Annals of Tourism Research, Elsevier, vol. 110(C).
    22. Xu, Shilin & Liu, Yang & Jin, Chun, 2023. "Forecasting daily tourism demand with multiple factors," Annals of Tourism Research, Elsevier, vol. 103(C).
    23. Villamediana, Jenely & Küster, Inés & Vila, Natalia, 2019. "Destination engagement on Facebook: Time and seasonality," Annals of Tourism Research, Elsevier, vol. 79(C).
    24. Li, Cheng & Zheng, Weimin & Ge, Peng, 2022. "Tourism demand forecasting with spatiotemporal features," Annals of Tourism Research, Elsevier, vol. 94(C).
    25. Edmond H. C. Wu & Jihao Hu & Rui Chen, 2022. "Monitoring and forecasting COVID-19 impacts on hotel occupancy rates with daily visitor arrivals and search queries," Current Issues in Tourism, Taylor & Francis Journals, vol. 25(3), pages 490-507, February.
    26. Tarmo Kalvet & Maarja Olesk & Marek Tiits & Janika Raun, 2020. "Innovative Tools for Tourism and Cultural Tourism Impact Assessment," Sustainability, MDPI, vol. 12(18), pages 1-30, September.
    27. Yong Liu & Xiang-jie Fu & Jeffrey Lin Yi Forrest, 2025. "Forecasting tourism demand with pre-holiday attribute," Information Technology & Tourism, Springer, vol. 27(3), pages 613-648, September.
    28. Yi-Chung Hu & Geng Wu & Mei-Ling Wu, 2025. "Generation of ensemble forecasts using functional-link net for decomposition ensemble learning to forecast tourist arrivals," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(5), pages 4159-4184, October.
    29. Tan, Zhi Qin & Li, Yunpeng, 2026. "Post-pandemic tourism forecasting with ensemble RNN," Annals of Tourism Research, Elsevier, vol. 116(C).
    30. Li, Cheng & Ge, Peng & Liu, Zhusheng & Zheng, Weimin, 2020. "Forecasting tourist arrivals using denoising and potential factors," Annals of Tourism Research, Elsevier, vol. 83(C).
    31. Law, Rob & Li, Gang & Fong, Davis Ka Chio & Han, Xin, 2019. "Tourism demand forecasting: A deep learning approach," Annals of Tourism Research, Elsevier, vol. 75(C), pages 410-423.
    32. Katerina Volchek & Anyu Liu & Haiyan Song & Dimitrios Buhalis, 2019. "Forecasting tourist arrivals at attractions: Search engine empowered methodologies," Tourism Economics, , vol. 25(3), pages 425-447, May.
    33. Xu, Jian & Zhang, Wei & Li, Hengyun & Zheng, Xiang (Kevin) & Zhang, Jing, 2024. "User-generated photos in hotel demand forecasting," Annals of Tourism Research, Elsevier, vol. 108(C).
    34. A Fronzetti Colladon & B Guardabascio & R Innarella, 2021. "Using social network and semantic analysis to analyze online travel forums and forecast tourism demand," Papers 2105.07727, arXiv.org.
    35. Ulrich Gunter, 2021. "Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests," Forecasting, MDPI, vol. 3(4), pages 1-36, November.
    36. Cao, Zheng & Li, Gang & Song, Haiyan, 2017. "Modelling the interdependence of tourism demand: The global vector autoregressive approach," Annals of Tourism Research, Elsevier, vol. 67(C), pages 1-13.
    37. Liu, Yuan-Yuan & Tseng, Fang-Mei & Tseng, Yi-Heng, 2018. "Big Data analytics for forecasting tourism destination arrivals with the applied Vector Autoregression model," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 123-134.
    38. Yang, Yang & Zhang, Honglei, 2019. "Spatial-temporal forecasting of tourism demand," Annals of Tourism Research, Elsevier, vol. 75(C), pages 106-119.
    39. Li, Hengyun & Hu, Mingming & Li, Gang, 2020. "Forecasting tourism demand with multisource big data," Annals of Tourism Research, Elsevier, vol. 83(C).
    40. Mazanec, Josef A., 2020. "Hidden theorizing in big data analytics: With a reference to tourism design research," Annals of Tourism Research, Elsevier, vol. 83(C).
    41. Gao, Huicai & Li, Hengyun & Zhang, Chen Jason, 2025. "Time and feature varying tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 112(C).
    42. Anastasiou, Dimitris & Drakos, Konstantinos & Kapopoulos, Panayotis, 2022. "Predicting international tourist arrivals in Greece with a novel sector-specific business leading indicator," MPRA Paper 113860, University Library of Munich, Germany.
    43. Jiahui Huang & Chenglong Zhang, 2024. "Daily Tourism Demand Forecasting with the iTransformer Model," Sustainability, MDPI, vol. 16(23), pages 1-22, December.
    44. Song, Haiyan & Qiu, Richard T.R. & Park, Jinah, 2019. "A review of research on tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 75(C), pages 338-362.
    45. Ulrich Gunter & Irem Önder & Stefan Gindl, 2019. "Exploring the predictive ability of LIKES of posts on the Facebook pages of four major city DMOs in Austria," Tourism Economics, , vol. 25(3), pages 375-401, May.
    46. Mingming Hu & Haifeng Yang & Doris Chenguang Wu & Shuai Ma, 2024. "A novel two-stage combination model for tourism demand forecasting," Tourism Economics, , vol. 30(8), pages 1925-1950, December.
    47. Shaolong Suna & Dan Bi & Ju-e Guo & Shouyang Wang, 2020. "Seasonal and Trend Forecasting of Tourist Arrivals: An Adaptive Multiscale Ensemble Learning Approach," Papers 2002.08021, arXiv.org, revised Mar 2020.
    48. Ulrich Gunter & Irem Önder & Egon Smeral, 2020. "Are Combined Tourism Forecasts Better at Minimizing Forecasting Errors?," Forecasting, MDPI, vol. 2(3), pages 1-19, June.
    49. Weaver, Adam, 2021. "Tourism, big data, and a crisis of analysis," Annals of Tourism Research, Elsevier, vol. 88(C).
    50. Silvia Emili & Paolo Figini & Andrea Guizzardi, 2020. "Modelling international monthly tourism demand at the micro destination level with climate indicators and web-traffic data," Tourism Economics, , vol. 26(7), pages 1129-1151, November.
    51. Guizzardi, Andrea & Pons, Flavio Maria Emanuele & Angelini, Giovanni & Ranieri, Ercolino, 2021. "Big data from dynamic pricing: A smart approach to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1049-1060.
    52. Li, Hengyun & Gao, Huicai & Song, Haiyan, 2023. "Tourism forecasting with granular sentiment analysis," Annals of Tourism Research, Elsevier, vol. 103(C).
    53. Gang Xie & Xin Li & Yatong Qian & Shouyang Wang, 2021. "Forecasting tourism demand with KPCA-based web search indexes," Tourism Economics, , vol. 27(4), pages 721-743, June.

  22. Ulrich Gunter & Egon Smeral, 2016. "The decline of tourism income elasticities in a global context," Tourism Economics, , vol. 22(3), pages 466-483, June.

    Cited by:

    1. Sushma Rewal Chugh, 2020. "Domestic Tourism: A Panacea for Global Disasters," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 7(5), pages 55-59, May.
    2. Helena Nemec Rudez, 2018. "The Relationship between Income and Tourism Demand: Old Findings and New Research," Academica Turistica - Tourism and Innovation Journal, University of Primorska Press, vol. 11(1), pages 67-73.
    3. Ulrich Gunter & Egon Smeral, 2025. "A novel suggestion on how to adequately treat stochastic non-stationary seasonality in tourism export forecasting," Tourism Economics, , vol. 31(4), pages 579-592, June.
    4. Hanson, Daniel & Toru Delibasi, Tuba & Gatti, Matteo & Cohen, Shamai, 2022. "How do changes in economic activity affect air passenger traffic? The use of state-dependent income elasticities to improve aviation forecasts," Journal of Air Transport Management, Elsevier, vol. 98(C).
    5. Kožić Ivan & Arčabić Vladimir & Sever Ivan, 2022. "Tourism and Business Cycles: Does the Relationship Fade Away?," Zagreb International Review of Economics and Business, Paradigm, vol. 25(1), pages 95-110.
    6. Angeliki N. Menegaki & Nicholas Tsounis & George M. Agiomirgianakis, 2022. "The economic impact of climate change (CC) on the Greek economy," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(6), pages 8145-8161, June.
    7. Martin Falk & Xiang Lin, 2018. "Income elasticity of overnight stays over seven decades," Tourism Economics, , vol. 24(8), pages 1015-1028, December.
    8. Federico Inchausti-Sintes, 2020. "A tourism growth model," Tourism Economics, , vol. 26(5), pages 746-763, August.
    9. Jonathan Stråle, 2022. "Household level heterogeneity in the income elasticities of demand for international leisure travel," Tourism Economics, , vol. 28(8), pages 2154-2175, December.
    10. David Boto-García & Alvaro Muñiz-Fernández & Levi Pérez, 2024. "Windfall money and outbound tourism: A natural experiment from lottery winnings," Tourism Economics, , vol. 30(5), pages 1257-1280, August.
    11. Adrian R Fleissig, 2021. "Expenditure and price elasticities for tourism sub-industries from the Fourier flexible form," Tourism Economics, , vol. 27(8), pages 1692-1706, December.
    12. Mehmet Balcilar & Sahar Aghazadeh & George N Ike, 2021. "Modelling the employment, income and price elasticities of outbound tourism demand in OECD countries," Tourism Economics, , vol. 27(5), pages 971-990, August.
    13. Tzu-Ming Liu, 2020. "Habit formation or word of mouth: What does lagged dependent variable in tourism demand models imply?," Tourism Economics, , vol. 26(3), pages 461-474, May.
    14. Irem Önder & Ulrich Gunter, 2022. "Blockchain: Is it the future for the tourism and hospitality industry?," Tourism Economics, , vol. 28(2), pages 291-299, March.
    15. Lucie Plzáková & Egon Smeral, 2022. "Impact of the COVID-19 crisis on European tourism," Tourism Economics, , vol. 28(1), pages 91-109, February.
    16. Becken, Susanne & Carmignani, Fabrizio, 2020. "Are the current expectations for growing air travel demand realistic?," Annals of Tourism Research, Elsevier, vol. 80(C).

  23. Gunter, Ulrich & Önder, Irem, 2015. "Forecasting international city tourism demand for Paris: Accuracy of uni- and multivariate models employing monthly data," Tourism Management, Elsevier, vol. 46(C), pages 123-135.

    Cited by:

    1. Xi Wu & Adam Blake, 2023. "Does the combination of models with different explanatory variables improve tourism demand forecasting performance?," Tourism Economics, , vol. 29(8), pages 2032-2056, December.
    2. Mitra, Subrata Kumar & Chattopadhyay, Manojit & Jana, R.K., 2019. "Spillover analysis of tourist movements within Europe," Annals of Tourism Research, Elsevier, vol. 79(C).
    3. Muzi Zhang & Junyi Li & Bing Pan & Gaojun Zhang, 2018. "Weekly Hotel Occupancy Forecasting of a Tourism Destination," Sustainability, MDPI, vol. 10(12), pages 1-17, November.
    4. Han Liu & Yongjing Wang & Haiyan Song & Ying Liu, 2023. "Measuring tourism demand nowcasting performance using a monotonicity test," Tourism Economics, , vol. 29(5), pages 1302-1327, August.
    5. Xu Huang & Emmanuel Silva & Hossein Hassani, 2018. "Causality between Oil Prices and Tourist Arrivals," Stats, MDPI, vol. 1(1), pages 1-21, October.
    6. Elisa Jorge-González & Enrique González-Dávila & Raquel Martín-Rivero & Domingo Lorenzo-Díaz, 2020. "Univariate and multivariate forecasting of tourism demand using state-space models," Tourism Economics, , vol. 26(4), pages 598-621, June.
    7. Anca Mehedintu & Mihaela Sterpu & Georgeta Soava, 2018. "Estimation and Forecasts for the Share of Renewable Energy Consumption in Final Energy Consumption by 2020 in the European Union," Sustainability, MDPI, vol. 10(5), pages 1-22, May.
    8. Gunter, Ulrich & Önder, Irem, 2016. "Forecasting city arrivals with Google Analytics," Annals of Tourism Research, Elsevier, vol. 61(C), pages 199-212.
    9. Yuhong Yang & Tarik Dogru & Chao Liang & Jianqiong Wang & Pengfei Xu, 2024. "Developing and testing the efficacy of a novel forecasting methodology: Theory and evidence from China," Tourism Economics, , vol. 30(8), pages 2043-2069, December.
    10. Eden Xiaoying Jiao & Jason Li Chen, 2019. "Tourism forecasting: A review of methodological developments over the last decade," Tourism Economics, , vol. 25(3), pages 469-492, May.
    11. Jian-Wu Bi & Tian-Yu Han & Hui Li, 2022. "International tourism demand forecasting with machine learning models: The power of the number of lagged inputs," Tourism Economics, , vol. 28(3), pages 621-645, May.
    12. Wai Kit Tsang & Dries F. Benoit, 2020. "Gaussian processes for daily demand prediction in tourism planning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 551-568, April.
    13. Thao Nguyen-Da & Yi-Min Li & Chi-Lu Peng & Ming-Yuan Cho & Phuong Nguyen-Thanh, 2023. "Tourism Demand Prediction after COVID-19 with Deep Learning Hybrid CNN–LSTM—Case Study of Vietnam and Provinces," Sustainability, MDPI, vol. 15(9), pages 1-22, April.
    14. Apostolos Ampountolas, 2019. "Forecasting hotel demand uncertainty using time series Bayesian VAR models," Tourism Economics, , vol. 25(5), pages 734-756, August.
    15. Liu, Han & Chen, Yuxiu & Hu, Mingming & Chen, Jason Li, 2025. "Forecast by mixed-frequency dynamic panel model," Annals of Tourism Research, Elsevier, vol. 110(C).
    16. Xi Wu & Adam Blake, 2023. "The Impact of the COVID-19 Crisis on Air Travel Demand: Some Evidence From China," SAGE Open, , vol. 13(1), pages 21582440231, January.
    17. Tine Van Calster & Filip Van den Bossche & Bart Baesens & Wilfried Lemahieu, 2020. "Profit-oriented sales forecasting: a comparison of forecasting techniques from a business perspective," Papers 2002.00949, arXiv.org.
    18. Gaojun Zhang & Jinfeng Wu & Bing Pan & Junyi Li & Minjie Ma & Muzi Zhang & Jian Wang, 2017. "Improving daily occupancy forecasting accuracy for hotels based on EEMD-ARIMA model," Tourism Economics, , vol. 23(7), pages 1496-1514, November.
    19. Li, Xin & Pan, Bing & Law, Rob & Huang, Xiankai, 2017. "Forecasting tourism demand with composite search index," Tourism Management, Elsevier, vol. 59(C), pages 57-66.
    20. Marrocu, Emanuela & Paci, Raffaele & Zara, Andrea, 2015. "Micro-economic determinants of tourist expenditure: A quantile regression approach," Tourism Management, Elsevier, vol. 50(C), pages 13-30.
    21. Law, Rob & Li, Gang & Fong, Davis Ka Chio & Han, Xin, 2019. "Tourism demand forecasting: A deep learning approach," Annals of Tourism Research, Elsevier, vol. 75(C), pages 410-423.
    22. Kulshrestha, Anurag & Krishnaswamy, Venkataraghavan & Sharma, Mayank, 2020. "Bayesian BILSTM approach for tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 83(C).
    23. Jaume Rosselló-Nadal & Andreu Sansó-Rosselló, 2025. "A frequent mistake in aggregate tourism demand modeling: The use of a composite price index of competing destinations," Tourism Economics, , vol. 31(4), pages 777-788, June.
    24. A Fronzetti Colladon & B Guardabascio & R Innarella, 2021. "Using social network and semantic analysis to analyze online travel forums and forecast tourism demand," Papers 2105.07727, arXiv.org.
    25. Ulrich Gunter, 2021. "Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests," Forecasting, MDPI, vol. 3(4), pages 1-36, November.
    26. Umberto Minora & Stefano Maria Iacus & Filipe Batista e Silva & Francesco Sermi & Spyridon Spyratos, 2023. "Nowcasting tourist nights spent using innovative human mobility data," PLOS ONE, Public Library of Science, vol. 18(10), pages 1-17, October.
    27. Lim, Sungkyu & Seetaram, Neelu & Hosany, Sameer & Li, Matthew, 2023. "Consumption of pop culture and tourism demand: Through the lens of herding behaviour," Annals of Tourism Research, Elsevier, vol. 99(C).
    28. Liu, Yuan-Yuan & Tseng, Fang-Mei & Tseng, Yi-Heng, 2018. "Big Data analytics for forecasting tourism destination arrivals with the applied Vector Autoregression model," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 123-134.
    29. Silva, Emmanuel Sirimal & Hassani, Hossein, 2022. "‘Modelling’ UK tourism demand using fashion retail sales," Annals of Tourism Research, Elsevier, vol. 95(C).
    30. Pengfei Zhang & Hu Yu & Mingzhe Shen & Wei Guo, 2022. "Evaluation of Tourism Development Efficiency and Spatial Spillover Effect Based on EBM Model: The Case of Hainan Island, China," IJERPH, MDPI, vol. 19(7), pages 1-21, March.
    31. Silva, Emmanuel Sirimal & Ghodsi, Zara & Ghodsi, Mansi & Heravi, Saeed & Hassani, Hossein, 2017. "Cross country relations in European tourist arrivals," Annals of Tourism Research, Elsevier, vol. 63(C), pages 151-168.
    32. Gao, Huicai & Li, Hengyun & Zhang, Chen Jason, 2025. "Time and feature varying tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 112(C).
    33. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A regional perspective on the accuracy of machine learning forecasts of tourism demand based on data characteristics”," AQR Working Papers 201802, University of Barcelona, Regional Quantitative Analysis Group, revised Apr 2018.
    34. Song, Haiyan & Qiu, Richard T.R. & Park, Jinah, 2019. "A review of research on tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 75(C), pages 338-362.
    35. Shaolong Suna & Dan Bi & Ju-e Guo & Shouyang Wang, 2020. "Seasonal and Trend Forecasting of Tourist Arrivals: An Adaptive Multiscale Ensemble Learning Approach," Papers 2002.08021, arXiv.org, revised Mar 2020.
    36. Silvia Emili & Paolo Figini & Andrea Guizzardi, 2020. "Modelling international monthly tourism demand at the micro destination level with climate indicators and web-traffic data," Tourism Economics, , vol. 26(7), pages 1129-1151, November.
    37. Zhang, Yishuo & Li, Gang & Muskat, Birgit & Vu, Huy Quan & Law, Rob, 2021. "Predictivity of tourism demand data," Annals of Tourism Research, Elsevier, vol. 89(C).
    38. Mingming Hu & Haiyan Song, 2020. "Data source combination for tourism demand forecasting," Tourism Economics, , vol. 26(7), pages 1248-1265, November.
    39. Ke Xu & Junli Zhang & Junhao Huang & Hongbo Tan & Xiuli Jing & Tianxiang Zheng, 2024. "Forecasting Visitor Arrivals at Tourist Attractions: A Time Series Framework with the N-BEATS for Sustainable Tourism," Sustainability, MDPI, vol. 16(18), pages 1-28, September.

  24. Ulrich Gunter & Gerald Krenn & Michael Sigmund, 2013. "Macroeconomic, Market and Bank-Specific Determinants of the Net Interest Margin in Austria," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 25, pages 87-101.

    Cited by:

    1. Stefan Kerbl & Michael Sigmund, 2016. "From low to negative rates: an asymmetric dilemma," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 32, pages 120-137.
    2. Katharina Allinger & Julia Wörz, 2020. "The sensitivity of banks’ net interest margins to interest rate conditions in CESEE," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q1/20, pages 51-70.
    3. Michael Sigmund, 2021. "Assessing macro-prudential policies: the case of FX lending," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(2), pages 316-359, April.
    4. Ramona Busch & Christoph Memmel, 2016. "Quantifying the components of the banks’ net interest margin," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 30(4), pages 371-396, November.
    5. Sigmund, Michael & Agati, Alessandra, 2025. "Banking in the negative: a vector error correction analysis of bank-specific lending and deposit rates," Working Paper Series 3039, European Central Bank.
    6. Raja Almarzoqi & Sami Ben Naceur, 2015. "Determinants of Bank Interest Margins in the Caucasus and Central Asia," IMF Working Papers 2015/087, International Monetary Fund.
    7. Marcello Pagnini & Paola Rossi & Valerio Vacca & Michael Sigmund & Ulrich Gunter & Gerald Krenn, 2017. "How Do Macroeconomic and Bank-specific Variables Influence Profitability in the Austrian Banking Sector? Evidence from a Panel Vector Autoregression Analysis," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 46(3), pages 555-586, November.
    8. Marcel Barmeier, 2022. "The new normal: bank lending and negative interest rates in Austria (Marcel Barmeier)," Working Papers 242, Oesterreichische Nationalbank (Austrian Central Bank).
    9. Iktimal Abdel Reda & Husam Rjoub & Ahmad Abu Alrub, 2016. "The Determinants of Banks¡¯ Profitability under Basel Regulations: Evidence from Lebanon," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(10), pages 206-219, October.
    10. Sigmund, Michael & Siebenbrunner, Christoph, 2024. "Do interbank markets price systemic risk?," Journal of Financial Stability, Elsevier, vol. 71(C).
    11. International Monetary Fund, 2014. "Republic of Azerbaijan: Selected Issues," IMF Staff Country Reports 2014/160, International Monetary Fund.

  25. Stephan Barisitz & Ulrich Gunter & Mathias Lahnsteiner, 2012. "Ukrainian Banks Face Heightened Uncertainty and Challenges," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 23, pages 50-57.

    Cited by:

    1. Stephan Barisitz & Zuzana Fungáčová, 2015. "Ukraine: struggling banking sector amid substantial uncertainty," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 29, pages 72-92.
    2. Stephan Barisitz & Mathias Lahnsteiner & Daniela Widhalm & Tina Wittenberger, 2014. "Macrofinancial Developments in Ukraine, Russia and Turkey from an Austrian Financial Stability Perspective," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 27, pages 64-73.
    3. Barisitz, Stephan & Fungáčová, Zuzana, 2015. "Ukraine: Struggling banking sector and substantial political and economic uncertainty," BOFIT Policy Briefs 3/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
    4. Ruoyu Cai & Mao Zhang, 2017. "How Does Credit Risk Influence Liquidity Risk? Evidence from Ukrainian Banks," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 241, pages 21-33.

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