Combining statistical and judgmental forecasts via a web-based tourism demand forecasting system

Song, Haiyan; Gao, Bastian Z.; Lin, Vera Shanshan

doi:10.1016/j.ijforecast.2011.12.003

Cited by 86 publications

(82 citation statements)

References 51 publications

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“…A web-based TDFS offers an effective bridge between academics and industry practitioners. As a computer-based innovation, web-based TDFS often includes the following functions (Croce and Wöber, 2011;Song et al, 2013): (1) Furthermore, more forecasting models could be included and combined to generate more stable statistical forecasts and further reduce the risk of forecasting failure.…”

Section: Development Of Web-based Tourism and Hotel Demand Forecastinmentioning

confidence: 99%

New developments in tourism and hotel demand modeling and forecasting

Song

Shen

2017

IJCHM

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253

217

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Design/Methodology/approachArticles on tourism and hotel demand modeling and forecasting published in both Science Citation Index (SCI) and Social Sciences Citation Index (SSCI) journals were identified and analyzed. FindingsThis review finds that the studies focused on hotel demand are relatively less than those on tourism demand. It is also observed that more and more studies have moved away from the aggregate tourism demand analysis, while disaggregate markets and niche products have attracted increasing attention. Some studies have gone beyond neoclassical economic theory to seek additional explanations of the dynamics of tourism and hotel demand, such as environmental factors, tourist online behavior, and consumer confidence indicators, among others. More sophisticated techniques such as Research limitations/implicationsThe main limitation of this review is that the articles included in this study only cover the English literature. Future review of this kind should also include articles published in other languages. The review provides a useful guide for researchers who are interested in future research on tourism and hotel demand modeling and forecasting. Practical implicationsThis review provides important suggestions and recommendations for improving the efficiency of tourism and hospitality management practices. Originality/valueThe value of this review is that it identifies the current trends in tourism and hotel demand modeling and forecasting research and points out future research directions.

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Section: Development Of Web-based Tourism and Hotel Demand Forecastinmentioning

confidence: 99%

New developments in tourism and hotel demand modeling and forecasting

Song

Shen

2017

IJCHM

Self Cite

253

217

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“…La demanda en este sector ha sido analizada desde el punto de vista de pronóstico en numerosos estudios a nivel internacional (Guizzardi & Stacchini, 2015;Song, Gao & Lin, 2013;Liu et al, 2014). Algunas de las revisiones literarias muestran una descripción completa de los métodos usados en la modelación y pronós-tico de las demandas turísticas, que van desde las perspectivas econométricas clásicas has las nuevas técnicas de pronóstico emergentes, que emplean teoría estadística o matemática (Witt & Witt, 1995;Li, Song & Witt, 2005;Song & Li, 2008).…”

Section: Revisión De La Literaturaunclassified

Comparación de pronósticos para la dinámica del turismo en Medellín, Colombia

et al. 2017

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“…By contrast, Ang, Bekaert, and Wei (2007), Dovern andWeisser (2011), andLoungani (2001), among others, show that "consensus" (i.e., combined) survey-or expert-based forecasts do outperform model-based forecasts. Additionally, Song, Gao, and Lin (2013) and Lin, Goodwin, and Song (2014) document that combined expert-adjusted forecasts can improve on the individual model forecasts. Whichever application or setting, combined forecasts turn out to be more accurate.…”

Section: Introductionmentioning

confidence: 99%

“…Of course, it may happen that the expert-adjusted forecasts are biased; see, for example, Song et al (2013). Of course, it may happen that the expert-adjusted forecasts are biased; see, for example, Song et al (2013).…”

Section: Introductionmentioning

confidence: 99%

“…Whichever application or setting, combined forecasts turn out to be more accurate. Additionally, Song, Gao, and Lin (2013) and Lin, Goodwin, and Song (2014) document that combined expert-adjusted forecasts can improve on the individual model forecasts. So, apparently, even if experts adjust the model-based forecasts in the wrong direction, combined expert-adjusted forecasts may be more accurate.…”

Section: Introductionmentioning

confidence: 99%

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Combining expert‐adjusted forecasts

Dijk

Franses

2019

Journal of Forecasting

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It is well known that a combination of model-based forecasts can improve upon each of the individual constituent forecasts. Most forecasts available in practice are, however, not purely based on econometric models but entail adjustments, where experts with domain-specific knowledge modify the original model forecasts. There is much evidence that expert-adjusted forecasts do not necessarily improve the pure model-based forecasts. In this paper we show, however, that combined expert-adjusted model forecasts can improve on combined model forecasts, in the case when the individual expert-adjusted forecasts are not better than their associated model-based forecasts. We discuss various implications of this finding.

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Combining statistical and judgmental forecasts via a web-based tourism demand forecasting system

Cited by 86 publications

References 51 publications

New developments in tourism and hotel demand modeling and forecasting

New developments in tourism and hotel demand modeling and forecasting

Comparación de pronósticos para la dinámica del turismo en Medellín, Colombia

Combining expert‐adjusted forecasts

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