Forecast of tourism demand with the use of fuzzy and cointegration econometric techniques

Botzoris, George; Varagouli, E. G.; Profillidis, Vassilios; Papadopoulos, Basil K.; Lathiras, Petros

doi:10.3233/jcm-140501

Cited by 3 publications

(3 citation statements)

References 26 publications

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“…For six different world regions, Gunter and Smeral (2016) found a decline in tourism income elasticities, using panel data analysis, and for the last decade, the values of the income elasticities were below 1. But other works such as Botzoris et al (2014) or Dritsakis (2004) found income elasticities greater than 1.…”

Section: Final Remarksmentioning

confidence: 81%

Mexico and Uruguay inbound tourism demand

Mordecki¹,

Leiva²,

Puel³

2019

RBTUR

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The main objective of this paper is to estimate the tourism demand for Mexico and Uruguay, two very different countries, but for both of which tourism is an important activity, and mainly originating from a large neighbor. We try to analyze whether the determinants of tourism demand differ depending on the size of the country, or if being a neighboring country is the main determinant. So, we analyze the relationship between the number of American tourists visiting Mexico and Argentinian tourists visiting Uruguay, and the inbound tourists’ income and the bilateral real exchange rate (RER) between the visiting country and the hosting country, following the Johansen’s methodology. We found one cointegration relationship for each country, where the income-elasticity was greater than 2 for American tourists visiting Mexico, and nearly 3 for Argentinian tourists visiting Uruguay. Bilateral RERs were also significant in both models. Moreover, forecasts show the impacts of institutional changes on the tourism sector. The impact of arrival of President Macri to power was positive for Argentinian tourists visiting Uruguay, but President Trump's arrival in the US was negative for American tourists visiting Mexico.

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Section: Final Remarksmentioning

confidence: 81%

Mexico and Uruguay inbound tourism demand

Mordecki¹,

Leiva²,

Puel³

2019

RBTUR

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“…Botzoris etcs. develop an econometric models for the forecast of tourism demand, and the Johansen's maximum likelihood techniques and il's Inequality Coefficient are applied, fuzzy regression models are suggested and then compared in order to provide the forecasting ability of both techniques (Fuzzy and ECMs) [3]. Liu and Siva examine the optimal choices for publishers, and highlight two-sided information asymmetries in online advertising markets and the consequent trade-offs faced by a high-quality publisher using P4P schemesu, find that the hybrid scheme can emerge as an equilibrium choice in a variety of conditions by means of a new "uncompromised" equilibrium refinement, and provide prescriptive guidelines for firms choosing between different pricing schemes [4].…”

Section: Introductionmentioning

confidence: 99%

Research on enterprise information utility indifference curve of big data time

Yang

2015

JCM

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Based on the characters of information, a model of information utilities indifference curve has been build which combined information abundance and rechness. The information utilities indifference curve has been explained and discussed, and then analyses how enterprise choose information combination based on cost bind, that is the equilibrium condition of enterprise realizing the most satisfactory information utilities combination, and points out that the formed equilibrium must be broked by the advancement of information technology, this impels the change of enterprise's behavior model and organization structure, the new equilibrium comes into being.

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“…Botzoris et al, (2014) assessed tourism demand forecast with econometric models. Forecasting ability of models examined were verified with the Theil's Inequality Coefficient, which permits the investigation of residuals and the appraisal of the forecasting ability of the proposed models, offering a measure of how well a time series of estimated values compares to a corresponding time series of actual (observed) values.Profillidis and Botzoris (2015) examined relationship of air transportation traffic volume and economic activity for different geographical areas.…”

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confidence: 99%

Real time traffic load forecasting

Κολιδάκης¹

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Η παρούσα διδακτορική διατριβή με διακριτικό τίτλο: «Πρόβλεψη μεταφορικού φόρτου σε πραγματικό χρόνο: Μια υβριδική προσέγγιση με χρήση τεχνικών Ανάλυσης Ιδιάζοντος Φάσματος και Τεχνητής Νοημοσύνης» διερευνά και προτείνει μια υβριδική μεθοδολογία που συνδυάζει την Ανάλυση Ιδιάζοντος Φάσματος και την Τεχνητή Νοημοσύνη με στόχο την πρόβλεψη της μελλοντική εξέλιξης του φόρτου ενός μεταφορικού συστήματος, σε πραγματικό χρόνο. Η ανάπτυξη και υλοποίηση του προτεινόμενου μοντέλου πρόβλεψης μεταφορικού φόρτου με βάση την υπολογιστική νοημοσύνη, οδήγησε στην ανάπτυξη ενός πρωτότυπου και καινοτόμου λογισμικού, που μπορεί να χρησιμοποιηθεί ως ένα σύγχρονο εργαλείο υποστήριξης λήψης αποφάσεων, που παρέχει χρήσιμες πληροφορίες για την εξέλιξη του μεταφορικού φόρτου, την αποτελεσματική λειτουργία και την βέλτιστη διαχείριση ενός μεταφορικού συστήματος.

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Forecast of tourism demand with the use of fuzzy and cointegration econometric techniques

Cited by 3 publications

References 26 publications

Mexico and Uruguay inbound tourism demand

Mexico and Uruguay inbound tourism demand

Research on enterprise information utility indifference curve of big data time

Real time traffic load forecasting

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