Tourism Demand Analysis Algorithm Based on Data Forecast Model Analysis

2021 ◽  
pp. 28-37
Author(s):  
Meng Chen
1998 ◽  
Vol 4 (4) ◽  
pp. 301-323 ◽  
Author(s):  
Lindsay W. Turner ◽  
Yvette Reisinger ◽  
Stephen F. Witt

Pravaha ◽  
2018 ◽  
Vol 24 (1) ◽  
pp. 58-63
Author(s):  
Dila Ram Bhandari

Tourism is now one of the largest industries in the world that has developed alongside the fascinating concept of eco-tourism. Nepal Tourism Policy 2009 identifies tourism sector as an important vehicle for economic and social development. Revenue from tourism sector is observed from foreign currency exchange made by tourists and tourism industries as proxy of income. According to Tourism Towards 2030, the number of international tourist arrivals worldwide is expected to increase by an average of 3.3% a year over the period 2010 to 2030. At the projected rate of growth, international tourist arrivals worldwide are expected to reach 1.4 billion by 2020, and 1.8 billion by the year 2030. Nepal aims to transform its tourism sector into one of the largest foreign exchange earners in 2016 by attracting 2.5 million high spending tourists. Tourism was ranked as the fifth largest source of foreign exchange earnings in 2012 and third largest in 2013 contributing 5.2 percent to total foreign earnings of the country. This study shows the tourism infrastructure as well as seasonal arrival of tourists in Nepal and to develop the probabilistic travel model on the basis of tourist perception which will help the tourism department for the further economic development of the area. R-Studio based on data from the sample period from 2008 to 2016. The formula presented in this study can be used by policy makers to calculate future foreign exchange earnings, employment, arrivals and prices related to tourism in Nepal. Pravaha Vol. 24, No. 1, 2018, Page: 58-63


2021 ◽  
pp. 135481662110311
Author(s):  
Lucie Plzáková ◽  
Egon Smeral

The COVID-19 pandemic and the containment measures imposed damaged the world economy severely. As a consequence of the stringent restrictions on business and social life, as well as the consequent economic downturn, tourism demand has seen a unique dramatic slump in the year 2020. This study concentrates on analysing and forecasting demand for international travel of the euro area in terms of tourism imports. Starting out from a description of the key macroeconomic factors, it then analyses their effects on tourism demand and develops a forecast model using contemporary approaches considering asymmetric income elasticities of tourism demand. Scenarios are elaborated to project demand for foreign travel of the euro area until 2022.


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