Comparative analysis of exponential smoothing models to tourists' arrivals in Serbia

  • Papic-Blagojevic N
  • Vujko A
  • Gajic T
N/ACitations
Citations of this article
11Readers
Mendeley users who have this article in their library.

Abstract

Seasonality is one of the main aspects affecting tourism. Considering the rapid increase in international tourism demand over the last few decades, predictions of future trends of tourism demand are of particular importance for the Government and the economy. We analyze the seasonality of tourist presence in different cities in Serbia. In this paper, the exponential smoothing models have been applied on the data that was taken from Republic Statistical Office (RSO). The research was conducted on monthly data relating to the number of overnight stays in Belgrade, Novi Sad and Niš during the period from January 2000 to December 2013. The precision of the obtained predictions is determined by comparing the RMSE and BIC precision measures. Based on the selected data, forecasting was made and it is concluded that the selected models correspond to the observed data very well.

Figures

  • Figure 1. Number of tourists in Novi Sad, Belgrade and Niš (January, 2000 – December, 2013)
  • Table 1. Basic statistics
  • Table 2. Seasonal Factors
  • Table 3. Model statistics
  • Table 4. Exponential smoothing model parameters
  • Figure 2. Observed and fit values for the series Number of tourists in Novi Sad, Belgrade and Niš (January, 2000 – December, 2013)

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Papic-Blagojevic, N., Vujko, A., & Gajic, T. (2016). Comparative analysis of exponential smoothing models to tourists’ arrivals in Serbia. Ekonomika Poljoprivrede, 63(3), 835–845. https://doi.org/10.5937/ekopolj1603835p

Readers over time

‘16‘17‘18‘20‘21‘2200.751.52.253

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 3

60%

Professor / Associate Prof. 1

20%

Lecturer / Post doc 1

20%

Readers' Discipline

Tooltip

Computer Science 3

38%

Social Sciences 2

25%

Environmental Science 2

25%

Agricultural and Biological Sciences 1

13%

Save time finding and organizing research with Mendeley

Sign up for free
0