Abstract
This paper contributes to filling two gaps: i) the presence of a limited amount of studies focused on tourism demand turning points, ii) the prevalent recourse to linear models in demand analysis, disregarding the complex structure of tourism destinations. The paper uses the Horizontal Visibility Graph Algorithm, a technique able to transform a time series of observations into a network whose topology preserves some fundamental characteristics of the system examined. The empirical work focuses on Livigno, an Italian alpine destination.Findings reveal four turning points in the last 50 years; these changes are built around shifts in the origin market segments. The network's degree distribution confirms the complex structure of the destination and reconfirms the importance of non-linear models and methods for the analysis of tourism demand.
| Original language | English |
|---|---|
| Pages (from-to) | 23-33 |
| Number of pages | 11 |
| Journal | Tourism Management |
| Volume | 54 |
| DOIs | |
| Publication status | Published - 1 Jun 2016 |
| Externally published | Yes |
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Keywords
- Complex systems
- Horizontal visibility graph algorithm
- Network analysis
- Time series
- Tourism demand
- Tourism destinations
ASJC Scopus subject areas
- Development
- Transportation
- Tourism, Leisure and Hospitality Management
- Strategy and Management
Cite this
Mapping time series into networks as a tool to assess the complex dynamics of tourism systems. / Baggio, Rodolfo; Sainaghi, Ruggero.
In: Tourism Management, Vol. 54, 01.06.2016, p. 23-33.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Mapping time series into networks as a tool to assess the complex dynamics of tourism systems
AU - Baggio, Rodolfo
AU - Sainaghi, Ruggero
PY - 2016/6/1
Y1 - 2016/6/1
N2 - This paper contributes to filling two gaps: i) the presence of a limited amount of studies focused on tourism demand turning points, ii) the prevalent recourse to linear models in demand analysis, disregarding the complex structure of tourism destinations. The paper uses the Horizontal Visibility Graph Algorithm, a technique able to transform a time series of observations into a network whose topology preserves some fundamental characteristics of the system examined. The empirical work focuses on Livigno, an Italian alpine destination.Findings reveal four turning points in the last 50 years; these changes are built around shifts in the origin market segments. The network's degree distribution confirms the complex structure of the destination and reconfirms the importance of non-linear models and methods for the analysis of tourism demand.
AB - This paper contributes to filling two gaps: i) the presence of a limited amount of studies focused on tourism demand turning points, ii) the prevalent recourse to linear models in demand analysis, disregarding the complex structure of tourism destinations. The paper uses the Horizontal Visibility Graph Algorithm, a technique able to transform a time series of observations into a network whose topology preserves some fundamental characteristics of the system examined. The empirical work focuses on Livigno, an Italian alpine destination.Findings reveal four turning points in the last 50 years; these changes are built around shifts in the origin market segments. The network's degree distribution confirms the complex structure of the destination and reconfirms the importance of non-linear models and methods for the analysis of tourism demand.
KW - Complex systems
KW - Horizontal visibility graph algorithm
KW - Network analysis
KW - Time series
KW - Tourism demand
KW - Tourism destinations
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UR - http://www.scopus.com/inward/citedby.url?scp=84946761966&partnerID=8YFLogxK
U2 - 10.1016/j.tourman.2015.10.008
DO - 10.1016/j.tourman.2015.10.008
M3 - Article
VL - 54
SP - 23
EP - 33
JO - Tourism Management
JF - Tourism Management
SN - 0261-5177
ER -