Mapping time series into networks as a tool to assess the complex dynamics of tourism systems

Rodolfo Baggio, Ruggero Sainaghi

Research output: Contribution to journalArticle

24 Citations (Scopus)

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 languageEnglish
Pages (from-to)23-33
Number of pages11
JournalTourism Management
Volume54
DOIs
Publication statusPublished - 1 Jun 2016
Externally publishedYes

Fingerprint

time series
Time series
tourism
Tourism
Visibility
demand analysis
non-linear model
demand
Topology
recourse
linear model
visibility
topology
transform
market
Tourism demand
Destination
Turning point
Complex dynamics
Tourism destination

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 journalArticle

@article{520925847b8e4bccb5d513184097fea3,
title = "Mapping time series into networks as a tool to assess the complex dynamics of tourism systems",
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.",
keywords = "Complex systems, Horizontal visibility graph algorithm, Network analysis, Time series, Tourism demand, Tourism destinations",
author = "Rodolfo Baggio and Ruggero Sainaghi",
year = "2016",
month = "6",
day = "1",
doi = "10.1016/j.tourman.2015.10.008",
language = "English",
volume = "54",
pages = "23--33",
journal = "Tourism Management",
issn = "0261-5177",
publisher = "Elsevier Limited",

}

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

UR - http://www.scopus.com/inward/record.url?scp=84946761966&partnerID=8YFLogxK

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 -