GLP open science meeting 2014, Berlin

Agent Based Mapping for assessing

socio-economic networks of mountain tourism as a coupled HES

Tobias Luthe, Romano Wyss

Background

Regional economies are comprising businesses, directly and indirectly tied together, e.g. by collaborations between business actors.

Such economies are natural resources dependent social-economic-ecological systems (SEES).

Mountain regions such as the Swiss Surselva-Gotthard DMO are often dependent on the service (tourism) industry, which is organized as a coupled supply chain.

Gotthard-Surselva (Disentis, Sedrun, Andermatt)

Tourism business actor supply chain network of the Gotthard-Surselva DMO*

* For more explanation see Luthe, T., Wyss, R. and M. Schuckert. 2012. Network governance and regional resilience to climate change: empirical evidence from mountain tourism communities. Regional Environmental Change. Online first DOI: http://dx.doi.org/10.1007/s10113-012-0294-5.

Background

Mountain HES have to cope with global change impacts.

Resilience of such systems can be assessed based on network metrics and their interpretations from a network governance angle.

Planning resilience and sustainable development in a tourism geography context requires understanding of the regional and local socio-economic interrelations and dependencies of the supply chain, and its ecological embeddedness.

Network governance in a tourism HES

Each (tourism) business is dependent on the other, while still being competitors: tourists experience the whole supply chain.

Improving network governance is partly dependent on the awareness of economic dependencies (e.g. distribution of risk and benefit).

Data to construct and analyse social networks of tourism businesses is easy to retrieve.

Data to display economic dependencies between regional tourism actors rarely exists: money flows are global and often no direct money flows between supply chain actors are available in a service industry.

Theoretical SES frameworkAccess to resources

Social nodes

Ecological nodes

Basic conceptual framework displayed here is taken from Bodin and Tengö (2012) Disentangling intangible social–ecological systems. Global Environmental Change 22, 430-439.

HES as a SE(E)S

Social Ecological

Economic

Theoretical SE(E)S frameworkIntegrating the economic sphere as a market function

Supply (businesses)

Demand (tourists)Direct and indirect money flows

Theoretical SE(E)S frameworkThe economic sphere as the market: tourists function as agents to map economic linkages

Social nodes

Ecological nodes

Theoretical SE(E)S frameworkThe economic sphere as the market: agent based mapping

Social nodes

Ecological nodes

Questions

How can the economic dependencies be included in SE(E)S analysis of mountain HES?

> How can indirect economic dependencies between tourism supply chain actors be analysed?

> Can tourists (‚feeding‘ from the supply chain, while being the businesses ‚pray‘) function as agents, indirectly connecting the supply chain by their spendings and ‚mapping‘ the economic ties?

What additional information delivers the economic network compared to the collaborative network?

Data collection

Tourists visiting the region for a typical one week stay filled out a daily questionnaire, noting their spendings in CHF

throughout the businesses of the tourism supply chain.

In total, 43 Agents (tourists) from six hotels in the three communities indirectly connect 70 businesses with 547 links.

Constructing an indirect economic networkThe tourist experiences the supply chain as a whole package

Direct spendings

Agent (tourist)

Constructing an indirect economic networkThe tourism product is complete if all supply exists

Indirect economic dependencies

Agent (tourist)

The original social collaboration network of the Gotthard DMO

140 nodes1420 linksDensity: 7.2%

The ABM economic network of the Gotthard DMO (node size=betweenness centrality)

e.g. gas station (orange) is of high importance in this economic network, but did not pop up in the orginal collaborative network

70 nodes547 linksDensity: 10.8%Size by degree centrality

Node size by cluster centralitye.g. gas station has little importance here

ABM economic network of the Gotthard DMOHotel Rhätia

ABM economic network of the Gotthard DMOHotel RhätiaDirect spendings of tourists staying at this hotel

ABM economic network of the Gotthard DMOHotel RhätiaIndirect economic dependencies

Andermatt cableways

ABM economic network of the Gotthard DMOAndermatt cablewaysDirect spendings

ABM economic network of the Gotthard DMOAndermatt cablewaysIndirect economic dependencies

Results and Discussion

An explorative indirect regional economic network was mapped by tourists as agents; further network metrics can be analyzed

Supply chain interconnections could be displayed

Insights on tourists‘ (agents) consumption behavior could be derived

Different centralities (e.g. degree, cluster, bridging) provide insights on actor roles from various perspectives, different to the collaborative network

Sample limited to only a small number of hotels

Economic actor weights (=tourists‘ spendings) are of limited value

Better understanding regional competition and dependencies

Economic network is an additional source of information to social collaborative network, e.g. for planning cooperations and resilience

Possibility of distributing subsidies in a regional, systemic understanding

One step further from social networks to socio-economic-ecological networks

Conclusions

Tobias.Luthe@htwchur.chRomano.Wyss@htwchur.ch

Exploring Agent Based Mapping