=Paper=
{{Paper
|id=Vol-2761/HAICTA_2020_paper58
|storemode=property
|title=An Integrated Indicator Based Knowledge Evaluation System for Sustainable Tourism Management in Greece: Empirical Approach of Multiple-criteria Decision Analysis Making for Future Tourism Spatial Planning
|pdfUrl=https://ceur-ws.org/Vol-2761/HAICTA_2020_paper58.pdf
|volume=Vol-2761
|authors=Georgios Apostolidis
|dblpUrl=https://dblp.org/rec/conf/haicta/Apostolidis20a
}}
==An Integrated Indicator Based Knowledge Evaluation System for Sustainable Tourism Management in Greece: Empirical Approach of Multiple-criteria Decision Analysis Making for Future Tourism Spatial Planning==
https://ceur-ws.org/Vol-2761/HAICTA_2020_paper58.pdf
An Integrated Indicator Based Knowledge Evaluation
System for Sustainable Tourism Management in Greece:
Empirical Approach of Multiple-criteria Decision
Analysis Making for Future Tourism Spatial Planning
Georgios Apostolidis
Department of Spatial Planning and Development, Faculty of Engineering, Aristotle
University of Thessaloniki, GR-54124, Greece; e-mail: gapostolidis@plandevel.auth.gr
Abstract. Indicators are a modern tool for measuring and identifying the quality
of goods such as tourism and recreation in a region. Index systems have been
established throughout Europe and almost all over the world to present thematic
directions through an evaluation of the current situation and analysis of the
features that relate to prospects for sustainable development. The purpose of this
paper is to present a system of tourism sustainability indicators for Greece which
is the only one available that is highly detailed and shows the diversity and the
new dimensions for tourism projects and studies. The results of this study
highlight the importance of such a system for a country, especially concerning
an area with tourist attraction to make it possible for the area to endure in the
future, based on institutionalized strategies and goals.
Keywords: Tourism Management; Operation research; Decision Support
System; AHP; Delphi.
1 Introduction
Leisure activities and tourism concepts, which comprise part of the developmental
process of the Greek state, according to Soutsas et al. (2006) can be used for the
regional development and the evaluation of the factors contributing to the development
and design of an area. The tourist characteristics of the Greek Prefectures present a
dynamic attraction for visitors and lead to the formation of tourist flows, thus, creating
a spatial background of cross-regional policy with economic, social, ecological,
environmental, and cultural cohesion (Polyzos and Arabatzis 2008a,2008b). It is now
perceived that spatial analysis and sustainability surveys for tourism (Curry and Luiz,
1992) have been applied in countries around the world since tourism is identified as a
key to the multi-thematic development (cultural, residential, environmental, urban
planning etc.) of a region (Xiao, 2013).
Taking into account the United Nations Agenda (2030), which is a plan of actions
and salvation for humanity, the planet and prosperity, Environmental Resources
comprise one of the 17 statutory goals (GOALS) of sustainable development on which
the Member States must focus at both the local and global level and in turn, exploit
385
sustainably and rationally by preserving and restoring sound ecosystems (services,
functions, values), to contribute to the mitigation of the chain of values of life and the
phenomenon of climate change (United Nations General Assembly, 2015;United
Nations Environment Assembly of the United Nations Environment Program,
2016;The 2030 Agenda for Sustainable Development).
It should be noted that sustainable tourism and sustainable tourism development are
the most important cross-cutting objectives and comprise an integral part of the United
Nations Agenda 2030. More specifically, a tool that the Institution anticipates and
encourages to be developed and used is that of the indicators which reflect a milestone
in the success of a global shift towards sustainable development (Economic and Social
Council United Nations, 2017;The Sustainable Tourism Program of the 10-Year
Framework of Programs on Sustainable Consumption and Production Patterns; The
Sustainable Tourism Program committed to driving the change, 2015).
According to the guidelines and Special Indicator Charts issued by the European
Commission (2020), research models can be identified as social, environmental,
tourism, and financial ones reflecting tailored country-specific impact strategy analysis
criteria.
What is more, Greece must proceed to a tourist portfolio by creating landscape
levels and systems, spatial analysis, modelling of tourism demand, and economic
environmental valuation in order to be able to defend itself by preserving its identity
in line with what commands the future of Europe, the next scientific development and
generation, as well as the economy. In addition, not only direction models have to be
followed but also the relevant directives and regulations of the European Parliament
and the Council of Europe, should be updated by the Greek state. From Greek Ministry
of Environment Energy and Climate Change (2013), it can be inferred that areas with
special forms of tourism and sophisticated features need to be rebuilt and supported in
order to achieve sustainable development and avoid the mythology and degradation of
the product. Therefore, modification and revision of Greek Ministry of Environment
Energy and Climate Change (2013) should bring the desired effect and curb
weaknesses in the country.
It is the aim of this research to create a system of tourism sustainability indicators
for Greece in order to forecast and define the strategies to be followed in particular
areas. After all, the ultimate goal of this research is the introduction and establishment
of a new tourism assessment tool for the future management of the tourist product
considered, as well as for purposes of decision making of suitable scenarios for
interventions in recreational areas and in the natural landscape.
2 Methodology - Sample
The sample size for the population of the Prefecture of Pella was estimated based
on the types of Simple Random Sampling (Zerva et al. 2018; Tsiantikoudis et al. 2013).
In effect, the sample size is 382 people and is representative of the general socio-
economic conditions of the local population.
386
2.1 Sustainability Indicators
In this section we present the evaluation of impact (AHP) in pairs along with the
analysis of effect (Delphi) that were constructed by encompassing the variables used
and which are the following with a consistency of significance of incidence more or
less (Srdjevic and Srdjevic 2011;Chen et al. 2013;Latinopoulos and Vagiona
2013;Srdjevic et al. 2017;Vasileiou et al. 2017)
A) Larger significant impact has values of: 1-3-5-7-9 (higher significance): 1=equal
incidence, 3=weak effect & 9=absolute prevalence of incidence when the evaluation
takes place bottom up.
B) Less significant impact is given by:1-1/3-1/5-1/7-1/9 (lower significance) when the
evaluation takes place top down.
For the evaluation of the above we constructed the following:
C) Vulnerability indicators showing whether there will be endurance and resistance in
the scenario, take values: (-1,0,+1).
D) Insight indicators reflecting the respondent's sense of how the scenario should be
applied in the near future, take values: (0 and+1).
E) Objective Crisis Indicators referring to the confidence interval of the survey, receive
values: (-1,0,+1).
G) Sustainability indicators referring to the sustainable application of the scenario over
time, take values: (-1,0,+1).
Finally, CI & CR and λmax were estimated according to the following formulas (Gao
and Hailu, 2012;Etongo et al. 2018):
CI = (λmax-n)/(n-1) (2)
CR = Cl/RI (3)
It is worth mentioning that other methods of multicriteria analysis have been
rejected (such as the PROMETHEE Group, the ELECTRE Group, the DEA Method
& Linear Programming) as they are mostly applied according to the available literature
with the financial data and the quantitative data that they deal with. It needs hardly be
argued that TOPSIS was rejected on the grounds that it is the MCDM method that is
used for the formation and mechanism of food production, supply and logistics of the
food market, and not for tourism and sustainable tourism development, and economics
of the environment, and values & preferences (Arabatzis and Grigoroudis
2010;Arabatzis et al. 2010;Velasquez and Hester 2013;Lima et al. 2014); Vlontzos et
al. 2014). Finally, for the influence matrices, the positive and negative effects scale
(Jose, 1996) was used with ascending and descending order respectively of panel
values of (high negative effect) -4,-3,-2,-1,0 (no effect) and (high positive effect)
+4,+3,+2,+1 (Siomkos, 2004). The decision-making system implemented could not
have been completed without the significant presence and extraction of the indicators
for tourism, which ultimately paved the way and the light to be given to the region so
as to bring significant benefits to users and to smooth out environmental, social, and
387
economic problems. After all, land use transformations in a spatial framework of
analysis encompass the contribution and presence of human activity as a whole.
The following figure shows the analytical scopes for the sustainability indicators for
tourism at all levels, that were applied and followed in order to produce the best
intervention scenarios eventually.
Fig. 1. Decision Making System of Sustainability Indicators.
Coding of DSS,
Level1 = Sustainability
Level2 = inENV, inSOC, inTOUR, inPOL
Level 3 = Environmental Indicators, Socio-Economic Indicators, Tourism Indicators,
Policy Indicators
Level4 = (1,2…n) Choice Strategy
Strategy1: Creating Jobs and Employment.
Strategy2: Absorption and Increase of Investments.
Strategy3: Reconstruction of Cultural and Natural Heritage Identity.
Strategy4: Land Usage & Sustainable Management of Environmental Resources.
Strategy5: Planning and Landscaping.
Strategy6: Development of projects and programs.
Strategy7: Programming of Recreational Values.
3 Research Area
The research area selected was the Thermal Springs of Pozar and the Voras Ski
Center (Pella Regional Unit-Greece). What follows is the analysis of the area
concerning its spatial design combined with the natural environment, tourism,
388
economy, society and the characteristics forming a comprehensive background of an
analysis of strengths, weaknesses, opportunities and threats.
Table 1. Spatial Planning of alternative forms of tourism in the research area.
Strengths (S)
* Alternative forms of tourism and leisure activities Opportunities (Ο)
activities*Areas with high natural value and importance
* Altitude
* Natural Resources (Forestry, Healing, Grassland, Aquatic, *Image formatting by the media
Herbs, Therams)
*Geothermy * Annual management
*Hydropower * Funding from European Programs
*Traditional and preserved settlements with a high cultural ID *Saving energy
*Nodal geographic location and location *Improving the quality of human life
*Modern transport networks * Synthesis of uses of land and natural landscapes
*Local Tourist Networking of Tourist Destinations
*Scheduling visitation
* Wind power Threats (T)
* Solar power * High quality tourist product by competitors
*Expensive destination due to the economic crisis in relation to the
Spatial Planning services provided
SWOT *Insufficient promotion
*Thefts
Weaknesses (W) * Bureaucracy
* Loss of demand abroad * Electricity problems
*Bulky European markets * Climatic conditions
*A decline in traditional characteristics over the years * Lack of skilled human resources
*Same day visits from nearby destinations * Insufficient legislative design and environment
* Low Quality of tourism infrastructure * High competition from Balkan countries
* Non-promoted local products *Pollution
* Missing cartographic data * Natural disasters-extreme phenomena (fires, floods, landslides,
* Inaccurate display of visitation erosion, avalanches snow, storms,ice)
*Fuzzy logic and sense of direction of site layout *Extensive-illegal logging
*Deficient management
4 Results
Τhe corresponding indicator weights and the Consistency Index & Consistency
Ratio estimators according to mathematical modelling and the Random Consistency
Index parameters for each indicator are presented. In the results of Level2 of the AHP
analysis, social indicators are identified as having the most weighing and priority with
the ones of the environment following next. However, moving to a next stage, it is
found that new criteria have to be taken into account in shaping the area. The indicators
of the scenario showed a promising outcome for the region.
389
priority vector (Weights)
inENV
0,40
0,30
0,20
0,10
priority vector
inPOL 0,00 inSOC
(Weights)
inTOUR
Fig. 2. Weights of four-dimensional Indicators.
The results from level 3, highlighted not only the critical parameters that were taken
into account in the planning of the tourist package and plan but also the interventions
that need to be implemented. Particular attention needs to be paid to the outcome of
the results on environmental indicators, and especially on RES which showed a
consistency of responses and high weight of sustainable choice for the region. Also,
concerning the tourist indicators, the second strand of each market and labor indicator
offered an important finding while the policy indicators highlighted the importance of
the state on this issue. Finally, the scales of insights, viability, objective judgment, and
vulnerability have graphically depicted the implementation of the scenarios and the
kilometer distance on index impact. What is also noteworthy, is the last core which
was formed with reference to all the indicators in an application with the corresponding
λmax & CI & CR.
The last part of the AHP analysis was completed with the analysis strategies for
each indicator. At this stage, the highest level of details is presented, with the results
being valuable to the design of the product. Most of the indicators have shown
consistent and sustainable results with a sustainable CR estimate of <10%, which also
highlights the involvement of the respondents in the project coordination. In particular,
the following environmental indicators did not receive high weighing: inFOR1,
inFOR3, inFOR7, inFOR9, inFOR12, inFOR14, inFOR17, inRAN1, inRAN2,
inRAN3, inGAME1, inGAME3, inWET1, inWET3, inWET5, inWET7, inWET8,
inWET9, inRES2, inRES4, inSPA1, inSPA2, inSPA3, inSPA5. From the Social and
Economic Indicators, the inSOC7, inSOC8, inSOC10, inSOC11 did not indicate
consistency and impact weighing. However, only one parameter, the one of
competition, inTOUR1, seems to be of no particular concern to the respondents, which
390
highlights a high-quality tourist product without the risk of competition. Finally,
concerning the policy indicators, inPOL13 & inPOL15, the responses provided suggest
that no strategy is needed. The remaining criteria have demonstrated strong
interpretable components of the direction that should be given to the region. It is worth
mentioning that this research is the only one that examines the tourist status of a region
and provides the maximum level of detail on the goals to be set for sustainable
development in Greece.
391
GOAL
inFOR1
inPOL16
inPOL15
inPOL14
inPOL13 inFOR2
inFOR3
inFOR4
inFOR5
inPOL12 0,35 inFOR6
inPOL11
inPOL10 inFOR7
inFOR8
inPOL9 0,30 inFOR9
inPOL8 inFOR10
inPOL7 inFOR11
inPOL6 inFOR12
inPOL5 0,25 inFOR13
inPOL4 inFOR14
inPOL3 0,20 inFOR15
inPOL2 inFOR16
inPOL1 inFOR17
inTOUR15 0,15 inRAN1 S1
inTOUR14 inRAN2
inTOUR13 0,10 inRAN3 S2
inTOUR12 inRAN4
inTOUR11 0,05 inRAN5 S3
inTOUR10 inGAME1
inTOUR9 0,00 inGAME2 S4
inTOUR8 inGAME3
inTOUR7 inGAME4 S5
inTOUR6 inGAME5 S6
inTOUR5 inWET1
inTOUR4 inWET2 S7
inTOUR3 inWET3
inTOUR2 inWET4
inTOUR1 inWET5
inSOC12 inWET6
inSOC11 inWET7
inSOC10 inWET8
inSOC9 inWET9
inSOC8 inWET10
inSOC7
inSOC6 inRES1
inRES2
inSOC5
inSOC4 inRES3
inRES4
inSOC3
inSOC2
inSOC1 inRES5
inSPA1
inSPA2
inSPA6 inSPA3
inSPA5 inSPA4
Fig. 3. Indicators of inSTORM Strategy Action.
The results showing the effects of the Delphi method at the specific analysis level
in the area of tourist interest under consideration are presented graphically in the light
of the dimensions of each indicator which was applied. Of the six regions in total, the
3, the Ski Center, the Airport and the Wetland, appear to be influenced by the system
392
of indicators applied. In particular, the R2 values showed high correlations between the
kilometer distances and the effects exercised according to the sample responses (0.865
and 0.8824, respectively).
140
120 y = 21,8x + 23
100 R² = 0,865
Effect (km)
80 Ski Resort_inENV_km
60 Ski Resort_inSOC_km
40 Ski Resort_inTOUR_km
20 Ski Resort_inPOL_km
0
0 1 2 3 4 5
indicators
Fig. 4. Effect of Indicators on kilometer distance to the ski center.
45
40
35 y = 7,5x + 2,5 Airport of Panagitsa (Flight
Effect (km)
30 R² = 0,8824 Center)_inENV_km
25 Airport of Panagitsa (Flight
20 Center)_inSOC_km
15 Airport of Panagitsa (Flight
10 Center)_inTOUR_km
5 Airport of Panagitsa (Flight
0 Center)_inPOL_km
0 1 2 3 4 5
indicators
Fig. 5. Effect of indicators on kilometer distance from the airport.
393
70
60
50
Wetland of
Effect (km)
Agras_inENV_km
40
Wetland of
30 Agras_inSOC_km
Wetland of
20 Agras_inTOUR_km
y = -15x + 70 Wetland of
10 Agras_inPOL_km
R² = 0,8824
0
0 1 2 3 4 5
indicators
Fig. 6. Effect of Indicators on Kilometer Distance to the Agra Wetland.
5 Conclusions
The results show how sustainable management of the Voras Mountain can be
achieved through different scenarios of tourism intervention, which are in line with the
European model and strategies set by the European Commission concerning climate
change.
The results of this research present new knowledge about the region and the Greek
area, but also updated, and improved the existing ones informing the international
literature on the subject as well. It has, therefore, become clear that a unified plan
should be created for these areas with particular tourist patterns. Over the years, local
regulation and society are regarded as the key to change and reform. The findings have
a key role and significant value for research, management, environment, economy,
spatial planning and policy since demand for recreation has a significant impact on the
market and sustainability indicators for tourism have been unknown in these areas so
far (future research paths).
The present research presents some key credible and valid supremacies such as the
focus of research planning and the research contribution, the motivation of the study,
the methodological support of the findings, its position in the existing subject field.
Furthermore, there is strong consistency between the goals, the findings and the
subsequent discussion (theoretical and empirical integration). In particular, the
research presented the tourist value of a leisure pole, that had never been investigated
previously, introducing a massive pillar of indicators (indicators for Sustainable
394
Tourism Management-inSTORM) with different dimensions and offering an excellent
design of interventions in the area along with their organization, resulting in the
contribution of the results to the initiation of a new dialogue and the development of a
new framework for tourism.
Currently, all public services have the knowledge and expertise as well as all the
necessary information tools which enable them to make their own tourism
management studies and intergovernmental tourism boards. Not only in Greece at the
local and regional level but also internationally, all countries should adopt legislation
(Horizon Europe 2021-2027), a standard management system for tourism and
sustainability, the same way that it has taken place for the forest, water and climate.
Acknowledgements.
Fundings:
-General Secretariat for Research and Technology (GSRT)
-Hellenic Foundation for Research and Innovation (HFRI)
of the Greek Ministry of Education Research and Religious Affairs.
Aristotle University of Thessaloniki-A.U.TH Research Committee,
National Project/95157/AUTh/GREECE.
Title: The role of economic assessment of environmental resources in
planning sustainable tourism development.
References
1. Arabatzis, G., Aggelopoulos, S. and Tsiantikoudis, S. (2010). “Rural Development
and LEADER+in Greece: Evaluation of Local Action Groups.” Journal of Food,
Agriculture & Environment 8 (1): 302–7.
2. Arabatzis, G. and Grigoroudis, E. (2010). “Visitors’ Satisfaction, Perceptions and
Gap Analysis: The Case of Dadia-Lefkimi-Souflion National Park.” Forest Policy
and Economics 12 (3): 163–72. https://doi.org/10.1016/j.forpol.2009.09.008.
3. Chen, Y., Yu, J. and Khan, S. (2013). “The Spatial Framework for Weight
Sensitivity Analysis in AHP-Based Multi-Criteria Decision Making.”
Environmental Modelling and Software 48: 129–40.
https://doi.org/10.1016/j.envsoft.2013.06.010.
4. Curry, B. and Luiz, M. (1992). “Environmental Issues in Tourism Management
Computer Modelling for Judgemental Decisions.” International Journal of Service
Industry Management 3 (1): 57–69. https://doi.org/10.1108/09564230310474165
Hierarchical.
5. Economic and Social Council United Nations. (2017). “Progress report on the 10-
year framework of programmes on sustainable consumption and production
patterns”, United Nations.
6. Etongo, D., Kanninen, M., Epule, T.E. and Fobissie, K. 2018. “Assessing the
Effectiveness of Joint Forest Management in Southern Burkina Faso: A
SWOTAHP Analysis.” Forest Policy and Economics 90: 31–38.
https://doi.org/10.1016/j.forpol.2018.01.008.
395
7. European Union social indicators - Europe. (2020). "Poverty and social exclusion
target", European Commission.
8. Europe Targets. (2020).
9. Gao, L. and Hailu, A. (2012). “Ranking Management Strategies with Complex
Outcomes: An AHP-Fuzzy Evaluation of Recreational Fishing Using an Integrated
Agent-Based Model of a Coral Reef Ecosystem.” Environmental Modelling and
Software 31: 3–18. https://doi.org/10.1016/j.envsoft.2011.12.002.
10. Greek Ministry of Environment Energy and Climate Change. (2013). “Approval of
Changes Special Framework for Spatial Planning and Sustainable Development for
Tourism and Strategic Environmental Impact Study That.”
11. Jose, P. D. (1996). “Corporate Strategy and the Environment: A Portfolio
Approach.” Long Range Planning 29 (4): 462–72. https://doi.org/10.1016/0024-
6301(96)00038-6.
12. Latinopoulos, D. and Vagiona, D. (2013). “Measuring the Sustainability of
Tourism Development in Protected Areas: An Indicator-Based Approach.”
International Journal of Innovation and Sustainable Development 7(3): 233.
https://doi.org/10.1504/IJISD.2013.056942.
13. Lima J., Rodrigues, F., Osiro, L. and Carpinetti, L.C.R. (2014). “A Comparison
between Fuzzy AHP and Fuzzy TOPSIS Methods to Supplier Selection.” Applied
Soft Computing Journal 21: 194–209. https://doi.org/10.1016/j.asoc.2014.03.014.
14. Polyzos, S. and Arabatzis, G. (2008a). “Determinant Factors of Tourist
Attractiveness of Greek Prefectures.” International Journal of Sustainable
Development and Planning 3 (4): 343–66. https://doi.org/10.2495/SDP-V3-N4-
343-366.
15. Polyzos, S. and Arabatzis, G. (2008b). “SPatial Distribution of Natural Resources
and Their Contribution to Regional DeveloPment. the Case of Greece.” Journal of
Environmental Protection and Ecology 9 (1): 183–99.
16. Siomkos, G. (2004). “Strategic marketing”. Stamouli, Athens, 2004.
17. Soutsas, K., Tsantopoulos, G., Arabatzis, G. and Christopoulou, O. (2006).
“Characteristics of Tourism Development in Mountainous Regions Using
Categorical Regression: The Case of Metsovo (Greece).” International Journal of
Sustainable Development and Planning 1 (1): 32–45. https://doi.org/10.2495/SDP-
V1-N1-32-45.
18. Srdjevic, B. and Srdjevic, Z. (2011). “Bi-Criteria Evolution Strategy in Estimating
Weights from the AHP Ratio-Scale Matrices.” Applied Mathematics and
Computation 218 (4): 1254–66. https://doi.org/10.1016/j.amc.2011.06.006.
19. Srdjevic, B., Srdjevic, Z., Dantas, Y. and Medeiros, P. (2017). “Multicriteria and
Social Choice Methods in Assessing Water Management Plans.” In HAICTA
2017, 541–53.
20. The Sustainable Tourism Programme committed to drive the change. (2015).
"Setting the Foundations for Collective Impact", Annual Magazine for 2015.
21. The Sustainable Tourism Programme of the 10-Year Framework of Programmes
on Sustainable Consumption and Production Patterns, UNEP.
396
22. Tsiantikoudis, S., Soutsas, K. and Apostolidis, G. (2013). “Contribution of Game
Resources to the Quality of Life : The Case of the Evros Prefecture.” Journal of
Environmental Protection and Ecology 14 (1): 240–46.
23. United Nations General Assembly. (2015). "Transforming our world: the 2030
Agenda for Sustainable Development", United Nations.
24. United Nations Environment Assembly of the United Nations Environment
Programme. (2016). "Sustainable consumption and production", United Nations.
25. United Nations Agenda (2030).
26. Vasileiou, M., Loukogeorgaki, E. and Vagiona, D. (2017). “GIS-Based Multi-
Criteria Decision Analysis for Site Selection of Hybrid Offshore Wind and Wave
Energy Systems in Greece.” Renewable and Sustainable Energy Reviews 73: 745–
57. https://doi.org/10.1016/j.rser.2017.01.161.
27. Velasquez, M. and Hester, P. (2013). “An Analysis of Multi-Criteria Decision
Making Methods.” International Journal of Operations Research 10 (2): 56–66.
https://doi.org/10.1007/978-3-319-12586-2.
28. Vlontzos, G., Arabatzis, G. and Manos, B. (2014). “Investigation of the relative
efficiency of LEADER + in rural areas of Northern Greece”. International Journal
of Green Economics, 8(1), p. 37-48.
29. Xiao, H. (2013). “Key Concepts in Tourism Research.” Annals of Tourism
Research 42: 449–50. https://doi.org/10.1016/j.annals.2013.05.007.
30. Zerva, A., Tsantopoulos, G. Grigoroudis, E. and Arabatzis, G. (2018). “Perceived
Citizens’ Satisfaction with Climate Change Stakeholders Using a Multicriteria
Decision Analysis Approach.” Environmental Science and Policy 82: 60–70.
https://doi.org/10.1016/j.envsci.2018.01.008.
397