Evaluation of the Prosperity Levels of EU and EU Candidate Countries by Clustering and PSI Method

Evaluation of the Prosperity Levels of EU and EU Candidate Countries by Clustering and PSI Method

İbrahim Budak (Pamukkale University, Turkey), Günay Kiliç (Pamukkale University, Turkey) and Arzu Organ (Pamukkale University, Turkey)
DOI: 10.4018/978-1-7998-1188-6.ch005


Although prosperity is often associated with the word wealth, it also includes other factors that may be independent of wealth, such as happiness and health. The prosperity state can be defined as a developing, growing, wealth state and a successful social status. Increasing the levels of prosperity is a goal of states. States can create communities in cooperation with other states to improve their level of prosperity. One of these communities is the European Union (EU), which is established by European states. This chapter evaluates the position of EU member states and EU candidate countries' prosperity levels compared to world states. In the study, 2018 Legatum Institute prosperity index of 149 countries was used. These countries are divided into groups by using clustering analysis from data mining techniques. The countries are evaluated using the Preference Selective Index (PSI).
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Literature Review

Some of the data mining techniques used in the study, clustering and MCDM methods, are summarized in Table 1.

Table 1.
Some studies with clustering and psi method
Gomez-Muñoz & Porta-Gándara (2002: 171-182).Modeling of Renewable Energy Systems
Weatherill & Burton (2009: 565-588).Separation of Shallow Seismic Welding Regions
Winters et. (1997: 1369-1374).Classification of Shoulder Pain
Armstrong et. (2012: 2198-2205).Investigation of the Heterogeneity of Geriatric Population
ClusteringPark et. (2013: 910-915).Cluster Selection for Wireless Sensor Network
Ada (2001: 319-332).Evaluation of the EU and Turkey's Development
Öz et. (2009: 1-29).Comparison of EU and Turkey's Human Capital
Turanlı et. (2006: 95-108).Examining the Economic Similarities of EU and EU Candidate Countries
Maniya & Bhatt (2011: 330-349).Selection of Flexible Production System
Madić et. (2017: 214-220).Determination of Laser Cutting Process Conditions
Khorshidi & Hassani (2013: 999-1010).Materials Selection
Sawant et. (2011: 176-181).Automatic Vehicle Selection
PSIMesran et. (2017: 230-234).Determination of Education Scholarship Recipients
Jahan et. (2012: 411-420).Ranking Stage of Material Selection Process
Joseph & Sridharan (2011: 201-216).Ranking of Scheduling Rule Combinations
Attri & Grover (2015: 207-216).Evaluation of the Design Phase of the Production System Life Cycle
Borujeni, M. P., & Gitinavard (2017: 207-218).Mining Contractor Selection

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