An Empirical Research of the Underdevelopment of the Welfare State

정의룡,

doi:10.18854/kpsr.2012.46.5.004

Cited by 5 publications

(7 citation statements)

References 7 publications

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“…The fuzzy-set analysis determines the number of memberships by categorizing the standards, and these standards consist of the ideal type formulated based on the theoretical background [58]. Accordingly, many recent studies are applying the fuzzy-set analysis to categorize individual ideal types [59,60].…”

Section: Methodology and Measurement Frameworkmentioning

confidence: 99%

Drivers and Ideal Types towards Energy Transition: Anticipating the Futures Scenarios of OECD Countries

Huh

Yoon

Chung

2019

IJERPH

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This study aims to identify the ideal types of energy transition of the thirty-five Organization for Economic Cooperation and Development (OECD) countries and to explore their implications using the fuzzy-set ideal type analysis. It then anticipates the futures scenarios of OECD member countries towards energy transition by placing the ideal type results. In particular, looking at the possibility of the futures towards energy transition, this study attempts to set up the comprehensive measurement framework of energy transition embracing the three key drivers (energy system (E), energy citizenship (S), and digital technology (T)). As a result, the eight OECD countries, including Denmark (fuzzy score 0.889), UK (0.800), and Norway (0.788) belonging to Type 1 (E*S*T) with the all high features of three key drivers, are expected to have ‘Outlier (super-potent) Futures’ of energy transition. The twelve countries of Type 2 (E*S*t), 3 (E*s*T), and 5 (e*S*T) with two high features of three ones will belong to the ‘Best (reformative) Futures’. The five countries of Type 4 (E*s*t), 6 (e*S*t), and 7 (e*s*T) with one high feature among three ones will be located in ‘Business-As-Usual Futures’. Finally, the ten countries, including Hungary (fuzzy score 0.881), Greece (0.716), Israel (0.679) belonging to Type 8 (e*s*t) with all three low features, are expected to have ‘Worst (declined) Futures’ of energy transition.

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Section: Methodology and Measurement Frameworkmentioning

confidence: 99%

Drivers and Ideal Types towards Energy Transition: Anticipating the Futures Scenarios of OECD Countries

Huh

Yoon

Chung

2019

IJERPH

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“…Through this process it analyzes the degree of memberships of each category, translating the existing original data results into fuzzy-set membership scores. As the number of the sets is decided by the ideal type, different from the existing cluster analysis, through Fuzzy-Set Ideal Type Analysis that this research conveys, more systematic categorization and interpretation become available [59,60,64].…”

Section: Fuzzy-set Multiple Conjunctural Analysis and Ideal Type Analmentioning

confidence: 98%

“…While these types are confronted by criticism to be categorized by arbitrary interpretation of the researchers, however, the fuzzy-set analysis determines the number of memberships by categorization standards that consist the ideal type extracted under theoretical background [51,58]. Accordingly, many recent studies are applying fuzzy-set analysis to categorizing types [59,60].…”

Section: The Rationale Of Fuzzy-set Analysismentioning

confidence: 99%

Towards a Green State: A Comparative Study on OECD Countries through Fuzzy-Set Analysis

2018

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This study aims to develop an empirical measurement framework of the green state and compare twenty-four OECD (Organization for Economic Cooperation and Development) countries’ cases through the fuzzy-set multiple conjunctural analysis and the ideal type analysis. Based on the analysis model of the outcome set (Sustainable Development Goal Index) and the causal sets of seven variables on the four green state categories (‘ecological authoritarian state’, ‘ecological modern state’, ‘ecological democracy state’, and ‘ecological welfare state’), this study reveals the following results. Among OECD member countries, if ones have high environmental tax, high environmental innovation (patent), high economic development and democracy, high levels of environmental governance and social expenditure, or have high economic development and democracy, and high levels of environmental governance and environmental health, they can be seen to have reached a high level of green state (consistency: 0.980, total coverage: 0.675). Also, the thirteen ideal types of green state of twenty-four OECD countries were derived. Norway (fuzzy-set membership score of 0.515) is a country of Type 1, with a characteristic of ‘strong green state’ having all high features of the four green state categories. Greece (membership score, 0.692) and Ireland (0.577) belong to Type 13, characterized by ‘weak green state’ with all four low features. As a result, the green state types of the twenty-four OECD countries can be assorted into five levels: ‘Strong Green State’, ‘Quasi-Strong Green State’, ‘Quasi-Green State’, ‘Quasi-Weak Green State’, and ‘Weak Green State’.

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“…The Fuzzy-set analysis determines the number of memberships by categorization standards that consist of the ideal type extracted under theoretical background [29,36]. Accordingly, many recent studies are applying Fuzzy-set analysis to categorizing types [37,38].…”

Section: The Rationale Of Fuzzy-set and Ideal Type Analysismentioning

confidence: 99%

“…Through this process it analyzes the degree of memberships of each category, translating the existing original data results into fuzzy-set membership scores. As the number of the sets is decided by the ideal type, unlike the existing cluster analysis through Fuzzy-set Ideal Type Analysis which this research conveys, more systematic categorization and interpretation become available [37,38].…”

Section: The Rationale Of Fuzzy-set and Ideal Type Analysismentioning

confidence: 99%

The Time-Series of Energy Mix and Transition: A Comparative Study of OECD Countries through the Fuzzy-Set Analysis

2018

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This study aims to analyze the global trends of energy mix and energy transition from a chronological view (from Y1995 to Y2015) and identify the actual results based on the empirical findings. It sets up a measurement framework of energy mix (four energy sources: fossil fuel (F), hydroelectric (H), renewable (R), and nuclear (N)), and compares thirty-four Organisation for Economic Cooperation and Development (OECD) countries’ cases through the fuzzy-set ideal type analysis. In short, twelve ideal types of energy mix of the thirty-four OECD countries were derived in Y1995; eleven ideal types in Y2000, thirteen ideal types in Y2005, twelve ideal types in Y2010, and fifteen ideal types in Y2015, respectively. This study particularly reveals the gradual change of the features of energy transition, although an epoch-making trend of overall energy transition in OECD countries is not identified. For example, from1995 to 2010, in the case of Type 7 (F*h*r*N) with a characteristic of ‘pan-conventional energy-centered mix’ having two high features (F, N), and of Type 8 (F*h*r*n), characterized by ‘fossil fuel-centered energy mix’ with one high feature (F), seven to eight countries were steadily included, but in 2015 there was a significant decrease to four countries (solely Type 7). Throughout the five stages from 1995 to 2015, the type with the largest number of countries (20) was Type 10 (f*H*R*n, ‘pan-renewable energy-centered type’) led by hydroelectric (H) and renewable energy sources (R), followed by the second most, Type 12, (f*H*r*N, ‘hydro & nuclear-centered type’, characterized the high features of H and N) with nineteen countries.

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An Empirical Research of the Underdevelopment of the Welfare State

Cited by 5 publications

References 7 publications

Drivers and Ideal Types towards Energy Transition: Anticipating the Futures Scenarios of OECD Countries

Drivers and Ideal Types towards Energy Transition: Anticipating the Futures Scenarios of OECD Countries

Towards a Green State: A Comparative Study on OECD Countries through Fuzzy-Set Analysis

The Time-Series of Energy Mix and Transition: A Comparative Study of OECD Countries through the Fuzzy-Set Analysis

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