Intuitionistic fuzzy multi-criteria decision making framework based on life cycle environmental, economic and social impacts: The case of U.S. wind energy

Gümüş, Serkan; Küçükvar, Murat; Tatari, Ömer

doi:10.1016/j.spc.2016.06.006

Cited by 76 publications

(39 citation statements)

References 97 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Otherwise, there is a risk that the profitability of wind energy investments will decrease [5]. Political instability can trigger the deterioration of the peaceful environment in the society, which is concerning given that another risk factor for wind energy investors is social risk [12].…”

Section: Literature On the Risk Factors Of Wind Energy Investmentsmentioning

confidence: 99%

See 1 more Smart Citation

Multi-Faceted Analysis of Systematic Risk-Based Wind Energy Investment Decisions in E7 Economies Using Modified Hybrid Modeling with IT2 Fuzzy Sets

Qiu¹,

et al. 2020

View full text Add to dashboard Cite

This study aimed to analyze the systematic risks of wind energy investments. Within this framework, E7 countries are included in the scope of the examination. A large literature review was carried out and 12 different systematic risk factors that could exist in wind energy investments were identified. The analysis process of the study consisted of two different stages. First, the specified risk criteria were weighted with the help of the interval type 2 (IT2) fuzzy decision-making trial and evaluation laboratory (DEMATEL) method. Second, E7 countries were ranked according to the risk management effectiveness in wind energy investments. In this process, the IT2 fuzzy Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) approach was taken into consideration. The findings show that volatility in exchange rates and interest rates were the most important risks in wind energy investments. In addition, it was determined that China and Indonesia were the most successful countries in managing risks in wind energy investments. In contrast, India, Russia, and Turkey were determined to be the least successful. Additionally, the IT2 fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method was applied as a robustness check of the extended VIKOR method. It was concluded that the ranking results of the IT2 fuzzy TOPSIS method were similar to the results of the IT2 fuzzy VIKOR. It can be understood that the proposed ranking method was consistent with the comparative analysis results. From this point of view, it was observed that countries should take measures regarding their exchange rate and interest rate risks in order to increase the efficiency in wind energy investments. In this context, companies should first ensure that they do not have a foreign exchange short position in their balance sheets by conducting an effective financial analysis. In addition, it is important to use financial derivatives to minimize the exchange rate and interest rate risks. Using these results, it will be possible to manage this risk by taking the reverse position for the existing foreign currency and interest risk. In this way, it will be possible to increase the efficiency of wind energy investments, which will contribute to the social and economic development of each respective country.Energies 2020, 13, 1423 2 of 25 their own energy resources can benefit from these resources [1]. This situation gives these countries a serious cost advantage. On the other hand, countries that do not have sufficient energy resources have to supply the energy they need from outside, which makes these countries dependent on energy. Because of this problem, countries are developing several strategies to produce their own energy [2].Renewable energy sources are an important alternative that allows countries to produce their own energy. The most important feature of these energy alternatives, which come in different forms, such as wind, solar, biomass, geothermal, and hydroelectricity, is that they obtain their resources from natur...

show abstract

Section: Literature On the Risk Factors Of Wind Energy Investmentsmentioning

confidence: 99%

“…Political problems (C4) [4,5,12] Social conflicts (C5) [7,13] Legal issues (C6) [14,23] Market-based factors (D3)…”

Section: Macroeconomic Factors (D1)mentioning

confidence: 99%

Multi-Faceted Analysis of Systematic Risk-Based Wind Energy Investment Decisions in E7 Economies Using Modified Hybrid Modeling with IT2 Fuzzy Sets

Qiu¹,

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Choosing purely social indicators is often challenging. Consequently, some studies combine the social and the economic dimension and use socio-economic indicators for their analysis [79,80,83,89,150]. Others combine the social dimension with political implications [102,133,134], which is an attempt to include the dimension of public acceptance into S-LCA.…”

Section: Indicatorsmentioning

confidence: 99%

“…Fuzzy set theory provides a method to quantify linguistic terms [89] often obtained through expert elicitation, to determine the weights of criteria. Ren, et al [101] use fuzzy set theory to quantify the social indicators.…”

Section: Limitationsmentioning

confidence: 99%

Review of Sustainability Assessment Approaches Based on Life Cycles

et al. 2019

View full text Add to dashboard Cite

Many different approaches have been developed to quantify and evaluate sustainability. Here a review is performed on sustainability assessment based on Life Cycle Thinking, which mostly means Life Cycle Sustainability Assessment (LCSA). Until the end of 2018, 258 publications can be found, from which 146 include a case study. The highest number of publications appeared between 2016 and 2018 and, compared to the years before 2016, the number of authors has increased. However, in recent years the focus has been more on case studies than on methodological aspects of LCSA. The presented holistic approaches for LCSA are either too broad or too narrow for scientific guidance. Therefore, many questions concerning LCSA are still open, e.g., regarding definition of sustainability dimensions and the desire or need for multi-criteria decision-analysis. An underlying problem is the lack of discussion about sustainability concepts. The momentum in the community to perform case studies for LCSA should be used to also develop more guiding principles.

show abstract

“…As far as decision problems closely related to the project design of a wind farm are concerned, such an issue was discussed in [15,48]. To the wind farm design are also related technical aspects of wind turbines [16,49,50] as well as, in a broader context, risk assessment [51]. On the other hand, in [52], a decision model used for evaluating the influence of a wind farm on the environment in a given location was presented.…”

Section: Literature Reviewmentioning

confidence: 99%

Inter-Criteria Dependencies-Based Decision Support in the Sustainable wind Energy Management

Ziemba

2019

Energies

View full text Add to dashboard Cite

Decision problems related to the wind energy require considering many, often interrelated and dependent on each other, criteria. To solve such problems, decision systems based on Multi-Criteria Decision Analysis (MCDA) methods are usually used. Unfortunately, most methods assume independence between the criteria, therefore, their application in decision problems related to the wind energy is debatable. This paper presents the use of the Analytic Network Process (ANP) method to solve a decision problem consisting in selecting the location and design of a wind farm. The use of the ANP method allows capturing the complexity of the decision problem by taking into consideration dependencies between criteria. As part of the verification of the solution, the results of the ANP method were compared with those of the Analytic Hierarchy Process (AHP) method, which uses only hierarchical dependencies between criteria. The conducted verification showed that the inter-criteria dependencies may have a significant influence on the obtained solution. On the basis of the conducted sensitivity analysis and the research into robustness of the rankings to the rank reversal phenomenon, it has been found out that the ranking obtained with the use of the ANP is characterized by a higher quality than by means of the AHP.

show abstract

Intuitionistic fuzzy multi-criteria decision making framework based on life cycle environmental, economic and social impacts: The case of U.S. wind energy

Cited by 76 publications

References 97 publications

Multi-Faceted Analysis of Systematic Risk-Based Wind Energy Investment Decisions in E7 Economies Using Modified Hybrid Modeling with IT2 Fuzzy Sets

Multi-Faceted Analysis of Systematic Risk-Based Wind Energy Investment Decisions in E7 Economies Using Modified Hybrid Modeling with IT2 Fuzzy Sets

Review of Sustainability Assessment Approaches Based on Life Cycles

Inter-Criteria Dependencies-Based Decision Support in the Sustainable wind Energy Management

Contact Info

Product

Resources

About