Multifactorial Components Analysis of the Renewable Energy Sector in the Oecd Countries and Managerial Implications

Androniceanu, Ane-Mari; Georgescu, Irina; Dobrin, Cosmin; Drăgulănescu, Irina-Virginia

doi:10.17512/pjms.2020.22.2.03

Cited by 16 publications

(11 citation statements)

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“…Zarikas et al (2020) made an analysis which resulted in clustering countries with respect to active cases, active cases per population and per area based on the epidemiological data of John Hopkins Coronavirus Resource Center. Some other researchers proposed algorithms through an intelligent fusion of healthcare and simulated mobility data, and their results demonstrated the significance of dynamic clustering for reducing lockdown coverage, economic loss, and military unit deployment (Rahman et al, 2020;Androniceanu et al 2020a;. By analysing the number of cases and deaths in each country, James and Menzies (2020) found similar clusters of countries and determined the most effective strategies.…”

Section: Literature Reviewmentioning

confidence: 98%

Dynamic indexing and clustering of government strategies to mitigate Covid-19

Kinnunen¹,

Georgescu²,

Hosseini³

et al. 2021

EBER

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The objective of the article is to identify the reference group of countries with similar Covid strategies and other groups with their performance success, and to construct a composite Covid Mitigation Index for comparative purposes, thus, implying how to redesign the strategic policies. Research Design & Methods: Gaussian Mixture Modelling and Factor Analysis: the main design is quantitative, using Gaussian Mixture Modelling to find the optimal number of country clusters, and Factor Analysis with Principal Axis Factoring (FA-PAF) to build a composite index of governmental policies. Data includes eight mitigation policy variables and three supporting economic policy variables. Data are aggregated to form three periods and the cluster changes are identified by Gaussian Mixture Modelling. Then, the Covid Mitigation Index (CMI) is constructed by FA-PAF to obtain a comparative measure over the periods and the country clusters. The results were obtained by means of R studio and SPSS. Findings: The dynamic clustering leads to a decreasing number of clusters from nine clusters in the first period (January-February 2020), four clusters in the second period (March-April 2020), and two clusters in the third period (May-June 2020). In the first period, China (with CMI=48) took serious actions forming its own cluster, while 11 other countries (with CMI>10), e.g., early affected European countries such as Italy and Spain and large Asian countries such India and Indonesia, took moderate actions. In the second period all cluster averages were greater than China's in the first period, i.e., most world countries were dedicated to fight Covid-19. In Europe, Italy, San Marino and France showed the highest CMI values, similarly to Iraq and Palestine in the Middle East, Peru and Honduras in the Latin America, and China, India and Indonesia in Asia. In the third period, cluster averages showed even tighter policies even though 42 countries had lower CMI values than previously. Implications & Recommendations:The approach provided a big picture for decision makers both in business and in governments. The key idea was to reveal reference groups of countries which help governmental actors to design and adapt their strategies over time by learning by their own experience and the results of the better performing clusters. It was suggested that a multi-criteria approach accounting for individual government's preferences over health and economy is used along with the presented approach. Contribution & Value Added: Clustering with Gaussian Mixture Models and factor analysis based on Principal Axis Factoring for composite-index building were used. The methods are well-established, but they were applied in a novel way dynamically over time and for the composite CMI. CMI was built on two factors which identified the structure of mitigation policies and economic policies. The development of governmental polices over the first cycle of Covid-19 pandemic was described. Article type:research article

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Section: Literature Reviewmentioning

confidence: 98%

Dynamic indexing and clustering of government strategies to mitigate Covid-19

Kinnunen¹,

Georgescu²,

Hosseini³

et al. 2021

EBER

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“…The technology acceptance model (TAM), which was adopted for this study, predicts the intention to accept technology by individual users [35,36]. The model, developed by Davis [37], highlights the various factors that influence individual behavior towards the use of the new technology. The technology acceptance model (TAM) suggests that the level of acceptability of new technology by individuals is determined by factors including the perceived ease of use and the perceived usefulness.…”

Section: Theoretical Literature and Model Developmentmentioning

confidence: 99%

Evaluating Consumers’ Adoption of Renewable Energy

et al. 2021

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The purpose of this study was to evaluate the consumers’ adoption of renewable energy in Poland. The study focused on finding out the factors that influence the adoption of the technology, considering its importance in conserving the environment. The study was conducted using a quantitative method, with primary data collected from 467 households using renewable energy technology in Poland. The research adopted the TAM model. The independent variables of the study included renewable energy initial cost, environmental concern, risk and trust for renewable energy, ease of use, financial incentives, and relative advantage. The dependent variable was renewable energy adoption. Structural equation modelling (SEM) was used to analyze the study hypotheses. The research found out that environmental concerns, ease of use, financial incentives, and relative advantage have a positive and significant influence on adoption of renewable energy technology in Poland. However, renewable energy initial cost and risk, and trust for renewable energy did not significantly influence renewable energy adoption. The study recommended that the stakeholders should consider the aspects of environmental concern as a key role player in pushing for adoption of renewable energy. The government, non-governmental organizations, and concerned stakeholders should consider giving incentives towards renewable energy adoption. Creating awareness regarding the benefits and strengths of renewable energy should be prioritized to the households.

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“…The scientific community conducts discussions and studies of economic efficiency regarding renewable energy sources [18,19]. Given the criticism of the current approach to assessing economic efficiency, the criteria and methods for measuring it are widely discussed [20,21].…”

Section: Introductionmentioning

confidence: 99%

A Scoping Review of Renewable Energy, Sustainability and the Environment

et al. 2021

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The article aims to identify the latest trends in research on renewable energy, sustainability and the environment. A total of 92,873 publications from 123 Scopus sources for 2020–2021 are compared using the scoping review method. The results show that the most cited works in this sample are those by authors from the Asian region. The research of these authors focuses on the security, efficiency and reliability of separate elements in energy systems. Besides, the paper considers the problems regarding COVID disease along with the renewable energy sources, perovskite and organic solar panels, nanostructured materials and high energy density. Finally, the paper analyses applications of computer science methods in research on renewable energy, sustainability and the environment. The findings evidently show that recent advancements in computer science methods were not extensively used in the discussed research domain and give a great room for novel strategies of prognosing, simulation and processes optimisation.

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Multifactorial Components Analysis of the Renewable Energy Sector in the Oecd Countries and Managerial Implications

Cited by 16 publications

References 0 publications

Dynamic indexing and clustering of government strategies to mitigate Covid-19

Dynamic indexing and clustering of government strategies to mitigate Covid-19

Evaluating Consumers’ Adoption of Renewable Energy

A Scoping Review of Renewable Energy, Sustainability and the Environment

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