INTRODUCTION OF EEPSE GREEN ECONOMY INDEX FOR THE ANALYSIS OF REGIONAL TRENDS

The importance of analysing green economy has long been acknowledged by the international scientific community. Still there is strong demand for a comprehensive model which would serve as a scoreboard to assess a country’s progress on green track and identify regional developments. Having dwelled upon this task, this article suggests using an original method – so called EEPSE Green Economy Index (which combines educational, economic, political, societal and environmental indicators), based on the Quintuple Helix Model, to analyse green economy trends in the EU countries. The results of the present study advocate the efficiency of such a tool and show its potential in performing current analysis, as well as predicting future tendencies related to sustainable development.


Introduction
Scientific interest towards green economy has been growing constantly since the end of the 20th century and throughout the beginning of the 21st centurythe period, which saw a series of global forums devoted environmental issues, mainly to global warming. Among the most important events "Earth Summit" in Rio De Janeiro (1992), Kyoto Protocol (1997, the Copenhagen Climate Change Conference (2009), Paris agreement on climate change (2015) etc. are to be mentioned. All these events marked significant stages in elaborating a strategy for sustainable development by both scholars and decision-makers. Sustainable development in general is a continuous process of satisfying needs of the present and future generations. The definition is unanimously accepted, alas ways of implementation of this approach towards development is under continuous discussion (Tvaronavičienė et al., 2015;Strielkowski et al., 2016;Tvaronavičienė, 2017;Razminienė, Tvaronavičienė, 2018;Eddelani et al., 2019).
In Europe this issue received an additional impetus with the adoption of European Green Deal (presented on 11 December 2019) -a roadmap with actions to boost the efficient use of resources by moving to a clean, circular economy, restore biodiversity and cut pollution.
Achieving such ambitious goals goes in line with the development of green economy in European countries. Still, scholars and policymakers seem to lack an efficient instrument to measure a country's record on this track, and to draw comparison between groups of states. In line with existing and commonly acknowledged by scientific community indexes such as The Global Green Economy Index (GGEI), The Green Growth Index (GGI), The Global Green Finance Index (GGFI), Environmental Performance Index (EPI), whose components were used in the present study, this article aims to work out a new Green Economy Index based on the Quintuple Helix model, which would take into account educational, economic, political, social and environmental aspects of the phenomenon. Thus it is proposed to call it EEPSE Green Economy Index. It is argued that with its help it's possible not only to measure EU27 + UK countries' performance with regard to green economy, divide them into main clusters, revealing divergence/convergence processes within these groups, but also analyse different political, economic and societal events related to sustainable development.

Terms and definitions
To highlight the multidisciplinary and multidimensional nature of the phenomenon the qualitative contentanalysis of definitions of various green concepts has been performed (see Table 1). In this type of analysis (specifically latent analysis) data are presented in words and themes, which makes it possible to draw some interpretation of the results, and the researcher seeks to find the underlying meaning of the text (Bengtsson, 2016). Table 1. Definitions of various green concepts

Term
The introducing entity, year

Characteristics and definitions
Green economy Swart & Groot, 2020 A green economy is one which is low carbon, is resource efficient, and is socially inclusive… a green economy also comprehends the design and implementation of specific policy instruments targeted at the environment Green economy Fulai, 2010 A green economy is typically understood as an economic system that is compatible with the natural environment, is environmentally friendly, is ecological, and for many groups, is also socially just Green growth OECD, 2010 Green growth means promoting economic growth while reducing pollution and greenhouse gas emissions, minimising waste and inefficient use of natural resources, and maintaining biodiversity. Green growth means improving health prospects for populations and strengthening energy security through less dependence on imported fossil fuels. It also means making investment in the environment as a driver for economic growth Green innovation Leal-Millán & Antonio, 2020 Green innovations are all type of innovations that contribute to the creation of key products, services, or processes to reduce the harm, impact, and deterioration of the environment at the same time that optimizes the use of natural resources… and channel an appropriate use of the natural resources to improve the human well-being … which could contribute to sustainable development. Kemp & Pearson, 2007 (MEI project for the European Commission) the production, assimilation or exploitation of a product, production process, service or management or business method that is novel to the organization (developing or adopting it) and which results, throughout its life cycle, in a reduction of environmental risk, pollution and other negative impacts of resources use (including energy use) compared to relevant alternatives Source: examination of existing bibliography

Green innovation
As it can be seen from the definitions above (keywords are underlined), the aspects of the phenomenon include education ("novel methods", "assimilation"), economy ("creation of products, goods and services", "economic system"), politics ("organizational structures" and "institutional arrangements"), society ("to improve the human well-being", "socially just", "for many groups") and natural environment ("environmental improvements", "ecological", "biodiversity"). This fact provides grounds for applying the Quintuple Helix model to its analysis.

Methodology
The Quintuple Helix model, which is used as basis for the EEPSE Green Economy Index, has several features. First, it is one of the models based on the quality management of effective development, restoring balance with nature and preserving Earth's biological diversity. As Barth (Barth, 2011) puts it, this model can solve existing problems by applying knowledge and know-how, as it focuses on the social (public) exchange and transfer of knowledge within the subsystems of a particular state or a national state. Second, the innovative Quintuple Helix model explains the way knowledge, innovations, and environment (natural environment) are interrelated (Carayannis and Campbell, 2010;Barth, 2011). The Quintuple Helix model is both interdisciplinary and 418 transdisciplinary: the complexity of the five-spiral framework implies that a full analytical understanding of all spirals requires the continuous involvement of the entire disciplinary spectrum, ranging from Natural Sciences (due to inclusion of the natural environment) to Social Sciences and Humanities, to promote and visualize the system of collaboration between knowledge, know-how, and innovations for more sustainable development (Carayannis and Campbell, 2010). A visualized description of the model can be seen at Fig.1: Figure 1. The subsystems of the Quintuple Helix model. Source: Etzkowitz and Leydesdorff 2000;Carayannis andCampbell, 2009, 2010. As it is described at the figure, the first subsystem of this model is education, which forms the necessary "human capital". The secondeconomy -focuses on the "economic capital" (namely resource productivity, energy production and consumption, sustainable entrepreneurship etc). The third subsystempolitics -i.e. "political and legal capital" (in our context it refers to environmental regulations, taxes, international treaties etc.). The fourth subsystemsocietal -unites the "social" and the "information" capital (it includes, for instance, green economy perception, press freedom, level of democracy etc). Finally, the fifth subsystemenvironment (e.g. biodiversity, pollution etc.) provides society with the "natural capital".
All subsystems in the Quintuple Helix, as it can be seen at Figure 2, perform functions which influence each other (Ibid). In the innovative Quintuple Helix model, the natural environment is defined as an opportunity for further development and provision of sustainable development and co-evolution of the knowledge economy, knowledge society and democracy, which also influences the way we perceive and organise entrepreneurship (Etzkowitz and Leydesdorff 2000;Carayannis and Campbell, 2006, 2009, 2010Barth, 2011;Aleksejeva et al., 2020).

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ISSN 2345-0282 (online) http://jssidoi.org/jesi/ 2021 Volume 9 Number 1 (September) http://doi.org/10.9770/jesi.2021.9.4126) Figure 2. The Quintuple Helix model and its functions. Source: Lavrinenko et al., 2019 Now that the use of the Quintuple Helix has been substantiated, it seems reasonable to define specific indicators related to green economy. Previously a similar task was accomplished by the authors of this paper in 2019 (O. Lavrinenko et al., 2019), and the results of that study were taken as basis. Still, this time the set of all available statistical and integrated indicators corresponding to the Quintuple Helix model in the EU countries, which comprised the empirical base of the research, has been updated and broadened, so that each of the subsystems is represented by ten indicators (which makes 50 indicators in total). New indicators have been added (see Appendix 1), the technique has been improved.
All indicators were standardized, and then, in order to perceive them better, the transition to T scale by the formula T=50+10*z was made. Factors corresponding to the Quintuple Helix model are obtained as arithmetic means of the corresponding indicators; the integrated indicator is obtained as the arithmetic mean of the values of five subsystems. Hereinafter the overall indicator it is called EEPSE Green Economy Index.
Yet the feature of this paper is that it also seeks to test the potential of the proposed Index in analysing and foreseeing different political, economic and societal events related to green innovation and sustainable development. Particularly, in the present article it is applied to plug-in electric vehicle market share in the EU countries in 2020.

Research results
According to the results of the research, Sweden became the leader of the list of the EU countries with EEPSE Green Economy Index equalling 58,97. The second place was taken by the United Kingdom (58,14). At the same time Denmark (57,75) outscored Germany (56,42) in 2020 study. The top countries also include Finland (56.02), France (54,69) and the Netherlands (54.38).
As for the list of worst performers of the ranking, it includes Poland (43.21), Bulgaria (43.46), Cyprus (43.50), Hungary (44.94) and Romania (45.25). These results generally correspond to those, obtained during the first stage of the research (O. Lavrinenko et al., 2019).

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ISSN 2345-0282 (online) http://jssidoi.org/jesi/ 2021 Volume 9 Number 1 (September) http://doi.org/10.9770/jesi.2021.9.4126) 420 The cluster analysis was carried out in the five-factor EEPSE space. With the help of this pattern all EU countries were grouped into two homogeneous clusters (see Map, Figure 3). The first cluster (Cluster +, Table 4) includes countries which are characterized by higher value of indicators according to all five subsystems; other countries (Cluster -, Table 5) are characterized by a lower level of these indicators. The importance of predictors was as follows: 1.st political factor (the most important); 2.nd education; 3.rd society; 4.th environment; 5.th economy (the least important). This fact appears to be very interesting, since economy has the least importance when defining clusters, while politics plays the most important role. Considering the mean values of the subsystems in two clusters, it can be concluded that, as well as during the first stage of the research, all mean values of subsystems in the CL+ cluster exceed the mean values of subsystems in the CL-cluster. Particularly, the mean value of the "quality of education system" subsystem by 27 %, of the "political" subsystem by 18.5 %, of the "civil society" subsystem by 14.3 %, of the "economic aspects" subsystem by 14.2 %, of the "natural environment" subsystem by 11.3 %, (see Figure 4):

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ISSN 2345-0282 (online) http://jssidoi.org/jesi/ 2021 Volume 9 Number 1 (September) http://doi.org/10.9770/jesi.2021.9.4126) Figure 4. Comparison of Cluster + (1) and Cluster -(2). Source: the authors` calculations in SPSS according to statistical data As it has already been stated, Sweden became the leader by the EEPSE Green Economy Index in Cluster + (see Table 2 below), while the place in the bottom of this group is now occupied by the newcomer (as compared with the first stage of the research) -Ireland. The United Kingdom confirmed its leading positions in the educational subsystem (71.52), while another debutant of Cluster + Estonia showed the lowest academia record among the leaders (44.28). Sweden again became the leader in the economic subsystem (64.58), while Belgium is located at the bottom of the list (46.91). Sweden also has shown the best results in the "Civil society" (58,45) subsystem, while in the sphere of politics it yielded palm to Denmark (61,73) and Finland (60,92). Speaking of the "Natural environment" subsystem, Denmark scored the most (55.38) and Belgiumthe least (47.85).

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ISSN 2345-0282 (online) http://jssidoi.org/jesi/ 2021 Investigating the situation in the Cluster -(see Table 3), it has to be mentioned that certain differences in countries' positions have occurred here as well. As it has already been stated above, the countries with high scores which previously were in this group have managed to move to Cluster +. As a result, Clustergroup in 2020 included 14 (not 21) countries, with Slovenia (48,59) as a leader and Poland (43,21) as an underdog in terms of EEPSE GEI.
It is worth mentioning that Latvia secured strong positions in the top of the Cluster -, with overall performance being better than the one of neighboring Lithuania, and the best record in the economic subsystem among Cluster countries, but weak educational indicators:

Investigating green economy trends in the European Union
As the present research has been performed in three stages (approximately 4 years of observations), the data collected through this period of time were systematised and analysed to find out if there have been convergence or divergence trends in terms green economy development in the EU countries. Such analysis was applied both to overall EEPSE Green Economy Index and its components in the period of 2017-2020.
To reveal the tendencies the sigma convergence for data throughout the three stages of the research was tested.
The indicator -shows the convergence and divergence tendency depending on the value of sample variance.
Such approach has been widely used by scholars in relation to the economy of the EU. Simionescu (2014), for instance, utilizes it to measure the evolution of real convergence process between the EU countries in terms of GDP per capita in 2000 and 2012. Sometimes such an approach is also used to assess convergence and divergence processes across old and new members of the European Union.
Speaking of the present research, the variation is measured for factors and overall Green Economy Index using simple indicator (the mean) and synthetic indicators (variance, standard deviation, and coefficient of variation).
In a dynamic analysis the variation in decrease allows us to conclude the existence of a more obvious convergence process. And just the reversevariation in increase signals about the existence of a more obvious divergence process. At the same time, the most useful indicator is the coefficient of variation, because it allows to make necessary comparisons and conclusions.
The variance for different factors of green economy and its overall index in the EU 27 + UK countries was computed as:

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ISSN 2345-0282 (online) http://jssidoi.org/jesi/ 2021 The variance expresses the degree of variation of the values compared to the average. It is affected by outliers and by the variable measurement of unit. The variance is also used to calculate the standard deviation ( = ) and the coefficient of variation ( = ), the last one expressing in a relative form the variation compared to average. The indicator ( ) is used to characterize the level of convergence by measuring the variance of EEPSE Green Economy Index and its components for three stages of the research, utilizing the cross-section data about EU27 + UK countries. The indicator is relevant when comparisons are made. For describing the convergence tendency, time series are used on a discrete interval from t to t+T. In a certain time period when the variance of the variable decreases (the indicator value decreases in time), the convergence process took place: . When the variance grows, the divergence process took place: > .
In the first place the -convergence was tested for all countries under analysis regardless of the clusters (see Table  4). The results show that there is a convergence process in terms of overall EEPSE Green Economy Index in the EU countries. As it can be seen from the data in the Table, it can be attributed to convergence in the sphere of society, while coefficients of variation in the spheres of education and economy remain approximately the same. At the same time, the situation in two clusters differs. As it can be seen in Table 5, overall EEPSE Green Economy Index converges within the framework of Cluster +. It can be attributed to the convergence process in the sphere of economy and society. At the same time, there is a clear divergence process in the educational sphere. It can be explained by the fact that countries with good record on this track (the UK, Germany, France) manage to preserve their leadership and even to increase their advantages as compared to countries with lower academic results (Ireland, Luxembourg, Estonia). Moving on to the situation in Cluster -, it has to be mentioned that -divergence was confirmed in the sphere of economy of the 14 countries (see Table 6). At this point the EEPSE Green Economy Index, based on Quintuple Helix model, provided an ability to define scores for the EU countries (plus the UK) and divide them into two clusters, as well as to trace divergence and convergence processes in terms of green economy through the three stages of research. However, proposed model would gain additional value if it has potential in analysing or predicting political/societal/economic events related to green developments. The next chapter tests correlation of EEPSE Green Economy Index with the growth of plug-in electric car share in Europe in 2020.

Correlation with economy: case of plug-in electric car share growth
To test such correlation, it was decided to take the indicator of plug-in electric car market share in European countries in 2020. This year was remarkable since the average market share of new passenger plug-in electric cars in Europe more than tripled in this period of time to 11.4% (from less than 3.6% in 2019). Specialists name two reasons for thatunprecedented increase of plug-in vehicle sales, and decrease of conventional ICE car sales (Kane, 2021).
Data on such indicator was available for almost all EU27 + UK countries, except for Malta and Bulgaria (see Table 7):

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ISSN 2345-0282 (online) http://jssidoi.org/jesi/ 2021 Volume 9 Number 1 (September) http://doi.org/10.9770/jesi.2021.9.4126) From the list above it can already be observed that electric cars are sold better in countries with high EEPSE Green Innovation Index. This hypothesis was tested with SPSS software (see Table 8): As it can be seen from the chart above, the correlation between EEPSE Green Economy Index and plug-in electric car market share in the EU countries in 2020 was 0,790 with a very high statistical significance (p-value 0.000), which can be characterized as very strong (classification by Political Science Department at Quinnipiac University, as cited from Akoglu 2018).
It is interesting that the strongest correlation is found with the sphere of politics (0,796), not economy (0,716). True, electric car sales can hardly be described as purely economic factor, since electrification of transport is quite a complicated phenomenon. Electric vehicles are still very expensive as compared with conventional analogues. Thus, to boost their popularity some subsidies and support from the state are needed, be it tax discounts, cheap credits, road and parking privileges etc. Relevant infrastructure, including charging stations, should be created. Such tasks definitely lay within the sphere of political system.
The calculations made in this paper present quite interesting results. Previously the differences in electric cars market share in various European countries have been attributed by specialists and manufacturers mostly to the gap in GDP per capita. For example, European Automobile Manufacturers' Association (2019) explained, that in 2018 all countries with an electrically charged vehicle (ECV) market share of less than 1% had a GDP below €29,000, including both new EU member states in Central and Eastern Europe, as well as Spain, Italy and Greece. By contrast, the manufacturers continue explaining, an ECV market share of above 3.5% only occurs in countries with a GDP per capita of more than €42,000.
Taking this into account specialists take the Norwegian market as a benchmark. They point to the fact that just like its €73,200 GDP per capita, more than twice the EU average (€30,600) in 2018, Norway's 49.1% ECV share was then exceptional for Europe.
At the same time, the countries that come second and third, Sweden (8%) and the Netherlands (6.7%), have some of the highest GDPs in the EU but much lower ECV market shares.
Having investigated these data, market-oriented specialists come to the conclusion that not only there is a clear split between Central-Eastern and Western Europe, but also a pronounced North-South divide in terms of electric transport development (European Automobile Manufacturers' Association, 2019).
Of course, such distinctions in economic indicators between different European countries cannot be underestimated. Particularly, while western and northern Europeans (conditionally, CL+) have well-developed and diversified economies and can concentrate on green shift, others members of the EU still need to ensure necessary infrastructure, acceptable level of income etc., to catch up with the levels of development in Western Europe. So, two groups of countries have no option but to place emphasis on dealing with different tasks. Second, shifting to a greener economy costs money, and leaders might nor be willing to dismiss a generation of workers (their electorate).
With all the truth about such observations concerning economic subsystem, such a market-centric approach seems to be quite one-sided and to some extent even primitive. Particularly, this view presupposes that proliferation of green technologies (in this caseelectric cars) depends solely on economic prosperity.
Contrary to that, the EEPSE GEI model provides a better-balanced and multifactorial view on this phenomenon, which takes into account educational, economic, political, societal and environmental factors at the same time.
The effectiveness of such an approach has been confirmed withing the present chapter.

Discussion and conclusions
Different integral indicators are widely used as a tool to describe the development of green growth. Attempts to make the assessment of green economy have been made by several researches and institutions. For example, Kasztelan (Kasztelan, 2017) used 33 selected indicators of green economy on the basis of the OECD methodologies and database to that end. Diagnostic variables defining the level of green growth for particular countries were adjusted in an attempt to meet three criteria: substantive, formal, and statistical. Based on the results obtained, the author concludes that the green growth can provide solutions to economic and environmental problems and create new sources for growth (Kasztelan, 2017), however, its level in the OECD countries is still insufficient (Ibid). In his research Kasztelan (2018), having examined the green growth level in 28 EU countries, applied the same methods and determined 4 groups of countries: Sweden (0.6477) is the leader (in this part the results of Kasztelan (Kasztelan, 2018) study are close to the present dissertation), followed by the countries from the second group ( As it can be seen, Kasztelan (Kasztelan, 2018) divided the EU countries into four groups, contrary to two clusters found within the present article. It has to be mentioned again, that the OECD methodology (OECD 2017) which the scholar took as a basis, ignores the area of education, while the present paper assigns an important role to it.
The results and methodology of the present article can also be compared to the eco-innovation scoreboard and the eco-innovations index, which is aimed at capturing the different aspects of eco-innovation by applying 16 indicators grouped into five dimensions: eco-innovation inputs, eco-innovation activities, eco-innovation outputs, resource efficiency and socio-economic outcomes (Spaini, Markianidou and Doranova, 2018). The leaders according to this index are: Luxembourg (138 points), Germany (137 points), Sweden (132 points), Finland (121 points), Austria (119), Denmark (115); the worst performers are Cyprus (45), Bulgaria (50), Poland (59), Malta (59), Romania (66). Generally these results coincide with the outcome of the research performed by the authors of the present article. At the same time the differences may be caused by different methodology, because eco-innovation scoreboard places less emphasis on environmental and political issues and more on economy.
Therefore, there are both similarities in the assessment of the green economy presented in this paper and other studies, and differences, which can be affected (as well as by the methodology) by the time period, countries under research and indicators chosen. Key challenges of the indicator approach also include data availability, right balance between different indicator selection criteria, systemic understanding of the relationships between indicators, and the variable usage contexts of the indicators.
Still, the EEPSE Green Economy Index, presented within this papera set of policy-relevant key indicators based on Quintuple Helix modelproved usable for dealing with key green growth issues, analysing different countries' "green" performance and various economic, political and societal events related to green development.