An Analysis of the Relationships between Social Capital Levels and Selected Green Economy Indicators on the Example of Polish Voivodeships

Abstract

This article presents the results of a study analyzing the relationships between social capital levels and the green economy in Polish regions. By linking these concepts and examining the relationships between them, the study can offer valuable insights for promoting the development of social capital and the green economy. Social capital drives individual growth, and sustainable development plays a key role in this process by improving the quality of life and well-being at a level that is permitted by the current level of civilization. Therefore, social capital is a key prerequisite for sustainable development because it regulates the environmental impact of economic growth and lays the foundation for future development. Trust, openness, and the willingness to cooperate contribute to high levels of social capital, and they are essential for pursuing the common good and preventing the misuse of shared resources. The green economy concept paves the way to sustainable development by improving well-being, reducing environmental risks, and preventing resource depletion. The aim of this study was to identify and describe the relationships between social capital levels (measured based on the main criterion and indirect criteria, including public moral norms, engagement and social bonds, and social trust) and selected green economy indicators on the example of Polish voivodeships. The study involved Polish voivodeships, and data for analyses were obtained from statistical databases in the public domain. The analyzed phenomena are complex and multi-faceted, and they were measured with the use of composite variables. Composite indicators were determined with Hellwig’s method. The study revealed low levels of the examined phenomena and considerable differences between Polish regions. Social capital (main criterion) and engagement and social bonds (indirect criterion) were significantly correlated with the composite measure of a green economy. These results indicate that high levels of social capital can contribute to the growth of integrated, stable, and rapidly evolving communities that are able to effectively cope with the challenges of the green economy transition.

1. Introduction

Humans have the need and the ability to live in groups; they engage in social interactions, strive for common goals, and work collaboratively to solve problems in the pursuit of the common good [1,2]. Humans are a social species, and their ability to adapt plays a key role in social and economic development. In the economic sciences, these synergistic effects are referred to collectively as social capital [3,4]. Social capital is an interdisciplinary concept, and research on social capital combines various fields of science with analyses of human activity [5]. In research, this concept is often used to supplement and explain complex economic and social phenomena [6,7,8,9,10,11], including those associated with environmental protection [12,13,14].

The social capital theory was first defined by Bourdieu [15], and it was further elaborated by Coleman [16], Putnam [17], Fukuyama [18], and other scientists who made significant contributions to contemporary research on social capital as a multi-faceted and multidisciplinary concept. Various definitions of social capital have been proposed in the literature, but most of them recognize that social capital is closely linked with social interactions and social bonds [15,19,20,21]. Communities characterized by strong bonds and the ability to cooperate are much more effective in achieving common goals. Social collaboration also includes civic engagement, namely direct citizen participation in social, public, and political life [22]. Mutual trust between members of a given group is indispensable for building social cooperation [6,18,20,23,24]. Social trust is regarded as one of the most important indicators for assessing social capital levels [25]. Individuals establish interpersonal relationships by adhering to specific social norms and regulations [6,20,21,24,26] that promote desirable social attitudes [22], encourage rational cooperation, facilitate problem-solving, and orient joint actions toward the common good [16,27,28,29]. Social capital relies on the premise that social engagement influences social norms and, consequently, affects the behavior of entire societies. High levels of social capital facilitate the implementation of norms and regulations, and they guarantee that these norms are observed by citizens, entrepreneurs, and other actors [30]. Social movements and civic engagement influence political decisions and shape social norms. According to research, high levels of social capital also promote effective environmental management at the local level [30]. By fostering social cooperation and engagement, social capital promotes the growth of collectivist cultures and instills the awareness that natural resources constitute valuable public goods that should be protected [5]. Research has demonstrated that social capital can also contribute to environmentally responsive behaviors by encouraging citizens and households to change their daily habits, including in the area of waste management [12,31], energy and water consumption [12,31], and sustainable use of natural resources [32].

Social demands increase the pressure on the central government and local authorities to maximize the effectiveness of environmental policies, and the success of these policies is largely determined by social acceptance and the citizens’ willingness to cooperate [33]. Therefore, by contributing to the observance of formal norms, building trust in responsible actors, and fostering the belief that most citizens can act together to protect the common good, social capital can significantly promote responsible behaviors that are linked with the implementation of environmental policy [34]. By planning and making decisions about a shared future, citizens can build social capital, foster a widespread understanding of environmental threats, and propose innovative methods for taking joint actions toward sustainable development [35].

Social capital drives the development of local governments, and a high level of social capital stimulates sustainable development as the most desirable type of development that leads to an improvement in the quality of life and well-being at a level that is permitted by the current level of civilization. Social capital is recognized as an important aspect of sustainable development, and this concept has attracted the interest of international and local communities, central and local governments, and entrepreneurs [36]. Therefore, by controlling the environmental impact of economic growth and laying the foundations for future development, social capital plays a key role in the sustainable development concept [37]. This relationship has been confirmed by Grigorescu et al. [38]. A high level of social capital, namely trust, openness, and willingness to cooperate, is essential for protecting the common good and preventing misuse of shared resources. The knowledge and awareness that the environment has a fundamental impact on the quality of life are not sufficient by themselves. According to research, when social capital is unavailable, knowledge and awareness are rarely translated into the willingness to act for the environment or undertake responsible environmental behaviors [39]. High levels of social capital and social trust create a supportive environment for cooperation and the willingness to promote sustainable development at the local level [40]. Social initiatives that encourage changes in our approach towards natural resources and facilitate the transition to renewable energy are collectively termed green social capital, and they highlight the mutual association between social capital and environmental protection [41].

The recognition that social capital is linked with the environment plays a fundamental role in the green economy concept. The green economy can improve well-being while minimizing environmental risks and resource use. This concept has emerged in response to global challenges associated with rapid population growth and rising pressure on natural resources, which lead to irreversible changes in the environment [42]. The green economy concept combines various economic, philosophical, and environmental approaches and definitions of sustainable development [43].

The green economy concept first appeared in a report entitled “A Blueprint for a Green Economy”, which was developed by D. Pearce, A. Markandya, and E. Barbier for the British government in 1989 [44]. The report proposed a set of sustainable development guidelines for the British government. This concept was also addressed by the Declaration on Green Growth that was adopted by the Organization for Economic Growth and Cooperation (OECD) in 2009. This declaration asserted that the international community should strengthen its efforts to pursue green growth strategies as part of its response to the global crisis, and it acknowledged that “green” and “growth” can go hand-in-hand [45]. Over time, green growth (addressed by the OECD) and the green economy (addressed by the United Nations Environment Program (UNEP) and the European Environment Agency (EEA)) entered public discourse as closely interlinked but not synonymous concepts [46,47]. Green growth and development contribute to a green economy, which, in addition to social development, is one of the pillars of sustainable development [48]. The green economy concept was popularized by the Rio+20 United Nations Conference on Sustainable Development, which took place in Rio de Janeiro in 2012 with the aim of promoting the transition to a green economy. The aim of the conference was to reconcile the economic and environmental goals of the global community and to speed up the implementation of a green economy, namely a new model of socioeconomic development that focuses on environmental protection [49].

The green economy contributes to development, job creation, and eradication of poverty by stimulating investment and promoting the rational use of natural capital to improve the well-being of humans and other species in the long-term perspective. The green economy has been described as a system where economic growth and environmental responsibility work together in a mutually reinforcing fashion [50]. The aim of the green economy is to reform an imperfect economic system that increases consumption and leads to material improvements in the quality of life but induces irreversible environmental changes that can ultimately destroy the human species. The depletion of natural capital can reverse apparent economic growth, decrease the availability of fresh water, food and energy, and lead to inequality between individuals and countries. Therefore, the survival and continued development of the human race depends on the transition to a green economy, where the production, distribution, and consumption of goods and services enhance the value of the environment [51].

The green economy protects, regenerates, and invests in the natural environment. The unique value of environmental resources and ecosystem services is recognized and protected. The green economy also protects cultural values, which are the building blocks of every society [52]. The extent to which natural capital can be replaced by other types of capital is limited, which is why the demand for natural resources cannot exceed certain thresholds [53]. The green economy advocates innovative solutions for managing natural systems, such as the circular economy model, and it aligns economic growth with local community livelihoods based on biodiversity and natural systems [54].

The green economy model relies largely on well-being but also on community participation in the decision-making process and a shared sense of responsibility for the success of sustainable development policies [55,56]. An equitable green economy is based on five principles. The Well-being Principle focuses on improved wealth and well-being, not only financial wealth but also the full range of human, social, physical, and natural capital [56]. This principle prioritizes access to knowledge and education, environmentally-friendly technologies and production processes, and sustainable infrastructure, which increase prosperity but do not compromise the environment and natural resources [57].

The Justice Principle (second principle) promotes equal treatment of individuals and groups, both between and within generations. It encourages measures aiming to reduce social inequality and discrimination. Diverse opinions should be considered in the decision-making processes to avoid elite capture. The Justice Principle also strives to improve the social and economic status of women [58]. The discussed principle promotes the empowerment of small and medium-sized enterprises. It recognizes the significance of social organizations and encourages the authorities to include these organizations in the decision-making process. According to the Justice Principle, governments should strive to attain a fast and fair transition in a way that minimizes social costs, considers the interests of vulnerable groups in the transition process, and fosters innovative solutions in the area of social welfare and self-development [54]. These measures should aim to reduce disparities in living standards but also create sufficient space for high-quality wildlife. The Justice Principle adopts a long-term perspective on the economy by contributing to the welfare of future generations without compromising the interests of the present generation. To protect these interests, urgent action is needed to resolve multi-dimensional poverty and injustice by reinforcing a sense of solidarity and social justice, building trust and social bonds, supporting human rights, the rights of workers and minorities, as well as the right to sustainable development [59]. In turn, the Planetary Boundaries Principle (third principle) recognizes and nurtures diverse values of nature. The natural environment and healthy ecosystems can deliver numerous benefits to humans, such as ecosystem services and organic products. The green economy acknowledges that natural resources are limited, and it sets ecological thresholds to guarantee climate stability and the restoration of biodiversity. The Efficiency and Sufficiency Principle (fourth principle) promotes sustainable production and consumption, innovative green industries, and creates new opportunities for investment and employment [60]. The green economy is low-carbon, diverse and circular. It recognizes that the global consumption of natural resources should be limited to physically sustainable levels if human civilization is to remain within planetary boundaries. A green and equitable economy is a set of political measures and daily behaviors that decrease the demand for energy, goods, and natural resources while ensuring a decent standard of living for all, including access to housing, food, basic amenities, healthcare, transport, information, education, public space [61], fair distribution of income, and equal opportunities that reduce inequalities [62]. The Good Governance Principle promotes responsible, transparent and independent institutions, devolved decision-making, and social dialogue [63]. It requires public participation and encourages collaborative problem-solving. The Good Governance Principle supports an evidence-based approach—its norms and institutions are interdisciplinary and combine sound science and economics with local knowledge to propose optimal adaptive strategies. Institutions that are integrated, collaborative and coherent across sectors and governance levels embrace the Good Governance Principle. This principle fosters democratic accountability and freedom from vested interests in all institutions [64]. This principle builds a financial system that delivers well-being and sustainability in a way that safely serves the interests of entire societies [65].

By adhering to these principles, the green economy can become a tool for achieving sustainable development and linking economic activities to development levels [66]. However, none of the green economy goals can be achieved without social support and participation. The theoretical model combining the concepts of social capital and the green economy clearly indicates that a high level of social capital is a prerequisite for green growth. Therefore, the following research questions were formulated: is social capital correlated with the achievement of green economy principles, and if so, to what extent? Which components of social capital, a highly complex phenomenon, make the greatest contribution to the achievement of green economy principles? Based on the above hypothesis and research questions, the main aim of this study was to identify and describe the relationships between social capital levels (measured based on the main criterion and indirect criteria, including public moral norms, engagement and social bonds, and social trust) and selected green economy indicators on the example of Polish voivodeships. The presence of relationships between these concepts was determined in practice, and the levels of the evaluated phenomena were quantified in Polish voivodeships.

2. Materials and Methods

2.1. Data and Study Area

The study involved all sixteen Polish voivodeships. A voivodeship is the highest-level administrative division of Poland, which, according to the current NUTS 2021 classification, is equivalent to NUTS-2 mesoregions in the European Union. The only exception is the voivodeship of Mazovia, which consists of two regions: Mazovia and the Warsaw Metropolitan Area. The level of social capital and green economy indicators were quantified in each voivodeship. The development of social capital in Central-Eastern Europe is still influenced by the socialist economy. Poland is characterized by relatively high levels of economic growth in comparison with other former socialist countries. Poland constitutes the eastern boundary of the European Union, but its history continues to thwart social capital development. Detailed indicators characterizing the studied phenomena were identified based on a review of the literature. Social capital indicators were characterized based on the work of Coleman [16], Putnam [6], Grootaert and van Bastelar [67], Narayan and Cassidy [68], Będzik [69], Foxton and Jones [70], Siegler [71], and Inglot-Brzęk [72]. As regards the literature on green economy indicators, the first set of indicators measuring the transition to a green economy was published in 2011 by the OECD [73] and in 2012 by the UNEP [74]. These indicators are used to publish data and generate periodic reports on the progress towards achieving a sustainable transition to a green economy [75,76]. Green economy progress indicators provide vital information about the performance of voivodeships, but they are not always available at the local level [77,78]. The information about green economy performance was obtained from public databases (

Table 1. Sources of information for the analyzed indicators.

No.	Item	Source
1.	Public moral norms—SC1:
	indicators x1–x11	[79]
2.	Engagement and social bonds—SC2:
	indicators x12–x15	[80]
	indicators x16–x22	[81]
	indicators x23–x24	[79]
3.	Social trust—SC3
	Indicators x25–x30	[79]
4.	Green economy—GE:
	indicators x1–x10	[81]

Note: The symbols of the analyzed indicators correspond to those presented in Figure 1.

). In addition to the literature review, the choice of green economy indicators was also influenced by the availability of statistical data with the required level of detail. The analyzed period was 2018 to 2021 due to the availability of current information in public databases.

A total of 30 social capital (SC) indicators (main criterion) were identified for the needs of the study. The main criterion was divided into three indirect criteria: public moral norms (SC1), engagement and social bonds (SC2), and social trust (SC3) (Figure 1).

A similar procedure was applied to identify green economy (GE) indicators. However, due to a lack of sufficiently detailed data at the local (voivodeship) level, these indicators could not be presented in a hierarchical system, and 10 indicators were ultimately selected for analysis (Figure 2).

2.2. Methods

In the current study, Hellwig’s method was applied to calculate composite indicators describing the analyzed phenomena. This method was developed by the Polish economist and statistician Zdzisław Hellwig [82,83,84], and it is one of the oldest and the most popular techniques for computing a composite variable. Hellwig’s method is applied in analyses of complex phenomena [85,86,87,88,89,90,91,92,93], and it is used to replace a set of several variables with a single composite variable.

The diagonal elements of the inverse correlation matrix were analyzed to eliminate excessively correlated indirect criteria of social capital (SC) and the green economy (GE). Indirect criteria were regarded as excessively correlated when the value of the entries on the main diagonal was higher than 10 (variables 4, 5, 14, 15, and 21 were eliminated from SC; variable 9 was eliminated from GE). A total of 25 SC indicators and 9 GE indicators were ultimately used in the analysis.

The selected indicators were listed in X_mxn decision matrices, where rows denote the studied objects, and columns represent diagnostic variables. Therefore, x_ij is the value of the j^th variable (j = 1, …, n) (SC as the main criterion with three indirect criteria, and GE) in the i^th object (voivodeship):

$$X=\left[\begin{array}{c}{x}_{11} x_{12} \cdots x_{1m}\\ x_{21} x_{22} \cdots x_{2m}\\ \cdots \cdots \cdots \cdots \cdots \cdots \\ x_{n1} x_{n2} \cdots x_{nm}\end{array}\right],$$

(1)

In most cases, diagnostic variables cannot be directly compared because they are expressed in different units of measurement. Therefore, these attributes have to be normalized by eliminating the influence of the units of measurement. In this study, data were normalized using the following formula:

$$z_{ij}=\frac{\left( x_{ij}-{\overline{x}}_j\right)}{S_j}, (j=1, 2, \dots , m),$$

(2)

where:

$${\overline{x}}_j=\frac{1}{n} {\sum }_{i=1}^n{x}_{ij,} s_j=\sqrt{\frac{1}{n} {\sum }_{i=1}^n{\left(x_{ij}-{\overline{x}}_j\right)}^2}$$

(3)

The result was matrix Z of the standardized values of attributes.

$$Z=\left[\begin{array}{c}{z}_{11} z_{12} \cdots z_{1m}\\ z_{21} z_{22} \cdots z_{2m}\\ \cdots \cdots \cdots \\ z_{n1} z_{n2} \cdots z_{nm}\end{array}\right],$$

(4)

In the next step, matrix Z was used to determine a “development pattern”, namely an abstract object P₀ (voivodeship) with the optimal values of the analyzed variables. $P_0=\left[z_{01}, z_{02}, \dots , z_{0j}\right]$, where: z_0j = max{z_ij}, when Z_j is a stimulant, and z_0j = min{z_ij}, when Z_j is a destimulant. The Euclidean distances between each analyzed object P_i (voivodeship) and the identified “development pattern” were calculated with the use of the below formula:

$$q_i=\sqrt{{\sum }_{j=1}^m{\left(z_{ij}-z_{0j}\right)}^2},$$

(5)

The calculated values of q_i were used to compute Hellwig’s composite measure of development and evaluate the studied voivodeships. The following formula was applied to calculate Hellwig’s composite measure of development:

$$S_i=1-\frac{q_i}{q_0}, \left(i=1, 2, \dots , n\right),$$

(6)

where:

$$q_0={\overline{q}}_0+{2s}_0, {\overline{q}}_0=\frac{1}{n}{\sum }_{i=1}^n{q}_i, s_0=\sqrt{\frac{1}{n}{\sum }_{i=1}^n{\left(q_i-{\overline{q}}_0\right)}^2}.$$

(7)

Hellwig’s composite measure of development S_i usually assumes values in the range of (0, 1). Values closer to 1 represent higher levels of development in the evaluated objects. Below-zero values can be obtained when the development of a given object is significantly below the development of the remaining objects [94].

Polish voivodeships were divided into three classes with different levels of social capital (as the main criterion with indirect criteria) and green economy performance based on standard deviation and the arithmetic mean of Hellwig’s composite measure [95,96]:

-

$S_i\ge {\overline{S}}_i+0.5s_{S_i}-$class I—high level of the analyzed phenomena,

-

${\overline{S}}_i-0.5s_{S_i}\le S_i<{\overline{S}}_i+0.5s_{S_i}-$class II—moderate level of the analyzed phenomena,

-

$S_i<{\overline{S}}_i-{0.5s}_{S_i}-$class III—low level of the analyzed phenomena.

where:

-

$S_i$–value of the composite measure calculated with the use of Hellwig’s development pattern method,

-

${\overline{S}}_i$—arithmetic mean of the composite measure S_i,

-

$s_{S_i}$—standard deviation of the composite measure S_i.

Hellwig’s composite measure S_i was described with the use of additional indices denoting the type of the analyzed phenomena: social capital (main criterion)—SC, indirect criteria of SC—public moral norms (SC1), engagement and social bonds (SC2), and social trust (SC3); green economy performance—GE.

In the next step, the presence of correlations between composite measures of SC (main criterion), indirect criteria of SC, and GE was determined by calculating Pearson’s linear correlation coefficients in each voivodeship. Data were processed statistically in the Statistica program.

3. Results

3.1. Composite Measure of Social Capital (SC) and Green Economy Performance (GE)

The described procedure was used to calculate the composite indicator of social capital. Based on the hierarchical system of indicators, the calculations produced four partial composite indicators denoting the level of social capital in relation to three indirect criteria: public moral norms S_SC1i (

Table 2. Partial indicators and the composite indicator of public moral norms.

No.	Voivodeship	x1	x2	x3	x6	x7	x8	x9	x10	x11	SSC1i
1.	Lower Silesia	83.9	82.5	62.7	31.0	53.2	50.2	44.2	67.2	58.4	0.510
2.	Kuyavia-Pomerania	87.6	85.6	61.2	36.3	56.2	50.5	42.5	74.0	59.3	0.619
3.	Lublin	81.0	86.9	55.4	27.5	65.5	48.5	41.3	69.4	54.9	0.454
4.	Lubusz	85.3	80.6	59.0	30.5	64.3	47.0	36.2	70.0	68.7	0.544
5.	Łódź	78.6	73.5	48.6	24.6	47.2	37.3	32.9	66.8	53.0	0.164
6.	Małopolska	79.6	81.7	62.9	29.6	60.5	49.2	39.7	68.0	62.5	0.516
7.	Mazovia	81.8	80.8	54.9	32.3	51.8	32.6	36.8	70.7	61.0	0.366
8.	Opole	91.3	91.9	67.4	40.7	66.8	54.7	47.0	87.2	75.1	1.000
9.	Podkarpacie	84.7	84.7	61.1	26.5	62.5	47.4	39.2	79.6	64.4	0.597
10.	Podlasie	74.4	77.6	51.8	20.8	46.4	40.5	25.4	59.4	49.2	0.065
11.	Pomerania	82.9	86.1	57.4	34.5	56.8	40.7	40.9	69.5	58.6	0.489
12.	Silesia	81.0	79.9	55.9	31.4	55.1	43.2	40.9	70.3	59.5	0.450
13.	Świętokrzyskie	67.6	63.9	54.2	23.2	48.0	33.8	32.2	66.6	53.6	0.061
14.	Warmia-Masuria	83.6	80.2	59.8	35.2	57.0	46.2	39.6	72.8	56.9	0.519
15.	Wielkopolska	80.0	78.5	58.9	33.7	55.8	46.5	39.7	70.4	65.6	0.509
16.	West Pomerania	81.0	82.1	56.0	23.4	47.6	47.4	37.1	59.5	54.6	0.278
	Mean	81.5	81.0	58.0	30.1	55.9	44.7	38.5	70.1	59.7	0.446

Note: The symbols of the analyzed indicators correspond to those presented in Figure 1.

), engagement and social bonds S_SC2i (

Table 3. Partial indicators and the composite indicator of engagement and social bonds.

No.	Voivodeship	x12	x13	x16	x17	x18	x19	x20	x22	x23	x24	SSC2i
1.	Lower Silesia	83.9	82.5	5.4	44.0	17.5	462.5	11.7	3.4	7.7	59.5	0.251
2.	Kuyavia-Pomerania	87.6	85.6	11.8	37.0	17.9	299.4	8.6	2.6	3.8	58.3	0.236
3.	Lublin	81.0	86.9	13.7	41.0	14.5	202.6	9.1	5.3	6.4	65.1	0.310
4.	Lubusz	85.3	80.6	11.1	43.0	16.4	278.9	12.1	3.6	6.4	58.3	0.290
5.	Łódź	78.6	73.5	14.5	38.0	15.5	206.1	10.1	3.8	11.2	61.2	0.010
6.	Małopolska	79.6	81.7	17.3	41.0	14.1	226.2	11.8	5.5	3.8	63.7	0.347
7.	Mazovia	81.8	80.8	10.8	49.0	13.0	307.4	12.1	2.5	7.2	56.6	0.161
8.	Opole	91.3	91.9	10.2	41.0	15.2	179.7	12.2	4.5	4.4	66.0	0.350
9.	Podkarpacie	84.7	84.7	14.9	39.0	14.6	154.5	9.7	7.7	3.1	69.6	0.365
10.	Podlasie	74.4	77.6	18.4	38.0	25.4	133.1	8.9	3.8	4.2	54.5	0.183
11.	Pomerania	82.9	86.1	12.9	39.0	16.3	420.5	7.1	2.7	6.5	57.3	0.185
12.	Silesia	81.0	79.9	18.1	31.0	15.0	393.6	10.0	3.4	7.4	56.4	0.118
13.	Świętokrzyskie	67.6	63.9	20.0	40.0	14.2	415.1	7.2	3.4	8.1	64.2	−0.011
14.	Warmia-Masuria	83.6	80.2	16.8	44.0	14.1	89.1	9.3	3.3	8.3	56.0	0.135
15.	Wielkopolska	80.0	78.5	12.0	42.0	19.3	311.2	10.5	3.5	6.3	66.8	0.343
16.	West Pomerania	81.0	82.1	8.7	45.0	14.1	195.5	7.7	3.1	8.8	59.4	0.105
	Mean	81.5	81.0	13.5	40.8	16.1	267.2	9.9	3.9	6.5	60.8	0.365

Note: The symbols of the analyzed indicators correspond to those presented in Figure 1.

), social trust S_SC3i (

Table 4. Partial indicators and the composite indicator of social trust.

No.	Voivodeship	x25	x26	x27	x28	x29	x30	SSC3i
1.	Lower Silesia	83.9	82.5	62.7	31	53.2	50.2	0.583
2.	Kuyavia-Pomerania	87.6	85.6	61.2	36.3	56.2	50.5	0.696
3.	Lublin	81	86.9	55.4	27.5	65.5	48.5	0.511
4.	Lubusz	85.3	80.6	59	30.5	64.3	47	0.584
5.	Łódź	78.6	73.5	48.6	24.6	47.2	37.3	0.136
6.	Małopolska	79.6	81.7	62.9	29.6	60.5	49.2	0.564
7.	Mazovia	81.8	80.8	54.9	32.3	51.8	32.6	0.330
8.	Opole	91.3	91.9	67.4	40.7	66.8	54.7	1.000
9.	Podkarpacie	84.7	84.7	61.1	26.5	62.5	47.4	0.579
10.	Podlasie	74.4	77.6	51.8	20.8	46.4	40.5	0.148
11.	Pomerania	82.9	86.1	57.4	34.5	56.8	40.7	0.530
12.	Silesia	81	79.9	55.9	31.4	55.1	43.2	0.447
13.	Świętokrzyskie	67.6	63.9	54.2	23.2	48	33.8	−0.017
14.	Warmia-Masuria	83.6	80.2	59.8	35.2	57	46.2	0.579
15.	Wielkopolska	80	78.5	58.9	33.7	55.8	46.5	0.503
16.	West Pomerania	81	82.1	56	23.4	47.6	47.4	0.347
	Mean	81.5	81.0	58.0	30.1	55.9	44.7	0.470

Note: The symbols of the analyzed indicators correspond to those presented in Figure 1.

), and social capital S_SCi as the main criterion (

Table 5. Composite indicator of social capital (main criterion).

No.	Voivodeship	SSCi
1.	Lower Silesia	0.410
2.	Kuyavia-Pomerania	0.465
3.	Lublin	0.394
4.	Lubusz	0.440
5.	Łódź	0.097
6.	Małopolska	0.447
7.	Mazovia	0.257
8.	Opole	0.629
9.	Podkarpacie	0.490
10.	Podlasie	0.081
11.	Pomerania	0.364
12.	Silesia	0.302
13.	Świętokrzyskie	−0.027
14.	Warmia-Masuria	0.363
15.	Wielkopolska	0.428
16.	West Pomerania	0.204
	Mean	0.334

).

The value of Hellwig’s composite indicator S_SC1i ranged from 0.061 in Świętokrzyskie voivodeship to 1.000 in Opole voivodeship. The mean value of S_SC1i for Polish voivodeships was 0.446, with a standard deviation of 0.223. It should be noted that the values of S_SC1i differed considerably across voivodeships, but Poland was generally characterized by moderate adherence to public moral norms.

The value of Hellwig’s composite indicator S_SC2i ranged from −0.011 in the Świętokrzyskie voivodeship to 0.365 in the Podkarpacie voivodeship. The mean value of S_SC2i reached 0.216 with a standard deviation of 0.108. These values are very low, and they testify to low levels of social engagement and weak social bonds in all voivodeships.

The values of Hellwig’s composite indicator S_SC3i for social trust ranged from −0.017 in Świętokrzyskie voivodeship to 1.000 in Opole voivodeship. The mean value for all voivodeships was 0.470 with a standard deviation of 0.235, which approximates the mean value of indicator S_SC1. Once again, the lowest value of the analyzed indicator was noted in Świętokrzyskie voivodeship. In turn, Opole was characterized by the highest value of S_SC3i in all Polish voivodeship, as well as the maximum value of the analyzed indicator in the applied method.

The same procedure was applied to calculate Hellwig’s composite measure S_SCi of social capital (main criterion) for every voivodeship based on all 25 measures (indicators). The value of S_SCi differed considerably across voivodeships, ranging from −0.027 in the Świętokrzyskie voivodeship to 0.629 in the Opole voivodeship. The mean value of S_SCi reached 0.334 with a standard deviation of 0.167, which points to generally low levels of social capital in Poland.

The composite indicator of green economy performance (GE) ranged from 0.012 in Świętokrzyskie voivodeship to 0.511 in Podkarpacie voivodeship. The mean value of GE was determined at 0.243 with a standard deviation of 0.122. These results point to generally low levels of GE in Poland (

Table 6. Partial indicators and composite indicators of green economy performance.

No.	Voivodeship	x1	x2	x3	x4	x5	x6	x7	x8	x10	SGEi
1.	Lower Silesia	34.1	2208.0	147.9	77.5	2.8	7.7	5213.0	0.5	4.1	0.265
2.	Kuyavia-Pomerania	35.7	826.0	124.0	70.4	1.4	5.7	4943.8	0.9	3.4	0.161
3.	Lublin	29.6	244.0	121.1	54.0	2.5	4.6	2417.3	0.6	2.6	0.171
4.	Lubusz	31.9	491.0	137.4	74.9	4.7	8.5	2 75.7	0.6	3.6	0.394
5.	Łódź	37.4	602.0	127.0	64.7	3.1	5.6	16,317.8	0.7	3.5	0.102
6.	Małopolska	28.2	43.0	134.3	65.1	7.6	6.5	2229.2	0.3	3.4	0.390
7.	Mazovia	38.1	166.0	124.5	70.5	5.4	3.8	6066.9	0.4	4.2	0.108
8.	Opole	31.9	896.0	157.5	74.2	3.2	6.4	18,549.8	1.3	3.4	0.156
9.	Podkarpacie	24.7	137.0	89.0	72.4	8.9	17.5	1018.4	0.4	3.1	0.511
10.	Podlasie	36.2	1006.0	112.5	65.4	5.6	4.8	1912.2	0.4	3.0	0.228
11.	Pomerania	35.4	328.0	158.9	84.2	5.2	5.5	2865.2	0.3	3.8	0.309
12.	Silesia	31.4	4598.0	173.1	79.2	2.4	6.1	8179.9	1.0	3.6	0.258
13.	Świętokrzyskie	28.8	4598.0	83.2	60.4	1.4	4.0	12,377.4	1.1	2.9	0.012
14.	Warmia-Masuria	33.2	4598.0	108.5	75.1	4.6	6.5	1252.5	0.4	3.4	0.297
15.	Wielkopolska	39.2	4598.0	134.7	73.2	6.8	6.2	2704.7	0.4	3.5	0.259
16.	West Pomerania	34.4	4598.0	127.4	80.9	9.5	8.3	4005.7	0.9	4.2	0.268
	Mean	33.1	4598.0	128.8	71.4	4.7	6.7	5776.8	0.6	3.5	0.243

Note: The symbols of the analyzed indicators correspond to those presented in Figure 2.

).

Social capital measures, including indirect criteria and the main criterion, were classified with the use of the method described in Section 2 based on the arithmetic mean and standard deviation. The results are presented in cartograms in Figure 3. The values of the composite indicator Si for GE were also classified, and the results are shown in a cartogram in Figure 4. The boundary values of each class are presented in

Table 7. Boundary values of the composite indicator Si for the analyzed phenomena.

Class	SSC1i	SSC2i	SSC3i	SSCi	SGEi
I	<0.558–max>	<0.271–max>	<0.587–max>	<0.418–max>	<0.304–max>
II	<0.335–0.558)	<0.162–0.271)	<0.352–0.587)	<0.251–0.418)	<0.182–0.304)
III	<min–0.335)	<min–0.162)	<min–0.352)	<min–0.251)	<min–0.182)

.

The classification procedure revealed high levels of social capital in six voivodeships (Kuyavia-Pomerania, Małopolska, Lubusz, Opole, Podkarpacie, and Wielkopolska). Only four voivodeships were grouped in class III with the lowest values of the composite indicator (Łódź, Podlasie, Świętokrzyskie, West Pomerania). An analysis of the cartogram indicates that low values of SC can be attributed mainly to low levels of social engagement and weak social bonds. Eight Polish voivodeships (50%) were grouped in class III, denoting the lowest levels of the analyzed phenomena. These were: Łódź, Mazovia, Podlasie, Pomerania, Silesia, Świętokrzyskie, Warmia-Masuria, and West Pomerania. It should also be noted that this partial indicator of SC assumed a narrow range of values with a maximum of only 0.365. Despite the fact that the values of social trust and public moral norms were higher, very few voivodeships were characterized by the maximum values of these partial indicators. Only two voivodeships (Kuyavia-Pomerania and Opole) were grouped in class I for social trust, and only three voivodeships (Kuyavia-Pomerania, Podkarpacie, and Opole) were grouped in class I for public moral norms. It should be noted that voivodeships with high values of one partial indicator were generally characterized by high or very high values of the remaining partial indicators. None of the voivodeships was grouped in class I based on one indicator and in class III based on another indicator. These results could suggest that high values of one partial indicator lead to improvements in the remaining indicators. An interesting relationship was observed in the Mazovia voivodeship, which was placed in class III based on the values of indirect criteria and in class II based on the value of the main criterion (SC). Despite low values of partial indicators, Mazovia was characterized by a moderate level of SC relative to the remaining voivodeships.

The classification based on the values of the green economy performance indicator also revealed considerable differences across voivodeships. Four voivodeships were placed in class I (Małopolska, Lubusz, Pomerania, and Podkarpacie); six voivodeships were grouped in class II (Lower Silesia, Podlasie, Silesia, Warmia-Masuria, Wielkopolska, and West Pomerania), and six voivodeships were placed in class III (Kuyavia-Pomerania, Mazovia, Lublin, Łódź, Opole, and Świętokrzyskie).

3.2. Analysis of the Relationships between Social Capital and Green Economy Performance

The measures of social capital (main criterion) and green economy performance were bound by a significant moderate correlation. Pearson’s linear correlation coefficient reached 0.516 at p < 0.05 (

Table 8. Analysis of the relationships between social capital (main criterion and indirect criteria) and green economy performance—Pearson’s linear correlation coefficient.

Social Capital		Green Economy
Social capital as the main criterion		0.516
Indirect criteria	Public moral norms	0.352
	Engagement and social bonds	0.567
	Social bonds	0.406

Correlation coefficients are significant at p < 0.05.

). An analysis of the classes denoting various levels of the analyzed phenomena revealed that eight voivodeships were grouped in the same class with similar levels of SC and GE. The residents of Lubusz, Małopolska, and Podkarpacie voivodeships were characterized by high levels of social capital as well as high levels of green economy performance. Moderate levels of social capital and green economy performance were noted in the voivodeships of Lower Silesia, Silesia, and Warmia-Masuria, whereas low levels of these phenomena were observed in Łódź and Świętokrzyskie voivodeships. Interestingly, Kuyavia-Pomerania and Opole were characterized by high levels of social capital but low levels of green economy performance. Such discrepancies were not observed in the remaining voivodeships, which belonged to a single class in terms of both indicators.

A significant moderate correlation was also noted between engagement and social bonds (indirect criterion of SC) and green economy performance. This observation suggests that the residents of voivodeships characterized by high levels of social engagement and strong social bonds are also more likely to participate in activities that promote green growth.

4. Discussion

The strength of the relationships between social capital and green economy performance was examined in several stages. The levels of both phenomena were determined in the first stage. This was accomplished by reviewing the literature and collecting data characterizing the studied phenomena. The composite indicator of social capital was calculated based on 25 partial indicators divided into three groups of indirect criteria.

The first partial indicator, public moral norms (S_SC1), was calculated based on nine measures describing unconditionally unacceptable social practices and legal violations. Individuals who adhere to public norms and social expectations embody the ideals and values that serve as guidelines for distinguishing between desirable and undesirable behaviors in a given culture [97]. However, research has shown that human behaviors and attitudes are not always consistent and can infringe upon socially acceptable standards. In Poland, a certain departure from public moral norms is socially permissible. The above applies particularly to illegal employment, cheating on exams, or driving over the speed limit. This observation gives cause for concern because sociological research [14,98] has demonstrated that social values, norms, and behaviors play a key role in promoting civic engagement, including in environmental issues, and significantly influence the environmental awareness of local communities. Environmental awareness affects human attitudes and behaviors relating to the environment, and it is largely responsible for decisions that lead to excessive resource depletion or, conversely, decisions that promote balancing the needs of humans and the needs of the environment [99]. Personal interests can overshadow environmental protection and can contribute to social acceptance of questionable practices, such as illegal waste dumping or burning hazardous waste to generate heat [100]. It should be noted that the value of the green economy composite indicator was high only in the Podkarpacie voivodeship, which was also characterized by high adherence to public moral norms. In turn, despite high values of the public moral norm indicator in Kuyavia-Pomerania and Opole, these voivodeships were characterized by low values of the GE indicator. The correlation analysis also revealed an absence of significant correlations between these phenomena. This observation suggests that adherence to public moral norms does not always lead to the observance of green economy principles. However, these relationships may be difficult to capture based on such low values of the analyzed indicators. Nonetheless, low adherence to public moral norms is a negative phenomenon. Regional and national policies should aim to strengthen the rule of law and transparency in public life. Fair and consistent regulations that promote accountability for public actions and introduce punitive measures for violating the accepted standards can also improve the observance of public moral norms [101].

It should also be noted that adherence to public moral norms does not always result in greater environmental awareness or environmentally friendly actions. Therefore, it is important not only to identify the relationship between social capital and green economy performance but also to analyze the factors that affect the strength and direction of this relationship. According to Si et al. [102], when individual experiences and moral beliefs are consistent with the norms adopted by a social group, individuals are more likely to identify with and be influenced by that group. If green economy principles are disregarded by a social group, the failure to observe these principles is not considered an act that undermines the group’s moral norms.

Ethical behaviors and choices are closely associated with social trust [103]. Respect for shared norms and values creates fertile ground for trust, which, according to Fukuyama [18], acts as a lubricant that makes any group or institution run more efficiently. Trust is also perceived as a key mechanism that promotes and facilitates collective action, including sustainable resource use [104,105]. In the present study, this parameter was evaluated based on five indicators measuring social trust in various institutions and individuals—members of local communities. The results indicate that the local authorities and the Roman Catholic Church are regarded as most trustworthy, whereas neighbors are regarded as least trustworthy in Poland. However, the overall levels of social trust were moderate. According to Tourangeau and Yan [106], studies analyzing sensitive issues such as social trust do not always produce reliable results because respondents edit the reported information on the assumption that if they engage in socially undesirable behaviors, so do others. Other researchers have argued that institutional trust strongly affects social trust, which seems to be particularly true in former socialist countries [107,108]. Fairbrother [109] reported that social trust was associated with pro-environmental behaviors, but the results of the present study do not corroborate this observation. Despite high levels of social trust, Opole and Kuyavia-Pomerania voivodeships were characterized by low values of the green economy performance indicator. In turn, voivodeships with high values of the GE indicator were characterized by moderate levels of social trust. The statistical analysis did not reveal a significant correlation between social trust and green economy performance (r = 0.406, p < 0.05). The study demonstrated that social trust, in particular trust in neighbors and community members, requires improvement in most Polish regions. Trust in neighbors is a fundamental component of social capital. According to Jacobs, good neighborly relations contribute to a sense of security and build friendly environments. However, neighborliness is a process, rather than a fixed factor, and this understanding is essential for building good neighborly relations [110]. Therefore, to foster the development of social capital in Polish regions, the local authorities should prioritize measures that promote human interactions and integrate community members.

Green economy performance was bound by a significant correlation with engagement and social bonds (S_SC2) as a partial indicator of social capital. Pearson’s linear correlation coefficient reached r = 0.567 at p < 0.05. Engagement and social bonds were described with the use of ten measures, including participation in social and cultural initiatives, civic engagement, and volunteerism. Civic engagement (voter turnout in local elections and the European Parliament elections) and neighbor relations were characterized by the highest values in this group of measures. Only 6.5% of the respondents felt socially isolated, and more than 50% of the surveyed subjects had friendly relations with their neighbors. Social bonds are an abstract and metaphorical concept that describes the level of connectedness in human relationships, as well as the phenomena that determine the permanence of these relationships [111]. Social bonds and relationships enable humans to form groups and pursue the common good in a collaborative effort [112]. Factors that integrate communities in one area of life also contribute to the formation of strong bonds in other areas of social life [111,113], including pro-environmental activities [114,115,116]. Social interactions exert an intuitive influence on the pro-environmental behaviors of community members. Individuals who maintain close relationships with family members, neighbors, and friends are influenced by their attitudes toward the environment; therefore, social bonds contribute to community pressure for green behavior [117] and foster mutual green education. Numerous studies have shown that social engagement is directly proportional to the level of environmental education [118] and is essential for achieving sustainable development [119,120,121]. The results of the current study corroborate this observation to a certain extent because an increase in engagement and social bonds was accompanied by higher values of the green economy composite indicator, in particular in the voivodeships of Podkarpacie, Lubusz, and Małopolska, where the values of both indicators were relatively high. However, the reverse was also observed: despite high values of engagement and social bonds in Opole and Lublin, these voivodeships were characterized by low values of the green economy composite indicator.

Despite generally low values of engagement and social bonds in Poland (the maximum value of the composite indicator was 0.365), the measures describing this component of social capital probably exerted the greatest influence on the correlation between the main indicator of social capital S_SC and green economy S_GE (r = 0.516, p < 0.05). However, it should be stressed that both social capital and green economy have certain growth potential in Poland, and they can be significantly improved through education and environmental initiatives [102].

Therefore, social engagement and social bonds should be strengthened in all Polish regions to facilitate the achievement of green economy principles. According to Motyka [122], social bonds are not formed accidentally but evolve in the course of repeated and morally cohesive actions that build a sense of identity and community. Social bonding requires high levels of trust, a sense of security, and social support. Social bonds contribute to a sense of self-worth and empathy, promote engagement in community life, and encourage support for other members of the community. As a result, those with higher levels of social capital are also more likely to co-operate on environmental issues. By trusting in collective decision-making, they also influence an increase in knowledge among members of their community about the environmental impacts of various development activities [123].

The present study revealed that all components of social capital are mutually interdependent. Strong bonds in families, neighborhoods, and communities build a sense of identity and belonging, and can promote the achievement of green economy principles.

The values of all analyzed indicators differed considerably across Polish regions, which gives serious cause for concern. The reasons for the low values of nearly all indicators in central Poland should be explored in greater detail. Świętokrzyskie and Łódź voivodeships were grouped in class III based on the values of all examined indicators. Mazovia was also characterized by very low levels of social capital (it was ranked in class II based only on the value of the S_SC composite indicator). Somewhat higher values were noted in south-western Poland. Special attention should be paid to the results in Podkarpacie (ranked in class I based on four indicators and in class II based on one indicator) and Małopolska (ranked in class I based on three indicators and in class II based on two indicators). The results observed in two voivodeships escape easy interpretation. Despite high levels of social capital in Opole (ranked in class I based on four indicators) and Kuyavia-Pomerania (ranked in class I based on three indicators and in class II based on one indicator), these voivodeships were characterized by low values of the green economy performance indicator (class III). This discrepancy could be attributed to a “delay” effect between environmental education and awareness, and actual engagement in environmental initiatives. This assumption is theoretically correct, but further research is needed to determine whether a time shift exists between these factors.

The scope of the analyzed data is an important consideration in the type of analyses presented in this study. To achieve the research objectives, 30 measures were selected from statistical and institutional databases in the public domain. It should be noted that the range of the selected measures was limited by their type, scope, and availability. Therefore, there is a certain risk that these measures are incomplete or that an important factor that could have influenced the result was omitted. Indicators that are usually applied in socioeconomic research were carefully examined, and excessively correlated indicators were eliminated from the dataset to maximize the range of the analyzed data.

5. Conclusions

The levels of social capital and green economy performance were analyzed in Polish voivodeships based on 34 parameters that were publicly available, reliable, and mutually independent. Social capital was assessed as a composite indicator based on 25 partial indicators divided into three groups of indirect criteria describing public moral norms, engagement and social bonds, and social trust. Green economy performance was evaluated as a composite measure based on nine partial indicators. The strength of the relationships between the analyzed phenomena was evaluated by calculating Pearson’s linear correlation coefficients.

The results of the study were used to answer the research question, namely whether and to what extent social capital is correlated with green economy performance. The study revealed significant correlations between social capital and green economy performance in Polish voivodeships. The green economy is a long-term strategy, and social capital can act as a stimulating factor in the process of achieving green growth. Measures aiming to promote social capital in the short term can boost green growth in the long-term perspective. The study demonstrated that both phenomena require improvement, in particular in central Poland (Łódź and Świętokrzyskie voivodeships). The values of the social capital composite indicator were generally higher (four voivodeships were grouped in class III, Figure 3) than the values of the green economy performance indicator (six voivodeships were grouped in class III, Figure 4). The levels of social capital and green economy performance were generally higher in south-western Poland. These findings indicate that voivodeships that invest in social capital development will be able to accelerate their transition to a green economy. The results of this study can motivate the government to enhance social capital in Polish regions by promoting the concept of harmonious coexistence between humans and nature.

The levels of both phenomena were relatively low in all Polish voivodeships. This observation indicates that urgent action is needed to stimulate social capital development and green growth at the local level and that systemic solutions should also be developed at the national level. Therefore, strategic documents should promote measures that strengthen social bonds, the pursuit of the common good, and environmental awareness in Polish regions. The results of this study can be used to diagnose and monitor these phenomena. Information and awareness-building campaigns should be initiated at all levels of education, beginning from early childhood education. These campaigns should also involve social organizations and associations, including non-profit organizations that mobilize individuals to actively participate in the life of local communities.

The literature review revealed that both social capital and green economy significantly influence the quality of life and life satisfaction. These phenomena are synergistic and mutually propelling. High levels of social capital and green economy increase the living standards of the present generation while ensuring that future generations will also be able to meet their needs. Research on social capital and the green economy helps identify these dependencies, and it indicates that both phenomena should be monitored to achieve sustainable development goals.