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Through Sport to Innovation: Sustainable Socio-Economic Development in European Countries

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Using clustering and principal component analysis, we demonstrate that—at the national level in Europe—innovativeness correlates strongly to both social capital and participation in sport. In this aspect, countries such as the Scandinavian countries and the countries of Central and Eastern Europe differ visibly. Referring to prior empirical research, we claim that a causal relation between sports, through social capital, and innovativeness can be established. In the context of social capital accumulation, we further discuss the role of sports clubs, often perceived as a socially intensive form of participation in sport, but most likely diminishing in this respect lately.
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sustainability
Article
Through Sport to Innovation: Sustainable
Socio-Economic Development in European Countries
Hanna Nał˛ecz 1, Łukasz Skrok 2, Dawid Majcherek 3and El˙zbieta Biernat 4, *
1Department of Child and Adolescent Health, Institute of Mother and Child, Kasprzaka Str. 17A,
01-211 Warsaw, Poland; hanna.nalecz@imid.med.pl
2Department of Business Economics, Collegium of World Economy, SGH Warsaw School of Economics,
al. Niepodległo´sci 162, 02-554 Warsaw, Poland; lskrok@sgh.waw.pl
3Collegium of World Economy, SGH Warsaw School of Economics, al. Niepodległo´sci 162,
02-554 Warsaw, Poland; dm53757@doktorant.sgh.waw.pl
4Tourism Economy Research Unit, Collegium of World Economy, SGH Warsaw School of Economics,
al. Niepodległo´sci 162, 02-554 Warsaw, Poland
*Correspondence: elzbieta.biernat@sgh.waw.pl
Received: 15 November 2020; Accepted: 10 December 2020; Published: 15 December 2020


Abstract:
Using clustering and principal component analysis, we demonstrate that—at the national
level in Europe—innovativeness correlates strongly to both social capital and participation in sport.
In this aspect, countries such as the Scandinavian countries and the countries of Central and Eastern
Europe dier visibly. Referring to prior empirical research, we claim that a causal relation between
sports, through social capital, and innovativeness can be established. In the context of social capital
accumulation, we further discuss the role of sports clubs, often perceived as a socially intensive form
of participation in sport, but most likely diminishing in this respect lately.
Keywords: social capital; sports activity; innovation; labour market; EU countries
1. Introduction
Depending on the level of professionalism or discipline, sport can serve social functions
(pro-health, development of volitional features, socialisation, education and integration) [
1
,
2
]. It is
therefore an excellent platform for building social capital (SC). This fact is indicated by numerous
reports [
3
8
] which prove the coexistence of high levels of sports activity (SA) and SC among the
population of both children and adolescents, as well as adults. Involvement with sport is also positively
connected with building SC in neglected and special needs environments—e.g., those with a low
socio-economic status, with a criminal past, in national and religious minorities, among unassimilated
immigrants or those brought up in orphanages—by fostering social integration and community
development [9].
Skrok et al. [
10
] claim that generating SC through SA is particularly related to the relational
character of social capital, including, among others, the creation of social networks. These networks
may constitute a channel (apart from the eect of health status or skill level) through which positive
eects may occur, e.g., on the labour market. The aforementioned relationship between the SC and the
labour market constitutes nowadays an important research field, especially in the context of searching
for key reasons for dierences in the level of development of individual countries. Classical production
factors proposed, among others, by Smith [
11
], i.e., land, labour and physical capital, no longer explain
economic growth suciently. It is necessary to supplement them with the measures of human creativity
and the innovations developed thanks to it [12].
One of the best known indicators of creativity is technology, talent, tolerance (3Ts) developed by
Florida [
13
]. It is defined by the notion of a two-layer creative class. The first layer (super creative)
Sustainability 2020,12, 10489; doi:10.3390/su122410489 www.mdpi.com/journal/sustainability
Sustainability 2020,12, 10489 2 of 16
includes scientists, university professors, engineers, designers, architects, poets, novelists, artists,
writers, editors, people of culture, researchers and analysts. The second layer (creative professionals)
includes the people working in knowledge-based, high-tech and financial service sectors, as well as
legal, healthcare and business management professionals. Studies show that in 2015, countries such
as Denmark, Finland, Iceland and the Netherlands achieved the highest scores of this very indicator
among all EU countries [
14
]. It is noteworthy that, among the countries in the top 40, the creative class
represented over 40% of the workforce.
The 3Ts index was used by S. Yum [
15
] to develop its innovative version—creative class,
creative infrastructure, culture (3Cs). It took into account the cultural and infrastructural aspects of
creativity, which were omitted from the original and are increasingly important. The comparison of
both indicators is presented in Table 1.
Table 1.
Two creativity indexes: technology, talent, tolerance (3Ts) by Florida vs. creative class,
creative infrastructure, culture (3Cs) by Yum.
Creativity Index Florida’s 3Ts Creativity Index (2002)
Dimension Category Content
Talent Creative class
Human capital index Proportion of creative class
Proportion of university degrees holders
Technology High-tech innovation
Innovation index The amount of high-tech production
Proportion of patents owners
Tolerance Bohemian index
Melting pot index
Gay index
Proportion of artists
Proportion of foreigners
Proportion of gay people
Creativity Index Yum 3Cs Creativity index (2015)
Dimension Category Content
Creative class Creative class Proportion of creative class in general population
Creative infrastructure Study infrastructures
Rest infrastructures
People
The number of universities, creative industries (including R&D)
Number of cafes, restaurants, parks
Proportion of foreign-born people in general population
Culture Places
Buildings
Areas of historic preservation, number of libraries and museums
Note: Own compilation based on Florida (2002) and Yum (2015).
Innovation is the key process that shapes economic development. This concept was used for
the first time by Schumpeter [
16
], who emphasised the importance of new products and solutions.
He interpreted innovation as the introduction of a novel product or its novel variety, the implementation
of a new production process, the opening or creation of a new market, the use of new materials or the
application of a new production organisation. A sine qua non condition to consider a given solution as
an innovation is its commercialisation [17].
The most common innovation indicators include the following: Innovation Union Scoreboard,
Global Innovation Index and Global Competitiveness Report. The research conducted to date, for example,
by Olejniczuk-Merta [
18
], shows that—despite it being a long period after the political transformation
(over 30 years) and continuous central co-financing of innovation—Poland still has a low position in these
rankings: according to the Global Competitiveness Report (2019) [
19
], out of 141 examined economies, it ranks
37th; according to the Global Innovation Index (2019) [
20
], out of 129 economies—41st; and, according to the
European Innovation Scoreboard (2019) [
21
], out of 35 economies (including 27 EU countries)—last but four.
The results of the pan-European innovation rankings cited above, as well as a scarce research
combining sports activity, social capital and economic indicators with innovation, have led us to follow
the modern approach, that the eective and ecient development of an innovative economy requires
investment in human and social capital [15,22].
Therefore, we decided to explore more widely, and in the international context, the findings
from the National Bank of Poland (NBP) 2016 Report [
23
]. The NBP report reveals that the most
Sustainability 2020,12, 10489 3 of 16
innovative countries, such as Switzerland and the Scandinavian countries, perform much better than
Poland—both in terms of general interpersonal trust and trust in the parliament and the legal system,
as well as in terms of the analysed involvement with sports/recreational organisations. This statement
has become a direct inspiration to conduct this in-depth research of a confirmatory character, because the
conclusions of NBP 2016 suggested a positive relationship between SC, SA and innovation. This is
due to the general trust (including interpersonal trust, trust in social standards, trust in institutions),
which fosters innovation and technology diusion, and translates directly into the total productivity of
classical, previously mentioned, production factors [23].
By making a hypothesis concerning the direct or indirect relationship between SA and innovation,
the authors of this paper attempted a multidimensional analysis of the relationship between SA and
SC and innovation among European countries.
We perceive our research as a contribution to the previously unexplored dimension of co-variability
and the multidimensional relationship between sport activity, social capital and innovation. This will
allow greater insight and better understanding of the social determinants of economic mechanisms
and indicators.
The aim of this analysis is to verify the observations of the National Bank of Poland (NBP)—is SA, at a
country level, positively related not only to the level of SC, but also to the level of innovation? The work
was carried out within the framework of the National Science Centre grant No. 2017/27/B/HS4/00427
and constitutes a summary of the results of the work carried out within its scope. The interpretation of
the obtained results is embedded in the context of previous analyses.
2. Materials and Methods
This paper refers to a broad definition of innovation, according to the Oslo Methodology [24]:
An innovation is a new or improved product or process (or combination thereof) that diers significantly
from the unit’s previous products or processes and that has been made available to potential users
(product) or brought into use by the unit (process) (op cit. page 60). Innovation is more than a new
idea or an invention. An innovation requires implementation, either by being put into active use or
by being made available for use by other parties, firms, individuals or organisations. The economic
and social impacts of inventions and ideas depend on the diusion and uptake of related innovations.
Furthermore, innovation is a dynamic and pervasive activity that occurs in all sectors of an economy;
it is not the sole prerogative of the Business enterprise sector. Other types of organisations, as well as
individuals, frequently make changes to products or processes and produce, collect, and distribute new
knowledge of relevance to innovation (op cit. page 44).
Therefore, the analysis incorporates a set of innovation indicators that describe private sector
inputs (business expenditure on research and development—BERD, number of research and development
personnel), outputs (European Patent Oce (EPO) patent applications) and social context (attitude to
creativity as an important feature). It was decided to omit the inputs of the public sector as, on the one
hand, they are dependent on national policies and, on the other, on the condition of the state budget.
Due to the fact that the survey was conducted at the level of EU countries (including the UK),
the analysed variables were of a relative character (related to e.g., gross domestic product—GDP or
population size), or took the form of an average for a surveyed characteristic in a given country.
2.1. Data
The following sources of data at an aggregate country level were used in the analysis:
-
Eurobarometer 412 [
25
] as a source of information about sports activity and the people participating
in sport in clubs in 2013;
-
European Social Survey (ESS) (2012) and (2014) as a source of data on SC and social attitudes [
26
,
27
];
- Eurostat [28] as a source of data on innovation, GDP, population size and working conditions.
Sustainability 2020,12, 10489 4 of 16
The following variables were used as measures of innovation:
- share of business enterprise R&D expenditure in GDP (BERD);
- number of patent applications to the European Patent Oce per capita—EPO;
- number of researchers employed in the business sector per capita—RDp;
- seeing creativity as an important value—CR.
Except for the last point, the data source was Eurostat. In the case of CR, an average was calculated
(using the weights included in the ESS database) to answer the question of to what extent, on a
six-point scale, respondents agreed that “Thinking up new ideas and being creative is important to
them. They like to do things in their own original way”.
The answers to two questions from Eurobarometer 412 were used to devise sports activity
indicators. The first question, “By ‘exercise’ we mean any form of physical activity which you
do in a sports context or sport-related setting, such as swimming, training in a fitness centre or a
sports club, running in the park, etc. How often do you exercise or play sport?”, enabled us to
determine the total percentage of the people responding: “A few times a week” or “Almost daily”
(other options: “Occasionally” or “Never”) and thus determine the “sports activity” indicator—SA.
The second question, “Are you a member of any of the following clubs where you participate in sport
or recreational physical activity?” allowed for the construction of the “sports club” indicator—SClub.
SC was measured using a set of variables calculated using the weights defined in the ESS
database as:
-
averages for the questions in which the respondents assessed the importance of their values or
life attitudes on a six-degree scale, or on a 10-degree scale—the level of their confidence in other
people or institutions;
-
groups of the population that responded affirmatively or in a certain way to other questions,
e.g., about being a member of a political party or a trade union.
Detailed definitions of the indicators based on ESS, including the wording of the original questions,
are provided in Table S1 in the Supplementary Materials.
Data provided by Eurostat were used as indicators to describe working conditions—which may
aect the availability of leisure time and thus the possibility of engaging in sports activity. In particular,
they were based on the following:
-
EU Labour Force Survey (LFS)—i.e., the percentage of commuters within the same NUTS2 region
and the average working time of those in managerial, specialists and technical roles;
-European Working Conditions Survey (EWCS) [29]—i.e., average commuting time.
GDP per capita (in thousands of euros) was used as a variable describing the economic development.
Due to the lack of an ideal match between the periods of the above-mentioned research, it was
necessary to adjust the time structure. This was particularly true for the ESS data, which were based
on average values for 2012 and 2014 (if available). For the average commuting time (EWCS), data from
2015 were used.
The availability of data accounted for the fact that 22 European countries were eventually analysed.
These were the following: Austria, Belgium, Bulgaria, Cyprus, the Czech Republic, Denmark, Estonia,
Finland, France, Germany, Hungary, Ireland, Italy, Lithuania, Poland, Portugal, Slovakia, Slovenia,
Spain, Sweden, the Netherlands and the UK.
Sustainability 2020,12, 10489 5 of 16
2.2. Method
Due to the number of the SC measures, their high degree of correlation and the general nature of
the interdependencies analysed, principal component analysis (PCA; [
30
]) was used first to devise
the SC indicators (based on 23 variables from the ESS) and labour market relations (based on seven
variables from Eurostat). In each case, the PCA was carried out independently, and the first principal
component for each of them was used in further analysis. In the case of the SC index, this component
accounted for 50% of the total variance, and in the case of labour market relations, for 44%.
The SC index was interpreted as a negative measure of “anti-community”. This was influenced by
two aspects. The first is the negative impact of the variables measuring: trust in people and institutions,
participation in elections, unionisation, openness to others, life satisfaction. The second is the positive
impact of variables such as: perceiving it important to be admired (in connection with one’s own
skills) or respected by others. The impact of particular variables is presented in Figure S1 in the
Supplementary Materials.
The indicator for the relations on the labour market was interpreted as a measure of “concentration
on primary work” (WP)—due to negative impact of the prevalence of having a second job and the
average commuting time, and also due to the positive impact of average working time. The impact of
particular variables is presented in Figure S2 in the Supplementary Materials.
Next, the indicators calculated in the previous step, i.e., SC and WP, as well as the measures of
sports activity (share of people active in sports—SA, share of people exercising in sports clubs—SClub),
measures of innovation (BERD, patent applications to the European Patent Oce per capita—EPO,
researchers employed in the business sector per capita—RDp, perception of creativity as an important
value—CR) and GDP per capita (GDP) were used to cluster countries using the k-means method,
using the Euclidean distance and standardisation of variables [
31
]. The aim of the analysis was to
identify groups of countries that were as similar as possible with regard to the studied dimensions
(within clusters) and those that were dierent from each other in this respect.
A correlation table is presented for the variables used in clustering (for Pearson’s r coecient).
The presentation of the results (in Figure 1) in a two-dimensional system required limiting the
number of dimensions (again, using PCA). After verifying dierent sets of parameters (the verification
included an assessment of the separability of clusters and the assumption that each of them consists of
at least two elements, i.e., countries), results for four clusters were presented. Figure 1also shows the
average values of the variables used in clustering for individual groups of countries. The impact of
particular variables is presented in Figure S3 in the Supplementary Materials. In order to assess the
feasibility of the clustering analysis, we calculated the Hopkins statistic [
32
]. The Hopkins statistic
tests the spatial randomness of the data. We conducted the Hopkins statistic test iteratively by
get_clust_tendency in R, using 0.5 as the threshold to reject the alternative hypothesis. That is, if H <0.5,
then it is unlikely that dataset has statistically significant clusters. The Hopkins statistic for our dataset
is 0.64, which means that observations within the dataset are clusterable (the H value =0.64 which is
above the threshold 0.5).
The analysis was conducted using the R environment [
33
] and the factoextra package [
34
].
Results were based on 25 random initial configurations.
Sustainability 2020,12, 10489 6 of 16
Sustainability 2020, 12, x FOR PEER REVIEW 6 of 16
Figure 1. Cluster plot for nine indicators and 22 countries with mean values for clusters. Note:
SClub—sporting activity in sports clubs; SA—sporting activity; CR—perception of creativity as an
important feature (negative indicator); BERD—corporate R&D expenditure; RDp—R&D personnel;
EPO—patent applications submitted per capita; SC—negative anti-community indicator; WP—
concentration on the primary job (negative indicator); GDP—gross domestic product (GDP). BSS/TSS
ratio = 75.9%, average silhouette = 0.283, Dunn index = 0.343, minimum average dissimilarity between
two clusters to maximum average within cluster dissimilarity ratio = 1.108.
3. Results
The analysis of the data from the years 2012–2015 allowed us to distinguish four clusters, which
reveal patterns of interrelation between the described nine indicators in the examined areas: SA,
innovation and SC, in European countries. The Supplementary Materials contain Table S2, showing
the values of nine indicators for particular countries.
Cluster I contains: Denmark, Finland, Sweden and the Netherlands, and cluster II: Cyprus, Italy,
Slovakia and Spain. The third cluster consisted of seven countries: Austria, Belgium, France,
Germany, Ireland, Slovenia and the UK, and cluster IV: Bulgaria, the Czech Republic, Estonia,
Lithuania, Hungary, Poland, Portugal. These results are illustrated in Figure 1.
Clusters are evenly distributed in pairs. Countries belonging to cluster I are the countries with
the highest SA indicators (from 58% in the Netherlands to 70% in Sweden). They stand out from other
countries (from other clusters) with a high share in SClub (from 12% in Finland to 27% in the
Netherlands) and a high level of innovation indicators (EPO—from 200 submitted applications in the
Netherlands to 339 in Sweden; BERD—from 1% in the Netherlands to 2.3% in Sweden; CR—from 2.7
in Finland to 2.4 in Denmark; RDp—from 6.8 in the Netherlands to 8 in Finland) and social capital
(SC—from 3.4 in the Netherlands to 6.9 in Denmark; WP—from 0.8 in Finland to 4.8 in the
Netherlands). The GDP ratio (GDP per capita) is the highest in these countries.
In the countries belonging to cluster II, the SA indicator is almost half as low as in the first cluster
(from 30% in Italy to 46% in Spain). On average, 7% of adults train in sports clubs (SClub). The EPO
innovation indicator decreases to two- and one-digit values (from nine submitted applications in
Figure 1.
Cluster plot for nine indicators and 22 countries with mean values for clusters.
Note: SClub—sporting activity in sports clubs; SA—sporting activity; CR—perception of creativity
as an important feature (negative indicator); BERD—corporate R&D expenditure; RDp—R&D
personnel; EPO—patent applications submitted per capita; SC—negative anti-community indicator;
WP—concentration on the primary job (negative indicator); GDP—gross domestic product (GDP).
BSS/TSS ratio =75.9%, average silhouette =0.283, Dunn index =0.343, minimum average dissimilarity
between two clusters to maximum average within cluster dissimilarity ratio =1.108.
3. Results
The analysis of the data from the years 2012–2015 allowed us to distinguish four clusters,
which reveal patterns of interrelation between the described nine indicators in the examined areas:
SA, innovation and SC, in European countries. The Supplementary Materials contain Table S2,
showing the values of nine indicators for particular countries.
Cluster I contains: Denmark, Finland, Sweden and the Netherlands, and cluster II: Cyprus,
Italy, Slovakia and Spain. The third cluster consisted of seven countries: Austria, Belgium, France,
Germany, Ireland, Slovenia and the UK, and cluster IV: Bulgaria, the Czech Republic, Estonia, Lithuania,
Hungary, Poland, Portugal. These results are illustrated in Figure 1.
Clusters are evenly distributed in pairs. Countries belonging to cluster I are the countries with
the highest SA indicators (from 58% in the Netherlands to 70% in Sweden). They stand out from
other countries (from other clusters) with a high share in SClub (from 12% in Finland to 27% in the
Netherlands) and a high level of innovation indicators (EPO—from 200 submitted applications in the
Netherlands to 339 in Sweden; BERD—from 1% in the Netherlands to 2.3% in Sweden; CR—from 2.7 in
Finland to 2.4 in Denmark; RDp—from 6.8 in the Netherlands to 8 in Finland) and social capital
(SC—from
3.4 in the Netherlands to
6.9 in Denmark; WP—from
0.8 in Finland to
4.8 in the
Netherlands). The GDP ratio (GDP per capita) is the highest in these countries.
Sustainability 2020,12, 10489 7 of 16
In the countries belonging to cluster II, the SA indicator is almost half as low as in the first cluster
(from 30% in Italy to 46% in Spain). On average, 7% of adults train in sports clubs (SClub). The EPO
innovation indicator decreases to two- and one-digit values (from nine submitted applications in
Slovakia and Cyprus to 72 in Italy). R&D expenditure (BERD) is only 0.4% of the Slovak budget and
0.7% of the Italian budget. The CR indicator (2.5) remains on average at the same level as in cluster I
countries. The R&D personnel indicator is the lowest among all surveyed countries (from 0.5 in Cyprus
to 1.9 in Spain). Similarly, the values of social capital measures are very low (SC—from 3.8 in Slovakia
to
0.3 in Spain; WP—from 2.4 in Slovakia to 0.9 in Italy). The level of GDP is low, however, not the
lowest (which is the case in cluster 4).
Cluster III is characterised by quite high sports activity indicators (SA—from 43% in France to
52% in Ireland; SClub—from 11% in the UK to 24% in Germany), high SC indicators (SC—from 2.9 in
Slovenia to -2.2 in Belgium; WP—from 1.3 in Ireland to 0.6 in Germany) and innovation (EPO—ranging
from 62 in Slovenia to 261 in Germany; BERD—from 1% in the UK to 2% in Austria; CR—from 2.6 in
Belgium to 2.4 in Germany; RDp—from 4 in Slovenia to 5.9 in Austria) and high GDP.
Cluster IV includes the countries with the lowest sports activity indicators (SA—from 11% in
Bulgaria to 39% in Estonia; SClub—from 2% in Bulgaria to 12% in Estonia), very low innovativeness
(EPO—from 5 in Bulgaria to 24 in the Czech Republic; BERD—from 0.2 in Lithuania to 1 in the Czech
Republic; CR—from 3.4 in Bulgaria to 2.8 in Portugal; RDp—from 0.7 in Bulgaria to 3 in Lithuania) and
low SC (WP—from 2.3 in Bulgaria to
1.3 in Estonia), especially in the SC area (from 5.19 in Bulgaria
to
0.28 in Estonia). This cluster includes the countries with the lowest (of all the examined countries,
except Slovakia) GDP. Slovakia, with an income at a level of 13.7, was included in cluster II.
Moreover, we conducted robustness analysis of our results, presented in Figure 1. The first
additional cluster analysis is available in Figure S4 in the Supplementary Materials. Figure S4 illustrates
cluster analysis of eight variables (SA, CR, BERD, RDp, EPO, SC, WP, GDP). The one missing variable
compared with Figure 1is SClub. However, the results of analysis of these eight indicators lead
to the same clustering of countries as the results presented in Figure 1. Similarly, Figure S5 in the
Supplementary Materials shows that removing both variables related to sports (SClub and SA),
does not change the outcome. In addition, we provided another cluster analysis of 10 variables
(SA, CR, BERD, RDp, EPO, SC, WP, GDP and an additional one for general health). The results
are available in Figure S6 in the Supplementary Materials. Once again, this analysis illustrated the
same cluster construction as Figure 1. Figure S7 in the Supplementary Materials presents results of
analysis in which additional measures of social capital and working conditions have been used. In
this case, most countries from Eastern and Southern Europe are clustered together, but outcomes for
Northern and Western European countries do not change, emphasizing that this geographical split is
crucial. This division is also visible within the results of an alternative, hierarchical clustering method
(Figure S8 in Supplementary Materials). The validation of clustering was performed by those two
sensitivity analyses combined with the Hopkins statistic (H =0.64) as a clusterability measurement.
The correlation analysis for Pearson’s r coecient carried out based on the variables used in
clustering demonstrated that all the indicators in question are interrelated (Table 2). This fact is not
surprising, as all indicators are positively related to the level of economic development, measured by
the value of GDP per capita. Since dierences in economic development can be both the cause and the
eect of other international dierences (in other aspects), GDP can account for positive correlations
between these other aspects.
Sustainability 2020,12, 10489 8 of 16
Table 2. Pearson’s r correlation matrix for 22 countries.
Sport Activity
Indicators Creativity Indicators Social Capital
Indicators
Socioeconomic
Situation
SClub SA CR BERD RDp EPO SC WP GDP
Sport activity
indicators
SClub 1 0.79 *** 0.44 * 0.67 *** 0.79 *** 0.75 ***
0.79 ***
0.74 ***
0.83 ***
SA 0.79 *** 1 0.57 ** 0.77 *** 0.87 *** 0.8 ***
0.89 ***
0.66 ***
0.83 ***
Creativity
indicators
CR 0.44 * 0.57 ** 1 0.41 0.41 0.45 * 0.44 * 0.09 0.64 **
BERD 0.67 *** 0.77 *** 0.41 1 0.87 *** 0.86 ***
0.73 ***
0.42 0.73 ***
RDp 0.79 *** 0.87 *** 0.41 0.87 *** 1 0.9 ***
0.87 ***
0.67 ***
0.85 ***
EPO 0.75 *** 0.8 *** 0.45 * 0.86 *** 0.9 *** 1
0.88 ***
0.63 ** 0.85 ***
Social capital
indicators
SC
0.79 ***
0.89 ***
0.44 *
0.73 ***
0.87 ***
0.88 ***
1 0.73 *** 0.88 ***
WP
0.74 ***
0.66 ***
0.09 0.42
0.67 ***
0.63 ** 0.73 *** 1 0.62 **
Socioeconomic
situation GDP 0.83 *** 0.83 *** 0.64 ** 0.73 *** 0.85 *** 0.85 ***
0.88 ***
0.62 ** 1
Note: SClub—sporting activity in sports clubs; SA—sporting activity; CR—perception of creativity as an important
feature (negative indicator); BERD—corporate R&D expenditure; RDp—R&D personnel; EPO—patent applications
submitted per capita; SC—social capital (negative anti-community indicator); WP—concentration on the primary job
(negative indicator); GDP—gross domestic product. Significance: *** <0.001, ** <0.01, * <0.05. Normality assumption
is rejected at p=0.0013 for EPO, at p=0.0519 for RDp and at p=0.0966 for GDP). The values of Spearman’s rank
correlation (not reported) are close to reported Pearson’s coecients.
4. Discussion
This paper concludes the wider research concerning the role of sports activity in building social
capital. To date, the profile of adults engaged in sports has been analysed, with the use of a multi-level
social and environmental approach [
35
]. The key demographic and socio-economic characteristics and
the interactions occurring between them have been demonstrated, which accounted for the dierences
between practising and not practising sport [
36
,
37
]. The relationship between sports activity and
social capital at an individual level has been assessed, as well as the impact of sports activity on the
health, beliefs and social status of adults [
10
]. A question on how sports activity can contribute to the
accumulation of social capital in a country where its level is low has also been investigated [38].
The final stage of the research, the results of which are contained in this paper, is a multidimensional
analysis of the relationship between sports activity and social capital and innovation in European
countries. The data clustering analysis carried out with the use of the k-means method has revealed that
all these examined variables, characteristic of particular societies/economies, are positively correlated
with each other (including the level of economic development—GDP per capita). However, it should
be noted that they are less related to labour market organisation. We endeavor to show in this article
that high innovation in European countries such as Sweden, Finland, Denmark and the Netherlands is
accompanied by high SA (especially in clubs) and high SC, which translates into high GDP. This is also
confirmed by the pan-European innovation rankings mentioned in the introduction to this paper.
At the national level, social capital, sports activity and innovativeness seem to correlate
strongly—at least indirectly (e.g., in connection to the level of economic development). While the
relation observed between innovativeness and sports (even treated or understood as social activity) at
the national level can be considered a spurious one (e.g., resulting from economic development level),
we think that specific mechanisms that go from engagement in sports (especially when it is embedded
in a social setting), through selected dimensions of social capital, to innovativeness can be identified.
Firstly, the impact of engagement in sports activity on social capital is often implied.
The mechanisms behind this are synthetically presented by Pawlowski and Schütto[
39
]. The research
by Felfe, Lechner and Steinmayr and Schüttoet al. [
40
,
41
] show empirically that sport can be a tool
that fosters the development of SC among children and youths or reduces social problems. The same
is true for adults. Di Bartolomeo and Papa [
42
] describe an experiment (with the participation of
students) proving that physical activity itself, even in the short term, promotes trust and cooperation
with other people.
Our recently published research at an individual level, using a radius matching method [
10
],
provides arguments in line with the pre-existing empirical results (i.e., Felfe, Lechner and Steinmayr
Sustainability 2020,12, 10489 9 of 16
and Schüttoet al. [
40
,
41
]—engagement in sports activity (or involvement with sport clubs) can
contribute to the accumulation of social capital, but only within its selected dimensions. In particular,
thanks to the application of the results of a rich longitudinal study on social profiles of people living in
Poland, Social Diagnosis [
43
], we show that—for some groups (women over 40)—a positive impact of
sports activity on social involvement is substantial and broad in terms of the types of involvement
(including work for the benefit of local society). At the same time, for others (in particular, for younger
women and men), it contributes mainly to the extension or deepening of social networks and to the
development of a more positive and proactive attitude towards life and work.
Secondly, the relationship between SC and innovation—although understood generally and
intuitively, and often only mentioned—is heterogeneous and complex. This was demonstrated by
Echebarria and Barrutia [
44
] in their review of the empirical literature and their own quantitative
analysis. According to their reports, SC can foster innovation, e.g., by lowering transaction costs
(both transactions and knowledge sharing take place with a higher level of trust), or by increasing the
knowledge base (by expanding social networks). However, the empirical analyses they refer to show
that bridging social capital and weak ties, as well as associational activity, are crucial in this respect,
and not necessarily—for instance—trust or deepened relationships in a narrow social environment.
At the same time, Echebarria and Barrutia [
44
] observe a non-monotonous relationship between SC
and innovation. They demonstrate that maintaining too high SC (defined broadly, measured by an
aggregate index and based on the European Values Survey) is so costly that it limits innovation. It should
be noted that our observation regarding the relation between sports activity and the extension of social
networks, stipulated by Skrok et al. [
10
], is consistent with the observations concerning the relation of
social capital and innovation mentioned above.
Furthermore, social capital is found to be related to pro-innovative attitudes. For example,
as presented in Asteria et al.’s [
45
] gender equality studies, the network and social capital of the
community are related to women’s proactivity. In Perry-Smith and Shalley [
46
], social relations and
their translation into creativity were analysed. The authors “go beyond the idea that communication
and interaction in general facilitate creativity by describing the dynamic interplay between social
networks and creativity” (op. cit., pp. 100) and through multilevel analysis proved that “the social
relationships may facilitate creativity, and in some special conditions may actually constrain creativity”
(op. cit., pp. 100). They claim that increased communication and increased interaction are helpful in
supporting creativity at the organisational level, and Gong et al. [
47
] confirmed this relation at the
individual level.
In this context, it should be noted that the role of engagement in sports activity could be
especially important when it takes place in a manner allowing for transgressing boundaries of narrow,
hitherto existing social groups to which a given person belongs. One of the key questions in this respect
is whether organised, long-lasting forms of sports activity—training in sports clubs—are particularly
conductive to such eects. Indeed, the literature often analyses the role of sport clubs in the context
of the relationship between sports and social capital. Therefore, it arises from the findings presented
by Seippel [
4
] that being a member of sports clubs may be connected to a higher level of trust,
however, Downward, Pawlowski and Rasciute [
48
] suggest that the cause and eect dependency is
the reverse. The meaning of sport clubs might be more complex, however. Sillen [
49
] argues that the
success of sport clubs depends on their inclusiveness and ability to settle themselves in local societies.
Brown [
50
] shows that members of sports or recreation community organisations in Lund (Sweden)
and Ballarat (Australia), in comparison with the members of other organisations, had higher scores in
some measures of social capital (higher trust in government, greater tolerance and better relations with
neighbours) and not worse scores in other measures.
Sports clubs often bring together people from dierent backgrounds and even from dierent
cultures, which can contribute to fostering SC in compassionate, multicultural societies [51].
Remarkably, members of sport clubs in those countries characterised by a high level of both
social capital and involvement with sports clubs are often shown to be driven by dierent motives
Sustainability 2020,12, 10489 10 of 16
than the people involved in more flexible forms of sports activity. In particular, for the Netherlands,
Deelen, Ettema and Kamphuis [
52
] found that both social recognition and image and social aliation
and skill development are more often the goals of the former group than of the latter. On the other hand,
with respect to engagement in settings other than sports clubs, health orientation plays a greater role.
In other words, not only is social involvement more directly related to clubs, but so is the willingness
to make progress. These traits, in turn, can be linked to—respectively—accumulation of social capital
and innovativeness, understood as a process of improvement. This phenomenon is mirrored in the
fact that sports activity and exercising in sports club are studied separately at the EU level (see Special
Eurobarometer 412, 427).
We achieved results consistent with the observations presented above in another of our analyses [
38
].
Namely, at the aggregate, regional level (NUTS 4), we employed the instrumental variables method
(using data on sports infrastructure, detailed in terms of the types of infrastructure, as the source of
instruments) to analyse the impact of membership of sport clubs on social capital. The supplementary
character of these findings results from the fact that some dimensions of social capital can be only
measured at an aggregate level, e.g., the propensity of local societies to create organisations. Our main
finding is that, while there is no apparent relationship between membership of sports clubs and
civic involvement (measured by participation in general elections) or donorship (measured by tax
deductions resulting from donations), a positive relationship between the number of associations
or other organisations and social goals can be identified. In other words, at the societal level,
higher involvement with sport clubs coincides with a higher propensity not only to follow pro-social
goals, but also to plan activities towards fulfilling them. The latter might be interpreted as a willingness
to sustain and systematise these eorts, and not treat them as ad hoc or temporary tendencies.
Therefore, we argue that social activity and organised sports activity can create a virtuous cycle that,
in the long run, could also lead to other socio-economic benefits, such as innovativeness.
There are, however, arguments against the “special role” that sports clubs might play in stimulating
the accumulation of social capital (as opposed to sports activity in general, not in comparison with
other associations). In particular, returning to the analysis at the level of the countries presented in this
article, SA is associated with the measures of innovation no worse than SClub. This is also confirmed
by the results of the correlation analysis.
Explanations of the above result can be found in the literature. It proves, on the one hand,
that membership of a sports club gives more diverse benefits than recreational physical activity
(e.g., in individual disciplines, it has no social eect) [
53
], that it has a strong influence on general
physical activity [
54
] and that it plays a pivotal role in social integration [
55
]. On the other hand,
more and more researchers [
56
,
57
] consider it a myth that organised sport oers a developmental benefit
for everyone. Indeed, since the 1990s, there has been an increased involvement with non-organised,
informal sport [
58
]. Eime et al. [
53
] argue that this involvement has increased significantly over
the last decade. According to Borgers et al. [
59
] this is due to institutional changes, which are the
consequence of cultural and social changes, as well as changing values, habits and attitudes of people.
Today’s participants in sports do not want to be dependent on formal structures such as membership
obligations, opening hours and the availability of specific sports facilities [
58
]. They want to avoid the
stress (competition, losing, dissatisfaction) that is inherent in organised sport [
55
] (often accessible
only to small, privileged groups of people [
60
]). They seek greater flexibility and a greater sense of
autonomy. Research shows that self-organised SA can also have positive psychological and social
eects (among others, it can promote general life skills and pro-social behaviour) [
61
]. For example,
lifestyle sports can oer young people the opportunity to learn social skills such as: independence,
self-control, cooperation, problem solving [
62
]. According to Säfvenbom, Wheaton and Agans [
63
],
such contexts may produce thriving young people, not in spite of, but because of involvement in contexts with no
strict rules, no formal leaders and no a priori competence or performance goals. In addition, researchers argue
that the element of fun, inherent in self-organised SA, is more likely to foster creativity, identity building
and self-actualisation [
63
]. Fun is the result of internal motivation and can therefore be seen as an
Sustainability 2020,12, 10489 11 of 16
important factor in experiencing personal activity, pleasure, autonomy, self-determination, competence
development and self-esteem [
64
]. Furthermore, Deelen, Ettema and Kamphuis [
52
] point to the
perceived minimum skill level as a potential limitation in the general openness of sports clubs towards
society. One can argue that under such conditions, clubs would rather lead to the accumulation of
bonding, but not bridging social capital. Once again, however, the social aspect of membership of
sports clubs should be considered as dynamic and country specific [
65
]. In particular, with respect to
the Netherlands, Bovens and Trappenburg [
66
], Elling and Claringbould [
67
] and van Haaften [
68
]
show that sports clubs can even become exclusionary, segregating or self-segregating. In the case of
Germany, Burrmann, Braun and Mutz [
69
] show that, while in 2001 the members of sports clubs were
more pro-socially oriented than non-members, no such dierence could be observed in 2017/2018.
Scheerder et al. [
70
] show that, while in 1979 the members of the middle class, and even more so
of the upper class, were more likely to be involved in club participation than the members of the
lower class, no significant impact of social class was observed either in 1989 or in 1999. For the
non-organised participation, however, the results were the reverse (i.e., nonsignificant in 1979 and
significant, increasing with social class, in later years). For commercial gyms in Germany, Cardone [
71
]
argues that, while the behaviour of the members can be inward-orientated and exclusionary, it can also
transgress cultural dierences.
The contemporary nature of engagement in sports activity described above, not necessarily
dependent on involvement with sports clubs, is reflected in another of our articles [
36
]. We showed
that two of the three (apart from the age) most important factors accounting for engagement in sports
activity in Poland are of a social nature. One describes a narrow group, to which a given person
belongs, the other, adults in a household. Namely, the more other members of the latter engage in
sports activity, the greater the probability that a given person does as well. Secondly, a key variable
describes whether a given person goes to restaurants, bars or pubs. This suggests that, without judging
causality, openness to going out and using market services instead of traditional household production
is relevant. Once again, it is consistent with the conclusion on the social nature of sports activity and
the tendency of the latter and social capital to reciprocally reinforce one another. Moreover, it should
be noted that the greater propensity to engage in sports demonstrated by the adults who organise their
lives in a modern, market-based way is consistent with the previously described observations set out
by Florida [14] on the creative class.
To conclude, our previous studies (Skrok et al. [
10
]; Biernat et al. [
38
]; Biernat, et al. [
35
]) indicate
a positive direction of mutual dependencies between SA or SClub and SC. In light of these results,
the actions taken in Europe since the 1990s focusing on raising the profile of sports and physical activity
and the implementation of the so-called European model of sport by the European Commission go well
beyond their original objective—health. Therefore, they are of pivotal importance for supporting
the sustainable development of EU countries, in line with the UN’s sustainable developmental goals
(SDGs) [72,73].
However, given the diversity of forms and structures that characterise the field of sport in particular
Member States, the development of a universal model and a completely uniform organisational structure
cannot be an objective of the EU’s actions. In line with the European dimension of sport, a local sports
club plays a key role in the overall organisational structure of sport in the EU [
74
], although, as we have
pointed out, the literature on this subject has raised questions in this respect in recent years. Due to
its multidimensional nature and cross-sectoral links, it is one of the factors supporting sustainable
development of individuals and local communities. However, there are countries, such as Poland,
where sports clubs function poorly in terms of public awareness and their activity does not translate into
the popularisation of sport [
75
]. This is confirmed by Heinemann [
76
], Tuyckom and Scheerder [
77
] and
Breuer et al. [
78
], who point to the geographical, social and organisational diversity of sports activity in
the EU. Therefore, on the basis of strategic documents (e.g., White Paper on Sport,European Dimension in
Sport or Global action plan on physical activity 2018-2030), Member States create their own legal grounds
and implement internal policies while preserving their national character [7981].
Sustainability 2020,12, 10489 12 of 16
Our study is subject to limitations. Only 22 countries—all being EU members during the period
covered by the analysis—limits possibilities to generalise the conclusions. This is further reinforced by
the fact that the majority of empirical research included in the discussion was based on selected European
countries. Furthermore, only selected measures of innovativeness were available—even though they
cover dierent facets of this process, it is, undoubtedly, significantly more complex. For example,
the EPO procedure is only one of the elements of patenting strategies at the disposal of potential
intellectual property owners. In broad sense, innovativeness is not only restricted to R&D recorded
within ocial statistics on personnel and expenditure. Thirdly, the available measure of sports activity
was based on information that included the frequency, but not intensity, of it. Neither was information
on the social aspects of this activity available—even in individual disciplines, like running or cycling,
which one can engage in in solitude or alongside other people. The same could be said of sport
clubs—as discussed, their organisational culture might matter for the accumulation of social capital,
and this character varies internationally.
In light of the described limitations, one should emphasise the need for further research.
We consider ours as one of the first steps in the analysis of a non-obvious relationship between sports,
social capital and innovativeness. Certainly, whether it is possible to the replicate the observation
outside Europe would be an interesting question.
Secondly, further evidence on possible causal relations between involvement in sports, sport clubs
and particular dimensions of social capital and innovativeness both on personal (e.g., through creative
approach) and societal (e.g., through creation of productive social networks) aspects should not only
be of great value, but also possible in future, especially with increasing availability of microdata.
5. Conclusions
The analysis of European countries in terms of their level of innovation, sports activity and social
capital allowed us to distinguish four clusters. In the countries with high innovation, such as
Sweden, Finland, Denmark and the Netherlands, high sports activity and high social capital
were observed.
The majority of Central and Eastern European countries belong to the cluster with the lowest
sports activity indicators, very low innovativeness and low SC (especially in the SC area).
Sports activity (in the long term) can, through its socialising character, have the potential to
foster innovation.
Investment in European countries in the development of sport can contribute to their sustainable
development and SDG achievement, going beyond the original objectives and contributing to
economic development. In particular, this process can take place by supporting the building of
social capital, including entrenching social networks and promoting associations.
Supplementary Materials:
The following are available online at http://www.mdpi.com/2071-1050/12/24/10489/s1,
Table S1. Calculation of variables based on European Social Survey, Figure S1. The impact of variables on the
anti-community index (SC—Dim1), Figure S2. The impact of variables on the index of concentration on primary
work (WP—Dim1), Figure S3. The impact of variables and values of particular countries in the PCA presented
in Figure 1. Table S2. Cluster analysis values and averages for individual countries and the resulting clusters.
Figure S4. Cluster plot for 8 indicators (SClub excluded) and 22 countries. Figure S5. Cluster plot for 7 indicators
(SA and SClub excluded) and 22 countries. Figure S6. Cluster plot for 10 indicators (additional health variable
included) and 22 countries. Figure S7. Cluster plot for 11 indicators (second principal components for social
capital and working conditions included) and 22 countries. Figure S8. Clustering dendrogram for 9 indicators
and 22 countries.
Author Contributions:
Conceptualisation, H.N., Ł.S. and E.B.; methodology, Ł.S. and D.M.; software, does not apply;
validation, Ł.S. and D.M.; formal analysis, Ł.S. and D.M.; investigation, Ł.S. and D.M.; resources, Ł.S. and D.M.;
data curation, Ł.S. and D.M.; writing—original draft preparation, H.N., Ł.S., D.M. and E.B.; writing—review and
editing, H.N., Ł.S., D.M. and E.B.; visualisation, H.N., Ł.S., D.M. and E.B.; supervision, E.B.; project administration,
E.B.; funding acquisition, E.B. All authors have read and agreed to the published version of the manuscript.
Sustainability 2020,12, 10489 13 of 16
Funding:
The study was conducted as part of the project No. 2017/27/B/HS4/00427 “The role of sports activity in
building social capital in Poland” funded by the National Science Centre, Poland, and conducted in the Warsaw
School of Economics.
Conflicts of Interest: The authors declare that they have no competing interests.
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Słowa genialnego francuskiego filozofa i matematyka Blaise’a Pascala brzmią jakże aktualnie w okresie pandemii, ograniczenia kontaktów społecznych, zagrożenia zdrowia i życia setek milionów mieszkańców naszego globu. Jednak, choć w 2020 r. uwaga całego niemal świata skoncentrowana jest na zapobieganiu i przeciwdziałaniu skutkom niezwykle groźnej epidemii, nie możemy zapomnieć, że znacznie większe zagrożenie od kilku dziesięcioleci stwarza epidemia przewlekłych chorób niezakaźnych. Choroby serca i naczyń, choroby nowotworowe, cukrzyca, choroby przewlekłe układu oddechowego i pokarmowego są od lat i zapewne pozostaną nadal najważniejszymi przyczynami umieralności we wszystkich krajach uprzemysłowionych. Niepokojąco szybko, także w naszym kraju, rośnie populacja osób z nadciśnieniem tętniczym, zaburzeniami gospodarki lipidowej i węglowodanowej, nadwagą i otyłością. Niezadowalający stan zdrowia społeczeństwa polskiego, wysoki poziom czynników ryzyka i niekorzystnych zachowań zdrowotnych, zjawisko przedwczesnej umieralności mężczyzn oraz obserwowane od kilku lat zatrzymanie korzystnego trendu wzrostu długości życia Polek i Polaków winny skłaniać do podjęcia stanowczych działań w dziedzinie zdrowia publicznego. Wśród najważniejszych czynników które mają istotny wpływ na stan zdrowia, a także długość życia należy wymienić aktywność fizyczną (AF). Systematyczna aktywność fizyczna jest bardzo silnym biologicznym stymulatorem i należy do głównych determinant zdrowia fizycznego i psychicznego człowieka. Dysponujemy obecnie bardzo przekonywującymi dowodami, że właściwa aktywność fizyczna ma kluczowe znaczenie w kształtowaniu rozwoju fizycznego i sprawności fizycznej dzieci i młodzieży, szeroko rozumianej promocji zdrowia fizycznego i psychicznego we wszystkich grupach wieku, a także w profilaktyce, leczeniu i rehabilitacji wielu chorób przewlekłych. Najważniejsze dokumenty Światowej Organizacji Zdrowia oraz Komisji Europejskiej jednoznacznie wskazują, że regularny wysiłek fizyczny jest niezbędnym elementem dla efektywnego budowania potencjału zdrowia oraz zapobiegania wielu chorobom. Dotyczy to wszystkich pokoleń, w tym także małych dzieci i osób w podeszłym wieku. Brak aktywności fizycznej powoduje nie tylko wzrost ryzyka zachorowań na choroby niezakaźne takie jak otyłość, cukrzyca, choroby układu krążenia, płuc i nowotwory, ale także pogarsza zdrowie psychiczne, zwiększa podatność na stres, utrudnia relacje społeczne. Dobroczynny wpływ aktywności fizycznej wynika także z tego, że wpływa ona korzystnie na zmianę stylu życia osób regularnie ćwiczących, tj. ich dietę i redukcję stosowania używek. Wiedza na temat korzystnych efektów AF nie jest, wszakże wiedzą powszechną wśród wszystkich grup społeczeństwa. Z drugiej strony nawet dostateczny poziom wiedzy na temat zasad zdrowego stylu życia niekoniecznie oznacza szeroką społeczną akceptację zaleceń ekspertów i praktykowanie sprzyjającej zdrowiu aktywności fizycznej w życiu codziennym. Dotyczy to społeczeństw wielu krajów europejskich, w tym także, a może nawet w sposób szczególny społeczeństwa polskiego. Na przełomie XX i XXI wieku Polacy byli w gronie najmniej aktywnych społeczności europejskich. Mimo znaczącej poprawy w okresie ostatnich dwudziestu lat, kolejne badania wskazują na niedostateczny poziom regularnej aktywności fizycznej co najmniej 50% dorosłych Polaków oraz bardzo dalekie miejsce Polski w sondażach porównujących poszczególne kraje Unii Europejskiej. Te niepokojące informacje dobrze korespondują z danymi wskazującymi na szybki wzrost częstości nadwagi i otyłości u dzieci, młodzieży oraz dorosłych Polek i Polaków. oraz wskazującymi na niepokojący spadek poziomu sprawności fizycznej dzieci i młodzieży. Niedostateczny poziom regularnej aktywności fizycznej społeczeństwa polskiego powinien skłaniać do głębokiej analizy, postawienia właściwej diagnozy i podjęcia konkretnych i skutecznych działań w celu poprawy niezadowalającej sytuacji. Eksperci związani ze środowiskiem nauk medycznych, kultury fizycznej i sportu, a także pedagodzy, demografowie i specjaliści nauk społecznych od dawna podkreślają celowość tych kroków, zwłaszcza w kontekście zjawiska starzenia się społeczeństwa polskiego. Dlatego w marcu 2019 r. Komitet Zdrowia Publicznego PAN (KZP PAN) podjął decyzję o powołaniu Komisji ds. opracowania wytycznych dotyczących poprawy aktywności fizycznej w Polsce. Komisja, która z czasem przekształciła się w liczący ponad 50 osób interdyscyplinarny Zespół Ekspertów, wytyczyła trzy bardzo ważne dla społeczeństwa polskiego zadania: 1. O pracowanie i upowszechnienie Raportu Komitetu Zdrowia Publicznego PAN na temat aktywności fizycznej Polaków; 2. 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Zum Sportengagement in Kindheit und Jugend liegen eine Reihe differenzierter Studien vor. Deutlich weniger wissen wir darüber, wie sich Sportkarrieren in dieser Lebensphase entwickeln, wodurch sie beeinflusst werden und welche Bedeutung sie für Heranwachsende haben. Denn mehrjährige längsschnittliche Studien, die das komplexe Zusammenspiel des sportlichen Engagements auf der einen Seite und verschiedener Facetten der Persönlichkeit und der Gesundheit von Heranwachsenden auf der anderen Seite entwirren können, gibt es kaum. Die vorgelegte Studie hat Kinder 10 Jahre lang über die Jugendphase hinweg bis in die Adoleszenz begleitet und ihre Sport- und Bildungskarriere beleuchtet. In diesem Kontext geht sie einer Reihe von Fragen des gegenseitigen Einflusses von Sportengagements und physischer, psychischer und sozialer Entwicklung nach. Dank ihres längsschnittlichen Designs kann die Studie empirisch die Chancen, aber auch die Grenzen aufzeigen, die dem Sport innewohnen.
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This book takes a closer look at the societal functions of sports clubs by using the broad range of empirical data of a comparative study. There is a limited amount of up-to-date knowledge on the functions of sports clubs and their potential to promote public health, social cohesion and democratic participation through volunteering and thus contribute to public welfare in European societies. Most of the existing studies are country-specific and therefore do not allow for making comparisons from a cross-national perspective. In light of this, the project ‘Social Inclusion and Volunteering in Sports Clubs in Europe’ (SIVSCE) collected, analysed and discussed comparable data and knowledge across ten European countries and disseminated this knowledge to politicians, sports professionals and sports volunteers in Europe. The SIVSCE project contains comparative data of clubs as well as of members in selected sports clubs. In each country chapter, the comparative data from the SIVSCE project is put together in a coherent way. Particularly, the data of the member survey give in-depth information about the fulfillment of the different functions of sports clubs (e.g. extension of democratic participation, social integration). Providing in-depth data related to policy issues, structure and management of clubs and individual member surveys, this book will be useful for students―particularly those in sports management programmes―as well as researchers and practitioners in social science and economics.
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How does diversity of social ties influence creativity? Moving beyond the information argument, we theorize creative self-efficacy as a motivational explanation for the relationship between diversity of social ties and creativity. We further posit tie strength as a boundary condition for this mechanism. We collected social ties data from 309 employees and creativity data from 98 direct supervisors. Results showed that diversity of social ties had a direct positive relationship with creative self-efficacy and an indirect positive relationship with employee creativity via creative self-efficacy. These direct and indirect relationships were fortified when tie strength was reinforced. We contribute to and advance theory development by identifying and testing creative self-efficacy as a motivational mechanism for diversity of social ties. We show the importance of diversity of social ties and tie strength and their synergistic role in the motivational process linking social ties to creativity.
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The paper focuses on social capital-related attitudes of members of local civic organisations, particularly of sports club members. In line with Robert Putnam’s social capital argument, three questions are addressed: (1) Do social capital-related attitudes differ between sports club members and those among the German population who do not belong to a voluntary association? (2) Following a typology of associations, the question arises to what extent social capital-related attitudes vary between members of sports clubs and members of other voluntary associations? (3) And finally, are there differences in social capital-related attitudes of sports club members between 2001 and 2017/2018? Based on representative survey data from Germany collected in 2001 and 2017/2018, the analyses buttress some, but not all of the initial assumptions: in 2001 sports club members expressed more sociable orientations and lower levels of individualism compared to non-members. In 2017/2018, however, these effects had weakened or vanished. Hardly any clues can be found in support of the notion that sports club members are ‘better democrats’ than non-members. These results are discussed against the backdrop of alleged tendencies of professionalisation and consumer-orientation in sports clubs and raise the question if the social capital-producing capacity of sports clubs has eventually attenuated.
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Gyms that at the same time offer an environment for individualized training and social encounters are today attractive to a broad and culturally diverse group of people. The theoretical approach of ‘established’ and ‘outsiders’ from Elias and Scotson (2008 [1965]) and the ethnographic field work of this study show that in a gym, cultural differences play out in both exclusionary, rejecting behaviours and a gym-specific habitual principle of mutual help in sport activities that binds members and transcends cultural differences. Gym attendance and participation can enable intercultural interaction, strengthen mutual acceptance and support adaptation processes. Nevertheless, the potential of this interaction depends on gym-goers’ personal motives, their training habits and a gym’s active cultural diversity management. For full-text use: https://www.tandfonline.com/eprint/niAswKN4aiktMYMQGx9C/full?target=10.1080/16138171.2019.1607057 (50 free online copies)