**2. Knowledge and cultural heritage**

Private funding/sponsorship has known different dimensions over time, so some

During communism, the interest of the government for culture has known both favorable and foul times. The public identity was shaped according to the interests of the parties in power, and the works of art were preserved or destroyed [1] according to the personal acceptance of rulers. On the one hand, appreciated works of art considered valuable for the party were preserved and exposed in museums and in personal collections. On the other hand, the period produced losses and destruction of those cultural elements considered dangerous by the party.

After 1989, after the communist period ended, many central and eastern European governments reformed the budgetary allocations by diminishing the funds for culture to the favor of other destinations. The governance interest focused predominantly on supporting other budgetary segments, leaving the financial support for cultural heritage mostly in the care of the private sector. Public/private partnerships have begun to develop with the aim to sustain the cultural sphere. Countries like Romania, Bulgaria, Hungary, and Slovenia have adopted regulations granting tax

In the Western European side, the cult of donations/maecenas and sponsorship to support culture is much more developed. In Britain, for example, most of the museums are constituted as Charities (a legal form suitable for encouraging donations) [18]. Also, in countries like Denmark, Italy, France, and Spain, government initiatives aim to foster the development of a tradition in sponsorship; thus, the

The EU nations have developed a system of identification of potential threats that may harm the EU heritage, and, in accordance, appropriate policies and recommendations have been undertaken in order to mitigate the identified risks. Such potential risks are flood hazards, wars, earthquakes, pollution, uncontrolled urban-

The initiative is called Europa Nostra, it was launched in 2013, and it is funded by the European Investment Bank Institute and the Council of Europe Development

• The Constanta Casino—the identified problems are concerned with corrosion and rusting, salty moisture that heavily affects wooden elements, mold, freezing, and temperature that constantly affects the building's structure. Overall, the state is mainly held responsible for the situation because of lack of interest, failure in and prolonged public procurements, and abandonment.

• The wooden churches in Southern Transylvania and Northern Oltenia approximately 60 such churches are being followed as to be restored from

• Rosia Montana Mining Landscape in Transylvania—the site houses Roman edifices and roads along with small towns and villages, nestled in the

mountains. The threat comes from a large-scale mining project which would have a major serious impact on both the natural and cultural heritages of the

Romania also appears on the Europa Nostra list, with three objectives:

facilities to promote the private support of the cultural sector.

banks became an active sponsor of regional cultural spending.

**1.3 Shortlist of heritage protection programs**

ization, and unreported tourists.

Bank [19].

decay.

**296**

place (**Figure 6**).

states encourage and hold complex legal leverage in this direction compared to others. The succession of political regimes and the degree of economic development

seem to have deep roots in this regard.

*Heritage*

Cultural heritage represents a particular dimension in the life of a community. It sums up the wisdom of the past [11], gives confidence and recognition of history, and shapes the minds of future generations (**Figure 7**).

Research in cultural statistics has proved to be a real challenge. Limitations like the scarce number of statistical data and the usage of different reference points for reporting create serious difficulties in analyzing similar data between countries over a longer period of time. Heritage conservation projects are instrumented differently according to the governments' perception [20], so the reported indicators are not calculated on the basis of the same defining principles.

For many, culture is associated with arts and entertainment. The potential that culture has to support the economy, primarily because of the boost it may incur on

**Figure 7.** *Old Neolithic statues "the Thinker of Hamangia" and "the Sitting Woman," in the Museum of National History and Archeological of Constanta.*

tourism, is not always acknowledged and appreciated. Culture is often perceived as belonging to a secondary plan of economic growth, thus being considered more an expense for budget than as an investment for regional benefits. The situation is somewhat applicable to Romania, taking into account the limited funds allocated to culture related to the annual budget of less than 1% of GDP.

participants at the night of museums, which is an event meant to raise the

*Public Governance and Cultural Heritage: Exploring the Links between Culture and Social…*

• Number of visitor to cinemas—the indicator is also calculated on the basis of the number of tickets sold for access to movies in cinemas (CINEMA\_V\_No).

borrowed at least one book during the year, for personal reading (LIBR\_R\_No).

• The number of cinematic shows—calculated as sum of projections of films in

• Number of persons graduated from high schools/vocational schools—includes graduates of secondary schools with or without a diploma, as well as young graduates of a postsecondary school, masters schools, or special postsecondary

• Number of people with university studies—includes the number of people graduating from long-term higher education, inclusive with a master's or

• The active population—represents the number of working people (ACTIVE\_No).

• Number of unemployed people—represents people who are capable to work, are looking for a job, and who do not have a current job (UNEMP\_No).

• Number of retired persons—is the number of beneficiaries of social pensions in

The dynamics of interest in cultural heritage during that time can be observed based on the evolution of the number of visitors in museums and cinemas or readers

Available data is concentrated on the quantitative number of visitors but not on the quantified value of the tickets sold. Information on the value of ticket sales is significant for the own budgets of the cultural institutions but it is not available for

The absence of centralized data on the amount of value brought by visitors to culture institutions reveals a first limitation in study analysis. Information on the amount of receipts could, for example, provide an indication of the efficiency of governance as for the measures taken by the management to attract a greater number of visitors in terms of increasing the institutional own budget. Thus, the absence of data strengthens the idea that the culture sector is not regarded by the

The dynamic analysis of the chosen indicators according to **Table 1** indicates

The number of visitors to museums shows the evolution over time of the visitor's interest towards the exhibits presented in the museums in Romania. Although until 2010 the number of visitors in museums has an oscillating evolution, starting with the year 2011, an increase of interest for this sector can be observed. An explanation for the ascending trend of interest in museums may be the input of the event "the Night of Museums," which is held in May every year and when visitors have free access to museum exhibits. Also, school programs like "a different week," when students in schools are encouraged to organize group visits in museums, increase

certain trends in terms of "consumption of cultural products" in Romania.

governance as a significant point in the economic perspective.

• Number of readers in libraries—represents the number of people who

general interest towards arts and culture (MUSEUM\_V\_No).

cinemas during 1 year (CINEMA\_Show).

*DOI: http://dx.doi.org/10.5772/intechopen.90793*

postgraduate diploma (UNIV\_No).

the public system (RETR\_No).

public knowledge or research.

the annual visitor number in museums.

schools (HS\_No).

in libraries.

**299**

Based on these considerations, this chapter focuses mainly on the analysis of cultural indicators in Romania. We are thus trying to obtain a trustworthy comparable statistical reference, which would allow to draw conclusions on the influences of cultural heritage on people.

This study is intended to be an attempt to capture and quantify the influences and interdependencies between cultural heritage and the Romanian people stratified on several categories of occupation and activity. The analysis is customized with the scope of investigating the correlation between heritage and various categories of citizens, relevant to the analysis being the level of education, work capacity, unemployment, and the retired persons.

## **3. Research methodology**

The complexity of data defining the cultural field, as well as their impact on people, may present difficulties in calculating the links and causalities. Also, analyzed data can present strong correlations that would diminish the significance of the results. The solution in this situation is represented by the econometric modeling.

The PCA method is a tool to explore the correlation and interdependence of statistical data, as well as to create predictive models.

In this chapter, the principal component analysis (PCA) allows the transformation of the initial space of data into a new space of reduced size while maximizing the amount of information retained from the original space. In the new space created (called factor space), the initial variables can be designed, and the factor axes are determined by extracting the main components [21]. The main components are linear combinations of the initial variables, capable to condense the information of the original variables and to transpose it into a mathematical formula:

$$\ast x\_{j} = \alpha\_{1}^{j} \ast \mathcal{y}\_{1} + \alpha\_{2}^{j} \ast \mathcal{y}\_{2} + \dots + \alpha\_{n}^{j} \ast \mathcal{y}\_{n} = \sum\_{j=1}^{n} \alpha\_{i}^{j} \ast \mathcal{y}\_{i}$$

where


#### **4. Results and discussions**

The indicators analyzed in order to assess the impact of cultural heritage on the Romanian people, based on available statistical data during 1994–2018, are:

• Number of visitors to museums and public collections—calculated nationally based on the number of sold tickets. This indicator includes also the number of participants at the night of museums, which is an event meant to raise the general interest towards arts and culture (MUSEUM\_V\_No).


The dynamics of interest in cultural heritage during that time can be observed based on the evolution of the number of visitors in museums and cinemas or readers in libraries.

Available data is concentrated on the quantitative number of visitors but not on the quantified value of the tickets sold. Information on the value of ticket sales is significant for the own budgets of the cultural institutions but it is not available for public knowledge or research.

The absence of centralized data on the amount of value brought by visitors to culture institutions reveals a first limitation in study analysis. Information on the amount of receipts could, for example, provide an indication of the efficiency of governance as for the measures taken by the management to attract a greater number of visitors in terms of increasing the institutional own budget. Thus, the absence of data strengthens the idea that the culture sector is not regarded by the governance as a significant point in the economic perspective.

The dynamic analysis of the chosen indicators according to **Table 1** indicates certain trends in terms of "consumption of cultural products" in Romania.

The number of visitors to museums shows the evolution over time of the visitor's interest towards the exhibits presented in the museums in Romania. Although until 2010 the number of visitors in museums has an oscillating evolution, starting with the year 2011, an increase of interest for this sector can be observed. An explanation for the ascending trend of interest in museums may be the input of the event "the Night of Museums," which is held in May every year and when visitors have free access to museum exhibits. Also, school programs like "a different week," when students in schools are encouraged to organize group visits in museums, increase the annual visitor number in museums.

tourism, is not always acknowledged and appreciated. Culture is often perceived as belonging to a secondary plan of economic growth, thus being considered more an expense for budget than as an investment for regional benefits. The situation is somewhat applicable to Romania, taking into account the limited funds allocated to

Based on these considerations, this chapter focuses mainly on the analysis of cultural indicators in Romania. We are thus trying to obtain a trustworthy comparable statistical reference, which would allow to draw conclusions on the influences

This study is intended to be an attempt to capture and quantify the influences and interdependencies between cultural heritage and the Romanian people stratified on several categories of occupation and activity. The analysis is customized with the scope of investigating the correlation between heritage and various categories of citizens, relevant to the analysis being the level of education, work

The complexity of data defining the cultural field, as well as their impact on people, may present difficulties in calculating the links and causalities. Also, analyzed data can present strong correlations that would diminish the significance of the results. The solution in this situation is represented by the econometric modeling. The PCA method is a tool to explore the correlation and interdependence of

In this chapter, the principal component analysis (PCA) allows the transformation of the initial space of data into a new space of reduced size while maximizing the amount of information retained from the original space. In the new space created (called factor space), the initial variables can be designed, and the factor axes are determined by extracting the main components [21]. The main components are linear combinations of the initial variables, capable to condense the information of the original variables and to transpose it into a mathematical formula:

<sup>2</sup> <sup>∗</sup> *<sup>y</sup>*<sup>2</sup> <sup>þ</sup> … <sup>þ</sup> *<sup>α</sup> <sup>j</sup>*

• *α <sup>j</sup>* are the vectors that define the standardized linear combinations

Romanian people, based on available statistical data during 1994–2018, are:

The indicators analyzed in order to assess the impact of cultural heritage on the

• Number of visitors to museums and public collections—calculated nationally based on the number of sold tickets. This indicator includes also the number of

*<sup>n</sup>* <sup>∗</sup> *yn* <sup>¼</sup> <sup>X</sup>*<sup>n</sup>*

*j*¼1 *α j <sup>i</sup>* ∗ *yi*

culture related to the annual budget of less than 1% of GDP.

capacity, unemployment, and the retired persons.

statistical data, as well as to create predictive models.

*xj* <sup>¼</sup> *<sup>α</sup> <sup>j</sup>*

• *xj* is the principal component *j*

**4. Results and discussions**

where

**298**

<sup>1</sup> <sup>∗</sup> *<sup>y</sup>*<sup>1</sup> <sup>þ</sup> *<sup>α</sup> <sup>j</sup>*

• *yi* are the original variables, where *i* = 1, 2, … , *n*

of cultural heritage on people.

*Heritage*

**3. Research methodology**

#### **Table 1.**

*Cultural heritage indicators in Romania.*

An interesting trajectory is revealed also for the number of readers in bookstores comparative with the number of visitors in cinemas. By the year 2008, in Romania the number of people who borrowed books from libraries was superior to the number of visitors in cinemas. The data analyzed indicate the year 2008 as the period when the two indicators were equalized and presented the moment of decline of interest in the libraries and also the increase of the number of cinephiles.

level of the number of people analyzed, while the number of people with university

*Public Governance and Cultural Heritage: Exploring the Links between Culture and Social…*

In order to analyze the interest of citizens for cultural heritage in Romania, we used an econometric model based on principal component model. For the first stage, the average and the standard deviation for each variable was calculated

The high results obtained for standard deviation show that the variables taken for analysis are spread out and far from the mean or average. In other words, the initial indicators are very different from each other; they form a space with widely spread data points around the mean, where the calculation of causal dependencies

MUSEUM\_V\_No 10829214.00 2278168.062 CINEMA\_V\_No 5385778.92 1518761.996 LIBR\_R\_No 4933429.24 1033987.182 CINEMA\_Show 289554.48 162522.019 HS\_No 930147.72 117689.344 UNIV\_No 534974.80 178519.195 ACTIVE\_No 9276260.00 619501.210 UNEMP\_No 650368.00 264544.151 RETR\_No 5675760.00 397809.448

**Mean Std. Deviation**

studies occupies a small number of the population's total number analyzed.

would be very complex and very difficult to determine.

*The mean and standard deviation calculated for each variable.*

*Romanian citizens categorized by education and occupation.*

*DOI: http://dx.doi.org/10.5772/intechopen.90793*

(**Table 3**).

**Table 3.**

**301**

*Source: INSSE.*

**Table 2.**

Although the year 2008 marks the global economic crisis, when it comes to culture, the evolution of indicators that can quantify the interest for books or for movies indicates an interesting phenomenon. The audience went more towards cinemas, and the interest for libraries started a sustained decline trajectory. A possible explanation in this regard is that digitalization and computer-wide access to information sources decreased public interest for libraries, while the increasingly varied cinematographic productions and the construction of malls with included cinemas contributed to raise the interest for cinematographic productions.

The analysis was also concerned with the number of cinematographic performances broadcast. The interest was whether the visitor number could be determined by significant variations in the number of performances visited. The data indicate that the number of performances was relatively linear over time, so that it did not represent a factor of influence on the number of visitors in cinemas.

The assessment of cultural interest on Romanian population is based on the indicators of population categorized by education (people that graduated high school or some form of professional school and persons with university studies) and occupation (active population, unemployed, and retired persons).

**Table 2** reflects numerically and in evolution the indicators chosen for analysis. The graphical representation reveals an interesting evolution of the number of active persons with a general decline trend, which can be explained mostly by migrating labor force abroad. The number of retired persons occupies a significant

*Public Governance and Cultural Heritage: Exploring the Links between Culture and Social… DOI: http://dx.doi.org/10.5772/intechopen.90793*

#### **Table 2.**

An interesting trajectory is revealed also for the number of readers in bookstores comparative with the number of visitors in cinemas. By the year 2008, in Romania the number of people who borrowed books from libraries was superior to the number of visitors in cinemas. The data analyzed indicate the year 2008 as the period when the two indicators were equalized and presented the moment of decline of interest in the libraries and also the increase of the number of cinephiles. Although the year 2008 marks the global economic crisis, when it comes to culture, the evolution of indicators that can quantify the interest for books or for movies indicates an interesting phenomenon. The audience went more towards cinemas, and the interest for libraries started a sustained decline trajectory. A possible explanation in this regard is that digitalization and computer-wide access to information sources decreased public interest for libraries, while the increasingly varied cinematographic productions and the construction of malls with included cinemas contributed to raise the interest for cinematographic productions.

*Source: INSSE.*

*Cultural heritage indicators in Romania.*

**Table 1.**

*Heritage*

**300**

The analysis was also concerned with the number of cinematographic performances broadcast. The interest was whether the visitor number could be determined by significant variations in the number of performances visited. The data indicate that the number of performances was relatively linear over time, so that it did not represent a factor of influence on the number of visitors in cinemas. The assessment of cultural interest on Romanian population is based on the indicators of population categorized by education (people that graduated high school or some form of professional school and persons with university studies) and

**Table 2** reflects numerically and in evolution the indicators chosen for analysis.

The graphical representation reveals an interesting evolution of the number of active persons with a general decline trend, which can be explained mostly by migrating labor force abroad. The number of retired persons occupies a significant

occupation (active population, unemployed, and retired persons).

*Romanian citizens categorized by education and occupation.*

level of the number of people analyzed, while the number of people with university studies occupies a small number of the population's total number analyzed.

In order to analyze the interest of citizens for cultural heritage in Romania, we used an econometric model based on principal component model. For the first stage, the average and the standard deviation for each variable was calculated (**Table 3**).

The high results obtained for standard deviation show that the variables taken for analysis are spread out and far from the mean or average. In other words, the initial indicators are very different from each other; they form a space with widely spread data points around the mean, where the calculation of causal dependencies would be very complex and very difficult to determine.


**Table 3.**

*The mean and standard deviation calculated for each variable.*


**Table 4.** *The correlation*

 *matrix.*

Interdependencies between the analyzed variables can be seen with the correlation matrix. Bold values are considered insignificant and are not taken into

*Public Governance and Cultural Heritage: Exploring the Links between Culture and Social…*

According to the correlation matrix, the strong negative relationship between the visitor number in museums and the number of high school graduates and vocational schools (0.713) indicates that an increase in the number of high school graduates and schools determines a decrease in number of visitors to museums. Professionalization can cause a decrease in the number of visitors in museums. The situation can be explained by the fact that many visitors in museums are students, who have not yet completed their studies. So, the assumption that a great number of the visitors in museums are pupils, and their visits are determined by programs School, seems to be certified by current results. The termination of secondary or vocational education indicates a decrease in interest in cinema time (0.670), perhaps for more time needed for job search or for more careful spending behaviors. A similar strong relationship exists between the number of visitors in museums and the active population (0.588) or the number of unemployed (0.643), which can be explained on account of the fact that an increase in the number of active persons presents a lower interest or allocate less time to visits to the museum. Also, active people seem to give a lower interest to visits to the cinema (0.539), but instead it is likely to be more interested in culturalization by access to literature and the loan of books from libraries (+0.607). On the contrary, an interest in the loan of books in libraries appears to be represented by unemployed people looking for a job (+0.781), a situation that can be explained in the practice by the need for informa-

As for the number of retired persons, their interest seems to be rather oriented to reading (+0.597) rather than to visits to museums or cinemas, where statistical

The number of cinema performances appears to be positively influenced by the visitor number at the museums (+0.594) and conversely proportionately by the number of people interested in reading. Thus, the link between the need for enter-

The relevance of the sampling and the testing of the independence hypothesis

(**Table 5**). The result of KMO = 0.658 is significant for the application of the model [22]. A larger dataset would likely lead to a better KMO result of the test, but precisely the limited resources of credible information in the sphere of cultural heritage are one of the obstacles to the study. The significance of the model obtained using Bartlett's test of sphericity (Sig. = 0.000 < 0.05) indicates a probability of 95% as between the statistical variables analyzed there are significant links. Values greater than 0.8 in the correlation matrix indicate too high correlations between the analyzed variables, when some data may become redundant and may diminish the significance of the results. Thus, the application of the PCA method eliminates the risk of multicollinearity and also accomplishes the purpose of

Kaiser-Meyer-Olkin Measure of sampling adequacy 0.658 Bartlett's test of sphericity Approx. chi-square 263.413

> Df 36 Sig. 0.000

have been verified by the output of Kaiser-Meyer-Olkin and Bartlett's test

analysis (**Table 4**).

*DOI: http://dx.doi.org/10.5772/intechopen.90793*

tion and professionalization.

dimensionality reduction.

**Table 5.**

**303**

*KMO and Bartlett's test.*

analysis does not show any significant correlations.

tainment and the creation of leisure alternatives is tested.

*Public Governance and Cultural Heritage: Exploring the Links between Culture and Social… DOI: http://dx.doi.org/10.5772/intechopen.90793*

Interdependencies between the analyzed variables can be seen with the correlation matrix. Bold values are considered insignificant and are not taken into analysis (**Table 4**).

According to the correlation matrix, the strong negative relationship between the visitor number in museums and the number of high school graduates and vocational schools (0.713) indicates that an increase in the number of high school graduates and schools determines a decrease in number of visitors to museums. Professionalization can cause a decrease in the number of visitors in museums. The situation can be explained by the fact that many visitors in museums are students, who have not yet completed their studies. So, the assumption that a great number of the visitors in museums are pupils, and their visits are determined by programs School, seems to be certified by current results. The termination of secondary or vocational education indicates a decrease in interest in cinema time (0.670), perhaps for more time needed for job search or for more careful spending behaviors.

A similar strong relationship exists between the number of visitors in museums and the active population (0.588) or the number of unemployed (0.643), which can be explained on account of the fact that an increase in the number of active persons presents a lower interest or allocate less time to visits to the museum. Also, active people seem to give a lower interest to visits to the cinema (0.539), but instead it is likely to be more interested in culturalization by access to literature and the loan of books from libraries (+0.607). On the contrary, an interest in the loan of books in libraries appears to be represented by unemployed people looking for a job (+0.781), a situation that can be explained in the practice by the need for information and professionalization.

As for the number of retired persons, their interest seems to be rather oriented to reading (+0.597) rather than to visits to museums or cinemas, where statistical analysis does not show any significant correlations.

The number of cinema performances appears to be positively influenced by the visitor number at the museums (+0.594) and conversely proportionately by the number of people interested in reading. Thus, the link between the need for entertainment and the creation of leisure alternatives is tested.

The relevance of the sampling and the testing of the independence hypothesis have been verified by the output of Kaiser-Meyer-Olkin and Bartlett's test (**Table 5**). The result of KMO = 0.658 is significant for the application of the model [22]. A larger dataset would likely lead to a better KMO result of the test, but precisely the limited resources of credible information in the sphere of cultural heritage are one of the obstacles to the study. The significance of the model obtained using Bartlett's test of sphericity (Sig. = 0.000 < 0.05) indicates a probability of 95% as between the statistical variables analyzed there are significant links.

Values greater than 0.8 in the correlation matrix indicate too high correlations between the analyzed variables, when some data may become redundant and may diminish the significance of the results. Thus, the application of the PCA method eliminates the risk of multicollinearity and also accomplishes the purpose of dimensionality reduction.


**Table 5.** *KMO and Bartlett's test.*

**Correlation**

**302**

MUSEUM\_V\_No

CINEMA\_V\_No

LIBR\_R\_No

CINEMA\_Show

HS\_No

UNIV\_No

ACTIVE\_No

UNEMP\_No

RETR\_No

**Table 4.** *The correlation*

 *matrix.*

**0.375** 0.696

0.594 0.713

**0.043**

0.588

0.643

0.265

0.250

0.597

0.788

**0.486**

0.550

**0.227**

**0.173**

1.000

**0.497**

0.781

**0.250**

 **0.474**

**0.370**

0.820

1.000

0.539

0.607

**0.050**

0.509

**0.452**

1.000

**0.022**

**0.021**

0.714

**0.335**

1.000

0.670

0.816

0.776

 1.000

**0.426**

0.661

1.000

0.665

1.000

1.000

1.000

**MUSEUM\_V\_No**

**CINEMA\_V\_No**

**LIBR\_R\_No**

**CINEMA\_Show**

 **HS\_No**

 **UNIV\_No**

**ACTIVE\_No**

**UNEMP\_No**

 **RETR\_No**

*Heritage*

The extraction of communalities represents estimates of the variation in each variable contained in the calculated components. The large values of communalities presented in the column "Extraction" indicate that the extracted components represent the information contained in the initial variables well. The situation is due to the fact that there is a connection between the forms of access of cultural heritage (museums, cinemas, bookstores) and the population categorized by education and occupation (**Table 6**).

In the next stage of PCA method, the eigenvalues of the correlation matrix are the variables of the main components. The eigenvalues greater than 1 are the only ones retained in the analysis because they have a higher variance than the original standardized variables.

According to **Table 7**, the correlation matrix has only two eigenvalues greater than 1 that correspond to the inertia explained by the factorial axes. Therefore, the first factorial shaft explains 52,968% of the total variation of the variable cloud, and the first two factorial axes explain 80,853% of the total variation. The percentage determined by the first two eigenvalues determines the graphical representation of the factorial axes in connection with the projection of the puncture cloud, as observed in **Figure 8**.


#### **Table 6.**

*Table of communalities.*


**Figure 9** is a graphic representation of eigenvalues in correspondence with the number of components. Starting with the eigenvalue corresponding to component 3, the bonding line becomes almost flat, indicating that starting with component 3, each successive component accounts for less and less in the explanation of variance.

The component matrix in **Table 8** shows the correlation between variables and the two components extracted with a value greater than 1. The obtained values

Thus, the PCA method redistributes the variance on the first two extracted

*Correlation between the extracted principal components and the initial variables.*

*Public Governance and Cultural Heritage: Exploring the Links between Culture and Social…*

*DOI: http://dx.doi.org/10.5772/intechopen.90793*

components.

**305**

**Figure 9.**

*Scree plot graph—variation of eigenvalues.*

**Figure 8.**

#### **Table 7.** *Variance—the eigenvalues greater than 1.*

*Public Governance and Cultural Heritage: Exploring the Links between Culture and Social… DOI: http://dx.doi.org/10.5772/intechopen.90793*

**Figure 8.** *Correlation between the extracted principal components and the initial variables.*

**Figure 9.** *Scree plot graph—variation of eigenvalues.*

**Figure 9** is a graphic representation of eigenvalues in correspondence with the number of components. Starting with the eigenvalue corresponding to component 3, the bonding line becomes almost flat, indicating that starting with component 3, each successive component accounts for less and less in the explanation of variance. Thus, the PCA method redistributes the variance on the first two extracted components.

The component matrix in **Table 8** shows the correlation between variables and the two components extracted with a value greater than 1. The obtained values

The extraction of communalities represents estimates of the variation in each variable contained in the calculated components. The large values of communalities presented in the column "Extraction" indicate that the extracted components represent the information contained in the initial variables well. The situation is due to the fact that there is a connection between the forms of access of cultural heritage (museums, cinemas, bookstores) and the population categorized by education and

In the next stage of PCA method, the eigenvalues of the correlation matrix are the variables of the main components. The eigenvalues greater than 1 are the only ones retained in the analysis because they have a higher variance than the original

According to **Table 7**, the correlation matrix has only two eigenvalues greater than 1 that correspond to the inertia explained by the factorial axes. Therefore, the first factorial shaft explains 52,968% of the total variation of the variable cloud, and the first two factorial axes explain 80,853% of the total variation. The percentage determined by the first two eigenvalues determines the graphical representation of the factorial axes in connection with the projection of the puncture cloud, as

MUSEUM\_V\_No 1.000 0.666 CINEMA\_V\_No 1.000 0.541 LIBR\_R\_No 1.000 0.910 CINEMA\_Show 1.000 0.964 HS\_No 1.000 0.849 UNIV\_No 1.000 0.849 ACTIVE\_No 1.000 0.914 UNEMP\_No 1.000 0.834 RETR\_No 1.000 0.750

**Component Initial eigenvalues**

 4.767 52.968 52.968 2.510 27.886 80.853 0.660 7.330 88.184 0.615 6.831 95.015 0.206 2.291 97.306 0.168 1.870 99.176 0.033 0.367 99.543 0.027 0.300 99.843 0.014 0.157 100.000

**Initial Extraction**

**Eigenvalue Total % of variance Cumulative %**

occupation (**Table 6**).

*Heritage*

standardized variables.

observed in **Figure 8**.

**Table 6.**

**Table 7.**

**304**

*Variance—the eigenvalues greater than 1.*

*Table of communalities.*


old/new exhibits in museums as an expression of social behavior towards culture reveals the value of heritage as an expression of identity knowledge and vision. Corporate governance has to comply with requirements regarding the publicity of financial and nonfinancial statements on cultural heritage and statistical databases concerned with arts transactions, as instruments to prevent frauds and forgeries. The outcomes of greater governance publicity in cultural heritage reside in matters like trust, state legitimacy, social participation, and discouragement of

*Public Governance and Cultural Heritage: Exploring the Links between Culture and Social…*

The relationship between knowledge and transparency sets the incentives for governance efficiency and cultural heritage protection. With a better understanding of public managerial decisions comes cultural value acknowledgement and the

This chapter was supported by a grant of the Romanian Ministery of Research and Innovation, CCCDI – UEFISCDI, project number PN-III-P1-1.2-PCCDI-2017-

\*, Marioara Mirea<sup>2</sup> and Cosmin Susu<sup>2</sup>

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

1 Bucharest University of Economics Studies, Bucharest, Romania

\*Address all correspondence to: consultant.munteanu@gmail.com

2 Ovidius University of Constanta, Romania

provided the original work is properly cited.

0476/51-PCCDI/2018, within PNCDI III, ACRONIM: ARHEOCONS.

corruption.

improvement of protection measures.

*DOI: http://dx.doi.org/10.5772/intechopen.90793*

**Acknowledgements**

**Author details**

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Ionela Munteanu Florea<sup>1</sup>

#### **Table 8.**

*The component matrix.*

indicate that all variables contributed to the formation of the first factorial shaft, while the variable "number of readers in libraries" had an insignificant contribution to the formation of the second factorial axis.

The scree plot in rotated space reiterates graphic values determined in the correlation matrix and places in space the variables chosen against the formed factorial axes.
