The impact of social capital, human capital and knowledge sharing activity on school performance indicators: case of Saint-Petersburg
Social and human capital as a performance impactful factor. Measurement of school performance. The definition of concepts and measurement levels. Significance of educational organization type, correlation of the factors, compilation of the matrix.
| Рубрика | Менеджмент и трудовые отношения |
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| Язык | английский |
| Дата добавления | 01.12.2019 |
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The impact of social capital, human capital and knowledge sharing activity on school performance indicators: case of Saint-Petersburg
Introduction
social human capital school
A variety of intangible forms of capital have repeatedly proved its impact on organizational performance. For example, social capital as well as human capital are considered by many authors as company's competitive advantages (Chuang, Chen & Lin, 2016; Hatch & Dyer, 2004; Hoelscher, Hoffman & Dawley, 2005; Lawler, 2009; Liu, Horng, Chou, Huang & Chang, 2018). In recent decades, a certain degree of academic attention was received by another form of capital, which has many times appeared during discussion of both social capital (Inkpen & Tsang, 2005; Morel & Coburn, 2019; Sechi, Borri, De Lucia & Celmins, 2011; Wei, Zheng & Zhang, 2011) and human capital (Hsu, 2008; Kim, Atwater, Patel & Smither, 2016; Shih, 2010). This specific type of capital is knowledge, which along with its creation and sharing processes presents crucial value while developing competitive advantages (Lin, & Chen, 2008; Nonaka & Takeuchi, 1991). The importance of knowledge sharing as a field at the junction of social and human capital (Helms, Ignacio, Brinkkemper & Zonneveld, 2010) is associated with acquiring insights in order to produce new innovative solutions and improve organizations' performance indicators (Ahmad, 2017). Similar to social capital and human capital, intensive knowledge sharing has been examined to have an impact on the organizational success. Despite proved positive impact possessed by human capital, social capital and knowledge sharing (Chuang, et al., 2016; Hatch & Dyer, 2004; Lee, Lee & Kang, 2005), there is a scarcity of research focusing on the impact these factors may have on educational institutions. The least explored context in this regard is associated with primary and secondary education and preschool institutions, notwithstanding the fact that knowledge sharing, development of human and social capital represent major aspects of any educational institution's mission. Thus, low level of awareness concerning how these factors contribute to mission of educational organization and its effect on the performance of institution does not allow the latter to unleash its potential, which poses a significant problem.
Subsequently, the main aim of the research is to determine the effect human capital, social capital and knowledge sharing impose on results of educational organization performance. In order to achieve the goal, the paper settles the following research question: How does social capital, human capital and knowledge sharing affect the performance of primary and secondary education organizations (schools) of Saint-Petersburg?
In order to answer established research question, the study carries out the following tasks:
a) Determine the theoretical framework for human capital, social capital, knowledge sharing and educational organization performance within which research will be conducted.
b) Establish methodology enabling measurement of the above named concepts and assessment of the impact factor (social capital, human capital and knowledge sharing) may have on educational organization (school) performance.
c) Collect and process empirical data regarding educational schools' capital in Saint-Petersburg.
d) Elaborate school's interaction networks through educational activities for future knowledge sharing analysis.
e) Design inferential models explaining and evaluating factors' influence.
f) Based on the results, compare those with previous findings and develop a list of factor crucial for educational institutions covering human capital, social capital, knowledge sharing effect, providing both theoretical and practical contribution of the study.
Subsequently, the paper is structured in accordance to a succeeding scheme: following the introduction, the first part settles the theoretical framework of the thesis and provides review of previous studies on the topic; then, the second section establishes the research statement of the paper; the third part considers the research design and the methodology accompanied by description of data sources, sample and tools; the fourth part reveals results of the research, while the fifth focuses on comparison of those to previous findings and the discussion. The last section is devoted to conclusion that might be derived and followed by list of references and appendices presented at the end of the paper.
Summing up, the significance of this paper should be considered from two sides. From an academic point of view, this work fills in the gap in the study of social capital, human capital, knowledge sharing and educational organization performance indicators. From a managerial output, this study provides an understanding of how social capital, human capital and knowledge sharing influence the educational organizations performance and indicates the factor educational organization should take into account in order to reach higher performance rates.
1. Theoretical foundation
The theoretical foundation section presents the review of key concepts of the current study such as social capital, human capital, knowledge sharing and educational organization (schools) performance. Thus, chapter contains several parts: first three subsections are dedicated to the examined factors (social capital, human capital and knowledge sharing, respectively) and their influence on organizational performance; then, social capital and human capital are revised in the context of influence possessed on school's performance, the measurement approaches to which are given in the last subsection of the theoretical foundation.
1.1 Social capital as a performance impactful factor
Coleman (1988a) and Putnam (1993) were among the first who thoroughly examined the definition of social capital, they considered SC as an investment in social structures or its elements in anticipation for positive returns, which might be in form of economic or noneconomic outcomes (Coleman, 1988b), brokerage opportunities (Burt, 1997), or even market place advantage (Lil & Smith, 2001). Despite the fact that definition of social capital was constantly transformed by scholars to highlight those features of essential value for specific research, the core remained the same as the unique characteristics of social capital reflected in its original terminology were transferred through all of the interpretations (Adler & Kwon, 2002): social relations facilitating certain action among actors through a social structure (Coleman, 1988b). The differences in emphasis placed by each of the definitions laid the foundation for the classification framework based on forms of capital, elements in the focus, scope of the research and dimension.
The main three forms of social capital were identified by Coleman (1988a, 1988b) in his early articles devoted to the subject. The list consisted of obligations and expectations, information channels and social norms. In terms of social capital, obligations and expectations are tightly connected with overall trustworthiness of a social environment and an extent to which obligations and expectations are carried out; information channels are social relations structure that serves an information source and, thus, facilitate action; in contrast, norms and sanctions are aimed at both facilitating and constraining activities of social capital formation (Coleman, 1988b). With the development of both social capital phenomenon and academic field devoted to its examination, there were drawn other forms which social capital can take, e.g. trust and reciprocity (Robison, Schmid & Siles, 1999). Nevertheless, academicians have not reached consensus upon which particular forms should or should not be distinguished as forms of social capital (Robison et al., 1999).
Notwithstanding growing number of definitions, there has been done several attempts to classify attributes of social capital into categories which resulted in one of the most common academic typologies including three dimensions which are structural, relational and cognitive (Chow & Chan, 2008). First group involves the structure of social relations primarily in forms of networks as it is aimed at identification of interconnections measured via network density, connectivity and hierarchy. Second category is derived from evolved discussion of social capital forms and devoted to qualitative assessment of relationships and trust between people through norms, expectation and obligations, identification awareness toward collective goals. Third dimension focuses on understanding between actors of the community and what resources facilitate the sharing of both culture and knowledge (Nahapiet & Ghoshal, 1998).
Robison et al. (1999) also tried to summarize existing definitions of social capital and researches on the topic. Authors distinguished that various interpretations of social capital were focused on different structural elements and suggested three groups to which definitions of social capital can be attributed: those that dwell upon the substance of social capital, its sources or influence it might have (Robison et al., 1999). Even though the classification is not widely used, it has systematized existing studies and allowed to identify which research directions lack investigation in area of social capital.
Along with the focus of the research, the scope of investigation is also a crucial factor for social capital analyses interpretations (Adler & Kwon, 2002). Based on this factor, three types of approaches might be defined:
a) Internal or Bonding concentrated on the social network between actors within an existing formal or informal team. The term bonding here refers to a specific function analysed relations perform: tying actors to each other within a community.
b) External or Bridging type of social capital characterizes linkage of focal actors to external agents which can be associated with intangible bridges between different communities.
c) Neutral to the level of investigation of social capital might include both of the types (Lil & Smith, 2001) as well as do not include any and focus on individual perception.
Despite the developed research field, the conceptual basis of social capital is criticized because of its interdependence as some researchers accuse social capital of influence that cannot be verified apart from other factors (Krishna, 2002). Therefore, there were raised a necessity for a researcher to make a preliminary assumption of his or her position toward social capital: substantial position (the influence is caused solely by social capital); institutional position (the effect of social capital is a residual of social structure); and intermediate position (social capital has partial causal value).
Existence of these assumptions derives from inability to evaluate social capital and its effect accurately since the measurement of social capital highly depends upon the specific features of examined social capital that the paper has already described above (Nahapiet & Ghoshal, 1998). For instance, in case of structural dimension, measurement indicators might include presence of network, its configuration and quantitative characteristics such as density, nodes connectivity, hierarchy (Lee, Park & Lee, 2015). Moreover, the variation of measurement system depends on the level the research is conducted at: individual (Burt, 1997), team (Lee et al., 2015) or organizational (Chow & Chan, 2008). Krishna (2002) claims that there are more than three standard level of investigation and expands the classification of measurement model to 4 levels described in Table 1.
Table 1. Classification of measurement models based on research level*
|
Level of the research |
Measurement model |
Data gathering methods |
|
|
Individual level |
Network-based |
Interview, individual survey |
|
|
Norms-based |
Social survey |
||
|
Modified network based |
Individual survey |
||
|
Community level |
Network-based |
Individual survey |
|
|
Network plus norms |
Community survey |
||
|
Regional |
Network-based |
Individual survey, interviews, case studies, official sources of publicly available data |
|
|
National level |
Network-based |
World Value survey |
|
|
Networks and Norms separately |
Cross-regional surveys, publicly available data |
*Source: Krishna, A. (2002). Active social capital: tracing the roots of development and democracy
The concept of social capital can be applied to analysis of a number of spheres such as economic performance, public health, community life, labour market, geographical and national development to identify bottlenecks, increase the efficiency of undertaken actions and develop strategy of sources allocation (interpretations (Adler & Kwon, 2002; Nahapiet & Ghoshal, 1998). It also can be analysed independently as well as along with other types of capital which might possess positive effect on performance of entities of different scale.
1.2 Human capital as performance impactful factor
A number of researchers asserts that the study of social capital independently of human capital is associated with a row of difficulties, which in some cases might be insurmountable (Coleman, 1988b; Krishna, 2002). This concept is supported by assumed positions toward social capital causal value thoroughly described above. Indeed, examination of social capital effect in isolation from human capital might be incomplete, as both of them are elements of integral network, where nodes are actors, whose characteristics are derived from human capital theory, while connection between these nodes are described by social capital linkage patterns. Hence, Coleman in his works (1988a, 1988b) has paid specific attention to the relations between social and human capital.
According to Schultz (1961), human capital is one of the fundamental wealth of nation consisting directly of people and their accumulated knowledge and skills. Becker (1964) affirms that investments in human capital are similar to a firm's investment in its capital or equipment, since former as well as latter has a certain economic effect on objects of different levels (for instance, education and skills are positively related to income at the level of individuals). Several researches confirms the concept of human capital influence on performance of various entities (project teams (Franck, Nьesch, & Pieper, 2011; Harris, McMahan, & Wright, 2012), organizations (Hitt, Bierman, Shimizu & Kochhar, 2001; Finkelstein, Hambrick, & Canella, 2009; Beattie & Smith, 2010), etc.) and can be considered as competitive advantage.
Human capital, even though less tangible than traditional types of capital (Coleman, 1988b), can be evaluated in two major forms: general and firm or industry specific human capital (Becker, 1975). The evaluation is usually carried out through a list of variables such as employee skills and education levels, employee attitude and motivation, number of interactions and relationships between employees and/or management (Hitt et al., 2001; Lazear, 2009). Considering measurements, there exist at least three approaches recently used to assess human capital: the input or cost-based measure, the income-based measure, and the output-based measure (Velayutham & Rahman, 2018).
The inclusion of social relationship analysis within a group in the investigation of human capital value is a common practice (Hitt et al., 2001; Felнcio, Couto & Caiado, 2014) due to the fact that relationship in this matter are part of both social and human types of capital. Nevertheless, some experts consider them separately as independent, and concentrate the study on the influence of one on another (Han, Han & Brass, 2014; Bao, Zhu, Cen, Peng, & Xue, 2018). Thus, bringing back the assumptions one has to made toward human and social capital independence.
1.3 Knowledge sharing as intersection of social capital and human capital
Knowledge sharing represents a research field at the junction of social and human capital as sharing of knowledge appears as a result of social interaction of group representatives possessing specific information or knowledge (Helms et al., 2010). Social capital in these terms encourages and facilitates knowledge sharing behaviour (Nahapiet & Ghoshal, 1998). Interestingly, that knowledge sharing though involves presence of pertinent knowledge does not necessarily intend to transfer this knowledge entirely (Lee et al., 2015). In other words, knowledge sharing involves a social structure and norms contributing to the exchange and accumulation of any part of knowledge within a certain community. Both an individual and a group of any organizational level (team, firm, district) can create, share within and transfer tacit or explicit knowledge to external agents (Chow & Chan, 2008). Polanyi (1966), who was first to introduce the classification, described explicit knowledge as codified information that can be transmitted in formal, systematic language, while tacit knowledge is informal type of information that can hardly be communicated or formalized.
From organizational perspective, knowledge sharing in both its forms is a crucial source of competitive advantage, that is why creation of knowledge and converting it into organizational knowledge became an aim of special knowledge management department (Nonaka & Takeuchi, 1991). The importance of sharing knowledge is associated with acquiring insights in order to produce new innovative solutions and improve employees' performance indicators (Ahmad, 2017). Maurer, Bartsch, & Ebers (2011) define knowledge sharing as an intermediary through which social capital affects organizational innovation. Hu and Randel (2014) highlight that the dimension of mediated social capital depends upon form of shared knowledge: in case of explicit knowledge, latter serves as a link between innovations and relational capital, while tacit knowledge mediates relations between innovation and cognitive social capital.
As one may note from above, knowledge sharing is a multifaceted phenomenon with many attributes which again impedes defining the term and its elements irrefragably, however key aspects which are information (in any format), specific behaviour of either receiver to acquire or sender to transmit knowledge, represent the essence. Thus, knowledge sharing event would be an interaction of individuals that fulfil these criteria of presented information and behaviour intended on knowledge exchange. An example of a knowledge sharing event may be various conferences related in one way or another to the team's activities and profile (Vlasov, 2014). Such events create so-called temporary clusters, whose concept was proposed by Maskell, Bathelt and Malmberg (2006). According to authors, temporary cluster is a form of interorganizational interaction in the format of professional short-lived hotspots: conferences, exhibitions, congresses, distinguished by an intensive exchange of knowledge, development of a social network and generation of innovative solutions (Vlasov, 2014). Conferences in this regard occupy a special niche due to the fact that they provide direct access to new knowledge and create conditions for the generation of unique solutions and their exchange, as well as the opportunities to search for experts and develop social networks. Moreover, conferences stimulate not only interpersonal but as mentioned inter-organizational interaction (Vlasov, 2014).
Due to the fact that knowledge sharing represent the flows of information between units possessing the knowledge, a common approach to analyse knowledge sharing is construction of interaction networks between participants (Rajalakshmi & Wahidabanu, 2011; Bosua, 2015; Ahmad, 2017). Combined with methods of social networks analysis this approach allows to identify bottlenecks of current knowledge sharing system. Measurement of knowledge sharing in this case might be done both quantitatively - through typical graph and networks characteristics such as distance, cohesiveness or centrality; and qualitatively through its visual representation or sociogram by revealing social patterns. Because of similarity to Social Network Analysis and its methods this method acquired name of Knowledge Network Analysis. (Helms et al., 2010)
However, there exists an opinion that network analysis is not an exhaustive method which is limited in its conclusions when it comes to the examination of knowledge sharing (Helms et al., 2010; White, 2014). This is attributed to the fact that require Knowledge Network Analysis «focuses on the symptoms rather than the underlying causes and some bottlenecks require explanative abilities concerning the artefact network which KNA (Knowledge Network Analysis) currently does not have», that is why it might be accomplished with other methods (Helms et al., 2010).
Concerning previous research finding upon knowledge sharing, there was revealed a positive relationship between knowledge sharing and team performance (Lee et al., 2015). Knowledge received and generated within knowledge sharing system increases employees' capacity and improves overall rates of organizational performance (Ahmad, 2017; Lee, Lee & Kang, 2005). A number of researches has not dwelled on general beneficial influence of social capital and conducted a deeper analysis of specific features of knowledge sharing network that may accelerate or inhibit the process of knowledge exchange (Vlasov & Andreeva, 2015; Van Waes, De Maeyer, Moolenaar, Van Petegem & Van den Bossche, 2018; Wei, J., Zheng, W., & Zhang, 2011). For instance, Vlasov and Andreeva (2015) addressed to knowledge network appearing as a result of joint conference participation of firms revealed that different types of network embeddedness have different impact on knowledge creation. According to research findings, structural embeddedness does not possess correlation with new knowledge development due to the inability of organization efficiently process large amounts of information; junctional embeddedness has a positive relationship with generating knowledge because of informational asymmetry and diversification of information sources; on the contrary, positional embeddedness is negatively related to development of innovative knowledge as a result of organizational cognitive overload impeding knowledge transmitting further down the network (Vlasov & Andreeva, 2015). Moreover, the fact that the strength of the positive relationship is determined not by the number of conferences organisation take part in, but by the diversity or diversification of attended conferences possesses a particular interest (Vlasov, 2014), as one has to take conference features into account while constructing knowledge sharing networks based on conferences as a source of links between entities.
Described knowledge sharing relationships might be considered as an initial stage of network partnership, which orientation on the implementation of which is indicated in section 15 of the Law «On Education in the Russian Federation» (2018). Phenomena of social or network partnership applied to different fields was examined by a number of researchers: education (Solomin & Gromova, 2011; Basov, 2014), human resource management (Frolov, 2013), innovations (Franco & Peter, 2018). In terms of development of educational institution, network organization provides institutions with full range of actions necessary to achieve their goals; relationship consistency between all subjects of network interaction; implements a differentiated approach to pedagogical and managerial personnel in accordance with their informational and professional needs, allows to fulfil the shortcomings of their resources or meet the needs for innovative solutions to problems of pedagogical practice (Basov, 2014). Solomin and Gromova also consider network interaction as a source of competitive advantage (2011).
Overall, knowledge sharing is a relatively new field of research that has so far been focused on the effect it has on different types of organizations. Interestingly, that almost none of the studies considered the impact it might have on educational institutions of primary and secondary education, in the context of which the creation and sharing of knowledge present a crucial value and may propose one of the ways to achieve a network partnership, whose positive influence has been proven by a row of studies.
1.4 Human capital, social capital and school performance
Over the last decades, a number of studies focused on the impact of social capital on educational achievements has significantly increased (Yang, 2017) due to the fact that investments in social interaction between school and its students tend to have beneficial return (Dufur, Parcel & Troutman, 2013).
The majority of studies examine internal social capital of schools concentrating on the success of pupils and/or teachers (Roth, 2013; Salloum, Goddard & Larsen, 2017; Yang, 2017), while those who consider the school as an entire entity represent the minority (Grady, 2010; Misra, Grimes & Rogers, 2013). Quite a few of them focus on the social capital effect on schools' achievements comparing to performance of other educational organizations (Misra et al., 2013).
Taking into account positive impact of social capital on the organization that has already been proven by a number of researches in a variety of sectors, existence of a gap in studying its effect on educational organizations (schools) is unusual (Vlasov & Andreeva, 2015). Moreover, few studies in this area have demonstrated that in the case of schools there is also a link between social capital and success at both individual (Misra et al., 2013) and organizational levels (Grady, 2010).
Regarding human capital, the situation differs significantly, as influences of the former on the success of organizations, including educational, has been studied more extensively. For instance, several researches demonstrated that experience of teacher among all other factors has a crucial impact on student's educational achievements (Grady, 2010). Moreover, not only operating, but also the strategic human capital was investigated through a lens of social capital (Hardin-Bartley, 2014). For instance, Swanson, in his dissertation, considers a number of strategies for human resource allocation aimed at improved student achievement (Swanson, 2013).
Overall, there is a scarcity of studies which consider the interrelated effect of social and human capital on the performance of schools, which essentially represents a rather significant gap in the research field for future studies to occupy.
1.5 Measurement of school performance
Even though there are academic articles devoted to measurement of school performance (Fare, Grosskopf & Weber, 1989; Zvoch & Stevens, 2008), assessing achievements of school is still a tough issue as current research field does not provide an expanded variety of approaches to utilize. Most of the articles prefer to evaluate performance of school via its major goal accomplishment, expressed through the academic success of its students (grades, Basic Essential skill Tests, dropout rate, etc.) (Misra et al., 2013; Roth, 2013; Salloum et al., 2013; Yang, 2017). Some experts also use an organizational approach, according to which school success is associated with its performance as an entire organization, for instance, other measures of school success, such as teacher retention, student behaviour, and academic growth (Grady, 2010).
There also exist less common, sometimes unique approaches and evaluation designs. Zvoch and Stevens (2008), for instance, affirm that usage of only one rate leads to one-sided results, and thus, suggest a system of indices to assess school performance depending upon the research focus: outcome, cohort, dynamic (between cohort). Another attempt to design evaluation system for school performance was made by Choi, Goldschmidt & Yamashiro (2005), who defined following four factors rating school achievements:
a) Adequate Yearly Progress/Program Improvement: This indicator captures whether schools make Adequate Yearly Progress and/or appear on the Program Improvement list (for repeated low performance) via aggregate proficiency criteria, participation criteria, additional state requirements and presence of school in a list of Program Improvement;
b) Percent proficient: apart from Adequate Yearly Progress to measure proficient levels individually apart from other factors included in Adequate Yearly Progress.
c) Academic Performance Index: designed for California's state accountability system and aimed at capturing school performance in a number of subject areas, combined with the state ranking based on Academic Performance Index.
d) Value added: unique criteria to assess contribution of each school to its student achievement.
Nevertheless, as a majority of other unique approaches highlighted in foreign articles, this evaluation design relies upon student's achievements or Basic Essential Skill test (Fare et al., 1989; Neal, 1997).
In this regard, Russian academics along with practitioners of educational field have established other techniques for school performance evaluation partially overlapping with the already mentioned methods of foreign researchers. Henceforth, one of the most significant indicators of school's achievements were the results of unified state knowledge tests (State Final Certification in the 9th grade and Unified State Exam in the final grade) (Pastiuk, 2018) which are similar to Basic Essential Skill tests employed in examined researches. Design with individual student's achievements as a core of measurement is also used by Russian researchers, for instance, Prakhov applied it as an independent variable while analysing influence of school characteristics (2009). Notwithstanding the common usage of state tests results as a measurement system by researchers, educational institutions and their clients, in 2015 Education Committee refused to utilize the results as a basis for ranking educational institutions, claiming it an unnecessary ranging criteria (Kizyma, 2018), which imposes a certain limitation for the study. Finally, as mentioned, there exists organizational approach, in which the main marker of school success is the level of achievement of a certain goal expressed in different ways, e.g. adaptation. Thus, defining the social adaptation of the graduate as the school's goal, Shchukovsky (2009) revealed that satisfaction with the educational process can be an indicator of student adaptation and the performance of the school as an entire organisation.
Among other methods proposed for the study of Russian educational organizations' performance there are academic publications activity (Balatsky & Ekimova, 2014), quality of educational services (as teacher's professional activities) and the quality of learning (as student's own activities in mastering knowledge and skills) (Demina & Mikhailova, 2016), as well as target, resource and socio-psychological effectiveness (Litvinenko, 2014). The latter measurements considering target, resource and socio-psychological effectiveness deserve special attention due to the complicated usage, especially when applied simultaneously. Considering the effectiveness of an educational organization as a complex characteristic of organization's activities results including the degree of its compliance with the main educational goals and objectives along with the resources and time spent to achieve these results target, resource, socio-psychological approaches allow to evaluate the effectiveness or the performance from different perspectives (Table 2) (Litvinenko, 2014).
Table 2/ Description of target, resource and socio-psychological effectiveness*
|
Type |
Target Effectiveness |
Resource Effectiveness |
Socio-psychological Effectiveness |
|
|
Characteristic |
It describes organization potential in terms of reaching a variety of different targets each specific organizations faces or settle. |
It compares the resources used by the organization and the result obtained, related to the time of their receipt. |
It provides a characteristic of the level of students moral qualities, the moral and psychological climate in the educational organization. |
|
|
Performance Indicators |
the level of achievement of organization objectives; appraisal of the development level of the organization; assessment of customer satisfaction with the quality of education provided by organization |
evaluation of the material resources provision; assessment of the level of employees' salaries; the level of resources for the implementation of core and additional programs; appraisal of the formation and development of educational environment |
evaluation of the organizational culture of an educational institution; assessment of the level of socio-psychological climate in the team; the level of motivation of teachers and students for development and self-development |
*Source: Litvinenko E.V. (2002). Formation of a methodology for evaluating work in educational organizations
Despite the rather extensive list of the discussed approaches for measuring educational institutions' performance, there is still a field for developing new individual techniques both on the basis of already existing state-owned methods of performance assessment and adapted measurement systems taken from related researches.
Summarizing all the information discussed above, social capital as well as human capital present extensively explored filed, which, however, lacks precision in their conceptual framework, thus imposing on a potential researcher of the topic a number of assumptions that must be identified before proceeding the study. At the same time, the area at the junction of social and human types of capital does not possess the same degree of exploration and might be considered as a prosperous field for academic researches. This concerns not only the knowledge sharing phenomenon thoroughly described above, but also the joint and/or mutual influence of social and human capital on organizational activity which requires deeper research. Despite the fact that a number of studies (Hitt et al., 2001; Finkelet al., 2009; Beattie & Smith, 2010; Yang, 2017; Dufur et al., 2013) have confirmed that social capital and human capital both independently and interconnected have a positive impact on the performance of commercial and non-profit companies, a very small part of the researchers focused on the effect these two types of capital have on the success of educational institutions, including the context of knowledge sharing. All this illustrates the gap in current global research filed of not only educational organizations, but also of social and human capital, and knowledge sharing. This study aims to occupy the niche by providing quantitative and qualitative research of the effect social capital, knowledge sharing and human capital might have on performance of educational institutions on the case of St. Petersburg schools.
2. Statement of the research question
The theoretical foundation made it possible to reveal an existing gap among academic studies devoted to social and human capital along with knowledge sharing. Precisely, current research field lacks clarity and profoundness in the examination of the impact named factors (social capital, human capital and knowledge sharing) may have on educational organizations of different types. The least explored context in this regard is associated with primary and secondary education and preschool institutions, meanwhile at the higher education level, the relationship between both forms of capital and performance, as well as between networking and university achievements has been proven to be beneficial for participants of the interaction (Frolov, 2013; Solomin & Gromova, 2011). Subsequently, the main aim of this research is to contribute to scientific knowledge by occupying the gap related to lack of studies investigating the role of human and social capital, as well as knowledge sharing in the activities of primary and secondary education institutions.
In order to achieve goal, the paper settles the following research question to explore: How does social capital, human capital and knowledge sharing impact the performance of primary and secondary education organizations (schools) of Saint-Petersburg?
The current education system of Russia possesses four types of educational institutions: preschool, general educational, professional educational and higher education organizations (Federal law On education in the Russian Federation, s. 23, 2018). General educational are subdivided into those who are oriented on primary general education (начальное общее) apart from secondary general (среднее общее) education, on secondary general education apart from primary general education, and those, who combine both minority (Government of St. Petersburg Education Committee, 2019). Due to the fact, that general educational organizations with orientation on either primary or secondary education represent the minority (Government of St. Petersburg Education Committee, 2019), the analysis of social capital, human capital and knowledge sharing impact is conducted on the level of general educational organizations, who provide both primary and secondary education and whose representatives are schools, gymnasiums, lyceums (Government of St. Petersburg Education Committee, 2019). The latter represents the typology of objects of the research, whose role will be further developed. Consequently, the subject of the research is the relationship between social capital, human capital, knowledge sharing and school performance. This statement of object and subject of the research correlates with other studies in the field and allows to compare results of the paper to previous findings.
Furthermore, theoretical foundation provides an ability to assume anticipated research results and develop a series of following hypotheses that were based on similar scientific experience. The null hypothesis in accordance with the rules of its formation (Field, 2009) states that none of named factors (social capital, human capital, knowledge sharing activity) possess significant impact on school performance. In other words,
H0: Social capital, human capital and knowledge sharing activity has no effect on school performance.
In accordance with the studies considered before, whose findings stated not only the existence of influence of these factors, but their positive relationship with the achievements of organizations, including educational, one may assume that the null hypothesis will be rejected in favour of alternative hypotheses, which sound as follows:
H1: Human capital possess a significant impact on schools' performance.
H2: Social capital possess a significant impact on schools' performance.
H3: Knowledge sharing possess a significant impact on schools' performance.
The fact that first two hypotheses do not name the direction of influence social and human capital may have is not accidental, since previous studies has revealed that various characteristics of these forms of capital can have both positive (Grady, 2010; Dufur et al., 2013). and negative relation to organizational achievements (Vlasov & Andreeva, 2015). As far as the third hypothesis is concerned, it is crucial to define the concept of active knowledge sharing. Active knowledge sharing is considered as knowledge sharing process with a high level of network characteristics (e.g. betweenness centrality), which will be distinguished and thoroughly discussed in the methodology part.
Nevertheless, these three hypotheses present basic assumptions devoted to the presence of factors' influence, which is a necessary basis that should be investigated before testing the following more detailed hypotheses concerning factors. This work also suggests that there exist relationships not only between afore-mentioned factors and performance, but also between the factors themselves. Based on this, two additional hypotheses about the connection of human capital, social capital and knowledge sharing appear:
H4: Knowledge sharing activity is related to social and human capital indicators.
H5: The type of school plays the role of moderator for social capital, human capital, knowledge sharing activity and schools' performance.
While the fourth hypothesis implies the confirmation of the theoretical foundation of knowledge sharing discussed earlier, including the opinion that it acts as an intersection of human and social capital, the last hypothesis makes a fundamentally new assumption specific for Russian educational institutions (due to the structure of education system in Russia) that, owing to the difference of the institutions considered and resulting in its typology, knowledge sharing will have various forms depending on the type of educational institution (schools, gymnasiums, lyceums). Together these hypotheses are going to assist in determining features causing the difference in knowledge sharing activity of the educational organizations.
First three hypotheses considering the relationship between examined factors and school's performance are tested through regression analysis, where dependent variable is one of school's performance measurements, while independent variables are factors extracted from factor analysis. The significance of factors within the regression model as well evaluation of distribution of school's performance measurements assessed via the nonparametric criteria for statistical significance will provide a base to either approve or reject hypothesis on existence of impact imposed by investigated factors. The fourth hypothesis devoted interrelationships between factors is also tested by nonparametric criteria for statistical significance in distribution and by correlation matrix built for the factors. The fifth hypothesis concerning the role of educational organization type is tested through nonparametric criteria for statistical significance in distribution for both measurements of school's performance and factors. All mentioned methods as well as stages of their implication are described in more detail in the next section.
Overall, the proposed hypotheses allow to derive conclusions on how social capital, human capital and knowledge sharing activity influence the performance of general educational organizations and thereby answer the research question the paper has settled. In order to test the reviewed hypotheses and explore the stated research question the following methodology was designed.
3. Methodology
In order to test five reviewed hypotheses and explore the stated research question the succeeding tasks were identified for each of which the appropriate method was chosen in accordance with the theoretical foundation. More precisely, after the research question and hypotheses were already stated the research design represents the following overall scheme:
a) Distinguish key concepts considered in the hypotheses and research question and establish measurement system with a subsequent list of suitable variables;
b) Determine general population of examined research objects and develop sample framework and rules necessary for data collection;
c) Collect and pre-process obtained data in order to bring it to a single mind;
d) Conduct an exploratory analysis of gathered dataset to get a primary understanding of the research objects and identify features that may possess influence on following research steps;
e) Construct and perform knowledge sharing network analysis with highlighting interaction clusters and extracting knowledge sharing activity indicators such as betweenness, in and out degree centrality, etc.;
f) Perform factor analysis in accordance with principle component analysis algorithm to reduce dimensions and reveal whether chosen set of variables fits the proposed set of factors: human capital, social capital, knowledge sharing.
g) Evaluate the influence both factors and distinct variables associated with human capita, social capital, knowledge sharing may impose on performance of educational organizations through regression analysis of different types;
h) Interpret the results obtained in the context of the set hypotheses, the research question, and previous findings;
i) Define limitations current research design and obtained data may have on findings and subsequent conclusions;
j) Develop possible areas for further research on relevant topics.
Each of the considered steps possess its own set of methods and tools necessary for solving the specific task described below.
3.1 The definition of concepts and measurement levels
The prior research activity is identification of key concepts that contribute to the theoretical framework of the study to conduct. In the current research, key concepts include social capital, human capital, knowledge sharing and school performance, that were thoroughly examined by the paper in the theoretical background section.
One may also note that along with exploration of principal definitions of aforementioned constructs there were observed major approaches to its measurement. These measurement systems were adjusted to educational organization type and characteristics of St. Petersburg educational institutions. Hence, human capital measurement includes school characteristics related to human resources and their development within an institution such as total number of teachers, share of teachers, awarded with the qualification category in the total number of teachers, amount of workers with official academic achievements, etc. The variables are selected in accordance with the definition of human capital (Becker, 1964; Schultz, 1961) and reviewed approaches to its measurement through qualification and skills, load and productivity, trainings and development, and other employee-related variables (Beattie & Smith, 2010; Hitt et al., 2001). The measurement of social capital is closely related to the assessment of the knowledge sharing activity as it implies an evaluation of the social interaction of the school with other network participants (Morel & Coburn, 2019). Thus, the measurement of social capital is performed through assessing the network each school possesses as well as its position in the overall network (centrality, size of the cluster to which the institution belongs, etc.) (Morel & Coburn, 2019; Vlasov & Andreeva, 2015). The network is constructed using business events as links between participants (Vlasov & Andreeva, 2015). As network characteristics there were chosen (Hanneman & Riddle, 2011):
a) In/Out degree centrality possesses equal values in this research due to the fact that graph has no direction, and demonstrates the number of connections (closest neighbours) the node possesses (Scale: 0 to 301).
b) Betweenness centrality (allows to evaluate the importance of nodes in terms of the number of paths passing through them) (Scale: 0 to 1).
c) Hub/Authorities based on Kleinberg's centrality score it indicates the amount of references the node receives (authorities) and makes (hub); because the graph is undirected, the values of hub and authorities are equal and demonstrate overall node access rate (Scale: 0 to 1).
d) Closeness centrality assesses how fast one node may reach any other in the network, illustrating the degree of remoteness of social capital (neighbours of the second and further order) from the node: the higher the closeness is, the bigger closest social capital is and the easier it is to reach it (Scale: 0 to 1).
e) Page Rank reveals mutual importance of the node; unlike hub and authorities, it measures not only the number of links to the node, but also the significance of connecting nodes (Scale: 0 to 10).
f) Transitivity implies an assessment of how adjacent vertices of the node are connected without node participation and measures subgraph closure (Scale: 0 to 1).
g) Clique Count identify independent subgraphs and measures the size of the biggest vertices set, thus illustrating the scale of surrounding relatively autonomous community (Scale: 0 to 23 (maximum number of independent subgraphs within sample).
h) Triad Count indicated the number of subgraphs containing three vertices including explored node which shows the amount of triple groups a node may have within first order neighbours (Scale: 0 to 44 580 (maximum number of possible triads)).
i) Clustering reflecting attribution of node to a community revealed by either fast greedy or walktrap algorithms discussed further.
At the same time, the characteristics of knowledge sharing are the variables associated with participation of educational organization in knowledge sharing activities (Luo & Zhong, 2016; Van Waes et al., 2018; Vlasov & Andreeva, 2015): the number of educational events in which institution has participated, whether an organizations had an experience of being an educational platform, whether it was awarded for its innovation activity, etc.
To appraise the performance of Saint-Petedrsburg schools, there were chosen several methods highlighted while theoretical examination. Due to the fact, that usage of only one measurement may lead to one-sided results (Zvoch & Stevens, 2008), there were selected several variable to evaluate schools' performance. Even though application of State Unified Exam results is currently impossible, there were taken other state-owned methods of performance assessment (Choi et al., 2005) are used: results of independent assessment of the quality of education (НОКО), the presence of educational organisation as well as its score in ratings of St. Petersburg educational institutions implementing educational programs of secondary general education in five directions: mass education, high achievements records, quality of provided educational process conditions, level of human resource provision and management quality. Rankings enable evaluating school's performance from different sides, including academic achievements commonly used for measuring school's performance (Misra et al., 2013; Roth, 2013; Salloum et al., 2013; Yang, 2017), and, overall, represent modified approach to assessment of school's performance through target effectiveness (Litvinenko, 2014). The full list of variables attributed to the named concepts is located in Appendix 1.
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