Formulating and elaborating a model for the measurement of intellectual capital in Spanish public universities

Abstract

Intellectual capital approaches become critical at universities mainly due to the fact that knowledge is the main output as well as input in these institutions. Although some attempts to measure intellectual capital have been made so far, there is still a long way to go. The purpose of the present article is to provide a model for the measurement of intellectual capital in higher education institutions. The results of a study done at Spanish public universities are used to indicate which intangible elements need to be measured, and a new framework for the measurement and management of intellectual capital is presented.

Points for practitioners

The main contribution of this article is the validation of the consensus on the key intangible elements and indicators that should comprise a university intellectual capital model. Our proposed intellectual capital model helps universities on the path to presenting information that is useful to their stakeholders, contributing to greater transparency, accountability and comparability in the higher education sector. This article offers useful and specific guidelines for intellectual capital reporting practice in universities. The creation of a framework of intellectual capital reporting facilitates benchmarking analysis and comparative studies in order to help decision-making processes, improve the articulation of public policies and increase transparency in the whole system.

Keywords

intellectual capital model Spain universities

Introduction

In the actual knowledge-based economy, investments in human resources, information technology, research and development, and customer relations have become essential in order to maintain the organization’s competitive position and to ensure its future (Cañibano et al., 2000; Elena and Warden, 2011; Goldfinger, 1997; Nakamura, 1999). The source of economic value and wealth is the set-up and handling of intangible assets, frequently grouped under the generic term ‘knowledge’ or ‘intellectual capital’.

Intangibles and intellectual capital have become a very important issue during the last decade, not only for academics, but also for users, governments, regulators, enterprises, investors and other stakeholders (Sánchez and Elena, 2005). This growing interest has extended from firms to public institutions (Melián-González et al., 2010), such as universities and research centres (Bezhani, 2010; Melián-González and Bulchand-Gidumal, 2009).

Intellectual capital approaches become critical mainly due to the fact that universities’ main goals are the production and the diffusion of knowledge and their more important investments are in research and human resources (Elena, 2004). Therefore, both inputs and outputs are mainly intangibles.

Universities become critical elements for the production, transmission and dissemination of knowledge:

due to the key role they play in the three fields of research and use of its results, thanks to industrial cooperation and spin-off; education and training, in particular training of researchers, and regional and local development, to which they can contribute significantly. (European Commission, 2003)

For that reason, the European Union considers that ‘investing more and better in the modernization and quality of universities is a direct investment in the future of Europe and Europeans’ (European Commission, 2005: 2).

In this context, European higher education institutions are currently immersed in a process of profound change, the intention of which is to improve the effectiveness, efficiency and transparency of these institutions with the aim of contributing to the development and improvement of the competitiveness of the European economy (Dixon and Coy, 2007; European Commission, 2010; Ramírez et al., 2007; Sánchez and Elena, 2007; Silvestri and Veltri, 2011).

Since there is presently no common international framework for managing information on the intangible determinants of corporate value (only scattered efforts around the world), it seems appropriate to devote efforts to the development of new measurement and management techniques in order to help universities to identify, measure and monitor their intangible sources of value, and thereby increase the efficiency and effectiveness of their management.

New measurement and management systems allow universities to be in a better position to:

create transparency about the use of public funds;

explain the achievements of research, training, innovation and their benefits to stakeholders;

illustrate the development of intangible assets;

reveal leverage effects and externalities;

communicate (new) organizational values; and

demonstrate their competitiveness (Warden, 2003).

However, despite all this, only a few universities are trying to measure and manage their intellectual capital, but they are finding many difficulties. In order to solve those problems, this article will develop a proposal for a new intellectual capital measurement model for Spanish public universities. This purpose is to be achieved via the following operational objectives:

The analysis of existing models proposed at Spanish universities,

The identification of the key intangible elements in a public university. This involves identifying the intangible elements that university stakeholders demand most. To this end, a questionnaire was designed and sent to every member of the Social Councils of Spanish public universities in order to identify the intangible items that they consider essential for universities.

The elaboration of a battery of indicators to measure these key intangible elements.

The article is structured as follows. In the second section, we briefly explore the concept of intellectual capital in higher education institutions and justify the importance of measuring and managing their intellectual capital. The third section describes the most significant initiatives in measuring and managing intellectual capital in Spanish universities. In the fourth section, we present our proposal of an intellectual capital measurement model for Spanish public universities. Final conclusions are drawn in the fifth section.

Relevance of intellectual capital for universities

The term ‘intellectual capital’ is used to cover all of the non-tangible, or non-physical, assets and resources of an organization, including its processes, innovation capacity, patents and the tacit knowledge of its members and their network of collaborators and contacts. So, intellectual capital has been defined as the combination of intangible resources and activities that ‘allows an organization to transform a bundle of material, financial and human resources in a system capable of creating stakeholder value’ (European Commission, 2006).

Intellectual capital is often represented as consisting of three basic and strongly interrelated components: human capital, structural capital and relational capital (Cañibano and Sánchez, 2008; Leitner, 2004; Rafiee et al., 2010; Ramírez et al., 2007; Secundo et al., 2010).

In the case of universities, we could define the components in the following way:

Human capital: The set of explicit and tacit knowledge of the universities’ personnel (professors, researchers and assistants) acquired through formal and informal educational and actualization processes embodied in their activities.

Structural capital: The explicit knowledge related to the internal process of the dissemination, communication and management of scientific and technical knowledge in the organization. Structural capital may be divided into:

○ Organizational capital: This refers to the operational environment derived from the interaction between research, management and organization processes, organizational routines, corporate culture and values, internal procedures, the quality and scope of the information system, and so on.

○ Technological capital: This refers to the technological resources available at the university, such as bibliographical and documentary resources, archives, technical developments, patents, licenses, software, databases, and so on.

Relational capital: This gathers the wide set of economical, political and institutional relationships between the university and its non-academic partners: enterprises, non-profit organizations, the local government and society in general. It also includes the perception that others have of the university: its image, appeal, reliability and so on.

The following are some of the reasons why it is a major necessity for higher education institutions to measure and manage their intellectual capital:

Knowledge is the principal output and input of higher education institutions. Universities produce knowledge, either through scientific and technical research (the results of investigation, publications, etc.) or through teaching (students trained and productive relationships with their stakeholders). Their most valuable resources also include their teachers, researchers, administration and service staff, university governors, and students, with all their organizational relationships and routines (Leitner, 2004). It is true to say, then, that universities’ inputs and outputs are largely intangible (Cañibano and Sánchez, 2008).

Continual demands for greater information and transparency about the use of public money exist (Warden, 2003), mainly due to the fact that most of the funding for public universities is handed over by the government (Sánchez and Elena, 2006).

The greater independence of universities regarding their organization, management and budget distribution requires greater social responsibility, which will lead universities to prepare accounting information to report to society, as well as to facilitate and satisfy the information needs of participants in the institution itself.

The implementation of the European Space for Higher Education promotes the mobility of both students and teachers within the territory of Europe, while, at the same time, encouraging both collaboration and competition between universities. This environment of greater competition and necessary collaboration means that these institutions are now committed to accessing citizens and transmitting relevant information on their activities. All this could well play an important role in the decision-making processes of the users of the accounting information, for example, in the case of potential students choosing where to study.

Lastly it is important to point out that universities are now facing growing competition due to lower funding, which puts them under greater pressure to communicate their results.

In our opinion, higher education institutions have to elaborate models especially designed to identify and provide information on the organisations’ strategies, objectives, visions, activities and key intangible resources, based on financial and non-financial indicators. The intention of these models is to contribute to the progressive recognition of intellectual capital as a key strategic factor to confront the competitive challenges currently facing universities.

Models for measuring and managing intellectual capital at Spanish institutions of higher education

This section describes three important initiatives in measuring and managing intellectual capital that are being developed at Spanish universities:

the Programa de Capital Intelectual (PCI) Project in the Madrid region;

the Observatory of the European University (OEU) at the Autonomous University of Madrid (UAM); and

the Knowledge Management Project at the University of the Basque Country.

The PCI project in the Madrid region

This project was carried out by a research group from the Institute for Business Administration (IADE), belonging to the UAM, and directed by Professor Eduardo Bueno. This studied the intellectual capital of universities and public research centres (PRCs) in the Madrid region.

The project aims to discover the research capability of universities and PRCs through an efficient management of their intellectual capital, and how to attain the maximum economic and social return of the resources. The investigation was carried out in two separate parts. One of them developed an Intellectual Capital Indicators Program applied to research activity; the other part was a proposal of a knowledge management model for the research activities of universities and PRCs.

The board of indicators was based in the Intelect Model (Euroforum, 1998) supplemented by other proposals, such as the indicators included in the Spanish National Plan for Universities Quality Evaluation. This board of indicators proposes an inventory and measurement of the potential and quality of the research results in universities and PRCs in the Madrid region. The indicators selected for the measurement of research results were organized into three different levels (see Table 1).

Table 1.

Generic enumeration of intellectual capital indicators for the measurement and management of the research activities of universities

First level of indicators	Related to the number of meetings and conferences organized, doctoral programmes, research projects, books and articles, invited lectures, communications, research visits, patents, doctoral theses, awards and fellowships, and so on
Second level of indicators	No. of books and published articles/Total number of professors No. of communications and lectures/Total number of professors No. of defended doctoral theses/Number of doctoral students No. of PhDs/Total number of personnel No. of research visits/Number of research personnel
Third level of indicators	% of revenues from Spanish administration % of revenues from European Union institutions % of revenues from private companies

Source: Adapted from Bueno et al. (2002).

Afterwards, a Model of Intellectual Capital Management is developed, considering the universities’ and PRCs’ research activity as the source of creation diffusion and the reuse of knowledge. This model considers the research activity made by these institutions as the result of using intellectual capital, with the aim of estimating the most important intellectual capital variables for the studied organizations. Also, it considers that research processes are fed by resources (inputs) in order to get results (outputs), and tries to assess the relationships between them, as it is indicated in Figure 1.

Figure 1.

Knowledge leadership and management model

Specifically, the inputs or resources considered would be those outlined in Figure 2.

Figure 2.

Intellectual capital structure for research activity in universities and research organizations in the Madrid region

Universities and PRCs use the resources (inputs) to achieve different research processes (with important differences according to scientific traditions in each knowledge area) in order to obtain the following results (outputs):

Scientific production:

○ books published;

○ articles and book chapters;

○ patent rights and any other type of copyright;

○ research projects carried out; and

○ lectures and communications at conferences and meetings.

Social perception of the organization.

Intellectual capital increase in the organization.

Research networks established among organizations.

Intellectual capital assessment and evaluation are made by means of the results of the research (dynamic evolution of the indicators), comparative analysis and benchmarking, and analysis of their social consideration.

The OEU at the UAM

The OEU, created in June 2004, is a project developed within the ‘European Policies for Research and Innovation in the Move towards European Research Area’ (PRIME) ‘Network of Excellence’, involving the cooperation of 15 European universities.

One of the aims of the OEU is to better understand the importance of managing intangibles in public universities in order to improve their level of quality and competitiveness (Sánchez and Elena, 2005). Its overall objective is to provide universities with adequate tools for the governance of their research activities. For this purpose, the OEU will initially develop procedures for data collection in order to, subsequently, produce indicators for universities’ strategy and management procedures. This will require discussing and testing new indicators of university performance and activity, as well as finding methods for the representation and measurement of the multidimensional aspects of performance. The final objective is to provide universities with a benchmark for comparisons with similar universities thanks to the development of a platform of quantitative data at the university level across Europe.

The OEU research team (OEU, 2005) has developed a framework for the characterization of research activities undertaken by universities: the Strategic Matrix. This two-dimensional matrix facilitates the analysis of, and helps to characterize the status of, university research management in order to identify the best performing universities and to compare the setting in which universities operate. The first dimension of the matrix deals with the thematic aspects of university research management (funding, human resources, academic outcomes, third mission and governance). The second dimension of the matrix deals with transversal issues that cross these thematic categories (autonomy, strategic capabilities, attractiveness, differentiation profile and territorial embedding). A few Key Questions were selected for each cell of the Strategic Matrix. For each one, a few relevant indicators and possible schemes for collecting the data required for these indicators was proposed.

Furthermore, the OEU proposed the presentation of an intellectual capital report, called the ICU report (Sánchez et al., 2006), specifically designed for universities and research centres, with the aim of improving transparency and promoting the homogeneous publication of the indicators of intellectual capital. The proposed ICU report consists of three fundamental sections that describe the logical movement from internal strategy and management (the design of the vision and objectives of an institution) towards a system of indicators (OEU, 2006: 211): (a) the vision of the institution; (b) intangible resources and activities; and (c) the system of metrics.

One of the most proactive universities within the OEU is the UAM, which has participated actively in the definition of indicators and in the data collection process. To this effect, the UAM developed a ‘Strategic Research Plan’ in order to improve and promote research activities within the university. This document reflects the university’s research objectives and allows the identification of some critical intangibles to work on. Once these intangibles are identified, different indicators may be defined in order to measure the resources and activities undertaken to improve such intangibles and to monitor them (Elena, 2004). The definition of commonly selected indicators that allows managers and stakeholders to understand and compare research activities is an essential starting point. Table 2 shows the proposed indicators for UAM to measure the intangible resources or activities.

Table 2.

UAM strategic objectives, critical intangibles and possible indicators

Strategic objectives	Critical intangibles	Possible indicators
To improve research management	Research service and Research and Business Transfer Office (OTRI)	Number of requests for advice Number of requests advised Satisfaction level with the service Number of dissemination initiatives of the research activity Level of impact of the dissemination channel Number of visits to private companies
To promote research activity	Level of excellence of research groups Coordination between the different university research offices	Number of research groups and areas of knowledge Number of researchers in each group Ratio of PhD researchers to doctoral researchers Number of publications with international impact Level of mobility of researchers (junior and senior) Private or public funds
To assess research activities	Transparent criteria to assess research results	Doctoral theses Publications, international and national conferences, patents Links with private companies Links with other research groups (networks)
To increase the participation of the UAM in the VI Framework Programme	Advice Office	Number of projects with European funds Number of countries and research teams involved in these European projects Mobility of the researchers
To renovate labs	Satisfaction of researchers	Number of researchers working in labs Amount of funds invested Number of computers and other materials and resources for research Level of safety
To support the Scientific Park of Madrid and the creation of the ‘patent centre’	Network of universities, research centres and private companies in Madrid	Number of projects with public researchers and private companies in Madrid involved Dissemination activity: mass media news, publications in scientific reviews
To promote libraries	Productivity of the service and satisfaction of users	Number of courses and users of these services Degree of integration with other libraries New books acquired by libraries Amount of funds to acquire books Number of online reviews

Source: Elena (2004).

Finally, UAM highlights the main methodological problems that emerge in the gathering and analysis of the data and provides suggestions for some of them.

The Knowledge Management Project at the University of the Basque Country

The University of the Basque Country developed a knowledge management case-study project in a key and strategic cross-organizational process, ‘Research–Development–Transfer’ (R&D&T), of scientific and technological knowledge within universities. The aim is to show an original methodology for the assessment of that process through the search for critical knowledge. The knowledge embodied in the process creates the R&D&T capital.

The idea that underlines this project is that ‘knowledge management in universities can be defined as a whole process that increases their intellectual capital, that could be defined as all the administrative, scientific and technical knowledge that generates or will generate benefits in the future’ (Araujo, 2000). An important portion of intellectual capital at universities is the R&D&T capital, that is, the intellectual capital due to the process of creation of scientific and technical knowledge and its transference to the social environment (companies, governmental institutions and other social agents).

The starting methodological framework was the Intellectus Model (CIC, 2003). Intellectual capital is divided into three categories: human capital, structural capital (made up of organisational capital and technological capital) and relational capital (formed by business capital and social capital).

The starting point of the project is that management practices do not act directly as drivers of intellectual capital, but stimulate and promote some key types of knowledge that are the genuine drivers of intellectual capital (Rodríguez et al., 2004). Consequently, a basic task concerning knowledge management is to find the key knowledge types that act as drivers of intellectual capital in an organization and then discover the management practices that promote them. Table 3 shows the types of knowledge that act as drivers of R&D&T capital at a public university.

Table 3.

Key types of knowledge as drivers of R&D&T capital at universities

As drivers of human capital

H1 – Scientific and technical knowledge.

H2 – Specific skills and knowledge concerning the actual process of research.

H3 – Knowledge and acceptance of the need for applied and basic research.

H4 – Knowledge and acceptance of the need to share knowledge with other areas.

H5 – Knowledge and acceptance by university researchers of the image of the university.

As drivers of structural capital

S1 – Knowledge shared by researchers concerning the experience of knowledge transfer at the university.

S2 – Knowledge of the creation and maintenance of value chains of scientific and technical knowledge.

S3 – Knowledge shared and accepted by university researchers concerning quality indicators for applied research and its transfer.

S4 – Knowledge of the management of the scientific and technical knowledge transference process.

S5 – Knowledge of the administrative management of projects and contracts.

As drivers of relational capital

R1 – Knowledge of the needs of companies, organizations, institutions and society in general.

R2 – Knowledge of the ways in which companies and non-university bodies involved in applied research meet the needs of businesses and institutions in this area, in terms of both methods and prices.

R3 – Knowledge of ways of dealing with the private sector and with institutions in order to form strategic alliances and to cooperate on projects.

R4 – Knowledge of techniques and methods to improve the image and reputation of the institution as a producer of transferable scientific and technical knowledge.

R5 – Knowledge by companies, organizations and institutions of the possibilities offered by the university as a supplier of scientific and technical knowledge.

Source: Rodríguez et al. (2004).

Finally, some indicators were proposed to measure the volume and main characteristics of the basic and applied research produced by universities, and what would increase the efficiency of their research. As a summary, some of the proposed indicators are shown in the Table 4.

Table 4.

Intellectual capital indicators for university research

Human capital

Average size of research groups

Structure of research groups

Average scientific production of the research group (in number of activities or projects)

Average scientific production of the research group (in amount of funding)

Average research years

Structural capital

Rate of contracts promoted by researchers at the university

Rate of funding by science specialties

Relational capital

Rate of research projects by science specialties

Rate of funding by companies’ contracts

Rate of promotional investment

Agreements with public and private organizations to develop an effective research activity and to improve services

Source: Adapted from Landeta et al. (2004).

Proposal for an intellectual capital measurement model for Spanish public universities

A new intellectual capital measurement model for implementation at Spanish public universities will now be discussed. Our aim is to design a model that identifies a detailed list of the key intangible elements in a university and to define a battery of indicators that allows these intangible elements to be measured.

The methodology used to elaborate a new intellectual capital measurement model for Spanish public universities has been:

First, identification of the strategic objectives of the Spanish public universities through examination of documents concerned with the objectives and strategic plans of the university.

Second, identification of the key intangible elements in a university. This identification has been determined through a questionnaire sent to the members of the Social Council of the Spanish public universities. The results of the interviews have received statistical analyses.

Third, elaboration of a definitive list of indicators to measure these key intangible elements.

Our intellectual capital model is a tool especially designed to identify, measure, manage and provide information on Spanish public universities’ intangible resources. This tool allows for identifying and providing information on the organisations’ strategies, objectives, visions, activities and key intangible resources, based on financial and non-financial indicators.

Figure 3 shows the stages to be followed in the development and implementation of an intellectual capital model in universities.

Figure 3.

Stages in the development and implementation of an intellectual capital model in universities

In what follows, each of these phases is analysed.

Definition of strategic objectives for intangible elements

First, it is necessary to discuss the corporate objectives and strategies that lead managers to focus on the essential processes of value creation. Defining the organization’s strategic framework will then facilitate the formulation of objectives for intangible elements, which, in turn, define the areas where specific skills, structures and relationships are to be created or improved.

We have examined the documents concerned with the objectives and strategic plans of the different Spanish public universities. These documents give a complete description of the mission and vision of the university and the institution’s current strategic objectives.

Overall, it was found that the mission of Spanish public universities is:

the transmission of knowledge and culture;

training and research support;

the social integration and employment of graduates; and

the enrichment of the social, cultural and economic environment.

Also, the main strategic objectives, outlined in the function of the mission and vision, are:

improvement in university teaching;

improvement in university research; and

relationship with the environment (knowledge transfer).

Identification of key intangible elements in a university

This phase refers to the presentation of the intangible elements needed to launch institutions’ strategic objectives. Specifically, based on the Intellectus Model (CIC, 2003), we proposed 42 intangible elements according to the public higher education institutions’ characteristics: 12 relating to human capital (concerning the abilities and skills of the people belonging to the institutions); 14 relating to structural capital (referring to how the institution is structured and how it works); and 16 relating to relational capital (reflecting the institutions’ relations with students and the outside world) (see Table 5).

Table 5.

Proposed intangible elements

Human capital	Intangible elements
HC1	Typology of university staff (historical data on increase and decrease of staffing numbers, staff age structures, type of contract, etc.)
HC2	Academic and professional qualifications of teaching and research staff (% of teachers, % of civil servants, etc.)
HC3	Mobility of teachers and researchers (% of teachers with fellowships, etc.)
HC4	Scientific productivity (books, articles published, etc.)
HC5	Professional qualifications of administration and service staff
HC6	Mobility of graduate students
HC7	Efficiency of human capital
HC8	Teaching capacities and competences (didactic capacity, teaching innovation, teaching quality, languages, etc.)
HC9	Research capacities and competences (research quality, participation in national and international projects, % of doctors, six-year terms, etc.)
HC10	Capacity for teamwork
HC11	Leadership capacity
HC12	Training activities
Structural capital	Intangible elements
SC1	Facilities and material resources supporting pedagogical qualification and innovation
SC2	Facilities and material resources supporting research and development
SC3	The institution’s assessment and qualification processes
SC4	Organizational structure
SC5	Teaching management and organization (academic networks, periodical exchange with foreign teachers, teaching incentives, etc.)
SC6	Research management and organization (internal communication of results, efficient management of research projects, research incentives, theses read, etc.)
SC7	Organization of scientific, cultural and social events
SC8	Productivity of the administration, academic and support services
SC9	Organization culture and values
SC10	Effort in innovation and improvement (expenditure on innovation, staffing levels, etc.)
SC11	Management quality
SC12	Information system (document processes, databases, ICT use, etc.)
SC13	Technological capacity (total expenditure on technology, availability and use of computer programs, intranet/Internet use, etc.)
SC14	Intellectual property (patents, licences, etc.)
Relational capital	Intangible elements
RC1	Efficiency of graduate teaching (average duration of studies, drop-out rate, graduation rate, etc.)
RC1	Efficiency of graduate teaching (average duration of studies, drop-out rate, graduation rate, etc.)
RC2	Student satisfaction
RC3	Graduate employability
RC4	Relations with students (capacity to respond to students’ needs, permanent relations with graduates, etc.)
RC5	Relations with the business world (spin-offs, R&D contacts and projects, etc.)
RC6	Relations with society in general (institutional representation in external organizations, collaboration in national and international projects, etc.)
RC7	Application and dissemination of research (dissemination of results, social appropriateness of research)
RC8	Results with the media
RC9	University image
RC10	Collaborations and contacts with public and private organizations
RC11	Collaboration with other universities
RC12	Strategic links
RC13	Relations with quality institutions
RC14	The regional, national and international reputation of the university
RC15	Social and cultural commitment
RC16	Environmental responsibility

In order to identify which intangible elements are the most relevant for university stakeholders, a questionnaire was designed and sent to every member of the Social Councils of Spanish public universities. It was thought that these participants would provide a good example of the attitude of university stakeholders since they represent the different social groups connected with universities: university governors, students, teaching and research staff, administration and services staff, union organizations, business organizations, and public administrations.

The population to be studied was therefore composed of the 1904 members of the Social Councils of Spanish public universities. Replies were received from 247 members, 22.57 percent of the total. The size of the sample was considered sufficient since in a binomial population, the estimation error would be 5.37 percent for a reliability level of 95 percent.

The information was collected via an online survey during May–July 2011. The questionnaire consisted of five-point Likert scale questions. Those surveyed were asked to rate on a five-point Likert scale the importance they gave to the different intangible elements in universities.

Table 6 shows the frequencies obtained in the empirical study (mean, median, standard deviation and the 25th and 75th percentiles) for the different intangible elements (grouped in three categories of intellectual capital).

Table 6.

Intangible variables used in the study

Intangible elements	Mean	Median	Standard deviation	Percentile
Intangible elements	Mean	Median	Standard deviation	25	75
HC1	3.66	4	0.433	3	4
HC2	4.60	5	0.321	4	5
HC3	4.54	5	0.552	4	5
HC4	4.58	5	0.365	4	5
HC5	3.66	4	0.672	3	4
HC6	4.37	4	0.327	4	5
HC7	4.44	5	0.413	4	5
HC8	4.60	5	0.438	4	5
HC9	4.39	4	0.285	4	5
HC10	4.08	4	0.366	4	5
HC11	3.99	4	0.452	3	5
HC12	4.44	5	0.369	4	5
SC1	4.12	4	0.344	4	5
SC2	4.47	4	0.343	4	5
SC3	4.31	4	0.383	4	5
SC4	4.06	4	0.602	3	5
SC5	4.63	5	0.402	4	5
SC6	4.40	4	0.329	4	5
SC7	4.46	4	0.406	4	5
SC8	4.05	4	0.449	3	5
SC9	4.12	4	0.437	3	5
SC10	4.58	5	0.352	4	5
SC11	4.54	5	0.394	4	5
SC12	4.48	4	0.363	4	5
SC13	4.49	5	0.394	4	5
SC14	4.58	5	0.358	4	5
RC1	4.63	5	0.295	4	5
RC2	4.66	5	0.377	4	5
RC3	4.79	5	0.252	5	5
RC4	4.29	4	0.359	4	5
RC5	4.79	5	0.271	5	5
RC6	4.47	5	0.354	4	5
RC7	4.37	4	0.374	4	5
RC8	4.01	4	0.547	3	5
RC9	4.65	5	0.313	4	5
RC10	4.40	4	0.348	4	5
RC11	4.56	5	0.284	4	5
RC12	4.42	4	0.335	4	5
RC13	4.44	4	0.341	4	5
RC14	4.47	5	0.405	4	5
RC15	4.40	4	0.398	4	5
RC16	4.49	5	0.434	4	5

First, it must be observed that, in general, a high mean value was awarded to the different intangible elements relating to human, structural and relational capital, which shows a strong emphasis on the need for universities to measure and manage their intellectual capital.

The statistical criteria followed by Castilla and Gallardo (2003), Larrán et al. (2010) and Pelau et al. (2011) in the field of study relative to information on intangible assets was adopted in order to consider an element as ‘essential’ in the model of intellectual capital proposed in this article. That is, an element is ‘essential’ if it shows a mean value of above 4.5 and a median of 4 points or more, in conjunction with a minimum 25th percentile score of 4 points and a minimum 75th percentile score of 5 points (see Table 6). Additionally, calculations of Spearman bivariate correlations were carried out in order to eliminate the redundant indicators (Dominiak et al., 2013) (see Tables 7 –9).

Table 7.

Spearman correlations between human capital indicators

	HC1	HC2	HC3	HC4	HC5	HC6	HC7	HC8	HC9	HC10	HC11
HC2	0.19
HC3	0.29*	0.72**
HC4	0.28	0.59**	0.68**
HC5	0.10	0.37*	0.23	0.16
HC6	−0.13	0.40**	0.34*	0.41**	0.12
HC7	−0.17	0.51**	0.52**	0.31**	0.37*	0.55**
HC8	0.03	0.63**	0.60**	0.67**	0.22	0.37*	0.56**
HC9	−0.08	0.36**	0.45**	0.43**	0.01	0.55**	0.56**	0.59**
HC10	0.05	0.37*	0.40**	0.40**	0.33*	0.28	0.40**	0.47**	0.37**
HC11	0.15	0.17	0.42**	0.43**	0.22	−0.03	0.21	0.46**	0.31*	0.67**
HC12	0.01	0.27	0.22	0.26	0.39	0.28	0.26	0.21	0.35*	0.40**	0.09

Notes: Variables are described in Table 5. * Significant bilateral correlation at the level of 0.05; ** significant bilateral correlation at the level of 0.01.

Table 8.

Spearman correlation between structural capital indicators

	SC1	SC2	SC3	SC4	SC5	SC6	SC7	SC8	SC9	SC10	SC11	SC12	SC13
SC2	0.51**
SC3	0.49**	0.35*
SC4	0.38**	0.35*	0.43**
SC5	0.21	0.26	0.51**	0.66**
SC6	0.09	−0.02	0.24	0.41**	0.55**
SC7	0.15	0.18	0.22	0.41**	0.32*	0.59**
SC8	0.40**	0.27	0.50**	0.57**	0.45**	0.34*	0.54**
SC9	0.50**	0.27	0.46**	0.52**	0.28	0.21	0.47**	0.75**
SC10	0.37*	0.45**	0.43**	0.70**	0.49**	0.22	0.29	0.44**	0.49**
SC11	0.19	0.50**	0.34*	0.45**	0.35*	0.07	0.07	0.33*	0.31*	0.47**
SC12	0.20	0.37**	0.46**	0.66**	0.47**	0.48**	0.47**	0.59**	0.53**	0.60**	0.47**
SC13	0.29	0.31*	0.32*	0.59**	0.52**	0.32*	0.39**	0.51**	0.47**	0.67**	0.45**	0.52**
SC14	0.36*	0.56**	0.43**	0.12	0.18	0.23	0.24	0.29	0.38**	0.40**	0.45**	0.39**	0.27

Notes: Variables are described in Table 5. * Significant bilateral correlation at the level of 0.05; ** significant bilateral correlation at the level of 0.01.

Table 9.

Spearman correlation between relational capital indicators

	RC1	RC2	RC3	RC4	RC5	RC6	RC7	RC8	RC9	RC10	RC11	RC12	RC13	RC14	RC15
RC2	0.70**
RC3	048**	0.78**
RC4	0.50**	0.57**	0.50**
RC5	0.59**	0.67**	0.55**	0.47**
RC6	0.28	0.48**	0.29*	0.37*	0.42**
RC7	0.19	0.40**	0.48**	0.30*	0.53**	0.62**
RC8	0.38**	0.39**	0.24	0.62**	0.26	0.28	0.19
RC9	0.40**	0.61**	0.65**	0.41**	0.68**	0.18	0.54**	0.34*
RC10	0.45**	0.59**	0.56**	0.32*	0.62**	0.40**	0.47**	0.35*	0.72**
RC11	0.30*	0.51**	0.50**	0.26	0.37**	0.55**	0.52**	0.19	0.29*	0.47**
RC12	0.41**	0.53**	0.42**	0.66**	0.40**	0.36*	0.43**	0.59**	0.46**	0.55**	0.31*
RC13	0.25	0.54**	0.57**	0.45**	0.34**	0.52**	0.75**	0.32*	0.51**	0.47**	0.56**	0.56**
RC14	0.39**	0.48**	0.29	0.45**	0.55**	0.39**	0.25	0.53**	0.55**	0.53**	0.28	0.30*	0.21
RC15	0.31*	0.53**	0.46**	0.61**	0.51**	0.47**	0.47**	0.57**	0.59**	0.41**	0.17	0.41**	0.54**	0.66**
RC16	0.37*	0.55**	0.53**	0.52**	0.41**	0.33*	0.24	0.63**	0.47**	0.47**	0.41**	0.43**	0.42**	0.43**	0.56**

Notes: Variables are described in Table 5. * Significant bilateral correlation at the level of 0.05; ** significant bilateral correlation at the level of 0.01.

Specifically, the analysis of the data obtained from the various statistics (mean, median, mode, range, typical deviation, 25th and 75th percentiles, and bivariate Spearman correlations) led to classifying the following intangible elements as essential and not redundant to universities:

Human capital: academic and professional qualifications of the teaching and research staff, scientific productivity, and teaching capacities and competences.

Structural capital: teaching management and organization, effort in innovation and improvement, management quality, and intellectual property.

Relational capital: efficiency of graduate teaching, student satisfaction, graduate employability, relations with the business world, the university’s image and collaboration with other universities.

Selection of indicators and data collection

Valid indicators must now be drawn up for each intangible element considered as key in Spanish public universities. This phase is critical since the interest and viability of this intellectual capital model depends primarily on the characteristics and quality of the indicators and the data sources used to design them. During data collection, it is of prime importance to motivate employees to carry out the task and convince them of the benefits of an intellectual capital model.

The indicators should have the following characteristics (Meritum Project, 2005):

they must promote a visualization that allows actions to be translated into a system of indicators;

they must have an array of indicators that describe the university’s value creation process;

they must include indicators from all three components of intellectual capital;

they may contain a mix of financial and non-financial indicators; and

all indicators must be verifiable.

Finally, a set of 31 indicators was proposed (see Table 10). Again, these indicators were validated through interviews with the members of the Social Councils of Spanish public universities. All indicators achieve high mean and median values – approaching 5 points. Therefore, these indicators are classified as fundamental or essential for measuring university intellectual capital.

Table 10.

Proposed intellectual capital model for Spanish universities

	Intangible elements	Indicators
	HUMAN CAPITAL
HC2	Academic and professional qualifications of staff	% of doctors among teaching and research staff Number of qualified teachers % of graduate administration, technical and auxiliary staff
HC4	Scientific productivity	Rate of participation in research projects Proportion of six-year research periods Production of doctoral theses Number of scientific/teaching publications
HC8	Teaching capacities and competences	Total teaching and research staff/students Number of participants in training programmes Number of hours dedicated to teacher training
	STRUCTURAL CAPITAL
SC5	Teaching management and organization	% of classes with less than 50 students Rate of first-cycle credits in English
SC10 SC11	Effort in innovation Management quality	R&D expenditure Number of R&D projects under development Quality certificates awarded
SC14	Intellectual property	Generation of patents Scientific production
	RELATIONAL CAPITAL
RC1	Efficiency of graduate teaching	Drop-out rate Graduation rate Performance rate
RC2	Student satisfaction	Graduate satisfaction with studies (surveys) % of pre-registered in first option in relation to total number of places on offer
RC3	Graduate employability	Employment rate Time until first employment
RC5	Relations with the business world	Rate of in-company work experience Evaluation of university training by employers Number of collaboration agreements on projects and activities with enterprises
RC9	University’s image	Society’s opinion of the university Doctorate programmes with official mention of quality Rate of students from foreign universities on postgraduate programmes
RC11	Collaboration with other universities	% of teachers received from other universities

The values of the indicators can be calculated and presented for different successive periods, which permits a time-based comparative analysis. The main benefit of using an intellectual capital model is its potential to function as a management tool to help to allocate resources, define a strategy, prioritize challenges, monitor performance and facilitate decision-making.

Conclusions

This article presents a model for measuring the success of reaching university goals through the management of their intellectual capital. Specifically, based on the results of our empirical study, a proposal for an intellectual capital measurement model for Spanish public universities was developed.

Some of the success factors to be considered when drawing up intellectual capital models include: (1) defining strategic objectives as exactly as possible; (2) discussing corporate objectives and strategies; (3) using a non-complex model; (4) drawing up exact, transparent indicators; (5) reducing the number of indicators while making sure that they are significant; (6) initiating a learning process in the interpretation of the indicators; (7) defining a project team with clear responsibilities; (8) ensuring higher management commitment; (9) explaining the benefits of an intellectual capital model to all employees participating and ensuring that they all participate; and (10) initiating a discussion process at all levels of the organization.

The implementation process of our intellectual capital model basically comprises the following phases:

the definition of strategic objectives for intangible elements;

the identification of key intangible elements in a university; and

the selection of indicators and data collection.

Therefore, the first step was to know the mission and strategic objectives of Spanish public universities as a means of identifying the intangible elements needed in obtaining those objectives. Then, a basic task was to find the intangible elements of relevance to universities. In this sense, according to the Spanish public universities’ characteristics, a set of 42 intangible elements was proposed. These intangible elements have been analysed through in-depth interviews with the stakeholders of Spanish public universities. The results obtained show 13 intangible elements considered key in Spanish universities. Agreement on the disclosure of a list of intangible elements means that the university is willing to commit to transparency and accountability, which is a highly positive signal.

Finally, for this new framework to be successful, all of the key intangible elements must be measured in terms of some indicators that tap into the contribution that each will make to the management of intellectual capital at the university. Therefore, a battery of 31 indicators was presented, which were validated in our empirical study. The publication of these indicators would be a healthy exercise in transparency for these institutions in order to facilitate access for their stakeholders to a variety of information relevant to their decision-making. Therefore, these intellectual capital indicators could facilitate benchmarking analysis and comparative studies to help decision-making processes, improve the articulation of public policies and increase transparency in the whole system.

One of the basic premises is that intellectual capital is specific to each organization and its value and relevance depend on its potential contribution to the key objectives of the institution. This means that there is no homogeneous pattern of reporting on the intellectual capital of universities. Consequently, based on the results of our empirical study and in order to obtain a balance between standardization and the idiosyncrasies of each university, our work suggests: first, that all Spanish universities should provide information on a set of basic and general intangibles that are useful for all the institutions; and, second, that every university should present a set of specific intangible elements of the institution, thereby serving the demands of their stakeholders.

As a whole, the results obtained in our research not only advance the research into stakeholders’ expectations in the university community, but also offer useful and specific guidelines for intellectual capital reporting practice in Spanish universities. Our proposed intellectual capital model is intended to be an effectively practical application and easy to use, contributing to greater transparency and comparability in the higher education sector. The intention of our proposal for an intellectual capital model for universities is to contribute to the progressive recognition of intellectual capital as a key strategic factor to confront the competitive challenges currently facing universities. In this sense, the selection of the intangible elements for the model has been made on the basis of the most relevant strategic objectives for Spanish universities. A broad consensus on the relevance of information on intellectual capital according to these objectives is clear from the results of this work. For example, a high percentage (89.1 percent) of those surveyed in our study showed great interest in Spanish universities presenting information on intellectual capital. Also, in general, a high mean value was awarded to the different intangible elements relating to human, structural and relational capital, which shows a strong emphasis on the importance of intellectual capital.

Despite the contributions of this empirical study, the authors recognize several limitations that suggest future lines of analysis. One of the main limitations refers to the sample under study and the structure of the survey. The fact that only members of the Social Councils in Spanish universities were analysed means that there are other groups of users that have not yet been analysed (e.g. investors and suppliers of resources, the media, etc.). Hence, it would be interesting in the future to expand the sample to a broader community of representation.

Some other lines of future research are: a) to compare our proposed intellectual capital indicators with other reports (a benchmarking approach); b) the analysis of the different perceptions of each group of stakeholders regarding the importance of disclosing information about intellectual capital (university, government, teaching staff, students, etc.); and c) the creation of a structural equation model of intellectual capital for empowerment in universities.

Footnotes

Funding

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Yolanda Ramírez is Contracted-Lecturer in the Department of Accounting at the University of Castilla-La Mancha, Spain. Her current research interests include intellectual capital, knowledge management and quality management. Her research work is focused on methods and techniques for building models of measuring and managing intellectual capital in universities. Her work has been published in several international academic journals such as Journal of Intellectual Capital, Knowledge Management Research & Practice, Spanish Accounting Review and International Journal of Learning and Intellectual Capital.

Montserrat Manzaneque is Contracted-Lecturer in the Department of Accounting at the University of Castilla-La Mancha, Spain. Her current research interests include, among others, corporate governance, knowledge management and innovation. Her research work is focused on methods and techniques to explain different models of intellectual capital. Her work has been published in several international academic journals, such as African Journal of Business Management, Studies in Managerial and Financial Accounting and Knowledge Management Research & Practice.

Alba María Priego is Lecturer in the Department of Accounting at the University of Castilla-La Mancha, Spain. Her undergraduate courses focus on cost and financial accounting. Her main research interests are related to the financial analysis of business failure and corporate governance. Her work has been published in international and national journals, such as Academia Revista Latinoamericana de Administración, Internacional Business and Economics Research Journal, Copernican Journal of Finance and Accounting and Revista Pecunica.

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