Performance and planning model for HEIs: A developmental engine for intellectual capital

Abstract

BACKGROUND:

HEIs implement different techniques for the problem of assessing the progress towards the notified goals or the achievements, which is the only way to ensure that the HEIs are functioning properly along the right way or not.

OBJECTIVE:

The aim of this paper is to propose a model for assessing the performance, which may be of interest to institutions, partners, society and students.

METHODS:

In this paper, the technique of performance-related goals of HEIs, and a statistical approach are proposed. The methodology of this paper will manage briefly the issues of the applicability of the technique, how to derive the “goals” for HEI’s, taking into consideration the indicators of the Intellectual Capital (Human, Organizational, and Relational), and how to collect the data from HEIs successfully. The processes of assuring the technique of performance-related goals, deriving and implementing the goals, and the acquisition and testing of data are developed.

RESULTS:

The findings of this paper are in two directions, i.e. in the proposing of a performance model for HEIs which is based on the goals of HEIs; and in the application side, i.e. in the practical results of the evaluation of HEIs and how to clarify the performance of institutions and how to compare between them. The findings show that the practical results are significant, and reliable.

CONCLUSIONS:

This paper develops a significance model for performance appraisal of HEIs, how we can compare between the performance of HEIs, and to rank their performance. The practical results of the model are both accurate and significant.

Keywords

Quality management performance improvement data modelling goal intellectual capital

Dr. Zuhair A. Al-Hemyari currently is a full Professor and expert in research at the University of Nizwa, Oman. He holds a Ph.D. in Mathematical Statistics from The Indian Institute of Technology. His basic research interests are single and double-stage sampling techniques, Bayesian- shrinkage procedures, reliability theory and applications, modelling and optimization, data analysis, knowledge management, intellectual capital and performance indicators. Besides teaching, he has published about 87 papers, participated in 43 international conferences. Formerly, he is a full Professor and expert at the Ministry of Higher Education, Oman. Prof. Zuhair was an Academic Advisor and Project Executor of several projects.

Dr. Abdullah M. Alsarmi is a senior consultant in the management and quality of higher education with Ph.D. in Education from the University of Pittsburgh, PA, USA. He has over 30 years of experience in higher education. He developed interest in performance indicators at institutional, regional, and international levels. He worked for over 16 years as the Undersecretary of the Ministry of Higher Education, a position that has given him a wide exposure and insights to various issues and challenges facing higher education not only at the national level but globally as well. He ran students exchange programs with more than 40 countries. He also chaired the board of the Omani Academic Accreditation Authority, the body in charge of regulating quality of education in Oman.

1 Introduction

The topic of IC has gained a wide importance among international organizations and researchers from various disciplines due to the importance of the topic and its being an important resource for achieving and maintaining the competitive advantages.

Since the last decade, the intellectual capital (IC) has received much attention and is considered as a critical engine for developing countries and societies. Many international organizations and bodies have been interested in the issue of how to develop the intellectual capital; and they have given a great deal of support to HEIs and research institutions which are among the most important centers designed for developing the IC, where the teaching, leaning and research activities significantly affect the IC.

Various international research organizations and many researchers around the world have been proposing models for measuring and developing the IC, and studying the mechanisms and factors that allow the development of the IC. Therefore, many models for developing the quality audit and performance of HEIs have been developed to ensure the continuous development of IC. It is worth mentioning that there are many common bases in the field of strategic management of these two topics. Some of the bases which are common between the two concepts, and can benefit from each other are “resource-based view, knowledge-based view, intellectual capital-based view, dynamic capabilities, and configurational approach” [1].

The IC may be defined as “intellectual resources that have been formalized, captured and leveraged to create assets of higher value” (p. 1) [2]; or “as the economic value of two categories of intangible assets of a company: organizational (structural) capital and human capital” (p. 3) [3]. Thus, based on the above definitions, IC may be categorized to Human Capital, Structural Capital and Relational Capital [4].

We may define the Human, Organizational, and Relational Capitals as given below: Human Capital “is defined as the knowledge that the human resources would take with them if they were to leave the institution”; Organizational Capital “is defined as the knowledge that stays within the institution at the end of the working day. It comprises the governance principles, the organizational routines, procedures, systems, cultures, databases, publications, intellectual property, etc.”; and Relational “is defined as all resources linked to the external relationships of the institution such as customers, suppliers, R&D partners, Government, etc.” [4].

A plethora of IC literature shows that there is a mutual importance of IC and HEIs; and furthermore, several references show that the proposed models for measuring and developing the performance of HEIs of any country are significantly developing the IC and vice versa because of the existence of several common issues and measures between IC and HEIs [5 –12]. At the same time, the IC intangibles have a dual impact on HEIs and the country. The IC intangibles have an important impact on developing the Gross Domestic Product (GDP) of any country [9]. One conclusion regarding the importance of IC in GDP is as follows “the contribution of unmeasured intellectual capital to economic growth was 10% –11% of Gross Domestic Product (GDP) in the United States over the period 1995–2003, rivaling the contribution of tangible capital, and both types of capital contributed equally to labor productivity growth in those years” [4].

In addition, measuring the IC of HEIs has significant importance to the HEIs. Also, the HEIs actively contribute to the development of intellectual capital through the interaction between human capital and other forms of IC through effective knowledge management models and strategies [4 , 13–21].

In fact, HEIs typically have to run many activities regarding the inputs, processes, resources, and outputs, and to be serviced properly. Thus, the strategic plans of HEIs should have different compatible and corresponding compositions and each composition should service part of the corresponding activities.

In addition, the mission of any institution is the fundamental part of its strategic plan, also, the vision, and institutional goals, which are parts of the supporting compositions; whereas goals, objectives, strategies and operation plans form the other parts of “strategic plan” [22 –24]. In addition, strategic plans in HEIs are constructed for either a five or ten-year time-frame, and “goals and objectives form the basis of the portion of the strategic plan most often used as the public document, approved by the governing board, and distributed to the campus community” (p.11) [23].

Moreover, the institutional strategy of any HEI should facilitate the operation of the institution in the direction of enabling it to achieve its policy of making it an effective institution in terms of its development, internal and external audits, fostering its internationalization, and of its influencing and engaging the community. Fielden and Abercromby [25] studied the problem of how the management can affect the institution and the type of priority areas in creating an effective institution. To fulfill this, he proposed the following five main areas: “achievement of goals, development of people, expansion/growth and self-renewal and impact on the wider community” (p.2) [25].

Modelling the goals of HEIs, in order to measure the quality and assess the performance of HEIs is an international phenomenon and used in most international HEIs [26 –38]. In addition, UoB [39] studied the significance relation between leadership and institutional performance/improvement; and its impact on the students in achieving their goals.

The research-based studies on modelling and assessing the goals of international HEIs are quite numerous, and assessing the performance of HEIs through assessing the levels of achieving these goals is an effective and accurate technique. At the same time, there is a big gap in the literature of the above issues in developing countries, i.e. it is very limited, and if it is available it is not implemented or measured [9 , 40–43].

Throughout the world, the issue of structuring the goals of HEIs is one of the important steps in establishing the HEIs, and, as mentioned earlier, it is a part of any institutional strategy [25, 44]. Moreover, structuring the goals of HEIs is widely used and the levels to achieve these goals are required for the processes of auditing and development. It is also required for the continued advancement of institutional performance, which gives rise to the educational accreditation [13].

Moreover, setting and performing educational goals within the strategic plan of any HEI has a dual importance: first for itself and second for utilizing the benefits of goals setting aimed at improving the institutional environment, inputs, outputs and processes. It is not possible to do so without a precondition, i.e. assessing the progress towards the declared goals (ibid).

Thus, the issue of robust and accurate assessing of the progress towards the notified goals or their achievements is the only way to ensure that the HEIs are functioning properly along the right path (ibid).

A study called “Pathways to Success”, was conducted for the US Government by the “Advisory Committee on Student Financial Assistance” regarding the 2020 goals [45]. In this regard, many issues in his paper were explained. One of these issues was “how to measure progress toward and the achievement of those goals?” (p. 9) [45].

Thus, the necessity of the topic of this paper comes from the success of the above international applications of the technique as well as national needs in regard to filling the gaps in the technique of performance-related goals of HEI literature in higher education. In addition, studying the performance of HEIs in developing countries through the evaluation of the learning goals has a number of significant aims [9 , 47].

This paper is intended as a main topic for management-stream, which emphasizes a managerial practical side of quality. At the same time, it studies a very important issue in institutional strategy, which emphasizes the overall performance and performance of HEIs goals. However, it serves as a reference paper on statistical applications which contains a number of statistical tools for accuracy, data collection and data cleaning.

The writing of this paper has the following mode: The literature of goals of HEIs are explained in Section 2. In Section 3, the objectives of this paper are given. Section 4 has focused on the tools and methods used in this paper. The proposed goals are explained in Section 5. The ways of data collection are demonstrated in Section 6. The proposed rules of data detecting and cleaning are confirmed in Section 7. In Section 8, the practical results of the overall performance and HEIs goals are discussed. Comprehensive statistical testing of the practical results is performed in Section 9. The concluding remarks, expected problems and dilemmas are discussed in Sections 10 and 11 respectively.

2 The importance of IC in HEIS: Review of literature

The literature of IC practices of HEIs and the goals of HEIs as a technique for measuring the performance of HEIs are huge, and some of them are to be reviewed in this Section.

Without any doubt, the existence of IC, and the role of incubating IC institutions (HEIs, research centers,...) in enhancing its output, will inevitably lead to playing a fundamental role in developing the performance of institutions.That is the reason why we can see several important projects in IC and new models for measuring IC for different sectors proposed by many pioneer international organizations (foe example the World Bank, OECD, OEU,...) and European HEIs (for example Sweden, Denmark, Austria and Spain) because the IC receives great attention. In addition, the existence of an interrelated relationship between IC and the performance of HEIs is well organized in most international HEIs [2–21 , 48–50]; and most of the international institutions believe in the possibility of achieving their institutional goals through the development of IC and their performance.

In order to clarify the strong relationship between IC and HEIs, it is important to be aware of the well known essential role of HEIs in intangible activities, where the academic staff of HEIs are storehouses of knowledge and information, and that they have a role in transmiting these to students and to the wider society; and that there are several essential concepts and institutional processes in HEIs, such as the input and output of HEIs, the goals of HEIs, policies, intellectual activities and the processes of contributing knowledge, skills and personal development to students and employees. In addition, the institutional plans and processes through which they seek to implement the institutions’ goals in producing, transferring and disseminating the knowledge, and contributing actively to supply the labor markets with graduates with knowledge, i.e., developing the human resources for society, constitute important components of the intellectual capital.

The general importance of measuring and enhancing the IC for the economic growth is explained in Section 1. The above cited authors have discussed several important factors of IC for the HEIs. Some of these are:

“it can help to identify strengths and weaknesses within the public organization, because IC management implies a categorization of resources and capabilities”;

“it can help to reveal the current state of the university's mission and the level of achieving its institutional goals, because IC reports show the exact value added by the organization's intangible assets and how the results of IC reports are aligned with its institutional mission and goals”.

“it can be used as a general controlling and monitoring instrument, because IC is a set of indicators that can be communicated and can thus encourage discussion on what has to be managed”.

“it can achieve greater information and transparency about the use of public money due to the continuous process of both academic and financial accountability”.

“it can help to formulate the institutional strategy”;

“it can communicate effectively with external shareholders”.

“it can help to compete for funding; because of the shortage of funding HEIs are competing and under greater pressure to communicate their IC results”.

“it can lead to the enhancement of the performance of HEIs and vice versa”.

It is well known that the mission of an HEI is the foundation of the strategic plan. The vision and the institutional goals and values, which are essential and important parts of the supporting compositions, are vital components in any given institution’s successful functioning. In addition, goals, objectives, strategies and operation/ enforcement plans are parts of any strategic plan of HEIs.

In order to evaluate the quality, interpretation and achievement of any HEI, the goals of HEIs have to be identified and studied [9 , 40–43]. In this Section, some papers on refining the goals of HEIs are reviewed.

It may be mentioned here that the issue of developing the performance, resources and the management processes of the HEIs has been considered by several other authors from different directions (see for example, [51 –61]).

The “Council of European Ministers for Education” met in 2001 to approve the proposed strategic goals for European HEIs which denominate “the four major World Declaration objectives” [25]. The “four major World Declaration objectives” and some strategic goals of several HEIs are given in Table 1.

Table 1
Examples of strategic goals/ objectives of HEIs

Author Identified Strategic Goals

[47] “Statewide Campus”, “Compelling Learning Experience” and “Top-Tier University”.

[13] “Promotion of access to higher education based on merit, and, addressing the areas of equal opportunity; seamless and open access to higher education and assistance to minorities and the disadvantaged”; “Modernization of higher education systems with a focus on access rates and overall participation rates; funding for research and development and review of international trends including fees and mobility trends”; and “closer linkages with society, especially with the world of work; lifelong sources of professional training and the development of entrepreneurial skills –higher education to turn out job creators, and, social responsibility”

[58] “To develop relevant programs that will equip students with lifelong decision making, planning and management skills”; “To ensure an effective and efficient system-wide approach to student access, success and retention by assisting faculties and cooperating with related institutional units”; “To develop relevant programs that will equip students with life-long career decision-making, planning and management skills”; “To provide guidance &support to all WSU faculties in designing &managing academic programs” and “To promote excellence in learning and teaching by means of integrated information and communication technology”.

[37] “Promote academic quality by building and supporting a distinguished faculty”; “Provide opportunities for a public university education and contribute to economic and cultural development”; “Provide a premier student-centered, educational experience that fosters retention and success”; “Enrich our learning and working environment by attracting and supporting a more diverse faculty, staff, and student body” and “Develop and manage human, financial, physical, and technological resources effectively, efficiently, and ethically to support the university’s mission”.

[59] “To develop our capacity to generate and share knowledge in the UK, Europe, and globally, ensuring significant contributions to public policy-making and economic growth”, “To work effectively with other institutions and organizations, where such partnerships can lead to outstanding research and teaching”, “To enhance structures for collaboration across departments, colleges, and the University”, “To fulfill the aims that no potential student should be deterred from applying to Oxford by financial or other barriers and that no student’s success should be hampered by financial difficulties”, “To ensure, through a commitment to the personal education of each student, a quality of education and experience which enables students to apply the values, skills, and intellectual discipline they have acquired in their future lives and careers, and which generates a lifelong sense of connection with Oxford”, “To contribute effectively to the cultural, social, and economic life of the city of Oxford and the Oxfordshire region”, and “To recruit and retain the best academic staff and ensure that under-represented groups have equality of opportunity in recruitment, personal development, and career progression in all areas of employment in the University”.

[60] “Sustainable comprehensive internationalization as an integral part of the university’s mission and strategic plan”; “Promote greater involvement of all students in significant international education experiences”; “Create and maintain a stimulating and supportive academic and cultural environment for international students and scholars”; “Increase the international activity of faculty and professional staff”; “Internationalize the curriculum”; “Assure research and scholarship pertaining to international matters permeates disciplinary and interdisciplinary fields”, and “Ensure international awareness is an integral part of appropriate outreach and extension activities”

[42] “To continue building Keele as a broad-based research-led University of about 13000 students recognized internationally for excellence in education, research and enterprise”; “To deliver international excellence and impact in focused areas of research”; “To contribute positively to the society, economy, culture, health and well-being of the communities we serve”, and “To promote environmental sustainability in all that we do”.

[41] “Establish a centralized location for plans, programs, and activities that include extension activities in Frankfort city and the Frankfort area”; “Augment the University’s community relations role in Frankfort and the Commonwealth”; “Support the University’s brand by deepening business and educational relationships with additional Frankfort businesses and government agencies”; “Support the University’s goals 2 and 3 by establishing a unit that provides financial returns to the University”, and “Support the University’s other strategic goals by enhancing the impact of the University in the community, thus, improving student enrollment and the quality of KSU’s campus life”.

[34] “Knowledge and learning are for everyone”; “Openness enhances scientific research and collaboration”; “Our University is the best place to study and work”; “Our University is a leader in responsibility and sustainability”.

Author	Identified Strategic Goals
[47]	“Statewide Campus”, “Compelling Learning Experience” and “Top-Tier University”.
[13]	“Promotion of access to higher education based on merit, and, addressing the areas of equal opportunity; seamless and open access to higher education and assistance to minorities and the disadvantaged”; “Modernization of higher education systems with a focus on access rates and overall participation rates; funding for research and development and review of international trends including fees and mobility trends”; and “closer linkages with society, especially with the world of work; lifelong sources of professional training and the development of entrepreneurial skills –higher education to turn out job creators, and, social responsibility”
[58]	“To develop relevant programs that will equip students with lifelong decision making, planning and management skills”; “To ensure an effective and efficient system-wide approach to student access, success and retention by assisting faculties and cooperating with related institutional units”; “To develop relevant programs that will equip students with life-long career decision-making, planning and management skills”; “To provide guidance &support to all WSU faculties in designing &managing academic programs” and “To promote excellence in learning and teaching by means of integrated information and communication technology”.
[37]	“Promote academic quality by building and supporting a distinguished faculty”; “Provide opportunities for a public university education and contribute to economic and cultural development”; “Provide a premier student-centered, educational experience that fosters retention and success”; “Enrich our learning and working environment by attracting and supporting a more diverse faculty, staff, and student body” and “Develop and manage human, financial, physical, and technological resources effectively, efficiently, and ethically to support the university’s mission”.
[59]	“To develop our capacity to generate and share knowledge in the UK, Europe, and globally, ensuring significant contributions to public policy-making and economic growth”, “To work effectively with other institutions and organizations, where such partnerships can lead to outstanding research and teaching”, “To enhance structures for collaboration across departments, colleges, and the University”, “To fulfill the aims that no potential student should be deterred from applying to Oxford by financial or other barriers and that no student’s success should be hampered by financial difficulties”, “To ensure, through a commitment to the personal education of each student, a quality of education and experience which enables students to apply the values, skills, and intellectual discipline they have acquired in their future lives and careers, and which generates a lifelong sense of connection with Oxford”, “To contribute effectively to the cultural, social, and economic life of the city of Oxford and the Oxfordshire region”, and “To recruit and retain the best academic staff and ensure that under-represented groups have equality of opportunity in recruitment, personal development, and career progression in all areas of employment in the University”.
[60]	“Sustainable comprehensive internationalization as an integral part of the university’s mission and strategic plan”; “Promote greater involvement of all students in significant international education experiences”; “Create and maintain a stimulating and supportive academic and cultural environment for international students and scholars”; “Increase the international activity of faculty and professional staff”; “Internationalize the curriculum”; “Assure research and scholarship pertaining to international matters permeates disciplinary and interdisciplinary fields”, and “Ensure international awareness is an integral part of appropriate outreach and extension activities”
[42]	“To continue building Keele as a broad-based research-led University of about 13000 students recognized internationally for excellence in education, research and enterprise”; “To deliver international excellence and impact in focused areas of research”; “To contribute positively to the society, economy, culture, health and well-being of the communities we serve”, and “To promote environmental sustainability in all that we do”.
[41]	“Establish a centralized location for plans, programs, and activities that include extension activities in Frankfort city and the Frankfort area”; “Augment the University’s community relations role in Frankfort and the Commonwealth”; “Support the University’s brand by deepening business and educational relationships with additional Frankfort businesses and government agencies”; “Support the University’s goals 2 and 3 by establishing a unit that provides financial returns to the University”, and “Support the University’s other strategic goals by enhancing the impact of the University in the community, thus, improving student enrollment and the quality of KSU’s campus life”.
[34]	“Knowledge and learning are for everyone”; “Openness enhances scientific research and collaboration”; “Our University is the best place to study and work”; “Our University is a leader in responsibility and sustainability”.

3 Research objectives

In this research, our objectives are [to]:

discuss the most settled goals for several HEIs,

propose the technique of performance-related goals for assessing HEIs,

examine and realize the mechanisms of refining the “goals” of HEIs,

clarify the strong relationship between IC and the performance of HEIs,

estimate and discuss the performance of the private HEIs in accordance with the overall performance and the performance of each goal, and

study the practical results and determine their level of “reliability”, “efficiency”, “significance, “relationship” and “solidity”.

discuss some of the expected problems.

4 The tools and methods

4.1 Assuring the technique of performance-related goals

Several international practices with respect to the methods of monitoring and evaluating the performance of HEIs numerically were studied. It may be worthwhile mentioning that the national comprehensive exercises are not available. After a long debate, it was eventually agreed that the technique of performance-related goals of HEIs is preferred.

As it was mentioned in Sections 1 and 2, the issue of structuring the goals of HEIs in any institutional strategy is well-known, and assessing the performance of HEIs through assessing the levels of achieving these goals is an international phenomenon and used for auditing and development. Nevertheless, we believe that it is necessary to obtain the views of an elite academic body on their understanding of this technique and its applicability in Oman.

In order to assure the technique of performance-related goals of HEIs, the main question related to the proposed technique is developed and split into four secondary questions, each of which are to be assessed. The main question is,

MQ: Based on your experience, what is the importance of evaluating the performance of HEIs in terms of assessing the level of achievement of their goals?

For the problem of assessing the main and secondary questions, a survey was prepared, edited and disseminated to 77 teaching staff from HEIs to gauge the secondary questions. The secondary questions are:

SQ1: Based on your experience, what is the possibility of evaluating the performance of your institution in terms of assessing the level of achievement of its goals?

SQ2: Based on your experience, what is the possibility of splitting the goals of your institution into objectives in order to assess the level of achievement of the goals?

SQ3: Based on your experience, what is the possibility of splitting the objectives of your institution into indicators in order to assess the level of achievement of the objectives of your institution?

SQ4: What is the possibility of measuring the indicators of your institution in order to evaluate the performance of your institution?

In order to measure the respondents’ opinion, the five-level Likert scale: (1) Strongly disagree; (2) Disagree; (3) Neither agree nor disagree; (4) Agree; (5) Strongly agree, is used in this survey. The survey was designed, evaluated and disseminated to a sample of 77 senior “academic staff” from most of the HEIs in Oman. The completed surveys were collected from 64 respondents and the results of the surveys were analyzed.

For the purpose of clarifying the results of the survey, it is necessary to rely on the answers of the respondents in calculating the weighted averages and percentages, because they are accurate, simple and understandable measures. The number of respondents to the survey, weighted average and the proportion based on the above scale is given by Table 2 below,

Table 2
The number respondents of the survey, weighted averages and proportions based the five-level Likert scale

SQ Strongly disagree Disagree Neither agree nor disagree Agree Strongly agree Averages Percentages

SQ1 0 1 0 16 58 4.62 92.73%

SQ2 2 1 1 22 49 4.42 88.31%

SQ3 1 2 2 32 38 4.27 85.46%

SQ4 1 2 2 32 38 4.27 85.46%

SQ	Strongly disagree	Disagree	Neither agree nor disagree	Agree	Strongly agree	Averages	Percentages
SQ1	0	1	0	16	58	4.62	92.73%
SQ2	2	1	1	22	49	4.42	88.31%
SQ3	1	2	2	32	38	4.27	85.46%
SQ4	1	2	2	32	38	4.27	85.46%

It may be worthwhile mentioning that the weighted average and the proportion of each question are calculated by the equations:

Weighted Average = {(1x number of respondents of Strongly disagree) + (2 x number of respondents of Disagree) + (3 x number of respondents of Neither agree nor disagree) + (4 x number of respondents of Agree) + (5 x number of respondents of Strongly agree)} / 77.

And

Percentage = { /(77x5)}x100

Table 2 shows that the weighted averages (and the proportions) of the respondents rating of the secondary questions are equal respectively to 4.62, 4.42, 4.27 and 4.27 and the corresponding percentages of the respondents rating of the same secondary questions are equal to 92.73%, 88.31%, 85.46% and 85.46% respectively. These results show a high level of acceptance of the implementation of the proposal of the technique of performance-related goals of HEIs.

4.2 Deriving and implementing the strategic goals

In the last Section, the survey shows that the proposal of the technique of performance-related goals of HEIs has been assured. In this Section, the processes of refining and implementing the goals are to be discussed.

Several strategic goals of international institutions are reviewed in Section 2. For measuring the performance, progress and achievement of HEIs in Oman, the goals of HEIs have to be derived and should be confirmed. The methodology of this paper will manage briefly the issues/ problems of how to derive the goals for HEIs from some resources and how the goals and the process can be implemented. The following steps were taken:

In order to propose goals for HEIs, several papers on how to write the performance-related goals/objectives of HEIs were studied. It is worth mentioning that in this paper we have considered the following two principles in constructing the goals:

The Goals of HEIs in Oman should be drawn from the national policy of the Sultanate of Oman [38]. It was simulated by global practices and has to be coordinated with the vision and mission of HEIs.

Goals have to be wide or bulk, and thus they are not easy to be gauged [14 , 61].

A set of goals have been proposed on the bases of The Education Strategy –2040 of Oman. Moreover, the proposed set of goals was susceptible to a lengthy debate with the stakeholders of HEIs.

In order to study the characteristics of the proposed goals (“specific”, “clarity”, “importance” and “approbation” of goals, the proposed set was investigated, reviewed by a group of “academic staff” from HEIs and revised in [29, 30].

In order to handle the second issue/ problem of the research, i.e. how the goals and the process can be implemented, the following steps have been taken:

Each goal was divided into many statistical indicators. It may be worthwhile mentioning that the goals were refined to 116 statistical indicators (ibid).

The total weight of overall performance and the weight of goals, and the scale of measurements of each goal/indicator have been proposed and discussed with many experts and HEIs, and thus subsequently modified. It may be worthwhile mentioning that HEIs were divided into two categories (university colleges and colleges) on the bases of many important factors. The weight of the overall performance was assigned (1000 points) for each of the HEIs (university college (UC)/college (U)), and the weights of the goals for university college/ college are given in Table 3.

Table 3
Weight of Goals (w(g_j))

G U C C

G1 200 200

G2 450 550

G3 100 50

G4 100 50

G5 150 150

Total 1000 1000

G	U C	C
G1	200	200
G2	450	550
G3	100	50
G4	100	50
G5	150	150
Total	1000	1000

4.3 Population and sample

The framework of this research constitutes the total number of government and private HEIs in Oman. Typically, the “population” should be chosen on the basis of the framework of the research, and thus the framework of the research contains all HEIs in Oman (10 government HEIs, 6 government technical colleges, 15 government institutes of health, and 40 private HEIs). In this research, because of the bulk and diversity of the population, the private HEIs are identified as the population of the study. It may be worth mentioning that 6 HEIs were exempted because they were only just started at the time of implementation and 4 did not support the data of this research.

In order to compute the qualitative indicators of the goals, the percentage of partecipants) from students/academic staff) from the population of HEIs is about 11%, i.e the size of the sample is 4571 students and academic staff members which consists of 3689 students and 882 academic staff members. It may be worthwhile mentioninng that the population of this study is 42188 (40281 students and 1907 academic staff); and the sample size of the academic staff is very high)about 46%) because the number of academic staff in some academic programs is very small, and it is not possible to take a sample from it, and for the purpose of studying their opinions, the majority of them were selected in the sample.

In addition, the total sample of this study is divided into sub-samples (stratified random samples) taken from each institution/program randomly. It may be remarked here that, the MoHERI has data bases for collecting diferente types of data from the private and goverment HEIs regarding the students, non-acdemic staff, academic staff, resources, activities, etc.

Regarding the 10 non-participated HEIs in this study. it was mentioned that 6 HEIs were exempted because they were only just started at the time of implementation, and 4 institutions have apologized for not participating, because of the lack of time and the lack of statisticians to help in collecting the data of the indicators which were required for the study.

It is useful to clarify that there are no actual national studies related to the problem of measuring the performance of HEIs in Oman that included the process of collecting data from the HEIs.

It may be worth mentioning, because of this research is dealing with the derivation of goals of HEIs, the development of quantitative indicators, sampling and data collection technique, that a comprehensive plan has been developed that explains some of its steps through the Sections of this paper and includes the following:

“Identify potential or available sources of data”,

“Generate a list of data collection options”,

“Decide on an appropriate data collection option”,

“Select and develop a data collection tool”,

“Develop and implement a system for collecting data on a continuing basis” (see [62], page 7),

Develop some accurate equations for calculating the performance, and

Decide on appropriate statistical measures and techniques to analyze the performance.

5 The proposed goals

In the last Section, the proposal of the technique of performance-related goals of HEIs was assured through the main and four secondary questions, and the processes of refining and implementing the “goals” of HEIs of Oman were discussed.

This section provides the derived goals, which represents the second stage of the methodology. The description of each goal is as follows.

“To promote access and admission to higher education”. It may be possible to describe access and admission in two dimensions: “through participation if the policy of ensuring that students are able to enter and commence study at an institution of higher education is ensured. A&A with success goes a step further, defining true access as completion of a degree or certificate program that prepares one for a vocation” [45].

“To develop a culture of academic excellence and achievement among undergraduate and graduate students”. Academic excellence may be described as “excellence in teaching and learning in the context of an overall case for excellence, and will show exceptional quality over a range of activities. Promotion will be achieved on the basis of outstanding contributions to leadership in teaching and learning”. “Excellent performance” in teaching and related administration is also an essential prerequisite” [26–30 , 39].

“To form themselves into a centre which has the highest academic standards and excellence of research”. Excellence in research should be “in the context of an overall case for excellence, and will demonstrate work of originality which has made an observable impact on the subject”.

“To enhance institutional internationalization”. The typical and common (“widely-cited”) definition of “higher education internationalization” is “the process of integrating an international / intercultural dimension into the teaching, research and service functions of the institution” [22]. It may also refer to “the process of integrating the institution and its students, faculty and staff into a globalizing world” [22].

“To promote community engagement”. “Community engagement” means the level and variety of connections between HEIs and the community. It “describes collaboration between institutions of higher education and their larger communities (local, national, global) for the mutually beneficial exchange of knowledge and resources in a context of partnership and reciprocity” [61].

5.1 Remarks

In this paper there are five goals to be measured and studied, where each goal is split into several indicators. In fact, each goal contains some indicators related to IC. Specifically, and based on data availability in HEIs, there are 15 indicators developed about the Human Capital (Average class size; Student-Instructor ratio; Student-Administration staff ratio; IT support staff in relation to all students and staff; Total number of computers in relation to all students; Ph.D. holders in relation to total academic staff; Total number professors and associate professors in relation to total academic staff; The total number of funded research proposals in relation to total research projects and papers of the institution; The institution’s budget allocated to conference participation in relation to total budget; The institution’s budget for academic staff training and development in relation to total budget; The institution’s budget for non-academic staff training and development in relation to total budget;. . . etc), 24 indicators about Organizational/Structural Capital and 21 indicators about Relational Capital.

Some of the proposed IC models for HEIs in the world with applications are:

Fazlagić, [14] (is based on Human Capital, Structural Capital and Customer Capital); Leitner, et al., [15]; Leitner [16]; Sánchez, et al., [4 , 19]; Sánchez-Torres et al., [20]; Chu et al., [13]; Malhotra, [3]; Al-Hemyari and Al-Sarmi [9] (are based on Human Capital, Structural Capital and Relational Capital) and Najar, et al., [17] (is based On Human Capital, Organizational Capital, Technological Capital, and Relational Capital).

Most of the proposed IC models in the literature of IC have neither given nor implemented any of the numerical results of the IC indicators.

6 The acquisition of data

It is well-known that “one of the connections between strategic planning and continuous quality improvement is the reliance on data as the basis for decision-making” [32] (p. 8). At the same time, one of the well-known problems with HEIs in the developing countries is the lack of capable databases. In fact, it was planned that the process of acquisition of the data from HEIs would be by using successive steps. Therefore, we had used the following main ways:

The Statistical System of the Ministry of Higher Education (MoHERI) contains different information on students, academic staff, non-academic /administrative staff, many institutional activities; national/international patents, student appeals, number of text books, building areas, laboratories’ area, library area, student hostels, sport fields, . . . etc. This information is used to check the second method of collecting data.

The second method of collecting data was concerned with self- reported data, data which is collected and submitted by all private HEIs. This channel provided data for most of the quantitative indicators. The implementation of this channel involved the following sub-steps:

A workshop for all private HEIs was organized to satisfy the intentions:

Discussing the proposed package of goals, objectives and performance indicators.

Identifying a contact person at HEIs as the point of connection for the research.

Distributing the list of PIs to all HEIs, where the precise form of the data collection has been specified for each of the PIs.

Finally, the self-reported data were subject to many actions of data cleaning, after which they were discussed with the contact persons of the HEIs.

In order to obtain a high level of interaction and co-operation, completion and submission of the self-reported data, the HEIs were given sufficient time to submit the self-reported data.

In this research whenever data is required to be collected for the qualitative/ indicators, the sample size taken represents about 11% of the population. It may be noted here, that the surveys were designed in [26] and applied in this research.

Remark: It may be noted here, that the raw data of the 116 indicators from HEIs are collected and available on the website of MoHERI Oman (and submitted to the editor).

7 Data detecting and cleansing

The analytical process of the data collected in this project comprises many steps, whereas the data cleaning constitutes an important and major step of the process. As mentioned earlier, the process of data acquisition from HEIs has used two channels. In this research, the most proposed indicators are quantity indicators; and because of the lack of databases of the HE sector; the self-reported data was mainly used.

For the problem of analyzing the data precisely, an appropriate screening process, controlling sampling error and non-sampling error (coverage error, non-response error, response error and processing error) have to be considered and developed ([63]).

For the problem of controlling the sampling and non-sampling errors, the following actions were taken and to be discussed briefly:

To minimize the response errors in the self-report data of private HEIs, the definitions of indicators, scale of measurements and the required data for indicators of each goal were supplied as a glossary to all private HEIs.

To minimize the non-response error, i.e. the problem of failure to get data from the HEIs; direct communications and regular meetings were convened between the contact persons and the research team.

In the case of collecting data for qualitative indicators, the coverage error and sampling error had to be controlled. For this purpose, the following actions were applied: selecting samples from all academic programs, representing all the study variables (gender, year of study, age of student, level of study etc), implementing a random stratification protocol and using larger sample sizes, whenever possible.

The data was checked by using many measures of exploratory data mining [63]. Also, any activity with anomalous data was diagnosed and isolated for further clarification with HEIs.

The data was compared between HEIs (pair wise and multiple; within HEIs) and a cross-check was used, where possible.

8 The practical results

In previous Sections the acquisition of data and data detecting and cleansing, were explained respectively. As mentioned earlier in previous Sections, each goal was divided into many components/indicators [29, 30], and the row data of the 116 Ind (indicators) from HEIs are collected and available on the website of MoHERI, Oman (and submitted to the editor).The final results (estimators) of the indicators, goals and of the overall performance of each of the HEIs are obtained by combining the results of the related indicators, weights (Table 3) and applying the index-equations 1–3 below, given in Tables 4 5 and presented in this Section.

Table 4
shows that the overall performance of HEIs

HEIs $\hat{OP}$ HEIs $\hat{OP}$ HEIs $\hat{OP}$

HEI 1 608.719 HEI 11 696.934 HEI 21 503.587

HEI 2 459.629 HEI 12 536.633 HEI 22 577.969

HEI 3 467.586 HEI 13 539.765 HEI 23 602.346

HEI 4 467.114 HEI 14 585.252 HEI 24 483.139

HEI 5 628.376 HEI 15 524.222 HEI 25 536.420

HEI 6 428.629 HEI 16 541.652 HEI 26 697.439

HEI 7 478.933 HEI 17 438.247 HEI 27 458.341

HEI 8 594.681 HEI 18 562.834 HEI 28 540.494

HEI 9 645.033 HEI 19 589.829 HEI 29 584.964

HEI 10 634.729 HEI 20 575.875 HEI 30 490.052

Average 548.029

HEIs	$\hat{OP}$	HEIs	$\hat{OP}$	HEIs	$\hat{OP}$
HEI 1	608.719	HEI 11	696.934	HEI 21	503.587
HEI 2	459.629	HEI 12	536.633	HEI 22	577.969
HEI 3	467.586	HEI 13	539.765	HEI 23	602.346
HEI 4	467.114	HEI 14	585.252	HEI 24	483.139
HEI 5	628.376	HEI 15	524.222	HEI 25	536.420
HEI 6	428.629	HEI 16	541.652	HEI 26	697.439
HEI 7	478.933	HEI 17	438.247	HEI 27	458.341
HEI 8	594.681	HEI 18	562.834	HEI 28	540.494
HEI 9	645.033	HEI 19	589.829	HEI 29	584.964
HEI 10	634.729	HEI 20	575.875	HEI 30	490.052
Average	548.029

Table 5

Shows the performance of each goal of HEIs

HEI	G1	G2	G3	G4	G 5
1	138.8	285.72	52.2	65.4	66.6
2	104.4	261.23	25.4	6.4	62.2
3	111.8	264.99	25.4	6.4	59
4	111.8	260.31	25.4	10.6	59
5	161.8	382.98	17.4	4.8	61.4
6	105.8	256.83	9.6	15.6	40.8
7	103.6	293.53	22.4	3.2	56.2
8	156.2	244.28	58	51.8	84.4
9	133	358.03	29.4	33.2	91.4
10	165	249.53	66	56.6	97.6
11	150.4	372.13	39.2	27.2	108
12	109	265.63	39.6	48	74.4
13	125.8	264.97	40	43.2	65.8
14	112.8	345.25	28.4	22.8	76
15	141.2	236.62	39.4	31.6	75.4
16	133	317.85	5.6	14.4	71
17	150	183.05	14	31	60.2
18	134.2	334.83	29	17.4	47.4
19	163.4	229.23	39.6	69	88.6
20	154.8	240.28	75.6	38.6	66.6
21	110.4	307.99	7	22.4	55.8
22	142.8	362.17	15.6	11.6	45.8
23	82	399.55	26.8	37.2	56.8
24	124.2	278.14	19	8.4	53.4
25	131.8	316.02	4.2	2.4	82
26	189	307.24	56.2	66	79
27	154	222.94	27	0	54.4
28	154.6	226.49	52	47	60.4
29	152.4	335.36	11.8	26.2	58.4
30	163.2	224.05	31.6	13.8	57.4
Mean	135.71	287.58	29.35	27.74	67.18

The above measures of HEIs were achieved by SPSS Statistics-22 and hereby given as numerical values in Tables 4 5.

8.1 The practical results of the overall performance

In order to compute the overall performance of HEIs, the performance of each goal in any of the HEIs, and the “average” (estimated mean) of each goal, three equations have been developed are explained below.

The overall performance of an HEI j is computed by the following equation, $\begin{matrix} {\hat{OP}}_{j} & = \sum_{i = 1}^{5} P (g_{ij}) \times w (g_{i}), i = 1, 2, . . . 5, \\ j = 1, 2, . . . 30, \end{matrix}$ (1)

where P(g_ij) represents the performance of each goal (G) i in institution j and w(g_i) represents the corresponding weight (Table 3). The average (estimated mean) of the overall performance is computed by, $\begin{matrix} \bar{OP} = (\sum_{j = 1}^{30} {\hat{OP}}_{j} / 30) = \\ (\sum_{j = 1}^{30} \sum_{i = 1}^{5} P (g_{ij}) \times w (g_{i})) / 30 . \end{matrix}$ (2)

Finally, the “average” (estimated mean) of each goal (G) is computed by, ${\bar{P}}_{i} = \sum_{j = 1}^{30} P (g_{ij}) / 30, i = 1, 2, . . . 5, j = 1, 2, . . . 30 .$ (3)

Tables 4 5 show that the overall performance of HEIs and the performance of each goal for HEI_j, j = 1,2,. . . ,30.

It has been noticed from Table 4 that the overall performance of HEIs and the performance of each goal varied from 428.630 to 697.439.

The average of overall performance as a national standard for private HEIs is equal to 540 out of 1000. This shows that the national value was an average.

Based on the same Table, the overall performance of the HEIs may be classified into four sets: the first set: (below average < $\hat{μ}$ ): {HEIs: 2, 3, 4, 6, 7, 12, 13, 15, 16, 17, 21, 24, 25, 27, 28, 30}, the second set: (were “average and above average” ([ $\hat{μ}$ -Std. Deviation≤ ${\hat{OP}}_{j}$ < $\hat{μ}$ + Std. Deviation])): {HEIs: 1, 8, 14, 18, 19, 20, 22, 23, 29}, the third set: (good ([ $\hat{μ}$ + Std. Deviation≤ ${\hat{OP}}_{j}$ < $\hat{μ}$ + 2 Std. Deviation])): {HEIs: 5,9,10} and the fourth set: (very good ([ ${\hat{OP}}_{j}$ ≥ $\hat{μ}$ + 2Std. Deviation])): {HEIs: 11, 26}.

8.2 The practical results of the goals

iv.
The average and results of G 1 are shown in Table 5. The average was 135.707 and performance of most HEIs was≥average and varied from 82 to189.

The performance of HEIs in accordance with G 2 was high (287.57) and varied from 183.05 to 399.55 and the performance of half of the HEIs was good (Table 5).

We observed that the performance of most of HEIs in accordance with G 3 was below the average (29.353) and ranged from 7 to 75.5 (Table 5).

The results of Goal 4 for the thirty HEIs are given in Table 5. The Table shows that the performance of 13 HEIs was equal to or greater than the average (27.740) and the results of this Goal ranged from 0 to 68.

The performance of Goal 5 for the 30 HEIs, is given in Table 5. Table 5, shows that the performance ranged from 40.800 to 108 and that there were 12 HEIs which had performance equal to or greater than to the average (67.180).

The results show that the performance of IC indicators as well as the results of the Human, Organizational, and Relational Capitals of HEIs is almost average, which is quite satisfactory if we know that the attention paid to this issue in most developing countries is simple.

Regarding the HEIs, 15 out of 30 HEIs achieved performance average or more than average in overall IC indicators, and another 15 achieved below the average in overall IC indicators.

9 Statistical analysis of the practical results

The theoretical bases of qualitative measurement and quality processes of any practical results require testing, screening, evaluating, and addressing questions such as: How stable are the measurement scales? How efficient are our estimation processes? How good and accurate are the practical results?

For the studying of the problems which are addressed in the above questions, i.e. to emphasize the efficiency, significance, relationship, substance and solidity of the practical results, the following statistical tests and methods were demonstrated.

9.1 Hypotheses testing

For the problem of investigating the variation in the practical results of the overall performance and each goal, the T-test can be developed. It is well-known that the T-test is applied to determine the significance of the differences in a sample. In addition, the data should include one continuous variable, which is similar to what we have in this research, i.e. 30 values for overall performance of HEIs and the performance for each goal of 30 HEIs. Moreover, one of our purposes is to find out the significance of the differences between the results of the HEIs.

The hypothesis in a T-test is that the results of the overall performance and all goals of the 30 HEIs are being compared so as to achieve the same results. The hypothesis is denoted by H₀: μ _i = W_i, against H₁: μ _i ¬ =W_i, i = 1,2,3,4,5,6 where μ_i represents the mean of i^th factor (the overall performance and the five goals) and W_i, represents the test value (weight) of each factor (see Table 3).

The analytical results of the T-test for the overall performance and the five goals show that all the above null hypotheses are rejected (Sig. values (p) = 0.000). The results show that there were significant differences among the results of the 30 HEIs with respect to the overall performance and the five goals.

9.2 Correlation coefficients analysis

In this section, we are concerned with detecting the level of the simple correlation between the overall performance and each goal of the results of the 30 HEIs. In other words, to be sure that there is a significant relationship between the overall performance and each goal or not, the correlation coefficients (η) were computed and tested by the following hypothesis, H₀:η _oxi = 0, against H₀:η _oxi ¬ =0, where 0 represents the overall performance and i represents the i^th goal. The results of the Pearson correlation coefficients between the overall performance and each goal are equal to 0.467,0.564,0.465,0.557, and 0.650 respectively with the significance values (p) ranging from 0.000 to 0.008. It is realized that there were good values of η _oxi and there were highly significant relations between the overall performance and the results of each “goal” of the 30 HEIs.

It is good to have a high and significant correlation coefficient between the results of each goal and the overall performance of HEIs. Also, the above results of the correlation coefficient are good, especially with highly significant probability to show that the meanings of these results are substantial. At the same time, it is not possible statistically to obtain a very high correlation coefficient because the combined goals constitute the general performance, and this is what Table No. 7 shows in its last line.

9.3 Stepwise regression analysis

In this study, we are much involved in studying the possibility of modelling the relation between the overall performance and the five goals. Unequivocally, there is a number of multiple regression methods in the literature of modeling which can be used.

The “Stepwise Multiple Regression Method” is one of the efficient techniques used for building a “multiple linear model” between a dependent variable and a set of independent variables in accordance with a number of estimation and testing rules [64]. In addition, the stepwise method usually chooses the best predictors from a set of independent variables (the goals in this research) to predict the values of a dependent variable (the overall performance).

It may be worthy of mention that there are many applications in most of the academic disciplines (science, education, engineering. . . etc.), which are dedicated to “the topic of modelling of the linear regression model in trying to describe how variables are related” (ibid).

In fact, in the topic of model building, the main aim of the researchers is to detect a statistical model that is appropriate to represent the phenomenon on the basis of a set of data of the phenomenon and which can be generalized and used as a predictive model for the phenomenon in future.

In addition, the goal and the effort of the process of model building are achieved if the error of the prediction values is small, which completely depends on the quality of the collected data and the estimation procedure of the unknown parameters of the model.

In this paper, we studied the overall performance and the performance of the five goals. To complete the study, we tried to find a good forecasting model for the overall performance as dependent variables and as a linear function of the five goals by using the stepwise regression approach. In each step/model of the approach, the multiple correlation coefficients R², analyses of variance, significance values and estimating the unknown parameters in each step/model were calculated.

The outcomes of the stepwise regression approach are presented in Tables 6 –9 (in the appendix). Table 6 shows that the five steps of the approach are given as five models and the entered variables/ removed variables on the bases of cumulative R² of each goal (goal 4, goal 2, goal 3, goal 1 and goal 5) and the probability of significance (0.05) are also presented. In Tables 6 –9, M stands for Model of stepwise.

Table 6
Method of Stepwise regression

M Variables Entered

1 G4

2 G2

3 G3

4 G1

5 G5

M	Variables Entered
1	G4
2	G2
3	G3
4	G1
5	G5

Table 7

Model Summary

M	_R	R ²	F Change	Sig. F Change
1	0.650	0.423	21.260	0.000
2	0.831	0.691	24.205	0.000
3	0.934	0.873	38.854	0.000
4	0.982	0.964	64.979	0.000
5	1.000	1.000	178076.49	0.000

Table 8

ANOVA

M	Item	Sum of Squares	df	F ratio	(p)
1	Regression	64943.71	1	21.260	0.000
	Residual	88588.233	29
	Total	153531.94	30
2	Regression	106017.45	2	31.238	0.000
	Residual	47514.495	28
	Total	153531.94	30
3	Regression	134051.06	3	61.930	0.000
	Residual	19480.883	27
	Total	153531.94	30
4	Regression	147964.69	4	172.755	0.000
	Residual	5567.246	26
	Total	153531.94	30
5	Regression	153531.16	5	982321.597	0.000
	Residual	0.781	25
	Total	153531.94	30

Table 9

Coefficients

M	Item	β	Std. Error	(p)
1	Constant	347.822	44.804	0.000
	G5	2.999	0.650	0.000
2	Constant	162.909	50.277	0.003
	G5	2.821	0.486	0.000
	G2	0.685	0.139	0.000
3	Constant	106.709	34.001	0.004
	G5	1.678	0.366	0.000
	G 2	0.923	0.098	0.000
	G3	2.070	0.332	0.000
4	Constant	–16.100	23.983	0.508
	G5	1.271	0.206	0.000
	G2	0.996	0.054	0.000
	G3	1.671	0.188	0.000
	G1	1.043	0.129	0.000
5	Constant	–0.171	0.292	0.565
	G5	0.998	0.003	0.000
	G2	1.000	0.001	0.000
	G3	0.998	0.003	0.000
	G1	1.002	0.002	0.000
	G4	1.002	0.002	0.000

Table 7 shows the computed values of multiple correlations R (second column), multiple correlations R² (third column), R² change, and the values of the criterion F change are good and increasing with the moved variables (std. error of the estimate and R² change which are decreasing functions of the models). It is really interesting to observe that R = 1 (R² = 1) in model 5.

Table 7 also shows the most important results (in the last column), which are the values of Sig. F Change. Sig. F Change values are highly significant (0.000), which gives signals to the improvement process in model building; and it is significant in all models.

The analyses of the tests of ANOVA for the 5 models are given in Table 8 (in the appendix). Table 8 indicates very robust results that show that the residual is a sharply “decreasing function” with the models (the F ratio is an increasing function with the models), and there were highly significant differences in each model (Sig. values (p) = 0.000).

Finally, Table 9 gives the results of the estimation values of the unknown parameters of each model and the results of testing the significance of the parameters of each model.

It is interesting to observe that the constant term of each model is decreasing, whereas the estimated values of each of the parameters of all goals in each model are tested and accepted with high probability (the rejection probability (p) = 0.000). Table 9 (in the appendix) shows that the best fitted model is model no. 5 - this being on the basis of the results (F Change and F ratio respectively) of Tables 7 8 which show the smallest values of std. error (column 4, Table 8) in comparison to the other models.

In addition, by concentrating on model 5 of Table 9 (ignore the row of constant), we will notice that all the independent variables (goals) are important predictors for the dependent variable (the overall performance). The final estimated regression model may be constructed on the basis of model no. 5 in Table 9.

10 Concluding remarks

The technique of performance-related goals of HEIs was proposed in this paper and confirmed by assessing four secondary questions through collecting the opinions of a sample of 77 senior “academic staff”. The process of refining the goals of HEIs was discussed, and the goals of HEIs were refined. In addition, tools and methods of measurement were proposed and a flexible framework/ methodology of the problem was developed. The practical problem of assessing the overall performance and the performance of the goals of HEIs were discussed.

Five broad goals were defined and studied. The framework, data collection from 30 HEIs, data cleaning and data analyses were proposed. An interesting likelihood is to develop a flexible methodology and feasible policy for assessing the performance of HEIs.

The performance of HEIs was estimated, discussed and compared in accordance with the overall performance and the results of each goal in order to search for the best HEI. In addition, the performance of HEIs was placed into four categories. In fact, the performance of a few HEIs was very good.

The statistical approach, analyzes and tests the practical results which have been developed in this paper through reliability analyses, hypotheses testing, correlation coefficient and stepwise regression analysis. The results of statistical measures indicate very robust results which are highly significant of the actual practical results (Tables 4 &5).

A clear statement regarding the main objective of data analyses is identified. The findings show that practical results (see Sections 9.1 and 9.2 and Tables 6 –9) are significant, reliable, correlate and confident. Moreover, comparing the modeling and testing procedures used in this paper with those used in existing literature shows that developed tests dominated the others.

It is worth noting that this study of IC indicators has been developed for the first time in Oman, with a good number of IC indicators being implemented in 30 HEIs, and, that these HEIs have been informed about their results. The results were average; and their being so were due to several reasons, including the lack of databases of complete data in the HEIs of IC indicators, and the weak level of attention paid in HEIs concerning this matter. But in general, the research has achieved important results, which are in bringing the HEIs’ attention to the importance of IC issues - especially to IC indicators for HEIs, and, that this research is considered as an attempt to activate the HEIs databases to be more effective.

Thus, the theoretical approach proposed in this paper is examined and there are many insights into its applicability; and these should be used by HEIs for internal auditing. Furthermore, the gains of the practical results of this paper are very important and have to be considered by the private HEIs for future improvement in their achievement and performance.

11 Expected problems and dilemmas

In this section, some important issues are explained to exemplify some expected practical problems that appear when working with the problem of assessing the performance of private HEIs. Some suggestions and recommendations have also been discussed with regard to where they might be used in future applications intended to increase the efficiency of the results.

In this paper, many important educational activities are studied and estimated, while some other important activities are not considered for some purposes, e.g. availability of databases or the difficulties in assessing these activities. Thus, it may be necessary to consider a number of other activities in future implementation. This is a challenging task.

Excellence of some educational activities (institutional facilities, research, and internationalization) may have been achieved but only with high funding/costs. In fact, private HEIs are funded by private authorities, fees and government. Yet, the policies and the limited resources of private HEIs in developing countries may preclude the achievement of the excellence of some activities. This is another challenging task.

Private HEIs in many countries offer different programs. The second goal (to form themselves into a center which has the highest academic standards and excellence of research) may not fit properly with the objectives of some programs like music, drawing, stitching, . . .

Most national databases collected data from HEIs annually. These databases suffer from two main problems. Firstly, the information in these databases has not been collected properly. Secondly, the collected data usually are in different educational configurations. Using these databases is very difficult to understand and analyzing the data of these databases is a complex task.

Proposing the central theoretical approach for assessing private HEIs in developing countries, sometimes is not acceptable because of the findings of such an approach affecting the marketing purposes of the HEIs. For this reason, and as an agreement between the HEIs and the MoHE regarding naming the HEIs, has been forged, thus the explicit names of HEIs are not given in this paper.

Private HEIs are not similar in terms of their buildings, laboratories and classrooms. They are managed by one shift of staff, and sometimes by the same, and at other times by different shift(s) of students. These problems definitely affect the computations of some indicators/activities, which is called “school crowdedness”. These are measured in square meters and are related to the size of buildings, sports fields, library, students per laboratories and classrooms.

Footnotes

Acknowledgments

The authors are thankful to Mr. Francis Andrew, Polyglot Institute Ibri, Oman, for proofreading the paper. The authors are also thankful to the editor and the anonymous referees for their valuable suggestions that helped to improve this article.

The research has not received any funding source.

Author contributions

CONCEPTION: Al-Hemyari and Al Sarmi

METHODOLOGY: Al-Hemyari and Al Sarmi

DATA COLLECTION: Al-Hemyari

INTERPRETATION OR ANALYSIS OF DATA: Al-Hemyari

PREPARATION OF THE MANUSCRIPT: Al-Hemyari and Al Sarmi

REVISION FOR IMPORTANT INTELLECTUAL CONTENT: Al-Hemyari and Al Sarmi

SUPERVISION: Al-Hemyari and Al Sarmi

Supplementary materials

The data of this paper is available on the website of MoHERI, Oman. .

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Performance and planning model for HEIs: A developmental engine for intellectual capital

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSIONS:

Keywords

1 Introduction

2 The importance of IC in HEIS: Review of literature

4 The tools and methods

4.1 Assuring the technique of performance-related goals

Table 3 Weight of Goals (w(g j )) G U C C G1 200 200 G2 450 550 G3 100 50 G4 100 50 G5 150 150 Total 1000 1000

5 The proposed goals

5.1 Remarks

6 The acquisition of data

7 Data detecting and cleansing

8 The practical results

9.1 Hypotheses testing

9.2 Correlation coefficients analysis

9.3 Stepwise regression analysis

Table 6 Method of Stepwise regression M Variables Entered 1 G4 2 G2 3 G3 4 G1 5 G5

11 Expected problems and dilemmas

Footnotes

Acknowledgments

Author contributions

Supplementary materials

References

Table 3
Weight of Goals (w(g_j))

G U C C

G1 200 200

G2 450 550

G3 100 50

G4 100 50

G5 150 150

Total 1000 1000

Table 6
Method of Stepwise regression

M Variables Entered

1 G4

2 G2

3 G3

4 G1

5 G5