EFFECT OF INTELLECTUAL CAPITAL COSTS ON EARNINGS GENERATION OF LISTED DEPOSIT MONEY BANKS IN NIGERIA

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ABSTRACT

 

This work examined the effect of Intellectual capital costs on earnings generation of listed deposit money banks in Nigeria. The study adopted the ex-post facto research design and panel regression statistical technique, involving the use of time series and cross-sectional data. Data covered the period of eight-years (2011-2018); considering the total population of fourteen (14) listed deposit money banks in Nigeria, random sampling was employed in selecting firms for this study involving eleven (11) deposit money banks. Data were sourced secondarily from the firms' published annual financial statements. Value Added Intellectual Coefficient (VAIC) theory as developed by Pulic (1998) was adopted for this study. It was discovered from the findings that Human Capital Efficiency (HCE), Structural Capital Efficiency (SCE) and Capital Employed Efficiency (CEE), as components of Intellectual capital costs all have a positive and significant effect on gross earnings. Therefore, Intellectual Capital Costs have a positive and significant effect on earnings generation of listed deposit money banks in Nigeria.  In view of our findings, deposit money banks should ensure that an advanced and all-encompassing training and retraining programme is put in place to certify an up to date human resource, which is both efficient and effective. In addition, managing directors of deposit money banks should carry out a proper implementation and regular monitoring of the systems, procedures and program (structural capital), all with an effective and efficient support from higher and middle line management, as this will ensure expansion in all frontiers of the business.






TABLE OF CONTENTS

Title Page                                                                                                 i

Declaration                                                                                              ii

Certification                                                                                             iii

Dedication                                                                                               iv

Acknowledgements                                                                                 v

Table of Contents                                                                                    vi

List of Tables                                                                                           ix

List of Figures                                                                                          x

Abstract                                                                                                    xi

 

CHAPTER 1: INTRODUCTION                                                                    

 

1.1          Background to the Study                                                            1

1.2          Statement of the Problem                                                           3

1.3          Objectives of the Study                                                              4

1.4          Research Questions                                                                    5

1.5          Statement of Hypotheses                                                            5

1.6       Significance of the Study                                                            5

1.7       Scope of the Study                                                                       6

1.8       Operational Definition of Terms                                                 6

1.9       Limitations of the Study                                                              7

 

CHAPTER 2: REVIEW OF RELATED LITERATURE                             

2.1       Conceptual Framework                                                               8

2.1.1    Concept of intellectual capital                                                     8

2.1.2    Categories of intellectual capital                                                 8

2.1.3    Characteristics of intellectual capital                                          12

2.1.4    Value added intellectual coefficient (VAIC)                               12

2.1.5    Capital employed efficiency (CEE)                                            13

2.1.6    Human capital efficiency (HCE)                                                 14

2.1.7    Structural capital efficiency (SCE)                                              14

2.1.8    Phases of intellectual capital development                                 15

2.1.9    Intellectual capital costs                                                              16

2.1.10  Intellectual capital development steps                                         18

2.1.11  Measuring intellectual capital                                                            19

2.1.12  Intellectual capital costs model (views)                                      20

2.1.13  Importance of intellectual capital costs                                       31

2.1.14  Intellectual capital administration measures                                      32

2.1.15  Intellectual capital costs and earnings generation                              38

2.2       Theoretical Framework                                                                  38

2.2.1    Value added intellectual coefficient theorem (VAICTM)             38

2.2.2    Knowledge based theory (view)                                                  42

2.2.3    Agency theory                                                                             41

2.3        Empirical Review                                                                        43

2.4        Summary/Gap in Literature                                                        65

 

CHAPTER 3: METHODOLOGY                                                                                                       

3.1   Research Design                                                                                     67

3.2   Area of the Study                                                                            67

3.3   Population of the Study                                                                   67

3.4   Sampling Size                                                                                 67

3.5   Method of Data Collection                                                              68

3.6   Method of Data Analysis                                                                68

3.7   Model Specification                                                                                68

 

CHAPTER 4: RESULTS AND DISCUSSIONS

4.1       Descriptive Statistics                                                                   70

4.2       Unit Root Test                                                                             71

4.2.1    Panel unit root test for dependent & independent variables        71

4.3       Co-integration Test                                                                      73

4.3.1    Co-integration test for the series LOGE and HCE                      73

4.3.2    Co-integration test for the series LOGE and SCE                       74

4.3.3    Co-integration test for the series LOGE and CEE                      75

4.4       Test of Constant Variance (Heteroskedasticity)                         75

4.4.1    Test of constant variance for model 1                       76

4.4.2    Test of constant variance for model 2                                 76

4.4.3    Test of constant variance for model 3                              76

4.5        Test of Hypotheses                                                                      77

4.6         Discussion of Findings                                                               83

 

CHAPTER 5: SUMMARY OF FINDINGS, CONCLUSION AND RECOMMENDATIONS         

5.1         Summary of Findings                                                                 85

5.2         Conclusion                                                                                 85

5.3         Recommendations                                                                     85

5.4         Suggestion for Further Studies                                                  86

References                                                                                          

Appendices                                                                                                         

 

 

 

 

 

LIST OF TABLES

 

4.1       Description Statistics of Dependent & Independent Variables     70

4.2.1    Result of Panel Unit Root Tests for Dependent Variables          72

4.3.1    Co-integration Test-Engle-Granger                                            73

4.3.2    Co-integration Test-Engle-Granger                                            74

4.3.3    Co-integration Test-Engle-Granger                                            75

4.4.1    Model 1 Heteroskedasticity Test: White                                     76

4.4.2    Model 2 Heteroskedasticity Test: White                                     76

4.4.3    Model 3 Heteroskedasticity Test: White                                     76

4.5.1.1 Correlated Random Effects-Hausman Test                                 77

4.5.1.2 Estimates of Random Effect (Model 1)                                       78

4.5.2.1 Correlated Random Effects-Hausman Test                                 79

4.5.2.2 Estimates of Random Effect (Model 2)                                       80

4.5.3.1 Correlated Random Effects-Hausman Test                                 81

4.5.3.2 Estimates of Random Effect (Model 3)                                       82

 

 

 

 

 

 

 

LIST OF FIGURES

 

2.1   Categorisation of Intellectual Capital                                              15

2.2   Managing of Intellectual Capital                                                     18

2.3   Diagrammatical Representation of Wissensbilanz Model               22

2.4   Description of the Meritum Model                                                  28

2.5   Skandia’s Navigator (Customer focus)                                            30

2.6   Pictorial Description of the New Approach Model                         32

3.1   Explanation of Variables                                                                 69

 

 

 

 

  

 

 

CHAPTER 1

INTRODUCTION

 

1.1       BACKGROUND TO THE STUDY

The study of intellectual capital costs, in recent years, is an area that is now securing relevance in today’s academia, knowledge economy and business. This plays a central function in the innovation, productivity, growth, performance and competitiveness of organisations. The scope of intellectual capital comprises human resources, the company’s composition and processes, research and development, rights related to intellectual property and technology, as well as software and consumer networks (Zehri, Abdelbaki & Bouabdellah, 2012).

 

Remarkably, it is no longer a debate that, in recent times, the accounting world has witnessed the gradual move from industry-based concentration to high concentration on technology that enhances the creativity, skills and expertise of people to drive firms forward.

Inyada (2018), in order to buttress the aforementioned assertion, added that such a move from being industry-based, focuses on assets that are physical in nature, such as plants, factories, equipment and machinery, to the level of deploying cutting-edge technology and leveraging novel information. Moreover, that which is innovation-based focuses on talent, expertise, skill-set, creativity, experience and dedication of people in an establishment’s human capital. By implication, the fundamental difference between the two environments is the nature of their assets.

 

Previous researches in line with this study have proved that the advancement to ability, knowledge, expertise, skills, attitude of workers and experience (which intellectual capital is comprised of) is no doubt of greater value to an organisation. In addition to facing enormous globalised competition, there is an extensive recognition that intellectual capital is a crucial force that positions economic growth (Huang & Liu, as cited in Sharabati, Jawad, & Bontis, 2010). Furthermore, in today’s knowledge-based economy, common researchers have also claimed that systems, people and procedures have remained indispensable assets for organisational advancement. The predominance of intangibles and knowledgeable individuals has propelled the world to face a global competition, which appears as an outstanding characteristic of every emerging economy of today.

 

That being said, the origin of intellectual capital costs is traced to Scandinavia, where, traditionally, businesses have a greater time horizon, and where there is a formidable inclination “engineering” to innovation and research (Barney, as cited in Gogan & Duran, 2014). This type of cost management is used mainly in Denmark, Holland, Taiwan, Sweden, Norway, China, Canada, Finland, Japan, Taiwan and, to a lesser extent, in Austria, Israel, Italy, Spain, and Australia. Organisations use performance management of intellectual capital in one way or another by realising or guessing its role in achieving competitive advantage. In summary, the management of intellectual capital costs is a set of management tools which enables the organisation to enjoy access to the knowledge they have, but they do not operate effectively.

 

Next to this, earnings are very important concepts that relate to the form and way in which financial resources that are readily available to an organisation are properly utilised to give rise to the overall corporate objective of an organisation. It is, therefore, crucial that the performance of an organisation is measured on a regular basis to guarantee continuity and sustainability.

One particular sector considered to be knowledge-intensive and a source of rich intellectual capital concentration is the banking and financial sector. Compellingly, this sector is highly innovative, research-intensive and strongly balanced in its use of the human capital intervention. Hence, the need to manage intellectual asset is very important for every organisation within the banking sector that desires to generate and improve its earnings steadily, which, in turn, will make it stand out amongst its competitors.

 

1.2       STATEMENT OF THE PROBLEM

There have been conflicting results in this research area especially in Nigeria. While some researchers agree that intellectual capital costs relate positively and significantly to organisational performance and, as such, also provide competitive edge over others, some other researchers believe that the relationship between intellectual capital costs and organisational performance is negative and of no significance; and that the physical assets still stand as the central force of organisational performance (Inyada, 2018).

 

As captured in the annual reports, one of the common phrases in the chairman’s statement, is that, “Our employees are our greatest assets”.  Citing Nigeria as a case study, though these institutions in the financial sector often boast of rich intellectual assets, there has always been lopsided awareness given to the contribution and value of these “treasured assets” on the overall earnings of banks. These are clearly seen in recent times, from the high level drastic “human asset (staff) fallout” due to poor working conditions, job transfer or switch by bank staff owing to poor remuneration, little or no budget for staff training for all cadre, tight work schedule & conditions, high influx employment ratio of casual staff amongst others with no conversion policy even after meeting the satisfactory working condition before conversion to full staff amongst other issues. One of the reason behind all these bottle neck is due to improper accountability, redefining and mis-management of these unique human asset, coupled with the rising global economic crisis. Also, with the latest financial re-engineering and technological improvement of most financial institutions in Nigeria, there have been high exposure and reports of financial crime (e-fraud) arising from security breach. In the wake of this reality, whenever organisations take up the task of investing completely in physical assets, they often try to select the investment that will give rise to the highest return on their outlay. In addition to the above-mentioned bottlenecks, been faced with the challenge of having the most suitable intellectual capital to carry on its work efficiently and effectively, some deposit money banks results in poaching from competitors, since it will take time to actualise the process of new staff recruitment and training to meet their human capital needs. Little wonder Guest, Michie, Conway, and Sheehan (as cited in Oko, Onodi, and Tapang, 2018) noted that it had been a spontaneous argument that organisations which are best able to meet the difficulty of handling their intellectual capital cost will be those which can utilise its valuable, scarce and inimitable resources that have been acquired.

In addition to the task of effectively and prudently managing intellectual capital costs, the management of financial institutions are confronted with the challenge of how to enjoy a competitive edge in the world markets, while in search of improved productivity via encouraging the spread of high-performance in workplaces. Owing to this development and challenge, this research is set out to look at the effects of intellectual capital costs on the generation of earnings of deposit money banks in Nigeria.

 

1.3       OBJECTIVES OF THE STUDY

The broad objective of the study is to examine the effect of intellectual capital costs on earnings generation of listed deposit money banks in Nigeria.

   The Specific objectives are:

1.              To ascertain the effect of human capital efficiency on gross earnings.

2.              To examine the effect of structural capital efficiency on gross earnings.

3.              To determine the effect of capital employed efficiency on gross earnings.

 

1.4      RESEARCH QUESTIONS

(i)    To what extent does human capital efficiency affects gross earnings?

(ii)  To what extent does structural capital efficiency affects gross earnings?

(iii)                  To what extent does capital employed efficiency affects gross earnings?

 

1.5      STATEMENT OF HYPOTHESES

The following are the null hypotheses of the study:

1.         Human capital efficiency has no significant effect on gross earnings.

2.         Structural capital efficiency has no significant effect on gross earnings.

3.         Capital employed efficiency has no significant effect on gross earnings.

 

1.6       SIGNIFICANCE OF THE STUDY

Considering that the subject of the study is of utmost importance in the accounting and finance world, it will be beneficial to the following stakeholders:

To Banks: This study will be absolutely crucial, in order to have a comprehensive knowledge of the nature of their intellectual capital costs and their contribution to their baseline.

To Shareholders: They will best understand the modalities on how to determine which bank to invest in, when considering their returns on intellectual capital, and having a thorough grasp of why organisations engage in the services they carry out.

Management: They will have to appreciate the need for giving a high priority to the incorporation of intellectual capital in their financial statements, and as well consider the significance of intellectual capital costs on a firm, as a going concern.

Researchers: Undoubtedly, they will find the research really essential, as it will add to existing literature and also aid more research in the future.

 

1.7       SCOPE OF THE STUDY

This study is on the effect of Intellectual Capital costs on earnings generation of listed deposit money banks in Nigeria. The data used for the study were derived from the published financial statement of eleven (11) commercial banks listed on the Nigerian Stock Exchange. The period ranging from 2011 – 2018 covers the aspect of dealing with the data for statistical analysis, as there has been little or no research covered on this area within these period.

 

1.8       OPERATIONAL DEFINITION OF TERMS

The following definitions relevant for the study shall be adopted:

Capital employed efficiency: This measures the relational capital value added to the entity, which captures the entire value contribution to the stakeholders.

Earnings: This is the income accrued and derived by an organisation from the activities it carries out within a period.

Human Capital: This is the know-how, skill, and expertise held in the heads (initiative) of the staff or their valuable knowledge asset that creates wealth for the organisation.

Human capital efficiency: This is the proportion of the value-added to the human capital of an organisation.

Intellectual Capital: This is the expertise inherent in the staff, system, and procedures of a workplace and the inter-related relationship with customers been combined to provide a positive value drive of an organisation.

Intellectual Capital Costs: This involves the functional costs of the expertise, software and hardware, and the dynamic relationship that drives the entire worth of the organisation.

Relational Capital: This involves the value creating stakeholder relationship of the organisation.

Structural capital: This is the software and hardware, system, processes and procedures component of an entity that creates wealth for the organisation.

Structural capital efficiency: This is the proportion of the structural capital to the value- added in an organisation.

 

1.9       LIMITATIONS OF THE STUDY

There are many impediments against the conduct of research in Nigeria just as in any developing country. The study limitations are as follows:

1.         Non-availability of required up to date data during this study to widen the scope. Thus, the researcher is necessitated to use the data available at hand to carry out this research work.

2.         The firms selected for the study comprises only listed deposit money banks.

 


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