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The Effect of Intellectual Capital Drivers on Performance and Value Creation: the Case of Tunisian Non-financial Listed Companies

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Abstract

The value of companies is traditionally estimated from the material wealth they hold. In the context of the knowledge economy (KE), these elements are no longer enough to estimate this value. Many authors are interested on new sources of value creation called immaterial. Nevertheless, the intangible elements, without physical or intangible substance, are difficultly taken into account by old accounting methods. The work done around our problem tries to define a model that reflects the overall performance of firms of the NE, by adding information about the intangibles to the old accounting data. The present study is looking for reliable measures of the performance of Tunisian firms which are operating in the new economy. The failure of accounting and financial data leads us to add other information. The pieces of information are related to intangible capital which is the main source of value creation for firms in the KE; however, they are ignored in traditional metrics. The results obtained, following the different operated regression, indicate the significance of the variables: “book value, BVE;” “return on equity, ROE;” and “return on assets, ROA.” However, the other ratios are insignificant. Furthermore, the explanatory power of the model is fairly low hovering around 20%. This result allows us to confirm the failure of classical accounting and financial data to translate firm performance of KE. Thus, we validated our initial hypothesis that stresses the usefulness of accounting and financial data in evaluating the performance of firms in the KE. Similarly, data on intangible capital is embodied in three aspects–structural, customer, and human–that play important roles in assessing this. The obtained results indicate that the explanatory power of the model, taking into account the intangible component, is higher than that based solely on the accounting and financial data. Indeed, adjusted R² lies in a range between 30 and 66%. This validates our second hypothesis on the role of intangibles in the chain of value creation. This study shows the important role of intangible capital information in the process of decision-making. Thus, investors and managers should give particular attention to immaterial components which allowed a better appreciation of the overall performance of Tunisian firms operating on NE. This is the contribution of our work.

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Authors and Affiliations

  1. High Institute of Accounting and Business Administration, Bizerte, Tunisia

    Inès Ben Cheikh

  2. Institute of Higher Commercial Studies, Bizerte, Tunisia

    Hédi Noubbigh

Authors
  1. Inès Ben Cheikh
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  2. Hédi Noubbigh
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Corresponding authors

Correspondence to Inès Ben Cheikh or Hédi Noubbigh.

Appendices

Appendix 1: John Core Model and Variables (2003)

The established empirical model is the following:

$$ \begin{array}{l}MVE={\alpha}_0+{\alpha}_1BVE+{\alpha}_2NI+{\alpha}_3NEG\_NI+{\alpha}_4RND+{\alpha}_5\mathrm{ADVERT}\\ {}+{\alpha}_6\mathrm{CAP}\_\mathrm{EX}+{\alpha}_7\mathrm{SALES}\_GR+\varepsilon \end{array} $$

Such as MVE is the market value of the share, BVE is the book value of the share, NI is net income before extraordinary items, NEG_NI is net income before extraordinary items if this variable is <0 or equal; otherwise, it is set to 0, R&D are research and development expenses, ADVERT are advertising costs, CAP_EX is investment in property, and SALES_GR is a proxy for income growth.

Appendix 2: Matrix Correlation of Ratios

 

MVE

BVE

ROE

RMN

REND

EPS

ROA

PER

MVE

1.0000

       

BVE

0.3247

(0.0000)***

1.0000

      

ROE

− 0.2818

(0.0004)***

− 0.4262

(0.000)***

1.0000

     

RMN

0.0701

(0.3894)

− 0.0139

(0.8619)

0.3808

(0.0000)***

1.0000

    

REND

0.7106

(0.0000)***

0.5164

(0.0000)***

− 0.6909

(0.0000)***

− 0.1824

(0.210)

1.0000

   

EPS

0.1163

(0.1481)

− 0.2332

(0.0028)**

0.4449

(0.0000)***

0.4711

(0.0000)***

− 0.1518

(0.0544)

1.0000

  

ROA

0.1051

(0.1915)

− 0.0188

(0.8127)

0.6239

(0.0000)***

0.6717

(0.0000)***

− 0.2550

(0.0011)***

0.6852

(0.0000)***

1.0000

 

PER

0.0475

(0.5562)

0.0473

(0.5559)

0.1562

(0.0508)**

0.1580

(0.0503)**

− 0.1625

(0.0434)**

0.1155

(01497)

0.1835

(0.0214)**

1.00000

  1. *Significativité à 10%, **significativité à 5%, ***significativité à 1%

Appendix 3: Vif Test and Breusch-Pegan Test (Applied on Ratios)

.vif

 Variable

VIF

1/VIF

  fpers

26.29

0.038032

  invcorp

21.86

0.45741

  rt

2.67

0.374499

  invinc

1.24

0.807535

  crrev

1.23

809,863

  BVE

1.21

825,178

  pub

1.18

847,006

Mean VIF

7.96

.hettest

  1. Breusch-Pagan/Cook-Weisberg test for heteroskedasticity
  2. Ho: constant variance
  3. Variables: fitted values of MVE
  4. Chi2(1) = 23.77
  5. Prob > chi2 = 0.0000

Appendix 4: Matrix Correlation of Intangible Components

 

MVE

BVE

INVINC

FIXASS

NI

INCGROW

ADV

PERSC

MVE

1.0000

       

BE

0.3255

1.0000

      
 

(0.0000)***

       

INVINC

0.4334

−0.0890

1.0000

     
 

(0.0000)***

(0.2974)

      

FIXASS

−0.0696

−0.0234

0.0851

1.0000

    
 

(0.3940)

(0.7712)

(0.3211)

     

NI

0.0442

−0.0312

0.0742

−0.0765

1.0000

   
 

(0.5828)

(0.6927)

(0.3855)

(0.3412)

    

INCGROW

0.0481

−0.0075

0.1444

−0.0283

0.0721

1.0000

  
 

(0.5524)

(0.9250)

(0.0934)*

(0.7271)

(0.3713)

   

ADV

−0.1458

−0.2354

−0.0716

−0.0728

0.0419

−0.1158

1.0000

 
 

(0.1521)

(0.0167)**

(0.5077)

(0.4695)

(0.6746)

(0.2490)

  

PERSC

−0.0561

−0.0693

0.1123

0.8153

−0.0321

0.0751

−0.0942

1.00000

 

(0.4893)

(0.3838)

(0.1882)

(0.0000)***

(0.6862)

(0.3512)

(0.3415)

 
  1. *Significance level at 10%, **significance level at 5%, ***significance level at 1%

Appendix 5: Vif Test and Breusch-Pegan Test (Applied on Intangible Components)

.vif

 Variable

VIF

1/VIF

  fpers

26.29

0.038032

  invcorp

21.86

0.45741

  rt

2.67

0.374499

  invinc

1.24

0.807535

  crrev

1.23

809,863

  BVE

1.21

825,178

  pub

1.18

847,006

Mean VIF

7.96

  1. Breusch-Pagan/Cook-Weisberg test for heteroskedasticity
  2. Ho: constant variance
  3. Variables: fitted values of MVE
  4. Chi2(1) = 23.77
  5. Prob > chi2 = 0.0000

Appendix 6: Matrix Correlation of Intangible Components with Detailed Structural Component

 

MVE

BVE

RT

INVLOGINF

INVRD

INMATINF

CRREV

PUB

FPERS

MVE

1.0000

        

BVE

0.3255

(0.0000)***

1.0000

       

RT

0.0442

(0.5828)

− 0.0312

(0.6927)

1.0000

      

INVLOGINF

0.1235

(0.1550)

− 0.0707

(0.4082)

0.0740

(0.3847)

1.0000

     

INVRD

− 0.0730

(0.3637)

− 0.0140

(0.8597)

0.0851

(0.3211)

− 0.0433

(0.7447)

1.0000

    

INMATINF

0.3194

(0.0013)**

− 0.0386

(0.6960)

0.1283

(0.1920)**

0.5780

(0.0000)***

− 0.0222

(0.8195)

1.0000

   

CRREV

0.0481

(0.5524)

− 0.0075

(0.9250)

0.0721

(0.3713)

0.1393

(0.1046)*

− 0.0194

(0.8091)

0.2390

(0 .0166)**

1.0000

  

PUB

− 0.1458

(0.1521)

− 0.2354

(0.0167)**

0.0419

(0.6746)

− 0.0458

(0.6643)

0.0848

(0.3923)

− 0.0456

(0.7121)

− 0.1158

(0.2490)

1.0000

 

FPERS

− 0.0561

(0.4893)

− 0.0693

(0.3838)

− 0.0321

(0.6862)

0.1207

(0.1538)

− 0.0559

(0.4795)

0.3828

(0.0001)***

0.0751

(0.3512)

− 0.0942

(0.3415)

1.00000

  1. *Significance level at 10%, **significance level at 5%, ***significance level at 1%

Appendix 7: Vif Test (Applied on Intangible Components with Detailed Structural Component)

Variable

VIF

1/VIF

FPERS

2.40

0.416693

INVMATINF

2.25

0.444979

INVLOGINF

1.82

0.550938

BVE

1.69

0.590936

RT

1.25

0.799889

CRREV

1.21

0.824290

PUB

1.16

0.860190

INVRD

1.07

0.935149

Mean VIF

1.61

 

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Cheikh, I.B., Noubbigh, H. The Effect of Intellectual Capital Drivers on Performance and Value Creation: the Case of Tunisian Non-financial Listed Companies. J Knowl Econ 10, 147–167 (2019). https://doi.org/10.1007/s13132-016-0442-0

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