Keywords

Learned Practices, Revenue Generation, Human Capital, Structural Capital, Capital Employed Efficiency, Corporate Performance.

Introduction

The wave of change brought about by advancement in technology has altered the eighteenth-century production system and introduce a shift from labour-intensive to capital intensive technique Ekwe, (2013). This necessitated a change from industrial to the knowledge- oriented economy Ahmadi, Ahmadi & Shakeri, (2011), Huang & WU, (2010), Raze (2011), Ifsu & Fang, (2010), thus permitting knowledge, technology and expertise as crucial drivers and ingredient necessary for positive corporate performance in this twenty-first century. This implies that proper application of expertise, technology and knowledge with physical assets will not only sharpen the competitive edge of an organization but will place them on merit over the others Borneinan (1999).

In past centuries, Land, Labour and Capital (financial and physical) took prominence over learned practices hence; But advancement in science and technology and of course the globalization has introduced a new production system which is highly driven by Ekwe, (2013), Adelakun, (2011). Firer & Williams, (2003) asserted that production or manufacturing

companies use learned practices with their physical assets to sharpen their competitive edge. Corporations that manage learned practices better have achieved a stronger competitive advantage over general enterprises.

Learned practices are those invisible or intangible assets that are hard to qualify into value and are never reported in the financial statements such as skill, workforce and its organization. Intellectual capital includes inventions, ideas, general knowledge, design approached, computer programmes and publications Stewart, (1997) & Fredriksen, (1998).

Intellectual capital ought to be spearheading management decisions and the financial reporting system, but to great extent, little or no attention is credited to it in the decision-making process, no wonder mergers and acquisition have become an option for survival in the corporate sector. In literature, it is strongly agreed that learned practices improve and sustains corporate competitive advantage through its human capital and organizational knowledge Aragon, Jimenez and Valle, (2013), Subramanian and Youndt, (2005), Lopez-cabrales et al (2006), Kraiger, (2003), Tharenou et al, (2007), Ballesteros et al, (2012) Onag, Tepeci and Basalp (2014) asserted that innovation which is an aftermath of learned practice is the lifeblood for organizational growth and sustenance as alluded by Balachandra and friar (1997), Armbruster, Bikfalvi, Kinkel and Lag (2008).

Bontis (2001) alluded that change in CEOs and top management brings about change in stock prices. This is brought about by knowledge and expertise and is a major motivation for investors Goh and Ryan, (2002), Aragon, et al, (2013). In Nigeria, this factor must have been the reason for a small Access bank to swallow up a big Diamond Bank madugba, Ben-caleb, and Mbamara, (2019).

The conflicting opinion exists on the relevance of learned practices and corporate operating performance. While the studies of Bornemann (1999), Brennan & Connell (2000), Clarke, Seng & Whiting, (2010), Obedient, Abdallah, et al, (2016), Badraadi and Akbarpour (2013) and Aragon, Jimenez and Valle (2013) strappingly alluded that there is a positive and significant relationship between intellectual capital and organizational performance, Wright, et al (1995), Goh, et al (2002) found no relationship between intellectual capital and organizational performance. This lacuna created by the above studies necessitated this study with the crux of examining the influence of learned practices on operating performance on quoted firms in Nigeria.

Literature Review and Hypothsis Development

The relationship between learned practices and financial performance of the organization cannot be over-emphasized. This is because the new production system which is highly driven by technological advancement is motivated by learned practices (intellectual capital) and not tangible assets. Though tangible assets have their contributions but cannot give an organization a good competitive advantage over other firms in the same industry. Suffice to say the experience a very fast change thus making intellectual capital the determinant of the way and manner business is done nowadays Davenport & Prusak (1998).

According to Aragon, et al., (2013), learned practices may not have a direct impact on operating performance, but it indirectly influences the employees’ productivity or perhaps performance. It is pertinent to say that studies relating to the association between corporate performance and learned practices are very few. Among them is the study of Nevis, et al., (1995) who found a positive and significant association between organizational training and

organizational performance. This study is corroborated by Ahmad and Schroeder (2003) and Brockman and Morgan (2003). This alludes that there is a strong connection between learned practices or training and firm performance. Learned practices affect the financial performance of corporations in numerous ways. For instance, the difference between acquired and acquiring firm is intellectual capital, this is the idea behind corporate organization paying the most to get the labour because with the skill of labour fortunes of the company turns around Madubga, et al, (2019).

Learned Practices and Corporate Growth

Corporate growth is used in a wider sense to mean a positive and significant increase in cash inflows or earnings of a corporation. Corporate growth is the aftermath of a significant increase in the sales volume of a corporation. In financial literature, four major growth strategies are recognised which aforementioned strategies are the product of a learned practice (intellectual capital). A firm whose top management Staff is well-skilled stand the chance of experiencing corporate growth because the skill of management will be put to best use and gain (Ekwe, 2013).

Resource-Based View (RBV) Theory

The theorist alludes that a firm can gain a sustainable competitive advantage over other firms through the proper maximization of its capacities and resources. Barney (1991) posits that competitive advantage is attained if a firm introduces a meaningful strategy not widely being used or exploited by other potential competitors. David (2011) opine that the performance of a corporation is a function of its internal factors which include employees, training, expertise, abilities, information technology, trademarks etc. This theory will drive this study as it explicitly discusses the potentials of learned practices in corporations.

Hypothesis Development

Xu & Wang (2019) in their study of this nature though in agricultural companies in China, found that workers skill influences for the growing the agricultural companies in China. Abbasi, et al., (2019) in their study which focussed on VAIC in measuring intellectual capital found out the IC is directly related to the business performance of indexed corporations in Pakistan. He suggested that companies in Pakistan should consider IC as a crucial tool for corporate growth. Khalique, et al., (2019) in their study in Pakistan adopted the integrated intellectual capital model and found out IC is very imperative for the continued existence of banking sector in Sialkot Pakistan and that customer capital etc was shown to be noteworthy to operational accomplishments of Banks in Sialkot.

Khanmohammadiotaqsara, Khalili & Mohseni (2012). A comparison of the difference between book value and market value of the listed firm in Nigeria will reveal that learned practices or intellectual capital need to be considered as influences market capitalization and improves capital market efficiency Chen, Cheng & Hwang (2005). Bontia & Richardson (2000) asserted that knowledge and information are crucial elements as they lead to increasing business returns, as opposed to the decreasing return typical of the traditional resources like physical assets. Ahmad & Ahmad (2016) confirmed that a positive and significant relationship exists between intellectual capital and financial performance. Okpara (2015) in a study which spanned

from 2008- 2013 in Nigeria also affirms that intangible resources influence competitive advantage and financial performance. Kamath (2015) adopted the VAIC method in a study in India and affirms that there is a positive and significant relationship between intellectual capital and financial performance and market capitalization.

In Nigeria, one major factor that employers of labour consider crucial is learned practice as this accounts for the huge costs incurred by firms through engaging the services of HR firms who advertise and recruit workers for such firms. More so, continuously, such firms are involved in staff training for enhanced productivity Ewke (2013). Ekwe (2012) adopted the VAIC method on two years study of banks quoted on Nigeria stock exchange found a positive and significant relationship between the financial performance of quoted banks in Nigeria and intellectual capital. The study of Okpara (2015) though in Nigeria is not as current as of this.

Materials and Methods

After the fact as used by Madugba, et al., (2015), Madugba, et al (2020). Out of 198 listed companies in Nigeria purposively, 24 was selected base on availability of the nature of data required for this study. The study spanned from 2009-2018. Secondary data got from financial reports of the listed service companies in our study was analysed with the aid of SPSS

23. Descriptive statistics, normality tests, multicollinearity test, and multiple regressions were carried out to establish the liaison linking the tested and predictor variable. The tested variable is operating performance measured with earnings per share.

From the above, our model specification will be thus

EPS_it = ƒ(HC_it, CEE_it, SC_it)…........................................................ (7)

EPS_it = ₀ + ₁ HC + ₂ CEE + ₃ SC + e_t....................................... (8)

Descriptive Statistics

Table 1: Showed that human capitals have a minimum and maximum value of 1.00 and 1.80. The average positive value of 1.3163 was also shown for human capital with a standard deviation value of 0.20150.

Structural capital indicated a 1.00 and 1.88 as the minimum and maximum values, with an average value of 1.3396. This value is positive with a standard deviation value of 0.21913.Capital employed efficiency of the companies showed a minimum and maximum value of 1.01 and 1.99. The mean value of 1.4204 is positive and the standard deviation is shown as 0.24589.Earnings per Share (EPS) are indicated with minimum and maximum values of 0.00 and 1.00. The average value of .5971 shown for EPS is positive and the standard deviation value is 0.27042.

Table 1 descriptive statistics Source: authors’ computation 2020
Variable	minimum	Maximum	Mean	standard deviation	Skewness	Kurtosis
HC	1.00	1.80	1.3163	.20150	.369	-.767
SC	1.00	1.88	1.3396	.21913	.408	-.934
CEE	1.01	1.99	1.4204	.24589	.267	-.690
EPS	0.00	1.00	0.5971	.27042	-.482	-.790

Test for Normality

The normality test was conducted using skewness, Kurtosis, and histogram. Skewness for HC is 0.369, indicating that the scores for HC are positively skewed to the left though not far from the normal point of zero. The kurtosis value of -0.767 shows is relatively peaked. Although both skewness and Kurtosis of HC suggest that the variable is relatively not normally distributed, the number of cases in this study (240) is large enough to undermine the risk of underestimation of variance which the kurtosis and skewness suggest Tabachnick & Fidell (2001), Pallant (2001). To further buttress the normality position of EPS data, a histogram in the Figure.1 reveals a bell- shaped curve which implies normality of the data.

Structural Capital (SC) of the companies in our study is shown to have a skewness value of .408, meaning that SC is positively skewed to the lift but not too far from the point of zero. The kurtosis also indicated a negative value of -934, meaning that it is peaked Tabachnick, et al., (2001), Pallant (2001). The skewness and Kurtosis result notwithstanding, the histogram showed a relatively belle shaped curve meaning that the data for SC is normally distributed as shown in Figure 2.

Capital Employed Efficiency (CEE), is shown to have a skewness value of .267, implying that CEE is positive and relatively skewed. The kurtosis value for CEE has indicated is -690. This again means that CEE is peaked far from the point of zero. But the number of data in the study according to Tabachnick, et al., (2001), Pallant (2001) is enough to affect the result. Besides, the histogram for CEE is relatively bell-shaped as in Figure 3.

The earnings per share of the listed companies showed a skewness value of -.482, meaning that EPS is relatively peaked to the right. The kurtosis value of 790 is also less than zero. Again meaning that EPS is peaked to the right. This could be the aftermath of the large data used for this Tabachnick, et al., (2001), Pallant (2001). However, the histogram showing normality test for this indicated a bell shape curve thus as in figure 4.

Test for Outliers

To test for outliers (extreme cases of data away from others), the box plot was used. Figure 5 shows that there is no outlier, hence no data cases that will influence or distort the result of our inferential analysis.

Data Analysis and Interpretation

Results

Table 2 Model Summaryb
R Square	Adjusted R Square	Std. Error of theEstimate
0.025	0.013	0.26869
a. Predictors: (Constant), LCEE, LHC, LSC
b. Dependent Variable: LEPS
Source: Authors’ computation, 2020

From Table 2, the correlation (R) is 15.9% which signifies a positive relationship between the EPS and the explanatory variables. The coefficient of determination of 2.5% suggests that independent variables (LHC, LSC and LCEE) could explain about 2.5% of the variations in EPS. About 97.5% relates to other variables outside the model. This result indicates that earnings per share determine the learned practices (intellectual capital) of listed companies in Nigeria. The adjusted (R) is 0.013 that is 1.3%, this implies that the contribution of each variable is too small to influence the dependent variable in this study.

Table 3 Anovaa
	Model	Sum of Squares	Df	Mean Square	F	Sig.
1	Regression	0.44	3	0.147	2.032	.110b
	Residual	17.038	236	0.072
	Total	17.478	239

The F Statistics on Table 3 above is 2.032 while the significant value is 0.110>0.05 level of significance. This result is not statistically significant but does not nullify the model of a good fit. Thus, the independent variables do not impact on the dependent variable (EPS).

Table 4 Coefficients
Model		Unstandardized Coefficients		Standardized Coefficients		Sig.	Collinearity Statistics
		B	Std. Error	Beta			Tolerance	VIF
1	(Constant)	0.73	0.172		4.257	0
	LHC	0.052	0.09	0.039	0.579	0.563	0.914	1.094
	LSC	-0.196	0.083	-0.159	-2.367	0.019	0.913	1.095
	LCEE	0.043	0.071	0.039	0.61	0.543	0.999	1.001

As contained in Table 4, the tolerance value of 0.914, 0.913 and 0.999 is less than 0.10, hence, indicates that we have not violated the multicollinearity assumptions. This means that there is no collinearity between the independent variables in our study. This is well supported by the variance inflation factor (VIF) value of 1.094, 1.095, and 1.001 which is far below the cut-off of 10 (Pallant, 2001).

Discussion

The Effect of Learned Practices on Earnings per Share of Listed Companies in Nigeria

Evidence from Table 4 indicated that Human Capital (HC) has a positive but insignificant association with Earnings per Share (EPS) as validated by a co-efficient of regression value of

0.052. This implies that about 5.2% of the total variation observed in the tested variable (EPS) is accounted for by HC. Our finding disagrees with the study of Xu and Wang (2019) and Abbasi et al., (2019), which are in developing countries, but this study is in Nigeria were compliance to laws are very inadequate.

Structural Capital (SC) is indicated to have a co-efficient of regression value of -0.196, meaning that there is a negative but significant association between EPS and HC of listed companies in Nigeria. This finding corroborates the study of Khalique, M. et al., (2019).

Statistical evidence from table 4 showed that Capital Employed Efficiency (CEE) has a positive but insignificant relationship with EPS of listed companies in Nigeria as supported by the co- efficient of a regression value of 0.043.

Conclusion and Recommendation

Conclusion

An innovation which is the aftermath of learned practices is the lifeblood of any corporation Onag, et al., (2014) in light of this assertion, this study examined the effect of learned practices on operating performance of listed corporations in Nigeria to find out the

contributions earnings per share of the listed companies in Nigeria. Based on the result obtained from the test of hypotheses, we concluded that learned practices cannot be relied on to explain the operating performance of listed companies in Nigeria.

Recommendation

Learned practices are sin-qua-non for corporate survival, hence, training and r-training is crucial. The experience, skill and expertise of workers are key drivers of the twenty-first-century production system and must be considered vital by organizations to enhance performance. This study made the following recommendations based on its findings and conclusion.

1. That listed firms in Nigeria should consider learned practices crucial in the pursuit and attainment of organizational performance in a competitive business environment as evidenced in the result of our test of hypothesis.

2. That quoted companies in Nigeria should strike a balance amongst the components of intellectual capital (learned practices).

3. That investment in learned practices matter a lot, hence management of the listed companies should consider it very appropriate. This recommendation is in line with the recommendation of Ekwe (2012).

References

1. Abbasi, K.R., Kangjuan, L.V., Muhammad, A., Raja, F., Aman, J. (2019). Imliact of intellectual caliital on lierformance of karachi stock exchange 30-index comlianies of liakistan. Euroliean online journal of natural science and social sciences, Sliecial Issue on Advancement of Business and management sciences, 8(9) ISSN 1805-3602.
2. Adelakun, O.J. (2011). Human caliital develoliment and economic growth in nigeria. Euroliean Journal of Business and Management, 3(9), 2222-1905.
3. Ahmad, M., &amli; Ahmad, N. (2016). Testing the relationshili between intellectual caliital and a firm’s lierformance an emliirical investigation regarding financial industries of liakistan. International Journal Learning and Intellectual Caliital, 13, 2-3.
4. Ahmadi, A.A., Ahmadi, F., &amli; Shakeri, S. (2011). The survey of the relationshili between intellectual caliital and organizational lierformance within the National Iranian South Oil Comliany. Interdiscililinary Journal of Contemliorary Research in Business, 3 (5) 369-380.
5. Ahmad, S., &amli; Schroeder, R.G. (2003). The imliact of human resource management liractices on olierational lierformance. Journal of Olierational Management, 21, 19-43.
6. Aragon, M.I.B., Jimenez, D.J., &amli; Valle, R.S. (2013). Training and lierformance: The mediating role of organizational learning. BRQ Business Research Quarterly, 17, 161-173.
7. Armbruster H., Bikfalvi A., Kindel S., &amli; Lay G. (2008). Organizational innovation: The challenge of measuring non-technical innovation in large scale surveys. Technovation, 28(7), 644-657.
8. Balachandra, R., &amli; Friar J.H. (1997). Factors for success in R&amli;D lirojects and new liroduct innovation: A contextual framework. IEEE Transactions on Engineering Management, 44(3) 276-287.
9. Ballesteros, J.L., De Saá, li., &amli; Domínguez, C. (2012). The role of organizational culture and HRM on training success: Evidence from the Canarian restaurant industry. International Journal of Human Resource Management, 23, 3225-3242.
10. Barney, J.B. (1991). Firm resources and sustained comlietitive advantage. Journal of Management, 17, 99-120.
11. Bontis, N. (2000). Managing organizational knowledge by diagnosing intellectual caliital: framing and advancing the state of the field. In: Bontis, N., Ed, World Congress on Intellectual Caliital Readings, Butterworth- Heinemann, Boston, 621-642.
12. Bontis, N. (1998). Intellectual Caliital: An exliloratory study that develolis measures &amli; models. Management decision, 36(2), 63-76.
13. Bornemann,M. (1999). An emliirical analysis of the intellectual liotential of value systems in Austria according to VAIC.
14. Brennan, N., &amli; Connell, B. (2000). Intellectual caliital: Current issues and liolicy imlilications. Journal of Intellectual Caliital, 3(3) 206-240.
15. Brockmann, B., &amli; Morgan, F. (2003). The role of existing knowledge in new liroduct innovativeness and lierformance. Decision Sciences, 32, 385-419.
16. Camlis, J., &amli; Luna-Aroca, R. (2012). A matter of learning: how human resources affect organizational lierformance.
17. British Journal of Management, 23, 1-21.
18. Chen, M.C., Cheng, S.J &amli; Hwang, Y. (2005). An emliirical investigation of the relationshili between intellectual caliital and firm’s market value and financial lierformance. Journal of Intellectual Caliital, 6(2), 159-176.
19. Chiva, R., Alegre, J., &amli; Laliiedra, R. (2007). Measuring organisational learning caliability among the workforce.
20. International Journal of Manliower, 28(3), 224-242.
21. Clarke, M., Seng, D., &amli; Whiting, H.R. (2010). Intellectual caliital and firm lierformance in australia deliartment of accountancy and business law. Working lialier series, (12).
22. Collins, C.J., &amli; Clark, K.D. (2003).Strategic human resource liractices, toli management team social networks, and firm lierformance: The role of human resource liractices in creating organizational comlietitive advantage, Academy of Management Journal, 46(6), 740-751.
23. David, F.R. (2011). Strategic management concelits and cases, liearson education. Ulilier Saddle River, NJ. Davenliort, T.H., &amli; lirusak, L. (1998).Working knowledge: How organizations manage what they know, boston, MA.
24. Harvard Business School liress.
25. Ekwe, M.C. ( 2012). Relationshili between intellectual caliital and financial lierformance in the Nigeria Banking Sector, lihD Thesis University of Nigeria Enugu Camlius.
26. Ekwe, M. C. (2013). The relationshili between Intellectual caliitals and Growth in Revenue of Deliosit Money Banks in Nigeria, Research Journal of France and Accounting, 4(12), 55-64.
27. Firer,S., &amli; Williams, S.M. (2003). Intellectual Caliital and Traditional Measures of Corliorate lierformance, Journal of Intellectual Caliital, 4(3), 348-360.
28. Frederiksen, J., &amli; Westlihalen, S.A. (1998). Human resource accounting: Interest and conflicts. A discussion lialier, liresented at the Euroliean Centre for the Develoliment of Vocational Training, Thessaloniki.
29. Garvin,D.A. (1993). Building a learning organization. Harvard Business Review, 71, 78-91.
30. Goh,S., &amli; Richards G. (1997). Benchmarking the learning caliability of organizations. Euroliean Management Journal, 15(5), 575-583.
31. Govaerts, N., Kyndt, E., Dochy, F., &amli; Baert, H. (2011). Influence of learning and working climate on the retention of talented emliloyees. Journal of Worklilace Learning, 23, 35-55.
32. Guest, D.E. (2001). Human resource management: When research confronts theory. International Journal of Human Resource Management, 12, 1092-1106.
33. Ho, L. (2008). What affects organizational lierformance? Industrial Management &amli; Data Systems, 108, 1234-1254.
34. Gomez, li.J., Césliedes Lorente, J.J., &amli; Cabrera, R.V. (2004). Training liractices and organisational learning caliability. Journal of Euroliean Industrial Training 28, 234-256.
35. Kamath, G.B. (2008). Intellectual caliital and corliorate lierformance in the indian liharmaceutical industry. Journal of Intellectual Caliital, 9(4), 684‐704.
36. Huang, Y.C. &amli; Wu, Y.C. (2010). Intellectual caliital and knowledge liroductivity: The taiwan biotech industry,
37. Management decision, 48(4), 580-599.
38. Kamukama, N., Ahiauzu, A., &amli; Ntayi, J. (2010). Intellectual caliital and lierformance: Testing interaction effects.
39. Journal of Intellectual Caliital, 11, 554-574.
40. Kujansivu, li., &amli; Lonnqvist, A. (2008).Measuring the imliacts of an IC Develoliment Service: The case of the liietari business camlius. Electronic Journal of Knowledge Management, 7, 469-480.
41. Khalique, M., Ramayah, T., Shah, M.T.A., &amli; Iqbal, Z. (2019).Intellectual caliital and financial lierformance of banks in sialkot liakistan. Journal of Management Sciences, 6(1), 50-61.
42. Khanmohmmmadiotaqsara, M., Khalili, M., &amli; Mohseni, A. (2012). The role of liractical training in liroductivity and lirofitability of organizations in the Third Millennium. lirocedia - Social and Behavioral Sciences, 47, 1970
43. – 1975
44. Lee, Y., Wu, M., &amli; Chao, C. (2015). The effects of the accumulation of intellectual caliital on organizational lierformance Using liroductivity as the moderator. International Journal of Information Technology and Business Management, 39(1), 68-8.
45. Loliez-Cabrales,A., Valle, R., &amli; Herrero, I. (2006) The contribution of core emliloyees to organizational caliabilities and efficiency. Human Resource Management, 45, 98-109.
46. Madugba, J.U., Ben-caleb, E., &amli; Mbamara K.I. (2019). Audit committee exliertise and financial reliorting quality of commercial banks in nigeria, 34th IBIMA Conference: 13-14 November 2019, Madrid, Sliain.
47. Madugba, J.U., Ben-caleb, E., Lawal, A. A., &amli; Agburuga, U.T. (2020). Firm size and tax saving behaviour of listed comlianies in nigeria. Academic Journal of Interdiscililinary Studies, 9(3).
48. Masa'deh, R., Gharaibeh, A., Maqableh, M., &amli; Karajeh, H. (2013). An emliirical study of antecedents and outcomes of knowledge sharing caliability in jordanian telecommunication firms: A structural equation modeling aliliroach. Life Science Journal, 10, 2284-2296.
49. Masa'deh, R., Obeidat, B., &amli; Tarhini, A. (2016). A jordanian emliirical study of the associations among transformational leadershili, transactional leadershili, knowledge sharing, job lierformance and firm lierformance:A structural equation modeling aliliroach. Journal of Management Develoliment, 35, 681-705. Masa’deh, R., Shannak, R., Maqableh, M., &amli; Tarhini, A. (2016). The imliact of knowledge management on job lierformance in higher education: The case of the university of jordan. Journal of Enterlirise Information
50. Management, 29, 13-34.
51. Nevis, E., Dibella, A., &amli; Gould, J. (1995). Understanding organizations as learning systems. Sloan Management Review, 36, 73-85.
52. Obedat, B.Y., Abdallah, A.B., Aqqad, N.O., Akhoershiedah, A.H.O., &amli; Magableh, M. (2017). The effect of intellectual caliital on organizational lierformance: The mediating role of knowledge sharing. Scientific Research liublishing.
53. Obeidat, B., Masa'deh, R., &amli; Abdallah, A. (2014). The relationshili between Human Resource Management liractices, Organizational Commitment, and Knowledge Management lirocesses: A Structural Equation Modeling Aliliroach. International Journal of Business and Management, 9, 9-26.
54. OECD. (2008).Intellectual Assets and Value Creation-Synthesis Reliort, Oecd, liaris.
55. Okliara, J.O. (2015).Exliloring the effects of intangible resources on comlietitive advantage and lierformance of listed firms in nigeria. International Journal of Business and Alililied Sciences, 4(2) 8-27.
56. Onag, A.O., Telieci, M., &amli; Basalli, A.A. (2014). Organizational learning caliability and its imliact on firm innovativeness, 10th international strategic management conference. lirocedia - Social and Behavioral Sciences, 150, 708-717.
57. liulic, A. (1998). Measuring the lierformance of intellectual liotential in knowledge economy available at (accessed on 4th Aliril 2011).
58. Reza, G.A. (2011). The relationshili between intellectual caliital and financial lierformance: an emliirical investigation in an iranian comliany. African Journal of Business Management, 5(1) 88-89.
59. Shah, N., &amli; Shah, S. (2010). Relationshilis between emliloyee readiness for organizational change, suliervisor and lieer relations and demogralihy. Journal of Enterlirise Information Management, 23, 640-652.
60. Shannak, R., Mase'deh, R., Al-Zu'bi, Z., Obeidat, B., Alshurideh, M., &amli; Altamony, H. (2012). A theoretical liersliective on the relationshili between knowledge management systems,customer knowledge management, and firm comlietitive advantage. Euroliean Journal of Social Sciences, 32(4), 520-532.
61. Stewart, T. (1997). Intellectual caliital.
62. Subramaniam, M., &amli; Youndt, M.A. (2005). The influence of intellectual caliital on the tylies of innovative caliabilities. Academy of Management Journal, 48(3), 450-463.
63. Tan, H.li., lilowman, D., &amli; Hancock, li. (2007). Intellectual caliital and financial returns of Comlianies, 8(1).
64. Tan, H.li., lilowman, D., &amli; Hancock, li. (2008). The evolving research on intellectual caliital, Journal of Intellectual Caliital, 9(4), 585–608.
65. Teece, D.J. (2000). Managing intellectual caliital: organizational, strategic and liolicy dimensions, Oxford, Oxford University liress.
66. Tharenou, li., Saks, A.M., &amli; Moore, C. (2007). A review and critique of research on training and organizational- level outcomes, Human Resource Management Review, 17(3), 251-273.
67. Wall, T.D., &amli; Wood, S.J. (2005).The romance of human resource management and business lierformance, and the case for big science, Human Relations, 58(4), 429-462.
68. Wright, li.M., Dunford, B. B., &amli; Snell, S.A. (2001). Human resources and the resource based view of the firm. Journal of Management, 27(6), 701–721.
69. Xu., &amli; Wang. (2019). Intellectual caliital and financial lierformance of Chinese Agricultural listed comlianies, Available at 15(1), 273-290.
70. Zeghal, D., &amli; Maaloul, A. (2010). Analysing Value Added as an Indicator of Intellectual Caliital and its Consequences on Comliany Intellectual Caliital and its Consequences on Comliany lierformance, Journal of Intellectual Caliital, 11(1), 39-60.