Abstract

The study was based on the investigation and validation of the association between the most emerging traits of human capital in the organizations i.e. Emotional Intelligence (EI) and Organizational Learning Capacity (OLC) and further testing the moderating role of Individual Innovation among the faculty and staff of Higher Education Institutions (HEI’s) in Pakistan. The results show that EI has a significant contribution towards the OLC and when measured together with the trait of Individual Innovation the results significantly improved which suggest that individual innovation positively and significantly affect the relationship between EI and OLC.  The study has implication for policymakers for the enhancement of EI traits in their employees and also for the individuals to focus and improve the value of EI in their personality to gain the benefits of their innovation and organizational learning capacity.

Key Words

Emotional Intelligence, Organizational Learning Capacity, Individual Innovational, Education Sector of Pakistan

Introduction

In business management, we define an organisation as an artificial person created through mercantile law, which carries all the traits of any human being other than breathing. In the context of this the key organ who form & run any organization is an individual, and on later stages makes that organization flourish & learned, which helps the transformation of the organization by embedding individuals learning behavior trait (Ghosh, Shuck & Petrosko, 2012). 

Learning is known as a permanent change in behavior (Ugoani, 2017; Argyris & Schon, 1978), that also affect the cognitive process (Levitt & March, 1988), this happens when someone interacts with the environment (Ghosh, et al, 2012) and also occurs from experience (Ab.Aziz, 2010). Learning is a bi-fold tool which is used to transfer the knowledge most desired, primarily increase the organizational capacity secondary keep organization learned. 

The learning inside the organizations occurs at three levels (Sapie et al., 2015) i.e. ‘individual level’, ‘group level’ and ‘organizational level’. According to Senge (2006), learning is worth fully functionalized through the concepts of learning organization where an organization persistently strive to expand its capacity for making its future and empower its people to think and interact with its environment freely (Argyris & Schon, 1978).

Literature Review

Kazemi et al. (2013) have identified positive and strong relationship between the traits of EI and organizational learning, further review of this study proposed that emotional intelligence notably impact team learning attitudes (Ghosh et al., 2012). The factors that influence employee behavior by the effects of emotional intelligence, impacts organizational learning (Kazemi, Baghban, et al., 2013). Scott-Ladd and Chan (2004) earlier to Kazemi & Ghosh studies claimed that higher emotional intelligence leads towards more effective organizational learning, predominantly in the area of participative decision making.

It is very important for the managers to show commitment toward organizational learning, to know the importance of empowerment (Aydin & Ceylan, 2009). The employees must be considered as partners and they must be having their discretion to make a decision because the organization, is not supposed to be the one to define the scope for every activity (Hormiga, Hancock, & Valls-Pasola, 2013). The main focus must be towards organizational gains as it will help to improve the 

organization’s capability to assimilate learning more swiftly than the competitors which in fact would be beneficial for the organization (De Geus, 1988). More often, people with high emotional intelligence have the ability to relate the incompatible (Tsakalerou, 2016) & exposed way and they are always eager for involvement in doing things in a new way (Gardner and Stough, 2002), they are at their best comfort level as they are working at a place where the individual and team contributions are appraised & recognized (Goleman, 1995; Smith, 2002). They are likely to be predisposed in accepting or rejecting such occurrences of assigned tasks as Schutte et al. (1998) highlighted that employees with a greater level of EI will be more beneficial for the organization as they want the results that benefit others as well as themselves (Tsakalerou, 2016). Furthermore, their contribution towards organizational learning will be far better as they have higher concentrations of general intelligence, emotional knowledge (Johnson & Indvik, 1999), regulation and perception (Scott-Ladd and Chan, 2004). 

Grounded in the above discussion, it is proposed that:

H1: Emotional Intelligence Positively & Significantly Effects On Organizational Learning Capacity.

Emotional Intelligence and Individual Innovation:

The increasingly recognized key characteristic of leaders in contemporary organizations is the interpersonal dimension of leadership (Goleman, 1995, 1998). There are few mechanisms that can clarify why emotional intelligence can be the factor that helps in achieving innovation (Tsakalerou, 2016). Firstly, employees having better EI have a tendency to maintain a good relationship with their colleagues and staff (Jafri et al., 2016; Goleman, 1995; Wong and Law 2002). This develops more interaction and exchange of information among colleagues, which helps in generating new ideas for different issues (Jordan, 2004), and formulate various solutions of difficult problems at work, therefore, regarded as ‘idea generation’ (Jafri et al.,2016; Smith, 2002). In addition, peace of mind, stable life, and focused attitude are some of the most valuable traits of employees with high EI that leads them to generate effective ideas, translate them into the environment and bring them to a level of idea realization (Abubakr and Al-Shaikh, 2007). Thus, the employees having a greater value of EI inspire their co-workers by producing innovative ideas (Jordan, 2004) and staying positive and flexible in their working environment (Ivcevic, Brackett, et al., 2007).

According to Sy, Tram, & O’Hara, 2006), previous research unfolds that proper management of emotions can enhance the morale of individuals and teams that make the organizations achieve targets and also increase in productivity gains that ultimately enhance the commitment, trust, and loyalty of the individuals. Till now we are well aware that work performance and EI are directly proportional to each other, various studies also suggested that people having greater emotional intelligence exhibit extra-ordinary behaviors in a positive sense. For instance, Charbonneau and Nicol (2002) in their study on the teenagers identified that youngsters with higher EI tend towards generosity and righteous behavior citizenship. Similarly, Carmeli and Josman (2006) proved a strong association between EI and creative traditionalism. In another research by Wong and Law (2002) validated that greater EI of employees leads to better job performance. Dincer & Orhan (2012) found a noteworthy relationship between employees EI and individual innovation in their study among 332 private bank employees.

H2: EI Will Tend To Produce Positive & Strong Relationship With Individual Innovation.




Individual Innovation & Organizational Learning Capacity:

Organizational learning is aimed to empower advancement & adaptability through individual reactions (Çömlek et al., 2012) and the power to take decisions at all levels in the organization (Solomon, 1994). In a worldwide economy, organizations that pay attention to learning and development will probably deliver inventive arrangements as essential for global competitiveness (Lundvall and Nielson, 2007). A firm is considered to be innovative because of the manner in which it empowers learning among its workers and it is the fact which actually enhances the overall capability of the organization to be innovative (Sapie et al., 2015). Thus, organizational learning is a major factor that enhances the value of human capital (Çömlek et al., 2012), therefore it viewed as contributing attribute that can expand the work environment build up the abilities of workers (KhairulAnuar, 2009).

Gomes & Wojahn (2017) identified that the association between OLC and organizational innovation; however, empirical evidence to support this perspective is too limited in SME’s. In their research, they have identified that innovative performance of an individual is affected by organizational learning capability. The key to this lies in motivating employees so that there is willing dissemination to learning within the company (Al-omari, 2017). And this is where the alignment between learning, behavior (motivation), and innovation becomes important (Gopinath, 2009). OLC has an effect on innovativeness and the relationship among both variables/traits are acknowledged as a source of competitive advantages in the metalworking industry (Çömlek, Kitapç?, et al. 2012).

Sapie et al. (2015) measured the degree of the OL and IWB among 254 employees of SMEs in Malaysia and developed the strong linkage between the learning organizations capacity and innovative work behavior and innovative human capital and recommended as a vital factor for the survival of SMEs in the global competitiveness based economy. 

H3: Individual Innovation Will Have Positive & Significant Association With Organizational Learning Capacity.

Reviewed literature has identified that emotional intelligence has directly and indirectly linkages with Individual Innovation and Organizational Learning Capacity (Al-omari, 2017; Imran et al., 2014; Islam et al., 2011), however trait of Individual Innovation affect the relationship between EI and OLC has not been tested in the studied literature. Thus, this research provides the association in enhancing the OLC through EI by integrating the aspect of Innovation and suggest appropriate measures as well as contributing knowledge through empirical results. This establishes the following hypothesis for the existing study:

H4: Individual Innovation will positively and it significantly mediates between EI & OLC.

H5: Individual Innovation will positively and it significantly moderates the relationship of EI & OLC.

Methodology

This is an empirical research in which primary data from the sample of the population was acquired to test the hypothesis. The instrument was developed from the adopted questionnaire of previous researches and was pre-tested on the sample of 25 faculty members and administrative staff of the HEIs to inspect its construct validity. The construct validity was tested using cronbach’s alpha test which resulted the value above 0.70. Emotional intelligence was measured using 33 items scale developed by Schutte & others in 1998, based on the theoretical model of Solevy & Mayer in 1990. Individual innovativeness was measured using 20 items self-report scale, developed by Hurt, Joseph and Cook in 2013 (Hurt, Joseph, & Cook, 2013). Organizational learning capacity was measured using 16- item “Organizational Learning Capacity Scale (OLSC)” developed by Kimberly D. Bess, Douglas D. Perkins and Diana L. Mccown (Bess, Perkins, et al., 2011).

Figure 1

Conceptual Framework



Descriptive Analysis

The descriptive analysis provides an overview of the data in the study. It helps in identifying the statistical distribution or the variability of the collected data in terms of central tendency and variation from mean value so that dispersion in the data may be observed.    

Following table illustrations the descriptive statistics estimates with measures of frequencies, measure of central tendencies, measures of dispersion, skewness, and kurtosis for N=367. Minimum and maximum mean value for the 5 Likert scale instrument remained to 1.25 to 4.68 which indicates that there is variation in the respondents. SD of EI, II & OLC remained at 0.404, 0.475 and 0.557 respectively which indicates that the number for EI and II remained close to the mean value whereas, number of OLC responses were a bit spread out.

Table 1.  Descriptive Statistics

	Min	Max	Mean	Std. Deviation	Skewness
					Stat	Std. Error
Emotional Intelligence (EI)	1.97	3.94	3.17	0.404	-0.348	0.129
Individual Innovation (II)	1.75	4.25	3.24	0.475	-0.443	0.147
Organizational Learning Capacity (OLC)	1.25	4.68	3.21	0.557	-0.355	0.132

The results show that the skewness of Emotional Intelligence (-0.348), Individual innovation (-0.443) and  Organizational Learning Capacity (OLC) (-0.355) lies in the category of approximately symmetric which indicate that the distribution is skewed toward the left tail.

While analyzing the gender statistics in the valid responses it was highlighted that male respondents were more prominent. 56.13% were male respondents while  43.87 were female respondents.

Table 2. Gender Analysis

Gender	No	Percent
Male	206	56.13%
Female	161	43.87%
Total	367	100%

While analyzing the age group of the respondents, it was probed that most of responses were from the age group of  31-40 years i.e. 44.69% which indicates that maximum respondents were from mid-career which were mostly Lecturers and some were fresh PhDs and Assistant Professors.  Age group analysis of this research can be evaluated in a perspective that Organizational Learning Capacity have an effect on the younger people.

Table 3. Age group Analysis

Age group (years)	No	Percent
Below 30	57	15.53%
31- 40	164	44.69%
41- 50	50	13.62%
51- 60	89	24.25%
60 Above	7	1.91%
Total	367	100%

Structural Equation Modelling (SEM)

SEM technique was adopted to test and validate the developed hypothesis. The analysis in Structural Equation Modelling was carried out at two levels. One is the Measurement model also known as the outer model and second was the Structural model also called as inner model. The outer or the measurement model specifies the relationship between the latent variables and their observed indicators whereas, the inner or the structural model is related to the relationships between exogenous and endogenous latent variables. For measurement model construct reliability and validity of the instrument and data were tested to further carry out the structural model analysis.

 

Construct Reliability and Validity

Reliability analysis provides the extent to which a construct of a scale for measuring the variable is reliable and consistent. The most common measure to result acquired through reliability analysis is referred to as Cronbach alpha (?) which is mostly used when multiple Likert questions survey is used in a study. After running the PLS Algorithm in SMART-PLS following analysis for measurement model was obtained:

Figure 2

Simple Model



Table 4. Construct Reliability and Validity

Construct	Cronbach's Alpha	rho_A	Composite Reliability	Average Variance Extracted (AVE)
Emotional Intelligence (EI)	0.751	0.848	0.783	0.551
Individual Innovation (II)	0.709	0.820	0.769	0.498
Organizational Learning Capacity (OLC)	0.803	0.876	0.843	0.679

The Cronbach’s Alpha of all three variables was above than the standard limit of 0.7 which signifies that reliability of the scale is good and further analysis can be carried out. However, in PLS-based research, the composite reliability keeps more importance than the alpha value. Composite reliability leads to higher estimates of true reliability. The value of composite reliability should be equal to or greater than 0.70 for an adequate model for confirmatory purposes (Henseler et al., 2012). Hence in this research, the value of composite reliability of EI, II, and OLC stood at 0.783, 0.769 and 0.843 therefore considered appropriate for further analysis.

Discriminant validity is another powerful analysis of SEM which identifies the strength of the relationship among the variables under study. The values of discriminant validation with Fornell Larcker criterion are as under:

Table 5. Discriminant Validity - Fornell Larcker Criterion

Construct	Emotional Intelligence (EI)	Individual Innovation (II)	Organizational Learning Capacity (OLC)
Emotional Intelligence (EI)	0.789
Individual Innovation (II)	0.646	0.705
Organizational Learning Capasity (OLC)	0.515	0.543	0.824

The diagonal values of the Discriminant Validity table show the square root of the AVE value and the other values shows the correlation with other latent variables. Since the top value of each factor column is higher than the correlation values, therefore the data fulfills the criteria of discriminant validity. 

Figure 3

Model with loading and Moderating effect



The values mentioned in the blue circle depicts the variance explanation of endogenous latent variable by the exogenous variable whereas, numbers on the arrow are the path coefficients which explain that how strong effect on one variable is on another variable. Therefore, the coefficient of determination, R2 for Organizational Learning Capacity (OLC) – the endogenous variable is 0.749 which means that two latent variables (Emotional Intelligence and Individual Innovation) substantially explain 75% of the variance in OLC. Whereas, Emotional Intelligence moderately explains Individual Innovation with 41% of the variance. 

The inner model suggests that Individual Innovation (II) has the strongest effect on Organizational Learning Capacity (OLC) with path co-efficient value of 0.673 whereas, Emotional Intelligence (EI) has a lower effect on OLC (0.258). The effect of EI on Individual Innovation is strong with path co-efficient value of 0.646. Interestingly II as a moderating variable does not affect the relationship between Emotional Intelligence and OLC  as the path co-efficient value stands at -0.013.



Checking Structural Path Significance in Bootstrapping

After having satisfied with the instrument, data validity, and reliability, structural path significance was tested using a bootstrapping algorithm in SmartPLS for both the next inner and outer model. SmartPLS generate T-statistics for significance testing. Once the bootstrapping completed, path Co-efficient (Mean, Std Dev, t_values) was reviewed for the acceptance of the hypothesis. All the T-statistics were found larger than 1.96, except for the moderating effect of II, therefore, pr0claimed that outer model loadings are highly significant. Further, the P values of all the developed hypothesis were less than .05, therefore, were all accepted.  

Table 6. Path and Hypothesis Table Single Effect

Hyp	Linkages	Beta Values	Std Error	t-values	P Values	Decision
H1	EI à OLC	0.258	0.061	4.206	0.000	Accepted
H2	EI à II	0.646	0.034	18.899	0.000	Accepted
H3	II à OLC	0.673	0.061	11.029	0.000	Accepted

Table 7.  Path and Hypothesis Table Mediation Effect

						Confidence Interval
						UL	LL
Hyp	Linkages	Beta Values	Std Error	t-values	P Values	2.5%	97.5%	Decision
H4	EI à II à OLC	0.435	0.049	8.892	0.000	0.350	0.544	Accepted

Table 8.  Path and Hypothesis Table Moderation Effect

Hyp	Linkages	Beta Values	Std Error	t-values	P Values	Decision
H5	Moderating Effect II à OLC	-0.013	0.029	0.426	0.670	Rejected

The mediation effect of Individual Innovation was significant in this research, therefore, it was concluded that Individual Innovation significantly plays mediating role between Emotional Intelligence (EI) and Organizational Learning capacity (OLC) which means that the path from EI to OLC must satisfy the conditions and requirements of Individual Innovation. On the other hand, the moderation effect of Individual Innovation on the relationship between EI and OLC is not significant with lower t-value and higher P-value therefore the developed Hypothesis 5 was rejected for this research. 



Conclusion and Recommendations

Emotional Intelligence has been identified as a key trait for successful job completion and personality development trait. Pakistan is a developing country where systems are still in the infant stage and are striking very rapidly for the need to cope up the international requirements. On the other hand education reforms are enduring across the world where the European Bologna process has emerged across the world where annually based degree system is converted to credit hours based degree and many other aspects are under review.   In such a scenario, the change acceptance by the employee’s has a very critical role in accomplishing the overall growth of the organization at national & international level (Ugoani, 2017). For this purpose, it is strongly recommended that heads of the universities and HEI’s should train their people for enhancing their learning capacity and innovation capabilities through the building and improving the Emotional Intelligence, which ultimately reduces angriness, restlessness and enhance the overall efficiency of the Individual as well as organization. 

References

• Ab. Aziz , Y. (2010). Organizational Behavior A Strategic Approach. Sintok: Universiti Utara Malaysia Publisher.
• Abubakr, M. S. and F. N. Al-Shaikh (2007). Emotional intelligence at work: Links to conflict and innovation. Employee Relations 29(2), 208-220
• Ahmad, A., & Khan, A. (2017). Provincial Autonomy and Devolution of Language Policy in Pakistan: Retrospect and Prospect. Dialogue, 12(4), 361-378.
• Ahmad, A., Hussan, S., & Malik, M. S. (December 2018). An Overview of English Language as a Window of Economic Opportunity in Pakistan. Review of Economic and Development Studies, 4(2), 281-291.
• Al-omari, M. (2017). Engineers Innovative Work Behavior : The Role of Emotional Intelligence. European Journal of Business and Management, 9(21), 8-18.
• Argyris, C., & Schon, D.A. (1978). Organizational learning: A theory of action perspective. Reading, MA: Addision Wesley
• Aydin, B and Ceylan, A (2009), Does organizational learning capacity (OLC) have impact on organizational effectiveness? Research analysis of the metal industry. Development and Learning in Organizations, 23 (3) 21 - 23.
• Bess, K. D., D. D. Perkins, et al. (2011). Testing a measure of organizational learning capacity and readiness for transformational change in human services. Journal of prevention & intervention in the community, 39(1), 35-49.
• Carmeli, A., & Josman, Z. E. (2006). The relationship among emotional intelligence, task performance, and the relationship among emotional intelligence, task performance, and organizational citizenship behaviors. Human Performance, 19(4), 403-419.
• Charbonneau, Danielle. & Nicol, Adelheid. (2002). Emotional Intelligence, and Leadership in Adolescents. Personality and Individual Differences, 33, 1101-1113.
• Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (295-336). Mahwah, New Jersey: Lawrence Erlbaum Associates.
• Çömlek, O., Kitapçı, H., Çelik, V., & ÖzÅŸahin, M. (2012). The effects of organizational learning capacity on firm innovative performance. Procedia - Social and Behavioral Sciences, 41(6), 367-374.
• De Geus, A.P. (1988). Planning as learning. Harvard Business Review, 88(2), 70-74.
• Dincer, H. and N. Orhan (2012). Relationship between emotional intelligence and innovative work behaviors in Turkish banking sector. International Journal of Finance & Banking Studies, 1(1), 21-28.
• Gardner L, Stough C. 2002. Examining the relationship between leadership and emotional intelligence in senior level managers. Leadership and Organization Development Journal, 23(2): 68-78.
• Ghosh, R., Shuck, B., & Petrosko, J. (2012). Emotional intelligence and organizational learning in work teams. Journal of Management Development, 31(6), 603-619.
• Goleman, Deniel. (1995). Emotional Intelligence. New York, NY: Bantam.
• Goleman Deniel. (1998). What makes a leader? Harvard Business Review Nov/Dec, 92-102.
• Gopinath, M. (2009). Organizational Learning and its Linkages with Employee Innovation/ Behaviors. Journal of Contemporary Research in Management, (Oct-Dec), 31-41.
• Gomes, G., & Wojahn, R. M. (2017). Organizational learning capability, innovation and performance: study in small and medium-sized enterprises (SMES). Revista de Administração, 52(2), 163-175.
• Henseler, Jörg; Ringle, Christian M.; & Sarstedt, Marko (2012). Using partial least squares path modeling in international advertising research: Basic concepts and recent issues. Pp. 252-276 in Okzaki, S., ed. Handbook of partial least squares: Concepts, methods and applications in marketing and related fields. Berlin: Springer.
• Hormiga, E., Hancock, C., & Valls-Pasola, J. (2013). The relationship between employee propensity to innovate and their decision to create a company. Management Decision, 51(5), 938-953.
• Hurt, H. T., Joseph, K., & Cook, C. D. (1977). Scales for the measurement of innovativeness. Human Communication Research , 4, 58-65.
• Hurt, H. T., Joseph, K., & Cook, C. D. (2013). Individual Innovativeness (II) .Measurement Instrument Database for the Social Science. Retrieved from