Abstract
Some school teachers find the changing nature of the teaching profession frustrating if they are unable to modify their current emotions to suit the desired emotional states. The purpose of the present study is to investigate the role of the emotional intelligence (EI) model in predicting school teachers’ job performance in five selected secondary schools in Dungun, Terengganu. The EI model is developed to assess the secondary school teacher’s performance based on the theory proposed by Goleman. Using the EI model that consists of four dimensions: self-awareness, self-regulation, social awareness, and relationship management, the researchers hope that school teachers’ job performance can be measured more accurately. Data from 196 teachers were analysed using Smart-PLS and the results indicate that self-regulation, social awareness, and relationship management are significant in predicting school teachers’ job performance. The results of the study signify that school teachers need to improve the level of their self-regulation, social awareness, and relationship management to assist them in improving their overall job performance. It can be done by monitoring the self and others' emotional states and taking necessary actions to establish relationships with others, especially the students.
Keywords: Job performance, relationship management, social awareness, self-regulation, self-awareness
Introduction
The educational sector is among the critical sectors that contribute to the country’s development especially when the country is working towards achieving a high-income status (Chan et al., 2015). Among other efforts, Malaysia needs to establish a good education system because a good system helps transform Malaysia from a middle-income country to a high-income nation (Yoke & Panatik, 2016). Teachers in secondary schools are facing great issues and challenges. They are preparing students who are going to sit for two compulsory national-level examinations. This responsibility creates a big pressure for secondary school teachers to exert their best efforts to ascertain that students are mentally well-prepared and ready for those examinations. Other than that, their working environment, student dispositions and behaviours, massive workload, and parents’ expectations also contribute to the psychological distress of school teachers (Ishak et al., 2010).
Mohamad and Jais (2016) claimed that massive workloads and responsibilities have caused negative emotional consequences among Malaysian teachers. This phenomenon is expected to be worse compared to the last two decades if there is no effort made by the government to address this problem. The Star (2016) reported that a female teacher who had experienced excessive stress and criticism of her work attempted suicide by drinking poison. The reason for this action is that teachers today are not only responsible for educating but also expected to execute other functions including managerial and administrative roles that require their time commitment, attention to detail, and extra energy. Sometimes, parents’ unnecessary demands and inappropriate attitudes add to their stress levels and affect their mental health. Naqvi et al. (2016) demonstrated that teachers with low EI are inclined to exhibit low job performance because they are mostly incapable of comprehending and recognizing their emotions and incompetency in managing their actions and social skills and are easily affected by unfavourable emotions.
However, school teachers who are skillful at assessing their feelings are adept at identifying their necessities and are more attentive to their felt emotions to accomplish their goals, which will help them to achieve superior job performance. Furthermore, Mohd. Ishak et al. (2010) claimed that teachers who are great at managing their emotions or empathic tend to be more interested in other people’s emotions, especially in comprehending students’ needs. These groups of teachers are remarkably more committed than the others and possess effective teaching competencies. Mohamad and Jais (2016) also said that teachers with higher EI degrees will do their job better than others. Thus, to ameliorate teachers’ job performance, their levels of EI must be further increased (Asrar-ul-Haq et al., 2017).
Although there are several research that have been undertaken to examine the role of EI in influencing teachers’ job performance, additional study is required to verify and confirm the previous research findings by using more specific samples: secondary school teachers. Although they are in the same profession, the nature and demands of the job are quite different as secondary school teachers are required to perform a variety of tasks and have more responsibilities as compared to other types of school teachers. Having that focus on mind, the present study is anticipated to ameliorate the existing knowledge on the function of EI in influencing secondary school teachers’ job performance.
Literature Review
Job Performance
Job performance relates to the actions and behaviours of people at work. Job performance is the total anticipated value derived from the employees’ behaviour when they are performing their tasks at a designated period where employers normally assess and reappraise their employees’ work and rate their achievement based on their capabilities to accomplish the assigned tasks and job given within the specific time allocation. Borman (2011) defined employee job performance as the total expected value to the organization of the discrete behavioural episodes that an individual carries out over a period.
In general, EI and job performance have been found to have a positive and significant link and people who possess higher degrees of EI normally will be more thriving when performing cognitive tasks as compared to those who have lower degrees of emotional intelligence. Asrar-ul-Haq et al. (2017) conducted an EI study among teachers in Pakistan. They discovered that teachers with higher EI levels will usually outperform others in their jobs. People with high EI ability can manage and regulate their negative emotions and don’t allow these emotions to distract them from concentrating on their job which will consequently improve their job performance (Asghari Aghdam & Mahjoub, 2013). EI relates to the abilities of individuals to identify and regulate their emotions and those of others who exist in their surroundings (Goleman, 2001). Goleman (2001) proposed four main competencies from the EI model, which are known as relationship management, social awareness, self-regulation, and self-awareness.
Therefore, the present study attempts to identify and analyse the four-dimensional construct of EI, which encompasses four dimensions: self-awareness, self-regulation, social awareness, and relationship management. It also aims to find out whether school teachers’ job performance is influenced by the four-dimensional constructs of EI.
Self-Awareness
Self-awareness is the recognition of one’s own feelings and feelings of others (Rexhepi & Berisha, 2017). Shafiq and Rana (2016) defined self-awareness as the ability to recognize one’s feelings, differentiate between them, know what one is feeling and why, and know what causes the feelings. Ramirez-Asis et al. (2021) defined emotional self-awareness as a way of identifying a person's emotions and how they could affect him. Maqbool et al. (2017) stated that the first step to becoming emotionally intelligent is to be self-aware of own emotions.
Self-awareness concerns the ability to comprehend an individual’s own emotions, personalities, beliefs, strengths, and weaknesses (Stosny, 2011). Self-awareness helps people realize their emotions and how the changes in emotions will affect their daily lives. People who have self-awareness are quick to detect the changes in their emotions and know how the emotions influence them. Asghari Aghdam and Mahjoub (2013) in their studies among school teachers discovered that teachers who possess high self-awareness exhibit high job performance. Those who are doing a job that requires them to manage their emotions well such as in the teaching profession must be aware of themselves and their emotions when performing the job (Naqvi et al., 2016).
Perera (2021) postulated that emotional self-awareness is a component of personal competence (self) and self-awareness involves the ability to handle the capacity to “administer one's own and others' emotions successfully”. The ability to stay positive in challenging times and focus on critical decision-making are reflections and indicators of good management of emotions. It is therefore critical for teachers to be equipped with emotional self-awareness since they are required to control their emotions to avoid experiencing any emotional burst that might interrupt classroom activities. Therefore, based on the previous review of the literature it can be seen clearly that self-awareness plays an important role in influencing teachers’ job performance. Therefore, the following hypothesis is stated:
H1: Self-awareness will influence secondary school teachers’ job performance.
Self-Regulation
Self-regulation is the ability to monitor and control own behaviour, emotions, or thoughts, altering them following the demands of the situation. Self-regulation is the process that enables individuals to guide their goal-directed activities over time and across changing circumstances, including the modulation of thought, affect, and behaviour (Steinbauer et al., 2018). They also stated that EI is directly related to teachers’ performance.
According to Stosny (2011), self-regulation is the ability to act in the best possible manner for the extended future benefits without violating any ethical beliefs that will induce feelings of guilt, shame, and anxiety in the future. Self-regulation shows how teachers control themselves when dealing with their students and performing other tasks and functions besides teaching. Teachers who possess superior self-regulation know how to keep their actions and emotions in control (Pekrun, 2021) and refrain from dictating negative actions as they understand that all negative emotions and behaviours will create a bad image and reputation for their teaching profession. Another study among Malaysian teachers also discovered a positive connection between emotional self-regulation and teachers’ job performance (Mohamad & Jais, 2016).
Self-regulation ensures teachers can manage themselves well by allowing them to think about the impact of their actions on people surrounding them and how to avoid engaging in undesired conflicts. Bakker and de Vries (2021) claimed that individuals with high EI will be able to recognize their job strain and fatigue, and consequently be able to regulate their strain. These individuals can be categorised as those who can regulate their feelings, emotions, and behaviour when dealing with others. Therefore, it is paramount for teachers to possess emotional self-regulation in performing their tasks since their profession requires them to interact with students, other teachers, and administrative staff who have a myriad of perceptions, emotions, temperaments, and behaviours.
Pekaar et al. (2018) claimed that self-regulation is predictive of reduced stress, increased work engagement, and improved objective performance. Moreover, these authors found that social work trainees who were able to recognize their own emotions (including fatigue) engaged in more emotion regulation behaviours and more often proactively asked for social support, coaching, and feedback (i.e., job crafting), resulting in higher levels of well-being (Pekaar et al., 2018). In another research, Fathi et al. (2021) found that emotional regulation is important to reduce burnout among Iranian teachers. The appraisal of own emotions particularly fostered adaptive self-regulation when trainees regulated their emotions. From the above discussion, the hypothesis below is highlighted:
H2: Self-regulation will influence secondary school teachers’ job performance.
Social Awareness
Empathy is the experience of understanding another person’s condition from his perspective. A person places himself in another person’s shoes and feels what he is feeling. Empathy is known to increase prosocial (helping) behaviours. It is used to describe a wide range of experiences. Emotion researchers generally define empathy as the ability to sense other people’s emotions, coupled with the ability to imagine what someone else might be thinking or feeling. Social awareness is a fundamental ability to comprehend the emotions (Goleman, 2001), needs, and concerns of others (Wolff, 2005). It allows one to navigate the social environment (Salovey & Mayer, 1990), and have a way of taking in what people are saying and finding ways to relate to them, perceive emotions, and utilize them in an effective manner (Gunu & Oladepo, 2014).
Madani and Asgari (2014) in their study in Iran found that social awareness and job performance are positively related. Teachers with high social awareness will be able to quickly detect any peculiarities in their student’s behaviour. These teachers are always interested in students’ well-being and are always willing to assist their students at any time. Similarly, Krishnan et al. (2018) in their study among school teachers in Malaysia support the earlier findings of Madani and Asgari (2014). In a different research setting, Alferaih (2017) established that EI is an important determinant of job performance among Saudi banking managers. Granziera and Perera (2019), on the other hand, found that teacher self-efficacy (including social awareness) predicted work satisfaction via engagement. Therefore, the following hypothesis is forwarded for testing:
H3: Social awareness will influence secondary school teachers’ job performance.
Social Skills (Relationship Management)
Social skills, also called people skills, refer to a person's talent in managing relationships with others and building systems (Yan et al., 2018). The set of social skills includes respect for others, mutual regard, commitment, openness, tolerance, empathy, negotiation, communication, etc. (Rexhepi & Berisha, 2017). It involves the ability to meet each other’s needs, relate to each other over time, and exchange information about one's feelings, thoughts, and ideas. Social interaction provides many advantages. It gives the individuals confidence and social acceptance. It helps managers in many ways, including doing many things that cannot be completed alone, for example, getting support from a team or completing a project (Rexhepi & Berisha, 2017).
Social skills or relationship management is related to the way people manage their relationships with others (Stosny, 2011). It is related to how they will correctly respond to people around them based on their current position and required needs. This assumption has been well established to affect teachers’ job performance (Li et al., 2018; Saleem et al., 2020). As academics, teachers are not only required to communicate with their students but also to address and manage other greater issues and concerns from their counterparts to encounter high anticipations and requisitions from parents and to follow the changing policies by the government (Naqvi et al., 2016). Thus, the relationship is hypothesized as follows:
H4: Relationship management will influence secondary school teachers’ job performance.
Research Methods
This study examines the association of EI and its four dimensions with school teachers’ job performance in the context of Malaysia, where very few studies have explored such a topic so far. The research approach that is being used in the present study is quantitative research. The population frame chosen for the study consists of 351 school teachers from five secondary schools in Dungun, Terengganu, Malaysia. For sampling purposes, stratified random sampling was utilized to select the samples for the study. It is a cross-sectional study using a survey research design whereby data were collected once using a structured survey questionnaire.
Apart from demographic factors, a five-point Likert scale starting from 1 for strongly disagree to 5 for strongly agree was utilized to gauge respondents’ perception on all latent constructs in the survey instrument. Construct measurement for EI was adapted from Schutte et al. (2007) Model: SSEIT (Self Report EI Test). Measurement for individual employees’ job performance was adapted from Koopmans et al. (2014). In a probabilistic research sampling, a minimum of 196 samples are needed to adequately represent the population of 351 (Sekaran & Bougie, 2016). Nonetheless, 200 questionnaires were distributed to overcome the issue of non-response. In total, 140 responses were received, equivalent to a 70% return rate. Out of these 140 responses 22 were unusable and subsequently removed leaving 118 usable questionnaires for analysis.
Findings
Common Method Variance
In the SEM-PLS context, common method variance is a response error that is rooted in the utilized measurement method, and not by the scheme of causes and effects in the studied model (Kock, 2015). Common method variance could possibly tarnish the credibility of a study when the research adopts data from a single source (Mackenzie et al., 2011). Other factors for instance, the instructions given in a questionnaire or the measurement scales provided by the researcher, or the implicit social desirability connected with responding to items in the survey instrument in a definite way can drive respondents to answer in some similar fashion that can lead to an erroneous conclusion from the study.
To treat this condition, the study applied a statistical procedure namely the collinearity test, as proposed by Kock and Lynn (2012). As mentioned by Kock and Gaskins (2014), the test is a complete process for conducting concurrent assessments of both vertical and lateral collinearity. To set this, the variance inflation factor (VIF) for all latent variables in the model was computed. If the result is more than 3.3 it indicates that the model is likely to be affected by common method variance. On the other hand, if all VIF values deriving from a collinearity test are equal to or lesser than this threshold value, the model is free from common method variance.
In the present study, the full collinearity test was performed by regressing a marker variable (random number) generated from the latent variable scores from each construct to each latent variable in the studied model. The results in Table 1 show that all VIF outputs of the latent variables in the model show values less than 3.3. Hence, the model is confirmed to be free from the common method variance issue (Kock & Lynn, 2012).
The current research study employed the Partial Least Squares (PLS) Structural Equation Modelling (SEM) process as recommended by Ringle et al. (2015) that consists of two stages of analytical procedure i.e. measurement model and structural model by using the SmartPLS 3 software version 3.2.8. Before computing the structural modelling, the research analysed the latent constructs’ measurement model for their items’ dimensionality, validity, and reliability as recommended by Henseler et al. (2015). Cronbach’s (α) and composite reliability (CR) were also used to test the assumptions.
Measurement Model
The study comprises five latent variables namely job performance (JP), self-awareness (SA), self-regulation (SR), social awareness (SOA), and relationship management (RM). Table 2 presents the output of the analysis of the reliability and validity of the data in the study. Gefen et al. (2000) suggested that the composite reliability (CR) values should be more than 0.70 to indicate that these constructs own a sufficient degree of internal consistency. Additionally, the average variance extracted (AVE) values above the minimum threshold value of 0.5 demonstrate good convergent validity (Bagozzi & Yi, 1988). Hair et al. (2014) suggested that having this threshold value denotes that the items in each construct explain more than 50% of the variances in the constructs. As a rule of thumb, item loading higher than 0.5 for indicator reliability is considered a necessity (Kim, 2010). However, items with loading between 0.4 and 0.5 can be removed if they decrease the CR and AVE beyond their respective threshold values (Kim, 2010), and any item’s loading that is less than 0.4 can be considered for removal.
In this study, three items: JP5 (in Job Performance), SA2 (in Self-Awareness), and RM1 (in Relationship Management) were removed due to low loading from their respective constructs to achieve the acceptable level of convergent validity. The removal of these items is meant to raise their corresponding construct’s AVE values above the 0.5 threshold. Nonetheless, there were no issues on each construct’s CR after the removal of these three items. The convergent validity is now verified, and the analysis can now proceed to evaluate the data discriminant validity.
As shown in Table 3, following the suggestion given by Henseler et al. (2015), the heterotrait-monotrait (HTMT) ratio of correlations criterion was used to determine the discriminant validity of all latent variables in the model. As the correlation values of the respective constructs did not exceed the HTMT criterion threshold value of 0.90 (Henseler et al.), the discriminant validity is confirmed. Consequently, it is now appropriate to proceed with structural measurement analysis.
Structural Model
As presented in Table 4, the bootstrapping procedure was utilized to test the hypotheses by generating results for each path relationship in the model. Bootstrap sub-samples using 5000 cases were chosen to allow for the estimation of the model in each sub-sample (Hair et al., 2014). Three significant path relationships were discovered (ST → JP, ß = 0.349, p < 0.01; SOA → JP, ß = 0.249, p < 0.01; RM → JP, ß = 0.209, p < 0.05) at 99% and 95 % confidence levels, however, one path relationship was found to be not significant (SA → JP, ß = 0.096, p > 0.05) at 95 % confidence level. Additionally, given the positive values of all the beta loadings, it is evident that three of the four hypotheses in the study were supported. Using the suggested threshold value of 3.3 as the criteria of variance inflation factor (VIF), the multicollinearity index among the variables computed in the model did not detect any issues (Hair et al., 2014).
As presented in Table 5, apart from the findings obtained for the hypothesis, the SmartPLS 3 software was also able to generate quality outputs for the coefficient of determination (R2), the cross-validated redundancy (Q2) including the effect size (f2), of all exogenous constructs on the endogenous constructs. The value for the coefficient of determination (R2) of 0.539 suggests that the exogenous variables in this study explain 53.9% of the variance in job performance which Cohen (1988) indicated as having substantial explanatory capacity.
Chin (1998) suggested that the aim of PLS–SEM is to predict, thus, the blindfolding procedure should be used to determine the predictive abilities of the exogenous variables. Referring to Fornell and Cha (1994), the Q2 value of 0.259 for job performance is larger than 0, signifying that all exogenous variables can predict the endogenous variable well. Additionally, the f2 effect size values exhibit the importance of each exogenous construct in predicting endogenous constructs. Cohen (1988) suggested that values close to 0.02 are determined as small, close to 0.15 as medium, and more than 0.35 as large. It is interesting to see that the effect size of self-regulation on job performance (f2 = 0.104) is the largest compared to that of self-awareness (f2 = 0.01), relationship management (f2 = 0.054), and social awareness (f2 = 0.085).
As suggested by the literature (Shmueli et al., 2016, 2019), in addition to the blindfolding procedure, it is also recommended to perform the PLS prediction approach. The model is acknowledged to have fewer errors in its predictive ability (Shmueli et al., 2016, 2019) if the RMSE, MAE, and MAPE values in the PLS model are lower than those in the Linear Model (LM), and the Q2 value for PLS is higher than LM. As presented in Table 6, almost all values fulfill the requirements except for JP8, hence this indicates that the predictive performance of the available indicator data has been improved through a theoretically established path model.
Discussion
From the results, it can be summed up that three out of four variables of EI had a significant and positive relation with job performance. However, the results revealed that self-awareness is not positively significant in influencing job performance, other variables such as self-regulation (SR), social awareness (SOA), and relationship management (RM) have shown a positive influence on job performance. The findings are consistent with those found in research done on public sector employees in Pakistan where employees who have strong EI outperformed those who possess low EI levels (Mahmood et al., 2015).
Similarly, this paper postulates that strong EI is capable of positively enhancing teachers’ performance. Teachers who are not able to control their emotions will find it challenging to execute their roles and responsibilities as educators. If teachers are unable to control their emotions, they are likely to exhibit unprofessional attitudes and behaviour when performing their jobs. When this happens, it will disrupt the student’s learning process and eventually will cause a bigger problem for the country in the future. The present study revealed that self-regulation (SR), social awareness (SOA) and relationship management (RM) are significant predictors of teachers’ job performance.
Self-regulation refers to the ability to respond and react in a long-term ethical dilemma that will help avoid any feelings of guilt, shame, and anxiety. Pekaar et al. (2018) argued that appraisal of one’s emotions may lead to emotional regulation. Emotion appraisal may attract one's attention to the felt emotion without altering its impact. Then, the emotion of an individual is regulated to alleviate mood and ameliorate social interaction. Thus, teachers must have strong self-regulation ability to effectively perform their duties since teachers have to interact not only with their students but also with their colleagues and superiors daily.
Social awareness (SOA) reflects the ability to recognize and interpret the scenarios, issues, and situations that are developing around them. This ability would enable individuals to put themselves in other people’s situations. In the context of teachers, SOA would enhance their performance because they need to interact with their students who have different social, cultural, and educational backgrounds. Even though this result contradicts the study by Krishnan et al. (2018), we argue that the teaching profession requires academicians to have high SOA because they need to interact face-to-face with their students. This argument is consistent with the model of the prosocial classroom as proposed by Jennings and Greenberg (2009) which emphasizes the value of teachers having social/emotional ability and well-being as the foundation of a healthy teacher/student relationship. This relationship will create a healthy classroom climate that will help create positive student social, emotional, and academic outcomes.
Relationship management is also known as the individual’s social skills ability. It can also be understood that those with excellent social skills would have the ability to manage their relationship with others. Individuals who have good social skills would also be able to react to other people based on their needs and preferences. This finding is supported by the work of Rahman and Taniya (2017) who argued that shared goals and objectives are translated into common beliefs in interpreting what behaviours, attitudes, procedures, and policies employees jointly desire. Thus, an effective management-teacher relationship will lead them to share common goals and values that will motivate them to direct their energies toward achieving higher productivity.
Conclusion
Teachers’ professions are challenging and stressful because they deal with various job demands and social responsibilities, including interacting with students. Therefore, teachers need to have a special ability that shields them from being vulnerable to clamorous situations. That ability is EI which refers to the ability to recognize and regulate his/her own emotions and those of others around them. The present study can provide empirical evidence that three out of four dimensions of EI are significant in influencing secondary school teachers’ job performance. Self-regulation, social awareness, and relationship management are required by school teachers to enable them to effectively execute their responsibilities without having to feel the negative outcomes of their heavy workloads. The finding can facilitate interpersonal interactions which can in turn lead to effective job outcomes. To sustain high performance and competitive advantage, EI should be developed and improved through a systematic and consistent approach. This study also opens an avenue for future researchers to investigate the appropriate emotional recognition and regulation strategies that can be used by schoolteachers to make them more effective in conducting teaching and learning activities for their students.
References
Alferaih, A. (2017). Conceptual model for measuring Saudi banking managers' job performance based on their emotional intelligence (EI). International Journal of Organizational Analysis, 25(1), 123-145. DOI:
Asghari Aghdam, B., & Mahjoub, A. (2013). The effect of emotional intelligence on performance and motivation of staff case study (East Azarbaijan the Red Crescent). International Journal of Management Academy, 1(2), 109-120.
Asrar-ul-Haq, M., Anwar, S., & Hassan, M. (2017). Impact of emotional intelligence on teacher performance in higher education institutions of Pakistan. Future Business Journal, 3(2), 87-97. DOI:
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94. DOI:
Bakker, A. B., & de Vries, J. D. (2021). Job Demands-Resources theory and self-regulation: New explanations and remedies for job burnout. Anxiety, Stress, & Coping, 34(1), 1-21. DOI:
Borman, W. C. (2011). Gold medal award for life achievement in the application of psychology: Walter C. Borman. American Psychologist, 66(5), 348–350. DOI:
Chan, C. M., Chang, S. M., Chong, Y. S., & Tang, C. U. (2015). The influence of job stress, burnout, and job satisfaction among primary school teachers in Ipoh [Doctoral dissertation, UTAR].
Chin, W. W. (1998). The partial least squares approach to structural equation modelling. Modern Methods for Business Research, 295(2), 295-336.
Cohen, J. (1988). Statistical power analysis for the behavioural sciences (2nd Ed.). Erlbaum Associates.
Fathi, J., Greenier, V., & Derakhshan, A. (2021). Self-efficacy, reflection, and burnout among Iranian EFL teachers: The mediating role of emotion regulation. Iranian Journal of Language Teaching Research, 9(2), 13-37.
Fornell, C., & Cha, J. (1994). Partial Least Squares. In Bagozzi RP (Ed.). Advanced methods of marketing research. Blackwell.
Gefen, D., Straub, D., & Boudreau, M. C. (2000). Structural equation modelling and regression: Guidelines for research practice. Communications of the Association for Information Systems, 4(1), 1–78. DOI:
Goleman, D. (2001). Emotional intelligence: Why it can matter more than IQ. Bantam Books.
Granziera, H., & Perera, H. N. (2019). Relations among teachers' self-efficacy beliefs, engagement, and work satisfaction: A social cognitive view. Contemporary Educational Psychology, 58, 75-84. DOI:
Gunu, U., & Oladepo, R. O. (2014). Impact of EI on employee performance organizational commitment: A case study of Dangote flour mills workers. University of Mauritius Research Journal, 20, 1-32.
Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2014). A primer on Partial Least Squares Structural Equation Modelling (PLS-SEM). Sage.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modelling. Journal of the Academy of Marketing Science, 43(1), 115-135. DOI:
Ishak, N. M., Iskandar, I. P., & Ramli, R. (2010). Emotional intelligence of Malaysian teachers: A comparative study on teachers in daily and residential schools. Procedia - Social and Behavioural Sciences, 9, 604-612. DOI:
Jennings, P. A., & Greenberg, M. T. (2009). The prosocial classroom: teacher social and emotional competence in relation to student and classroom outcomes. Review of Educational Research, 79(1), 491-525. DOI:
Kim, D. Y. (2010). The impacts of quality management practices on innovation [Doctoral dissertation, Carleton University].
Kock, N. (2015). Common Method Bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1-10. DOI: 10.4018/ijec.2015100101
Kock, N., & Gaskins, L. (2014). The mediating role of voice and accountability in the relationship between internet diffusion and government corruption in Latin America and Sub-Saharan Africa. Information Technology for Development, 20(1), 23-43. DOI:
Kock, N., & Lynn, G. S. (2012). Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations. Journal of the Association for Information Systems, 13(7), 546-580. DOI:
Koopmans, L., Bernaards, C. M., Hildebrandt, V. H., de Vet, H. C. W., & van der Beek, A. J. (2014). Measuring individual work performance: Identifying and selecting indicators. Work, 48(2), 229-238. DOI: 10.3233/wor-131659
Krishnan, R., Mahphoth, M. H., Ahmad, N. A. F. b., & A'yudin, N. A. (2018). The influence of emotional intelligence on employee job performance: A Malaysian case study. International Journal of Academic Research in Business and Social Sciences, 8(5). DOI:
Li, M., Pérez-Díaz, P. A., Mao, Y., & Petrides, K. V. (2018). A multilevel model of teachers' job performance: understanding the effects of trait emotional intelligence, job satisfaction, and organizational trust. Frontiers in Psychology, 9. DOI:
Mackenzie, S. B., Podsakoff, P. M., & Podsakoff, N. P. (2011). Construct measurement and validation procedures in MIS and behavioural research: Integrating new and existing techniques. Management Information System Quarterly, 35(2), 293-334.
Madani, S. T., & Asgari, M. (2014). The relationship between EI and job involvement (case study: The elementary school teachers of Tonekabon City). Journal of Applied Environmental and Biological Sciences, 29-35.
Mahmood, A., Arshad, M. A., Ahmed, A., Akhtar, S., & Rafique, Z. (2015). Establishing linkages between intelligence, emotional and spiritual quotient on employee’s performance in the government sector of Pakistan. Mediterranean Journal of Social Sciences, 6(6 S2), 553-553. DOI:
Maqbool, R., Sudong, Y., Manzoor, N., & Rashid, Y. (2017). The impact of emotional intelligence, project managers' competencies, and transformational leadership on project success: An empirical perspective. Project Management Journal, 48(3), 58-75. DOI:
Mohamad, M., & Jais, J. (2016). Emotional intelligence and job performance: A study among Malaysian teachers. Procedia Economics and Finance, 35, 674-682. DOI:
Naqvi, I. H., Iqbal, M., & Akhtar, S. N. (2016). The relationship between emotional intelligence and performance of secondary school teachers. Bulletin of Education and Research, 38(1), 209-224.
Pekaar, K. A., Bakker, A. B., van der Linden, D., & Born, M. P. (2018). Self- and other-focused emotional intelligence: Development and validation of the Rotterdam Emotional Intelligence Scale (REIS). Personality and Individual Differences, 120, 222-233. DOI:
Pekrun, R. (2021). Teachers need more than knowledge: Why motivation, emotion, and self-regulation are indispensable. Educational Psychologist, 56(4), 312-322. DOI: 10.1080/00461520.2021.1991356
Perera, M. (2021). The effect of EI on work outcomes in the construction industry [Doctoral dissertation, Auckland University of Technology].
Rahman, M. S., & Taniya, R. K. (2017). Effect of employee relationship management (ERM) on employee performance: A study on private commercial banks in Bangladesh. Human Resource Management Research, 7(2), 90-96.
Ramirez-Asis, E., Huaman-Osorio, A., Sáenz-Rodríguez, R., Guerra-Muñoz, M., Asnate-Salazar, E., & Alvarado-Tolentino, J. (2021). The effect of emotional intelligence on job satisfaction and organizational commitment: The case of educational sector. NVEO-NATURAL VOLATILES & ESSENTIAL OILS Journal| NVEO, 95-115.
Rexhepi, G., & Berisha, B. (2017). The effects of emotional intelligence in employee performance. International Journal of Business and Globalisation, 18(4), 467. DOI: 10.1504/ijbg.2017.084351
Ringle, C. M., Wende, S., & Becker, J. M. (2015). SmartPLS 3. SmartPLS.
Saleem, A., Aslam, S., Yin, H.-b., & Rao, C. (2020). Principal leadership styles and teacher job performance: Viewpoint of middle management. Sustainability, 12(8), 3390. DOI:
Salovey, P., & Mayer, J. D. (1990). Emotional intelligence. Imagination, Cognition and Personality, 9(3), 185-211. DOI:
Schutte, N. S., Malouff, J. M., Thorsteinsson, E. B., Bhullar, N., & Rooke, S. E. (2007). A meta-analytic investigation of the relationship between emotional intelligence and health. Personality and Individual Differences, 42(6), 921-933. DOI:
Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach. John Wiley & Sons.
Shafiq, M., & Rana, R. A. (2016). Relationship of emotional intelligence to organisational commitment of college teachers in Pakistan. Eurasian Journal of Educational Research, 16(62), 1-14. DOI:
Shmueli, G., Ray, S., Velasquez Estrada, J. M., & Chatla, S. B. (2016). The elephant in the room: Predictive performance of PLS models. Journal of Business Research, 69(10), 4552-4564. DOI:
Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J.-H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322-2347. DOI:
Steinbauer, R., Renn, R. W., Chen, H. S., & Rhew, N. (2018). Workplace ostracism, self-regulation, and job performance: Moderating role of intrinsic work motivation. The Journal of Social Psychology, 158(6), 767-783. DOI:
Stosny, S. (2011). Self-regulation. Psychology Today. https://www.psychologytoday.com/blog/anger-in-the-ageentitlement/201110/self-regulation
The Star. (2016, August 02). Teacher attempts suicide after criticism. https://www.thestar.com.my/news/nation/2016/08/02/teacher-attempts-suicide-after-criticism
Wolff, S. B. (2005). Emotional Competence Inventory (ECI)-Technical Manual. Hay Acquisition Company: McClelland Centre for Research and Innovation. http://www.eiconsortium.org/pdf/ECI_2_0_Technical_Manual_v2.pdf
Yan, X., Yang, K., Su, J., Luo, Z., & Wen, Z. (2018). Mediating role of emotional intelligence on the associations between core self-evaluations and job satisfaction, work engagement as indices of work-related well-being. Current Psychology, 37(3), 552-558. DOI:
Yoke, L. B., & Panatik, S. A. (2016). School teachers' EI in relation to demographic characteristics and job outcomes. International Business Management 10(6), 858 - 864.
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06 May 2024
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Zakaria, Z., Majid, M. N., Othman, A. K., Ariffin, N. F., & Zahari, A. S. M. (2024). Predicting School Teachers’ Job Performance Through Emotional Intelligence Model. In A. K. Othman, M. K. B. A. Rahman, S. Noranee, N. A. R. Demong, & A. Mat (Eds.), Industry-Academia Linkages for Business Sustainability, vol 133. European Proceedings of Social and Behavioural Sciences (pp. 528-541). European Publisher. https://doi.org/10.15405/epsbs.2024.05.44