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The Effect of Motivation, Emotional and Spiritual Intelligence on Lecturer Performance

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Empirical study

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International Journal of Management Science and Business Administration
Volume 6, Issue 4, May 2020, Pages 42-54


The Effect of Motivation, Emotional and Spiritual Intelligence on Lecturer Performance

DOI: 10.18775/ijmsba.1849-5664-5419.2014.64.1004
URL: http://dx.doi.org/10.18775/ijmsba.1849-5664-5419.2014.64.1004

1 Rosemarie S. Njotoprajitno, 2 Rully Arlan Tjahjadi, 3 Nur,
4 Bram Hadianto, 5 Andre Sunjaya

1 2 3 4 5 Management Department of Economics Faculty, Maranatha Christian University, Indonesia

Abstract: Lecturers are individuals employed by the higher educational institutions to educate students based on their competency. The roles of lecturers are not limited to the education of students only but also include the activities related to the research and the service community. These three aspects are considered to be measures of lecturers’ performance. Consequently, the institutions must focus on the factors behind the performance of their lecturers to increase performance. By denoting the evidence of the previous study, the three determinants of performance are identified, namely, motivation, emotional and spiritual intelligence. Therefore, this study attempts to examine and analyze these determinants in the context of private university lecturers becoming active members of the Indonesia Management Forum. To collect the data, we utilize a simple random sampling and survey method. Also, we use a variance-based structural equation as the model to analyze the attained data. Overall, this study concludes that there is a positive effect of emotional intelligence on the performance of lecturers. On the other hand, the effect of motivation and spiritual intelligence is not confirmed.

Keywords: Emotional Intelligence, Lecturer Performance, Higher Education Institution, Spiritual Intelligence

The Effect of Motivation, Emotional and Spiritual Intelligence on Lecturer Performance

1. Introduction

Human resources are considered to be the main organizational assets (Gabčanová, 2011). Therefore, maintaining their commitment is mandatory for achieving excellent performance (Rishipal and Manish, 2013) and ensuring organizational success (Vosloban, 2012). Similarly, such situations can be applied to lecturers in higher educational institutions. The lecturers and their achievement will determine the quality of these institutions, (Zahraini, 2014). In Indonesia, lecturers’ performance is measured by the three components, i.e., education and teaching; research, and community service (Muttaqiyathun, 2010; Pramudyo, 2010; Taruno, Thoyib, Zain, and Rahayu, 2012), and the Board of National Accreditation for Higher Education is authorized to perform the valuation for outcomes based on these three aspects.

To ensure their lecturers achieve excellent performance, the higher education institutions have to identify antecedents leading to superior performance. These include motivation (Muttaqiyathun, 2010; Pramudyo, 2010; Nur’aeni, 2011; Trisnaningsih, 2011; Taruno, Thoyib, Zain, and Rahayu, 2012; Faitullah, 2014; Anwar, 2017; Rina and Kusuma, 2017; Narasuci, Setiawan, and Noermijati, 2018), emotional (Muttaqiyathun, 2010; Faitullah, 2014), and spiritual intelligence (Muttaqiyathun, 2010; Anwar, 2017). Unlike the studies involving lecturers, some research finds that intrinsic motivation has no impact on employee performance in state-owned firms (Muogbo, 2013). Others suggest emotional intelligence decreases the enactment of the officers in educational and cultural departments (Bestyasamala, 2018), while it has previously been established that spiritual intelligence does not affect the performance of nurses (Haryono, Rosadi, and MdSaad, 2018). Based on two conflicting results, this study intends to test and analyze the effect of motivation and emotional and spiritual intelligence on the performance of lecturers.

2. Literature Review and Hypothesis Development

Motivation is the power to encourage employees to achieve outstanding results. Highly motivated employees can cooperate, assist, support, and inspire each other (Gibson, Ivancevich, Donnelly, & Konopaske, 2012). According to Muttaqiyatun (2010), motivation has a positive effect on lecturer performance. The result was supported by a number of studies, such as Pramudyo (2010), Nuraeni (2011), Trisaningsih (2011), Taruno et al. (2012), Faitullah (2014), Anwar (2017), Rina & Kusuma (2017), Narasuci et al. (2018). Therefore, the first hypothesis is declared as follows:

H1: Motivation has a positive effect on lecturer performance.

Emotional intelligence is comprised of emotional and social capabilities in all aspects of individual life (Tridhonanto & Agency, 2010). Someone who possesses and utilizes it on a daily basis will easily attain top performance (Agustian, 2007). According to Muttaqiyathun (2010) and Faitullah (2014), emotional intelligence positively influences lecturers’ performance. Anwar’s (2017) and Makkasau’s (2018) results confirm this conclusion. Therefore, the second hypothesis is declared as follows.

H2: Emotional intelligence will have a positive effect on lecturer performance.

Spiritual intelligence concentrates on the personality and is often associated with wisdom (Zohar & Marshall, 2007). This intelligence leads to revealing the truth, which then benefits the soul. People possessing this intelligence will make the better performance it and improve the quality of their life (Imawan, 2004). This type of intelligence contributes to performance in the face of substantial working strains because it brings about joyfulness and rationality (Noermijati, 2013). Muttaqiyathun (2010) and Makkasau (2018) support this explanation by affirming that the effect of spiritual intelligence on performance is positive. Therefore, the third hypothesis is declared as follows.

H3: Spiritual intelligence will have a positive effect on lecturer performance.

3. Methodology

3.1 Population and Samples

The private university lecturers who have become active members of Indonesia’s Management Forum before 2019 are study population. According to the information from the forum secretariat, the number of members is around 500. To get the total samples (n) that represent the total population (N), we used the Slovin formula cited in Suliyanto (2009), presented in equation 1 with the border of error (e) of 5%.

                   (1)

By this formula, the total samples calculated are To select 222 lecturers, furthermore, we utilize the simple random sampling method.

3.2 Data Collection Method

This research uses the primary data of respondents of the online survey carried out from March to April 2019. Unfortunately, not all respondents provided a full response. Only 100 lecturers filled the questionnaire completely. Therefore, the response rate is 100/222 x 100% = 45.05%. This rate is higher than 20%, which is the required response set by Sugiyanto et al. (2018). It means this level is still acceptable.

3.3 Determining Research Variables

The first variable is motivation, which has been measured with a scale adopted from Perwita et al. (2016) consisting of five items of intrinsic motivation (M1-M5) and extrinsic motivation (M6-M10) (see Table 1).

Table 1:  Indicators of motivation

The type of motivation Indicator
Intrinsic motivation M1: Working as a lecturer is interesting to me.

M2: Working as a lecturer provides me with an opportunity to improve.

M3: Working as a lecturer can improve my reputation.

M4: Working as a lecturer encourages me to acquire some achievements.

M5: Working as a lecturer stimulates me to fulfil my duties.

Extrinsic motivation M6: My decision to be a lecturer is due to interpersonal relationships with other parties.

M7: My decision to be a lecturer is due to conducive working conditions.

M8: My decision to be a lecturer is due to quality supervision.

M9: My decision to be a lecturer is due to a clear procedure for compensation.

M10: My decision to be a lecturer is for adequate financial compensation.

Source: Adopted from Perwita et al. (2017)

The second variable is emotional intelligence, where its measurements are denoting the study of Tjun, Setiawan, and Setiana (2017) consisting of five dimensions, namely, self-awareness (SA), self-control (SC), motivation (MOT), empathy (E), and social skills (SCL). Moreover, each indicator of these dimensions is in Table 2.

Table 2: Indicators of the dimensions of emotional intelligence

Dimension Indicator
Self-awareness SA1: I like myself.

SA2: I know my strength.

SA3: I exist for a reason.

A4: I am angry with reason.

SA5: I never doubt my ability.

SA6: I can do something.

SA7: I am not worried about my future.

SA8: I dare to be different from my friends.

SA9: I can get what I want.

SA10: I will finish the job, although I do not like its responsibility.

Self- control SC1: I am patient with other people.

SC2: I easily recover quickly after feeling disappointed.

SC3: I think of what I want before acting.

SC4: I remain calm in situations making other people angry.

SC5: I can control my life.

SC6: I am calmer than others.

SC7: I am not quickly bored and tired of doing things.

SC8: Tight competition does not reduce my enthusiasm.

SC9: To achieve another larger goal, I can delay the satisfaction of my momentary pleasure.

SC10: I immediately finish the work I plan without wasting time.

Motivation MOT1: I know the purpose of my life.

MOT2: I like trying new things.

MOT3: I always try the same job again until I am successful.

MOT4: I join various information and ideas.

MOT5: I am happy to face challenges to solve problems.

MOT6: If I encounter obstacles to reach a goal, I will turn to another one.

MOT7: I do not easily surrender when doing difficult tasks.

MOT8. The hope of success influences me more than the fear of failure.

MOT9: I am interested in work requiring me to give new ideas.

MOT10: I often introspect to rediscover the important one in my life.

Empathy (E) E1: I own a lot of close friends from various backgrounds.

E2: I can usually find out how other people feel about me.

E3: I feel that my friend does not drop me.

E4: I easily understand others’ point.

E5: I am confident when talking to people I don’t know.

E6: I can make people I don’t know talk about themselves.

E7: I can convey something that attracts other people’s attention during the meeting.

E8: I can feel that people are hurt, although they do not tell it.

E9: I am a source of advice for my friends with problems.

E10: I can put myself in someone else’s position

Social skills (SS)

 

 

 

 

 

SS1: I can accept critiques with an open mind as long as they can be justified.

SS2: I easily come up with the topic of conversation with others.

SS3: I easily become friends with people.

SS4: Ethics guides me when I deal with others.

SS5: My problems do not affect my relationships with others.

SS6: I can feel the mood of a group.

SS7: I joy and do not talk too much when I am among people.

Source: Adopted from Tjun, Setiawan, and Setiana (2009)

The third variable is spiritual intelligence, with indicators adopted from King (2008) as well as Anwar & Osman-Gani (2015). It covers 24 question items distributed into four dimensions: critical existential thinking (7 items), personal meaning production (5 items), transcendental awareness (7 items), conscious state expansion (5 items).

Table 3: Indicators of the dimensions of spiritual intelligence

Dimension Indicator
Critical existential thinking CET1: I often ask the question and reflect on the characteristics of reality.

CET2: I use the time to reflect on the reason for my existence.

CET3: I can deeply reflect on something that happened after death.

CET4: I have developed my theory about things like life, death, reality, and existence.

CET5: I often reflect on the meaning of events in my life.

CET6: I often contemplate the relationship between humans and the whole universe

CET7: I think about unlimited power.

Personal meaning production PMP1: I can find meaning and purpose in life so that it helps me adapt to stressful situations.

PMP2: I can define goals or reasons for my life.

PMP3: When I failed, I was still able to find meaning in my failure.

PMP4: I can make decisions according to the purpose of my life.

PMP5: I can find meaning and purpose in my daily experience.

Transcendental awareness TA1: I recognize aspects of myself better than my physique.

TA2: I easily feel beyond tangible items.

TA3: I realize a deeper relationship between me and others exists.

TA4: I define myself deeper than my physique.

TA5: I have a high awareness of non-physical aspects of life.

TA6: I recognize the quality of people more meaningful than their body, personality, or emotion.

TA7: Recognizing aspects of non-physical life helps me concentrate.

Conscious state expansion CSE1: I can achieve a high level of consciousness.

CSE2: I can control myself when entering a higher level of consciousness.

CSE3: I can freely move between levels of consciousness

CSE4: I often see problems and choices clearly when a high awareness exists.

CSE5: I can develop techniques to enter higher awareness.

Source: Adopted from Anwar & Osman-Gani (2015)

The fourth variable is the lecturer’s performance. We define it as the success of the lecturer to perform the activities related to research, community service, and teaching. Furthermore, three aspects become the dimension of the performance. The indicators used in this study for each dimension refer to the relevant content of the accreditation instrument version 4 for the study program. For the research performance dimension, the indicators are as follows.

  1. I can publish my research results in reputable international and national journals (RP1)
  2. I can publish my research results in the proceeding of international and national conferences or seminars (RP2).
  3. I can publish my research results in international and national media that can be accessed by the public (RP3).
  4. I can get external funds from abroad or domestic to finance the research (RP4).
  5. I can obtain an intellectual property right based on the results of my research (RP5).
  6. I can produce books with ISBN based on the results of my research (RP6).

For the community service performance dimension, the indicators are as follows.

  1. I can publish the activity related to the service for the community in the related journals and proceedings (CSP1)
  2. I can obtain an intellectual property right based on the activities of the service for the community (CSP2).
  3. I can obtain an intellectual property right based on the activities of the service for the community (CSP3).
  4. I can produce books with ISBN based on the results of the service community (CSP4).

For the teaching performance dimension, the indicators are as follows.

  1. I can mix the results of my research into the learning materials for the students (TP1).
  2. I can mix the results of my service community into the learning materials for the students (TP2).

3.4 Validity and Reliability Test

Although the instruments are already designed based on existing literature, testing the data validity and reliability is still vital. The validity and reliability test intends to prove the accuracy and consistency of respondents’ answers, respectively.

  • This research uses confirmatory factor analysis (CFA) as the validity test, by comparing the loading factor value of each indicator with the 0.5. If its value exceeds 0.5, the answer of respondents is valid. If it has a value below 0.5, it should be removed (Sholihin & Ratmono, 2013).
  • This research utilizes the Cronbach Alpha (CA) analysis as the reliability test after all respondents’ answers of indicators are valid. This analysis is conducted by comparing the CA value with 0.7. A collection of convincing indicators is reliable if the CA is higher than 0.7(Ghozali, 2016).

3.5 Data Analysis Method

Examining the effect of motivation (M), emotional intelligence (EI), and spiritual intelligence (SI) on lecturer performance (LP) requires for a method variance-based structural equation model to analyze data. This is because these variables are not directly observed, and the number of respondents is between 30 and 100 (Ghozali, 2014). Additionally, this model is exhibited in equation two.

LP = β0 + γ1.M + γ2.EI + γ3. SI + ζ                                                               (2)

4. Result and Discussion

4.1 The Statistics of the Demographic Characteristics

The statistic used is the frequency to capture the total lecturers categorized by gender, functional position, the study field, working duration, work status, academic degree. Table 4 presents the number of lecturers by gender. Of the 100, 66 females (66%) and 34 males (34%) participate in this survey.

Table 4: The Total Lecturers categorized by gender

Gender The number of lecturers Percentage
Male 34 34%
Female 66 66%
Total 100 100%

Source: Processed Survey Data

Table 5 exhibits the number of lecturers joining this survey, categorized by their functional position. The number of the expert assistants is 25 (25%),  the senior lecturer is  45%, the associate professors are 27 (27%), and there are 3 professors (3%).

Table 5: The Total Lecturers categorized by Functional Position

Functional Position The number of lecturers Percentage
Expert Assistant 25 25%
Senior Lecturer 45 45%
Associate Professor 27 27%
Professors 3 3%
Total 100 100%

Source: Processed Survey Data

Table 6 illustrates the number of lecturers categorized by the field of their study. This table informs that the number of lecturers from the management field is 88, from the accounting field is 2, from the business administration field and industrial engineering field is 2. There is one lecturer from Islamic economics and finance field, the economics of development field, and information system field, respectively.

Table 6: The total number of lecturers  categorized by  the field of study

The Field of Study The number of lecturers Percentage
Business administration 2 2%
Accounting 5 5%
Islamic economics and finance 1 1%
Economics of development 1 1%
Management 88 88%
Information system 1 1%
Industrial engineering 2 2%
Total 100 100%

Source: Processed Survey Data

Table 7 displays the number of lecturers by their tenure. This table shows that the number of lecturers having a tenure less than 10 years is 19, between 10 and 20 is 44, between 21 and 30 is 30, over 30 is 7.

Table 7: The number of lecturers categorized by the working duration

Working duration The number of lecturers Percentage
< 10 Year 19 19%
10 – 20 Years 44 44%
21 -30 Years 30 30%
>30 Years 7 7%
Total 100 100%

Source: Processed Survey Data

Table 8 shows the number of lecturers categorized by their status. This table shows that the number of lecturers without and with the additional managerial assignment is 53 and 47, respectively.

Table 8: The number of lecturers categorized by the work status

Status of work The number of lecturers Percentage
Lecturer without the additional managerial assignment 53 53%
Lecturer with additional managerial assignments 47 47%
Total 100 100%

Source: Processed Survey Data

Table 9 displays the number of lecturers categorized by academic degrees of master of 54 and doctor of 46, respectively.

Table 9:  The number of lecturers categorized by the academic degree

Academic Degree The number of respondents Percentage
Master 54 54%
Doctor 46 46%
Total 100 100%

Source: Processed Survey Data

4.2 The Output of Validity and Reliability Test and Interpretation

This study uses confirmatory factor analysis  (CFA) to test the data validity. For motivation, the first result is illustrated in Table 10A. As seen in this table, M6 is the invalid indicator because the loading factor value is 0.298, lower than 0.5. Hence, removing M6 is essential.

Table 10A: The beginning CFA result: The Loading Factor Values of Motivation Indicators

Indicator Loading

factor

Interpretation Indicator Loading

factor

Interpretation
M1 0.613 Valid M6 0.298 Invalid
M2 0.729 Valid M7 0.672 Valid
M3 0.581 Valid M8 0.665 Valid
M4 0.740 Valid M9 0.645 Valid
M5 0.664 Valid M10 0.749 Valid

Source: Modified Warp PLS Output

After removing M6, CFA was conducted again, and the result is in Table 10B. As seen in this table, all the indicators are valid because all the loading factors are above 0.5.

Table 10B: The final CFA Result: The Loading Factor Values of Motivation Indicators

Indicator Loading

factor

Interpretation Indicator Loading

factor

Interpretation
M1 0.629 Valid M7 0.659 Valid
M2 0.739 Valid M8 0.648 Valid
M3 0.588 Valid M9 0.649 Valid
M4 0.748 Valid M10 0.734 Valid
M5 0.678 Valid

Source: Modified Warp PLS Output

For self-awareness as the first dimension of emotional intelligence, SA3, SA4, SA7, and SA10 are the invalid indicators because their loading factor values are 0.257, 0.268, 0.476, 0.426, respectively, lower than 0.5 (see Panel A of Table 11A). For motivation as the second dimension of motivation, MOT1 and MOT6 are invalid because their loading factors are 0.319 and 0.064, respectively, lower than 0.5 (see Panel B of Table 11A). For empathy and social skill as the third and fourth dimensions, all the indicators are valid because these loading factor values are higher than 0.5 (see Panel C and D of Table 11A).

Table 11A: The beginning result of CFA: The Loading Factor Values of Self-Awareness, Self-Control, Motivation, Empathy, and Social Skill Indicators

Panel A. Dimension of self-awareness
Indicator Loading factor Interpretation Indicator Loading factor Interpretation
SA1 0.589 Valid SA6 0.776 Valid
SA2 0.660 Valid SA7 0.476 Invalid
SA3 0.257 Invalid SA8 0.730 Valid
SA4 0.268 Invalid SA9 0.766 Valid
SA5 0.730 Valid SA10 0.426 Invalid
Panel B. Dimension of self-control
Indicator Loading factor Interpretation Indicator Loading factor Interpretation
SC1 0.787 Valid SC6 0.865 Valid
SC2 0.624 Valid SC7 0.629 Valid
SC3 0.708 Valid SC8 0.761 Valid
SC4 0.817 Valid SC9 0.805 Valid
SC5 0.793 Valid SC10 0.683 Valid
Panel C. Dimension of motivation
Indicator Loading factor Interpretation Indicator Loading factor Interpretation
MOT1 0.319 Invalid MOT6 0.064 Invalid
MOT2 0.660 Valid MOT7 0.740 Valid
MOT3 0.774 Valid MOT8 0.560 Valid
MOT4 0.670 Valid MOT9 0.830 Valid
MOT5 0.831 Valid MOT10 0.677 Valid
Panel D. The Dimension of Empathy
Indicator Loading factor Interpretation Indicator Loading factor Interpretation
E1 0.583 Valid E6 0.739 Valid
E2 0.622 Valid E7 0.678 Valid
E3 0.645 Valid E8 0.688 Valid
E4 0.763 Valid E9 0.789 Valid
E5 0.680 Valid E10 0.757 Valid
Panel E. The Dimension of Social Skill
Indicator Loading factor Interpretation Indicator Loading factor Interpretation
SS1 0.777 Valid SS5 0.817 Valid
SS2 0.758 Valid SS6 0.615 Valid
SS3 0.585 Valid SS7 0.584 Valid
SS4 0.864 Valid

Source: Modified Warp PLS Output

After eliminating the invalid indicators of SA3, SA4, SA7, SA10, MOT1, and MOT6, the CFA is conducted again, and the result is shown in Table 11B. As illustrated by this table, all the indicators of each dimension of emotional intelligence are valid since these loading factor values are higher than 0.5.

Table 11B: The final result of CFA: The Loading Factor Values of Self-Awareness and Motivation

Panel A. Dimension of self-awareness
Indicator Loading factor Interpretation Indicator Loading factor Interpretation
SA1 0.635 Valid SA6 0.788 Valid
SA2 0.730 Valid SA8 0.726 Valid
SA5 0.762 Valid SA9 0.741 Valid
Panel B. Dimension of motivation
Indicator Loading factor Interpretation Indicator Loading factor Interpretation
MOT2 0.668 Valid MOT7 0.741 Valid
MOT3 0.776 Valid MOT8 0.553 Valid
MOT4 0.687 Valid MOT9 0.824 Valid
MOT5 0.844 Valid MOT10 0.662 Valid

Source: Modified Warp PLS Output

Once the indicators are valid, determining the validity status of each dimension, reflecting emotional intelligence is required. The result is listed in Table 11C. Dimensions are valid because their loading factor is higher than 0.5.

Table 11C:.The final result of CFA: The Loading Factor Value of The Emotional Intelligence Dimensions

Dimension Loading Factor Interpretation
Self-awareness 0.735 Valid
Self-control 0.875 Valid
Motivation 0.883 Valid
Empathy 0.824 Valid
Social skill 0.870 Valid

Source: Modified Warp PLS Output

Table 12A shows the loading factor values of the indicators of the dimensions of spiritual intelligence. Because these values are higher than 0.5, the validity test on these indicators is achieved.

Table 12A: The CFA result: The Loading Factor Indicators Values of Dimensions of Spiritual Intelligence

Panel A. Dimension of Critical Existential Thinking Panel C. Dimension of transcendental awareness
Indicator Loading factor Interpretation Indicator Loading factor Interpretation
CET1 0.859 Valid TA1 0.765 Valid
CET2 0.881 Valid TA2 0.747 Valid
CET3 0.868 Valid TA3 0.844 Valid
CET4 0.650 Valid TA4 0.856 Valid
CET5 0.853 Valid TA5 0.887 Valid
CET6 0.932 Valid TA6 0.825 Valid
CET7 0.813 Valid TA7 0.869 Valid
Panel B. Dimension of personal meaning production Panel D. Dimension of conscious state expansion
Indicator Loading factor Interpretation Indicator Loading factor Interpretation
PMP1 0.826 Valid CSE1 0.822 Valid
PMP2 0.905 Valid CSE2 0.918 Valid
PMP3 0.896 Valid CSE3 0.946 Valid
PMP4 0.865 Valid CSE4 0.909 Valid
PMP5 0.887 Valid CSE5 0.927 Valid

Source: Modified Warp PLS Output

After determining the validity of all indicators, deciding the validity status of each dimension, reflecting spiritual intelligence is essential. Results are illustrated in Table 12B. In this table, the loading factor value exceeds 0.5. Therefore, the five dimensions reflecting spiritual intelligence are valid.

Table 12B: Loading Factor Value of Dimensions of Spiritual Intelligence

Dimension Loading Factor Interpretation
Critical existential thinking 0.814 Valid
Personal meaning production 0.761 Valid
Transcendental awareness 0.855 Valid
Conscious state expansion 0.815 Valid

Source: Modified Warp PLS Output

Table 13A shows the loading factor values of the dimensions of lecturer performance. Since these values are higher than 0.5, the validity test on these dimensions gets achieved.

Table 13A: The CFA result: The Loading Factor Indicator Values of Dimensions of Lecturer Performance

Panel A. Dimension of research performance
Indicator Loading factor Interpretation
RP1 0.612 Valid
RP2 0.596 Valid
RP3 0.638 Valid
RP4 0.728 Valid
RP5 0.751 Valid
RP6 0.731 Valid
Panel B. Dimension of community service performance
Indicator Loading factor Interpretation
CSP1 0.830 Valid
CSP2 0.841 Valid
CSP3 0.863 Valid
CSP4 0.854 Valid
Panel C. Dimension of teaching performance
Indicator Loading factor Interpretation
TP1 0.947 Valid
TP2 0.947 Valid

Source: Modified Warp PLS Output

Once all the indicators are valid, determining the validity status of each dimension, reflecting lecturer performance is vital. Results are shown in Table 13B. Because these values are higher than 0.5, the validity test on these dimensions gets achieved.

Table 13B: Loading Factor Value of Dimensions of Lecturer Performance

Dimension Loading Factor Interpretation
Research Performance 0.895 Valid
Community Service Performance 0.853 Valid
Teaching Performance 0.675 Valid

Source: Modified Warp PLS Output

This study uses the Cronbach Alpha (CA) analysis to determine the reliability of the valid indicators for motivation and dimension of emotional and spiritual intelligence, as well as lecturer performance. The result is in Table 14. Because all coefficients of CA are higher than 0.7, the reliability test stand reached.

Table 14: Cronbach Alpha’s Coefficient of The Valid Indicators

Latent Variable/

Dimension

Measurement Status Total valid Indicators The name of valid indicators Cronbach

Alpha

Motivation Latent variable 9 M1, M2, M3, M4, M5, M7, M8, M9, M10 0.851
Emotional intelligence (EI)/self-awareness Dimension 6 SA1, SA2, SA5, SA6, SA8, SA9 0.825
EI/self- control Dimension 10 SC1, SC, SC3, SC4, SC5, SC6, SC7, SC8, SC9, SC10 0.912
EI/motivation Dimension 8 MOT2, MOT3, MOT4, MOT5, MOT7, MOT8, MOT9, MOT10 0.867
EI/ empathy Dimension 10 E1, E2, E3, E4, E5, E6,

E7, E8, E9, E10

0.881
EI/social skill Dimension 7 SS1, SS2, SS3, SS4, SS5, SS6, SS7 0.841
Spiritual intelligence (SI)/ critical existential thinking Dimension 7 CET1, CET2, CET3, CET4, CET5, CET6, CET7 0.929
SI/personal meaning production Dimension 5 PMP1, PMP2, PMP3, PMP4, PMP5 0.924
SI/ transcendental awareness Dimension 7 TA1,  TA2, TA3, TA4, TA5, TA6, TA7 0.923
SI/ conscious state expansion Dimension 5 CSE1, CSE2, CSE3, CSE4, CSE5 0.944
Lecturer Performance (LP)/ Research Performance Dimension 6 RP1, RP2, RP3, RP4, RP5, RP6 0.764
LP/ Community Service Performance Dimension 4 CSP1, CSP2, CSP3, CSP4 0.869
LP/ Teaching Performance Dimension 2 TP1, TP2 0.885

Source: Modified Warp PLS Output

4.3 The Estimation Result of Structural Equation Model

After testing the validity and reliability of the data, estimating the variance-based structural equation model (SEM) is the subsequent step, and the result is in Table 15.

Table 15: The Estimation Result of Variance-based SEM for The Effect of Motivation, Emotional and Spiritual Intelligence on Lecturer Performance

The determinant of lecturer performance Path Coefficient Standard error t-statistic Probability Value
Motivation 0.140 0.140 1.000 0.160
Emotional Intelligence 0.361 0.141 2.560 0.006
Spiritual Intelligence 0.160 0.137 1.168 0.122

Source: Modified Warp PLS Output

4.4 The Test Result of the Hypotheses

The first research hypothesis states that motivation has a positive effect on lecturer performance; it becomes the first alternative hypothesis. Moreover, we test the null hypothesis by comparing the probability value of t-statistic for motivation with a significance level (α) of 5%. In Table 15, this value is 0.160. Since this value is higher than α, the null hypothesis stating motivation does not affect the lecturer’s performance is accepted.

The second research hypothesis states that emotional intelligence has a positive effect on lecturer performance; it becomes the second alternative hypothesis. Moreover, we tested the null hypothesis by comparing the probability value ​​of t-statistic for emotional intelligence with a significance level (α) of 5%. In Table 15, this value is 0.006. Since this value is lower than α, the null hypothesis is rejected. Instead, the alternative hypothesis is accepted.

The third research hypothesis states that spiritual intelligence has a positive effect on lecturer performance. Moreover, we test the null hypothesis by comparing the probability value ​​of t-statistic for spiritual intelligence with a significance level (α) of 5%. In Table 15, the probability value is 0.122. Since this value is higher than α, the null hypothesis, declaring spiritual intelligence does not affect the lecturer’s performance, is recognized.

4.5 Discussion

In this research, motivation does not have a positive effect on lecturer performance. Even when lecturers are well encouraged, this does not impact on their performance. According to Robescu & Iancu (2016), this is due to the difficulty of tasks have to accomplish. In the context of this study, the responsibilities of lecturers encompass publishing their articles in a reputable international journal and resulting in useful outcomes based on their research.

Moreover, this research displays that emotional intelligence has a positive effect on the lecturers’ performance. This intelligence enables lecturers to collaborate when they teach a team of students and design the contents of subjects for improving the curriculum, execute the research and service community activity and publish their results in the related average journal to get the various forms of intellectual property rights. Therefore, this research confirms the study of Muttaqiyathun (2010), Faitullah (2014), Anwar (2017), and Makkasau (2018).

Furthermore, this research shows that spiritual intelligence does not affect lecturer performance. This means that spiritual intelligence cannot contribute to working performance. Therefore, this research affirms the study result of Haryono et al. (2018).

5. Conclusion

The goal of this research is to examine and analyze the impact of motivation, emotional, and spiritual intelligence on lecturer performance by SEM based on variance.  Based on the executed analysis, this study implies two things.

  1. Motivation and spiritual intelligence do not affect lecturer performance.
  2. Emotional intelligence has a positive effect on lecturer

Evidence has both practical and theoretical suggestions.

  • As a practical implication, achieving an excellent performance requires the training of emotional intelligence. Therefore, higher education institutions can facilitate this training for their lecturers to increase the ability to control their emotions and to cooperate in the teamwork.
  • As a theoretical implication, the next researchers can do two things. Firstly, employing the other determinants of lecturer performance like intellectual intelligence, compensation, work environment, leadership, organizational citizenship behaviour, and stress. Secondly, treating spiritual intelligence as a moderating variable of the causal relationship between stress and performance.

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