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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 motivationIndicator
Intrinsic motivationM1: 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 motivationM6: 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

DimensionIndicator
Self-awarenessSA1: 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- controlSC1: 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.

MotivationMOT1: 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

DimensionIndicator
Critical existential thinkingCET1: 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 productionPMP1: 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 awarenessTA1: 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 expansionCSE1: 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

GenderThe number of lecturersPercentage
Male3434%
Female6666%
Total100100%

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 PositionThe number of lecturersPercentage
Expert Assistant2525%
Senior Lecturer4545%
Associate Professor2727%
Professors33%
Total100100%

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 StudyThe number of lecturersPercentage
Business administration22%
Accounting55%
Islamic economics and finance11%
Economics of development11%
Management8888%
Information system11%
Industrial engineering22%
Total100100%

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 durationThe number of lecturersPercentage
< 10 Year1919%
10 – 20 Years4444%
21 -30 Years3030%
>30 Years77%
Total100100%

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 workThe number of lecturersPercentage
Lecturer without the additional managerial assignment5353%
Lecturer with additional managerial assignments4747%
Total100100%

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 DegreeThe number of respondentsPercentage
Master5454%
Doctor4646%
Total100100%

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

IndicatorLoading

factor

InterpretationIndicatorLoading

factor

Interpretation
M10.613ValidM60.298Invalid
M20.729ValidM70.672Valid
M30.581ValidM80.665Valid
M40.740ValidM90.645Valid
M50.664ValidM100.749Valid

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

IndicatorLoading

factor

InterpretationIndicatorLoading

factor

Interpretation
M10.629ValidM70.659Valid
M20.739ValidM80.648Valid
M30.588ValidM90.649Valid
M40.748ValidM100.734Valid
M50.678Valid

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
IndicatorLoading factorInterpretationIndicatorLoading factorInterpretation
SA10.589ValidSA60.776Valid
SA20.660ValidSA70.476Invalid
SA30.257InvalidSA80.730Valid
SA40.268InvalidSA90.766Valid
SA50.730ValidSA100.426Invalid
Panel B. Dimension of self-control
IndicatorLoading factorInterpretationIndicatorLoading factorInterpretation
SC10.787ValidSC60.865Valid
SC20.624ValidSC70.629Valid
SC30.708ValidSC80.761Valid
SC40.817ValidSC90.805Valid
SC50.793ValidSC100.683Valid
Panel C. Dimension of motivation
IndicatorLoading factorInterpretationIndicatorLoading factorInterpretation
MOT10.319InvalidMOT60.064Invalid
MOT20.660ValidMOT70.740Valid
MOT30.774ValidMOT80.560Valid
MOT40.670ValidMOT90.830Valid
MOT50.831ValidMOT100.677Valid
Panel D. The Dimension of Empathy
IndicatorLoading factorInterpretationIndicatorLoading factorInterpretation
E10.583ValidE60.739Valid
E20.622ValidE70.678Valid
E30.645ValidE80.688Valid
E40.763ValidE90.789Valid
E50.680ValidE100.757Valid
Panel E. The Dimension of Social Skill
IndicatorLoading factorInterpretationIndicatorLoading factorInterpretation
SS10.777ValidSS50.817Valid
SS20.758ValidSS60.615Valid
SS30.585ValidSS70.584Valid
SS40.864Valid

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
IndicatorLoading factorInterpretationIndicatorLoading factorInterpretation
SA10.635ValidSA60.788Valid
SA20.730ValidSA80.726Valid
SA50.762ValidSA90.741Valid
Panel B. Dimension of motivation
IndicatorLoading factorInterpretationIndicatorLoading factorInterpretation
MOT20.668ValidMOT70.741Valid
MOT30.776ValidMOT80.553Valid
MOT40.687ValidMOT90.824Valid
MOT50.844ValidMOT100.662Valid

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

DimensionLoading Factor Interpretation
Self-awareness0.735Valid
Self-control0.875Valid
Motivation0.883Valid
Empathy0.824Valid
Social skill0.870Valid

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 ThinkingPanel C. Dimension of transcendental awareness
IndicatorLoading factorInterpretationIndicatorLoading factorInterpretation
CET10.859ValidTA10.765Valid
CET20.881ValidTA20.747Valid
CET30.868ValidTA30.844Valid
CET40.650ValidTA40.856Valid
CET50.853ValidTA50.887Valid
CET60.932ValidTA60.825Valid
CET70.813ValidTA70.869Valid
Panel B. Dimension of personal meaning productionPanel D. Dimension of conscious state expansion
IndicatorLoading factorInterpretationIndicatorLoading factorInterpretation
PMP10.826ValidCSE10.822Valid
PMP20.905ValidCSE20.918Valid
PMP30.896ValidCSE30.946Valid
PMP40.865ValidCSE40.909Valid
PMP50.887ValidCSE50.927Valid

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

DimensionLoading FactorInterpretation
Critical existential thinking0.814Valid
Personal meaning production0.761Valid
Transcendental awareness0.855Valid
Conscious state expansion0.815Valid

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
IndicatorLoading factorInterpretation
RP10.612Valid
RP20.596Valid
RP30.638Valid
RP40.728Valid
RP50.751Valid
RP60.731Valid
Panel B. Dimension of community service performance
IndicatorLoading factorInterpretation
CSP10.830Valid
CSP20.841Valid
CSP30.863Valid
CSP40.854Valid
Panel C. Dimension of teaching performance
IndicatorLoading factorInterpretation
TP10.947Valid
TP20.947Valid

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

DimensionLoading FactorInterpretation
Research Performance0.895Valid
Community Service Performance0.853Valid
Teaching Performance0.675Valid

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 StatusTotal valid IndicatorsThe name of valid indicatorsCronbach

Alpha

MotivationLatent variable9M1, M2, M3, M4, M5, M7, M8, M9, M100.851
Emotional intelligence (EI)/self-awarenessDimension6SA1, SA2, SA5, SA6, SA8, SA90.825
EI/self- controlDimension10SC1, SC, SC3, SC4, SC5, SC6, SC7, SC8, SC9, SC100.912
EI/motivationDimension8MOT2, MOT3, MOT4, MOT5, MOT7, MOT8, MOT9, MOT100.867
EI/ empathyDimension10E1, E2, E3, E4, E5, E6,

E7, E8, E9, E10

0.881
EI/social skillDimension7SS1, SS2, SS3, SS4, SS5, SS6, SS70.841
Spiritual intelligence (SI)/ critical existential thinkingDimension7CET1, CET2, CET3, CET4, CET5, CET6, CET70.929
SI/personal meaning productionDimension5PMP1, PMP2, PMP3, PMP4, PMP50.924
SI/ transcendental awarenessDimension7TA1,  TA2, TA3, TA4, TA5, TA6, TA70.923
SI/ conscious state expansionDimension5CSE1, CSE2, CSE3, CSE4, CSE50.944
Lecturer Performance (LP)/ Research PerformanceDimension6RP1, RP2, RP3, RP4, RP5, RP60.764
LP/ Community Service PerformanceDimension4CSP1, CSP2, CSP3, CSP40.869
LP/ Teaching PerformanceDimension2TP1, TP20.885

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 performancePath CoefficientStandard errort-statisticProbability Value
Motivation0.1400.1401.0000.160
Emotional Intelligence0.3610.1412.5600.006
Spiritual Intelligence0.1600.1371.1680.122

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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