57
INTERNATIONAL ISLAMIC ECONOMIC SYSTEM CONFERENCE (I-iECONS 2021)
The Role of Grit in Determining Work Engagement and Innovative Behaviour Outcome for Lifelong Learning in Digital Economy
Siti Hamimah Rasidi
Faculty of Economics and Muamalat, Universiti Sains Islam Malaysia (USIM), Bandar Baru Nilai, 71800 Nilai, Negeri Sembilan Malaysia
Tel: +606 798 6304/6402 E-mail: siti.rasidi@raudah.usim.edu.my
Abstract
The role of grit by Duckworth has captured scholars’ attention, especially in education. Evidence suggested that grit can be applied in other fields such as business. Grit encapsulates persistency in terms of passion for internal motivation and purpose for external motivation. With rapid technology changes, there is a need to foster innovative work behaviour to shape lifelong learning culture. With the advent of the digital economy, it is knowledge-intensive. Thus, pushing the need for people to be more innovative. This paper investigates the role of grit as the determinant of work engagement and innovative work behaviour. The study was conducted on public sector employees in Malaysia. Data collection was made from sample respondent n=227 employees working in six government agencies in Malaysia about online government services. A theoretical framework was developed underpinning Social Learning Theory (SLT) by Bandura to include personal factors and environmental factors to instil the right behaviour and create self-regulated psychological mechanisms. PLS-SEM was employed to conduct partial least squares for data analysis. Findings indicate profound result with significance (p<0.000), and all hypotheses were fully supported. This research emphasizes the spirit of Islamic tradition and practice in acquiring knowledge, implying it is a lifelong learning journey.
Keywords: grit; work engagement; lifelong learning; public sector innovation
1. Introduction
Grit was firstly mentioned in the academic scene by Duckworth et. al (2007) to demonstrate the importance of a non-cognitive construct to benchmark human performance. The role of grit has increased considerable research primarily because it can be nurtured and developed for the sake of lifetime success. In recent years, non-cognitive constructs are widely endorsed and seen as growing evidence in popular motivation books such as resilience by Reivich & Shatte (2003), growth mindset by Dweck (2007) and flourish by Seligman (2012). Grit, however, stood out beyond concept, as it is built on empirical testing within education achievement. Traditional school curriculum emphasised cognitive skills and abilities as key indicators. Scholars then consider grit a new approach to assess performance character strength, drawn upon to achieve one’s potential in a particular challenge (Soutter & Seider, 2013). The same degree of assessment can be applied to employees. The advent of the digital economy brings the importance of having non-cognitive skills that encapsulate personal attributes in innovation. Non-cognitive skills are defined as patterns of thought, feelings and behaviour of individual that develop over time throughout their life (Borghans, L; Duckworth, A; Heckman, 2008).
58
1.1 The role of grit at workplace from the Western and Islamic Perspectives
Non-cognitive skills like grit provides greater benefit for an employee to attain the disposition to pursue long term goals with persistence and determination (Duckworth et. al, 2007). Employees with grit tend to have more confidence. In challenging times at the workplace, rather than believing to fail, employees can cope with setbacks. It pushes the employee to explore their potential. In addition, gritty employees are focused on the outcome they can control by not wasting time or energy thinking about issues they cannot control. Finally, those with grit know that learning from mistakes is part of the learning curve. They take it as a challenge and move on to prevent re-occurring.
Therefore, attaining grit builds on the character to become a self-improver and problem solver, leading to innovative work behaviour. As an individual, one must be creative to increase product and services in better quality, reduced price, and improved customer satisfaction. These performance indicators are organizationally defined and expected to cascade down to employees to follow.
This study brings out Islamic tradition in the importance of character building. The first point is that it is part of the teachings of the Prophet Muhammad S.A.W to ensure that humans are created to perform good deeds. Character building cultivates the existence of general trait such as patience and gratitude. Nevertheless, success is oriented in grit to ensure human ambition and determination for long term goals. The Quran mentioned this in Surah An-Najm:
ﻰَﻌَﺳ ﺎَﻣ ﱠﻻِإ ِنﺎَﺴْﻧِ ْﻺِﻟ َﺲْﯿَﻟ ْنَأ َو
« And that there is not for man except that [good] for which he strives for (39) »
۳۹
Another point, the measurement of success in Islam covers life in this world and hereafter. Unlike the Western psychology scholars’ point of view, success is meant in this world and only for worldly things. Typically, grit employees are determined workers, sometimes over-confident, claiming themselves as the do-ers and the contributors. Theoretically, scholars Ryan and Deci (2017) highlight the improved version of Self-Determination theory (SDT) to include psychological nutrient essential for individual adjustment, integrity and growth. Human motive or desires are not fit into this definition because character building has not been recognised. Only later, emerging scholars in positive psychology start to develop well-being theories such as flow by Csikszentmihalyi (2008) and flourish by Seligman (2012). However, Islam already discovered human values in combination within faith. Islam guides faithful believer to safe passage with the objective of eternal endgame in the worship or ibadah to Allah. The Quran specified the need to stay on the right course in Surah Hud:
ٌﺮﯿ ِﺼَﺑ َنﻮُﻠَﻤْﻌَﺗ ﺎَﻤِﺑ ُﮫﱠﻧِإ ا ْﻮَﻐْﻄَﺗ َﻻ َو َﻚَﻌَﻣ َبﺎَﺗ ْﻦَﻣ َو َت ْﺮِﻣُأ ﺎَﻤَﻛ ْﻢِﻘَﺘْﺳﺎَﻓ
«So remain on a right course as you have been commanded, [you] and those who have turned back with you [to Allah], and do not transgress. Indeed, He is Seeing of what you do» (112)
Compared against Islam and Western perspective, Muslims focus on the reality of circumstances instead of the individual alone. A Muslim avoids cognitive dissonance in which negative feelings and thoughts arise when facing calamity or conflict at work or even when confronted with toxic employment practices that could increase turnover and affect the employee physically and emotionally. Such act can be overcome by contemplation with increased invocation of Allah, supplication of do’a and faith with total reliance on the One Al-Mighty. Therefore, this study is interested to explore grit in the context of self-learning as a character skill or soft skills especially when the job requires acquiring knowledge or obtaining inspiration.
1.2 The implication of grit in lifelong learning at workplace
Previous studies in grit have identified the predictive role of grit in job performance. (Agarwal, 2014) mentioned Social Exchange Theory to measure justice, trust and innovative behaviour. Social exchange in employer relationship typically relates to the wellbeing of the employee from the psychological needs. This concept is rooted in Human Resource Management (HRM) about the employer-employee expectations at workplace. Employees initiate innovation because of job expectation to perform process or products improvement. HRM literature has also
59
mentioned that innovation can only occur if employees engage in generating and implementing ideas (Bos-Nehles et al., 2017). In other words, to promote innovativeness, self-learning is a desired character because motivated or self- directed employee are willing seize opportunity and provide the solution.
However, the push for innovation has made learning at workplace becomes as default. HRM firms explained that rapid technological advancement transforms traditional workplaces into contemporary digital workplaces (Cascio &
Montealegre, 2016; Maselli et al., 2012; Herrera et al., 2010). This transformation has unsettling consequence especially in the area of talent management. Companies have problems retaining human assets with the right knowledge, skills, and abilities (KSAs). Indonesia reported that talent management becomes top agenda at country level to fight industrial revolution 4.0 to overcome lost potential of talented people (Wolor et al., 2020). Moreover, with the global issue on Covid19, digital economy relies on technology to change society and workplace.
None of the existing organisational approach appears to provide solution for talent retention at individual level.
Many researchers begin to realise the absence of literature on talent proactive behaviour or self-initiated behaviour as major gap (Meyers, 2020; Parker & Collins, 2010; Tymon et al., 2010). This gap cannot be forgo based on the perception that organisation can afford passive employees. Consequently, organisations will have to accept that they have to rely on employees to contribute and innovate fully. Recent empirical evidence in 2020 shows that work engagement correlates with job crafting behaviour and innovativeness amongst Indian IT employees (Sharma &
Nambudiri, 2020). The argument is that people join workplaces where they are comfortable contributing their knowledge, skills, and abilities. However, by the time they spent most of time at the same organisation, they have chosen the domain and the environment that they believe best fit their disposition. Hence, in the absence of organisation stimulants, rewards and extrinsic motivation, employees tend to redesign their job in order to fit their abilities and preference thus enhancing personal outcomes including being innovative (Wrzesniewski & Dutton, 2001). This becomes the defining talent hunt for active employee instead of passive employee for HRM to ponder.
1.3 Study objectives
Thus, this study presents a step towards conceptualising personal and environment factors towards innovative work behaviour. Grit serves as the personal factor to ensure employee has non-cognitive sense to continue their pursuit at work. Whereas work engagement serves as the environment factor necessary in this study to show the function of work condition fuelled by energy. Evidence shows that employees are higher in work engagement when they have higher levels of personal resources, including self-efficacy, optimism, and resilience (Mäkikangas et al., 2013). Evidently, work engagement and innovative work behaviour are correlated and can accomplish output such as ideas generation, ideas promotion and ideas realisation (Černe et al., 2018; Janssen, 2000; van Zyl et al., 2019).
As a whole, this study attempts to analyse grit as determinants for work engagement and innovative work behaviour in achieving an employee’s attention towards strengthening intrinsic motivation for lifelong learning.
Moreover, author Duckworth (2007) established the said attributes as vital to achieve long-term goals. Recent empirical studies by Dugan et al. (2019), Eskreis-Winkler et al. (2014) and Suzuki et al. (2015) have demonstrated the significance of grit in achieving respective outcomes such as sales performance, talent retention and happiness at work. These are positive outcomes to show that it elevates the human potential without being directed or influenced by others.
As such, this study reports the result from a survey whose main objectives was to assess the following research objectives:
Under Model 1, this study attempts: -
To evaluate the role of consistency of interest from the grit construct on the relationship with grit To evaluate the role of persistency of effort from the grit construct on the relationship with grit To determine whether grit is correlated to work engagement
To determine whether grit is correlated to innovative work behaviour Under Model 2, the study attempts: -
To assess the role work engagement with innovative work behaviour To assess the role of innovative work behaviour with Ideas Generation
60 Consistency
of Interest
Persistent of Effort
Grit Second Order
Work Engagement
Innovative Work Behaviour
Vigour
Dedication Absorption
Ideas Generation
Ideas Promotion
Ideas Realisation First Order Second Order EP
RS ON AL
NE V I RO MN NE T
BE HA VI OU R Legend:
Positive correlation Mediating role
Underpinning theory
To assess the role of innovative work behaviour with Ideas Promotion To assess the role of innovative work behaviour with Ideas Realisation
Finally, under Model 3, the study attempts to discover whether work engagement mediates the relationship between grit and innovative work behaviour
In the next section, we present a theoretical framework that investigates the defining attributes of grit: (1) consistency of interest and (2) persistent effort towards sustainable outcomes such as work engagement and innovative work behaviour.
1.4 Theoretical framework
This study employs theoretical framework that is skewed towards psychology by postulating on Bandura’s Principle of Social Learning Theory depicting personal, environment and behaviour. It is in Figure 1 below.
Fig.1. Theoretical framework for the role of grit in determining work engagement and innovative work behaviour.
The rationale for choosing Bandura’s learning paradigm is because it suggested that people observed the behaviour of others and learned to react from those actions with the environment. In the past, this theory was argued extensively on the early psychological theory on learning which focused strictly on reinforcement that the western viewed as operant conditioning. In addition, the rationale for this study is to study micro unit of analysis.
Nevertheless, this study acknowledged organisational learning literature that looks at macro unit of analysis from renowned scholars like Argyris and Schoen (1978). It seems somewhat less prominent when it comes to innovation by studying organisational structure without focusing on humans as the subject. Furthermore, the walls of corporate in traditional human resource management (HRM) has been shaken with the global phenomenon on Covid-19 outbreak. Work from home or #WFH has become the norm and shall be relevant in coming years with intensity of digitalisation.
61 1.5 Hypotheses
Grit is defined by consistency of interest and persistency of effort. The focus is to understand which grit dimension shows a more cause-effect or significant predictor for this study. One empirical study proposes that work engagement can be explored as a fully mediating model and partial mediating model between the role of trust and innovative work behaviour by looking at the result coming from Goodness of fit Indexes (Agarwal, 2014). However, the interest of this study is to understand the role of grit using the reflective measurement model or common factor model to report which dimension is more significant in carrying the correct score. Thankfully, this study can refer to recent IS journals focusing on structural equation modelling that provides a guideline on how to report both confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) (Benitez et al., 2020; Tehseen et al., 2019).
Thus, this study suggests the following hypotheses under Model 1:
H1: Consistency of Interest has a positive impact on Grit H2: Persistency of Effort has a positive impact on Grit H3: Grit is positively related to Work Engagement
H4: Grit is positively related to Innovative Work Behaviour
Now, work engagement is comprised of three dimensions which is vigour, dedication and absorption. Innovative Work Behaviour comprises three dimensions: ideas generation, ideas promotion, and ideas realisation. This study suggests that both constructs as outcome and sustainability factor is a context-specific phenomenon. Therefore, this study continues to hypothesise Model 2 to do estimation towards formative measurement model especially for Innovative Work Behaviour to understand which is more significant.
H5: Work Engagement is positively related to Innovative Work Behaviour H6: Innovate Work Behaviour has a positive impact on Ideas Generation
H7: Innovative Work Behaviour has a positive impact on Ideas Promotion H8: Innovative Work Behaviour has a positive impact on Ideas Realisation
Finally, to tie the evidence, this study includes a hypothesis on mediating role of Work Engagement between Grit and Innovative Work Behaviour. According to Smart-PLS, analysing the strength of the mediator and its relationships with the other constructs allows substantiating the mechanisms that underlie the cause-effect relationship between an exogenous construct and an endogenous construct which is useful in observing data in human resource management practice (Ringle et al., 2020).
Thus, this study includes the hypothesis under Model 3:
H9a&H9b: Work Engagement mediates the relationship between Grit and Innovative Work Behaviour
2. The current study
This study aims to determine the role of grit as a determinant for work engagement and innovative work behaviour. The literature on grit is based on the psychometric properties of the Short Grit Scale. This study shall be tested using Structural Equation Model (SEM), Model 1 is to perform confirmatory factor analyses were used to determine the second-order of testing latent variable from the two dimensions in grit which is Consistency of Interest (CI) and Persistent of Effort (PE). Then, Model 2 of this study is to understand the second-order testing latent variable for formative measurement for Innovative Work Behaviour. Finally, Model 3 of this study is to complete the hypothesis with a mediating relationship between grit, work engagement and innovative work behaviour.
62 3. Methods
3.1. Sample and study procedure
This study surveyed public sector employees who were working in six different agencies in Malaysia. These agencies were situated within the Klang Valley and Putrajaya, which is the government administration location.
Data was collected from each department from the represented agencies where they make important economic policies contributions in their organisation. In the data, only age, gender, tenure and education level were used in the descriptive analysis. Of the 300 questionnaires distributed, 227 records were used with a response rate of 75%.
3.2. Measures
Grit-S scale from Duckworth et al. (2007) was utilised in the study to measure two dimensions: Consistency of Interest (CI) and Persistent of Effort (PE). This measurement has eight (8) questions and the reliability test results from 0.80 to 0.90, respectively. Four items are reverse coded.
Utrecht Work Engagement Scale (UWES) by Schaufeli et al. (2006) was employed in the study to measure three dimensions: 1) Vigour 2) Dedication 3) Absorption. This measurement has nine (9) questions, and the Cronbach alpha ranges from 0.89 to 0.97.
Innovative Work Behaviour scale by Janssen (2000) was used in the study to measure three dimensions: 1) Ideas Generation 2) Ideas Promotion 3) Ideas Realisation. This measurement has nine (9) questions, and the reported Cronbach alpha was 0.95 as a composite.
All questionnaires were developed using the 5-Likert scale to standardise the measurement.
3.3. Data analysis
The PLS-SEM was utilised for quantitative analysis because it simultaneously analyses both reflective and formative constructs (Joseph F. Hair et al., 2019). In addition, PLS-SEM required suitable sample size of 10 times more than the highest number of model construct items (Ringle et al., 2020). Hair et al. (2019) suggested using G*power statistical software to calculate the minimum sample size. However, this study relied on Cohen (1982) to define the minimum sample size has to be 191 with a maximum number of four arrows pointing at a construct. The result is acceptable based on Cohen (1982) recommended table to get the significance level at1% for minimum R2 to get the statistical power of 80%. Thus, the data used in this study has achieved a sufficient sample size of 227 usable records.
3.4. Reliability analysis
After executing in Smart-PLS software, Cronbach’s alpha and Composite Reliability test was conducted. Based on the outcome, the result showed that convergent reliability was satisfactory with a value above 0.75, which is the minimum level. All constructs hypothesised in this study indicated satisfactory discriminant criterion for Average Variance Extracted (AVE) with values above 0.5, which is the minimum level.
The original questionnaire has 26 items which consist of eight items for grit, nine items for work engagement and nine items for innovative work behaviour. The data was revised to fit the cleaned items from the total items, which resulted in a balance of 20 cleaned items. Table 1 summarised the result as new items for each construct.
63
Table 1. Result of convergent validity, cronbach alpha, composite reliability and AVE.
Construct Items Cronbach’s Alpha rho_A Composite Reliability Average Variance Extracted (AVE)
Consistency of Interest 0.790 0.806 0.864 0.615
D2 0.707
D4 0.813
D5 0.768
D6 0.842
Persistent of Effort 0.928 0.934 0.965 0.933
D7 0.963
D8 0.969
Grit 0.866 0.879 0.901 0.607
D2 0.707
D4 0.813
D5 0.768
D6 0.842
D7 0.963
D8 0.969
Work Engagement 0.961 0.961 0.967 0.785
E1 0.873
E2 0.899
E3 0.925
E4 0.867
E5 0.917
E6 0.859
E7 0.880
E8 0.860
IG 0.911 0.912 0.957 0.918
F1
F2
IP 1.000 1.000 1.000 1.000
F6
IR 0.922 0.922 0.951 0.865
F7
F8
F9
IWB 0.935 0.936 0.949 0.757
F1
F2
F6
F7
F8
F9
Note:
Convergent Validity with cleaned items loading
Cronbach alpha has to be above 0.70 and Composite Reliability above 0.70 Average Variance Extracted has to be above 0.50
3.5. Measure model analysis – cross loadings
Then, the table below shows the cross-loadings result to test discriminant validity from individual items in the construct utilised for evaluating the measurement model.
64 Table 2. Result of Cross-loading.
Construct Label CI Grit IG IP IR IWB PE WE
New_Grit D2 0.7070 0.6200 0.3730 0.2490 0.3340 0.3620 0.3820 0.3670
D4 0.8130 0.7060 0.5410 0.5410 0.6040 0.6250 0.3940 0.5930
D5 0.7680 0.7410 0.4350 0.4260 0.4600 0.4870 0.5320 0.6880
D6 0.8420 0.8810 0.4400 0.4000 0.4270 0.4660 0.7770 0.5700
D7 0.6060 0.8090 0.2120 0.1810 0.1810 0.2090 0.9630 0.4590
D8 0.7150 0.8840 0.3860 0.3860 0.3870 0.4230 0.9690 0.5810
New_WE E1 0.6060 0.6280 0.3300 0.3190 0.2880 0.3360 0.5300 0.8730
E2 0.5540 0.5760 0.3640 0.4090 0.3670 0.4090 0.4800 0.8990
E3 0.6500 0.6700 0.4920 0.5150 0.5260 0.5610 0.5590 0.9250
E4 0.5670 0.5270 0.4420 0.3990 0.4710 0.4910 0.3530 0.8670
E5 0.5400 0.5650 0.3700 0.4440 0.4310 0.4520 0.4770 0.9170
E6 0.6640 0.6670 0.3930 0.3840 0.5420 0.5080 0.5330 0.8590
E7 0.7000 0.6520 0.5680 0.5310 0.6270 0.6460 0.4390 0.8800
E8 0.7270 0.6720 0.5030 0.4950 0.5000 0.5470 0.4510 0.8600
New_IWB F1 0.5580 0.5000 0.9600 0.6530 0.7170 0.8580 0.3090 0.4940
F2 0.5340 0.4770 0.9570 0.6340 0.6700 0.8280 0.2910 0.4580
F6 0.5190 0.4720 0.6720 1.0000 0.7970 0.8670 0.2980 0.5000
F7 0.5670 0.4610 0.6650 0.7200 0.9230 0.8770 0.2020 0.5010
F8 0.4970 0.4520 0.6560 0.7490 0.9350 0.8860 0.2850 0.5300
F9 0.5590 0.5170 0.6980 0.7530 0.9330 0.9000 0.3450 0.4770
3.6. Measure model analysis – AVE
Then, table below shows the Average Variance Extracted result using the Fornell-Larcker criterion. The goal is to ensure factor loading and the AVE were considered correlated for each construct.
Table 3. Result for average variance extracted to show latent variable correlations.
CI Grit IG IP IR IWB PE WE
CI 0.784
Grit 0.951 0.779
IG 0.570 0.510 0.958
IP 0.519 0.472 0.672 1.000
IR 0.581 0.513 0.724 0.797 0.930
IWB 0.619 0.552 0.880 0.867 0.955 0.870
PE 0.686 0.878 0.314 0.298 0.299 0.332 0.966
WE 0.714 0.705 0.497 0.500 0.540 0.568 0.541 0.885
Note:
The values in the boldface are the square root of AVE
3.7. Additional criteria – VIF for collinearity issues
Finally, based on the PLS-SEM result, additional criteria have been applied to check for multicollinearity issues.
From the result, there are no reported issues as the VIF are below 5.0. According to Hair et al. (2019), anything VIF exceeding 5.0 indicates the said problem in collinearity. If there are two or more predictors in the model, it is correlated and provides redundant information.
65 Table 4. Result from Collinearity (VIF)
Work engagement
as DV VIF Innovative Work
Behaviour as DV VIF
CI 1.890 WE 1.000
PE 1.890
Grit 1.890
WE 1.000
3.8. Plan of analysis
At this point, the strategy of the study is to conduct a measurement model in three separate plans of analysis based on the proposed hypotheses. For Model 1, the intent is to find out the reflective measurement model from grit construct using the 1st order and 2nd order analysis. For Model 2, the intent is to determine the formative measurement model from the Innovative Work Behaviour construct using first and second-order analysis as per Figure 2 and Figure 3 below. Model 3 summarizes the mediating effect between the constructs – grit, work engagement and innovative work behaviour.
Fig. 2. Model 1- Grit Reflective Measurement.
66
Fig. 3. Model 2 – Innovative Work Behaviour Formative Measurement
Finally, this study includes the mediating role of work engagement between grit and innovative work behaviour as part of the final hypothesis. It is shown as per the diagram below.
Fig. 4. Mediating Role of Work Engagement Between Grit and Innovative Work Behaviour 4. Results
4.1 Model 1 - Grit Reflective Measurement result
As a start, the result for Hypothesis 1, 2, 3 and 4 were fully supported to show the effect from reflective measurement. The result from PLS path analysis was run and demonstrated as per Figure below.
67
Fig. 5. Result from Reflective Measurement Based on the PLS path analysis, the result is shown below:
Table 5. Result from Reflective Measurement for hypothesis.
Hypothesis Path
Relationship Std Beta
Sample Mean
(M)
Error Std t-values p-
values Decision H1 CI -> Grit 0.6860 0.6880 0.0240 28.6930 0.0000 Supported**
H2 PE -> Grit 0.3960 0.3950 0.0180 21.4710 0.0000 Supported**
H3 Grit -> WE 0.7100 0.7090 0.0550 12.8580 0.0000 Supported**
H4 Grit -> IWB 0.5630 0.5680 0.0520 10.7940 0.0000 Supported**
Note:
Strongly significant with p**<0.01 Significant p<0.05
According to Hair et al.(2019), the R2 values in the 2nd order construct of grit was the highest from the Consistency of Interest at 0.686. Likewise, it is considered substantial if anything is above 0.67 for R2 (Chin, 1988a). Then, we calculate for predictive relevance Q2 using the blindfolding function in Smart-PLS, and the result shows all values are more than 0 (Stone 1974; Geisser,1975). According to Hair et al. (2017), the model showed predictive relevance when Q2 was more than 0. Therefore, the criteria for the hypothesis in Model 1 are validated.
4.2 Model 2 -Innovative Work Behaviour Formative Measurement result
Then, for Hypothesis 5, 6, 7 and 8, the result was fully supported to show the effect from formative measurement. The result from PLS path analysis was run and demonstrated as per Figure below.
68
Figure 6: Result from Formative Measurement Based on the PLS path analysis, the result is shown below:
Table 6. Result from Innovative Work Behaviour Formative Measurement.
Hypothesis Path
Relationship Std Beta Std
Error t-values p-
values Decision H5 WE -> IWB 0.576 0.060 9.550 0.000 Supported**
H6 IWB -> IG 0.880 0.026 33.832 0.000 Supported**
H7 IWB -> IP 0.867 0.021 41.599 0.000 Supported**
H8 IWB -> IR 0.955 0.009 110.647 0.000 Supported**
Note:
Strongly significant with p**<0.01 Significant p<0.05
According to Hair et al.(2019), the R2 values for Ideas Realisation in the 2nd order construct of Innovative Work Behaviour was the highest at 0.911. Likewise, it is considered substantial if anything is above 0.60 for R2 (Cohen, 1988). Then, we calculate for predictive relevance Q2 using the blindfolding function in Smart-PLS, and the result shows all values are more than 0 (Stone, 1974; Geisser,1975). According to Hair et al. (2017), the model showed predictive relevance when Q2 was more than 0. Therefore, the criteria for the hypothesis in Model 2 are validated.
4.3 Model 3- mediation result
For Hypothesis 9a and 9b, the result was fully supported. The bootstrapping procedure (500 subsamples) was applied based on Hair et al. (2014) recommendation to determine the effect of mediating role. Figure 5 shows the result as per below.
69
Fig. 7. Model 3 Mediating Role of Work Engagement Between Grit and Innovative Work Behaviour.
The table below represents the standard beta, standard error, t-values and p-values.
Table 7. Result of Work Engagement as Mediator.
Mediating Role Original
Sample (O)
Sample Mean (M)
Standard Deviation (STDEV)
T Statistics (|O/STDEV|)
p-Values
Grit -> Innovative Work Behaviour 0.358 0.372 0.078 4.611 0.000
Grit -> Work Engagement 0.722 0.719 0.046 15.794 0.000
Work Engagement -> Innovative Work Behaviour 0.309 0.306 0.087 3.536 0.000 4.3.1 Total direct effect
According to Preacher and Hayes (2008), the mediating analysis result found that grit significantly predicts work engagement, b=0.722, t=15.794, p=0.000. Work engagement was a significant predictor of innovative work behaviour, b=0.309, t=3.536, p=0.000. Thus, R2 explains approximately 3.536 of the variances in the relationship between work engagement and innovative work behaviour. The relationship between the IV (grit) and the DV (innovative work behaviour) via the mediator (work engagement) has a causal relationship where the p<0.000.
Therefore, the mediating variable is said to have a direct effect, and it is significant. The table below presents the path coefficients of the direct effects for mediation. Therefore, the criteria for the hypothesis in Model 3 are validated.
70 1.3.2 Total indirect effect
Similarly, Preacher and Hayes (2008) provide a guideline on total indirect effects for mediation. When work engagement is not present in the model, grit predicts innovative work behaviour, b=0.223, p=0.000. A significant standardised indirect effect was the confidence interval (CI) for lower and upper limit, i.e. [0.123, 0.323]. The interpretation of this result is relatively small, and zero does not cross both CI values. Table 6 summarises the result.
Table 2: Result of Total Direct and Indirect Effect for Work Engagement as Mediator Original sample = standard
beta for indirect
effect
IV- ->
Mediator Mediator -->
DV Automatic
calculation Standard
deviation Automatic calculation
Bootstrapped Confidence Interval
Path a Path b Indirect
Effect SE t-value 95% LL 95%
UL
M1 0.722 0.309 0.223 0.051 4.374 0.123 0.323
2. Discussion
The organisation is always looking for talented resources beyond intelligence and non-cognitive skills are in demand. It has come to the point of survival of the business to have executive excellence that can readily produce an adaptive response to stay ahead of change (Kanter, 2000). This study addresses the gap in understanding non- cognitive skill like grit to support pro-active behaviour such as being innovative. The result shows that consistency of interest is more significant than persistent effort in the construct of grit. The reason employee with goal-setting more likely to internalise and set their job expectations.
Then, from the HRM practice, the importance of soft HRM brings psychology to the core theme to address critical resource loading employees to be efficient organisation. Hard HRM was deemed as traditionally looking at the fundamental function, which boils down to personnel management. Perhaps soft HRM needs to consider learning from risk and provide decision-making on a more ephemeral basis. HRM would then be similar to project management when dealing with sophisticated employees, typically known as knowledge workers. Work engagement is part of the motivation to ensure that the employees bring position emotions to the workplace. Partly, this study explains that the dimension of ideas realisation become significant in innovative work behaviour. Most passive employees can provide idea generation and promotion without further commitment to carry on the idea into reality.
Only innovative employees are characterised as active employees who would consciously agree to realise the idea into reality to solve a burning problem or simply improve the situation. Perhaps, soft HRM must be trained to spot talent instead of herding the mass employees and train them to be innovative. Innovation is part of seeking the right candidate that matches the business objectives.
From a theoretical building perspective, Bandura (1986) provides the importance of reciprocating elements between behaviour, personal resources and environment in Social Learning Theory. However, Bandura does not explain how Hobfall (2002) later proposed the Conservation of Resources theory to protect and accumulate resources over time, especially when challenging times and the perceived risk in the employment may affect employee to be innovative. Perhaps, non-cognitive skills like grit can transcend over time to stabilise active employees to continue innovating. Also, few studies look at the innovativeness of an employee, especially in designing the task. Perhaps, in the future study, one can explore whether job crafting intervention is required to redesign their individual needs.
71 3. Limitation
This study was conducted amongst public sector employees involved in the policy making and understood the importance of innovation on the national agenda. Perhaps the next study would focus on industry-level knowledge workers or employees undergoing digital transformation in their workplace. Innovation is part of a long-term journey, and it would be an interesting topic to study gestation in innovation. Furthermore, despite the statistical result in this study supports the significance of grit as an advantage, there is also a need to study the disadvantage of grit based on the dimension persistent of effort. It can be counterproductive when a problem that fights against the solution. There is no satisfaction measurement in grit to recognise the time limit to stop pursuing given tasks.
Finally, when innovation involves new product development, the investment must be justified to ensure consensus by the Management. However, this study suggests including HR investment in business settings. Typically, in HRM, soft skills are desired during the onboarding of talent. Then during a performance review, perhaps there is a need to incorporate business objectives with talent competency objectives to manage the workforce effectively. Otherwise, HRM would need to tap resources and initiate project collaboration that can be a future business.
4. Conclusion
With digitalisation, everyone at work is inevitable to join the race to learn and unlearn. Grit can be a good quality to have when empowering employees with broader learning, which has become essential. To work from home, suddenly, the desk has become invisible, and one has to be equipped with online tools such as SKYPE, ZOOM and Microsoft Teams. This study argues that the people quality should not have reduced to demonstrate innovative work behaviour with the dependency on technologies. Instead, one should be agile enough to strengthen their character with grit and start over to accept any challenges that come.
Acknowledgements
Author indebted to acknowledge supervisors, friends and family who support and encourage participation in this conference as part of a knowledge sharing and feedback-seeking session. Doing so marks one form of academic milestone in the long-term journey to complete this study.
References
Agarwal, U. A, 2014. Linking Justice, Trust And Innovative Work Behaviour To Work Engagement. Personnel Review 43, 1, 41-73.
Benitez, J., Henseler, J., Castillo, A., Schuberth, F., 2020. How To Perform And Report An Impactful Analysis Using Partial Least Squares:
Guidelines For Confirmatory And Explanatory IS Research. Information and Management 57, 2, 103-168.
https://doi.org/10.1016/j.im.2019.05.003.
Borghans, L., Duckworth, A., Heckman, J., 2008. The Economics and Psychology of Personality Traits. Journal of Human Resources 43, 4, 972- 1059. https://doi.org/10.3386/jhr.43.4.972
Bos-Nehles, A., Renkema, M., Janssen, M., 2008. HRM And Innovative Work Behaviour: A Systematic Literature Review. Personnel Review 46, 7, 1228-1253. https://doi.org/10.1108/PR-09-2016-0257
Cascio, W., Montealegre, R., 2016. How Tech Is Changing Work and Organisations. Annual Review of Organizational Psychology and Organisational Behaviour 3, 6, 349-375. https://doi.org/10.1146/annurev-orgpsych-041015-062352
Černe, M., Batistič S., Kenda, R., 2018. HR Systems, Attachment Styles With Leaders, And The Creativity–Innovation Nexus. Human Resource Management Review 28, 3, 271–288. https://doi.org/https://doi.org/10.1016/j.hrmr.2018.02.004
Chin, W. W., 1998a. Issues and Opinion on Structural Equation Modelling. MIS Quarterly 22,1, VII-XVI.
Duckworth, A. L., Peterson, C., Matthews, M. D., Kelly, D. R., 2007. Grit: Perseverance And Passion For Long-Term Goals. Journal of Personality and Social Psychology 92, 6, 1087-1101. https://doi.org/10.1037/0022-3514.92.6.1087
Dugan, R., Hochstein, B., Rouziou, M., Britton, B., 2019. Gritting Their Teeth To Close The Sale: The Positive Effect Of Salesperson Grit On Job Satisfaction And Performance. Journal of Personal Selling and Sales Management 39, 1, 81–101.
https://doi.org/10.1080/08853134.2018.1489726
Eskreis-Winkler, L., Shulman, E. P., Beal, S. A., Duckworth, A. L., 2014. The Grit Effect: Predicting Retention In The Military, The Workplace, School And Marriage. Frontiers in Psychology 5, 2, 1–12. https://doi.org/10.3389/fpsyg.2014.00036
Geisser, S., 1975. The Predictive Sample Reuse Method with Applications. Journal of the American Statistical Association 70, 350, 320-328. doi:
10.1080/01621459.1975.10479865
Hair, Joe F., Sarstedt, M., Hopkins, L., Kuppelwieser, V. G., 2014. Partial Least Squares Structural Equation Modeling (PLS-SEM): An Emerging Tool In Business Research. European Business Review 26, 2, 106–121. https://doi.org/10.1108/EBR-10-2013-0128
72
Hair, Joseph F., Risher, J. J., Sarstedt, M., Ringle, C. M., 2019. When To Use And How To Report The Results of PLS-SEM. European Business Review 31,1, 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Herrera, F., Chan, G., Legault, M., Raheemah, Mohammad, Kassim, Vikas, S., 2010. The Digital Workplace: Think, Share, Do Transform Your Employee Experience. Deloitte & Touche LLP, 37, 3, 4. https://www2.deloitte.com/content/dam/Deloitte/mx/Documents/human- capital/The_digital_workplace.pdf
Janssen, O., 2000. Job Demands, Perceptions Of Effort--Reward Fairness And Innovative Work Behaviour. Journal of Occupational &
Organizational Psychology 73,3, 287–302. http://10.0.5.68/096317900167038
Kanter, R. M., 2000. Kaleidoscope Thinking, in “Executive Excellence”. In: Management 21st Century Someday We’ll all Manage This Way, (Eds). Finance Times Prentice Hall, New York, pp. 250-261.
Mäkikangas, A., Schaufeli, W., Tolvanen, A., Feldt, T., 2013. Engaged Managers Are Not Workaholics: Evidence From A Longitudinal Person- Centered Analysis. Revista de Psicologia Del Trabajo y de Las Organizaciones, 29, 3, 135–143. https://doi.org/10.5093/tr2013a19
Maselli, M. B., Ilaria, E., Martellucci, E., 2012. Workplace Innovation and Technological Change. CEPS Special Report
Meyers, M. C., 2020. The Neglected Role Of Talent Proactivity: Integrating Proactive Behavior Into Talent-Management Theorising. Human Resource Management Review 30, 2. https://doi.org/10.1016/j.hrmr.2019.100703
Parker, S. K., Collins, C. G., 2010. Taking Stock: Integrating and Differentiating Multiple Proactive Behaviors. Journal of Management 36, 3, 633–662. https://doi.org/10.1177/0149206308321554
Reivich, K., Shatte, A., 2003. The Resilience Factor: 7 Keys to Finding Your Inner Strength and Overcoming Life’s Hurdles (1st edition).
Harmony.
Ringle, C. M., Sarstedt, M., Mitchell, R., Gudergan, S. P., 2020. Partial Least Squares Structural Equation Modeling in HRM Research.
International Journal of Human Resource Management 31,12, 1617–1643.
Schaufeli, W. B., Bakker, A. B., Salanova, M., 2006. The Measurement Of Work Engagement With A Short Questionnaire: A Cross-National Study. Educational and Psychological Measurement, 66,4, 701–716. https://doi.org/10.1177/0013164405282471
Seligman, M. (2012). in “Flourish”. A Visionary New Understanding of Happiness and Well-Being (Ed.). Atria Books.
Sharma, A., Nambudiri, R., 2020. Work Engagement, Job Crafting And Innovativeness In The Indian IT Industry. Personnel Review 49,7,1381–
1397. https://doi.org/10.1108/PR-11-2019-0607
Stone, M. (1974). Cross-Validatory Choice and Assessment of Statistical Predictions. Journal of the Royal Statistical Society. Series B (Methodological) 36, 2, 111-147. doi: 10.2307/2984809
Suzuki, Y., Tamesue, D., Asahi, K., Ishikawa, 2015. Grit and Work Engagement: A Cross-Sectional Study. PLOS ONE 10, 9, 1–12.
https://doi.org/10.1371/journal.pone.0137501
Tehseen, S., Qureshi, Z. H., Johara, F., Thurasamy, R., 2019. Assessing Perceived Business Success As A Reflective-Formative (Type II) Second-Order Construct Using PLS-SEM Approach. Journal of Sustainability Science and Management 14, 5, 84-114.
Tymon, W. G., Stumpf, S. A., Doh, J. P, 2010. Exploring Talent Management In India: The Neglected Role Of Intrinsic Rewards. Journal of World Business 45, 2, 109–121. https://doi.org/10.1016/j.jwb.2009.09.016
van Zyl, L. E., van Oort, A., Rispens, S., Olckers, C., 2019. Work Engagement And Task Performance Within A Global Dutch ICT-Consulting Firm: The Mediating Role Of Innovative Work Behaviors. Current Psychology. https://doi.org/10.1007/s12144-019-00339-1
Wolor, C. W., Khairunnisa, H., Purwana, D., 2020. Implementation Talent Management To Improve Organisation’s Performance In Indonesia To Fight Industrial Revolution 4.0. International Journal of Scientific and Technology Research 9, 1, 1243–1247.
Wrzesniewski, A., Dutton, J. E., 2001. Crafting a Job: Revisioning Employees as Active Crafters of Their Work. The Academy of Management Review 26, 2, 179. https://doi.org/10.2307/259118
