







































Humanitas: Indonesian Psychological Journal  

Vol. 22 (1), February, 1-12 

ISSN:  2598-6368(online); 1693-7236(print)                                                                 

       humanitas@psy.uad.ac.id             http://journal1.uad.ac.id/index.php/Humanitas                                10.26555/humanitas.v22i1.755 

Workforce agility in startup employees: The role of psychological 

empowerment, emotional intelligence and job autonomy 

Hasna Uzzakiyah1*, Galang Lufityanto2 

1Faculty of Psychology, Ahmad Dahlan University, Yogyakarta, Indonesia  
2 Department of Psychology, College of Liberal Arts, Wenzhou-Kean University 

Corresponding author: hasna@psy.uad.ac.id   
 

This is an open access article under the CC BY-SA license. 

 

Introduction 

A competitive market, unexpected situations, and fast-paced changes are faced by companies 
nowadays (Varshney & Varshney, 2020) especially in the post-COVID era. This situation 
forces organizations to swiftly adapt to the challenges and opportunities in the unstable 
business environment  (Alviani et al., 2024). Due to this situation, employee capability should 
be increased by companies to respond to the changing environment. Workforce Agility 
(WFA) is defined as the ability of workers to respond to rapid environmental changes and is 
divided into three aspects: proactivity, adaptability, and resilience (Sherehiy & Karwowski, 
2014). It is considered vital for individuals facing dynamic situations and maintaining a 
competitive edge. According to the data, WFA has been proven to help companies adopt New 
Ways of Working (NWW) in manufacturing companies in response to the changing 
environment (Cornelis & Febriansyah, 2023). In the small and medium-sized enterprises 

(SME) sector, WFA is also recognized for helping companies survive and grow post-

ARTICLE  INFO 

 

ABSTRACT  

 

Article history 

Received September 10, 2024 

Revised February 08, 2025 

Accepted February 12, 2025 

 Workforce Agility (WFA) is crucial for startup companies, 
particularly in unexpected situations. Research shows that WFA 
significantly contributes to an organization's ability to thrive amidst 
uncertainty and competitive challenges. WFA can be influenced by 
both internal and external factors. In this study, psychological 
empowerment (PE) and emotional intelligence (EI) are represented 
the internal factors, while job autonomy (JA) served as the external 
factor. This research aims to explore the relationships between PE and 
EI on WFA with JA as grouping variable. A quantitative approach 
was utilized, involving 180 employees from various startups. 
Multiple regression analysis was conducted to assess the relationships 
between PE, EI, and WFA, categorized into three levels of JA. The 
results indicated that PE and EI simultaneously have a significant 
positive impact on WFA. The model explained 52% of the variance 
(R² = 0.52, F=93.8, p< 0.01). The study concluded that enhancing PE 
and EI among startup employees can improve their WFA. However, 
when JA levels segmented participants, only those in the low and 
medium JA groups exhibited a relationship between PE and EI on 
WFA. Thus, PE and EI can only increase WFA in subjects with low 
and medium level of JA. 

 

     

 
Keywords 

Emotional Intelligence 

Job Autonomy 

Psychological Empowerment 

Startup 
Workforce Agility 
 

 

 

 

mailto:humanitas@psy.uad.ac.id
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Hasna Uzzakiyah et.al (Workforce agility in startup employees: The role of...) 

pandemic by implementing cross-training, work design, and employee empowerment 
techniques within the organization (Elanthi & Dhanabhakyam, 2021).  

Although WFA has become necessary for companies to respond quickly to changes, 

the literature examining WFA in the startup sector is limited. At the same time, it is known 

that the number of startups in Indonesia has been growing each year. Unfortunately, not all 

startups in Indonesia achieve success in the first year. A study shows that a high startup failure 

rate is faced by Indonesia, with 75% being confronted with difficulties in scaling their 

business (Afdi & Purwanggono, 2017). According to the study, the failures of startups in 

Indonesia are attributed to the lack of appropriate team capabilities to build a business, caused 

by a lack of experience in dealing with change, difficulty finding investors, and a lack of 

business experience (Singgih & Sari, 2024). Therefore, a team with high WFA is required in 

the startup sector for long-term business continuity.  

A preliminary study indicated that WFA is needed for startups in Indonesia. 

Environmental changes have made it necessary for startups in Indonesia to change products 

or services to survive (CNN Indonesia, 2020). Therefore, it was revealed by several startups 

in preliminary studies that they need people who are innovative, creative, and adaptable 

(resource person-1), employees who are willing to act without being ordered by superiors, 

flexible to change (resource person-2), and employees who can complete tasks quickly, 

effectively, without reducing the quality of work (resource person-3). The conclusion of the 

preliminary study shows that the changing business direction in startups requires Human 

Resources (HR) that are listed in aspects of WFA (Sherehiy & Karwowski, 2014).  

Based on previous research, WFA is more studied from the external side, such as the 

role of technology (Youndt et al., 1996), organizational structure (Alavi et al., 2014), and 

work organization (Sherehiy, 2008). On the other hand, WFA literature that discusses the 

internal side of individuals is still limited. Individual internal factors need to be developed so 

that individuals can increase independence in work and not depend on environmental factors 

(Thomas & Velthouse, 1990). Internal factors in employees play a more significant role in 

eliciting expected behavior in the work environment than external factors (Olafsen et al., 

2015). This is because internal factors arise within the individual due to liking and satisfaction 

with the work done. Meanwhile, external factors depend on environmental factors that 

encourage individuals to work (Beqiri, 2019). This internal factor is essential, especially when 

companies face significant changes. Of course, this also impacts startup companies, which 

are considered the most vulnerable actors in the world economy (Kuckertz et al., 2020). 

Therefore, companies must pay attention to individual internal factors to produce optimal 

performance even when the company undergoes system changes. 

Internal factors in this study are represented by Psychological Empowerment (PE), 

known to enhance WFA. Previous research has demonstrated that PE contributes to 

increasing WFA among the public and private sectors (Muduli & Pandya, 2018). However, 

this relationship has not yet been explored in startup companies. PE is defined as an 

individual’s intrinsic motivation to perform their work role, comprising four cognitive 

factors: meaning, competence, impact, and self-determination. Individuals with high PE are 

often capable of working independently without depending on direction and rewards from 

others (Thomas & Velthouse, 1990). Consequently, their task completion speed increases, 

their initiative in problem-solving grows, and their resilience when facing challenges 

improves (Thomas & Velthouse, 1990). The influence of PE on WFA is also shaped by the 

provision of Job Autonomy (JA) to employees (Scott & Bruce, 1994). JA allows employees 

to make decisions and complete tasks independently without overly relying on superiors. This 

autonomy positively impacts PE, as employees feel that they feel the sufficient ability to 

tackle problems (Wang & Netemeyer, 2002). The individual motivation to solve problems 



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Hasna Uzzakiyah et.al (Workforce agility in startup employees: The role of...)  

independently can expedite responses to environmental changes (Condry & Chambers, 

1978), because guidance and coordination from superiors are unnecessary (Gunasekaran, 

1999).  

Emotional Intelligence is another internal factor that can influence WFA (Hosein & 

Yousefi, 2012). Emotional Intelligence (EI) refers to the capacity to manage one's emotions 

and respond suitably to the feelings of others. It encompasses four key aspects: self-

awareness, self-control, self-motivation, empathy, and social relationships (Goleman, 1998). 

People with high EI often adapt more readily to different situations (Goleman, 1998). Thus, 

EI is seen as a crucial factor when individuals face rapid changes in the organizational 

environment (Vakola et al., 2004). By understanding their own emotions and others, 

individuals can communicate ideas and goals more effectively (Vakola, 2013), enabling 

organizations to better prepare for competitive situations (Hosein & Yousefi, 2012). The 

relationship between EI and WFA is also influenced by how the organization provides JA to 

employees. JA allows individuals to express genuine emotions and encourages proactive 

behavior (Cooper & Sawaf, 1997). Conversely, individuals who are not given JA are limited 

in expressing emotions due to their fear of a response from supervisors or superiors. 

Therefore, JA is needed to develop fundamental emotional reactions and encourage 

employees to take the initiative in responding to environmental changes. 

Based on theoretical studies, WFA is considered as a factor that startup employees must 

have when facing dynamic changes (Sherehiy & Karwowski, 2014). Employees with a high 

WFA are likely to see a change as a challenge and take positive opportunities from the change 

(Zhang & Sharifi, 2000). Internal factors such as PE and EI are known to increase WFA 

(Hosein & Yousefi, 2012; Muduli & Pandya, 2018). In addition, external factors such as JA 

is considered to influence the role of PE and EI on WFA (Abraham, 2000; Scott & Bruce, 

1994). This study aims to determine the role of PE and EI on WFA in all subjects and to 

examine the role of PE and EI on WFA based on JA type, especially in startup companies. In 

the future, this research can be used as a reference for startup companies that want to develop 

WFA based on individual internal and external factor.  

Existing research on WFA has predominantly explored PE and EI separately, with 

limited attention to their combined effects. This study investigates the gap by integrating PE 

& EI into WFA. Additionally, while prior studies have primarily treated WFA as a general 

trait, this study considers how different levels of JA shape these relationships. Furthermore, 

unlike most studies that are conducted on WFA in the manufacturing sector, this study 

extends the investigation to startup companies, offering new insight into WFA within 

dynamic work environments.  

Based on previous theoretical studies, the hypothesis is stated as follows: (1) PE and EI 

impact on WFA across subjects; (2) PE and EI impact on WFA for subjects with low JA; (3) 

PE and EI impact on WFA for subjects with medium JA; and (4) PE and EI impact on WFA 

for subjects with high JA 

Method 

This research method utilized a quantitative approach by distributing surveys through the 
Google Form application. In this research, PE and EI were considered predictor variables that 
positively influence the criterion variable WFA. Meanwhile, JA was used as a grouping 
variable, affecting the impact of PE and EI on WFA. The JA variables were categorized into 
low, medium, and high levels.  

 



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Participants 

The study's population comprised startup employees actively working for the company. A 
purposive sampling technique was utilized, focusing on employees with specific 
characteristics: those working at startups for 0 to 5 years, involved in technology services, 
exhibiting a dynamic organizational culture, having completed their probation period, and 
aged between 20 and 35. It has been noted that most young employees in this age prefer 
working at startups due to the opportunities for career growth, risk-taking culture, and high 
levels of innovation that appeal to young employees (Ouimet & Zarutskie, 2014). 

Table 1 

Characteristics of the Research Subject 

Category
 

Low JA (%) 

N=30 

Medium JA (%) 

N=114 

High JA (%) 

N=36 

Total (%) 

N=180 

Gender 

Man 61.5% 57.9% 77.8% 61% 

Woman 38.5% 42.1% 22.2% 39% 

Employee Status 

Full Time 90% 86% 88.9% 87% 

Part Time 3.3% 7.9% 5.6% 7% 

Freelance 6.7% 6.1% 5.6% 6% 

Startup Type 

TO 13.3% 19.3% 19.4% 19% 

E-Commerce 10% 14% 2.8% 11% 

Service 23.3% 28.1% 33.3% 28% 

Education 10% 12.3% 13.9% 12% 

Tourism 16.7% 5.3% 11.1% 8% 

Other 26.7% 21.1% 19.4% 22% 

Length of work (years) 

0 – 1 46.7% 61.4% 66.7% 60% 

1 – 2 33.3% 22.8% 25% 25% 

2 – 3 3.3% 12.3% 2.8% 9% 

3 – 4 6.7% 2.6% 5.6% 4% 

>4 10% 0.9% 0% 2% 

Note: % = percentage; JA = Job Autonomy 

The total number of subjects in this research is 180 employees who are currently 

working in a startup companies. The sample size was determined based on the 

recommendations of Hair et al. (2010) who indicated that the minimum required sample size 

for regression analysis depends on the number of independent variables. They stated that each 

independent variable requires a minimum total sample of 15 to 20 subjects. Therefore, the 

inclusion of 180 subjects was appropriate for this research. The full characteristics of the 

subject can be seen in Table 1 and Table 2 

Table 2  

Advanced Characteristics of Research Subjects 

 

 
 

 

Note: R = average; SD = Standard deviation; JA = Job Autonomy; WFA = Workforce Agility; PE = 

Psychological Empowerment; EI = Emotional Intelligence 

 

Variable All Data       Low JA Medium JA      High JA 

R SD Distance R SD R SD R SD 

WFA 121.53 15.49 88-161 108.93 12.65 120.36 12.45 135.75 15.61 

PE 49.29 4.67 35-60 44.63 4.57 48.43 4.88 55.88 4.38 

EI 38.77 5.92 28-52 36.90 3.23 38.32 3.95 41.72 6.30 

 



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Instruments 

 

The WFA scale in this study utilizes a version adapted by the Mind, Brain & Behavior 

Laboratory at the Faculty of Psychology, Universitas Gadjah Mada. This scale consists of 23 

items reflecting proactivity, adaptability, and resilience. The WFA scale's validity is based on 

the content validity of Aiken V, which has a threshold value of 0.63 (Aiken, 1985). The test 

results indicate that the Aiken V values range from 0.75 to 0.97 demonstrating validity. The 

WFA scale was administered to 60 subjects with characteristics similar to the participants. 

The results show that the reliability of Cronbach’s Alpha is 0.89, indicating it is reliable or 

consistent (Gudmundsson, 2009). This scale is assessed using a 7-point Likert scale, ranging 

from 1 (never) to 7 (always). 

The scale used to measure PE is based on Spreitzer (1995) which was adapted by Nastiti 

(2015). This scale consists of 12 items that represent four aspects: meaning, competence, self-

determination, and impact. The validity of the PE scale is determined using Aiken V content 

validity, with a minimum value of 0.63 (Aiken, 1985). Test results indicate that the Aiken V 

value for the PE scale ranges from 0.79 to 1.00, which is considered valid. The PE scale was 

administered to 60 subjects with characteristics similar to the participants. The results show 

that the reliability, as measured by Cronbach's Alpha, is 0.92, which is regarded as reliable or 

consistent (Gudmundsson, 2009). Responses on this scale are evaluated using a 5-point scale 

that ranges from 1 (very inappropriate) to 5 (very appropriate). 

The scale used to measure EI refers to Goleman et al. (2007) adapted by Santyafatni 

(2018). This scale consists of 13 items representing five aspects: self-awareness, motivation, 

self-regulation, empathy, and relationship management or social skills. The validity of the EI 

scale utilizes Aiken V content with a value threshold of 0.63 (Aiken, 1985). The test results 

show that the Aiken V value on the EI scale moves from 0.76 – 0.84, which is considered 

valid. The EI scale was tested on 60 subjects with the same characteristics as the study 

subjects. The results show that the reliability of Cronbach Alpha is 0.70, which is considered 

reliable or consistent (Gudmundsson, 2009). The response in this scale is measured using a 

4-point scale with a range of 1 (very inappropriate) to 4 (very appropriate).  

The scale for measuring JA is based on Breaugh (1985) and was adapted by Saragih 

(2011). The JA scale includes 9 items that represent three aspects: work methods, work 

scheduling, and work criteria. Saragih (2011) stated that the JA scale has satisfactory 

goodness fit indices for the context of workers in the industrial field. Based on the CFA 

results, this scale has an RMSEA of 0.00, a CFI of 1.00, and a TLI of 1.03. The value indicates 

that this scale has been constructively validated. The JA scale was tested on 60 subjects with 

the same characteristics as the study subjects. The results show that the reliability of Cronbach 

Alpha is 0.81, which is considered reliable or consistent (Gudmundsson, 2009). Responses 

on this scale were measured using a 7-point scale ranging from 1 strongly disagree to 7 

strongly agree. 

Data Analysis 

The data analysis used in this study was multiple linear regression to determine the role of 

PE and EI on WFA. Next, to assess the role of PE and EI on WFA within the JA category, 

the data analysis employed was multiple regression with multigroup. Before performing 

regression, this study tested assumptions: residual normality, multicollinearity and linearity. 

Statistical analysis was conducted using the Statistical Package for Social Science (SPSS) 

program version 25. 

 



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Results 

The categorization of research data is carried out using an empirical approach that uses 
references to subject data. The categorization used is by dividing the data into three levels 
according to (Azwar, 2011). The results of data categorization are listed in Table 3. 

Table 3 

Number of subjects based on data categorization of each variable 

Category Formula WFA PE EI JA 

Low X < M-1SD 26 20 21 30 

Medium M-1SD X < M+1SD 127 120 124 114 

High M+1SD X 27 40 35 36 

Note: X: sample raw score; M: average distribution in sample; SD: standard deviation; WFA = Workforce 
Agility; PE = Psychological Empowerment; EI = Emotional Intelligence; JA = Job Autonomy. 

The correlation matrix in this study is listed in Table 4. The results show that the EI 

positively correlated with the WFA variable of 0.53 (p<0.01). The PE positively correlated 

with the WFA variable of 0.67 (p<0.01), while the PE and EI simultaneously positively 

correlated with the WFA of 0.45 (p<0.01). 

Table 4 

Correlation Matrix of Predictor Variables to Criteria Variables  

Variable M SD 1 2 

WFA 121.53 15.49   

EI 38.77 4.67 0.53**  

PE 49.29 5.92 0.67** 0.45** 

Note: **significant with p<0.01; *significant with p<0.05; M=Mean; SD=Standard Deviation; WFA=Workforce 

Agility; PE=Psychological Empowerment; EI=Emotional Intelligence 
 

To answer hypothesis 1 in this study, the analysis used is multiple regression analysis, 

while to answer hypotheses 2 - 4, the analysis used is multiple regression analysis with 

multigroup. The results of the analysis are summarized in Table 5. 

Table 5  

Regression Analysis Results 

JA N EI p-value PE p-value R-Squared F df 

All Data 180  0.28** p< 0.01 0.54** p< 0.01 51.5% 93.8 2.18 

Low 30 0.42** p< 0.01 0.44** p< 0.01 47.4% 12.14   2.27 

Medium 114 0.28** p< 0.01 0.46** p< 0.01 35.3% 30.26 2.11 

High 36  0.30     p=  0.09       0.34   p=  0.06 31.6%   7.62   2.33 

Note: ** significant with p<0.01 ; * significant with p<0.05; PE=Psychological Empowerment; EI=Emotional 

Intelligence; JA=Job Autonomy 

Table 5, results from the multiple regression analysis indicated that variations in the PE 

and EI variables could account for 52% of the variations in the WFA variables across all 

subjects. Meanwhile, another 48% were influenced by other variables not included in this 

research. This study demonstrates that PE and EI significantly impact on WFA, with values 

of (F=9.38; p<0.01). Additionally, EI accounted for a role of 0.28 (p<0.01) and PE accounted 

for 0.54 (p<0.01) in relation to WFA. An increase of 1 unit in the standard deviation of EI 

will lead to an increase of 0.28 units in the standard deviation of the WFA score, while an 

increase of 1 unit in the standard deviation of PE will result in an increase of 0.54 units in the 



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Hasna Uzzakiyah et.al (Workforce agility in startup employees: The role of...)  

standard deviation of the WFA score. Therefore, the study's results support the first 

hypothesis, indicating the impact of PE and EI on WFA. 

Table 5 indicates that, for subjects with low JA, variations in the PE and EI variables 

accounted for 47% of the variations in the WFA variables, while the remaining 53% were 

influenced by factors not included in this research model. In the low JA category, both PE 

and EI significantly contribute to WFA with values (F= 12.14; p<0.01). Additionally, EI has 

a role of 0.42 (p<0.01), while PE's role is 0.44 (p<0.01) in relation to WFA. An increase of 

1 unit in standard deviation of EI will result in an increase of 0.42 units standard deviation 

of WFA score, while an increase of 1 standard deviation of PE will lead to an increase of 

0.44 units in the standard deviation of WFA score.  

Additionally, the analysis results indicated that both PE and EI significantly impacted 

on the moderate JA category. In the subject category with moderate JA, the variation in PE 

and EI variables explained 35% of the variation in WFA variables, while the remaining 65% 

was influenced by variables not included in this research model. In the medium JA category, 

PE and EI together play a significant role in WFA with values (F= 30.26; p< 0.01). 

Furthermore, EI has a role of 0.28 (p< 0.01) and PE of 0.46 (p<0.01) to WFA. That is, an 

increase of 1 standard deviation in EI will result in an increase of 0.28 units standard 

deviation of WFA score, while an increase of 1 standard deviation of PE will lead to an 

increase of 0.46 units in the standard deviation of WFA score. 

Meanwhile, the analysis results indicated that PE and EI did not significantly 

contribute to WFA in the high JA category. In addition to the hypothesis test, further analyses 

were conducted to determine the average differences of each variable across JA categories. 

Additional analyses performed using ANOVA analysis techniques are listed in Table 6. 

Table 6 

Summary of additional analyses of PE, EI and WFA variables from all JA categories 

Variable JA Category N Average F df P 

PE 

Low 30 44.63 51.15 2 p< 0.01 

Medium 114 48.44  177  

High 36 55.89    

EI 

Low 30 36.90 11.27 2 p< 0.01 

Medium 114 38.33  177  

High 36 41.72    

WFA 

Low 30 108.93 35.10 2 p< 0.01 

Medium 114 120.36  177  

High 36 135.75    

Table 6 presents analysis results showing that in general there are significant JA category 

differences (p<0.01) in PE variables (F= 51.15; p<0.01); EI variables (F= 11.27; p<0.01) 

and WFA variables (F= 35.10; p<0.01) where the high JA category has the highest value 

among other categories. 

 

Discussion 

This research examines the role of PE and EI to WFA based on JA level among employees 
working in startup companies in technology services. The majority of subjects involved in 
this study were male, worked full time, engaged in technological services and worked for 
less than one year. 



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The results found that there is a positive relationship between PE and WFA in all startup 

employees. Individuals with high PE tend to have high intrinsic motivation in doing work. 

High intrinsic motivation can make individuals feel empowered and able to make a major 

contribution to the organization. This perception is what keeps individuals motivated to 

contribute proactively and flexibly in the face of change without orders from superiors. 

Conversely, individuals with low PE feel less empowered and able to contribute to the 

organization, so initiative and proactive behavior do not naturally arise in individuals. 

The results of this study support the findings of several studies regarding the 

relationship between PE to WFA in employees both in the public and private sectors (Muduli 

& Pandya, 2018), in which intrinsic motivation in work can lead to proactive and resilient 

behavior (Thomas & Velthouse, 1990), and also intrinsically motivated individuals will do 

work without fixating on external factors, rather it is due to the internal impulse of the 

individual (Ryan & Deci, 2000). Thus, even though organizations undergo system changes, 

people with high intrinsic motivation still perform best in the work environment. 

PE becomes an important factor that needs to be developed to improve WFA, especially 

when startup companies face significant environmental changes. Significant changes can 

impact changes in organizational systems such as changes in working hours, technology 

systems (Gigauri, 2020), and salary reductions due to the recession (Estrada, 2020). This 

change will certainly affect employee well-being, so it impacts decreasing performance 

(Gigauri, 2020). Therefore, startups need to increase intrinsic motivation that can encourage 

individuals to do work activities because the work is meaningful to them. This satisfaction 

will later be rewarded internally for individuals, so they do not have to rely on external 

rewards to motivate them to work. 

Other findings in the study suggest that EI plays a positive role in WFA. The positive 

results of EI’s role in WFA can be explained in several ways. First, for startup workers, facing 

change has become a daily routine (Hamel & Välikangas, 2003). This change requires 

employees to be able to quickly adjust to existing changes and provide innovation to the 

company’s progress. These demands sometimes make some employees   depressed and 

stressed because it is not easy for them to work with several possibilities and uncertain 

situations. However, individuals with high EI tend to be able to understand their emotions, 

making it easier for them to manage stress, anxiety, and worry that arise when facing pressure. 

Second, when confronting change, startup companies need good teamwork, so that employees 

can respond to changes more effectively. Individuals with high EI tend to cooperate with 

colleagues, because they can respond appropriately to other people’s emotions and 

communicate ideas and goals effectively (Vakola, 2013). Thus, individuals with high EI can 

help organizations to be better prepared for competitive situations (Hosein & Yousefi, 2012). 

The third finding in this study revealed that PE and EI together play a significant role 

in WFA only in the low and medium JA categories. However, PE and EI did not significantly 

increase WFA in the high JA category. In addition, this study found that the results of the 

ANOVA test on the average variables PE, EI and WFA in each JA category showed 

significant differences. From these data, it shows that the high JA category has the highest 

average of PE, EI, and WFA compared to other categories. 

In the context of startup companies, PE and EI have insignificant roles in increasing 

WFA among employees with the high JA category can be caused by several things. 

Employees with high JA tend to have full control over the work (Nie et al., 2023). This allows 

them to make decisions regarding the work they do. PE involves feelings of control and 

influence over one’s work. Thus, employees with high levels of JA already have significant 

control in making decisions regarding their work, which is a major component of PE. 

Therefore, additional PE may not provide a significant control or influence for employees 



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with high JA. On the other hand, EI doesn’t play a significant role in increasing WFA. This 

is because employees with high JA, like CEOs, tend to have greater responsibilities than those 

with low and medium JA. They are responsible for making decisions and guiding 

organizations toward long-term objectives (Papadakis, 2006). This explanation demonstrates 

that employees with high JA need other skills to boost WFA rather than improving EI.  

However, this study has some limitations; specifically, it involves subjects who work 

in startup companies, which vary significantly in valuation levels in Indonesia. In fact, 

differences in valuation levels also influence variations in subject characteristics among 

startup companies. Additional research is necessary to identify the level of startup will be 

studied, ensuring that the results are more representative of specific types of startups. The 

results of this study indicated among employees with high JA, PE and EI did not influence 

WFA. Further research is anticipated to investigate other factors, such as strategic thinking, 

leadership, and the capability to forecast the market, which are likely to enhance agility in 

employees with high JA. 

Conclusion 

Psychological empowerment and emotional intelligent play a role in workforce agility in 
startup employees. Meanwhile, psychological empowerment and emotional intelligent play 
a role in workforce agility only in the low and medium job autonomy categories, while the 
high job autonomy category does not show a significant role of psychological empowerment 
and emotional intelligent in workforce agility. 

Declarations 

Author contribution. First author: idea conceptualization, review literature, data collection, 

and writing the article. Second author: guide the research framework, review and 

improve the manuscript. 

Funding statement. This research was conducted with independent funding from author. 

Conflict of interest. The authors declare no conflict of interest. 

Additional information. No additional information is available for this paper. 

References 

Abraham, R. (2000). The role of job control as a moderator of emotional dissonance and 

emotional intelligence–outcome relationships. The Journal of Psychology, 134(2), 

169–184. https://doi.org/10.1080/00223980009600860  

Afdi, Z., & Purwanggono, B. (2017). Designing a strategy based on the lean startup method 

to encourage the growth of technology-based startups in Indonesia. Industrial 

Engineering Online Journal, 6(4), 1–13. 

https://ejournal3.undip.ac.id/index.php/ieoj/article/view/20398  

Aiken, L. R. (1985). Three coefficients for analyzing the reliability and validity of ratings. 

Educational and Psychological Measurement, 45(1), 131–142. 

https://doi.org/10.1177/0013164485451012  

Alavi, S., Abd. Wahab, D., Muhamad, N., & Arbab Shirani, B. (2014). Organic structure 

and organisational learning as the main antecedents of workforce agility. International 

Journal of Production Research, 52(21), 6273–6295. 

https://doi.org/10.1080/00207543.2014.919420  

https://doi.org/10.1080/00223980009600860
https://ejournal3.undip.ac.id/index.php/ieoj/article/view/20398
https://doi.org/10.1177/0013164485451012
https://doi.org/10.1080/00207543.2014.919420


10   

               ISSN 2598-6368 (online) / ISSN 1693-7236 (print) 

  

Hasna Uzzakiyah et.al (Workforce agility in startup employees: The role of...) 

Alviani, D., Hilmiana, Widianto, S., & Muizu, W. O. Z. (2024). Workforce agility: A 

systematic literature review and research agenda. Frontiers in Psychology, 15. 

https://doi.org/10.3389/fpsyg.2024.1376399  

Azwar, S. (2011). Attitudes and behavior in: Human attitudes theory and measurement. 

Pustaka Pelajar. 

Beqiri, T. (2019). Empirical study on intrinsic motivation factors of employees in transition 

economies. International Journal of Economics and Business Administration, 7(4), 

307–319. https://doi.org/10.35808/ijeba/345  

Breaugh, J. A. (1985). The measurement of work autonomy. Human Relations, 38(6), 551–

570. https://doi.org/10.1177/001872678503800604  

CNN Indonesia. (2020, November 4). Pandemi Covid-19 ubah cara dan gaya 

berbisnis. CNN 

Indonesia. https://www.cnnindonesia.com/ekonomi/20201104090800-97-

565666/pandemi-covid-19-ubah-cara-dan-gaya-berbisnis 

Condry, J., & Chambers, J. (1978). Intrinsic motivation and the process of learning. In M. 

R. Lepper & D. Greene (Eds.), The hidden costs of reward: New perspectives on the 

psychology of human motivation (pp. 61–84). Erlbaum. 

Cooper, R. K., & Sawaf, A. (1997). Executive EQ: Emotional intelligence in business. Orion 

Business Books. 

Cornelis, F. C. P. N., & Febriansyah, H. (2023). The importance of new ways of working to 

influence workforce agility in the manufacturing sector for managing destructive 

situation. Asia Pacific Management and Business Application, 11(3), 263–282. 

https://doi.org/10.21776/ub.apmba.2023.011.03.1  

Elanthi, M. B., & Dhanabhakyam, M. (2021). Sustaining SMEs and entrepreneurial 

innovation in the Post-Covid-19 era. In Agile workforce a post pandemic revival plan 

for SMEs (pp. 1–18). https://doi.org/10.4018/978-1-7998-6632-9.ch001  

Estrada, M. A. R. (2020). Economic waves: The effect of the Wuhan Covid-19 on the world 

economy (2019-2020). SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3545758 

Gigauri, I. (2020). Effects of covid-19 on human resource management from the perspective 

of digitalization and work-life-balance. International Journal of Innovative 

Technologies in Economy, 4(31), 1–10. 

https://doi.org/10.31435/rsglobal_ijite/30092020/7148  

Goleman, D. (1998). Working with emotional intelligence. Bloomsbury. 

Goleman, D., Boyatzis, R., & McKee, A. (2007). The emotional leaders. Gramedia Pustaka 

Utama. 

Gudmundsson, E. (2009). Guidelines for translating and adapting psychological instruments. 

Nordic Psychology, 61(2), 29–45. https://doi.org/10.1027/1901-2276.61.2.29  

Gunasekaran, A. (1999). Enablers of total quality management implementation in 

manufacturing: A case study. Total Quality Management, 10(7), 987–996. 

https://doi.org/10.1080/0954412997172 

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis 

with readings (7th ed.). Prentice Hall International. 

Hamel, G., & Välikangas, L. (2003). The quest for resilience. Harvard Business Review, 

81(9), 52–131. https://pubmed.ncbi.nlm.nih.gov/12964393/  

https://doi.org/10.3389/fpsyg.2024.1376399
https://doi.org/10.35808/ijeba/345
https://doi.org/10.1177/001872678503800604
https://www.cnnindonesia.com/ekonomi/20201104090800-97-565666/pandemi-covid-19-ubah-cara-dan-gaya-berbisnis
https://www.cnnindonesia.com/ekonomi/20201104090800-97-565666/pandemi-covid-19-ubah-cara-dan-gaya-berbisnis
https://doi.org/10.21776/ub.apmba.2023.011.03.1
https://doi.org/10.4018/978-1-7998-6632-9.ch001
https://doi.org/10.31435/rsglobal_ijite/30092020/7148
https://doi.org/10.1027/1901-2276.61.2.29
https://pubmed.ncbi.nlm.nih.gov/12964393/


Humanitas: Indonesian Psychological Journal 11 

 

Hasna Uzzakiyah et.al (Workforce agility in startup employees: The role of...)  

Hosein, Z. Z., & Yousefi, A. (2012). The role of emotional intelligence on workforce agility 

in the workplace. International Journal of Psychological Studies, 4(3), 48–61. 

https://doi.org/10.5539/ijps.v4n3p48  

Kuckertz, A., Brändle, L., Gaudig, A., Hinderer, S., Morales Reyes, C. A., Prochotta, A., 

Steinbrink, K. M., & Berger, E. S. C. (2020). Startups in times of crisis – A rapid 

response to the Covid-19 pandemic. Journal of Business Venturing Insights, 13, 

e00169. https://doi.org/10.1016/j.jbvi.2020.e00169  

Muduli, A., & Pandya, G. (2018). Psychological empowerment and workforce agility. 

Psychological Studies, 63(3), 276–285. https://doi.org/10.1007/s12646-018-0456-8  

Nastiti, A. (2015). Job satisfaction in terms of psychological empowerment and 

organizational learning capability. Gadjah Mada University. 

Nie, T., Tian, M., Cai, M., & Yan, Q. (2023). Job autonomy and work meaning: Drivers of 

employee job-crafting behaviors in the VUCA times. Behavioral Sciences, 13(6), 493. 

https://doi.org/10.3390/bs13060493  

Olafsen, A. H., Halvari, H., Forest, J., & Deci, E. L. (2015). Show them the money? The role 

of pay, managerial need support, and justice in a self‐determination theory model of 

intrinsic work motivation. Scandinavian Journal of Psychology, 56(4), 447–457. 

https://doi.org/10.1111/sjop.12211  

Ouimet, P., & Zarutskie, R. (2014). Who works for startups? The relation between firm age, 

employee age, and growth. Journal of Financial Economics, 112(3), 386–407. 

https://doi.org/10.1016/j.jfineco.2014.03.003  

Papadakis, V. M. (2006). Do CEOs shape the process of making strategic decisions? 

Evidence from Greece. Management Decision, 44(3), 367–394. 

https://doi.org/10.1108/00251740610656269  

Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic 

motivation, social development, and well-being. American Psychologist, 55(1), 68–78. 

https://doi.org/10.1037/0003-066X.55.1.68  

Santyafatni, K. M. (2018). The role of social support and emotional intelligence on work-

life balance. Gadjah Mada University. 

Saragih, S. (2011). The effects of job autonomy on work outcomes: Self efficacy as an 

intervening variable. International Research Journal of Business Studies, 4(3), 203–

215. https://doi.org/10.21632/irjbs.4.3.203-215  

Scott, S. G., & Bruce, R. A. (1994). Determinants of innovative behavior: A path model of 

individual innovation in the workplace. Academy of Management Journal, 37(3), 580–

607. https://doi.org/10.2307/256701  

Sherehiy, B. (2008). Relationships between agility strategy, work organization and 

workforce agility. ProQuest. 

Sherehiy, B., & Karwowski, W. (2014). The relationship between work organization and 

workforce agility in small manufacturing enterprises. International Journal of 

Industrial Ergonomics, 44(3), 466–473. https://doi.org/10.1016/j.ergon.2014.01.002  

Singgih, R. P., & Sari, M. P. (2024). The urgency of agile leadership training to produce 

competitive startups in the Vuca era. Journal of Ilmiah Global Education, 5(2), 1162–

1169. https://doi.org/10.55681/jige.v5i2.2765  

Spreitzer, G. M. (1995). Psychological, empowerment in the workplace: Dimensions, 

measurement and validation. Academy of Management Journal, 38(5), 1442–1465. 

https://doi.org/10.2307/256865  

https://doi.org/10.5539/ijps.v4n3p48
https://doi.org/10.1016/j.jbvi.2020.e00169
https://doi.org/10.1007/s12646-018-0456-8
https://doi.org/10.3390/bs13060493
https://doi.org/10.1111/sjop.12211
https://doi.org/10.1016/j.jfineco.2014.03.003
https://doi.org/10.1108/00251740610656269
https://doi.org/10.1037/0003-066X.55.1.68
https://doi.org/10.21632/irjbs.4.3.203-215
https://doi.org/10.2307/256701
https://doi.org/10.1016/j.ergon.2014.01.002
https://doi.org/10.55681/jige.v5i2.2765
https://doi.org/10.2307/256865


12   

               ISSN 2598-6368 (online) / ISSN 1693-7236 (print) 

  

Hasna Uzzakiyah et.al (Workforce agility in startup employees: The role of...) 

Thomas, K. W., & Velthouse, B. A. (1990). Cognitive elements of empowerment: An 

“interpretive” model of Intrinsic task motivation. The Academy of Management Review, 

15(4), 666–681. https://doi.org/10.2307/258687  

Vakola, M. (2013). Multilevel readiness to organizational change: A conceptual approach. 

Journal of Change Management, 13(1), 96–109. 

https://doi.org/10.1080/14697017.2013.768436  

Vakola, M., Tsaousis, I., & Nikolaou, I. (2004). The role of emotional intelligence and 

personality variables on attitudes toward organisational change. Journal of Managerial 

Psychology, 19(2), 88–110. https://doi.org/10.1108/02683940410526082  

Varshney, D., & Varshney, N. K. (2020). Workforce agility and its links to emotional 

intelligence and workforce performance: A study of small entrepreneurial firms in 

India. Global Business and Organizational Excellence, 39(5), 35–45. 

https://doi.org/10.1002/joe.22012  

Wang, G., & Netemeyer, R. G. (2002). The effects of job autonomy, customer 

demandingness, and trait competitiveness on salesperson learning, self-efficacy, and 

performance. Journal of the Academy of Marketing Science, 30(3), 217–228. 

https://doi.org/10.1177/00970302030003003  

Youndt, M. A., Snell, S. A., Dean, JR., J. W., & Lepak, D. P. (1996). Human resource 

management, manufacturing strategy, and firm performance. Academy of Management 

Journal, 39(4), 836–866. https://doi.org/10.2307/256714  

Zhang, Z., & Sharifi, H. (2000). A methodology for achieving agility in manufacturing 

organisations. International Journal of Operations & Production Management, 20(4), 

496–513. https://doi.org/10.1108/01443570010314818  

  

https://doi.org/10.2307/258687
https://doi.org/10.1080/14697017.2013.768436
https://doi.org/10.1108/02683940410526082
https://doi.org/10.1002/joe.22012
https://doi.org/10.1177/00970302030003003
https://doi.org/10.2307/256714
https://doi.org/10.1108/01443570010314818

