INTRODUCTION
In 2019, the world community was shocked by the COVID-19
pandemic, which could infect almost all countries worldwide. This incident
affects countries to lock down. This is useful so as not to spread the COVID-19
disease and start limiting people's activities and only working at home.
The trend of working from home is starting to stick and is
almost used by many large companies. This phenomenon has become a
civilizational shift towards office operations. Previously, employees were
required to work in the office at a time determined by the company. A flexible
working arrangement (FWA) is an option that can be applied during the COVID-19
and post-COVID-19 pandemics.
Working Hours Survey recorded the responses from nearly
2,400 civil servants regarding their views on working hours and conditions and
the impact of the COVID-19 pandemic on their work lives (FDA, 2021). The survey
results show that 62% of employees choose to dress casually 1 day a week, 60%
work remotely, 54% work flexibly. This shows that the trend to work flexibly is
the most preferred choice besides casual clothes. This research also says that
83% of HR professionals predict that in the next five years, telecommuting will
become commonplace for various organizations. As many as 26% said that
productivity increased by telecommuting. As much as 5% said there was an
increase in employee attendance. This happened before the COVID-19 pandemic
showed that telecommuting had become an option for employees.
Flexible work arrangements positively affected
productivity because they were much more motivated because there was no direct
attachment from their superiors (Pandiangan, 2018).
Flexibility of working hours for female workers has a positive value on
productivity, which means that if the company applies the flexibility of
working hours, the productivity will be even better (Antiqka & Pradhanawati, 2017). Flexible work
arrangements positively influence employee performance or productivity with
high and dominating categories (Gunawan & Franksiska, 2020).
However, different from Boltz et al. (2020), flexibility does
not always increase productivity. Part-time workers under a flexible schedule
are statistically less productive than those with a regular full-time schedule. Rimadias (2019)
suggests that work flexibility does not affect perceived productivity. Kattenbach et al. (2010)
found that flexible work arrangements had a negative effect on employee
performance. The application of Work From Home (WFH) faces challenges because
apart from not all types of work can be done from home but also faced with
obstacles such as work tools, coordination, disturbances from within the home
such as housework taking care of children, problems network and so on (Waizenegger et al., 2020). Working in a
shared space with other householders causes distraction and difficulty focusing
on work tasks. These challenges pose a problem for some communities in dealing
with these trends. It is also supported by the results of the Effect of Salary,
Flexible Working Hours, and Work Stress on Employee Performance at Companies in
Batam City. Flexible working hours significantly
negatively affected employee performance (Fanda & Slamet, 2019). This means that
the implementation of flexible working hours provided by the company to
employees does not provide good benefits for the company.
Fadhila and Wicaksana (2020)
suggested that FWA, if applied in several cases, can be said to be effective
with responses from employees who feel happy because they can freely manage
work schedules. Several factors need special attention, namely, (1) gender
factor, namely the workload of female and male employees, which is still
considered burdensome to women; (2) factors for providing infrastructure and
technology; (3) leadership factors with their relationship as a means of
communication, coordination, and work patterns; (4) policy factors, where it is
necessary to have applicable rules so that employees can achieve their
performance; and (5) the factor of the type of work and position, where not all
can apply FWA. On the other hand, there are obstacles to the application of
FWA. Barriers that arise include (1) availability of workspace, technology
infrastructure, and increased costs of using technology; (2) difficulty in
determining the level of performance and productivity because there are still
constraints in terms of real-time; (3) the emergence of a cultural shock to the
use of technology, the responsibility to manage homework that can affect the
stress level of employees, as well as the presence of interference from family
members and can reduce concentration (4) the negative effect of FWA on the
mental psychology of employees.
According to Wibisono (2017), the
millennial generation is commonly referred to as generation Y, where this
generation was born between 1980-2000 or aged between 19 years to 39 years (Wibisono, 2017). Hidayahtullah
in Meilinda, (2019) mentions the characteristics of the
millennial generation, namely: 1) millennials trust user-generated content
(UGC) more than unidirectional information, 2) they prefer smartphones over
television, 3) they have social media, 4) they do not like reading
conventionally, 5) lack loyalty, but work effectively 6) conduct cashless
transactions, 7) master or understand technology, 8) can take advantage of
technology and information, 9) tend to be more lazy and consumptive. The
following are the characteristics and values of work by the millennial
generation according to Sukoco et al. (2020),
namely: 1) wanting a varied job and there is an opportunity to develop. 2) want
strong mentor support. 3) flexible work, adequate quality of work environment,
and work-life balance. 4) have a sense of optimism, focus on achieving
self-confidence, believe in moral and social values, respect diversity, work
together, and be pragmatic in solving problems.
METHOD
The research
method used by the researcher is a quantitative method used to examine the
population and sample through research instruments, as well as collect data and
then analyze it statistically. The type of research used is experimental
research to explain the causal relationship between one variable and another.
Furthermore, the causal research design was chosen to test the hypothesis about
the effect of one or several variables (independent variables) on other
variables (dependent variables) (Sugiyono, 2013).
According to Sugiyono (2013),
research variables are attributes, properties, or values of a person, object,
or activity that have variations set by researchers to be studied and then
drawn conclusions. There are four variables in this study, including:
1) Independent
Variable (X)
This variable is often referred to
as the independent variable that acts as a stimulus or predictor. The
independent variable in the study is Flexible working arrangements Carlson
et al. (2010) in Wicaksono (2019). Work flexibility is a formal policy
set by resource management or informal arrangements related to flexibility in a
company. Furthermore, Carlson defines schedule flexibility as a flexible work
arrangement which means choosing a place and time to work, formal or informal,
to facilitate employee policy.
2) Intervening
variable
This variable theoretically affects
the relationship between the independent and dependent variables into an
indirect relationship. This variable becomes an interrupting variable or is
placed between the independent and dependent variables. The intervening
variable in this study is job satisfaction. Robbins & Judge in (Fadli & Oktariani, 2021)
1) define
job satisfaction as "Job satisfaction describes a positive feeling about a
job, resulting from an evaluation of its characteristics." which is the
result of the evaluation of its characteristics.
3) Dependent
Variable (Y)
This variable is often referred to
as the dependent variable influenced or the result of the independent variable.
The dependent variables of this study are turnover intention and productivity.
a) According to Elmi (2018), the
turnover intention is the exit of employees due to their desires. Turnover
intention can be caused by several factors, including career opportunities,
salary, supervision, geography, and personal or family reasons.
b) Productivity, according to Panjaitan (2017), describes the relationship between the
number of goods that can be produced and the sources of labor, capital, and
others used to produce these results. Productivity measures how productive a
process is in producing a job.
The
population in this study were all private and non-private employees and the
millennial generation in Jakarta. This population is also based on the following
characteristics:
Table 1
Population
|
Characteristics
|
Indicators
|
|
Age
|
Less
than 20 years
|
|
20-25 years
|
|
26-30 years
|
|
31-35 years
|
|
36-40 years
|
|
More
than 40 years
|
|
Sex
|
Male
|
|
Female
|
|
Marital
status
|
Single
|
|
Married
|
|
Education
background
|
Secondary
School
|
|
Diploma/ Bachelor
|
|
Master/ doctoral
|
|
Work
duration
|
Less
than 1 year
|
|
1-5 years
|
|
6-10 years
|
|
11-15 years
|
|
16-20 years
|
|
More
than 20 years
|
|
Work
policy implementation
|
Work from home (WFH)
|
|
Work from office (WFO)
|
|
WFH and WFO
|
The sample used
in this study using purposive sampling was chosen because this technique
determines the sample with certain considerations. In contrast, in this study,
millennial generation employees in Jakarta are the considerations used as
reference.
For
the number of samples taken, because the current population is unknown, the
researcher decided to determine the number of samples using the Lemeshow (2013) formula, which is as follows:
n = 0.9604/0.01
n = 96.04
Note:
n: Total Sample
z: Z score at 95% confidence = 1.96
p: maximum estimate = 0.5
d: alpha (0.10) or sampling error
10%
Based
on this formula, it can be determined that the sample is 94 or rounded up to
100.
In
the data collection method, researchers use several data sources. More details
will be described as follows:
1)
Primary
data sources are obtained through questionnaires distributed to millennial
employees in Jakarta.
2)
Secondary
data sources in this study were obtained indirectly through books, journals,
and surveys conducted by official institutions whose discussions were directly
related to the variables studied.
Data
collection techniques were carried out through questionnaires distributed as
primary data sources. In contrast, this study used literature and document
review techniques as secondary data sources.
1) Questionnaire
The questionnaire is a data
collection technique that gives respondents a set of written statements to
answer (Sugiyono, 2013). Questionnaires
are used when there are large numbers of respondents and can reveal
confidential matters. The scale used by researchers in preparing the
questionnaire is a Likert. Sugiyono (2013)
argues that the Likert measures attitudes, opinions, and perceptions of a
person or group of people about social phenomena. The answer to each instrument
item has a positive gradation. There are five weighting categories in the
Likert as follows:
Table
2
Likert
|
Scale
|
Descriptions
|
Positive arguments
|
|
1
|
Strongly
agree
|
5
|
|
2
|
Agree
|
4
|
|
3
|
Uncertain
|
3
|
|
4
|
Disagree
|
2
|
|
5
|
Strongly
disagree
|
1
|
Source: Sugiyono (2013)
2) Documents
In this study, the collection of
supporting data sources through documents related to research variables and
matters related to research is carried out by reviewing literature books,
journals, the internet, and articles that provide real information regarding
the development of Flexible working arrangements (FWA).
Data Analysis
Method
1) Descriptive
Statistical Analysis
Descriptive statistical analysis is
statistics used to analyze data by describing or describing data that has been
collected as it is without intending to make conclusions that apply to the
general public or generalizations (Sugiyono, 2013). The statistics
used in this study are the mean, minimum, maximum, sum, standard deviation, and
others. The variables of this study include flexible working arrangements,
turnover intention, job satisfaction, and productivity.
2) Inferential
Statistical Analysis
The data analysis technique used in
this study is a structural equation model using the Smart-PLS program. This
SEM-PLS method can carry out three activities simultaneously, namely checking
the validity and reliability of the instrument (confirmatory factor analysis),
testing the relationship model between variables (path analysis), and getting a
suitable model for prediction (structural model and regression analysis) (Harahap, 2020). The use of PLS
is because this program is better able to describe more complex relationships
between variables.
a) Evaluation
of the Measurement Model (outer model)
The outer model is a model that
relates indicators to latent variables, which is also called a measurement
model (Harahap, 2020). Furthermore, the
outer model with reflective indicators will be measured through convergent
validity and discriminant validity, which will measure indicators for forming
latent constructs and composite reliability and Cronbach alpha.
1) Convergent validity: Reflective
indicators will be assessed based on the correlation between item-scored
component scores and construct scores. Testing the validity of each indicator
will be high if it correlates more than 0.70 with the construct to be measured (Ghazali & Latan, 2015).
Even so, the validity of the numbers 0.5 to 0.6 can still be considered
sufficient. However, if it is below 0.5, the indicator will be removed.
2) Discriminant validity: testing is
done by looking at the cross-loading between indicators and constructs. Another
way to be used is to compare the square root of the AVE (average variance
extracted). The recommended AVE value is greater than 0.50.
3) Composite reliability: This
reliability measurement can be done in two ways: Cronbach's Alpha and Composite
Reliability. The construct is considered to have good or consistent reliability
if all variables in the study have a reliability > 0.7 and Cronbach's Alpha
> 0.6.
b) Evaluation
of Structural Model (inner model)
A structural model test was
conducted to analyze the relationship between exogenous and endogenous
variables. This test consists of two stages: the determinant coefficient test R
Square (R2) and hypothesis testing.
1) Coefficient
of Determination Test (R2)
According
to Ghazali
and Latan (2015), The R2 test a
coefficient that explains how much the dependent variable can be explained by
the independent variables together. The greater the value of R2
indicates,
the better the model can explain the dependent variable. A value close to one
means that the independent variables provide almost all the information needed
to predict the variation of the dependent variable.
2) Structural
Model Validation with Goodness of Fit (GoF)
This
test was conducted to validate the combined performance of the measurement
model and the structural model that had been carried out previously. The GoF calculation is as follows:
i. 
The
criteria for the value of the GoF calculation are
0.10 (GoF small), 0.25 (GoF
medium), and 0.36 (GoF large).
In
addition, there is a Q-Square predictive relevance to measure how well the
value generated by the model is. Q-square value > 0 indicates that the model
has predictive relevance. In contrast, the value of Q-Square 0 indicates that
the model lacks predictive relevance. The formula for calculating Q-square is:
ii. Q2 = 1 – ( 1 – R12)
( 1 – R22 ) ... ( 1- Rp2 )
Where:
R12, R22 ... Rp2 is the R-square variable endogenous in
the equation model. The magnitude of Q2 has a value with a range of
0 < Q2 < 1, which means the model is getting better if the
value is getting closer to 1. The quantity of Q2is equivalent to the
coefficient of total determination in path analysis.
In addition, the coefficient of
determination in each dependent variable is evaluated by looking at the
percentage of variance that has been described. If the value of R2 is0.25
– 0.50, then the value of the coefficient of determination is weak, 0.50 – 0.75
means moderate, and 0.75 and above means substantial.
3) Hypothesis
Testing
Hypothesis testing using SmartPLS can be seen from the Path Coefficient value,
namely the t-statistic value of the relationship between variables in the
study. The t-test using the formula or SmartPLS is
seen from the comparison between the t-test value and the value in the t table.
If P-Values > 0.05 or t count
< t table, Ho is accepted, and Ha is rejected. However, if P-Values <
0.05 or t count > t table, Ho is rejected, and Ha is accepted.
4) Direct
Effect Test between Variables
Test
the direct influence hypothesis can use the T-test. The t-test procedure used
is bootstrapping.
Bootstrapping
is used to see if there is a significant relationship between the observed
variables. The criteria for accepting or rejecting the hypothesis are that Ha
is accepted and Ho is rejected when the t-statistic shows > 1.96, and to reject
or accept the hypothesis using a probability value, and then Ha will be
accepted if the p-value <0.05.
RESULTS AND DISCUSSION
This study only focused on millennial employees who worked
flexibly in Jakarta. The total number of respondents was 117 respondents.
However, researchers will focus on millennial generation employees who have
worked flexibly and are domiciled in Jakarta. From 117 respondents, researchers
got 100 respondents according to the desired criteria: having worked flexibly,
domiciled in Jakarta, and in the millennial age range. Based on the results of
distributing questionnaires, 12 percent have worked in a compressed workweek,
have worked flexitime by 23 percent, have worked
remotely (WFH, WFA), which is 45 percent, has worked part-time by 7 percent,
the rest are 13 percent who work in combination. Percent. Based on the results
of distributing questionnaires to 100 employee respondents who work flexibly,
it can be seen that the description of the characteristics of respondents and
researchers grouping based on age, gender, marital status, years of service,
and last education of respondents is as follows:
Table
3
Number
of Respondents Based on Gender
|
Gender
|
Total
|
Percentage
|
|
Male
|
42
|
42%
|
|
Female
|
58
|
58%
|
|
Total
|
100
|
100%
|
Source: Primary Data by the researcher 2022
Based on table 3,
it can be seen that the employees surveyed who have worked flexibly in Jakarta
can be classified into 4 groups because the researcher only uses the population
of the millennial generation, namely the range of years of birth from 1984 to
1991. The survey can be classified as the age of 20-30 years, which is 66%,
30-41 years old, as much as 30%, and 41-50 years old, as much as 4%. Here are
the detailed data:
Table 4
Number of Respondents by Age
|
Age
of Respondents
|
Total
|
Percentage
|
|
20 - 30 years
|
66
|
66%
|
|
31 - 40 years
|
34
|
34%
|
|
Total
|
100
|
100%
|
Source: Primary Data by researchers 2022
Based on table
4, it can be seen that the surveyed employees who have worked flexibly in
Jakarta can be classified into There are two marital statuses, namely single
and married. The number of respondents whose status is single is 58%, and the
number of respondents with married status is 42%.
Table
5
Number
of Respondents Based on Marital Status
|
Status
|
Total
|
Percentage
|
|
Single
|
58
|
58%
|
|
Married
|
42
|
42%
|
|
Total
|
100
|
100%
|
Source: Primary Data obtained by researchers 2022
Based on table 5,
it can be seen that the surveyed employees who have worked flexibly in Jakarta
can be classified into four. Namely, the number of Diploma respondents was 17%,
undergraduate respondents were 53%, master respondents were 5%, and SMA or
equivalent was 25%.
Table 6
Number of Respondents Based on Last
|
Education
background
|
Total
|
Percentage
|
|
Diploma
|
17
|
17%
|
|
Master
|
5
|
5%
|
|
Bachelor
|
53
|
53%
|
|
High School or equivalent
|
25
|
25%
|
|
Total
|
100
|
100%
|
Source: Primary Data obtained by researchers 2022
Based on table 6,
it can be seen that respondents based on length of work can be divided into 4
classifications. Working less than 1 year as many as 16%, working 1-5 years as
much as 61%, 6-10 years as much as 14% and more than 10 years as many as 9% of
the total respondents.
Table 7
Length of work in the company
|
Work
duration
|
Total
|
Percentage
|
|
1 - 5 years
|
61
|
61%
|
|
6 - 10 years
|
14
|
14%
|
|
Less than 1 year
|
16
|
16%
|
|
more than 10 years
|
9
|
9%
|
|
Total
|
100
|
100%
|
Source: Primary Data by researchers 2022
Validity
testing is carried out through two stages, namely testing, convergent validity,
and discriminant validity.
1. Convergent
Validity
The results of the validation test
are shown in the following figures and tables:
Furthermore, a more detailed discussion of the
hypothesis will be described in the narrative below:
1. Hypothesis 1: Flexible working arrangement has a
significant positive effect on productivity.
Based on the
hypothesis test results shown in table 13, it is known that the statistical t
value of the flexible working arrangement has a significant positive effect on
productivity is 6609, which is greater than the value of t table = 1.67.
Likewise, the P-values of 0.000, which is smaller than = 0.05. The coefficient
is positive 0.584, which means that the flexible working arrangement
significantly positively affects the productivity variable of 58.4%. So it can
be said that the hypothesis statement H1, which reads "flexible working
arrangement has a significant positive effect on productivity," is
accepted.
2. Hypothesis 2: Flexible working arrangements
significantly positively affect job satisfaction.
Based on the
hypothesis test results shown in table 13, it is known that the t-statistical
value of the effect of flexible working arrangement on work is 4.223, which is
greater than the value of t table = 1.67. Likewise, the P-values of 0.000,
which is smaller than = 0.05. The coefficient is positive at 0.435, which means
that the flexible working arrangement significantly positively affects the job
satisfaction variable by 43.5%. So it can be said that the hypothesis statement
H2, which reads "flexible working arrangement has a significant positive
effect on job satisfaction," is accepted.
3. Hypothesis 3: Flexible working arrangement
significantly negatively affects turnover intention.
Based on the
hypothesis test results shown in table 13, it is known that the statistical
t-value for the effect of flexible working arrangements on turnover intention
is 2.217, which is greater than the t-table value = 1.67. Likewise, the
P-values of 0.027, which is greater than = 0.05. The coefficient is positive at
0.255, which means that the flexible working arrangement significantly
positively affects the turnover intention of 25.5%. So it can be said that the
hypothesis statement H3, which reads "flexible working arrangement has a
significant negative effect on turnover intention," is rejected.
4. Hypothesis 4: Job satisfaction has a significant
positive effect on productivity.
Based on the results
of the hypothesis test shown in table 13, it is known that the statistical t
value on the effect of job satisfaction on productivity is 2,745, which is
greater than the value of t table = 1.67. Likewise, P-values of 0.006, which is
greater than = 0.05. The coefficient is positive at 0.236, which means that job
satisfaction has a significant positive effect on the productivity variable of
23.6%. So it can be said that the hypothesis statement H4, which reads
"Job satisfaction has a significant negative effect on productivity,"
is accepted.
5. Hypothesis 5: Job satisfaction has a significant
negative effect on turnover intention.
Based on the results
of the hypothesis test shown in table 13, it is known that the statistical t
value on the effect of job satisfaction on turnover intention is 1.614, which
is smaller than the value of t table = 1.67. Likewise, the P-values of 0.107,
which is greater than = 0.05. The coefficient is positive at 0.174, which means
that job satisfaction positively affects the turnover intention of 17.4%. So it
can be said that the hypothesis statement H5, which reads "job
satisfaction has a significant negative effect on turnover intention," is
rejected.
6. Hypothesis 6: Flexible working arrangements
significantly positively affect productivity through job satisfaction.
Based on the
hypothesis test results shown in table 13, it is known that the statistical t
value of the effect of flexible working arrangement on productivity through job
satisfaction is 2,386, which is greater than the t table value = 1.67.
Likewise, the P-values of 0.017 is smaller than = 0.05. The coefficient is
positive at 0.103, which means that the flexible working arrangement significantly
positively affects productivity through job satisfaction of 10.3%. So it can be
said that the hypothesis statement H6, which reads "flexible working
arrangement has a significant positive effect on productivity through job
satisfaction," is accepted.
7. Hypothesis 7: Flexible working arrangement
significantly negatively affects turnover intention through job satisfaction.
Based on the
hypothesis test results shown in table 13, it is known that the statistical t
value on the effect of job satisfaction on turnover intention through
productivity is 1,451, which is smaller than the value of t table = 1.67.
Likewise, the P-values of 0.147, which is greater than = 0.05. The coefficient
is positive at 0.075, which means that the flexible working arrangement positively
affects turnover intention through job satisfaction of 7.5%. So it can be said
that the hypothesis statement H7, which reads "flexible working
arrangement has a significant negative effect on turnover intention through job
satisfaction," is rejected.
Based on the results of hypothesis testing that have
been carried out, it can be explained as follows:
1. Effect of Flexible Working Arrangement on Productivity
Hypothesis 1 in this
study states that flexible working arrangement (FWA) has a significant positive
effect on productivity, and this hypothesis is accepted. The acceptance of this
hypothesis is in line with the results of previous research conducted by In a
journal (Pandiangan, 2018). It was found that
a flexible work arrangement positively affected productivity because they were
much more motivated. After all, there was no direct attachment from their
superiors. Flexibility of working hours
for female workers has a positive value on productivity, which means that if
the company applies the flexibility of working hours, the productivity will be
even better (Antiqka & Pradhanawati, 2017). According to (Gunawan & Franksiska, 2020),
flexible work arrangements positively influence the performance of employees
with high and dominating categories.
Furthermore, this
study also states that having FWA can make employees work better because they
can manage their working hours. In addition, the freer factor without
superiors' orders makes employees free to increase their work productivity.
2. Effect of Flexible Working Arrangement on Job
Satisfaction
Hypothesis 2 in this
study states that flexible working arrangements significantly positively affect
job satisfaction, and this hypothesis is accepted. The acceptance of this
hypothesis is in line with the results of the journal (Aziz-Ur-Rehman & Siddiqui, 2019)
that flexible work arrangements significantly impact the work-life balance and
job satisfaction of employees at Karachi State University Pakistan. Although
flexible arrangements have been associated with other constructs such as
productivity, organizational commitment, intention to leave work, or job
involvement, it is shown that these effects are strong and have a positive
relationship. Thus, work-life balance is a full mediator between flexible work
arrangements and job satisfaction. The journal includes flexible work
arrangements, work-life balance, job satisfaction, and employee loyalty (Stefanie et al., 2020). Flexible working
hours affect job satisfaction because respondents have a result orientation and
encourage communication with others and workload variations. Rimadias (2019)
say that teleworking is a strategy to overcome excessive workloads and be free
from fixed and temporal work schedules, which strengthens other flexible
performance outcomes in the company. Work flexibility is the ability of
employees to control the duration and time of work and the work location
provided by the company (Shagvaliyeva & Yazdanifard, 2014).
Generation Y or
millennials emphasize the benefits of FWA, such as increased work efficiency,
stress reduction, positive health effects, and positive health impacts.
Furthermore, in this study, the freedom factor without direct orders from
superiors influences their job satisfaction. Nakrošienė et al. (2019)
revealed that working from home can hone employees' time planning skills,
helping them spend more time being close to their families. A study by Beauregard
Mallett et al. (2020)
shows that 75% of employees who implement Work From Home believe that their
productivity is higher at home than in the office. A positive relationship
between working hours at home and work and life satisfaction (Mallett et al., 2020). There is a
negative relationship between fatigue and stress. This fact explains that
employees are likelier to feel happy if they implement a Work From Home work
system. Besides being able to manage their time easily, it is also closely
related to work productivity compared to working in an office. So it can be
said that, overall, for those who work from home, the results are mostly
positive, with employees and employers alike finding more or less equal
productivity than if work was completed in a more traditional setting (Beck & Hensher, 2020).
3. Effect of Flexible Working Arrangement on Turnover
Intention
Hypothesis 3 in the
study states that flexible working arrangement (FWA) has a significant positive
effect on turnover intention, and this hypothesis is rejected. The rejection of
this hypothesis is not in line with the results of previous studies conducted
by research Abednego et al. (2015)
which showed that schedule flexibility had a significant negative effect on
turnover intention. Is applied schedule flexibility, the higher the employee
satisfaction and the lower the level of turnover intention. The journal proves
that flexible working arrangements applied to an organization can reduce the
level of turnover intention. According to Almer and Kaplan (2002),
participants with flexible working hours will have a stronger desire to stay in
the company than participants who work standard working hours, and the conflict
experienced is also lower. However, in this study, an anomaly occurred in
previous studies. This is due to the place flexibility factor.
The most dominant
factor is that employees feel free because there is no direct order from their
superiors. This does not satisfy employees because the weakest factor is the
lack of freedom in choosing where to complete their work. This means that the
company provides freedom of time and duration of work to employees in
completing their work. However, the company does not provide freedom in various
places to complete their work. This is because, in this study, many employees
were already working in the office. After all, the pandemic had subsided. Millennial
generation employees carry out turnover intention because they feel that their
needs cannot be met at work, compensation that is not following
expectations, bad environment, and
unsatisfactory any assistance needed to complete the work (Ria et al., 2021).
4. The Effect of Job Satisfaction on Productivity
Hypothesis 4 in this
study states that job satisfaction has a significant positive effect on
productivity, and this hypothesis is accepted. The acceptance of this
hypothesis is in line with previous research Narpati et al. (2020)
from the discussion in his journal that job satisfaction has a significant
positive effect on work productivity. If there is an increase in job
satisfaction, there will be an increase in work productivity. Pratiwi and Widiyanto (2018)
explains that a person's high income or wages will make the workforce more
productive because the workforce is not disappointed with the efforts made to get the appropriate results. Robbins and Judge (2015)
explain that "job satisfaction is a positive feeling about work, resulting
from an evaluation of its characteristics." This means that someone with
high job satisfaction has positive feelings about work.
In contrast, someone
with a low level has negative feelings. A person with job satisfaction or a
happier worker is more likely to be productive (Robbins & Judge, 2015). Robbins'
statement is also supported by the results of research conducted by (Adiwinata, 2014), showing that job
satisfaction significantly affects employee productivity.
Furthermore, the
highest factor is that superiors provide clear directions so that employees
given tasks by their superiors can complete tasks according to the quantity and
quality determined by the organization.
5. The Effect of Job Satisfaction on Turnover Intention
Hypothesis 5 in this
study states that job satisfaction has a positive effect on turnover intention,
and this hypothesis is rejected. The rejection of this hypothesis is not in
line with the results of previous research. Evaluation of various alternative
jobs will ultimately result in turnover because individuals who choose to leave
the organization will expect more satisfactory results elsewhere (Yuda & Ardana, 2017). Job satisfaction
has an insignificant negative effect on turnover intention (Witasari, 2009). These results
prove that there are still many millennial employees in Jakarta who are not
satisfied with their work but are not yet willing to leave their jobs. These
satisfied employees never rule out the possibility of leaving work and looking
for work elsewhere. On the other hand, employees dissatisfied with their
current job do not immediately have the intention or desire to leave their
jobs.
Furthermore, this
study shows that the two variables between job satisfaction and turnover
intention cannot explain the relationship between variables. The results of
this study support research findings (Ramoo et al., 2013; Tarigan & Ariani, 2015), which state that
job satisfaction does not affect the intention to leave. This can be seen from
the data that some employees claim their job satisfaction has been fulfilled.
Some other employees feel quite comfortable and get enough results to work in
the company but still have the desire to move from the company. In addition,
according to Amin and Rahmiati (2018) in (Gayatri & Muttaqiyathun, 2020)
that the millennial generation seeking job satisfaction can be obtained not
only in one company, but personal satisfaction that can be obtained from
several companies dynamically continues to change so that can accelerate their
personal and career growth rapidly, where they are always looking for
opportunities to excel and are very concerned about professional development.
6. Effect of Flexible Working Arrangement on Productivity
through Job Satisfaction
Hypothesis 6 in this
study states that flexible working arrangements significantly positively affect
productivity through job satisfaction, and this hypothesis is accepted. This
study proves that FWA can partially mediate job satisfaction to productivity.
The acceptance of the hypothesis is in line with the journal (Nugroho & Hasanah, 2022). The results of
the analysis and discussion in the journal result that job satisfaction has a
positive and significant impact on employee work productivity when working from
home. Job satisfaction felt by employees can increase their work productivity.
The more satisfied employees are, the more productive employees will be.
Furthermore, in this study, the freedom felt by employees when working anywhere
makes them more satisfied at work and increases employee productivity.
7. Effect of Flexible Working Arrangement on Turnover
Intention through Job Satisfaction
Hypothesis 7 states
that flexible working arrangement has a positive effect on turnover intention
through job satisfaction, and this hypothesis is rejected. This hypothesis is
rejected because there is no evidence of the significance of job satisfaction
in mediating the effect of flexible working arrangements on turnover intention.
This is possible because the data collected cannot explain the mediating role
of job satisfaction.
This is possible because the respondents chosen by the
researchers are millennials in Jakarta, where they feel that their needs at
work cannot be fulfilled. There is no help needed in completing their work.
This is supported by Schaefer's research (2017) in (Putro et al., 2020)
which reveals that millennial generation employees carry out turnover intention
because they feel that their needs at work cannot be fulfilled, compensation
that is not in line with expectations, and bad environment, and the absence of
assistance.
CONCLUSION
A flexible working arrangement
(FWA) positively affects the employee productivity of millennials in Jakarta.
The factor without direct orders from superiors is the most dominant in
productivity. Employees feel free because they can express their current job.
Thus, it can bring up ideas, innovations, and ideas that can increase
productivity.
A flexible working arrangement
(FWA) significantly positively affects job satisfaction. The most important
factor of this influence is where the freedom factor in responding to job
satisfaction is the most decisive: working flexibly can have an effect. Freedom
without direct orders from superiors is the most dominant factor. Employees
feel satisfaction because there is no strict supervision by their superiors.
A flexible working arrangement
positively influences the turnover intention of the millennial generation in
Jakarta. FWA does not specify employees, reducing them not to leave their
current job. The most decisive factor is the freedom to choose the place of
work. However, employees are given the freedom to work. However, employees are
already thinking of looking for another job despite the office's policy of
giving them the freedom to work flexibly.
Job satisfaction has a positive
effect on productivity. If there is an increase in job satisfaction, there will
be an increase in work productivity. It seems that job satisfaction can have a
positive effect on productivity. Employee happiness will result in
productivity, and work quality and quantity can be increased.
Job satisfaction does not affect
turnover intention. Evaluation of various alternative jobs will ultimately
result in turnover because individuals who choose to leave the organization will
expect more satisfactory results elsewhere. Job satisfaction can reduce the
level of turnover intention in a company. However, it is possible that
employees who feel job satisfaction to leave work and look for work elsewhere
if they get a better job at this time. On the other hand, employees
dissatisfied with their current job do not immediately have the intention or
desire to leave their jobs. The co-worker factor is the main thing for the
dissatisfaction that occurs. Although other satisfactions have been met,
co-workers are a synergy in determining job satisfaction faced by employees.
A flexible working arrangement
(FWA) significantly positively affects productivity through job satisfaction.
FWA, through job satisfaction, can lead to higher productivity. The freedom
expected by millennials in Jakarta is to have freedom without direct orders
from superiors. This is an important factor so that there is no distraction
when employees are focused on doing a job. Job satisfaction will also be
increasingly influential in increasing productivity. The main factor is
leadership, where the leader can receive suggestions from subordinates to
achieve what employees want for their work.
Job satisfaction cannot mediate
the effect of a Flexible working arrangement on turnover intention. Researchers
feel that millennial generation employees in Jakarta cannot fulfill their needs
at work.
REFERENCES
Abednego, K. S., Gunawan, E. A., & Widjaja, D. C. (2015).
Pengaruh Schedule Flexibility Terhadap Turnover Intention Dengan Kepuasan Kerja
Sebagai Variabel Perantara Di Surabaya Plaza Hotel. Jurnal Hospitality Dan
Manajemen Jasa, 3(1), 12–25. Google Scholar
Adiwinata, I. (2014). Pengaruh Kepuasan Kerja dan Motivasi
Kerja terhadap Produktivitas Kerja Karyawan CV. Intaf Lumajang. Agora, 2(1),
22–30. Google Scholar
Almer, E. D., & Kaplan, S. E. (2002). The effects of
flexible work arrangements on stressors, burnout, and behavioral job outcomes
in public accounting. Behavioral Research in Accounting, 14(1),
1–34. Google Scholar
Antiqka, O. D., & Pradhanawati, A. (2017). Pengaruh Peran
Ganda, Fleksibilitas Jam Kerja dan Upah Teradap Produktivitas Kerja pada PT.
Holi Karya Sakti Semarang (Studi Kasus pada Buruh Perempuan Bagian Produksi). Jurnal
Ilmu Administrasi Bisnis, 6(2), 1–11. Google Scholar
Aziz-Ur-Rehman, M., & Siddiqui, D. A. (2019).
Relationship between flexible working arrangements and job satisfaction
mediated by work-life balance: Evidence from public sector universities employees
of Pakistan. Available at SSRN 3510918. Google Scholar
Beck, M. J., & Hensher, D. A. (2020). Insights into the
impact of COVID-19 on household travel and activities in Australia–The early
days under restrictions. Transport Policy, 96, 76–93.Elsevier
Boltz, M., Cockx, B., Diaz, A. M., & Salas, L. M. (2020).
How does flexible schedules affect workers’ productivity? A Field Experiment.
Google Scholar
Fadhila, A. A., & Wicaksana, L. (2020). Sistematik
Review: Fleksibel Working Arrangement (FWA) Sebagai Paradigma Baru Asn Di
Tengah Pandemi Covid-19. Spirit Publik: Jurnal Administrasi Publik, 15(2),
111–130. Google Scholar
Fadli, M., & Oktariani, O. (2021). Hubungan Antara
Kepuasan Kerja Dengan Stres Kerja Karyawan Di PT. Grand Shafa Nauli. Jurnal
Mahasiswa Fakultas Psikologi, 2(1), 23–35. Google Scholar
Fanda, N. M., & Slamet, M. R. (2019). Pengaruh Gaji, Jam
Kerja Fleksibel Dan Stres Kerja Terhadap Kinerja Karyawan Pada Perusahaan Di
Kota Batam. Journal of Applied Managerial Accounting, 3(1),
81–95. Google Scholar
FDA. (2021). Working Hours Survey: 97% want to continue
working remotely.
Gayatri, E., & Muttaqiyathun, A. (2020). Pengaruh Job
Insecurity, Beban Kerja, Kepuasan Kerja dan Komitmen Organisasi terhadap
Turnover Intention Karyawan Milenial. Proceeding of The URECOL, 77–85. Google Scholar
Ghazali, I., & Latan, H. (2015). Partial Least Squares;
Konsep, Tekhnik dan Aplikasi Menggunakan Program Smart PLS 3.0. Semarang:
Badan Penerbit Undip. Google Scholar
Gunawan, T. M. E., & Franksiska, R. (2020). Pengaruh
Pengaturan Kerja yang Fleksibel Terhadap Kinerja Karyawan dengan Work Life
Balance sebagai Variabel Mediasi. Procuratio: Jurnal Ilmiah Manajemen, 8(3),
308–321. Google Scholar
Harahap, L. K. (2020). Analisis SEM (Structural Equation
Modelling) dengan SMARTPLS (partial least square). Fakultas Sains Dan
Teknologi Uin Walisongo Semarang, 1(1). Google Scholar
Kattenbach, R., Demerouti, E., & Nachreiner, F. (2010).
Flexible working times: effects on employees’ exhaustion, work‐nonwork conflict
and job performance. Career Development International. Google Scholar
Mallett, O., Marks, A., & Skountridaki, L. (2020). Where
does work belong anymore? The implications of intensive homebased working. Gender
in Management: An International Journal. Google Scholar
Nakrošienė, A., Bučiūnienė, I., & Goštautaitė, B. (2019).
Working from home: characteristics and outcomes of telework. International
Journal of Manpower. Google Scholar
Narpati, B., Andrian, A., & Nursal, M. F. (2020). Pengaruh
Turnover Intention dan Kepuasan Kerja terhadap Produktivitas Kerja Sales
Promotion Girl (SPG) Matahari Department Store–Bekasi. Business Management
Analysis Journal (BMAJ), 3(2), 174–188. Google Scholar
Nugroho, R. S., & Hasanah, K. (2022). Kepuasan Dan
Produktivitas Kerja Karyawan Saat Bekerja Dari Rumah Studi Kasus Pada PT. Ims
Madiun. CAPITAL: Jurnal Ekonomi Dan Manajemen, 5(2), 127–142. Google Scholar
Pandiangan, H. (2018). Flexible Working Arrangement dan
Pengaruhnya Terhadap Work Life Balance pada Driver Layanan Jasa Transportasi
Online di Kota Yogyakarta. Yogyakarta: Tesis Universitas Sanata Dharma. Google Scholar
Pratiwi, D. W., & Widiyanto, W. (2018). Pengaruh Faktor
Internal dan Faktor Eksternal terhadap Produktivitas Kerja. Economic Education
Analysis Journal, 7(2), 654–670. Google Scholar
Putro, T. A. D., Ajeng, N., & Qomariyah, O. (2020). Stres
Kerja, Keterlibatan Kerja dan Intensi Turnover pada Generasi Milenial. Psikostudia:
Jurnal Psikologi, 9(2), 154–163. Google Scholar
Ramoo, V., Abdullah, K. L., & Piaw, C. Y. (2013). The
relationship between job satisfaction and intention to leave current employment
among registered nurses in a teaching hospital. Journal of Clinical Nursing,
22(21–22), 3141–3152. Google Scholar
Ria, D. P., Refachlis, M. I., AU, M. D., Supia, I., &
Hadi, C. (2021). Analisis Kualitas Hubungan Leader Member Di Indonesia. Google Scholar
Rimadias, S. (2019). Factors Affecting Perceived Productivity
On Teleworkers During Covid-19 Pandemic In Indonesia. Factors Affecting
Perceived Productivity On Teleworkers During Covid-19 Pandemic In Indonesia.
Google Scholar
Robbins, S. P., & Judge, T. A. (2015). Perilaku
Organisasi Edisi 16. Jakarta: Salemba Empat. Google Scholar
Shagvaliyeva, S., & Yazdanifard, R. (2014). Impact of
flexible working hours on work-life balance. American Journal of Industrial
and Business Management, 2014. Google Scholar
Stefanie, K., Suryani, E., & Maharani, A. (2020).
Flexible work arrangement, work life balance, kepuasan kerja, dan loyalitas
karyawan pada situasi Covid-19. Jurnal Ilmiah MEA (Manajemen, Ekonomi, &
Akuntansi), 4(3), 1725–1750. Google Scholar
Sugiyono. (2013). Metode Penelitian Kuantitatif,
Kualitatif dan R&D. Bandung: CV. Alfabeta. Google Scholar
Tarigan, V., & Ariani, D. W. (2015). Empirical study
relations job satisfaction, organizational commitment, and turnover intention. Advances
in Management and Applied Economics, 5(2), 21. Google Scholar
Waizenegger, L., McKenna, B., Cai, W., & Bendz, T.
(2020). An affordance perspective of team collaboration and enforced working
from home during COVID-19. European Journal of Information Systems, 29(4),
429–442. Google Scholar
Wicaksono, I. S. (2019). Pengaruh Kompensasi Dan
Fleksibilitas Kerja Driver Gojek Terhadap Kinerja Dengan Kepuasan Kerja Sebagai
Variabel Intervening. Google Scholar
Witasari, L. (2009). Analisis pengaruh kepuasan kerja dan
komitmen organisasional terhadap turnover intentions (studi empiris pada
Novotel Semarang). Universitas Diponegoro. Google Scholar
Yuda, I., & Ardana, I. K. (2017). Pengaruh kepuasan kerja
dan stres kerja terhadap turnover intention pada karyawan Hotel Holiday Inn
Express. E-Jurnal Manajemen Unud, 6(10), 5319–5347. Google Scholar
