93
1 INTRODUCTION
Information and communication technology
disruption has spread to all sectors, including
transportation [1]. One of the transportation sectors
facing the impact of this disruption is the maritime
transportation sector, such as transportation services at
ports [2]. The existing technological disruption takes
the form of digitalization and automation
systems[3][4]. Ports must adopt these technological
developments to enhance the effectiveness and
efficiency of their services. One example of the
adoption of digital innovations and automation
systems in ports is the implementation of the
Inaportnet system, which facilitates online ship
services, a single window service (National Single
Window), and the development of container terminal
operations systems [5][6]. This system simplifies the
ship service process, including document processing,
digital payment of services, and ship services. The
adoption of this technology across all ports in
Indonesia requires readiness in terms of human
resources, financial aspects, and the level of technology
utilization.
Indonesia, as an archipelagic country connected by
waterways, has many ports. Indonesia has 639 ports,
which are grouped into several categories based on the
scope of port services. The operation of seaports in
Indonesia is regulated by Regulation of the Minister of
Transportation of the Republic of Indonesia No. PM 50
of 2021 concerning the Operation of Seaports. This
regulation outlines the national port system, including
the roles, functions, types, and hierarchy of ports;
Port Authority Readiness Assessment: The Impact
of Disruption Technology Information in Indonesia
E. Wirza
Merchant Marine Polytechnic of West Sumatera, Padang Pariaman, Indonesia
ABSTRACT: Information technology disruption has spread to the global shipping industry, including its
application in ports. The purpose of this study is to measure the readiness of port management organizations in
Indonesia to face this disruption, as seen from the aspects of individual employees and financial aspects
influenced by the level of IT use. The study was conducted using a quantitative approach involving 65 port
managers through a survey, followed by model measurement using Partial Least Squares-Structural Equation
Modeling (PLS-SEM) and critical interval measurement. The results of the study indicate that individual readiness
and financial readiness have an effect on organizational readiness in facing IT disruption, with strong intervention
from the level of IT use within the organization. In addition to measuring the effects on organizational readiness,
this study categorizes the level of readiness of each variable of individual readiness, financial readiness, and
organizational readiness. The findings of this study indicate that although the organizational readiness of the Port
is categorized as good, it is still at the lower threshold. Therefore, it is necessary to improve readiness in several
indicators and variables that still have sufficient values, namely the employee competency readiness variable and
organizational financial readiness.
http://www.transnav.eu
the International Journal
on Marine Navigation
and Safety of Sea Transportation
Volume 20
Number 1
March 2026
DOI: 10.12716/1001.20.01.11
94
activities conducted at ports, both government and
commercial; port location determination; master port
plans (core port facilities and supporting facilities);
port development and expansion; and port operational
areas and areas of port interest. The hierarchy of ports
in Indonesia is divided into four levels: first, main ports
serve as the center of national and international trade
cargo handling activities, handle large cargo volumes,
and act as the main gateway for maritime
transportation. Second, feeder ports handle medium
volumes of domestic cargo, link feeder and main ports,
and facilitate interprovincial distribution. Third,
regional feeder ports handle domestic cargo with
limited volumes, serving as distribution hubs from
local ports to feeder or main ports, with regional
coverage. Fourth, feeder ports handle small cargo
volumes for local distribution, supporting regional
economies and intra-provincial or inter-district ferry
services. All ports within this hierarchy must provide
optimal services by implementing digital technology
and automation. Ports with high service levels, such as
main ports, are considered capable of adapting well to
the implementation of such technologies.
Infrastructure, human resources, and financial aspects
support this. However, these aspects have limitations
for ports at lower hierarchical levels. Therefore, this
port hierarchy highlights gaps in infrastructure,
human resources, and financial capabilities. Given this
gap, it is necessary to assess the readiness level of these
port hierarchies to optimize the success of adopting
digital innovations and automation systems in lower-
tier ports such as regional feeder ports and local ports.
The success of adopting digital innovations and
automation systems in ports is not only determined by
improvements in facilities and infrastructure but also
by competent human resources who are adaptable to
the latest technological developments. Previous
studies have only focused on the general readiness of
ports for implementing digital innovations [7]; [8].
Meanwhile, research on the readiness of port resources
for implementing digital innovations is still limited,
especially in ports that provide services at the regional
and local levels. However, the readiness of port human
resources is a crucial factor supporting the successful
implementation of digital technology and automation.
This study aims to measure the readiness of port
management organizations to adopt digital innovation
technology and automation in ports, particularly
regional and local feeder ports. Through this
measurement, this study will provide an overview of
the level of individual and financial readiness so that
steps can be developed to improve readiness from
various individual and financial aspects. This study is
expected to contribute to developing port human
resources, especially human resources in port
organizations that align with the needs and
characteristics of ports in Indonesia.
2 LITERATURE REVIEW
Readiness is one of the key factors in addressing the
changes that will occur within an organization. An
organization's efforts to reconfigure various aspects to
improve efficiency and organizational service activities
constitute organizational change. An organization's
readiness to accept change can be assessed based on the
readiness of the organization's human resources to
accept change and the readiness of the organization's
internal structure. The readiness of human resources is
critical because, without adequate resources, the
programs developed by the organization will not
succeed. This underscores the importance of the
quality of human resources as a key consideration for
organizational leaders in addressing upcoming
changes. While organizational change may be positive,
employees often respond negatively to change and
may resist efforts to implement it. One of the keys to
success in addressing change within an organization is
the readiness of the organization's human resources to
face such changes [9].
The readiness of human resources to face change
can be seen in the confidence of individuals to accept
change (mentally and behaviorally) [10]. Additionally,
individuals' efforts to enhance their knowledge and
personal skills to prepare for change instill positive
confidence in their ability to embrace such changes [11]
successfully. As agents of change, employees must
have the desire or willingness to enhance their
potential and evolve in a positive direction, which can
positively impact the organization's readiness to
change [12].
In addition to the quality of human resources in the
form of employees, the organization's readiness from
various aspects also determines the organization's
success in facing change [13]. The aspects within an
organization that serve as benchmarks for facing
change are the organization's commitment to change,
the readiness of organizational management, and the
availability of human resources within the
organization [14]. Human resources working in ports
must have technical skills and the ability to adapt to
organizational changes [15] [16].
Supporting factors, such as information and
communication technology infrastructure, must be
prepared to ensure that port authorities can implement
digital technology and automation. In this era of
information and communication technology
development, ICT has become a fundamental asset for
organizations to cope with change. By understanding
the benefits of each ICT development and knowing
how to operate ICT, organizations are expected to
improve their performance effectively and efficiently
in facing the era of autonomous ships, which utilize
ICT developments [17][18][19][20][21][22]. The
availability of facilities and infrastructure must
support the utilization of ICT. With the presence of
these two aspects, the ease of obtaining information
(information accessibility) becomes faster. It can be
accessed at any time, regardless of where the relevant
parties are located [23]. Another important aspect that
organizations must prepare for when facing changes is
the funding required to reorganize the organization.
This financial aspect is also one of the main factors
organizations must address to have the capital to
improve [24]. This means improving efficiency and
providing higher-quality services at lower costs
[25][26].
95
3 MATERIALS AND METHODS
This study uses a quantitative questionnaire as the data
collection tool. The population of this study is
employees of the port authority offices in Indonesia.
The research sample was taken using random
sampling techniques with 65 respondents. The
questionnaire used in this study consists of two parts.
The first part contains information about the
respondents' demographics, such as age, gender,
education, length of service, and type of work. The
second part contains questions about individual and
organizational readiness and organizational
performance. The variables measured in this study
include the readiness of resources and organizations to
deal with change. The conceptual framework is shown
in Figure 1.
Figure 1. Conceptual Framework
Model testing was conducted using SMART-PLS.
This method was used to determine the influence of
each variable, namely employee mental readiness,
employee competency readiness, employees'
willingness to change and develop in line with
technological developments, and the financial
readiness of port authorities about the organizational
readiness of port authorities to implement digital
innovations that will support the operation of port
automation systems, with the intervention variable
being the level of information and communication
technology use in port authorities. In the next stage, the
data will be analyzed using descriptive statistical
analysis with a class interval approach for each
variable to measure and categorize the readiness
values of each variable. The interval values are
determined using the following formula:
:
,
highesttotal score lowesttotal score
Valueinterval range
numberof statement criteria
−
With the readiness value criteria for each variable as
follows, Table 2.
Table 2. Readiness Level Category
Category
Not Ready
Very less
Less
Enough
Good
Very good
The research results will be presented as tables,
graphs, and descriptive analysis. The research results
provide an overview of the characteristics of
respondents and the relationship between variables
and organizational readiness to face changes resulting
from the impact of digital innovation and automation
in ports.
4 RESULTS
4.1 Respondent Characteristics
This questionnaire was distributed online to port
authorities in Indonesia, with each office represented
by one respondent, yielding 65 respondents with the
following characteristics in Table 3.
Based on Table 3, 55% of respondents are of
productive/working age, with 45% having a bachelor's
degree and 66% working in technical jobs or jobs that
provide technical port services to service users. This
supports the research objective of focusing on workers
who work directly in the field on serving ships and
providing technical services at the port. Regarding
work experience at the port, 49% of respondents have
less than five years of experience.
Table 3. Respondent Characteristic
Variable
Classification
Frequency (%)
Gender
Male
49%
Female
51%
Ages
> 55 years
9%
46-55 years
25%
36-45 years
22%
25-35 years
35%
< 25 years
9%
Education
Senior High School
25%
Diploma
15%
Bachelor degree
45%
Graduate degree
15%
Doctoral/PhD degree
0%
Position
Technical jobs
66%
administration jobs
34%
Experience
< 05 years
49%
6-10 years
5%
11-15 years
9%
15-20 years
15%
> 20 years
22%
4.2 Evaluation of Measurement Model
Figure 2. Measurement Model
96
The outer model was used to test the validity and
reliability of the indicators used for each variable.
Figure 2 shows that all indicators have factor loadings
above 0.7, indicating good convergent validity and that
the research instrument has measured the construct
consistently and accurately. Path estimation results
show that competency readiness significantly
influences the level of IT use (0.141) and organizational
readiness (0.124). On the other hand, mental readiness
significantly affects the level of IT use (0.186) and
organizational readiness (0.100). Willingness to change
significantly affects the level of IT use (0.226) and
organizational readiness (0.015).
Meanwhile, financial readiness significantly
influences the level of IT use (0.438) and organizational
readiness (0.107). This means that mental readiness,
competency readiness, willingness to change, and
financial readiness can serve as benchmarks for
organizational readiness in facing digital innovation
and automation systems. Meanwhile, the intervention
pathway between IT usage level and organizational
readiness is 0.530. This indicates that mental readiness,
competency readiness, willingness to change, and
financial readiness in the effective use of IT can
enhance an organization's readiness to address digital
innovation and port automation systems. The
relatively high coefficient value indicates that IT usage-
related interventions significantly impact
organizational readiness.
Instrument testing was conducted using convergent
validity and composite reliability methods. The
convergent validity of the measurement model showed
that the measurement instruments could measure the
variables indicated by their construct scores/factor
loading values, with the criterion of factor loading
values for each instrument > 0,7. Based on data
processing, organizational readiness yielded one
invalid instrument, namely G5, which must be
eliminated from the model. Subsequently, the factor
loadings of all instruments on all variables were
deemed valid. After conducting construct validity
testing, the next step was construct reliability testing,
which was measured using composite reliability (CR)
for each indicator block. Hair (2014) states that the
composite reliability coefficient or average variance
extracted (AVE) value must be greater than 0,7. Table 4
shows that all variables' composite reliability
coefficient or average variance extracted (AVE) value
is above 0.7. This indicates that all constructs in the
estimation model meet the validity standards and
demonstrate good internal consistency.
The next test is variable validity testing using the
Fornell-Larcker Criterion test method. This test shows
the validity of variables with a greater correlation than
the correlation between different variables. Table 5
shows that the values for the constructs of competency
readiness (0.91), financial readiness (0.9), level of IT use
(0.85), mental readiness (0.873), organizational
readiness (0.824), and willingness to change (0.828) are
all greater than their correlations with other constructs
in the model. These findings indicate that each
construct in the model has good discriminant validity,
meaning that each construct can better explain its
indicator variables than others.
Table 4. Measurement Model Assessment
Construct
Item
Code
Outer
Loading
Composite
reliability
(rho_a)
Composite
reliability
(rho_c)
Average
variance
extracted
(AVE)
Note
Competency
Readiness
CR1
0.8
0.947
0.96
0.828
Valid
CR2
0.892
Valid
CR3
0.961
Valid
CR4
0.95
Valid
CR5
0.936
Valid
Financial
Readiness
FR1
0.849
0.957
0.962
0.81
Valid
FR2
0.918
Valid
FR3
0.9
Valid
FR4
0.941
Valid
FR5
0.933
Valid
FR6
0.854
Valid
Level of Use of
IT
LoIT1
0.773
0.947
0.954
0.723
Valid
LoIT2
0.843
Valid
LoIT3
0.815
Valid
LoIT4
0.916
Valid
LoIT5
0.911
Valid
LoIT6
0.894
Valid
LoIT7
0.811
Valid
LoIT8
0.827
Valid
Mental
Readiness
MR1
0.855
0.965
0.962
0.763
Valid
MR2
0.922
Valid
MR3
0.838
Valid
MR4
0.94
Valid
MR5
0.951
Valid
MR6
0.93
Valid
MR7
0.732
Valid
MR8
0.793
Valid
Organizational
Readiness
G1
0.863
0.937
0.944
0.679
Valid
G2
0.798
Valid
G3
0.782
Valid
G4
0.833
Valid
G5
0.673
Drop
G6
0.8
Valid
G7
0.811
Valid
G8
0.875
Valid
G9
0.825
Valid
Willingness to
Change
WCD1
0.801
0.938
0.946
0.686
Valid
WCD2
0.741
Valid
WCD3
0.76
Valid
WCD4
0.828
Valid
WCD5
0.827
Valid
WCD6
0.898
Valid
WCD7
0.879
Valid
WCD8
0.878
Valid
Table 5. Fornell-Larcker Criterion
Competency
Readiness
Financial
Readiness
Level of Use
of IT
Mental
Readiness
Organizationa
l Readiness
Willingness to
Change
Competency Readiness
0.91
Financial Readiness
0.738
0.9
Level of Use of IT
0.736
0.77
0.85
Mental Readiness
0.727
0.596
0.704
0.873
Organizational Readiness
0.675
0.674
0.784
0.637
0.824
Willingness to Change
0.602
0.514
0.663
0.681
0.564
0.828
Based on the Fornell-Larcker criteria analysis, the
correlation values between latent variables are smaller
than the square root of AVE for each construct.
Therefore, the measurement model in this study meets
the discriminant validity criteria according to the
Fornell-Larcker approach, making it suitable for
further structural analysis.
97
Table 6. R-square
R-square
R-square adjusted
Level of Use of IT
0.722
0.704
Organizational Readiness
0.643
0.613
The R2 test examined the relationship between
exogenous and endogenous latent variables. Table 6
shows that the R2 value for Level of Use IT is 0.722
(strong), indicating that 72.2% of mental readiness,
competency readiness, financial readiness, and
willingness to change can influence the level of use of
IT. In comparison, other variables influence 27.8%.
Meanwhile, the influence of mental readiness,
competency readiness, financial readiness, willingness
to change, and IT use on organizational readiness is
0.643 (strong). This indicates that its exogenous
variables influence 64.3% of the organizational
readiness variable, and other variables influence 35.7%.
Based on the obtained values, this model is accurate,
relevant, and reliable in explaining the influence of
each construct on organizational readiness.
Table 7 shows that the size of the influence of
competency readiness on the level of IT use is 0.141 and
on organizational readiness is 0.199, which is classified
as a slight to moderate effect. The effect of financial
readiness on IT use is 0.438, and on organizational
readiness, it is 0.339, which is classified as a moderate
to high effect. The effect of mental readiness on the
level of IT use is 0.186 and on organizational readiness
is 0.199, which is classified as a slight to moderate
effect. The effect of willingness to change is 0.226 on the
level of IT use and 0.135 on organizational readiness,
which is classified as a slight to moderate effect. The
effect of IT usage level on organizational readiness is
0.53, classified as moderate to high. This indicates that
the level of IT usage affects the shaping of
organizational readiness.
Table 7. Total Effect
Level of Use of IT
Organizational Readiness
Competency Readiness
0.141
0.199
Financial Readiness
0.438
0.339
Level of Use of IT
0.53
Mental Readiness
0.186
0.199
Willingness to Change
0.226
0.135
4.3 Readiness Level Assessment
The readiness level assessment for each variable was
obtained from the interval assessment of each
Indicator, with the results shown in Table 8.
Table 8. Readiness level of Indicator
Variable
Indicator
Skor
Level
Mental
Readiness
Ability to adapt to upcoming changes
3.40
Good
Ability to collaborate with internal
and external parties
3.28
Good
Ability to complete tasks and
responsibilities
3.35
Good
Ability to accept any changes that
occur
3.28
Good
Ability to encourage mental, creative,
and innovative thinking in developing
one's abilities and potential in facing
changes
3.31
Good
Emotional ability in facing work
pressure and changes
3.29
Good
Ability to develop effective
communication methods
3.25
Good
Ability to deal with problems arising
from change.
3.26
Good
Competency
Readiness
Knowledge of the benefits of
autonomous ships for the global
shipping industry
3.20
Good
Knowledge of digital systems in port
services
3.20
Good
Skills in operating digital systems in
port services
3.15
Good
Knowledge of communication systems
in port services
3.11
Good
Skills in operating communication
systems in port services
3.09
Good
Knowledge of cybersecurity in port
service systems
2.89
Enough
Ability to prevent cybercrime in port
service systems
2.68
Enough
Knowledge and skills in managing
change
3.22
Good
Willingness to
change
Willingness to take opportunities for
self-development
3.29
Good
Ability to consider the risks of all
decisions and actions taken
3.29
Good
Ability to improve oneself in learning
to enhance one's potential
3.37
Good
Active participation in training to
enhance one's potential
3.22
Good
Ability to accept and cope with new
changes
3.28
Good
Ability to enhance one's potential
through learning to know new things
3.29
Good
Ability to enhance one's potential
through learning to do new things
3.29
Good
The ability to improve one's potential
through the method of working in a
team (learning to live together) to
overcome changes caused by new
things
3.17
Good
Financial
Readiness
The availability of a budget for
Smartport-based port development
3.08
Good
The availability of a budget for
improving the reliability of port
facilities and infrastructure
3.05
Good
The availability of a budget for
improving IT-based services
3.03
Good
The availability of a budget for IT-
based port facility development
2.97
Enough
Availability of budget for improving
the quality of port human resources
2.98
Enough
Availability of budget for improving
the IT-based infrastructure
2.98
Enough
Level of use of
IT
Reliability of IT systems
3.12
Good
Appropriateness of IT utilization
3.00
Enough
Accuracy of IT usage targets
3.22
Good
Level of big data technology usage
3.08
Good
Level of usage in port operations
3.06
Good
Level of communication technology
usage
3.09
Good
Level of IT usage in administrative
services
3.22
Good
Level of IT usage in port security
monitoring
3.14
Good
Organizational
Readiness
Organizational readiness to use IT
3.06
Good
Organizational strategies for
implementing IT
3.11
Good
Organizational innovation in
implementing IT
3.12
Good
IT-based business models
3.12
Good
Organizational human resource
capabilities for implementing IT
2.89
Enough
Organizational readiness to improve
human resource quality
3.02
Good
IT-based service improvements
3.02
Good
IT facilities and infrastructure
capabilities
3.12
Good
98
Table 8 shows the readiness values of the construct
indicators for each variable. For the mental readiness
variable, a "GOOD" level was obtained for each
construct indicator. Meanwhile, two construct
indicators were obtained at the "ENOUGH" level for
the competency readiness variable. A 'GOOD' level
was obtained for each construct indicator for the
willingness to change variable. Three construct
indicators were obtained at the "ENOUGH" level for
financial readiness. The "ENOUGH" level in the "level
of use IT" category includes one construct indicator
and one Indicator in the "organizational readiness"
category. The "ENOUGH" level indicates that there is
still a need for improvement in the readiness of each
Indicator. From the readiness assessment for each
construct indicator, values are obtained for each
variable based on the criteria in Table 9.
Table 9. Readiness Assessment Criteria
Variable
Average Score
Category
Mental Readiness
3.30
Good
Competency Readiness
3.07
Enough
Willingness to change
3.28
Good
Financial Readiness
3.02
Enough
Level of Using IT
3.12
Good
Organizational Readiness
3.05
Good
Table 9 shows that overall organizational readiness
is already in the "GOOD" category, but the value is still
at the lower threshold. This indicates the need for
improvement in several influencing variables, such as
competency and financial readiness, in the "ENOUGH"
category.
5 DISCUSSION
This study shows that employee mental readiness,
competency readiness, employee willingness to
change, and financial readiness affect organizational
readiness to change in the face of disruption caused by
information technology developments through IT
usage level interventions. Mental readiness refers to
the extent to which an individual is prepared to face
uncertainty, pressure, and risks that may arise [27].
Mental readiness is an important variable for
organizational readiness to face disruption. This is
because each individual has different responsibilities
and roles within the organization, so good mental
readiness is one of the organization's assets for
surviving and advancing in line with developments.
Competency readiness and organizational
readiness are distinct yet interrelated concepts.
Competent individuals can contribute more effectively
to building organizational readiness, and conversely,
organizations with strong readiness are better
equipped to support individual competency
development. Competency readiness refers to the
extent to which individuals within an organization
possess the necessary skills, knowledge, and abilities to
perform tasks and contribute to organizational goals,
particularly in embracing change and innovation.
When competency and organizational readiness are
high, the organization is more likely to successfully
implement changes, adapt to new challenges, and
achieve its strategic goals [28]. However, if there is a
mismatch, this can lead to challenges in facing such
changes. For example, if an organization has good
management but lacks competent employees, it may
face difficulties in dealing with changes. Therefore, the
organization's readiness to successfully face changes
caused by disruption depends on the readiness of
individuals to face these changes [29].
Organizational readiness and willingness to change
are two interrelated factors and one of the keys to
successful organizational transformation. Willingness
to change is critical to organizational readiness,
especially at the individual level. An individual's
unwillingness to change can hinder the entire change
process. Willingness to change motivates individuals
to actively participate in achieving organizational
goals. Therefore, it is important to consider the
psychological aspects of individuals so that the level of
organizational readiness will increase [30].
Financial readiness relates to having sufficient
funds to support change innovation. Financial
readiness and organizational readiness are interrelated
variables. Organizations with financial resources can
fund the implementation of necessary changes. In
addition to providing facilities and infrastructure,
financial readiness is also needed for employee
training, integrating existing systems, and
implementing sustainable change plans. Therefore,
without financial readiness, organizational readiness
for change will not be achieved [31].
Level of IT use refers to the organization's readiness
to implement information technology through
adopting, integrating, and utilizing new technology.
The level of IT usage relates to both individual
employees and the organization. Individual mental
readiness, employee competency readiness, and
individual willingness to change using new technology
determine the organization's success in accepting the
impact of information technology disruption.
Therefore, assessing the level of IT usage within the
organization is necessary [32].
Assessing the level of organizational readiness is
essential to address changes resulting from the impact
of information technology disruption. Organizational
readiness assessment is about having a change plan
and ensuring that the organization is psychologically,
structurally, and strategically prepared to accept and
thrive amid new technological developments [33]. By
understanding the value of each variable that plays a
crucial role in preparing organizations to embrace
change, it is hoped that port management
organizations in Indonesia will begin to formulate
preparatory steps for indicators that require
improvement. Further research is recommended to
develop a more comprehensive model by combining
individual and team variables in assessing
organizational readiness.
6 CONCLUSIONS
From this study, it can be concluded that
organizational readiness is influenced by individual
readiness in the form of mental readiness, competency
readiness, and willingness to change in information
technology. The study results show that the level of
competency readiness of port managers and the level
of financial readiness of port organizations still need
improvement. Regarding competency readiness, the
99
Indicator that requires improvement is competency in
cybersecurity systems. Regarding financial readiness,
the availability of a budget for the provision of facilities
and infrastructure, and the development of
organizational human resources still require special
attention. By addressing these indicators, it is hoped
that organizational readiness for information
technology disruption can be improved.
ACKNOWLEDGMENTS
The authors thank the study participants and the reviewers
for their valuable contributions and feedback.
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