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What causes ‘very serious’ maritime accidents?



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Safety and Reliability – Theory and Applications – epin & Briš (Eds)
© 2017 Taylor & Francis Group, London, ISBN 978-1-138-62937-0
What causes ‘very serious’ maritime accidents?
B.M. Batalden & A.K. Sydnes
UiT—The Arctic University of Norway, Tromsø, Norway
ABSTRACT: Despite a reduction in the relative number accidents in maritime transport, severe acci-
dents continue to occur. The paper applies a modified Human Factor Analysis and Classification System
(HFACS) framework developed by Batalden & Sydnes (2014) to study maritime accidents. The study
builds on investigation reports published by the UK’s Marine Accident Investigation Branch (MAIB)
published in the period from 01 July 2002 until 01 July 2010. The study investigates 22 very serious acci-
dents and the 133 causal factors identified as leading to them. It concludes that very serious accidents,
distinguish themselves by having causal factors that are to be found higher up in organizations, in com-
parison to other accidents. Moreover, planning and supervision onboard vessels are identified as a main
ship operations and a safe working environment,…
assess all identified risks … and establish appropri-
ate safe guards, continuously improve safety man-
agement skills... (IMO 2002, p.7).
Despite a reduction in the relative number acci-
dents, severe accidents continue to occur (IMO
2012). Moreover, the human element is still the
main cause (Graziano etal. 2016, Tzannatos 2010,
Hetherington et al. 2006). Apparently the mari-
time regulatory regime fails to address human
factors and safety management challenges appro-
priately (Kuronen & Tapaninen 2010), as these have
remained relatively unchanged during the last cen-
tury (Schröder-Hinrichs etal. 2012). As such, the
study of human factors in maritime safety remain
a pertinent topic of study. Previous research on the
ISM Code and maritime safety management has
included methods of measuring safety standards,
the relation between safety management and safety
culture, stakeholders’ opinions on the ISM Code,
organizational learning within shipping companies,
reporting and analysis procedures, compliance with
the ISM Code and the ISM Code as part of inte-
grated quality management (Batalden & Sydnes
2014). There is also a considerable literature on the
investigation of maritime accidents, including stud-
ies of human and organizational factors (Schröder-
Hinrichs etal. 2011, Chauvin etal. 2013, Xi et al.
2009, Celik & Cebi 2009, Celik 2009). This study
analyses human factors at different levels of organi-
sations that cause very serious maritime accidents.
The research questions:
What are the causes of very serious accidents?
Are there differences in the causes of very seri-
ous accidents in comparison to other accidents?
The maritime transport industry (shipping)
accounts for more than 90% of global trade (IMO
2012), and has had a doubling in transport capac-
ity since 1980 (UNCTAD 2011). Shipping has
traditionally been conservative when it comes to
regulation. As most vessels conduct the main part
of their operations at sea, their owners have been
able to bypass regulations to gain profits (Stopford
1997). However, a new era in maritime safety was
entered in 1993 when the IMO Assembly adopted
Resolution A. 741(18), the ISM Code (IMO 1993).
This was against the back-drop of a series of very
serious maritime accidents during the 1980–90 s,
where the human element had been identified as
a main cause (Anderson 2003). The ISM Code is
part of the legal framework that regulates ship-
ping, including the International Convention for
the Safety of Life at Sea (SOLAS) of 1974, the
Standards of Training, Certification & Watchkeep-
ing Convention (STCW) of 1978, and the United
Nations Convention on the Law of the Sea (UNC-
LOS) of 1982 (Batalden & Sydnes 2014). The
ISM Code is mandatory by being incorporated in
SOLAS as Chapter IX ‘Management for the Safe
Operation of Ships’. Following the ISM Code, the
ship-owners are to develop, implement and main-
tain their own management systems for regulat-
ing behaviour and practice according to the ISM
Code (Rodriguez 1998–1999, Batalden & Sydnes,
2014). The Code is to ‘ensure safety at sea, preven-
tion of human injury or loss of life, and avoidance of
damage to the environment, in particular the marine
environment, and to property’ (IMO 2002, p.7). A
company’s SMS shall: ‘provide for safe practices in
To answer these, we apply a modified human Fac-
tor Analysis and Classification System (HFACS)
framework based on Reason (1990) and developed
by Batalden & Sydnes (2014). The first step is to
identify and code all causal factors that contributed
to the very serious accidents in our sample of study.
Second, we analyse if there are any difference in the
causal factors leading to ‘very serious’ accidents in
comparison to causal factors leading to less severe
This study has coded 94 maritime incident and
accident cases based on 85 investigation reports
issued by the UK’s Marine Accident Investigation
Branch (MAIB) between July 2002 and July 2010.
The timeframe chosen for the dataset is based on
a period with a stable regulatory framework for
safety management of the maritime transporta-
tion industry. The objective being to increase the
validity, making cases comparable regulatory wise.
Some of the reports contain incidents and acci-
dents involving two or more vessels, resulting in
more cases than reports. The cases were catego-
rized with respect to severity using the IMO defini-
tions “very serious”, “serious” and “less serious”
(IMO 1997). The cases categorized as “very seri-
ous” involve total loss of the ship, loss of life, or
severe pollution. In total, there were 22 cases coded
as “very serious” among the reports studied.
The reports were coded into a Human Fac-
tor Analysis and Classification System (HFACS)
framework using the qualitative data analysis soft-
ware NVivo 11. HFACS was initially developed
for the aviation industry, and more specifically for
military aviation operations. No doubt, there are
major differences between maritime operations
and aviation operations. While aviation operations
are perhaps more distinct and easier to divide into
the different levels of an organization, maritime
operations have many of the same features. Avia-
tion operations are typically more standardized
with less freedom in how to conduct the operations
compared to maritime operations. This challenges
the coding of investigation reports of maritime
operations as it becomes less clear when there is an
error or violation. For there to be an error or viola-
tion, it needs to be compared to some correct con-
duct. Celik & Er (2007) reports that HFACS has
been successfully applied in the US Navy, Marine
Corps, and the US Coast Guard, amongst others.
To deal with the difference between aviation opera-
tions developed by Wiegmann & Shappel (2003)
and maritime operations, the HFACS used in this
study was adapted to include sub-nodes specific to
the maritime transport. An example of the adjust-
ment is the inclusion of third tier categories for
unsafe supervision. This was done to include the
fact that maritime operations have greater auton-
omy, leaving the senior management onboard the
vessels partly responsible for planning and supervi-
sion of operations.
Facts from the reports were coded into the
HFACS framework by the first author. The first
author holds a license as a master mariner and
as an aviation pilot. Further, the first authors has
work several years as a safety manager in a Norwe-
gian ship owning company. To increase reliability
of the coding, an independent person coded a 20%
random sample to HFACS. The coding results
from the first author and the independent person
were compared using interrater Krippendorff’s
Alpha (α) (Krippendorff 2004) yielding an α value
of 0.824 which indicates an acceptable agreement
between the coders (Bakeman etal. 1997, Krippen-
dorff 2004).
Limitations of the study relates, amongst others,
to the possibility of underreporting of maritime
incidents (Hassel etal. 2011, Psarros etal. 2010)
and challenges of investigation methods (Lund-
berg et al. 2009). Using secondary information
from these investigation reports meant there was
less control of the data collected and the presenta-
tion of this data. Further, the study bases its results
and conclusions on reports conducted exclusively
by MAIB for casualties and incidents that either
happened in UK waters or where UK-registered
vessels were involved. The MAIB reports were
selected because of their accessibility, and because
they include human factor causes based on Rea-
son’s model of accident causation (Rothblum etal.
2002). The study is a limited case study, using
reports only from MAIB and it is not possible to
generalize beyond the scope of the case. The results
have however been discussed with both shore
based personnel and sailing personnel working
in the Norwegian maritime industry. Both groups
find the results to provide acceptable results. Com-
paring the results from this study with the study
of Schröder-Hinrichs etal. (2011) that used differ-
ent investigation reports indicate somewhat similar
findings between reports classified as very serious
and those classified as serious and less serious.
Reasons (1990) model of accident causation pro-
vides a framework for analysing and understanding
human errors at various levels in an organization.
The model has two interrelated causal sequences,
an active failure pathway and a latent failure path-
way. It is argued that human failures are not only
restricted to the ‘sharp end’ – the operators working
close to the source of danger – but also to be found
at other levels of organization (Reason 1995). In the
model, errors made at the ‘sharp end’ are labelled
‘Unsafe acts’, whereas latent failures are labelled
either ‘Preconditions to unsafe acts’, ‘Unsafe super-
vision’, or ‘Organizational influences’. Central to
the development and application of the accident
causation model, are more complex socio-technical
organisations. Organisational accidents differenti-
ate themselves typically by accumulation of latent
failures that makes it difficult if not impossible for
operators at the sharp end to comprehend the situ-
ation (Reason 1995). Decisions made at higher lev-
els of an organisation may follow the active failure
pathway, resulting in higher likelihood of errors and
violations. This may be due to issues such as reduced
manning level, general cost-cutting initiatives and
less training provided. Decisions made at higher lev-
els of organisations may also directly influence the
barriers and safeguards by following the latent fail-
ure pathway thus worsen the consequences of errors
and violations (Reason 1995). Some examples of
decisions that may follow the latent failure pathway
are missing or weakened soft and/or hard barriers. It
may also be that defences and barriers are deliber-
ately designed to save costs.
HFACS was developed to provide a methodo-
logical tool for accident investigation supplement-
ing Reasons model (Schröder-Hinrichs etal. 2011).
HFACS was originally developed for analysing
military aviation accidents, but has been adapted
by several researchers to study other phenomena
(Schröder-Hinrichs et al. 2011, Chauvin et al.
2013). Our study took HFACS-MSS (machinery
spaces of ships), as a starting point, and made
the necessary adaptions to make it suitable for
marine operations in general (Batalden & Sydnes
2014). We have also drawn on Xi etal. (2009), who
developed an HFACS method for marine human
factors. One difference between the HFACS-MSS
and the HFACS used in our study is the division of
unsafe supervision between shore-based manage-
ment and shipboard management. This has been
done to differentiate between unsafe supervision
carried out on board, and shore-based manage-
ment. Compared to the aviation industry, military
aviation in particular, maritime operations in the
merchant fleet are usually differently organized,
with tasks distinct from those in aviation.
4.1 Degree of severity
In the sample (N=94), 22 cases were coded as being
very serious, these involve the total loss of the ship,
loss of life, or severe pollution (IMO 1997). 23 cases
are coded as being serious (such as fire, explosion,
and damage to the hull rendering the ship not sea-
worthy, and any pollution) and 49 as less serious
(incidents where the ship or human life was in peril)
(IMO 1997). For the purpose of this study we do not
distinguish between serious and less serious cases, as
focus is on the study of very serious accidents.
In the coding the 94 reports using the HFACS
framework, 478 causal factors were identified at
the third tier. Table 1 presents the distribution of
these 478 factors by HFACS tiers and the sever-
ity of the incident. Of the 478 causal factors coded
in this study, 133 were related to the 22 ‘very seri-
ous’ cases. In total 345 causal factors were coded
as belonging to serious and less serious cases (of
which 133 to ‘serious’ and 212 to ‘less serious’).
4.2 HFACS coding to very serious accidents
There have been identified 133 causal factors
leading to the 22 cases that have been coded as
‘very serious’. Of these 25% (N = 33) belonged
to the category of Organizational influences, 38%
(N=51) to Unsafe supervision, 18% (N=24) to
Preconditions for unsafe acts, and 19% (N=25) to
Unsafe acts.
Among Unsafe acts 18% (N=24), there is rela-
tively even distribution of causal factors at the 2nd
tier between Errors (10%) and Violations (9%). At
the 3rd tier we see that Skill-based errors (6%) and
routine violations (8%) are pre-dominant.
Preconditions for unsafe acts represent 18%
(N= 24) of the factors causing serious accidents
and are as such the lowest-scoring category at the
1st tier. Half of these fall under the category of
Environmental factors (9%), while the remaining
are distributed between Crew conditions (5%) and
Personnel factors (4%). At the 3rd tier we see that
the Technological environment is the highest factor
with 7% (N=9).
51 causal factors were coded as belonging to
Unsafe supervision (38%). At the 2nd tier 23% of
the cases were related to Inadequate supervisions
(N=31) and 13% to Planned inappropriate opera-
tions (N=17). In comparison, the sub-nodes Failed
to correct known problems and Supervisory viola-
tions represent a total of 3 causal factors and are
as such remarkably low. On the 3rd tier we see that
both inadequate supervision On board (2.1.1) and
Shore based (2.1.2) have a very high score with 10%
and 14% respectively. In addition the inappropriate
planning of Shipboard operations (2.2.1) with 11%
(N=15) is a major factor. All other factors on the
3rd tier, are on the other hand very low.
Organizational influences represent 25% of the
causal factors (N= 33). Here the dominant sub-
node on tier 2 is Organizional processes with 17%
(N=22). Resources in turn cover 8% of the causal
factors (N = 10). Organizational climate, on the
other hand, including structure, policies and cul-
ture at the 3rd tier, only have 1single factor coded
as belonging to it, which by itself is remarkable.
At the 3rd tier, Oversight (1.3.3, 10%), Procedures
(1.3.2, 6%), and equipment/facility resources
(1.1.3, 6%) have the highest score.
Unsafe supervision with 38% stands out as a
major causal factor in very serious maritime acci-
dents at the 1st tier. Moreover, it is worth noting that
the two highest levels – Organisational influences
and Unsafe supervision – represent a total of 63%
of the causal factors, versus 37% belonging to Pre-
conditions for unsafe acts and Unsafe acts, that is,
closer to the ‘sharp end’.
Table 2 provides a ranking of the highest scor-
ing causal factors coded at the 2nd tier. When
analysing the 2nd tier, we found that Inadequate
Table1. Presentation of causal factors coded in HFACS.
Very serious Serious & less serious
Nr % Nr %
1. Organizational influences 33 25% 52 15%
1.1. Resources 10 8% 14 4%
1.1.1. Human resources 2 2% 8 2%
1.1.2. Technology resources 0 0% 0 0%
1.1.3. Equipment/facility resources 8 6% 6 2%
1.2. Organizational climate 1 1% 5 1%
1.2.1. Structure 0 0% 0 0%
1.2.2. Policies 0 0% 1 0%
1.2.3. Culture 1 1% 4 1%
1.3. Organizational processes 22 17% 33 10%
1.3.1. Operations 1 1% 4 1%
1.3.2. Procedures 8 6% 12 3%
1.3.3. Oversight 13 10% 17 5%
2. Unsafe supervision 51 38% 96 28%
2.1. Inadequate supervision 31 23% 62 18%
2.1.1. On board 13 10% 13 4%
2.1.2. Shore based 18 14% 49 14%
2.2. Planned inappropriate operations 17 13% 22 6%
2.2.1. Shipboard operations 15 11% 12 3%
2.2.2. Shore based planning 2 2% 10 3%
2.3. Failed to correct know problems 1 1% 4 1%
2.3.1. On board related failures 1 1% 2 1%
2.3.2. Shore based failures 0 0% 2 1%
2.4. Supervisory violations 2 2% 8 2%
2.4.1. On board violations 1 1% 7 2%
2.4.2. Shore based violations 1 1% 1 0%
3. Preconditions for unsafe acts 24 18% 88 26%
3.1. Environmental factors 12 9% 26 8%
3.1.1. Physical environment 3 2% 1 0%
3.1.2. Technological environment 9 7% 25 7%
3.2. Crew conditions 7 5% 21 6%
3.2.1. Cognitive factors 5 4% 13 4%
3.2.2. Physiological state 2 2% 8 2%
3.3. Personnel factors 5 4% 41 12%
3.3.1. Crew interaction 5 4% 38 11%
3.3.2. Personal readiness 0 0% 3 1%
4. Unsafe acts 25 19% 109 32%
4.1. Errors 13 10% 55 16%
4.1.1. Skill-based errors 8 6% 22 6%
4.1.2. Decision and judgement errors 4 3% 31 9%
4.1.3. Perceptual errors 1 1% 2 1%
4.2. Violations 12 9% 54 16%
4.2.1. Routine 11 8% 49 14%
4.2.2. Exceptional 1 1% 5 1%
Total N = 133 100% N = 345 100%
supervision stands out as the most prominent
causal factor. In summarising the top three 2nd tier
sub-nodes (2.1., 1.3, and 2.2), they represent 53%
of all causal factors at the 2nd tier.
Table 3 presents 3rd tier categories ranked as
containing most causal factors. We see that factors
coded to Unsafe supervision under Shore based
(supervision), Shipboard operations (planning)
and On board (supervision) add up to 35% of all
third tier causal factors. In addition (organisa-
tional) Oversight is high-scoring with 10%.
4.3 Very serious versus other accidents
In this section we compare Very serious accidents,
with those that have been coded as Serious and
Less serious. This may contribute to the under-
standing of what causal factors that are specific to
Very serious accidents. The analysis is based on the
data coded in Tabl e 1.
Figure1 provides an illustration of causal factors
coded on the 1st tier. As noted above Unsafe supervi-
sion (38%) and Organisational influences (25%) are
most high-ranking in Very serious accidents, while
Preconditions for unsafe acts (18%) and Unsafe acts
(19%) have a lower score. Interestingly, accidents
coded as Serious and Less serious have a different
pattern in the distribution of causal factors at the 1st
tier. Here Unsafe acts (32%) are the highest ranking
factor, Unsafe supervision (28%) is also high, Precon-
ditions for unsafe acts (26%) have a high score, while
Organisational influences (15%) have a low score. Fig-
ure1 demonstrates how Very serious accidents has a
pull in the direction of higher levels of organisation,
while Serious and Less serious accidents to a larger
extent have an opposite pull towards the ‘sharp end’.
By comparing the highest ranking 2nd tier
causal factors from Very serious accidents (Tab le2)
and see how these score among Serious and Less
serious, further detail is added to the analysis. Data
in Figure2 and 3 are organised according to level
of organisation from sub-nodes under 1 Organisa-
tional influences to those under 4 Unsafe acts. It is
clear that Organisational processes (17% vs 10%),
Inadequate supervision (23% vs 18%) and Planned
inappropriate operations (13% vs 6%) are more
important factors in Very serious accidents. Not-
withstanding, Planned inappropriate operations
also have a very high score in Serious and Less
serious cases (18%). In the case of Environmental
factors there is only a minor difference.
On the other hand, we see that Errors (10% vs
16%) and Violations (9% vs 16%) are markedly
more important in the case of Serious and Less
serious accidents. Also worth noting on the 2nd
tier is 3.3 Personnel factors that has a score of 12%
among Serious and Less serious cases is in contrast
to 4% among Very serious (see Table1).
Figure 3 presents the scores of HFACS on 3rd
tier nodes. When the 2nd tier node 2.1. Inadequate
supervision is coded into Shore based (2.1.2) and
On board (2.1.1), an interesting finding reveals itself.
Very serious and Serious and Less serious have the
same score (14%) on Shore based (Inadequate super-
vision). Moreover, for both categories of cases, this
is the highest ranked causal factor (for Serious and
Less serious cases, 4.2.1 Routine (Violations) have
the same score). The difference found at the 2nd tier
on Inadequate supervision is related to On board the
vessels (10% vs 4%). Equally, the difference found
in Planned inappropriate operations (2.2) largely is
related to 2.2.1 Shipboard operations where Very
serious accidents have a much higher score than oth-
ers (11% vs 3%). On Organisational processes, it is
Oversight (10%) that is prominent among Very seri-
ous, and twice as high as for Serious and Less seri-
ous (5%). Technological environment (3.1.2) is set to
Table2. High ranking 2nd tier HFACS coding.
2nd tier Very serious
2.1. Inadequate supervision 23%
1.3. Organizational processes 17%
2.2. Planned inappropriate operations 13%
4.1. Errors 10%
3.1. Environmental factors 9%
4.2. Violations 9%
Table3. High ranking 3rd tier HFACS coding.
3rd tier Very serious
2.1.2. Shore based 14%
2.2.1. Shipboard operations 11%
1.3.3. Oversight 10%
2.1.1. On board 10%
4.2.1. Routine 8%
3.1.2. Technological env. 7%
Figure1. Comparative 1st tier HFACS coding.
7% for both. However, Routine violations (4.1.2) is
almost twice as high among Serious and Less seri-
ous (14%) than Very serious accidents (8%). Worth
noting on the 3rd tier are also 3.3.1 Crew interaction
and 4.1.2 Decision and judgement errors. Here Seri-
ous and less serious score 11% and 9% versus Very
serious score of 4% and 3%, respectively.
This section will present highlights from the results
of this study and discuss the findings in relation to
the accident causation model developed by Reason
(1990) and research on maritime safety. The first
section will discuss the findings from the coding of
very serious accidents into the HFACS framework.
5.1 Distribution of causal factors
When looking at the coding of causal factors to
the first tier of the HFACS framework there is
an apparent distinction in causal factors coded to
the two higher levels, organizational influence and
unsafe supervision, compared to the two lower lev-
els, preconditions for unsafe acts and unsafe acts. In
this study of very serious accidents, more causal fac-
tors are coded to the higher levels of organizations.
It could be argued that this result may be ascribed
to the severity of the cases resulting in either death,
loss of vessel or severe pollution that might ini-
tiate a more thorough investigation with more
resources and willingness to penetrate further up the
organization(s) involved in the incident or accident.
However, Schröder-Hinrichs etal. (2011) found that
approximately 80% of the causal factors coded to
very serious accidents relate to the two lower levels,
Preconditions for unsafe acts and Unsafe acts. This
does not support the argument that very serious
accidents are more thoroughly investigated.
Assuming that the investigations of accidents
are comparable despite level of seriousness, another
explanation to our result may be that decisions made
at higher levels of organizations have a greater impact
on the probability of very serious accidents in the
maritime transportation industry. Hollnagel (2009)
has addressed this by his efficiency-thoroughness-
trade-off principle in order to explain the trade-offs
that individuals face during operations. Marais &
Saleh (2008) have developed a similar model at an
organizational level, focusing on efficiency and thor-
oughness. The higher numbers of causal factors
among the top organizational levels found in very
serious accidents may then be indicative that these
organizations have put insufficient effort and thor-
oughness in their management of activities. This can
influence levels of risk and safety through both active
failure pathways and latent failure pathways. There
has been a change from integrated ship owning com-
panies to a separation between owning and managing
companies in the shipping industry (Lorange 2009).
This has introduced a competition among ship man-
agement companies that may have strengthened focus
on increased efficiency at the cost of reduced thor-
oughness (Lorange 2009). For instance, both Batal-
den & Sydnes (2014) and Batalden & Sydnes (2015)
found limitations and weaknesses in the monitoring/
auditing mechanism within the maritime shipping
industry which is located at the organizational level of
the HFACS framework. Within the Offshore Support
Vessel (OSV) segment, some companies apply a strat-
egy aiming for ’quick fix’ rather than detailed efforts
to improve their safety management (Batalden &
Sydnes 2015). In a study of collisions cases, Chauvin
et al. (2013) reported similarly, weaknesses and fail-
ures in auditing processes.
Previous studies have reported violations of
procedure and drifting operational practices in
the merchant fleet (Dai et al. 2013, Oltedal 2012,
Antonsen 2009). However, for causal factors coded
to unsafe acts in this study, the findings are dissimi-
lar to the those of both Chauvin et al. (2013) and
Figure2. Comparative 2nd tier HFACS coding.
Figure3. Comparative 3rd tier HFACS coding.
Schröder-Hinrichs etal. (2011). While the findings
from this study indicate an even distribution between
violation and errors, Chauvin etal. (2013) found that
most unsafe acts related to violation, while Schröder-
Hinrichs etal. (2011) found that these mostly relate
to errors. This may be due to different area of focus
when selecting cases where Chauvin et al. (2013)
focus purely on collision cases while Schröder-
Hinrichs etal. (2011) focus on machinery spare fires
and explosions (Batalden & Sydnes 2014).
5.2 Very serious accidents versus other accidents
The higher representation of causal factors coded
to routine violations for serious and less serious
cases may indicate that violations identified at the
sharp end may have less severe impact on the out-
come. In addition, it may indicate that violations
are more frequently present when the risks are
clearer. It may be that decisions taken at a higher
organizational level distort the understanding of
hazards at the sharp end, and that violations are
less present due to this. With a noticeable differ-
ence between very serious and other accidents for
inadequate supervision, it seems that a greater
effort should be made to improve the safety aware-
ness and perhaps leadership training among the
managers (senior officers) onboard the vessels.
The results also indicate that planning of ship-
board operations are substandard, resulting in
very serious accidents. This is similar to the find-
ings of Macrae (2009) and Chauvin etal. (2013).
Schröder-Hinrichs etal. (2011) did however find
no inappropriately planned causal factors related
to very serious accidents in their study of machin-
ery space fires and explosions.
The comparison of very serious versus serious and
less serious accidents indicate a higher frequency of
higher-level organizational failures in in the former
case. In their study of maritime safety standards role
and seriousness of shipping accidents, Baniela &
Rios (2011) found that deviations from regulations
and procedures typically introduced by ISO 9000
and the ISM Code has “an associated probability of
getting involved in a serious casualty after an inci-
dent occurs” (Baniela & Rios, 2011, p518).
When comparing the seriousness of accidents,
very serious accidents have a higher number of
causal factors coded under Organisational proc-
esses that relate to a lack of risk management and
safety programs (Oversight, Table 1). Batalden &
Sydnes (2014b) identified the issue of limited use
of systematic risk assessment in the OSV segment
when identifying key shipboard operations and
establishing instructions, procedures and checklists.
Based on the 3rd tier analysis, it seems that the
main differences between very serious accidents and
other lay in a lack of planning and supervision on-
board, creating latent pathways for failures. Notably,
these are due to organisational procedures rather
than violations and errors in the sharp end. This
may hypothetically contribute to explain why they
cause very serious accidents, in that operators at the
sharp end may have had less opportunity to adjust
their operations to handle a situation, perhaps being
caught by surprise as situations emerge in an unex-
pected and incomprehensible way (Reason 1995).
This study has found that the main causal factors
leading to very serious accidents, when coded to
HFACS, are to be found in the higher levels of
organization, that is, organizational influence and
unsafe supervision. This distinguishes these acci-
dents from those categorized as serious and less
serious, where the highest scoring causal factors
are to be found among preconditions for unsafe
acts and unsafe acts in the HFACS model.
There is a need for further investigation into
how Organisational influences and Unsafe super-
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... Another paper related to human factors is based on the human factors index system of ship accidents to develop a multidimensional association rules algorithm by incorporating the Reason model and classic correlation rules algorithm [28]. Other works are centered on human factor as the main cause of most serious maritime accidents [29]. Authors use the model Human Factor Analysis and Classification System (HFACS) based on the Swiss Cheese model of human error, which had been developed to provide a methodological tool to investigating an accident in the aviation industry. ...
... Finally, it is interesting to highlight that these models include aspects like wind forces, among other variables, as an improvement of the limitations defined in previous works [12]. It is true that, like in other studies [14], the determination factor must be improved in future analysis and it must be done paying special attention to the influence of the human factor in some accidents, as it was concluded previously in agreement with the more recent research lines [29,30]. ...
Full-text available
The present paper shows an original study of more than 163 ship accidents in Spain showing which of the usually employed variables are related to each type of vessel accident due to the lack of information in this region. To this end, research was carried out based on the Spanish Commission for Investigation of Maritime Accidents and Incidents (CIAIM) reports. Detailed combinatory ANOVA analysis and Bayesian networks results showed a good agreement with studies of other regions but with some particularities per each type of accident analyzed. In particular, ship length was defined as the more relevant variable at the time to differentiate types of accidents. At the same time, both the year of build and the fact that the ship meets the minimum crew members required were excellent variables to model ship accidents. Despite this, the particularities of the Spanish Search and Rescue (SAR) region were defined at the time to identify accidents. In this sense, although variables like visibility and sea conditions were employed in different previous studies as variables related to accidents occurrences, they were the worst variables to define accidents for this region. Finally, different models to relate variables were obtained being the base of deterministic dynamic analysis. Furthermore, to improve the accuracy of the developed work some indications were obtained; revision of CIAIM accidents scales, identification of redundant variables, and the need for an agreement at the time to define the classification limits of each identification variable.
... The Human Factor Analysis and Classification System (HFACS) model separates these accidents from those classified as serious and less serious. The highest-scoring causal variables are found among preconditions for dangerous acts and unsafe acts [17]. Statistical studies have lately indicated that human error is the principal cause of the majority of marine accidents. ...
Full-text available
Multiple causes are responsible for marine accidents and incidents. Some of them are a collision of ships, internal technical failures, human errors, or weather effects. Most of them are just ignoring the shortage of international laws, bypassing registration, which they can remotely handle by registering the vessel in any other countries than their own country. Once it happens, it can harm the marine ecosystem, ocean water and coastal region; local people daily depend on fishing in various forms and degrees. Those effects of accidents are varying from minor injuries to fatal casualties. This study reveals the most critical role of regulations in avoiding similar accidents in the future by considering two recent cases in Sri Lankan water. In both cases, Sri Lanka didn't learn the lesson from previous experience to avoid a similar accident with multiple impacts on the environment and marine biodiversity. Therefore, in the end, some crucial actions are highlighted to implement to prevent similar events shortly.
... The Human Factor Analysis and Classification System (HFACS) model separates these accidents from those classified as serious and less serious. The highest-scoring causal variables are found among preconditions for dangerous acts and unsafe acts [17]. Statistical studies have lately indicated that human error is the principal cause of the majority of marine accidents. ...
Full-text available
Multiple causes are responsible for marine accidents and incidents. Some of them are a collision of ships, internal technical failures, human errors, or weather effects. Most of them are just ignoring the shortage of international laws, bypassing registration, which they can remotely handle by registering the vessel in any other countries than their own country. Once it happens, it can harm the marine ecosystem, ocean water and coastal region; local people daily depend on fishing in various forms and degrees. Those effects of accidents are varying from minor injuries to fatal casualties. This study reveals the most critical role of regulations in avoiding similar accidents in the future by considering two recent cases in Sri Lankan water. In both cases, Sri Lanka didn't learn the lesson from previous experience to avoid a similar accident with multiple impacts on the environment and marine biodiversity. Therefore, in the end, some crucial actions are highlighted to implement to prevent similar events shortly.
... For example, inadequate supervision (group 4, Table 2) has been extensively identified in previous studies as highly related to maritime accidents. For instance, B. M. Batalden and Sydnes (2017) identifying that and unsafe supervision as a main causal factor leading to very serious accidents. B.-M. Batalden and Sydnes (2014) also performed a study to investigate casualties and incidents, revealing that unsafe supervision emerges as the biggest challenge. ...
Maritime accidents are complex processes in which many factors are involved and contribute to accident development. In order to capture underlying factors in accidents, countries adapted an accident investigation system with the aim of learning from these rare events and prevent similar occurrences in the future. Often these accident investigation reports are converted into databases, which lack a concise and user-friendly classification system, as a result, there are a lot of inadequacies in data-collection and tagging procedures. Therefore, the authors propose to apply an approach to classify human factors (HFs) appeared in past maritime accidents, aiming to develop a set of HF categories which can be used for accidents learning. For this purpose, an accident database was obtained and a two-stage approach was adapted to conduct analysis: first, an open card-sorting case study is organised to group the HFs extracted from an historical accident database. Second, a hybrid card-sorting method was utilized to fully achieve the classification of HFs. Our study revealed issues where HFs are weakly defined and similar factors are duplicated by investigators who populate the database. High-level categories were developed and presented which covers the great majority of HF concerns involved in accidents.
... This gap was already identified by Schröder-Hinrichs, Baldauf & Ghirxi (2011) referring an over-representation of lower end organizational factors in accident investigation reports related machinery space fires and explosions. On the other hand, Batalden & Sydnes (2017) concluded that causal factors in very serious maritime accidents are from higher organization levels. Contextual elements also require further attention, namely those with effect in the conditions of operators and bridge design, which in turn may influence their behaviour and decision. ...
... An inadequate supervision has been extensively identified in the literature as highly related with maritime accidents. For instance, B. M. Batalden and Sydnes (2017) applied a modified Human Factor Analysis and Classification System (HFACS) framework, identifying that the main causal factors leading to very serious accidents are found in the higher levels of organization, that is organizational influence and unsafe supervision. Thus, Batalden and Sydnes (2014) also performed a study to investigate casualties and incidents, revealing that unsafe supervision emerges as the biggest challenge, and it is a causal factor leading to very serious accidents (34.7% of analyzed cases), to serious accidents (23.1%), and to less serious accidents (42.1%). ...
Conference Paper
Aiming to improve maritime safety, there is a need for a practical method that is capable of identifying the importance weightings for each contributing factor involved in accidents. Hence, Marine Accident Learning with Fuzzy Cognitive Maps (MALFCM) incorporated with Bayesian networks is suggested and applied in this study. MALFCM approach is based on the concept and principles of Fuzzy Cognitive Maps (FCMs) to represent the interrelations amongst accident contributor factors. Hence, in this study, grounding/stranding accidents were investigated with the proposed MALFCM approach. As a result, inadequate leadership and supervision, lack of training and unprofessional behavior were identified as the most probable causes of grounding accident. In addition, in the accident scenario analysis, it was observed that the lack of safety culture contributed most to the system failure based on the posterior to prior failures ratio.
... An interesting study has been presented in [30]. Authors used the Human Factor Analysis and Classification System (HFACS) framework, originated in the aviation industry, to analyze the reasons for marine accidents caused by human-related issues. ...
Full-text available
Unmanned vehicles have become a part of everyday life, not only in the air, but also at sea. In the case of sea, until now this usually meant small platforms operating near shores, usually for surveying or research purposes. However, experiments with larger cargo vessels, designed to operate on the high seas are already being carried out. In this context, there are questions about the threats that this solution may pose for other sea users, as well as the safety of the unmanned vehicle itself and the cargo or equipment on board. The problems can be considered in the context of system reliability as well as the resilience to interference or other intentional actions directed against these objects—for example, of a criminal nature. The paper describes the dangers that arise from the specificity of systems that can be used to solve navigational problems, as well as the analysis of the first experiences of the authors arising from the transit of an unmanned surface vessel (USV) from the United Kingdom to Belgium and back, crossing the busiest world shipping route—the English Channel.
Accidents that result in personnel injury or death occur in lifeboats, which are some of the most reliable means of abandoning a ship during drills, routine maintenance, and tests. Comprehensive research on lifeboat accidents is non-existent in literature. This article aims to prioritize the factors responsible for lifeboat accidents and to provide comprehensive recommendations for managers, policymakers, and seafarers. For this purpose, the Fuzzy Delphi method was used in the study. Twelve lifeboat accidents reported by flag states were examined, and detailed accident analyses were made by 12 field experts. As a result of the study, human errors, equipment unsuitability, lack of knowledge, and language problems of the personnel were determined as the most important factors in the causes of lifeboat accidents.
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Abstract Background Maritime pilots often navigate ships through challenging waterways. The required 24 h standby rotation system (ROS) poses a stressful working situation. This study aims to describe the current job-related stress and strain among maritime pilots and the effects on their work ability, taking into account the different rotation systems. Methods Within a cross-sectional survey, pilots of all German pilots’ associations were asked to complete an online questionnaire. The 1-week ROS (port pilots) was compared with the 4-month ROS (sea and canal pilots). The pilots’ subjective perception of stress and strain was assessed using an established ship-specific questionnaire. Daily sleepiness and work ability were examined respectively using the Epworth Sleepiness Scale (ESS) and the Work Ability Index (WAI). Results The study group consisted of 401 male German pilots with an average age of 48.5 years (participation rate 46.9%). More than 50% of the pilots evaluated irregular working hours as the main stressor in their job. 79.8% of the pilots (especially 4-month ROS) experienced high psychological demands in their workplace. 83.3% stated having regularly neglected their private obligations due to job assignments. Pilots from the 4-month ROS experienced insufficiently predictable free time and long operation times at a stretch as stressors (p
In considering effective countermeasures for preventing the same (or similar) type of accidents from happening again, an investigation and analysis to identify the common human and organisational factors (HOFs) among a group of accidents would be beneficial for decision making. The present study aims at proposing an approach that is capable of identifying the common HOFs between or among accidents, in line with the concept of reason’s swiss cheese model, without losing the context details of individual accidents. This approach applies why-because analysis, Human Factors Analysis and Classification System (HFACS) for Maritime Accidents (HFACS-MA, a derivative of HFACS) and grey relational analysis (GRA) to constitute a systematic analysis procedure that is divided into three stages. The first two are to identify the causal HOFs involved in every accident and to figure out the causation among them, and then the categories of the identified HOFs are classified according to the HFACS-MA in turn. Having these analysis results, the GRA, and two associative analysis processes, constituting the third stage of the procedure, are applied to identify the common HOFs from those accidents concerned. An experimental case study, with five marine accidents, is utilised to demonstrate that the analysis results of the proposed approach can not only illustrate the common HOFs among these accidents, but also reveal a comprehensive insight into each analyzed accident. Some considerations, including the future work, associated with the proposed method are also discussed and concluded in this article.
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This article studies the audit and inspection regimes for offshore support vessels (OSV) operating in the North Sea. The changes in regulatory style introduced by the International Safety Management (ISM) Code shifted the maritime transportation industry towards enforced self-regulation, but maritime safety has remained a concern. This article employs a qualitative research approach in studying the OSV segment operating out of Norway. Eighteen semi-structured interviews with industry members were conducted, supplemented by document studies. The study examines to what extent today's audit regimes are perceived to be adequate and how the companies operating OSVs respond to being audited. Although the interviewees feel that audits are necessary and play an important role in safety management, the audit practices identified show limitations as regards the scope of audits, which focus mainly on document control and the bridge department, rarely addressing the quality of the content in safety management systems (SMS). Many companies adopt compliance-seeking strategies such as brush-up and quick fixes. The study shows that considerable attention is paid to maintaining documentable audit trails, but with no assessment of the maritime operations. Contradictory to what is expected from a self-regulated industry, companies are found to adjust their SMS to fit with auditing standards. This undermines the concept that the companies themselves are the best to determine their own SMS' structure and content.
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In 1993, the International Maritime Organization adopted the International Safety Management (ISM) Code which requires all shipping companies operating certain types of vessels to establish safety management systems. Nevertheless, two decades later, maritime safety remains a concern. This article studies 94 maritime cases investigated by the Maritime Accident Investigation Branch in the UK. By providing an analysis of reported casualties and incidents, it highlights current challenges in maritime safety. For each casualty and incident, the study reviews the underlying causal factors. These causal factors are then coded according to the functional sections of the ISM Code, covering various aspects of safety management. To investigate human and organizational factors involved in the casualties and incidents, the human factor analysis and classification system (HFACS) is applied to code the same data. Finally, the relative seriousness of casualties and incidents is considered to discuss the findings from ISM Code and HFACS reviews. The study found that the main challenges pertain to the development of plans for shipboard operations, local shipboard management, and the ability of the company to verify when such practices deviate from best practices or required standards.
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The recent foundering of the Costa Concordia in January 2012 demonstrated that accidents can occur even with ships that are considered masterpieces of modern technology and despite more than 100 years of regulatory and technological progress in maritime safety. The purpose of this paper is, however, not to speculate about the concrete causes of the Costa Concordia accident, but rather to consider some human and organizational factors that were present in the Costa Concordia accident as well as in the foundering of the Titanic a century ago, and which can be found in many other maritime accidents over the years. The paper argues that these factors do not work in isolation but in combination and often together with other underlying factors. The paper critically reviews the focus of maritime accident investigations and points out that these factors do not receive sufficient attention. It is argued that the widespread confidence in the efficacy of new or improved technical regulations, that characterizes the recommendations from most maritime accident investigations, has led to a lack of awareness of complex interactions of factors and components in socio-technical systems. If maritime safety is to be sustainably improved, a systemic focus must be adopted in future accident investigations.
This paper applies a Human Error Identification tool called Technique for the Retrospective and Predictive Analysis of Cognitive Errors to the analysis of ship accidents. Grounding and collision accidents investigation reports involving sixty-four vessels published by the UK’s Maritime Accident Investigation Branch, the Transportation Safety Board of Canada and the National Transportation Safety board of the United States of America are coded and analysed using the taxonomy of the Technique for the Retrospective and Predictive Analysis of Cognitive Errors. A total of two hundred and eighty-nine errors performed by the operators are coded. The results of the codification process are analysed with the objective of identifying the main task errors, cognitive domains and the technical equipment involved in grounding and collision accidents and the factors that affect the performance of the operators. This identification is a necessary step towards safety improvements resulting from dealing with the identified problems. A discussion on the use of the taxonomy of the Technique for the Retrospective and Predictive Analysis of Cognitive Errors is provided and it is proposed to combine it with some elements of the CASMET approach to accident investigation so as to improve the applicability of the methodology to the analysis of ship accidents.
Human error is implicated in nearly all aviation accidents, yet most investigation and prevention programs are not designed around any theoretical framework of human error. Appropriate for all levels of expertise, the book provides the knowledge and tools required to conduct a human error analysis of accidents, regardless of operational setting (i.e. military, commercial, or general aviation). The book contains a complete description of the Human Factors Analysis and Classification System (HFACS), which incorporates James Reason’s model of latent and active failures as a foundation. Widely disseminated among military and civilian organizations, HFACS encompasses all aspects of human error, including the conditions of operators and elements of supervisory and organizational failure. It attracts a very broad readership. Specifically, the book serves as the main textbook for a course in aviation accident investigation taught by one of the authors at the University of Illinois. This book will also be used in courses designed for military safety officers and flight surgeons in the U.S. Navy, Army and the Canadian Defense Force, who currently utilize the HFACS system during aviation accident investigations. Additionally, the book has been incorporated into the popular workshop on accident analysis and prevention provided by the authors at several professional conferences world-wide. The book is also targeted for students attending Embry-Riddle Aeronautical University which has satellite campuses throughout the world and offers a course in human factors accident investigation for many of its majors. In addition, the book will be incorporated into courses offered by Transportation Safety International and the Southern California Safety Institute. Finally, this book serves as an excellent reference guide for many safety professionals and investigators already in the field. © Douglas A. Wiegmann and Scott A. Shappell 2003. All rights reserved.
The aim of this book is to show how a cultural approach can contribute to the assessment, description and improvement of safety conditions in organizations. The relationship between organizational culture and safety, epitomized through the concept of 'safety culture', has undoubtedly become one of the hottest topics of both safety research and practical efforts to improve safety. By combining a general framework and five research projects, the author explores and further develops the theoretical, methodological and practical basis of the study of safety culture.
Accident investigation and risk assessment have for decades focused on the human factor, particularly 'human error'. Countless books and papers have been written about how to identify, classify, eliminate, prevent and compensate for it. This bias towards the study of performance failures, leads to a neglect of normal or 'error-free' performance and the assumption that as failures and successes have different origins there is little to be gained from studying them together. Erik Hollnagel believes this assumption is false and that safety cannot be attained only by eliminating risks and failures. The ETTO Principle looks at the common trait of people at work to adjust what they do to match the conditions – to what has happened, to what happens, and to what may happen. It proposes that this efficiency-thoroughness trade-off (ETTO) – usually sacrificing thoroughness for efficiency – is normal. While in some cases the adjustments may lead to adverse outcomes, these are due to the very same processes that produce successes, rather than to errors and malfunctions. The ETTO Principle removes the need for specialised theories and models of failure and 'human error' and offers a viable basis for effective and just approaches to both reactive and proactive safety management.
In a recent article in this journal, Lombard, Snyder-Duch, and Bracken (2002) surveyed 200 content analyses for their reporting of reliability tests, compared the virtues and drawbacks of five popular reliability measures, and proposed guidelines and standards for their use. Their discussion revealed that numerous misconceptions circulate in the content analysis literature regarding how these measures behave and can aid or deceive content analysts in their effort to ensure the reliability of their data. This article proposes three conditions for statistical measures to serve as indices of the reliability of data and examines the mathematical structure and the behavior of the five coefficients discussed by the authors, as well as two others. It compares common beliefs about these coefficients with what they actually do and concludes with alternative recommendations for testing reliability in content analysis and similar data-making efforts.
Offshore wind farms are growing in size and are situated farther and farther away from shore. The demand for service visits to transfer personnel and equipment to the wind turbines is increasing, and safe operation of the vessels is essential. Currently, collisions between service vessels and offshore wind turbines are paid little attention to in the offshore wind energy industry. This paper proposes a risk assessment framework for such collisions and investigates the magnitude of the collision risk and important risk-influencing factors. The paper concludes that collisions between turbines and service vessels even at low speed may cause structural damage to the turbines. There is a need for improved consideration of this kind of collision risk when designing offshore wind turbines and wind farms.