The purpose of this study is to determine the distraction factors based on their contributions in affecting seafarers’ physical and psychological well-being.
A systematic average mean value technique incorporated with quantitative data collection is applied to determine the contributions of the involved factors in establishing the distraction problems among seafarers.
Element of “Food and nutrition” is recorded as the highest contributing factor to Malaysian seafarers, for deck and engine department, respectively, in establishing the distraction-related problem among five other factors involved.
This paper is only providing a scope of knowledge regarding the contribution of potential distraction factors existing on board the offshore ships. However, the potential distraction factors and their contributions, respectively, are very dynamic and may vary, depending on the situation of a particular area and who are being involved.
The result assists the shipping industry in recognizing the actual causes of the occurrences of marine casualties and incidents related to human factors.
The benefits are addressed to seafarers’ community where their well-being and work performances could be enhanced, thus reducing the occurrences of marine casualties and incidents. Local community at the shores also will be less threatened by marine pollution caused by the accidents of ships at sea.
The result provides a scope of knowledge regarding distraction-related factors in shipboard operation and also the introduction to a systematic assessment approach to determine and rank the parameters by using the systematic average mean value technique which is also a straightforward method and can be applied in any other circumstances.
Othman, M.K., Abdul Rahman, N.S.F. and Fadzil, M.N. (2017), "Determining the contribution of distraction factors on Malaysian seafarers using a systematic average mean value", Maritime Business Review, Vol. 2 No. 2, pp. 99-113. https://doi.org/10.1108/MABR-01-2017-0004Download as .RIS
Emerald Publishing Limited
Copyright © 2017, Pacific Star Group Education Foundation
In the maritime sector, when safety is a priority, the element of human factor is crucial to be assessed in a particular system (IMO, 2004; Othman et al., 2015) because the discipline of human factors is devoted to understand human capabilities and limitations to design equipment, work environments, procedures and policies that are compatible with the human ability. In this way, the designed technology, environments and organizations will work with people and enhance their performance, instead of working against people and degrading their performance. However, the technologies, environments and organizations that have been designed to enhance human performance may also act vice versa and be the key factors that lead to human errors, as they may incompatible with the optimal human performance (Rothblum, 2000). These incompatible factors could increase the risk of human errors and result in the occurrences of injuries, casualties, poor health and even fatalities. A serious increment of reported cases from year 2011 to 2015 which should be concerned of as the marine safety was seriously threatened as in Figure 1 (European Maritime Safety Agency, 2016).
Based on the investigations conducted to the increasing number of reported marine casualties and incidents since 2011 to 2015 as shown in Figure 1, the most contributing factor that caused the increase of marine casualties and incident per year was the human factor which were due to their erroneous actions in shipboard operation and it was represented by 71 per cent of total events recorded as illustrated in Figure 2.
Such contribution of human erroneous actions in marine casualties and incidents induced a worrying situation to the whole shipping industry, as safety is a priority in maritime operation and huge losses could be incurred if such incident cases kept increasing.
Several studies related that the causes of marine casualties and incidents in the shipping industry are due to the effects of distractions experienced by seafarers at their workplace (Geijerstam and Svensson, 2008; Othman et al., 2015, 2016). Distractions, or another term used, interruptions, in almost all instances, are disruptive to performances and may increase human errors (Trafton and Monk, 2007). The effects of interruptions also used to be studied in various fields of high-risk workplace environments such as aviation (Latorella, 1998), medicine (Sanderson and Grundgeiger, 2015) and vehicle operation (Kim et al., 2015) in which human error can have a serious, potentially disastrous consequence. Besides, interruptions are also explored in less-safety critical workplaces, such as offices, where interruptions can induce stress (Mark et al., 2008), anxiety (Bailey and Konstan, 2006) and poorer performance (Cades et al., 2010).
2. Literature review
Distraction can be defined as a diversion process of an individual or group’s attention from the desired area of focus in which it may block or diminish the reception of desired information. Distraction can be caused by several states of situations which consist of the lack of ability to pay attention, lack of interest in the object of attention or the great intensity, novelty or attractiveness of something other than the object of attention (Post and Schumm, 1997; Distraction, 2016). Sources of distractions come from both external sources and internal sources (Alboher, 2008) which may significantly affect the seafarers and may cause many undesirable effects such as excessive fatigue, mental stress and poor work performances (Trafton and Monk, 2007; Othman et al., 2015).
Generally, poor performance of a worker is an effect of insufficient number of healthy staffs, or not providing care according to standards, and not being responsive to the needs of the community and environment (Dieleman and Harnmeijer, 2006). A poorly designed ship or a system where the crew is tired or unaware of cultural differences could contribute to the lower level of safety of the ship operation (IMO, 2010; Othman et al., 2015). Therefore, in the end, the outcome of the effects could be more adverse which also may cause human injuries, serious marine casualties and also fatalities among crews (Othman et al., 2015).
Various factors can be considered to contribute in generating distraction effects to seafarers on board ships, mostly through fatigue, stress, poor health and poor attentions. The possible distraction factors that exist on board can be generated from various sources such as working and living conditions, interactions between human, individual factors, physical on board environment and also from food and nutrition supplied to them. This research is basically an extension work from the previous studies conducted by Othman et al. (2015, 2016). However, such papers did not clearly describe or discuss the weightage value of each contributing distraction factor in affecting seafarers’ conditions and rank them accordingly.
The previous studies had referred only to deck seafarers as a sample study. However, this extension study has taken into account both, deck and engine seafarers, to figure out the most important factor in causing distractions on board and that should be given attention for improvement. To determine the contribution of the distraction factors, the list of parameters to be evaluated is based on the parameters pointed out by Othman et al. (2015, 2016), and the parameters which were classified into the main criteria and sub-criteria are shown in Table I.
Therefore, the objective of this paper is to determine and rank the main distraction factors based on their contributions in affecting seafarers’ conditions at the working place (on board ship). This study is focusing on seafarers because they are valuable assets of the nation which play a crucial role in sustaining or increasing the profitability of the shipping business and marketability of local seafarers in global shipping industry. Thus, their well-beings shall be taken into account for future improvement.
A test case is developed using systematic mathematical steps incorporated with an average mean value technique to determine the contribution of the distraction factors before they are ranked in preference order. The average mean value technique is a systematic mathematical algorithm is using a basic mathematical formula, the averaging, to produce more effective calculation steps and reliable outcomes (Jacobs, 1994; Foerster, 2006). In this research, the average mean value technique is used to assist in finding the weight for each of the parameters involved. It is a straightforward concept by calculating the central tendency of the parameters based on the evaluation given by the respondents compared to the other method which is more complex to understand that may lead to misconduct of the real concept of the method. In addition, the outcomes would also be easily understood and interpreted. The formulae used for this technique, generally, are shown in Equations (1) and (2).
= represents the arithmetic mean;
= summation symbol; is the addition of a sequence of numbers; the result is their sum or total;
= value given per subject;
= total number of subjects involved; and
The weighted values of the main criteria and sub-criteria used to determine the amount of distractions faced by the seafarers. The weighted values were based on the evaluations given by selected respondents using five-point Likert scale values to each listed parameter involved in this study, after analysed using the systematic average mean value technique. The evaluation responses were gained based on survey process by distribution of sets of questionnaires to a total of 120 selected respondents, included: senior deck cadets (SDCs), junior deck officers, senior deck officers, senior engine cadets, junior engine officers and senior engine officers, who definitely have more than 12 months shipboard experience background and theoretical knowledge in shipboard operation. Responses from each of the groups were represented by a number of 20 respondents, respectively, in which to ensure the consistency in data collection as shown in Table II.
The sample respondents of this study was taken among Malaysian seafarers because there is lack of comprehensive research conducted regarding the distraction problem among Malaysian seafarers on board and based on that, this research may fill the gap of the literature regarding distraction issues especially for shipping operations, as distraction may have its own contribution in affecting seafarers at their workplace and induce errors in shipboard operation (Othman et al., 2015, 2016).
In this research, the spider web or radar chart is used to illustrate multivariate observations with an arbitrary number of variables or factors represented on axes starting from the same point and the score given (Chambers et al., 1983; Radar Chart, 2016; Abdul Rahman et al., 2016). The purpose of using this chart is to illustrate and prove the tendency (score) or aptitude of contribution of each main criterion in affecting each group of ship’s manning involved in this research.
A test case was created based on the current situation faced by Malaysian seafarers on board ships. The process of selection was started by identifying the issue faced by seafarers during on board ships and determining the parameters to be used as shown in Table I. Second, the main body of the test case contains:
calculation of the mean value of the evaluation sub-criteria;
calculation of the average mean value of each sub-criteria in separated respondents’ groups;
determination of average mean value of main criteria; and
calculation of weight value of each main criteria for each category or group involved.
Finally, it concluded by ranking the preference order of all main criteria. The illustrations of the steps conducted were shown further as below.
4.1 Step 1: Calculate mean value of the evaluation criteria
The value of each category recorded in Table AI represented the total rate given by the respondents according to the five-point “Likert” scales used in the survey questions, which will be used to measure the contribution of each criterion and sub-criterion involved in affecting their conditions based on their experiences working and living on board ship environment. For example, sub-criteria “SS” recorded the rate in total of 72, after the rate given for the sub-criteria “SS” by each respondent is totalled up according to separated category of respondent groups, “SDC”. The similar technique is used for all the other respondent groups involved in this study as shown in Table AI. Table AI summarized the total rate given by respondents as per categories involved respectively.
4.2 Step 2: Calculate the average mean value of the sub-criteria
All the feedback received from the respondents as according to the questionnaires distributed were further calculated by using Equation (1) of Average Mean Value technique for evaluating the criteria and sub-criteria mentioned. The output values determined throughout this technique were represented as the average mean value of the sub-criteria involved. The example of the calculation using Equation (1) is shown below:
The value of 3.60 represents the average mean value recorded for the sub-criterion “SS” based on the total evaluation made by the total of 20 respondents from “SDC” group. Similar calculations were performed for all sub-criteria in different key study areas for each group of respondents selected. The data of the average mean value of all sub-criteria evaluated are shown in Table AII.
4.3 Step 3: Determine the average weight value of main criteria
To determine the average mean value for the main criteria, initially, the levels of criteria need to be identified and separated. For this study, there are two levels of criteria which were identified as shown in Table I. The main criteria were known as Level 1, while the sub-criteria were known as Level 2. The average mean values of sub-criteria recorded in this study were determined to influence on the average mean value of the main criteria. All the results will subject to the ranking process which will rank the main factors in each group and show the degree of distractions recorded for each ship’s manning (Deck/Engine) which is indicated using the average weight value.
Based on Table I which is used to illustrate that the Level 2 criterion is deemed to influence the Level 1 criterion, the average mean values of the main criteria were determined based on the sum of the average mean values of all sub-criteria under each main criterion (refer to Tables AII and III) of separated groups. The total average mean value of “WC” was determined as follow:
Similar calculations were performed to determine the average mean value of all main criteria. The average mean value of each main criterion is summarized as in Table III.
Meanwhile, the average weight values of the main criteria were determined based on the averaging calculations computed on the average mean value of each criterion as shown in Table III with the total number of the sub-criteria of the criterion they contribute, respectively. The calculations of average weight values of all criteria were using Equation (2). Given the main criterion “WC” for the SDC category as an example, the weight value was computed as follows:
The weight of each criterion was determined by dividing the average mean value of the main criterion “WC” (refer Table AII) which is 22, with the total number of the sub-criteria placed under the main criterion “WC” which is 6. The output for the main criterion “WC” is computed as 3.66667. Similar calculations were conducted to all criteria to determine the average weight value of all the main criteria. Table IV summarized all the output values of the main criteria weight in average.
4.4 Step 4: Calculate the weight value of each main criteria for each category or group involved
The average weight contribution is determined to discover the tendency of the criteria in influencing each group/category of respondents involved in this study. The average weight contribution of a criterion is likely to represent the portion of contribution of the particular criterion when it is compared to the other contributions of the other criteria in similar group/category.
Taking the criterion “WC” as an example for determining a portion of contribution, the average weight value of 3.66667 is divided from the total value of all contributions recorded from six contributors for the “Senior Deck Cadets” group, respectively, which are 21.41167 as shown below.
The output of the calculation, which is also the average weight contribution of the criterion “WC”, is equal to 0.1713. In a similar way, the weight calculation algorithm was applied to all other main criteria with the given average weight values for each category. Table V summarizes all of the output values of the average weight contribution calculation for all the six categories involved.
The average weight contributions of main criteria were interpolated into a spider web or radar chart presentation to describe the average contribution of all main criteria on every category. The illustration of the main criteria contribution on each category is shown as in Figure 3.
Based on Figure 3, there were six parameters tested to determine their contributions to affect six groups of ship’s manning. Each coloured line with a dot represented a parameter. The contribution of each parameter was determined to the weighted amount of distractions which contributed to each group. The nearer the dotted coloured line to the group, the more significant/the higher the amount of distractions that the parameter influences the group. If all the dotted coloured lines are at almost the same point in a particular group, such illustration shows that the group was experiencing a significant distraction problem with the parameters tested.
Based on the values in Table V, the average weight contributions of the main criteria for deck and engine side manning were determined separately, according to category, in the issue of distractions on different departments because a person having different job scopes and responsibilities will experience different types and amounts of distractions. The calculation for determining the overall ranking order for each side/department was using the average weighting formula which generated from Equation (2). The example of calculation is shown as below and the outputs are summarized in Table VI:
Similar calculations were also performed for the Engine side ranking to determine the average weight of each main criterion recorded in each category.
Table VI shows the average weight contribution of each main criteria which caused distractions on the deck and engine side/department. It represents the extent or tendency to which the criteria are affecting both departments. As a result, the “Food & Nutrition” is recorded to be the highest contributing factors for both side/department, followed by “Individual Factors”. The average weight contribution of the other criteria can refer to Table VI, as each department experienced different amounts of distractions.
The factors of “food and nutrition” and “Individual factors” are leading the ranking order of overall analysis which means that they have a huge influence in affecting seafarers’ conditions on board ships compared to other factors involved in this research. The percentage value of contribution between each of the factors involved, regardless of the departments that they’re being into, are not so much different as each factor is interrelated with one another, for instance, food and nutrition may be the highest contribution in affecting overall Malaysian seafarers’ conditions due to the effect of individual factors who manage it such as in terms of the quality of preparation and maintenance of the food or the equality of the food served on board. The quality of preparation and maintenance of the food can be seen in terms of food preparation, taste and hygiene during preparation and storage, meanwhile, the equality can be seen in terms of quantity of the halal and non-halal food served on board the ship. Factor of individual may link in the food and nutrition consumed, as the individual factors of the steward crew may influence the hygiene and the quality of the food prepared. Thus, if the food and nutrition is not so good in terms of hygiene, quality, taste and segregation of the “halal” or non-halal’ food, all the crew, regardless of which department, could be affected, as they may engage with the feeling of un-satisfaction or doubtful situation to consume the food, thus will increase the poor consumption of healthy and nutritious foods for recovery from harsh working jobs. Besides, the crew may also experience a poor state of health condition due to consumption of poor quality of food, as they may engage with food poisoning, diarrhoea, nausea or dizziness, and these situations may probably interrupt the whole activities on board, as the affected person may be distracted by the uncomfortable feeling and lead him to be less aware or leave his duties to the other crew. Such actions may cause increase of negligence or unsafe acts to occur, or may cause other crew to engage with the fatigue problem during the working hours. In the end, the safety on board will be jeopardized if such actions are not under control.
The issue of food and nutrition is being the main cause that contributes to increase in the tendency of distraction problem among Malaysian seafarers, regardless from which department, because it is not just about getting the right fuel into bodies but also significantly important on a psychological level of an individual. The boredom of life on board ship can be treated by having good food, especially in good companies. Having good nutrition, which seafarers look forward to, is able to lift the mood of an individual, and it is important to consider the role that food plays or can play on board, as it can influence seafarers’ feeding rates and the rationale behind the consumptions.
As on board a ship is occupied with multi-national crew which do have different lifestyles, eating and working habits, especially the steward crew, these may develop a variety of questionable scenario on seafarers which may distract them most of the times, for example, regarding the quality of food prepared, hygiene, tastes or variety of the foods served each day and also, the status of “Halal” food for Muslim seafarers. This is because the cook or steward of the ship may not be a Muslim, and so, this may create a doubtful situation on seafarers, especially to the Muslim seafarers, because the quality of the foods is very important to them in terms of how it is being handled, stored and prepared. Sometimes this issue is not being given good attention by the companies and leads to the neglect of the standard and equality of food preparation for Muslim seafarers, for instance. Most Malaysian seafarers may consider the elements inside the food and nutrition factor are very important, as they may come from a Muslim background or “Halal”-practicing person for non-Muslim seafarers. Therefore, the factor of food and nutrition became the most contributing factor to cause distraction problems among Malaysian seafarers in this research.
Based on the findings, regardless of personal experiences, seafarers really need good and concerned managers and owners who acknowledge the importance of good management of food on board their ships, so that seafarers won’t be affected by this factor. With seafaring becoming increasingly challenging with highly loaded and strict requirements, it is also vitally important that crews do not become over fed with junk food and soft drinks. Realizing the possible effects that may develop, the requirements set by the authorities (i.e. in Occupational Safety and Health Administration, International Labour Organization, Maritime Labour Convention) should be well implemented and monitored not only on papers, but also in the real situation, to provide a good nutrition practice for seafarers. If not, seafarers tend to practice a poor diet and unable to fully recover to do the next job for each day, thus increasing the possibility of fatigue and negligence.
The contributions of all listed distraction factors are determined as shown in Table V which is meeting the objective of this study, to determine the amount of distractions faced by Malaysian seafarers while serving the shipboard operation due to the recognized distraction factors among seafarers at their workplace. The weightage values of the factors indicate that each factor does have variability of influence on the seafarers based on their work backgrounds. The findings of this study contribute a scope of knowledge regarding the potential distraction factors which may exist and increase the number of adverse risks on board ships. Nevertheless, the potential factors of the distraction problem on seafarers basically are very dynamic and subjective in which they are depending on the current situation of a particular area of study and who are being involved in this study. The findings of this study are only based on the surveys made to several offshore ships in Malaysia. Further research may be conducted to all maritime transports which are usually engaged with longer times at sea and shipboard operation.
This research contributes to the application of systematic evaluation approach to determine and rank the potential factors involved in creating distraction problem compared to the statistical data which can be retrieved from various sources. The value of this paper is to have a systematic approach to determine and rank the parameters by using the systematic average mean value technique where this systematic technique is a straightforward method and can be applied in any circumstances.
Besides, this research also may provide useful information to the companies to recognize the potential causes of a poor shipping operation or marine incident which may assist the companies to provide proactive actions in conducting a detailed inspection and in finding solution to improve the system to which less distraction.
The outcomes of this research and the systematic assessment approach are expected to benefit seafarers, shipping companies, shipping industry, society and also the nation if the distraction rates among seafarers could be lowered, which can then increase their work performances. Excellent work performances will form a chain of improvements, including but not limited to, improve the shipping operations, increase company revenue along with reduction of operational and maintenance costs, lower turnover jobs, increase employability rates of local seafarers, establish good impression and perception of society towards seafaring career and lower maritime pollution due to shipping accidents at sea. Positive improvement also may contribute to the increase of annual incomes from shipping sectors of the nation.
The list of parameters
|(Level 1)||(Level 2)|
|Working condition (WC)||Staffing or crewing strength/number (SS)|
|Burden of system in use/Technological inventions (BS)|
|Arrangement of working hours (AWH)|
|Work pace/demands/pressure (WP)|
|Distribution of works (DW)|
|Personal abilities/experiences (PAE)|
|Living condition (LC)||Comfortability of accommodations (CA)|
|Recreational activities/facilities (RAF)|
|Periods of rest (PR)|
|Shore alienation/leaves (SL)|
|Intensified activities (IA)|
|Hygiene and tidiness (HT)|
|Human interactions (HI)||Language barrier among crews (LB)|
|Quality of relationship (QR)|
|Social isolation/family separation/away from home (SI)|
|Level of autonomy (e.g. freedom from external control and influences) (LA)|
|Multi-national crews/cultures/beliefs (MC)|
|Supportive cultures (e.g. motivation and tutoring) (SC)|
|Behaviours/Individual factors (IF)||Discipline (DI)|
|Mind set (e.g. way of thinking, awareness) (MS)|
|On-board environment (OE)||Ship motions (SM)|
|Climatic conditions (CC)|
|Weather and mother nature (WM)|
|Visual condition (VC)|
|Exposure to hazardous substances/cargoes (EC)|
|Noise and vibrating circumstances (NV)|
|Food/nutrition (FN)||Organization of food nutrition/composition (OF)|
|Adequate supply of food (ASF)|
|Quality of food preparation (QFP)|
|Equality in distribution of food/needs (EDF)|
|Satisfaction on food preparation (SFP)|
Total respondents involved in this study
|Respondents||Working field||Total samples||Background|
|Senior cadets||Deck||20||More than 12 months sea times and engaged with current scenario of shipboard operations|
|Junior officers||Deck||20||More than 12 months sea times and engaged with current scenario of shipboard operations|
|Act as fourth officers/engineers, third officers/engineers and second officers on-board|
|Senior officers||Deck||20||More than 12 months sea times and engaged with current scenario of shipboard operations|
|Consist of second engineers, chief officers, chief engineers and captains of the ship|
Average mean value of main criteria
The average weight value of all main criteria for each category
|Senior deck cadets||3.66667||3.45833||3.55000||3.71667||3.42833||3.59167||21.41167|
|Junior deck officers||3.25000||3.22500||3.15000||3.46667||2.99167||3.49167||19.57501|
|Senior deck officers||3.70833||3.50000||3.45833||3.57500||3.46667||3.69167||21.40000|
|Senior engine cadets||3.75833||3.84167||3.69167||3.76667||3.73333||4.03333||22.82500|
|Junior engine officers||3.88333||3.76667||3.70000||3.75000||3.48333||3.87500||22.45833|
|Senior engine officers||2.90833||3.37500||2.87500||3.79167||3.70833||3.71667||20.37500|
The average weight contribution of all main criteria for each category
|Senior deck cadets||0.1713||0.1615||0.1658||0.1736||0.1601||0.1677|
|Junior deck officers||0.1660||0.1648||0.1609||0.1771||0.1528||0.1784|
|Senior deck officers||0.1733||0.1635||0.1616||0.1671||0.1620||0.1725|
|Senior engine cadets||0.1647||0.1683||0.1617||0.1650||0.1636||0.1767|
|Junior engine officers||0.1729||0.1677||0.1647||0.1670||0.1551||0.1725|
|Senior engine officers||0.1427||0.1656||0.1411||0.1861||0.1820||0.1824|
Ranking of main criteria according to category (deck side/engine side)
|Rank||Deck side||Average weight||Engine side||Average weight|
|2||Individual factors||0.1726||Individual factors||0.1727|
|3||Working condition||0.1702||Living condition||0.1672|
|4||Living condition||0.1633||On-board environment||0.1669|
|5||Human interactions||0.1628||Working condition||0.1601|
|6||On-board environment||0.1583||Human interactions||0.1558|
Total rate given by the respondents for the same sub-criteria
|Deck side||Engine side|
Average mean value of all sub-criteria evaluated using ARV technique
|Deck side||Engine side|
Abdul Rahman, N.S.F., Ismail, A. and Lun, V.Y.H. (2016), “Preliminary study on new container stacking/storage system due to space limitations in container yard”, Maritime Business Review, Vol. 1 No. 1, pp. 21-39.
Alboher, M. (2008), “Fighting a war against distraction”, Shifting Careers, The New York Times, available at: www.nytimes.com/2008/06/22/jobs/22shifting.html (accessed 21 May 2016).
Bailey, B.P. and Konstan, J.A. (2006), “On the need for attention-aware systems: Measuring effects of interruption on task performance, error rate, and affective state”, Computers in Human Behavior, Vol. 22 No. 4, pp. 685-708.
Cades, D.M., Werner, N.E., Boehm-Davis, D.A. and Arshad, Z. (2010), “What makes real-world interruptions disruptive? Evidence from an office setting”, Proceedings of the Human Factors and Ergonomics Society Annual Meeting, Vol. 54 No. 4, pp. 448-452.
Chambers, J.M., Cleveland, W.S., Kleiner, B. and Tukey, P.A. (1983), Graphical Methods for Data Analysis, Wadsworth Brooks/Cole, Pacific Grove, CA.
Dieleman, M. and Harnmeijer, J.W. (2006), Improving Health Worker Performance: In Search of Promising Practices, KIT – Royal Tropical Institute; World Health Organization, Geneva.
Distraction (2016), available at: https://en.wikipedia.org/w/index.php?title=Distraction&oldid=708812371 (accessed 6 April 2016).
European Maritime Safety Agency (EMSA) (2016), Annual Overview of Marine Casualties and Incidents 2016, European Maritime Safety Agency, Lisbon, available at: www.emsa.europa.eu/news-a-press-centre/external-news/item/2903-annual-overview-of-marine-casualties-and-incidents-2016.html (accessed 23 January 2017).
Foerster, P.A. (2006), Algebra and Trigonometry: Functions and Applications, Teacher’s ed., Prentice Hall, Upper Saddle River, NJ, p. 573, ISBN 0-13-165711-9.
Geijerstam, K. and Svensson, H. (2008), Ship Collision Risk – An Identification and Evaluation of Important Factors in Collisions with Offshore Installations, Lund, pp. 1-103, available at: https://lup.lub.lu.se/luur/download?func=downloadFile&recordOId=1689121&fileOId=1765259 (accessed 21 October 2015).
IMO (2004), Resolution A.947 (23) Human Element Vision, Principles and Goals for the Organization, available at: www.imo.org/blast/blastDataHelper.asp?data_id=27124&filename=A947%2823%29.pdf (accessed 25 May 2014).
IMO (2010), Final Act of the Conference of Parties to the International Convention on Standards of Training, Certification and Watch keeping for Seafarers, available at: www.imo.org/OurWork/HumanElement/TrainingCertification/Document 32.pdf (accessed 28 May 2014).
Jacobs, H.R. (1994), Mathematics: A Human Endeavor, 3rd ed., W.H. Freeman, p. 547.
Kim, S.J., Chun, J. and Anind, K.D. (2015), “Sensors know when to interrupt you in the car: detecting driver interruptibility through monitoring of peripheral interactions”, CHI ’15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, ACM, New York, NY, pp. 487-496.
Latorella, K.A. (1998), “Effects of modality on interrupted flight deck performance: implications for data link”, Proceedings of the Human Factors and Ergonomics Society Annual Meeting, Vol. 42 No. 1, pp. 87-91, doi:10.1177/154193129804200120.
Mark, G., Gudith, D. and Klocke, U. (2008), “The cost of interrupted work: more speed and stress”, The Proceedings of the Conference on Human Factors in Computing Systems, Florence, 5th-10th April 2008, doi: 10.1145/1357054.1357072.
Medhi, J. (1992), Statistical Methods: An Introductory Text, New Age International, pp. 53-58, ISBN 9788122404197.
Othman, M.K., Fadzil, M.N. and Abdul Rahman, N.S.F. (2015), “The Malaysian seafarers psychological distraction assessment using a TOPSIS method”, International Journal of e-Navigation and Maritime Economy, Vol. 3 No. 5, pp. 40-50.
Othman, M.K., Fadzil, M.N. and Abdul Rahman, N.S.F. (2016), “Examining the potential distraction factors among seafarers’ on board ships using a cause and effect analysis”, 7th International Conference on Postgraduate Education, Shah Alam, 1 December, ISBN: 978-967-0171-64-7.
Post, S.A. and Schumm, J.S. (1997), Executive Learning: Successful Strategies for College Reading and Studying, Prentice Hall, Upper Saddle River, NJ.
Radar Chart (2016), available at: https://en.wikipedia.org/wiki/Radar_chart (accessed 12 May 2016).
Rothblum, A.M. (2000), Human Error and Marine Safety, National Safety Council Congress and Expo, Orlando.
Sanderson, P.M. and Grundgeiger, T. (2015), “How do interruptions affect clinician performance in healthcare? Negotiating fidelity, control, and potential generalizability in the search for answers”, International Journal of Human-Computer Studies, Vol. 79, pp. 85-96, doi:10.1016/j.ijhcs.2014.11.003.
Trafton, G.J. and Monk, C.A. (2007), “Task interruptions”, Reviews of Human Factors and Ergonomics, Vol. 3 No. 1, pp. 111-126, doi:10.1518/155723408X299852.
Hankins, J. (2001), in Hankins, J., Lonsway, R.A.W., Hedrick, C. and Perdue, M.B. (Eds), Infusion Therapy in Clinical Practice, 2nd ed., Saunders, Collingwood, p. 42.
A huge appreciation delivered to Universiti Malaysia Terengganu for providing the research facilities and guidance. Also, a deep gratitude goes to Malaysia Maritime Academy and Malaysian seafarers for the valuable cooperation and participation in the survey.