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I have gained my extensive experience with proven track record of achievements at the professional and academic level by working for governments and international organizations at the national (Australian government), supranational (European Union) and international level (United Nations) in Europe, the USA and Australia.<br /><span class="u-fw700">Supervisors: </span>Prof. Philip Hans Franses for my PhD (The Econometrics of Maritime Safety)<br /><b>Address: </b>Melbourne, Australia<br /><div class="js-profile-less-about u-linkUnstyled u-tcGrayDarker u-textDecorationUnderline u-displayNone">less</div></div></div><div class="suggested-academics-container"><div class="suggested-academics--header"><p class="ds2-5-body-md-bold">Related Authors</p></div><ul class="suggested-user-card-list"><div class="suggested-user-card"><div class="suggested-user-card__avatar social-profile-avatar-container"><a href="https://ntnu-no.academia.edu/BekirSahin"><img class="profile-avatar u-positionAbsolute" 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class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/102628757/Predictive_power_of_inspection_outcomes_for_future_shipping_accidents_an_empirical_appraisal_with_special_attention_for_human_factor_aspects"><img alt="Research paper thumbnail of Predictive power of inspection outcomes for future shipping accidents – an empirical appraisal with special attention for human factor aspects" class="work-thumbnail" src="https://attachments.academia-assets.com/102848679/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/102628757/Predictive_power_of_inspection_outcomes_for_future_shipping_accidents_an_empirical_appraisal_with_special_attention_for_human_factor_aspects">Predictive power of inspection outcomes for future shipping accidents – an empirical appraisal with special attention for human factor aspects</a></div><div class="wp-workCard_item"><span>Maritime Policy &amp; Management</span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This paper investigates whether deficiencies detected during port state control (PSC) inspections...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This paper investigates whether deficiencies detected during port state control (PSC) inspections have predictive power for future accident risk, in addition to other vessel-specific risk factors like ship type, age, size, flag, and owner. The empirical analysis links accidents to past inspection outcomes and is based on data from all around the globe of PSC regimes using harmonized deficiency codes. These codes are aggregated into eight groups related to human factor aspects like crew qualifications, working and living conditions, and fatigue and safety management. This information is integrated by principal components into a single overall deficiency index, which is related to future accident risk by means of logit models. The factor by which accident risk increases for vessels with above average compared to below average deficiency scores is about 6 for total loss, 2 for very serious, 1.5 for serious, and 1.3 for less-serious accidents. Relations between deficiency scores and accident risk are presented in graphical format. The results may be of interest to PSC authorities for targeting inspection areas, to maritime administrations for improving asset allocation based on prediction scenarios connected with vessel traffic data, and to maritime insurers for refining their premium strategies.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="5f599ac01bdfbf45f038293b7b9f4eb4" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":102848679,"asset_id":102628757,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/102848679/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="102628757"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="102628757"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 102628757; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950666"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/95950666/Exploration_of_machine_learning_algorithms_for_maritime_risk_applications"><img alt="Research paper thumbnail of Exploration of machine learning algorithms for maritime risk applications" class="work-thumbnail" src="https://attachments.academia-assets.com/97986081/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/95950666/Exploration_of_machine_learning_algorithms_for_maritime_risk_applications">Exploration of machine learning algorithms for maritime risk applications</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">To manage and pre-empt incident risks effectively by maritime stakeholders, predicted incident pr...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">To manage and pre-empt incident risks effectively by maritime stakeholders, predicted incident probabilities at ship level have different application aspects such as enhanced targeting for ship inspections, improved domain awareness and improving risk exposure assessments for strategic planning and asset allocations to manage risk exposure. Using a unique and comprehensive global dataset from 2014 to 2020 of 1.2 million observations, this study explores 144 model variants from the field of machine learning (18 random forest variants for 8 incident endpoints of interest) with the aim to enhance prediction capabilities to be used in maritime applications. An additional point of interest is to determine and highlight the relative importance of over 500 evaluated covariates. The results differ for each endpoint of interest and confirm that random forest methods improve prediction capabilities, based on a full year of out of sample evaluation. Targeting the top 10% most risky vessels wou...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="43a5423b4b4d83afefb58638999e76f5" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":97986081,"asset_id":95950666,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/97986081/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950666"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950666"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950666; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950665"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/95950665/Measuring_the_effect_of_perceived_corruption_on_detention_and_incident_risk_an_empirical_analysis"><img alt="Research paper thumbnail of Measuring the effect of perceived corruption on detention and incident risk – an empirical analysis" class="work-thumbnail" src="https://attachments.academia-assets.com/97986078/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/95950665/Measuring_the_effect_of_perceived_corruption_on_detention_and_incident_risk_an_empirical_analysis">Measuring the effect of perceived corruption on detention and incident risk – an empirical analysis</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This manuscript uses a global and comprehensive approach based on 1.14 million observations to in...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This manuscript uses a global and comprehensive approach based on 1.14 million observations to investigate whether the effect of corruption can be measured towards safety qualities of vessels. Since safety qualities of vessels are influenced by many factors and the effect of corruption can be confounded by their interactions, a multi-step approach in used at ship. The findings confirm the hypothesis that port states with higher perceived corruption are less likely to detain vessels and that flag states or ship owners located in countries associated with higher perceived corruption are more likely to have very serious incidents as the operating environment might facilitate substandard shipping and weaker enforcement of international conventions or increased operating costs that can influence safety qualities of vessels in economic hardship. The findings also revealed the degree of underreporting for serious incidents by flag states. The results support the establishment of accountabi...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="fda0097881ce751644d219d130786f7d" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":97986078,"asset_id":95950665,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/97986078/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950665"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950665"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950665; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950664"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/95950664/Econometric_Analysis_on_the_Effectiveness_across_Port_State_Control_Regimes_What_are_the_Areas_of_Improvement_for_Inspections"><img alt="Research paper thumbnail of Econometric Analysis on the Effectiveness across Port State Control Regimes:What are the Areas of Improvement for Inspections?" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/95950664/Econometric_Analysis_on_the_Effectiveness_across_Port_State_Control_Regimes_What_are_the_Areas_of_Improvement_for_Inspections">Econometric Analysis on the Effectiveness across Port State Control Regimes:What are the Areas of Improvement for Inspections?</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The lack of trust in the maritime industry has led to a variety of inspections onboard ships that...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The lack of trust in the maritime industry has led to a variety of inspections onboard ships that are performed in the name of safety.This article is based on a combined dataset of port state control inspections and casualties for the time period 1999 to 2004 and identifies areas for improvement of port state control inspections.We use binary logistic regression on a dataset which is constructed of twin ships in order to better filter out effects associated with inspection variables such as deficiencies,time in-between inspections,detention or who inspected the vessel while incorporating a summary of ship’s inspection hi story.The model s suggest that there is some 1ack of fol1ow up on recti f- ying deficiencies that have been found during inspections.In addition, the results identify that the main areas of improvement of inspections are within the ISM code(International Safety Management Code) for tankers and general cargo vessels,ship and cargo operations and machinery and propuls...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950664"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950664"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950664; 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</script> <div class="js-work-strip profile--work_container" data-work-id="95950663"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/95950663/Probabilistic_assessment_of_drifting_MODU_risks"><img alt="Research paper thumbnail of Probabilistic assessment of drifting MODU risks" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/95950663/Probabilistic_assessment_of_drifting_MODU_risks">Probabilistic assessment of drifting MODU risks</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The drifting of mobile offshore drilling units (MODU) due to extreme environmental forcing events...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The drifting of mobile offshore drilling units (MODU) due to extreme environmental forcing events, such as due to the passage of a tropical cyclone, have the potential to result in major damage to the environment or infrastructure in the event of a grounding and/or collision. Accurate understanding of these risks is critical to the regulatory approvals and disaster response strategies for offshore oil and gas projects. Drifting vessel trajectories are caused by a combination of wind, surface current and wave - induced drag forces acting on the MOD as well as the restraining drag forces created by the catenary mooring and anchor system attached to the MODU. DHI&#39;s drifting vessel model is a Lagrangian agent-based model (ABM) that utilizes a quasi-stationary iterative solution to the force and moment balance relationships at each time step to evaluate the steady vessel drift speed and direction for a given combination of environmental forcings. The model also includes a description...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950663"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950663"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950663; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=95950663]").text(description); $(".js-view-count[data-work-id=95950663]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 95950663; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='95950663']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=95950663]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":95950663,"title":"Probabilistic assessment of drifting MODU risks","internal_url":"https://www.academia.edu/95950663/Probabilistic_assessment_of_drifting_MODU_risks","owner_id":37052266,"coauthors_can_edit":true,"owner":{"id":37052266,"first_name":"Sabine","middle_initials":null,"last_name":"Knapp","page_name":"SabineKnapp","domain_name":"eur","created_at":"2015-10-27T03:30:01.332-07:00","display_name":"Sabine Knapp","url":"https://eur.academia.edu/SabineKnapp"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950662"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/95950662/Quantification_and_Analysis_of_Risk_Exposure_in_the_Maritime_Industry_Averted_Incident_Costs_Due_to_Inspections_and_the_Effect_of_SARS_Cov_2_COVID_19_"><img alt="Research paper thumbnail of Quantification and Analysis of Risk Exposure in the Maritime Industry: Averted Incident Costs Due to Inspections and the Effect of SARS-Cov-2 (COVID-19)" class="work-thumbnail" src="https://attachments.academia-assets.com/97986076/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/95950662/Quantification_and_Analysis_of_Risk_Exposure_in_the_Maritime_Industry_Averted_Incident_Costs_Due_to_Inspections_and_the_Effect_of_SARS_Cov_2_COVID_19_">Quantification and Analysis of Risk Exposure in the Maritime Industry: Averted Incident Costs Due to Inspections and the Effect of SARS-Cov-2 (COVID-19)</a></div><div class="wp-workCard_item"><span>Safety</span><span>, 2021</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Shipping provides essential services even during global pandemics such as SARS-CoV-2 (COVID-19). ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Shipping provides essential services even during global pandemics such as SARS-CoV-2 (COVID-19). The present approach estimates the monetary value at risk (MVR) at the global and regional level for the world fleet and quantifies the amount of averted incident costs due to inspections. It also provides an indication of the effect of COVID-19 on both. This information can help maritime stakeholders to better understand their risk exposure and improve mitigation strategies. The analysis is based on the global fleet, using a comprehensive combination of data. The analysis confirms the importance to estimate all components at ship level, as safety qualities differ, and each vessel benefits differently from an inspection. Estimates of MVR were slightly higher than global insurance premiums with USD 13.7 to 17.8 billion. Over half of the MVR was due to other marine liabilities and hull and machinery, with cruise vessels leading to loss of life and injuries and oil tankers leading to pollut...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="6128eb9d218e7307313373fe2add7d0f" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":97986076,"asset_id":95950662,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/97986076/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950662"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950662"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950662; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950661"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/95950661/Dynamics_in_the_dry_bulk_market"><img alt="Research paper thumbnail of Dynamics in the dry bulk market" class="work-thumbnail" src="https://attachments.academia-assets.com/97986141/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/95950661/Dynamics_in_the_dry_bulk_market">Dynamics in the dry bulk market</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Recent dynamics in iron ore markets are driven by rapid changes in economic activities that affec...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Recent dynamics in iron ore markets are driven by rapid changes in economic activities that affect commodity markets, trade flows, and shipping activities. Time series models for the relation between these variables in Southeast Asia and the Australasian region are supplemented with models for safety and pollution risk. Steel production in China, Japan, and South Korea is related to iron ore exports and vessel activity in Australia, with an estimated time lag of about two months. The Purchasing Manager Index, which is popular among traders as indicator of economic activity, is found to have predictive power both for steel production and for iron ore exports. The growth in economic activity and vessel movements is associated with significantly higher risks for ship accidents and pollution.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="76a06217275de0eee303750e6774d24a" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":97986141,"asset_id":95950661,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/97986141/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950661"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950661"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950661; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950660"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/95950660/A_multi_layered_risk_estimation_routine_for_strategic_planning_and_operations_for_the_maritime_industry"><img alt="Research paper thumbnail of A multi-layered risk estimation routine for strategic planning and operations for the maritime industry" class="work-thumbnail" src="https://attachments.academia-assets.com/97986074/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/95950660/A_multi_layered_risk_estimation_routine_for_strategic_planning_and_operations_for_the_maritime_industry">A multi-layered risk estimation routine for strategic planning and operations for the maritime industry</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Maritime regulators and port authorities require the ability to predict risk exposure for strateg...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Maritime regulators and port authorities require the ability to predict risk exposure for strategic planning aspects to optimize asset allocation, mitigate and prevent incidents. This article builds on previous work to develop the strategic planning component and introduces the concept of a multilayered risk estimation framework (MLREF) for strategic planning and operations. The framework accounts for most of the risk factors such as ship specific risk, vessel traffic densities and met ocean conditions and allows the integration of the effect of risk control option and a location specific spatial rate ratio to allow for micro level risk assessments. Both, the macro (eg. covering larger geographic areas or EEZ) and micro level application (eg. passage way, particular route of interest) of MLREF was tested via a pilot study for the Australian region using a comprehensive and unique combination of dataset. The underlying routine towards the development of a strategic planning tool was ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="2115e55b058b47fee40964ea0f24d2e6" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":97986074,"asset_id":95950660,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/97986074/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950660"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950660"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950660; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "2115e55b058b47fee40964ea0f24d2e6" } } $('.js-work-strip[data-work-id=95950660]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":95950660,"title":"A multi-layered risk estimation routine for strategic planning and operations for the maritime industry","internal_url":"https://www.academia.edu/95950660/A_multi_layered_risk_estimation_routine_for_strategic_planning_and_operations_for_the_maritime_industry","owner_id":37052266,"coauthors_can_edit":true,"owner":{"id":37052266,"first_name":"Sabine","middle_initials":null,"last_name":"Knapp","page_name":"SabineKnapp","domain_name":"eur","created_at":"2015-10-27T03:30:01.332-07:00","display_name":"Sabine Knapp","url":"https://eur.academia.edu/SabineKnapp"},"attachments":[{"id":97986074,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/97986074/thumbnails/1.jpg","file_name":"EI2017-02-Report.pdf","download_url":"https://www.academia.edu/attachments/97986074/download_file","bulk_download_file_name":"A_multi_layered_risk_estimation_routine.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/97986074/EI2017-02-Report-libre.pdf?1675076975=\u0026response-content-disposition=attachment%3B+filename%3DA_multi_layered_risk_estimation_routine.pdf\u0026Expires=1739823330\u0026Signature=HuVg-Sp2UkK3xAcpbNG3M~-m7GKH7XUPL3mVZI6i0e1FfQ-Z2mgJK3LpjxLS9~9Gq3KTQt5QqgJPy0f5LG65fMX1dOiVOPL1E7r3-Q70gqCJNPS53g2XFNGPH5M0Of3W6wwrbrQT3SGLETzRY8KlBAaZTl0cxbKB~esSW83ENYt7En25gf4R5BrV0AR4GomOXrdG63YjNu1zYt-EEA9t7JdBrSDOF04mPxGXpU0HfO3SmiXQzkckGbyqWwQ-Fi~fexVETA~PMNPxaUxOwtFxM3E04SnK4QVjjNw8jXWG0PVN-KuusbyLYnQl4gZpmvBbjgd2KZNnuvD6O6p~Mrxgyg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":97986075,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/97986075/thumbnails/1.jpg","file_name":"EI2017-02-Report.pdf","download_url":"https://www.academia.edu/attachments/97986075/download_file","bulk_download_file_name":"A_multi_layered_risk_estimation_routine.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/97986075/EI2017-02-Report-libre.pdf?1675076971=\u0026response-content-disposition=attachment%3B+filename%3DA_multi_layered_risk_estimation_routine.pdf\u0026Expires=1739823330\u0026Signature=Pp5KgIbY5uZ~u42b4lYs6BwoN-NPa1YJk7mMkguTRwGeA6uIHYWPx5ESU4LPpXrXTt7D5wfCGvjF3rj~p6j~lyq-LGHTFQnq1x5Fpi55XGLcg8GriU46qYl~mTHw5mGRNn8UhBlaDK-~6XBgIe0OP8Oc6gWoRGGg3DmJElFEYgZ1GTBTi0wo2SQK3KN2LIYBiKOFUCBfi5Dz5wBLIG7wuY94ysIHi~w8ZD3Kj~~bUZ0emn8p8OMhzwjDvn0HluYbzn0tSlnukAz5MXXu0IRQBTeFjWNqtzBGDFJwI0fBYdaGljQhQzsPpeQlHtV~V2-YKtlHujVbSxYzW7EREZ3lcQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950658"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/95950658/Analysis_of_ship_life_cycles_The_impact_of_economic_cycles_and_ship_inspections"><img alt="Research paper thumbnail of Analysis of ship life cycles—The impact of economic cycles and ship inspections" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/95950658/Analysis_of_ship_life_cycles_The_impact_of_economic_cycles_and_ship_inspections">Analysis of ship life cycles—The impact of economic cycles and ship inspections</a></div><div class="wp-workCard_item"><span>Marine Policy</span><span>, 2009</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Due to the shipping industry&amp;amp;amp;#39;s international legal framework, there are loopholes...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Due to the shipping industry&amp;amp;amp;#39;s international legal framework, there are loopholes in the system, which can increase the risk of incidents with high economic costs due to the substandard operation of vessels. This article uses duration analysis and through the creation of ship life cycles provides insight into the effectiveness of inspections on prolonging ship lives. 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The appendix as well as an electronic version of the thesis can be found under the following location: <a href="http://hdl.handle.net/1765/7913" rel="nofollow">http://hdl.handle.net/1765/7913</a> for further reference. All rights reserved. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950654"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/95950654/Estimated_incident_cost_savings_in_shipping_due_to_inspections"><img alt="Research paper thumbnail of Estimated incident cost savings in shipping due to inspections" class="work-thumbnail" src="https://attachments.academia-assets.com/97986163/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/95950654/Estimated_incident_cost_savings_in_shipping_due_to_inspections">Estimated incident cost savings in shipping due to inspections</a></div><div class="wp-workCard_item"><span>Accident Analysis &amp; Prevention</span><span>, 2011</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The effectiveness of safety inspections has been analysed from various angles, but until now, rel...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The effectiveness of safety inspections has been analysed from various angles, but until now, relatively little attention has been given to translate risk reduction into incident cost savings. This paper quantifies estimated cost savings based on port state control inspections and industry vetting inspections. It is based on a unique dataset of 515,194 ship arrivals and inspections from the United States of America and Australia, and inspections of three industry vetting inspection regimes, for the time period 2002 to 2007. The risk reducing effect of inspections is estimated by means of duration models, in terms of inspection gains based on the probability of survival. The results suggest average total estimated cost savings in the range of USD 74 to 192 thousand (median USD 19 to 46 thousand) owing to reduced risk of total loss due to a port state control inspection. Cost savings for industry inspections are found to be even higher, especially for tankers. The savings vary by type, age and size of the ship. The benefits of an inspection are in general larger for older and larger vessels, and also for vessels with undefined flags and unknown classification societies. As inspection costs are relatively low in comparison to potential cost savings, the results underline the importance in determining high risk ships to prevent costs due to total loss of ships.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="5c42ea5f6cf557cc8071babe34e1da74" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":97986163,"asset_id":95950654,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/97986163/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950654"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950654"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950654; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950540"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/95950540/Empirical_analysis_of_the_effectiveness_of_the_legislative_framework_in_the_maritime_industry"><img alt="Research paper thumbnail of Empirical analysis of the effectiveness of the legislative framework in the maritime industry" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/95950540/Empirical_analysis_of_the_effectiveness_of_the_legislative_framework_in_the_maritime_industry">Empirical analysis of the effectiveness of the legislative framework in the maritime industry</a></div><div class="wp-workCard_item"><span>Marine Policy</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950540"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950540"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950540; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=95950540]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":95950540,"title":"Empirical analysis of the effectiveness of the legislative framework in the maritime industry","internal_url":"https://www.academia.edu/95950540/Empirical_analysis_of_the_effectiveness_of_the_legislative_framework_in_the_maritime_industry","owner_id":37052266,"coauthors_can_edit":true,"owner":{"id":37052266,"first_name":"Sabine","middle_initials":null,"last_name":"Knapp","page_name":"SabineKnapp","domain_name":"eur","created_at":"2015-10-27T03:30:01.332-07:00","display_name":"Sabine Knapp","url":"https://eur.academia.edu/SabineKnapp"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="56745770"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/56745770/Measuring_the_effect_of_perceived_corruption_on_detention_and_incident_risk_in_the_maritime_industry_An_empirical_analysis"><img alt="Research paper thumbnail of Measuring the effect of perceived corruption on detention and incident risk in the maritime industry – An empirical analysis" class="work-thumbnail" src="https://attachments.academia-assets.com/71979446/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/56745770/Measuring_the_effect_of_perceived_corruption_on_detention_and_incident_risk_in_the_maritime_industry_An_empirical_analysis">Measuring the effect of perceived corruption on detention and incident risk in the maritime industry – An empirical analysis</a></div><div class="wp-workCard_item"><span>Maritime Transport Research</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="a1214d0cf7c526eef2173f49e5465e88" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71979446,"asset_id":56745770,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71979446/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="56745770"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="56745770"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 56745770; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=56745770]").text(description); $(".js-view-count[data-work-id=56745770]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 56745770; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='56745770']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "a1214d0cf7c526eef2173f49e5465e88" } } $('.js-work-strip[data-work-id=56745770]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":56745770,"title":"Measuring the effect of perceived corruption on detention and incident risk in the maritime industry – An empirical analysis","internal_url":"https://www.academia.edu/56745770/Measuring_the_effect_of_perceived_corruption_on_detention_and_incident_risk_in_the_maritime_industry_An_empirical_analysis","owner_id":37052266,"coauthors_can_edit":true,"owner":{"id":37052266,"first_name":"Sabine","middle_initials":null,"last_name":"Knapp","page_name":"SabineKnapp","domain_name":"eur","created_at":"2015-10-27T03:30:01.332-07:00","display_name":"Sabine Knapp","url":"https://eur.academia.edu/SabineKnapp"},"attachments":[{"id":71979446,"title":"","file_type":"txt","scribd_thumbnail_url":"https://attachments.academia-assets.com/71979446/thumbnails/1.jpg","file_name":"PII_S2666822X21000228.txt","download_url":"https://www.academia.edu/attachments/71979446/download_file","bulk_download_file_name":"Measuring_the_effect_of_perceived_corrup.txt","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71979446/PII_S2666822X21000228.txt?1738436858=\u0026response-content-disposition=attachment%3B+filename%3DMeasuring_the_effect_of_perceived_corrup.txt\u0026Expires=1739823330\u0026Signature=Xfzy7HYt-EUo4F4wWbeFkRkUV9mcnHl3S5ztnqH6V-h1DNSaMNyI7MC4y8T6rIhv~WvIcv7j~SfjAyDDyRINUxxIbZnsioLLH7vPXR2wHJO42dsiryQtrvTQBihoszzTOu2Fmm-UiI9qRV7CPHbMiSXm8~X2DvvJ4YIZeYpCWqGLvi53Wvj6BRtcwH7NbnArKDRLzZv2nW4DYrayNB3QmYY60GMgbAZcUbAL4TEhPhURjBWYJssSez92giUlZvvsYf6NAY3SQHDQvdKHo03iOOtPiOEgmglbLvwKIwevKzw-gtCWoHW7jQmaght25Fq1XYoRxka32-kEwkfub-dzIg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="56745769"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/56745769/Shipping_inspections_detentions_and_incidents_an_empirical_analysis_of_risk_dimensions"><img alt="Research paper thumbnail of Shipping inspections, detentions, and incidents: an empirical analysis of risk dimensions" class="work-thumbnail" src="https://attachments.academia-assets.com/71979447/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/56745769/Shipping_inspections_detentions_and_incidents_an_empirical_analysis_of_risk_dimensions">Shipping inspections, detentions, and incidents: an empirical analysis of risk dimensions</a></div><div class="wp-workCard_item"><span>Maritime Policy & Management</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Inspections play a key role in keeping vessels safe. Inspection authorities employ different poli...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Inspections play a key role in keeping vessels safe. Inspection authorities employ different policies to decide which vessels to inspect, including type of vessel, age, and flag. Attention for vessel history is usually restricted only to past detentions. This paper demonstrates that the correlation between the probabilities of detention and (very serious and serious) incidents is very low and that proactive prevention of future incidents is improved by accounting for both risk dimensions, that is, by combining past incident and detention information for targeting highrisk vessels for inspection. Five combined methods are presented to classify vessels based on these two risk dimensions, each of which involves extensive sets of factors. These combined classification methods have predictive power for future incidents. Depending on the applied inspection rate, incorporation of incident risk improves inspection hit rates for vessels with future incidents by 30-50% compared to using only detention information. It is recommended to focus on vessels where both risks are relatively high. A practical example shows how the methods can be applied for inspection selection and for prioritizing inspection areas defined in terms of eight risk domains that include collisions, groundings, engine and hull failures, loss of life, fire, and pollution.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="805238e3589a86131e05fe39683d08d8" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71979447,"asset_id":56745769,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71979447/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="56745769"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="56745769"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 56745769; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=56745769]").text(description); $(".js-view-count[data-work-id=56745769]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 56745769; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='56745769']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "805238e3589a86131e05fe39683d08d8" } } $('.js-work-strip[data-work-id=56745769]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":56745769,"title":"Shipping inspections, detentions, and incidents: an empirical analysis of risk dimensions","internal_url":"https://www.academia.edu/56745769/Shipping_inspections_detentions_and_incidents_an_empirical_analysis_of_risk_dimensions","owner_id":37052266,"coauthors_can_edit":true,"owner":{"id":37052266,"first_name":"Sabine","middle_initials":null,"last_name":"Knapp","page_name":"SabineKnapp","domain_name":"eur","created_at":"2015-10-27T03:30:01.332-07:00","display_name":"Sabine Knapp","url":"https://eur.academia.edu/SabineKnapp"},"attachments":[{"id":71979447,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71979447/thumbnails/1.jpg","file_name":"03088839.2019.pdf","download_url":"https://www.academia.edu/attachments/71979447/download_file","bulk_download_file_name":"Shipping_inspections_detentions_and_inci.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71979447/03088839.2019-libre.pdf?1633768281=\u0026response-content-disposition=attachment%3B+filename%3DShipping_inspections_detentions_and_inci.pdf\u0026Expires=1739823330\u0026Signature=E8HM4yT8uzO2MkP1wJBHLXNCExSk0xNkEZwYf6Ef4fY01e-2BHLEfdvAUeAdGcRfPYsDsYRF7UI4k~CLN4qiCpJU3syw2Xjnq96sFDGTgdv1MRgZVUmUYsZkT8FYCIlO6RK90BPz-m7bx6fp2QoQRGK6IclXSfdGmbF-b2ODYrYtFI3XDOr-ng3oX5FXHYFF~eYub-dI1n8K~ELEqBsdKNjn9l6iUtKBat0Mk4jZky4C1eqFMuUDxkAuaEuJpSQMr2qRBZvLeaqBvSvMjHMv6M79Mmt-Dv05jdRgK22KcZ3ExaD3RiUc5gdzkrGDRqlRZn0wTiR8FzuKDvs5~5RNtA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":71979445,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71979445/thumbnails/1.jpg","file_name":"03088839.2019.pdf","download_url":"https://www.academia.edu/attachments/71979445/download_file","bulk_download_file_name":"Shipping_inspections_detentions_and_inci.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71979445/03088839.2019-libre.pdf?1633768282=\u0026response-content-disposition=attachment%3B+filename%3DShipping_inspections_detentions_and_inci.pdf\u0026Expires=1739823330\u0026Signature=QJGoqopibVPmXOaDohp0XmZjh5nTsqJ7P91Hqw~Hkt~W5EMTOCzaOzm7gPZ40Iis~EsIYyzEvlpO8e~JMSoNsYcNyPgBuAukIPaaT-8NyfKvLyYihFoau5-~mKUIvrgI2X~-kLBhLyM~ebjizlkrmpzijfxWfC-DpsGPDJPkaQmOZCq2hA7Tsq9IWMMrmbF-vuNI9xYnQ-Lh16A6JWXX7zMCY7NMGoPh756LsVEE~GxycUK8IZibfeZZnaEytbp~FwUn5xKXFsEjl6a2KcCAU1P4lN-m4f4LG9SKHinJ-DuQkhi3YT--UR0r1SgsoYL~gpsu5p0Dm1~OAgXXO1UAZg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="56745768"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/56745768/Predicting_Traffic_and_Risk_Exposure_in_the_Maritime_Industry"><img alt="Research paper thumbnail of Predicting Traffic and Risk Exposure in the Maritime Industry" class="work-thumbnail" src="https://attachments.academia-assets.com/71979444/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/56745768/Predicting_Traffic_and_Risk_Exposure_in_the_Maritime_Industry">Predicting Traffic and Risk Exposure in the Maritime Industry</a></div><div class="wp-workCard_item"><span>Safety</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Maritime regulators, port authorities, and industry require the ability to predict risk exposure ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Maritime regulators, port authorities, and industry require the ability to predict risk exposure of shipping activities at a micro and macro level to optimize asset allocation and to mitigate and prevent incidents. This article introduces the concept of a strategic planning tool by making use of the multi-layered risk estimation framework (MLREF), which accounts for ship specific risk, vessel traffic densities, and meets ocean conditions at the macro level. This article’s main contribution is to provide a traffic and risk exposure prediction routine that allows the traffic forecast to be distributed across the shipping route network to allow for predicting scenarios at the macro level (e.g., covering larger geographic areas) and micro level (e.g., passage way, particular route of interest). In addition, the micro level is introduced by providing a theoretical idea to integrate location specific spatial rate ratios along with the effect of the risk control option to perform sensitivi...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="a9b10eabc4759249f9322a2de42cbccf" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71979444,"asset_id":56745768,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71979444/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="56745768"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="56745768"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 56745768; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="56745767"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/56745767/Evaluation_of_total_risk_exposure_and_insurance_premiums_in_the_maritime_industry"><img alt="Research paper thumbnail of Evaluation of total risk exposure and insurance premiums in the maritime industry" class="work-thumbnail" src="https://attachments.academia-assets.com/71979520/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/56745767/Evaluation_of_total_risk_exposure_and_insurance_premiums_in_the_maritime_industry">Evaluation of total risk exposure and insurance premiums in the maritime industry</a></div><div class="wp-workCard_item"><span>Transportation Research Part D: Transport and Environment</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This study provides an empirical evaluation of maritime risk exposure expressed as the monetary v...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This study provides an empirical evaluation of maritime risk exposure expressed as the monetary value at risk (MVR), which incorporates life of crew and passengers, vessel value of hull and machinery, carried cargo value, third party liabilities, and potential external damages like pollution. MVR is based on individual safety quality data of about 130,000 vessels, on insurable values related to various potential damages, and on proxies for fractions of values lost at incidents. MVR provides a tool to enhance strategic planning of maritime administrations and insurance providers, which is illustrated by a high level comparison of annual risk exposure with insurance premiums for 2010 to 2014. The analysis reveals a global annual insurable value of 30.6 trillion USD with associated annual MVR of 38.8 billion USD for very serious and serious incidents. Although oil tankers show the highest risk exposure (1.75 million USD per tanker per year), safety qualities are found to be best for this ship type (1.4% annual incident risk) and worst for container vessels (2.8%). Annual growth rates in total risk exposure are mostly positive with highest value for dry bulk carriers (27.8%), whereas risk exposure tends to decline for pollution of oil tankers (-2.0%) and passenger vessels (-11.3%), and for loss of life of oil tankers (-1.9%) and dry bulk carriers (-1.4%) but not of passenger vessels (6.9%). A comparison across administrative dimensions reveals that most risk exposure lies with old open registries and with beneficial owners and DoC companies located in high income countries. Comparison with global insurance premiums suggests reasonably adequate coverage of maritime risks (excluding cargo). Our analysis indicates under-insurance of risk by around 5%, corresponding to about 1 billion USD per year, with some uncertainties remaining for the actual loss fractions of the various involved damages.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="81bd8b9078ea8d3ad46a4faa2c6ce183" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71979520,"asset_id":56745767,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71979520/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="56745767"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="56745767"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 56745767; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "81bd8b9078ea8d3ad46a4faa2c6ce183" } } $('.js-work-strip[data-work-id=56745767]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":56745767,"title":"Evaluation of total risk exposure and insurance premiums in the maritime industry","internal_url":"https://www.academia.edu/56745767/Evaluation_of_total_risk_exposure_and_insurance_premiums_in_the_maritime_industry","owner_id":37052266,"coauthors_can_edit":true,"owner":{"id":37052266,"first_name":"Sabine","middle_initials":null,"last_name":"Knapp","page_name":"SabineKnapp","domain_name":"eur","created_at":"2015-10-27T03:30:01.332-07:00","display_name":"Sabine Knapp","url":"https://eur.academia.edu/SabineKnapp"},"attachments":[{"id":71979520,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71979520/thumbnails/1.jpg","file_name":"EI2016-25.pdf","download_url":"https://www.academia.edu/attachments/71979520/download_file","bulk_download_file_name":"Evaluation_of_total_risk_exposure_and_in.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71979520/EI2016-25-libre.pdf?1633768281=\u0026response-content-disposition=attachment%3B+filename%3DEvaluation_of_total_risk_exposure_and_in.pdf\u0026Expires=1739823330\u0026Signature=P0aGSLZ5nPXO42V2xp6luSYSOssbU5mNzK0ZyPqJheERtDAqN8VDP4Nsplmp9hQ20H6ZFMwXNYCBJ6FNcoyA6iP0fU66zshV1IvvTCtabZDwcsL0KjtzI-vtg1L85PAje1qB9qC2juaI6ORKwUSHHkKWZUYdZSoVzAsMbGDccF~O4oVFQYzL59O8YyhFKipxEcDugS5qXfPYds-X0FFP4Y-iCSKwZwkrRluHW2S4UpW3saDw1tVslgVyrtl5wNwgrAerT6hN0IVlY0LL4RLzRJ9Og5s7aDcbLZ-9eexHdBXpsS0Nd3E6jfAZ8aVbZJsjC7tDlBthrgsgR4R4Ujq5bA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="56745766"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/56745766/An_integrated_risk_estimation_methodology_Ship_specific_incident_type_risk"><img alt="Research paper thumbnail of An integrated risk estimation methodology: Ship specific incident type risk" class="work-thumbnail" src="https://attachments.academia-assets.com/71979523/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/56745766/An_integrated_risk_estimation_methodology_Ship_specific_incident_type_risk">An integrated risk estimation methodology: Ship specific incident type risk</a></div><div class="wp-workCard_item"><span>Report Econometric Institute Erasmus University Rotterdam</span><span>, Apr 1, 2013</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Shipping activity has increased worldwide, including parts of Australia, and maritime administrat...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Shipping activity has increased worldwide, including parts of Australia, and maritime administrations are trying to gain a better understanding of total risk exposure in order to mitigate risk. Total risk exposure integrates risk at the individual ship level, risk due to vessel traffic densities, physical environmental criteria, and environmental sensitivities. A comprehensive and robust risk exposure metric can be beneficial to maritime administrations to enhance mitigation of potential harm and reduce vulnerability to the marine environment as well as to safeguard lives and property. This report outlines an integrated methodology to estimate total risk exposure, with specific attention for the ship specific risk for different types of incident. Some related application aspects of the models are discussed.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="e5530faedd0379c0616ad5086467962d" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71979523,"asset_id":56745766,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71979523/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="56745766"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="56745766"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 56745766; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "e5530faedd0379c0616ad5086467962d" } } $('.js-work-strip[data-work-id=56745766]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":56745766,"title":"An integrated risk estimation methodology: Ship specific incident type risk","internal_url":"https://www.academia.edu/56745766/An_integrated_risk_estimation_methodology_Ship_specific_incident_type_risk","owner_id":37052266,"coauthors_can_edit":true,"owner":{"id":37052266,"first_name":"Sabine","middle_initials":null,"last_name":"Knapp","page_name":"SabineKnapp","domain_name":"eur","created_at":"2015-10-27T03:30:01.332-07:00","display_name":"Sabine Knapp","url":"https://eur.academia.edu/SabineKnapp"},"attachments":[{"id":71979523,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71979523/thumbnails/1.jpg","file_name":"An_integrated_risk_estimation_methodolog20211009-18159-gsxuv6.pdf","download_url":"https://www.academia.edu/attachments/71979523/download_file","bulk_download_file_name":"An_integrated_risk_estimation_methodolog.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71979523/An_integrated_risk_estimation_methodolog20211009-18159-gsxuv6.pdf?1738436859=\u0026response-content-disposition=attachment%3B+filename%3DAn_integrated_risk_estimation_methodolog.pdf\u0026Expires=1739823330\u0026Signature=MMnORQQ~GzPOEW0SmvblYRvZG~x57xwn~2QvJrwlTwBFtie3OLZrrYGGDWwmCAI~~Zkp7YWM2fifI44fXzUcAJRLoTZPEUK0CnLtoWs9rbOdM5oQMFBiTqWvXn6-xlVGo~6EPMCRsDqQ40MJ83oNbq8kr0pbFJf61WpAPeovOdm5DBPx7UHRc3LVpSJ2mn~zmcnxXEfcyATT-ee2yvb2jqOtLT12K3ZVuhLqMc3euhvxXtepXiNPez~0pZWfbxS4kcBCxGOtRezvcj0zUp526RB~jZEPOa7dRvz0S8WGjcggrZvDUJvtKsgM~ANg91Nd1JN7bow9oihYOKUgDW-CpA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="56745765"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/56745765/Assessing_ecological_sensitivities_of_marine_assets_to_oil_spills_by_means_of_expert_knowledge"><img alt="Research paper thumbnail of Assessing ecological sensitivities of marine assets to oil spills by means of expert knowledge" class="work-thumbnail" src="https://attachments.academia-assets.com/71979442/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/56745765/Assessing_ecological_sensitivities_of_marine_assets_to_oil_spills_by_means_of_expert_knowledge">Assessing ecological sensitivities of marine assets to oil spills by means of expert knowledge</a></div><div class="wp-workCard_item"><span>F1000posters</span><span>, Sep 24, 2014</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="5f63746d0fabe339581ff07b454ac844" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71979442,"asset_id":56745765,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71979442/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="56745765"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="56745765"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 56745765; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="56745712"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/56745712/Improved_Strategies_for_the_Maritime_Industry_to_Target_Vessels_for_Inspection_and_to_Select_Inspection_Priority_Areas"><img alt="Research paper thumbnail of Improved Strategies for the Maritime Industry to Target Vessels for Inspection and to Select Inspection Priority Areas" class="work-thumbnail" src="https://attachments.academia-assets.com/71979379/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/56745712/Improved_Strategies_for_the_Maritime_Industry_to_Target_Vessels_for_Inspection_and_to_Select_Inspection_Priority_Areas">Improved Strategies for the Maritime Industry to Target Vessels for Inspection and to Select Inspection Priority Areas</a></div><div class="wp-workCard_item"><span>Safety</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Inspection authorities such as the Port State Control Memoranda of Understanding use different po...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Inspection authorities such as the Port State Control Memoranda of Understanding use different policies and targeting methods to select vessels for inspections and rely primarily on past inspection outcomes. One of the main goals of inspections is to improve the safety quality of vessels and to reduce the probability of future incidents. This study shows there is room for improvement in targeting vessels for inspections and in determining vessel-specific inspection priority areas (e.g., bridge management versus machinery related items). For the year 2018, sixty percent of vessels that experienced very serious or serious (VSS) incidents were not selected for inspection up to three months prior to the incident and forty percent of the vessels that were inspected still had incidents of which only four percent were detained. Furthermore, one can observe a very low correlation (−0.04) between the probabilities of detention and incidents (VSS) for the year 2018. The proposed approach trea...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="0a70962b0f47a0d97ba6298d20a29cc7" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71979379,"asset_id":56745712,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71979379/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="56745712"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="56745712"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 56745712; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="33091453"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/33091453/Ship_inspection_strategies_Effects_on_maritime_safety_and_environmental_protection"><img alt="Research paper thumbnail of Ship inspection strategies: Effects on maritime safety and environmental protection" class="work-thumbnail" src="https://attachments.academia-assets.com/53190646/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/33091453/Ship_inspection_strategies_Effects_on_maritime_safety_and_environmental_protection">Ship inspection strategies: Effects on maritime safety and environmental protection</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Global trade depends for a large part on maritime transport, and safe ships are needed not only t...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Global trade depends for a large part on maritime transport, and safe ships are needed not only to protect precious cargo but also to prevent environmental damage. Flag state and port state authorities spend much effort in ship safety inspections to ensure a minimum safety level and to prevent casualties. This paper investigates the safety gains of current inspection rules as well as options for further improvement. The analysis is based on a dataset of over four hundred thousand ship arrivals originating from some important trading nations between 2002 and 2007, complemented with data on port state control and industry inspections and casualties.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="7525b5f662655f38242c84b596a00170" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":53190646,"asset_id":33091453,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/53190646/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="33091453"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="33091453"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 33091453; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> </div><div class="profile--tab_content_container js-tab-pane tab-pane" data-section-id="3855779" id="papers"><div class="js-work-strip profile--work_container" data-work-id="102628757"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/102628757/Predictive_power_of_inspection_outcomes_for_future_shipping_accidents_an_empirical_appraisal_with_special_attention_for_human_factor_aspects"><img alt="Research paper thumbnail of Predictive power of inspection outcomes for future shipping accidents – an empirical appraisal with special attention for human factor aspects" class="work-thumbnail" src="https://attachments.academia-assets.com/102848679/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/102628757/Predictive_power_of_inspection_outcomes_for_future_shipping_accidents_an_empirical_appraisal_with_special_attention_for_human_factor_aspects">Predictive power of inspection outcomes for future shipping accidents – an empirical appraisal with special attention for human factor aspects</a></div><div class="wp-workCard_item"><span>Maritime Policy &amp; Management</span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This paper investigates whether deficiencies detected during port state control (PSC) inspections...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This paper investigates whether deficiencies detected during port state control (PSC) inspections have predictive power for future accident risk, in addition to other vessel-specific risk factors like ship type, age, size, flag, and owner. The empirical analysis links accidents to past inspection outcomes and is based on data from all around the globe of PSC regimes using harmonized deficiency codes. These codes are aggregated into eight groups related to human factor aspects like crew qualifications, working and living conditions, and fatigue and safety management. This information is integrated by principal components into a single overall deficiency index, which is related to future accident risk by means of logit models. The factor by which accident risk increases for vessels with above average compared to below average deficiency scores is about 6 for total loss, 2 for very serious, 1.5 for serious, and 1.3 for less-serious accidents. Relations between deficiency scores and accident risk are presented in graphical format. The results may be of interest to PSC authorities for targeting inspection areas, to maritime administrations for improving asset allocation based on prediction scenarios connected with vessel traffic data, and to maritime insurers for refining their premium strategies.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="5f599ac01bdfbf45f038293b7b9f4eb4" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":102848679,"asset_id":102628757,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/102848679/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="102628757"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="102628757"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 102628757; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950666"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/95950666/Exploration_of_machine_learning_algorithms_for_maritime_risk_applications"><img alt="Research paper thumbnail of Exploration of machine learning algorithms for maritime risk applications" class="work-thumbnail" src="https://attachments.academia-assets.com/97986081/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/95950666/Exploration_of_machine_learning_algorithms_for_maritime_risk_applications">Exploration of machine learning algorithms for maritime risk applications</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">To manage and pre-empt incident risks effectively by maritime stakeholders, predicted incident pr...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">To manage and pre-empt incident risks effectively by maritime stakeholders, predicted incident probabilities at ship level have different application aspects such as enhanced targeting for ship inspections, improved domain awareness and improving risk exposure assessments for strategic planning and asset allocations to manage risk exposure. Using a unique and comprehensive global dataset from 2014 to 2020 of 1.2 million observations, this study explores 144 model variants from the field of machine learning (18 random forest variants for 8 incident endpoints of interest) with the aim to enhance prediction capabilities to be used in maritime applications. An additional point of interest is to determine and highlight the relative importance of over 500 evaluated covariates. The results differ for each endpoint of interest and confirm that random forest methods improve prediction capabilities, based on a full year of out of sample evaluation. Targeting the top 10% most risky vessels wou...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="43a5423b4b4d83afefb58638999e76f5" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":97986081,"asset_id":95950666,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/97986081/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950666"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950666"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950666; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950665"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/95950665/Measuring_the_effect_of_perceived_corruption_on_detention_and_incident_risk_an_empirical_analysis"><img alt="Research paper thumbnail of Measuring the effect of perceived corruption on detention and incident risk – an empirical analysis" class="work-thumbnail" src="https://attachments.academia-assets.com/97986078/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/95950665/Measuring_the_effect_of_perceived_corruption_on_detention_and_incident_risk_an_empirical_analysis">Measuring the effect of perceived corruption on detention and incident risk – an empirical analysis</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This manuscript uses a global and comprehensive approach based on 1.14 million observations to in...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This manuscript uses a global and comprehensive approach based on 1.14 million observations to investigate whether the effect of corruption can be measured towards safety qualities of vessels. Since safety qualities of vessels are influenced by many factors and the effect of corruption can be confounded by their interactions, a multi-step approach in used at ship. The findings confirm the hypothesis that port states with higher perceived corruption are less likely to detain vessels and that flag states or ship owners located in countries associated with higher perceived corruption are more likely to have very serious incidents as the operating environment might facilitate substandard shipping and weaker enforcement of international conventions or increased operating costs that can influence safety qualities of vessels in economic hardship. The findings also revealed the degree of underreporting for serious incidents by flag states. The results support the establishment of accountabi...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="fda0097881ce751644d219d130786f7d" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":97986078,"asset_id":95950665,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/97986078/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950665"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950665"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950665; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950664"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/95950664/Econometric_Analysis_on_the_Effectiveness_across_Port_State_Control_Regimes_What_are_the_Areas_of_Improvement_for_Inspections"><img alt="Research paper thumbnail of Econometric Analysis on the Effectiveness across Port State Control Regimes:What are the Areas of Improvement for Inspections?" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/95950664/Econometric_Analysis_on_the_Effectiveness_across_Port_State_Control_Regimes_What_are_the_Areas_of_Improvement_for_Inspections">Econometric Analysis on the Effectiveness across Port State Control Regimes:What are the Areas of Improvement for Inspections?</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The lack of trust in the maritime industry has led to a variety of inspections onboard ships that...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The lack of trust in the maritime industry has led to a variety of inspections onboard ships that are performed in the name of safety.This article is based on a combined dataset of port state control inspections and casualties for the time period 1999 to 2004 and identifies areas for improvement of port state control inspections.We use binary logistic regression on a dataset which is constructed of twin ships in order to better filter out effects associated with inspection variables such as deficiencies,time in-between inspections,detention or who inspected the vessel while incorporating a summary of ship’s inspection hi story.The model s suggest that there is some 1ack of fol1ow up on recti f- ying deficiencies that have been found during inspections.In addition, the results identify that the main areas of improvement of inspections are within the ISM code(International Safety Management Code) for tankers and general cargo vessels,ship and cargo operations and machinery and propuls...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950664"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950664"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950664; 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</script> <div class="js-work-strip profile--work_container" data-work-id="95950663"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/95950663/Probabilistic_assessment_of_drifting_MODU_risks"><img alt="Research paper thumbnail of Probabilistic assessment of drifting MODU risks" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/95950663/Probabilistic_assessment_of_drifting_MODU_risks">Probabilistic assessment of drifting MODU risks</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The drifting of mobile offshore drilling units (MODU) due to extreme environmental forcing events...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The drifting of mobile offshore drilling units (MODU) due to extreme environmental forcing events, such as due to the passage of a tropical cyclone, have the potential to result in major damage to the environment or infrastructure in the event of a grounding and/or collision. Accurate understanding of these risks is critical to the regulatory approvals and disaster response strategies for offshore oil and gas projects. Drifting vessel trajectories are caused by a combination of wind, surface current and wave - induced drag forces acting on the MOD as well as the restraining drag forces created by the catenary mooring and anchor system attached to the MODU. DHI&#39;s drifting vessel model is a Lagrangian agent-based model (ABM) that utilizes a quasi-stationary iterative solution to the force and moment balance relationships at each time step to evaluate the steady vessel drift speed and direction for a given combination of environmental forcings. The model also includes a description...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950663"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950663"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950663; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=95950663]").text(description); $(".js-view-count[data-work-id=95950663]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 95950663; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='95950663']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=95950663]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":95950663,"title":"Probabilistic assessment of drifting MODU risks","internal_url":"https://www.academia.edu/95950663/Probabilistic_assessment_of_drifting_MODU_risks","owner_id":37052266,"coauthors_can_edit":true,"owner":{"id":37052266,"first_name":"Sabine","middle_initials":null,"last_name":"Knapp","page_name":"SabineKnapp","domain_name":"eur","created_at":"2015-10-27T03:30:01.332-07:00","display_name":"Sabine Knapp","url":"https://eur.academia.edu/SabineKnapp"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950662"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/95950662/Quantification_and_Analysis_of_Risk_Exposure_in_the_Maritime_Industry_Averted_Incident_Costs_Due_to_Inspections_and_the_Effect_of_SARS_Cov_2_COVID_19_"><img alt="Research paper thumbnail of Quantification and Analysis of Risk Exposure in the Maritime Industry: Averted Incident Costs Due to Inspections and the Effect of SARS-Cov-2 (COVID-19)" class="work-thumbnail" src="https://attachments.academia-assets.com/97986076/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/95950662/Quantification_and_Analysis_of_Risk_Exposure_in_the_Maritime_Industry_Averted_Incident_Costs_Due_to_Inspections_and_the_Effect_of_SARS_Cov_2_COVID_19_">Quantification and Analysis of Risk Exposure in the Maritime Industry: Averted Incident Costs Due to Inspections and the Effect of SARS-Cov-2 (COVID-19)</a></div><div class="wp-workCard_item"><span>Safety</span><span>, 2021</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Shipping provides essential services even during global pandemics such as SARS-CoV-2 (COVID-19). ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Shipping provides essential services even during global pandemics such as SARS-CoV-2 (COVID-19). The present approach estimates the monetary value at risk (MVR) at the global and regional level for the world fleet and quantifies the amount of averted incident costs due to inspections. It also provides an indication of the effect of COVID-19 on both. This information can help maritime stakeholders to better understand their risk exposure and improve mitigation strategies. The analysis is based on the global fleet, using a comprehensive combination of data. The analysis confirms the importance to estimate all components at ship level, as safety qualities differ, and each vessel benefits differently from an inspection. Estimates of MVR were slightly higher than global insurance premiums with USD 13.7 to 17.8 billion. Over half of the MVR was due to other marine liabilities and hull and machinery, with cruise vessels leading to loss of life and injuries and oil tankers leading to pollut...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="6128eb9d218e7307313373fe2add7d0f" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":97986076,"asset_id":95950662,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/97986076/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950662"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950662"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950662; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950661"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/95950661/Dynamics_in_the_dry_bulk_market"><img alt="Research paper thumbnail of Dynamics in the dry bulk market" class="work-thumbnail" src="https://attachments.academia-assets.com/97986141/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/95950661/Dynamics_in_the_dry_bulk_market">Dynamics in the dry bulk market</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Recent dynamics in iron ore markets are driven by rapid changes in economic activities that affec...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Recent dynamics in iron ore markets are driven by rapid changes in economic activities that affect commodity markets, trade flows, and shipping activities. Time series models for the relation between these variables in Southeast Asia and the Australasian region are supplemented with models for safety and pollution risk. Steel production in China, Japan, and South Korea is related to iron ore exports and vessel activity in Australia, with an estimated time lag of about two months. The Purchasing Manager Index, which is popular among traders as indicator of economic activity, is found to have predictive power both for steel production and for iron ore exports. The growth in economic activity and vessel movements is associated with significantly higher risks for ship accidents and pollution.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="76a06217275de0eee303750e6774d24a" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":97986141,"asset_id":95950661,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/97986141/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950661"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950661"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950661; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950660"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/95950660/A_multi_layered_risk_estimation_routine_for_strategic_planning_and_operations_for_the_maritime_industry"><img alt="Research paper thumbnail of A multi-layered risk estimation routine for strategic planning and operations for the maritime industry" class="work-thumbnail" src="https://attachments.academia-assets.com/97986074/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/95950660/A_multi_layered_risk_estimation_routine_for_strategic_planning_and_operations_for_the_maritime_industry">A multi-layered risk estimation routine for strategic planning and operations for the maritime industry</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Maritime regulators and port authorities require the ability to predict risk exposure for strateg...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Maritime regulators and port authorities require the ability to predict risk exposure for strategic planning aspects to optimize asset allocation, mitigate and prevent incidents. This article builds on previous work to develop the strategic planning component and introduces the concept of a multilayered risk estimation framework (MLREF) for strategic planning and operations. The framework accounts for most of the risk factors such as ship specific risk, vessel traffic densities and met ocean conditions and allows the integration of the effect of risk control option and a location specific spatial rate ratio to allow for micro level risk assessments. Both, the macro (eg. covering larger geographic areas or EEZ) and micro level application (eg. passage way, particular route of interest) of MLREF was tested via a pilot study for the Australian region using a comprehensive and unique combination of dataset. The underlying routine towards the development of a strategic planning tool was ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="2115e55b058b47fee40964ea0f24d2e6" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":97986074,"asset_id":95950660,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/97986074/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950660"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950660"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950660; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "2115e55b058b47fee40964ea0f24d2e6" } } $('.js-work-strip[data-work-id=95950660]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":95950660,"title":"A multi-layered risk estimation routine for strategic planning and operations for the maritime industry","internal_url":"https://www.academia.edu/95950660/A_multi_layered_risk_estimation_routine_for_strategic_planning_and_operations_for_the_maritime_industry","owner_id":37052266,"coauthors_can_edit":true,"owner":{"id":37052266,"first_name":"Sabine","middle_initials":null,"last_name":"Knapp","page_name":"SabineKnapp","domain_name":"eur","created_at":"2015-10-27T03:30:01.332-07:00","display_name":"Sabine Knapp","url":"https://eur.academia.edu/SabineKnapp"},"attachments":[{"id":97986074,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/97986074/thumbnails/1.jpg","file_name":"EI2017-02-Report.pdf","download_url":"https://www.academia.edu/attachments/97986074/download_file","bulk_download_file_name":"A_multi_layered_risk_estimation_routine.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/97986074/EI2017-02-Report-libre.pdf?1675076975=\u0026response-content-disposition=attachment%3B+filename%3DA_multi_layered_risk_estimation_routine.pdf\u0026Expires=1739823330\u0026Signature=HuVg-Sp2UkK3xAcpbNG3M~-m7GKH7XUPL3mVZI6i0e1FfQ-Z2mgJK3LpjxLS9~9Gq3KTQt5QqgJPy0f5LG65fMX1dOiVOPL1E7r3-Q70gqCJNPS53g2XFNGPH5M0Of3W6wwrbrQT3SGLETzRY8KlBAaZTl0cxbKB~esSW83ENYt7En25gf4R5BrV0AR4GomOXrdG63YjNu1zYt-EEA9t7JdBrSDOF04mPxGXpU0HfO3SmiXQzkckGbyqWwQ-Fi~fexVETA~PMNPxaUxOwtFxM3E04SnK4QVjjNw8jXWG0PVN-KuusbyLYnQl4gZpmvBbjgd2KZNnuvD6O6p~Mrxgyg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":97986075,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/97986075/thumbnails/1.jpg","file_name":"EI2017-02-Report.pdf","download_url":"https://www.academia.edu/attachments/97986075/download_file","bulk_download_file_name":"A_multi_layered_risk_estimation_routine.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/97986075/EI2017-02-Report-libre.pdf?1675076971=\u0026response-content-disposition=attachment%3B+filename%3DA_multi_layered_risk_estimation_routine.pdf\u0026Expires=1739823330\u0026Signature=Pp5KgIbY5uZ~u42b4lYs6BwoN-NPa1YJk7mMkguTRwGeA6uIHYWPx5ESU4LPpXrXTt7D5wfCGvjF3rj~p6j~lyq-LGHTFQnq1x5Fpi55XGLcg8GriU46qYl~mTHw5mGRNn8UhBlaDK-~6XBgIe0OP8Oc6gWoRGGg3DmJElFEYgZ1GTBTi0wo2SQK3KN2LIYBiKOFUCBfi5Dz5wBLIG7wuY94ysIHi~w8ZD3Kj~~bUZ0emn8p8OMhzwjDvn0HluYbzn0tSlnukAz5MXXu0IRQBTeFjWNqtzBGDFJwI0fBYdaGljQhQzsPpeQlHtV~V2-YKtlHujVbSxYzW7EREZ3lcQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950658"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/95950658/Analysis_of_ship_life_cycles_The_impact_of_economic_cycles_and_ship_inspections"><img alt="Research paper thumbnail of Analysis of ship life cycles—The impact of economic cycles and ship inspections" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/95950658/Analysis_of_ship_life_cycles_The_impact_of_economic_cycles_and_ship_inspections">Analysis of ship life cycles—The impact of economic cycles and ship inspections</a></div><div class="wp-workCard_item"><span>Marine Policy</span><span>, 2009</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Due to the shipping industry&amp;amp;amp;#39;s international legal framework, there are loopholes...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Due to the shipping industry&amp;amp;amp;#39;s international legal framework, there are loopholes in the system, which can increase the risk of incidents with high economic costs due to the substandard operation of vessels. This article uses duration analysis and through the creation of ship life cycles provides insight into the effectiveness of inspections on prolonging ship lives. 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The appendix as well as an electronic version of the thesis can be found under the following location: <a href="http://hdl.handle.net/1765/7913" rel="nofollow">http://hdl.handle.net/1765/7913</a> for further reference. All rights reserved. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950654"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/95950654/Estimated_incident_cost_savings_in_shipping_due_to_inspections"><img alt="Research paper thumbnail of Estimated incident cost savings in shipping due to inspections" class="work-thumbnail" src="https://attachments.academia-assets.com/97986163/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/95950654/Estimated_incident_cost_savings_in_shipping_due_to_inspections">Estimated incident cost savings in shipping due to inspections</a></div><div class="wp-workCard_item"><span>Accident Analysis &amp; Prevention</span><span>, 2011</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The effectiveness of safety inspections has been analysed from various angles, but until now, rel...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The effectiveness of safety inspections has been analysed from various angles, but until now, relatively little attention has been given to translate risk reduction into incident cost savings. This paper quantifies estimated cost savings based on port state control inspections and industry vetting inspections. It is based on a unique dataset of 515,194 ship arrivals and inspections from the United States of America and Australia, and inspections of three industry vetting inspection regimes, for the time period 2002 to 2007. The risk reducing effect of inspections is estimated by means of duration models, in terms of inspection gains based on the probability of survival. The results suggest average total estimated cost savings in the range of USD 74 to 192 thousand (median USD 19 to 46 thousand) owing to reduced risk of total loss due to a port state control inspection. Cost savings for industry inspections are found to be even higher, especially for tankers. The savings vary by type, age and size of the ship. The benefits of an inspection are in general larger for older and larger vessels, and also for vessels with undefined flags and unknown classification societies. As inspection costs are relatively low in comparison to potential cost savings, the results underline the importance in determining high risk ships to prevent costs due to total loss of ships.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="5c42ea5f6cf557cc8071babe34e1da74" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":97986163,"asset_id":95950654,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/97986163/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950654"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950654"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950654; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="95950540"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/95950540/Empirical_analysis_of_the_effectiveness_of_the_legislative_framework_in_the_maritime_industry"><img alt="Research paper thumbnail of Empirical analysis of the effectiveness of the legislative framework in the maritime industry" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/95950540/Empirical_analysis_of_the_effectiveness_of_the_legislative_framework_in_the_maritime_industry">Empirical analysis of the effectiveness of the legislative framework in the maritime industry</a></div><div class="wp-workCard_item"><span>Marine Policy</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="95950540"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="95950540"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 95950540; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=95950540]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":95950540,"title":"Empirical analysis of the effectiveness of the legislative framework in the maritime industry","internal_url":"https://www.academia.edu/95950540/Empirical_analysis_of_the_effectiveness_of_the_legislative_framework_in_the_maritime_industry","owner_id":37052266,"coauthors_can_edit":true,"owner":{"id":37052266,"first_name":"Sabine","middle_initials":null,"last_name":"Knapp","page_name":"SabineKnapp","domain_name":"eur","created_at":"2015-10-27T03:30:01.332-07:00","display_name":"Sabine Knapp","url":"https://eur.academia.edu/SabineKnapp"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="56745770"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/56745770/Measuring_the_effect_of_perceived_corruption_on_detention_and_incident_risk_in_the_maritime_industry_An_empirical_analysis"><img alt="Research paper thumbnail of Measuring the effect of perceived corruption on detention and incident risk in the maritime industry – An empirical analysis" class="work-thumbnail" src="https://attachments.academia-assets.com/71979446/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/56745770/Measuring_the_effect_of_perceived_corruption_on_detention_and_incident_risk_in_the_maritime_industry_An_empirical_analysis">Measuring the effect of perceived corruption on detention and incident risk in the maritime industry – An empirical analysis</a></div><div class="wp-workCard_item"><span>Maritime Transport Research</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="a1214d0cf7c526eef2173f49e5465e88" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71979446,"asset_id":56745770,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71979446/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="56745770"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="56745770"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 56745770; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=56745770]").text(description); $(".js-view-count[data-work-id=56745770]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 56745770; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='56745770']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "a1214d0cf7c526eef2173f49e5465e88" } } $('.js-work-strip[data-work-id=56745770]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":56745770,"title":"Measuring the effect of perceived corruption on detention and incident risk in the maritime industry – An empirical analysis","internal_url":"https://www.academia.edu/56745770/Measuring_the_effect_of_perceived_corruption_on_detention_and_incident_risk_in_the_maritime_industry_An_empirical_analysis","owner_id":37052266,"coauthors_can_edit":true,"owner":{"id":37052266,"first_name":"Sabine","middle_initials":null,"last_name":"Knapp","page_name":"SabineKnapp","domain_name":"eur","created_at":"2015-10-27T03:30:01.332-07:00","display_name":"Sabine Knapp","url":"https://eur.academia.edu/SabineKnapp"},"attachments":[{"id":71979446,"title":"","file_type":"txt","scribd_thumbnail_url":"https://attachments.academia-assets.com/71979446/thumbnails/1.jpg","file_name":"PII_S2666822X21000228.txt","download_url":"https://www.academia.edu/attachments/71979446/download_file","bulk_download_file_name":"Measuring_the_effect_of_perceived_corrup.txt","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71979446/PII_S2666822X21000228.txt?1738436858=\u0026response-content-disposition=attachment%3B+filename%3DMeasuring_the_effect_of_perceived_corrup.txt\u0026Expires=1739823330\u0026Signature=Xfzy7HYt-EUo4F4wWbeFkRkUV9mcnHl3S5ztnqH6V-h1DNSaMNyI7MC4y8T6rIhv~WvIcv7j~SfjAyDDyRINUxxIbZnsioLLH7vPXR2wHJO42dsiryQtrvTQBihoszzTOu2Fmm-UiI9qRV7CPHbMiSXm8~X2DvvJ4YIZeYpCWqGLvi53Wvj6BRtcwH7NbnArKDRLzZv2nW4DYrayNB3QmYY60GMgbAZcUbAL4TEhPhURjBWYJssSez92giUlZvvsYf6NAY3SQHDQvdKHo03iOOtPiOEgmglbLvwKIwevKzw-gtCWoHW7jQmaght25Fq1XYoRxka32-kEwkfub-dzIg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="56745769"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/56745769/Shipping_inspections_detentions_and_incidents_an_empirical_analysis_of_risk_dimensions"><img alt="Research paper thumbnail of Shipping inspections, detentions, and incidents: an empirical analysis of risk dimensions" class="work-thumbnail" src="https://attachments.academia-assets.com/71979447/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/56745769/Shipping_inspections_detentions_and_incidents_an_empirical_analysis_of_risk_dimensions">Shipping inspections, detentions, and incidents: an empirical analysis of risk dimensions</a></div><div class="wp-workCard_item"><span>Maritime Policy & Management</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Inspections play a key role in keeping vessels safe. Inspection authorities employ different poli...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Inspections play a key role in keeping vessels safe. Inspection authorities employ different policies to decide which vessels to inspect, including type of vessel, age, and flag. Attention for vessel history is usually restricted only to past detentions. This paper demonstrates that the correlation between the probabilities of detention and (very serious and serious) incidents is very low and that proactive prevention of future incidents is improved by accounting for both risk dimensions, that is, by combining past incident and detention information for targeting highrisk vessels for inspection. Five combined methods are presented to classify vessels based on these two risk dimensions, each of which involves extensive sets of factors. These combined classification methods have predictive power for future incidents. Depending on the applied inspection rate, incorporation of incident risk improves inspection hit rates for vessels with future incidents by 30-50% compared to using only detention information. It is recommended to focus on vessels where both risks are relatively high. A practical example shows how the methods can be applied for inspection selection and for prioritizing inspection areas defined in terms of eight risk domains that include collisions, groundings, engine and hull failures, loss of life, fire, and pollution.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="805238e3589a86131e05fe39683d08d8" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71979447,"asset_id":56745769,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71979447/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="56745769"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="56745769"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 56745769; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=56745769]").text(description); $(".js-view-count[data-work-id=56745769]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 56745769; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='56745769']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "805238e3589a86131e05fe39683d08d8" } } $('.js-work-strip[data-work-id=56745769]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":56745769,"title":"Shipping inspections, detentions, and incidents: an empirical analysis of risk dimensions","internal_url":"https://www.academia.edu/56745769/Shipping_inspections_detentions_and_incidents_an_empirical_analysis_of_risk_dimensions","owner_id":37052266,"coauthors_can_edit":true,"owner":{"id":37052266,"first_name":"Sabine","middle_initials":null,"last_name":"Knapp","page_name":"SabineKnapp","domain_name":"eur","created_at":"2015-10-27T03:30:01.332-07:00","display_name":"Sabine Knapp","url":"https://eur.academia.edu/SabineKnapp"},"attachments":[{"id":71979447,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71979447/thumbnails/1.jpg","file_name":"03088839.2019.pdf","download_url":"https://www.academia.edu/attachments/71979447/download_file","bulk_download_file_name":"Shipping_inspections_detentions_and_inci.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71979447/03088839.2019-libre.pdf?1633768281=\u0026response-content-disposition=attachment%3B+filename%3DShipping_inspections_detentions_and_inci.pdf\u0026Expires=1739823330\u0026Signature=E8HM4yT8uzO2MkP1wJBHLXNCExSk0xNkEZwYf6Ef4fY01e-2BHLEfdvAUeAdGcRfPYsDsYRF7UI4k~CLN4qiCpJU3syw2Xjnq96sFDGTgdv1MRgZVUmUYsZkT8FYCIlO6RK90BPz-m7bx6fp2QoQRGK6IclXSfdGmbF-b2ODYrYtFI3XDOr-ng3oX5FXHYFF~eYub-dI1n8K~ELEqBsdKNjn9l6iUtKBat0Mk4jZky4C1eqFMuUDxkAuaEuJpSQMr2qRBZvLeaqBvSvMjHMv6M79Mmt-Dv05jdRgK22KcZ3ExaD3RiUc5gdzkrGDRqlRZn0wTiR8FzuKDvs5~5RNtA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":71979445,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71979445/thumbnails/1.jpg","file_name":"03088839.2019.pdf","download_url":"https://www.academia.edu/attachments/71979445/download_file","bulk_download_file_name":"Shipping_inspections_detentions_and_inci.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71979445/03088839.2019-libre.pdf?1633768282=\u0026response-content-disposition=attachment%3B+filename%3DShipping_inspections_detentions_and_inci.pdf\u0026Expires=1739823330\u0026Signature=QJGoqopibVPmXOaDohp0XmZjh5nTsqJ7P91Hqw~Hkt~W5EMTOCzaOzm7gPZ40Iis~EsIYyzEvlpO8e~JMSoNsYcNyPgBuAukIPaaT-8NyfKvLyYihFoau5-~mKUIvrgI2X~-kLBhLyM~ebjizlkrmpzijfxWfC-DpsGPDJPkaQmOZCq2hA7Tsq9IWMMrmbF-vuNI9xYnQ-Lh16A6JWXX7zMCY7NMGoPh756LsVEE~GxycUK8IZibfeZZnaEytbp~FwUn5xKXFsEjl6a2KcCAU1P4lN-m4f4LG9SKHinJ-DuQkhi3YT--UR0r1SgsoYL~gpsu5p0Dm1~OAgXXO1UAZg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="56745768"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/56745768/Predicting_Traffic_and_Risk_Exposure_in_the_Maritime_Industry"><img alt="Research paper thumbnail of Predicting Traffic and Risk Exposure in the Maritime Industry" class="work-thumbnail" src="https://attachments.academia-assets.com/71979444/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/56745768/Predicting_Traffic_and_Risk_Exposure_in_the_Maritime_Industry">Predicting Traffic and Risk Exposure in the Maritime Industry</a></div><div class="wp-workCard_item"><span>Safety</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Maritime regulators, port authorities, and industry require the ability to predict risk exposure ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Maritime regulators, port authorities, and industry require the ability to predict risk exposure of shipping activities at a micro and macro level to optimize asset allocation and to mitigate and prevent incidents. This article introduces the concept of a strategic planning tool by making use of the multi-layered risk estimation framework (MLREF), which accounts for ship specific risk, vessel traffic densities, and meets ocean conditions at the macro level. This article’s main contribution is to provide a traffic and risk exposure prediction routine that allows the traffic forecast to be distributed across the shipping route network to allow for predicting scenarios at the macro level (e.g., covering larger geographic areas) and micro level (e.g., passage way, particular route of interest). In addition, the micro level is introduced by providing a theoretical idea to integrate location specific spatial rate ratios along with the effect of the risk control option to perform sensitivi...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="a9b10eabc4759249f9322a2de42cbccf" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71979444,"asset_id":56745768,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71979444/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="56745768"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="56745768"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 56745768; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="56745767"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/56745767/Evaluation_of_total_risk_exposure_and_insurance_premiums_in_the_maritime_industry"><img alt="Research paper thumbnail of Evaluation of total risk exposure and insurance premiums in the maritime industry" class="work-thumbnail" src="https://attachments.academia-assets.com/71979520/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/56745767/Evaluation_of_total_risk_exposure_and_insurance_premiums_in_the_maritime_industry">Evaluation of total risk exposure and insurance premiums in the maritime industry</a></div><div class="wp-workCard_item"><span>Transportation Research Part D: Transport and Environment</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This study provides an empirical evaluation of maritime risk exposure expressed as the monetary v...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This study provides an empirical evaluation of maritime risk exposure expressed as the monetary value at risk (MVR), which incorporates life of crew and passengers, vessel value of hull and machinery, carried cargo value, third party liabilities, and potential external damages like pollution. MVR is based on individual safety quality data of about 130,000 vessels, on insurable values related to various potential damages, and on proxies for fractions of values lost at incidents. MVR provides a tool to enhance strategic planning of maritime administrations and insurance providers, which is illustrated by a high level comparison of annual risk exposure with insurance premiums for 2010 to 2014. The analysis reveals a global annual insurable value of 30.6 trillion USD with associated annual MVR of 38.8 billion USD for very serious and serious incidents. Although oil tankers show the highest risk exposure (1.75 million USD per tanker per year), safety qualities are found to be best for this ship type (1.4% annual incident risk) and worst for container vessels (2.8%). Annual growth rates in total risk exposure are mostly positive with highest value for dry bulk carriers (27.8%), whereas risk exposure tends to decline for pollution of oil tankers (-2.0%) and passenger vessels (-11.3%), and for loss of life of oil tankers (-1.9%) and dry bulk carriers (-1.4%) but not of passenger vessels (6.9%). A comparison across administrative dimensions reveals that most risk exposure lies with old open registries and with beneficial owners and DoC companies located in high income countries. Comparison with global insurance premiums suggests reasonably adequate coverage of maritime risks (excluding cargo). Our analysis indicates under-insurance of risk by around 5%, corresponding to about 1 billion USD per year, with some uncertainties remaining for the actual loss fractions of the various involved damages.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="81bd8b9078ea8d3ad46a4faa2c6ce183" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71979520,"asset_id":56745767,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71979520/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="56745767"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="56745767"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 56745767; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "81bd8b9078ea8d3ad46a4faa2c6ce183" } } $('.js-work-strip[data-work-id=56745767]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":56745767,"title":"Evaluation of total risk exposure and insurance premiums in the maritime industry","internal_url":"https://www.academia.edu/56745767/Evaluation_of_total_risk_exposure_and_insurance_premiums_in_the_maritime_industry","owner_id":37052266,"coauthors_can_edit":true,"owner":{"id":37052266,"first_name":"Sabine","middle_initials":null,"last_name":"Knapp","page_name":"SabineKnapp","domain_name":"eur","created_at":"2015-10-27T03:30:01.332-07:00","display_name":"Sabine Knapp","url":"https://eur.academia.edu/SabineKnapp"},"attachments":[{"id":71979520,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71979520/thumbnails/1.jpg","file_name":"EI2016-25.pdf","download_url":"https://www.academia.edu/attachments/71979520/download_file","bulk_download_file_name":"Evaluation_of_total_risk_exposure_and_in.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71979520/EI2016-25-libre.pdf?1633768281=\u0026response-content-disposition=attachment%3B+filename%3DEvaluation_of_total_risk_exposure_and_in.pdf\u0026Expires=1739823330\u0026Signature=P0aGSLZ5nPXO42V2xp6luSYSOssbU5mNzK0ZyPqJheERtDAqN8VDP4Nsplmp9hQ20H6ZFMwXNYCBJ6FNcoyA6iP0fU66zshV1IvvTCtabZDwcsL0KjtzI-vtg1L85PAje1qB9qC2juaI6ORKwUSHHkKWZUYdZSoVzAsMbGDccF~O4oVFQYzL59O8YyhFKipxEcDugS5qXfPYds-X0FFP4Y-iCSKwZwkrRluHW2S4UpW3saDw1tVslgVyrtl5wNwgrAerT6hN0IVlY0LL4RLzRJ9Og5s7aDcbLZ-9eexHdBXpsS0Nd3E6jfAZ8aVbZJsjC7tDlBthrgsgR4R4Ujq5bA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="56745766"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/56745766/An_integrated_risk_estimation_methodology_Ship_specific_incident_type_risk"><img alt="Research paper thumbnail of An integrated risk estimation methodology: Ship specific incident type risk" class="work-thumbnail" src="https://attachments.academia-assets.com/71979523/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/56745766/An_integrated_risk_estimation_methodology_Ship_specific_incident_type_risk">An integrated risk estimation methodology: Ship specific incident type risk</a></div><div class="wp-workCard_item"><span>Report Econometric Institute Erasmus University Rotterdam</span><span>, Apr 1, 2013</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Shipping activity has increased worldwide, including parts of Australia, and maritime administrat...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Shipping activity has increased worldwide, including parts of Australia, and maritime administrations are trying to gain a better understanding of total risk exposure in order to mitigate risk. Total risk exposure integrates risk at the individual ship level, risk due to vessel traffic densities, physical environmental criteria, and environmental sensitivities. A comprehensive and robust risk exposure metric can be beneficial to maritime administrations to enhance mitigation of potential harm and reduce vulnerability to the marine environment as well as to safeguard lives and property. This report outlines an integrated methodology to estimate total risk exposure, with specific attention for the ship specific risk for different types of incident. Some related application aspects of the models are discussed.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="e5530faedd0379c0616ad5086467962d" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71979523,"asset_id":56745766,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71979523/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="56745766"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="56745766"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 56745766; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "e5530faedd0379c0616ad5086467962d" } } $('.js-work-strip[data-work-id=56745766]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":56745766,"title":"An integrated risk estimation methodology: Ship specific incident type risk","internal_url":"https://www.academia.edu/56745766/An_integrated_risk_estimation_methodology_Ship_specific_incident_type_risk","owner_id":37052266,"coauthors_can_edit":true,"owner":{"id":37052266,"first_name":"Sabine","middle_initials":null,"last_name":"Knapp","page_name":"SabineKnapp","domain_name":"eur","created_at":"2015-10-27T03:30:01.332-07:00","display_name":"Sabine Knapp","url":"https://eur.academia.edu/SabineKnapp"},"attachments":[{"id":71979523,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71979523/thumbnails/1.jpg","file_name":"An_integrated_risk_estimation_methodolog20211009-18159-gsxuv6.pdf","download_url":"https://www.academia.edu/attachments/71979523/download_file","bulk_download_file_name":"An_integrated_risk_estimation_methodolog.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71979523/An_integrated_risk_estimation_methodolog20211009-18159-gsxuv6.pdf?1738436859=\u0026response-content-disposition=attachment%3B+filename%3DAn_integrated_risk_estimation_methodolog.pdf\u0026Expires=1739823330\u0026Signature=MMnORQQ~GzPOEW0SmvblYRvZG~x57xwn~2QvJrwlTwBFtie3OLZrrYGGDWwmCAI~~Zkp7YWM2fifI44fXzUcAJRLoTZPEUK0CnLtoWs9rbOdM5oQMFBiTqWvXn6-xlVGo~6EPMCRsDqQ40MJ83oNbq8kr0pbFJf61WpAPeovOdm5DBPx7UHRc3LVpSJ2mn~zmcnxXEfcyATT-ee2yvb2jqOtLT12K3ZVuhLqMc3euhvxXtepXiNPez~0pZWfbxS4kcBCxGOtRezvcj0zUp526RB~jZEPOa7dRvz0S8WGjcggrZvDUJvtKsgM~ANg91Nd1JN7bow9oihYOKUgDW-CpA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="56745765"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/56745765/Assessing_ecological_sensitivities_of_marine_assets_to_oil_spills_by_means_of_expert_knowledge"><img alt="Research paper thumbnail of Assessing ecological sensitivities of marine assets to oil spills by means of expert knowledge" class="work-thumbnail" src="https://attachments.academia-assets.com/71979442/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/56745765/Assessing_ecological_sensitivities_of_marine_assets_to_oil_spills_by_means_of_expert_knowledge">Assessing ecological sensitivities of marine assets to oil spills by means of expert knowledge</a></div><div class="wp-workCard_item"><span>F1000posters</span><span>, Sep 24, 2014</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="5f63746d0fabe339581ff07b454ac844" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71979442,"asset_id":56745765,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71979442/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="56745765"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="56745765"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 56745765; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="56745712"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/56745712/Improved_Strategies_for_the_Maritime_Industry_to_Target_Vessels_for_Inspection_and_to_Select_Inspection_Priority_Areas"><img alt="Research paper thumbnail of Improved Strategies for the Maritime Industry to Target Vessels for Inspection and to Select Inspection Priority Areas" class="work-thumbnail" src="https://attachments.academia-assets.com/71979379/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/56745712/Improved_Strategies_for_the_Maritime_Industry_to_Target_Vessels_for_Inspection_and_to_Select_Inspection_Priority_Areas">Improved Strategies for the Maritime Industry to Target Vessels for Inspection and to Select Inspection Priority Areas</a></div><div class="wp-workCard_item"><span>Safety</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Inspection authorities such as the Port State Control Memoranda of Understanding use different po...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Inspection authorities such as the Port State Control Memoranda of Understanding use different policies and targeting methods to select vessels for inspections and rely primarily on past inspection outcomes. One of the main goals of inspections is to improve the safety quality of vessels and to reduce the probability of future incidents. This study shows there is room for improvement in targeting vessels for inspections and in determining vessel-specific inspection priority areas (e.g., bridge management versus machinery related items). For the year 2018, sixty percent of vessels that experienced very serious or serious (VSS) incidents were not selected for inspection up to three months prior to the incident and forty percent of the vessels that were inspected still had incidents of which only four percent were detained. Furthermore, one can observe a very low correlation (−0.04) between the probabilities of detention and incidents (VSS) for the year 2018. The proposed approach trea...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="0a70962b0f47a0d97ba6298d20a29cc7" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71979379,"asset_id":56745712,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71979379/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="56745712"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="56745712"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 56745712; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="33091453"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/33091453/Ship_inspection_strategies_Effects_on_maritime_safety_and_environmental_protection"><img alt="Research paper thumbnail of Ship inspection strategies: Effects on maritime safety and environmental protection" class="work-thumbnail" src="https://attachments.academia-assets.com/53190646/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/33091453/Ship_inspection_strategies_Effects_on_maritime_safety_and_environmental_protection">Ship inspection strategies: Effects on maritime safety and environmental protection</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Global trade depends for a large part on maritime transport, and safe ships are needed not only t...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Global trade depends for a large part on maritime transport, and safe ships are needed not only to protect precious cargo but also to prevent environmental damage. Flag state and port state authorities spend much effort in ship safety inspections to ensure a minimum safety level and to prevent casualties. This paper investigates the safety gains of current inspection rules as well as options for further improvement. The analysis is based on a dataset of over four hundred thousand ship arrivals originating from some important trading nations between 2002 and 2007, complemented with data on port state control and industry inspections and casualties.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="7525b5f662655f38242c84b596a00170" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":53190646,"asset_id":33091453,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/53190646/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="33091453"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="33091453"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 33091453; 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