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ÖgeDesign of seafarer-centric safety system; mental workload (MWL) prediction(Lisansüstü Eğitim Enstitüsü, 2022)It is known that human factor has a major effect on maritime casualties that cause great harm to environment, economy and maritime sector. It was stated that while human error is the primary contributor of accidents, a good part of collisions and groundings were related to mental workload (MWL) of watchkeeping officers. Automation, mechanization and the introduction of new technologies had changed the working conditions together with reducing the number of crew and increasing the MWL of operators. This clearly indicates that human element related issues will continue to be one of the major issues in marine transportation assets. In maritime-related studies, it has been analysed mostly how the ship's environment, working period and other factors affect the seafarers. Almost all maritime-related studies couldn't have a potential to develop MWL prediction system for maritime operations aspect. However, lots of studies on drivers and pilots, have produced successful results for MWL prediction. Taking into consideration the fact that MWL has major contribution to maritime casualties, the development of real-time MWL prediction system is vitally essential for ships. By implementing the similar measurement techniques used in the studies on drivers and pilots, to maritime transportation, this study aims to classify the physiological responses of the operators that can produce an output for state of officer on duty as "Safe" or "Risky" from the collected physiological data and task load data during the seaborn operations. This study predicates on the theories which are the statement "minimum performance requires sufficient behavioural activity" of Sheridan and Simpson (1979) together with inverted U function of Yerkes and Dodson (1908) which presents the relationship between arousal and performance. Moreover, the theory of Young et al. (2015) which presents the relationship among mental workload, performance, task demand and resource supply and indicates the overload region, guides this study in terms of building the structure of the experimental research. By being predicated on the above-mentioned theories, this study aimed to design Cognitive Seafarer - Ship Interface (CSSI) which is a main part of Seafarer-Centric Safety System. The physiological data of the 17 junior deck officers (12 subjects performed navigation scenario, 5 subjects performed cargo operation scenario) was recorded according to the design. By being correlated with the performance of the officer, the change of physiological responses of the subjects were analysed in low and high task load levels. The medical decision-making process, which deduced "Safe" or "Risky", was run for this change. For performance measurement that is a part of triangulated measurement strategy (Wierwille and Eggemeier, 1993), Officer Performance Model which is used for MWL classification, was developed for navigation and cargo operation tasks. Additionally, the inputs of Task Load Estimator were defined as data transcription from navigational aids according to results of classification. In summary, the following process were done and results were found. Firstly, the navigation and cargo operation scenarios were created to simulate ship environment. The difficulty level of navigation scenario was gradually adjusted (in order to prevent acquired skill) according to traffic density, visibility and geography by combining in 4 steps. The difficulty level of cargo operation scenario was gradually adjusted according to type and number of operation and operation period corresponding to a real cargo operation by combining in 3 steps. Task load assessments of the scenarios were carried out according to Operator Function Model (OFM-COG) and its sample implications in literature. The results of NASA-TLX scores of the subjects supported the increase of task load levels of the scenarios. ANOVA results showed that there are significant differences in the NASA-TLX scores of 5 different dimensions and in total, among 4 steps which have different task load levels for navigation scenario. Similarly, ANOVA results showed that there are significant differences in the NASA-TLX scores of 3 different dimensions and in total among 3 steps which have different task load levels for cargo operation scenario. According to the subjective assessments of the subjects, MWL increased during the both of navigation and cargo operation scenarios. Secondly, ROC curve analysis was performed for validation of developed officer performance model. Recorded performances of the participants were evaluated as "safe" and "risky" for each task by one ocean going Master expert for navigation tasks and by one ocean going Chief Officer for cargo operation tasks. According to the ROC curve analysis, developed officer performance model was validated with high significance and AUC values. These results showed that the developed officer performance model can be used in any study focused on performance measurement in navigation and chemical tanker cargo operations. Being validated measurement method, performances of the subjects showed that there is a negative significant correlation between performance score and task load in both of navigation and cargo operation tasks. With the distinction of the task load as high task load and low task load, the performance scores were also found significantly different in low and high task loads for both of navigation and cargo operation tasks. Thirdly, physiological responses of the subjects were often differentiated between low and high task loads. Although the change of time-based heart rate variability (HRV) features was not found meaningful according to literature during the increase of task load, the change of frequency-based, time-frequency and nonlinear HRV features were found significant and meaningful during the increase of task load. Moreover, the change of some electrodermal activity (EDA) features and some eye responses were found significant in this study. However, the change of EDA responses was not found strongly correlated with the increase of task load. This can be explained by the fact that electrodermal activity occurs in stressful conditions rather than mental workload. The "frustration" scores of the NASA-TLX supported the fact that the subjects didn't feel so stressed during the tasks. On the other hand, the change of pupil diameter features was found significant and meaningful during the increase of task load in navigation tasks but in cargo operation tasks. Additionally, the change of blink frequency features varied across the scenarios. The variable results of eye responses are thought that the selectivity of eye blinks and pupil diameter to MWL is low according to literature. Additionally, the reason of the fact that the change of some eye features was significant during the increase of task load is thought to be related with the characteristics of eye responses that pupil diameter change is correlated highly with error rate and blink rate increases in incorrect responses rather than correct responses. Therefore, these significances can be explained with the decrease of performance together arising from the increase of task load. On the other hand, the correlations between HRV and EDA features, HRV and eye features, EDA and eye features were found significant and meaningful in mental workload theory. Classification process was carried out with artificial neural network (ANN) code and "Classification Learner" tool of Matlab 2020a. Although the results of the classifications of the subjects' physiological responses on high and low task loads in this study did not give very good accuracies, compared with the studies in literature, they gave sufficient results. The classification accuracies, 75.7% in testing, 83.3% in all for navigation tasks, 80.0% in testing, 92.5% in all for cargo operation tasks and 61.3% in testing, 77.0% in all for cross-task classification have been found similar to those stated in the related studies whose mental workload and stress classification accuracies vary between 70.48% and 98%. According to classification efforts of physiological responses on high task load and low task load levels and performance scores of the subjects, the red lines of task demand became appear in this study. Continuing from the aim of Orlandi and Brooks (2018) and the contributions to MWL prediction in marine engine operations of Yan et al. (2019), the red lines of task demand in ship navigation was tried to determine in this study. Classification of physiological responses and the distinction of the task loads according to the performances of the subjects have ensured the task load to be separated as high task load and low task load. Thus, the inputs of the Cognitive Seafarer-Ship Interface (CSSI) were formed with the outputs of high task load details for navigation and the physiological responses given as features (classified in this study). CSSI processes the task loading together with physiological data of the officer and gives an output as "Risky" for safety of navigation in "The future Seafarer-Centric Safety System design" to be used on ships or at the Shore Control Centre for autonomous ships in future. Consequently, this study will contribute to literature, being the first study in terms of predicting MWL for navigation and cargo operations in maritime transportation. In addition, this study will be a guide for future studies as it reveals the design of the "Seafarer-Centric Safety System" to be developed in order to minimize maritime casualties.
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ÖgeDenizcilik aile işletmelerinde kurumsallaşma(Lisansüstü Eğitim Enstitüsü, 2021)Kurumsallaşma gelişen pazar koşullarında işletmelerin hayatta kalabilmeleri için son derece önemlidir. Kurumsallaşabilen işletmeler, iş ve işlemleri standart hale getirerek, kişilerden bağımsız bir sistem içerisinde yönetim fonksiyonlarını gerçekleştirebilmektedirler. Bu da profesyonel bir yönetim anlayışının doğmasına sebep olmaktadır. Aile işletmeleri dünya ekonomisinde önemli bir rol oynamaktadır. Denizcilik sektörü incelendiğinde de işletmelerin büyük bir kısmının aile işletmesi olduğu görülmektedir. Genellikle babadan oğula geçen bir yönetim anlayışıyla yönetilen ve kurumsallaşmayı başaramayan bu işletmeler, sürdürülebilirlik açısından büyük sorunlar yaşamakta ve birçoğu ikinci kuşağa erişemeden faaliyetlerini durdurmaktadır. İşletmelerin mevcut kurumsal yapılarını ölçmek, işletmenin hangi kurumsal yönetim fonksiyonlarında eksikliklerin olduğunu anlamaya yaramaktadır. Bu sebeple bu çalışmada Türkiye'de faaliyet gösteren gemi işletmeciliği firmalarına yönelik bir kurumsallaşma seviyesi ölçeği geliştirilerek, işletmelerin mevcut kurumsal yapıları incelenmiştir. Kurumsallaşma süreçlerinden hangi aşamalarda eksikliklerin olduğu tespit edilmiştir. Ayrıca kurumsallaşma fonksiyonları arasındaki ilişkiler incelenerek birbirlerine etki eden faktörler analiz edilmiştir. Çalışmada İMEAK Deniz Ticaret Odasına kayıtlı, Türk Bayraklı gemilere sahip ve aile işletmesi konumunda olan 177 gemi işletmeciliği firmasında çeşitli pozisyonlarda çalışan 193 kara personeline anket uygulanmıştır. Anket sonuçları SPSS 23.0 istatistik programında analiz edilmiştir. Ölçek geliştirme sürecinde önce Keşfedici Faktör Analizi (KFA) yapılarak ölçekte yer alan ifadelerin faktörleşmeleri sağlanmıştır. Başta 18 olan ifade sayısı 14 ifadeye düşürülmüştür ve ifadeler 3 faktör altında toplanmıştır. Faktörler, literatür ve uzman görüşleri yardımıyla; etkin örgüt yapısı, iç denetim ve yetki devri olarak adlandırılmıştır. KFA ile birlikte güvenilirlik analizleri yapılan ölçeğin yapı geçerliliğini test etmek adına Doğrulayıcı Faktör Analizi (DFA) yapılmıştır. KFA ve DFA sonuçlarına göre ölçek güvenilir ve geçerli bulunmuştur. Ölçekte yer alan faktörler arasındaki ilişkileri test etmek için SPSS AMOS 23.0 istatistik paket programında Yapısal Eşitlik Modellemesi (YEM) uygulanmıştır. Yapısal Eşitlik Modeli ile yapılan hipotez testleri incelendiğinde, Türk denizcilik aile işletmelerinde etkin bir örgüt yapısının oluşturulmasının, yetki devri ve iç denetimi faaliyetlerini olumlu yönde etkilediği sonucuna varılmıştır. Yetki devrinin iç denetime doğrudan ve anlamlı bir etkisinin olmadığı görülmekle birlikte, aracı değişken analizi yapılarak elde edilen sonuca göre etkin örgüt yapısının yetki devri ve iç denetim arasında tam aracılık etkisiyle bir köprü görevi gördüğü anlaşılmıştır. İşletmelerin kuşaklarıyla kurumsallaşma seviyeleri arasında bir ilişki olup olmadığı Anova Analizi ile test edilmiştir. Analiz sonucuna göre işletmelerin kaçıncı kuşak bir işletme olduğuyla kurumsallaşma seviyeleri arasında istatiksel olarak bir anlamlılık olmadığını görülmüştür. Denizcilik aile işletmelerinin kurumsallaşma seviyelerini tespit etmek adına frekans analizi yapılmıştır. Frekans analizi sonuçlarına göre Türkiye'de faaliyet gösteren aile sahipli gemi işletme firmalarının 3,51'lik bir ortalamayla yarı/orta seviyede kurumsallaştıkları tespit edilmiştir. Bu çalışma, denizcilikte kurumsallaşma alanında yapılan ilk nicel çalışmadır. Ayrıca literatürden farklı olarak, armatörler ve işletme sahiplerinin görüşleri yerine kara personelinin görüşleri ele alınmıştır. Bu şekilde armatör ve işletme sahiplerinin kendi işletmelerini değerlendirirken oluşabilecek taraflı tutumların engellenmesi amaçlanmıştır.
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ÖgeA quantitative approach on human factor analysis in maritime operations(Lisansüstü Eğitim Enstitüsü, 2021)The maritime authorities and international organizations have taken the issue of the pivotal role of the human element and its contribution to the safety of ship operations very seriously due to the growing global concern over maritime disasters. At this point, that at least 80 per cent of shipping casualties are related to the human element is underpinned by the conducted studies and investigation reports published by organizations such as IMO (International Maritime Organization), ILO (International Labour Organization) and experts in the field. Despite the economic and technological improvements, since tragic events had caused the worst environmental disasters in recent years, never has the human element been so crucial in the safe operation of ships. However, although the issue of human contribution to unsafe shipboard operations needs to be the focal point of the researches, there has not been a qualified novel study that can meet the gap of the maritime transportation industry. The purpose of this thesis is to develop a uniquely quantitative approach to evaluate the human error probabilities (HEPs) and to analyse the increasing operational risks due to human errors. In this context, a hybrid approach incorporating Fault Tree Analysis (FTA) and Interval type-2 fuzzy-based Success Likelihood Index Method (SLIM) is developed. The approach, additionally contributing to current human error probability assessment methods in academic literature, is applicable to all shipboard operations regardless of vessel type. With the study under this thesis, it is predicted to provide supportive guidance that enables shipping companies to undertake the early detection of unsafe cargo operations before they get out of control. With the risk assessment concentrated on the concept of the human-related operational failure by implementing the hybrid approach, system vulnerabilities that could result in an undesired event are considerably detected and the awareness in shipping safety management is increased. It is also predicted to reach solid targets by providing both qualitative and quantitative data to maritime container transportation safety as well as an insight into what measures may be necessary to reduce future losses. A hybrid approach that differs from a traditional HEP assessment, suitable customization to containership platform, a methodology that involves key risk and performance shaping factors (PSFs) based on the literature, industry standards, technical knowledge of marine experts and analysis of marine accident investigation reports, increased consistency in expert judgements, and analysis of the root causes of major risks to operational safety can be mentioned as original aspects of the thesis. Implementation of management of human error probability analysis integrating with risk analysis will provide a consistent tool for the maritime industry. As a result, the study offering proactive solutions to related issue of unsafe shipboard operations that closely related to both economic and environmental aspects of the maritime transportation industry will provide tangible contributions for enhancing safety.
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ÖgeA quantitative approach on human factor analysis in maritime operations(Lisansüstü Eğitim Enstitüsü, 2021)The maritime authorities and international organizations have taken the issue of the pivotal role of the human element and its contribution to the safety of ship operations very seriously due to the growing global concern over maritime disasters. At this point, that at least 80 per cent of shipping casualties are related to the human element is underpinned by the conducted studies and investigation reports published by organizations such as IMO (International Maritime Organization), ILO (International Labour Organization) and experts in the field. Despite the economic and technological improvements, since tragic events had caused the worst environmental disasters in recent years, never has the human element been so crucial in the safe operation of ships. However, although the issue of human contribution to unsafe shipboard operations needs to be the focal point of the researches, there has not been a qualified novel study that can meet the gap of the maritime transportation industry. The purpose of this thesis is to develop a uniquely quantitative approach to evaluate the human error probabilities (HEPs) and to analyse the increasing operational risks due to human errors. In this context, a hybrid approach incorporating Fault Tree Analysis (FTA) and Interval type-2 fuzzy-based Success Likelihood Index Method (SLIM) is developed. The approach, additionally contributing to current human error probability assessment methods in academic literature, is applicable to all shipboard operations regardless of vessel type. With the study under this thesis, it is predicted to provide supportive guidance that enables shipping companies to undertake the early detection of unsafe cargo operations before they get out of control. With the risk assessment concentrated on the concept of the human-related operational failure by implementing the hybrid approach, system vulnerabilities that could result in an undesired event are considerably detected and the awareness in shipping safety management is increased. It is also predicted to reach solid targets by providing both qualitative and quantitative data to maritime container transportation safety as well as an insight into what measures may be necessary to reduce future losses. A hybrid approach that differs from a traditional HEP assessment, suitable customization to containership platform, a methodology that involves key risk and performance shaping factors (PSFs) based on the literature, industry standards, technical knowledge of marine experts and analysis of marine accident investigation reports, increased consistency in expert judgements, and analysis of the root causes of major risks to operational safety can be mentioned as original aspects of the thesis. Implementation of management of human error probability analysis integrating with risk analysis will provide a consistent tool for the maritime industry. As a result, the study offering proactive solutions to related issue of unsafe shipboard operations that closely related to both economic and environmental aspects of the maritime transportation industry will provide tangible contributions for enhancing safety.
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ÖgeModelling departure time, destination and travel mode choices by using the generalized nested logit model: an example for discretionary trips( 2020)Nowadays, understanding the influences of different temporal and spatial factors on individuals' travel choices becomes essential especially after the pandemic of COVID-19 that invaded the world in 2020. Such an outbreak had its own influences on the future transportation planning studies. By words, policy makers have directed their interests toward newly emergency transportation policies that aim to distribute travels over wider time and space spans in accordance with precautionary and preventive measures to counteract Corona virus or any other similar future virus attacks. However, transportation planning studies still rely on traditional demand modelling approaches such as the four-step model. The four-step model is still exposed to considerable criticism for its shortages in representing the potential correlations between temporal, spatial factors and different travel dimensions which leads to inaccurate representations of individuals' actual travel behaviour. In order to overcome that, some researches have directed their interests toward using choice modelling approach as an alternative to some stages in four-step model. Even though these approaches show better performance in terms of goodness of fit and predictability power, most of them have represented travel dimensions individually rather than jointly. As there is a gap in literature about representing a unified choice model that connect different travel demand dimensions and consider various potential inter-correlation among them, this dissertation contributes filling this gap through introducing three research papers that employ various types of discrete choice models for jointly representing three major travel dimensions; destination, departure time and travel mode. Such models contribute more to mathematical modelling literature of transportation demand models that provide more detailed and specific micro-policy analyses where traditional four-step model cannot. The presented papers introduce three discrete choice models that differ in the level of accounting for correlation of error terms within elementary alternatives and therefore differ in cross-elasticity pattern while offering computational simplicity. In the first paper, limited number of correlation patterns is introduced by adopting the three-level Nested Logit (NL) models. In the second paper, opposite to traditional NL models that was introduced in previous paper, this paper assesses the effect of considering spatial correlation of adjacent discretionary destinations on the choice of the two other travel dimensions by using the Ordered Generalized Extreme Value (OGEV) approach. The third paper, introduces a novel modelling methodology for using the Generalized Nested Logit (GNL) model to represent multi-dimensional potential correlations; between different travel dimensions (inter-correlation), inside the same travel dimension (inner-correlation) and correlation due to ordered nature travel dimensions (e.g. spatial correlation among destinations and temporal correlation between departure times). Overall, in the published papers, different levels of correlation between departure time, destination and travel mode choices and within each travel dimension are represented through different assumed correlation structures according to the nesting structure limitations provided by each model. Moreover, the associated formulas for each proposed model that reflect different patterns of correlation (cross-elasticity) are explicitly introduced. From a policy implications standpoint, a calibrated version of departure time, destination and travel mode model will provide policy makers very detailed analyses about the inter-relationships associated with the three travel dimensions (while traditional four-step model cannot provide at micro-level). That leads to more certain, specific, efficient and precise policy decisions. Thus, developing these models can be considered as a significant milestone toward obtaining a consistent, efficient and integrated full-scale model that can lie in all travel demand dimensions (e.g. number and duration of activities for activity and tour-based models). The developed models have been estimated and calibrated by using shopping and entertainment trips data of Eskisehir city, Turkey. The data have been collected through a household survey that was conducted in 2015 in the context of Eskisehir strategic master plan project which was operated by Eskisehir Metropolitan Municipality. Eskisehir is a city in north-western Turkey. It is considered as a medium sized city with a population of 799724 (2013 census) distributed over about 2678 km2 area. The collected data include variables that represent attributes of alternatives and individuals' characteristics to be used in models' utility functions. The first group of alternatives' attributes is travel time related attributes where, in vehicle time and out of vehicle time (egress time, at stop waiting time and access time) for each individual trip have been obtained. Moreover, related to travel cost, the fare of public transportation modes (for public transportation users), trip cost for private cars as well as parking fees (for private car users) have been observed for each individual trip. Within the collected revealed data, a good portion of socio-economic individual characteristics related observations are presented. These data include car ownership, individual's age, monthly income and student status (if respondent is a student or not). The total number of observations related to the determined alternatives has been found to be 529. The estimation results of each model have been explicitly interpreted in each paper and logical as well as statistical comparisons between pairs of models have been conducted in order to ensure the superiority of more advanced approaches (OGEV and GNL) over the lesser ones (NL). In the light of the estimation results, generally, individuals have been found to jointly decide on "at which departure time", "to which destination" and "by which mode" rather than doing this separately as assumed by traditional four-step model. Neglecting the potential correlation among alternatives of the three travel dimensions has led to inaccurate estimates of measurements' indicators such as Value of Time (VOT) which results finally in incorrect and improper policy decisions. From another hand gradual improvements in predictability have been observed as the level of the represented correlation increases. That is, three-level NL model was found to offer improvements over Multinomial Logit (MNL) model, OGEV model is prominent over NL model and GNL is superior over all models. It is possible to argue that the proposed GNL approach has distinct improvements over all other proposed approaches. Its simplicity along with the incomparable flexibility in representing a lot of correlation patterns within and among three vital travel dimensions all of that under a unified modest model qualify it to be prominent. The proposed GNL model has provided very detailed analyses about the inter-dependencies associated with various departure times, travel modes and discretionary destinations where other models cannot. The estimation results have expressed the powerful analytical ability of the proposed GNL approach where it has the power of capturing unusual correlation patterns. These patterns are thoroughly specific, unexpected, and very difficult to be observed in the market. By words, the dissertation argues that there is no other approach as simple as the proposed GNL and leads to such temporal and spatial specific analyses. The advantages associated with the proposed GNL approach qualify it to be a strong peer to the traditional four-step model in micro-disaggregate modelling scopes if applied for medium and small-scale planning studies that involve limited number of alternatives in each travel dimension. It may be used with a large number of alternatives in each travel dimensions as well, however, through stratifying the whole population to small segments based on one or more travel dimensions to produce small segments suitable for readily estimation process. Finally, the proposed GNL methodology represents a time of day-based trip-end distribution model that can reproduce a considerably more accurate transportation mode based origin-destination matrix dependent on time of day. Moreover, unlike traditional four-step models, parameter estimates produced from the GNL model can provide significant indications which precisely reflect the individuals' actual behaviour. Obviously, that can enormously help policy makers to reach a solid perception about the effects of applying various strategies to manage demands through different times of day and towards different destinations.