Pub Date : 2021-09-01DOI: 10.1080/03088839.2021.1971783
Mengchi Li, M. Luo, Jue Wang
ABSTRACT Maritime services prefer to locate in places where factors indicating the business environment, such as its tax and legal systems, are attractive. However, when there are competing regions to choose from, it is important to understand the impact of each of these factors at each alternative location and whether the negative impacts of one factor may be offset by the positive impacts of other factors. This study analyzes the preferences of maritime services selecting from three potential business locations in Asia (Shanghai, Hong Kong, and Singapore) and the possibility of factor substitution. A stated preference survey is designed to collect the choices of industry leaders facing five major factor options, and discrete choice models are applied to analyze the alternative- and company-specific impacts of these factors. The estimated alternative-specific parameters are consistent with the socioeconomic and legal backgrounds of the three locations, and the company-specific parameters indicate that it is not necessary for maritime services to be located near their clients, namely, shipowners. Finally, the factor trade-off analysis can help each location to identify possible policy changes that may improve its competitiveness.
{"title":"Maritime services location decisions—an empirical analysis and implications","authors":"Mengchi Li, M. Luo, Jue Wang","doi":"10.1080/03088839.2021.1971783","DOIUrl":"https://doi.org/10.1080/03088839.2021.1971783","url":null,"abstract":"ABSTRACT Maritime services prefer to locate in places where factors indicating the business environment, such as its tax and legal systems, are attractive. However, when there are competing regions to choose from, it is important to understand the impact of each of these factors at each alternative location and whether the negative impacts of one factor may be offset by the positive impacts of other factors. This study analyzes the preferences of maritime services selecting from three potential business locations in Asia (Shanghai, Hong Kong, and Singapore) and the possibility of factor substitution. A stated preference survey is designed to collect the choices of industry leaders facing five major factor options, and discrete choice models are applied to analyze the alternative- and company-specific impacts of these factors. The estimated alternative-specific parameters are consistent with the socioeconomic and legal backgrounds of the three locations, and the company-specific parameters indicate that it is not necessary for maritime services to be located near their clients, namely, shipowners. Finally, the factor trade-off analysis can help each location to identify possible policy changes that may improve its competitiveness.","PeriodicalId":18288,"journal":{"name":"Maritime Policy & Management","volume":"50 1","pages":"182 - 197"},"PeriodicalIF":3.5,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44808739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-31DOI: 10.1080/03088839.2021.1971784
Lixian Fan, Jiaqi Xie
ABSTRACT In one of the most capital-intensive industries in the world, the investment decisions of container shipping companies, especially concerning new ships, are crucial to the success of companies. This study investigates shipowners’ ship choice decisions and ship size preference through multinomial logit models using a dataset compiled by Clarkson Research Services Limited. The model incorporates the factors that affect ship size choice from three aspects: the internal traits of companies (company trait), the environment of the shipping market (market-driven strategy) and the performance of rivals (competition strategy). Different factors have different influences on shipping companies’ ship choice behaviour and ship size preference in different market situations. From a market-driven perspective, the high new-built ship price makes companies choose small ships. In a prosperous market, when freight rates are high, medium-sized vessels are preferred, and investment in large vessels is less likely. From the company attributes perspective, the empirical estimation shows that larger container ships are preferred by larger shipping companies. When it comes to competitive strategy, shipping companies will be more inclined to choose larger ships when they see capacity expansion among their competitors. These results confirm the nature of an oligopolistic market structure of the container market.
{"title":"Identify determinants of container ship size investment choice","authors":"Lixian Fan, Jiaqi Xie","doi":"10.1080/03088839.2021.1971784","DOIUrl":"https://doi.org/10.1080/03088839.2021.1971784","url":null,"abstract":"ABSTRACT In one of the most capital-intensive industries in the world, the investment decisions of container shipping companies, especially concerning new ships, are crucial to the success of companies. This study investigates shipowners’ ship choice decisions and ship size preference through multinomial logit models using a dataset compiled by Clarkson Research Services Limited. The model incorporates the factors that affect ship size choice from three aspects: the internal traits of companies (company trait), the environment of the shipping market (market-driven strategy) and the performance of rivals (competition strategy). Different factors have different influences on shipping companies’ ship choice behaviour and ship size preference in different market situations. From a market-driven perspective, the high new-built ship price makes companies choose small ships. In a prosperous market, when freight rates are high, medium-sized vessels are preferred, and investment in large vessels is less likely. From the company attributes perspective, the empirical estimation shows that larger container ships are preferred by larger shipping companies. When it comes to competitive strategy, shipping companies will be more inclined to choose larger ships when they see capacity expansion among their competitors. These results confirm the nature of an oligopolistic market structure of the container market.","PeriodicalId":18288,"journal":{"name":"Maritime Policy & Management","volume":"50 1","pages":"219 - 234"},"PeriodicalIF":3.5,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42096857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-31DOI: 10.1080/03088839.2021.1968059
Ran Yan, Haoyu Mo, Shuaian Wang, Dong Yang
ABSTRACT To reduce CO2 emissions from shipping activities to, from, and within the European Union (EU) area, a system of monitoring, reporting, and verification (MRV) of CO2 emissions from ships are implemented in 2015 by the EU. Although the MRV records in 2018 and 2019 have been published, there are scarce studies on the MRV system especially from a quantitative perspective, which restrains the potential of the MRV. To bridge this gap, this paper first analyzes and compares MRV records in 2018 and 2019, and then develops machine learning models for annual average fuel consumption prediction for each ship type combining ship features from an external database. The performance of the prediction models is accurate, with the mean absolute percentage error (MAPE) on the test set no more than 12% and the average R-squared of all the models at 0.78. Based on the analysis and prediction results, model meanings, implications, and extensions are thoroughly discussed. This study is a pioneer to analyze the emission reports in the MRV system from a quantitative perspective. It also develops the first fuel consumption prediction models from a macro perspective using the MRV data. It can contribute to the promotion of green shipping strategies.
{"title":"Analysis and prediction of ship energy efficiency based on the MRV system","authors":"Ran Yan, Haoyu Mo, Shuaian Wang, Dong Yang","doi":"10.1080/03088839.2021.1968059","DOIUrl":"https://doi.org/10.1080/03088839.2021.1968059","url":null,"abstract":"ABSTRACT To reduce CO2 emissions from shipping activities to, from, and within the European Union (EU) area, a system of monitoring, reporting, and verification (MRV) of CO2 emissions from ships are implemented in 2015 by the EU. Although the MRV records in 2018 and 2019 have been published, there are scarce studies on the MRV system especially from a quantitative perspective, which restrains the potential of the MRV. To bridge this gap, this paper first analyzes and compares MRV records in 2018 and 2019, and then develops machine learning models for annual average fuel consumption prediction for each ship type combining ship features from an external database. The performance of the prediction models is accurate, with the mean absolute percentage error (MAPE) on the test set no more than 12% and the average R-squared of all the models at 0.78. Based on the analysis and prediction results, model meanings, implications, and extensions are thoroughly discussed. This study is a pioneer to analyze the emission reports in the MRV system from a quantitative perspective. It also develops the first fuel consumption prediction models from a macro perspective using the MRV data. It can contribute to the promotion of green shipping strategies.","PeriodicalId":18288,"journal":{"name":"Maritime Policy & Management","volume":"50 1","pages":"117 - 139"},"PeriodicalIF":3.5,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48084663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-25DOI: 10.1080/03088839.2021.1968058
Juan Li, Rong Zhang, Bin Liu
{"title":"Grey clustering evaluation of service capacity of cruise homeports in China","authors":"Juan Li, Rong Zhang, Bin Liu","doi":"10.1080/03088839.2021.1968058","DOIUrl":"https://doi.org/10.1080/03088839.2021.1968058","url":null,"abstract":"","PeriodicalId":18288,"journal":{"name":"Maritime Policy & Management","volume":"1 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44734857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-17DOI: 10.1080/03088839.2021.1959074
Baode Li, Jing Lu, Hangyu Lu, Jing Li
ABSTRACT Emergency response decision-making for maritime accidents needs to consider the possible consequences and scenarios of an accident to develop an effective emergency response strategy to reduce the severity of the accident. This paper proposes a novel machine learning-based methodology for predicting accident scenarios and analysing its factors to assist emergency response decision-making from an emergency rescue perspective. Specifically, the accident data used are collected from maritime accident investigation reports, and then two types of decision tree (DT) algorithms, classification and regression tree (CART) and random forest (RF), are used to develop scenario prediction models for three accident consequences including ship damage, casualty, and environmental damage. The hyper-parameters of these two DT algorithms are optimized using two state-of-the-art optimization algorithms, namely random search (RS) and Bayesian optimization (BO), respectively, aiming to obtain the prediction model with the highest accuracy. Experimental results reveal that BO-RF algorithm produces the best accuracy as compared to others. In addition, an analysis of feature importance shows that the number of people involved in an accident is the most important driving factor affecting the final accident scenario. Finally, decision rules are generated from the obtained optimal prediction model, which can provide decision support for emergency response decisions.
{"title":"Predicting maritime accident consequence scenarios for emergency response decisions using optimization-based decision tree approach","authors":"Baode Li, Jing Lu, Hangyu Lu, Jing Li","doi":"10.1080/03088839.2021.1959074","DOIUrl":"https://doi.org/10.1080/03088839.2021.1959074","url":null,"abstract":"ABSTRACT Emergency response decision-making for maritime accidents needs to consider the possible consequences and scenarios of an accident to develop an effective emergency response strategy to reduce the severity of the accident. This paper proposes a novel machine learning-based methodology for predicting accident scenarios and analysing its factors to assist emergency response decision-making from an emergency rescue perspective. Specifically, the accident data used are collected from maritime accident investigation reports, and then two types of decision tree (DT) algorithms, classification and regression tree (CART) and random forest (RF), are used to develop scenario prediction models for three accident consequences including ship damage, casualty, and environmental damage. The hyper-parameters of these two DT algorithms are optimized using two state-of-the-art optimization algorithms, namely random search (RS) and Bayesian optimization (BO), respectively, aiming to obtain the prediction model with the highest accuracy. Experimental results reveal that BO-RF algorithm produces the best accuracy as compared to others. In addition, an analysis of feature importance shows that the number of people involved in an accident is the most important driving factor affecting the final accident scenario. Finally, decision rules are generated from the obtained optimal prediction model, which can provide decision support for emergency response decisions.","PeriodicalId":18288,"journal":{"name":"Maritime Policy & Management","volume":"50 1","pages":"19 - 41"},"PeriodicalIF":3.5,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48004810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-09DOI: 10.1080/03088839.2021.1962557
Seçil Gülmez, Gül Denktaş Şakar, S. Baştuğ
ABSTRACT The increasing importance of maritime transportation in entire logistics flows have increased the interest in maritime logistics. Despite the growing body of the literature on this emerging discipline, there is lack of a detailed investigation regarding the categorization and emerging topics. The primary aim of this study is to analyse the advances in the literature and to suggest a research agenda for this concept by exploring the main research domains in this phenomenon. To achieve these aims, this study adopts content analysis-based review method to examine the concept and citation analysis to explore the latent structure of maritime logistics. The research streams have been obtained through two databases; the main themes, highlighted topics, and related analytical categories have been investigated through content analysis. Citation and co-citation analysis were conducted to understand the intellectual structure of the studies and the relationship of the analytical categories. The study presents a comprehensive synthesis of existing research suggesting a systematic source of information for both scholars and practitioners, shaping the future research agenda. The findings indicate that there is an increasing emphasis on design, optimization, and planning of port and ship operations while sustainability and marketing perspectives are somehow neglected in the researches.
{"title":"An overview of maritime logistics: trends and research agenda","authors":"Seçil Gülmez, Gül Denktaş Şakar, S. Baştuğ","doi":"10.1080/03088839.2021.1962557","DOIUrl":"https://doi.org/10.1080/03088839.2021.1962557","url":null,"abstract":"ABSTRACT The increasing importance of maritime transportation in entire logistics flows have increased the interest in maritime logistics. Despite the growing body of the literature on this emerging discipline, there is lack of a detailed investigation regarding the categorization and emerging topics. The primary aim of this study is to analyse the advances in the literature and to suggest a research agenda for this concept by exploring the main research domains in this phenomenon. To achieve these aims, this study adopts content analysis-based review method to examine the concept and citation analysis to explore the latent structure of maritime logistics. The research streams have been obtained through two databases; the main themes, highlighted topics, and related analytical categories have been investigated through content analysis. Citation and co-citation analysis were conducted to understand the intellectual structure of the studies and the relationship of the analytical categories. The study presents a comprehensive synthesis of existing research suggesting a systematic source of information for both scholars and practitioners, shaping the future research agenda. The findings indicate that there is an increasing emphasis on design, optimization, and planning of port and ship operations while sustainability and marketing perspectives are somehow neglected in the researches.","PeriodicalId":18288,"journal":{"name":"Maritime Policy & Management","volume":"50 1","pages":"97 - 116"},"PeriodicalIF":3.5,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47848921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-09DOI: 10.1080/03088839.2021.1959076
Theodoros Gavriilidis, A. Merika, A. Merikas, Christos Sigalas
ABSTRACT We developed a market sentiment measure for freight markets of the dry bulk shipping segment. Initially, keywords with positive and negative sentiment connotation were identified, and their relative importance was estimated, by administering two surveys with industry stakeholders. Next, a self-developed search algorithm software was developed to scan over 9,500 articles in shipping press, during 2008–2018, in order to calculate keywords’ frequencies. Following the construction of the sentiment measure, its validity was assessed with a system of simultaneous equations. Among others, our empirical results indicate a bidirectional relationship between market sentiment and maritime seaborne economic activity. The findings yield important implications for practitioners in maritime shipping industry.
{"title":"Development of a sentiment measure for dry bulk shipping","authors":"Theodoros Gavriilidis, A. Merika, A. Merikas, Christos Sigalas","doi":"10.1080/03088839.2021.1959076","DOIUrl":"https://doi.org/10.1080/03088839.2021.1959076","url":null,"abstract":"ABSTRACT We developed a market sentiment measure for freight markets of the dry bulk shipping segment. Initially, keywords with positive and negative sentiment connotation were identified, and their relative importance was estimated, by administering two surveys with industry stakeholders. Next, a self-developed search algorithm software was developed to scan over 9,500 articles in shipping press, during 2008–2018, in order to calculate keywords’ frequencies. Following the construction of the sentiment measure, its validity was assessed with a system of simultaneous equations. Among others, our empirical results indicate a bidirectional relationship between market sentiment and maritime seaborne economic activity. The findings yield important implications for practitioners in maritime shipping industry.","PeriodicalId":18288,"journal":{"name":"Maritime Policy & Management","volume":"50 1","pages":"58 - 80"},"PeriodicalIF":3.5,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"59679786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-08DOI: 10.1080/03088839.2021.1959077
Shiou-Yu Chen, Chin-Shan Lu, Kung-Don Ye, K. Shang, Jiunn-Liang Guo, Jeff Pan
ABSTRACT This study examines the organizational factors, leader-member exchange (LMX), and team-member exchange (TMX) affecting seafarers’ safety citizenship behavior (SCB) in respect of seafaring lives. Accordingly, we investigate the moderating effect of the safety climate on these relationships. Questionnaire surveys were collected from 283 seafarers in Taiwan’s shipping industry. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was employed to test the hypothesized causal relationships and moderating effect. The results showed that each of the safety climate, LMX and TMX were significantly related to the seafarer’s SCB; specifically, the safety climate strengthened the relationship between LMX and the seafarer’s SCB, but its effect on the relationship between TMX and seafarer’s SCB was insignificant. This study contributes to the academic literature on safety since it demonstrates the moderating role of the safety climate in linking LMX, TMX, and safety citizenship behavior that has been underestimated in previous research. We suggest that marine masters and shipping companies should specifically consider the influence of LMX and TMX within a ship, and reinforce a safety climate to improve safety performance.
{"title":"Enablers of safety citizenship behaviors of seafarers: leader-member exchange, team-member exchange, and safety climate","authors":"Shiou-Yu Chen, Chin-Shan Lu, Kung-Don Ye, K. Shang, Jiunn-Liang Guo, Jeff Pan","doi":"10.1080/03088839.2021.1959077","DOIUrl":"https://doi.org/10.1080/03088839.2021.1959077","url":null,"abstract":"ABSTRACT This study examines the organizational factors, leader-member exchange (LMX), and team-member exchange (TMX) affecting seafarers’ safety citizenship behavior (SCB) in respect of seafaring lives. Accordingly, we investigate the moderating effect of the safety climate on these relationships. Questionnaire surveys were collected from 283 seafarers in Taiwan’s shipping industry. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was employed to test the hypothesized causal relationships and moderating effect. The results showed that each of the safety climate, LMX and TMX were significantly related to the seafarer’s SCB; specifically, the safety climate strengthened the relationship between LMX and the seafarer’s SCB, but its effect on the relationship between TMX and seafarer’s SCB was insignificant. This study contributes to the academic literature on safety since it demonstrates the moderating role of the safety climate in linking LMX, TMX, and safety citizenship behavior that has been underestimated in previous research. We suggest that marine masters and shipping companies should specifically consider the influence of LMX and TMX within a ship, and reinforce a safety climate to improve safety performance.","PeriodicalId":18288,"journal":{"name":"Maritime Policy & Management","volume":"50 1","pages":"81 - 96"},"PeriodicalIF":3.5,"publicationDate":"2021-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41373400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-08DOI: 10.1080/03088839.2021.1940335
Hyun-Tak Lee, Heesung Yun
ABSTRACT This paper studies the dynamic relationship between ship prices and operating profits by using the fact that these two factors are cointegrated. To conduct an empirical analysis, we select Panamax 76K 5-year second-hand prices and 1-year time charter rates, and then define their linear combination as a log price–charter ratio. We find that almost all variations in price–charter ratios correspond to changing expectations about future returns. This finding implies that the mean reversion in price–charter ratios arises mainly from ship prices as prices tend to move toward operating profits. The implication is that price–charter ratios can be used to schedule ship investment timing. When unexpected down-side risks occur, one preemptive action to minimize additional losses is to lower vessel exposure right away before ship prices plummet in accordance with movements in the freight market.
{"title":"What moves shipping markets?: A variance decomposition of price–charter ratios","authors":"Hyun-Tak Lee, Heesung Yun","doi":"10.1080/03088839.2021.1940335","DOIUrl":"https://doi.org/10.1080/03088839.2021.1940335","url":null,"abstract":"ABSTRACT This paper studies the dynamic relationship between ship prices and operating profits by using the fact that these two factors are cointegrated. To conduct an empirical analysis, we select Panamax 76K 5-year second-hand prices and 1-year time charter rates, and then define their linear combination as a log price–charter ratio. We find that almost all variations in price–charter ratios correspond to changing expectations about future returns. This finding implies that the mean reversion in price–charter ratios arises mainly from ship prices as prices tend to move toward operating profits. The implication is that price–charter ratios can be used to schedule ship investment timing. When unexpected down-side risks occur, one preemptive action to minimize additional losses is to lower vessel exposure right away before ship prices plummet in accordance with movements in the freight market.","PeriodicalId":18288,"journal":{"name":"Maritime Policy & Management","volume":"49 1","pages":"1027 - 1042"},"PeriodicalIF":3.5,"publicationDate":"2021-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44789678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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