Search results

Increased political measures to protect the marine environment addresses a shipping industry characterised by strained financial resources, excess supply of capacity and consolidation. In addition, 5-15 per cent of industry participants are believed by shipping experts to neglect rules on vessel-source pollution to stay competitive within their industry and vis-à-vis other transport modes. This study aims to identify and quantify cost effects of maritime environmental legislation, to relate these with company characteristics and to investigate the impact of regulatory compliance.

A mixed-methods design was used to develop both a theoretical model of compliance costs effects and to quantify effect sizes. In total, 12 in-depth exploratory expert interviews were conducted and analysed. A theoretical framework emerged, which was evaluated, strengthened and fed with quantitative data from questionnaire data by 120 shipping companies. Partial least squares analysis was conducted to determine compliance cost effects.

It was found that organisational capacities played a significant role in determining compliance behaviour. Exterior determinants showed no significant correlation with legal compliance. This is a striking result, as it does not support achieving legal compliance with measures of strong enforcement.

European transport policy-making depends on scientifically sound studies on the impact of policy. An in-depth impact assessment on environmental legislation for the maritime industry highlights mechanisms applicable to environmental policy-making in transport and helps in building policy that considers compliance concerns, company characteristics and the interconnectedness of different transport modes for a sound response to the tragedy of the commons.

Originality lies in the inductive development of a comprehensive theory on shipping companies’ legal compliance behaviour and the empirical testing of this theory. Further value is derived from applying a sequential mixed-methods approach to the research problem, showing both the worth and challenge in combining different methodologies to achieve sound research results.

This paper aims to propose a machine learning-based automatic labeling methodology for chemical tanker activities that can be applied to any port with any number of active tankers and the identification of important predictors. The methodology can be applied to any type of activity tracking that is based on automatically generated geospatial data.

The proposed methodology uses three machine learning algorithms (artificial neural networks, support vector machines (SVMs) and random forest) along with information fusion (IF)-based sensitivity analysis to classify chemical tanker activities. The data set is split into training and test data based on vessels, with two vessels in the training data and one in the test data set. Important predictors were identified using a receiver operating characteristic comparative approach, and overall variable importance was calculated using IF from the top models.

Results show that an SVM model has the best balance between sensitivity and specificity, at 93.5% and 91.4%, respectively. Speed, acceleration and change in the course on the ground for the vessels are identified as the most important predictors for classifying vessel activity.

The study evaluates the vessel movements waiting between different terminals in the same port, but not their movements between different ports for their tank-cleaning activities.

The findings in this study can be used by port authorities, shipping companies, vessel operators and other stakeholders for decision support, performance tracking, as well as for automated alerts.

This analysis makes original contributions to the existing literature by defining and demonstrating a methodology that can automatically label vehicle activity based on location data and identify certain characteristics of the activity by finding important location-based predictors that effectively classify the activity status.

Ports are a significant link in a global supply chain and an economic entity that contributes to the country's economy. India has around 200 ports along its coastline of about 8,000 Km, yet none of them perform at par with many Asian ports. In the Indian port system, cargo throughput and the turnaround time (TAT) of ships calling at ports constitute the most significant performance measures. These performance metrics do not integrate sustainability measures such as emission levels and energy consumed. The draft is a constraint in many ports and ships visit with less than full shipload cargo. The TAT for such vessels may be lower, but the emission per ton of cargo carried is higher compared to a ship with full shipload cargo. Many ports have old or poorly maintained equipment. This state of equipment increases pollution and consumption of energy. In this paper, an attempt has been made to address the issue of undesirable and right outputs simultaneously in an Indian port system. This paper proposes a framework to ensure zero defects in Indian port operations and a port-sustainability-index to measure sustainable services in Indian ports.

The authors used data envelopment analysis (DEA) to show that all private terminals did not perform efficiently and contradicted the notion of Indian policymakers that privatization will lead to an increase in performance levels. A literature review was carried out to identify the dimensions and factors that affect ports' performance. A case study of a major port in India and expert group discussion was done to ascertain the views of stakeholders on deficiencies in the system. The authors complemented this approach with sentiment analysis of opinions expressed by stakeholders over a while, using SentiStrength analysis software (Thelwell, 2010, 2012). The authors used the combined findings to develop the port-sustainability-index (PSI), identify the research question, and develop an ontology of the port system. The authors use the concepts of ontology-design-pattern (ODP) and logistics-service-map (Glöckner et al., 2014; Glöckner and Ludwig, 2016, 2017), opinion mining (Pang and Lee, 2008) and competency questions (Glöckner and Ludwig, 2017) to develop a port system map followed by the identification of critical elements; and the flows (physical and information flow) that gets disrupted due to defects in the system. The ontology led to the identification of competencies and capabilities a port needs to possess. Based on these identification process competency questions were drawn, and the authors identified the plausible defects that port may encounter. The authors suggested the sustainability metrics for monitoring port performance and policy changes based on the competency questions, defects, and mitigation plans.

The authors introduced four KPIs, namely, port-sustainability-index (PSI), load factor (l_x and l_y), draft ratio (d_r), and turnaround-time ratio (TATR). The authors suggested significant policy changes for Indian ports. These included –(1) Introduction of virtual arrival (VA) policy, reducing randomness in the system by pre-scheduling arrivals and activities. (2) Redefining economic life of equipment and machinery in terms of expenditure, income and desired levels of output. (3) Pricing port charges based on stakeholders’ ability and willingness to pay. The port needs to declare its productivity levels and frame their charges accordingly. (4) The ports need to frame an output-oriented privatization policy where it specifies the growth of the port. (5) Framing vessel pricing policy where a vessel may pay tax for the use of non-clean fuel or a get discount for bringing higher parcel load. (6) Levy lower port charges for the shipper for transporting cargo by rail and barges. (7) Introduce a differential pricing system where port levies lower charges for export cargo compared to import load.

The research work can be extended to develop a simulation model to carry out policy experimentations concerning the improvement of performance and carry out sustainable operations. Alternatively, researchers may develop a multi-criteria optimization model to determine the best course of action, keeping the objective function as minimization of PSI value.

This paper provides the means to the Indian ports to remain competitive, lower emission levels and energy consumption, and optimize emission per ton of cargo handled in the port.

Society significantly benefits from this study as it recommends ways to minimize pollution that has a significant impact on human lives. Besides, the measures suggested in the paper will lower the cost of exports and imports, enhancing the real income of consumers.

The area of sustainable port operations has previously been under-researched in the Indian context. Authors contribute to the sustainable port operation literature by suggesting a port-sustainability-index, a framework to assess the defects in port operation and development of a port-ontology for further research in the area of a port system.