Containerized transport has emerged as a pivotal mode of transportation in global trade, which accounted for approximately 60% of total global trade volume. A core challenge within the shipping industry today is the issue of trade imbalances, which are rooted in factors such as gaps in income levels between domestic and foreign markets, variations in wage-bargaining structures, trade policies, and geopolitical tensions. The implications of trade imbalances are shown in regional surpluses and deficits. Surplus regions reflect a higher volume of imports than exports, which results in the accumulated containers used from sea transport. In contrast, deficit regions experience higher export volume than imports, which results in less containers available to transport goods due to less container input from import activities.
These imbalances significantly impact shipping companies' revenue, as they are required to meet container demand in deficit areas to capture customer demand across all regions. A commonly adopted strategy to address this challenge is empty repositioning, which involves relocating empty containers from surplus regions to deficit regions. However, this practice is associated with the trade-off of adding higher additional costs without generating direct significant revenue in the short-term for shipping companies.
Maersk, a leading player in the industry and acts as the case study for this research, also faces trade imbalance issues. Currently, Maersk prioritizes the demand from the deficit region, which is Far East (such as China), specifically Far East to Europe journey, which represents the journey with the highest revenue contribution in its operations. However, Maersk, especially the Equipment Flow team, who are in charge of planning the container allocation in European trade, wants to confirm whether their current approach is optimal or needs further improvement. . This thesis project aims to confirm whether the strategy they implemented in 2023 (reflected in Alternatives 1) is better than prioritizing the containers allocation to deficit regions, which is Far East (Alternatives 2).
The insights derived from this study are expected to contribute to a broader understanding of how shipping companies can manage their strategies in container allocation in response to trade imbalances. By examining these alternatives, the research seeks to provide actionable recommendations to address how they should allocate their containers in case of trade imbalances, ultimately supporting shipping companies in navigating this long-standing challenge more effectively.
The analysis of the alternative’s evaluation shows that overall total revenue when prioritizing empty container allocation to deficit regions compared to maintaining the export level alternative shows minimal effect due to the slight differences in both total revenues. In terms of total revenues, maintaining export level alternative’s (Alternative 1) yield slightly higher total revenues. However, if we look at the range of total revenues generated in Far East after curtailment, prioritizing empty containers to deficit regions depicted (Alternative 2) slightly higher range compared to Alternative 1 with the increase on total revenue’s range about 0.75%. However, this increase is not significant compared to the annual growth of revenue in the shipping industry which accounts for 2.7% per year (Cargo Shipping Market Revenue, 2024). In addition to the small increase in total revenue range in Alternative 2, the variation of total revenue in each region also increases. In the context of seasonality, the data distribution in Africa and Latin Africa shows no significant difference when performing Alternative 2. Far East and North America are affected by the seasonality due to their higher volume of trade. Amid these notable differences, seasonality does not affect the range of revenue in each region, but it makes the revenue more stable due to the nature of high contractual customer percentage in Maersk. This nature makes the demand more predictable.

The intersection of fossil fuel industry funding and climate change research is a contentious area, raising significant ethical and practical concerns. Fossil fuel companies have historically played a substantial role in funding research, which has sparked debates about potential biases in climate research due to financial ties. Understanding the extent and impact of this funding is crucial for ensuring unbiased and accurate information that forms the basis of climate policies.

This thesis investigates the terminology and methodology in climate research funded by the fossil fuel industry through a comprehensive scientometric analysis, as compared to general research and a pool of research from universities with ties to fossil fuel industry. The study aims to identify patterns of industry influence on scientific outcomes and the dissemination of climate-related information. Data is collected by extracting research paper abstracts and other relevant information from Scopus database over the period of 2014-2024, divided by subject areas and funding sources, leading to over a 100,000 papers analysed with 80\% relevance score word maps produced in VOSViewer. Thus, employing methodologies such as keyword-based data collection, Natural Language Processing (NLP), and topic modeling, the research identifies significant patterns in studies funded by fossil fuel companies, such as lack of focus on ESG terms, increased focus on carbon capture and hydrogen technologies, and more technical analysis methods. To ensure the robustness of these findings, the study employs validation techniques, including cross-referencing with independent literature and applying advanced statistical methods to control for potential confounding factors via topic modelling. This multifaceted approach enhances the credibility of the results and provides a clearer understanding of the extent and nature of industry-induced biases in climate research.

The analysis spans multiple disciplines, including energy, environmental science, earth and planetary science, and engineering, revealing that industry funded research outcomes are often tied directly to fossil fuel sector sphere of interests, while finding no significant influence patterns in university research. The findings of lack of ESG terms and increased focus on specific climate-mitigation technologies underscore the need for increased ESG interest and diversity in the industry funding of climate research to ensure its integrity and objectivity.

The thesis concludes with a discussion of the implications of these findings for policy and practice. It emphasizes the need for greater transparency in the disclosure of research funding sources and calls for the implementation of stricter guidelines to mitigate bias in scientific research, or for fossil fuel industry to ensure a larger diversity in the research funding. Additionally, it offers recommendations for future research, highlighting the importance of independent funding to preserve the objectivity and integrity of climate science.

By shedding light on the intersection of industry interests and scientific research, this thesis contributes to the ongoing debate about the ethical implications of industry-funded research. It underscores the critical importance of unbiased, evidence-based decision-making in addressing global climate change and supports the development of policies that ensure the reliability of scientific knowledge.

The research investigates the application of autonomous inspection technologies within the oilseed industry—a sector characterized by the extraction of oil from plant seeds like sunflower and rapeseed. The oilseed industry, with its complex production operations, has historically relied on labor-intensive and error-prone inspection methods that lead to significant financial losses and compromised product quality. The thrust of this research is to develop a systematic approach to assist industry leaders in selecting optimal autonomous inspection technologies for oilseed processing, improving efficiency and reducing human error. Employing an exploratory research approach, this thesis utilizes qualitative methodologies, including case studies and interviews, particularly effective in less researched fields. The research is structured around the double diamond model of design thinking, encompassing four stages: Discover, Define, Develop, and Deliver. First phase in Discover and Define includes a detailed examination of current processes and technologies, followed by the identification and definition of key operational problems. The final phases include developing an approach and validating it with a case study.

A significant portion of the thesis is dedicated to Multi-Criteria Decision Analysis (MCDA), using the Analytic Hierarchy Process (AHP) to evaluate various autonomous inspection technologies. This process systematically ranks technologies based on criteria such as usability, financial viability, and safety standards. The research culminates in a practical validation through a comprehensive case study conducted at Cargill. The case study not only tests the proposed systematic approach but also highlights its effectiveness in identifying optimal technologies. The findings confirm the viability of the proposed selection framework, emphasizing its potential to revolutionize inspection processes in the oilseed industry by integrating autonomous technologies. This thesis contributes to the strategic decision-making process in technological adoption, ensuring that selected technologies align well with industry needs and operational goals.

This thesis investigates strategies to enhance lead time performance in the order-to-delivery process of a specialized product in the paint and coatings industry, serving a specific regional market. The study applies Lean Six Sigma’s DMAIC framework to analyze the current state, identify challenges, and develop actionable solutions to achieve operational excellence and meet customer expectations. The research combines qualitative and quantitative methods, including process mapping, stakeholder interviews, and data analysis. This study identifies the primary issue of extended lead times exceeding service levels, resulting in delays, customer dissatisfaction, and diminished responsiveness.

Key findings reveal that a small percentage of products account for a significant portion of lead time challenges, underscoring targeted opportunities for improvement. Proposed solutions include creating an integrated supply chain grand design, mapping end-to-end processes, standardizing documentation and communication, fostering a culture of continuous improvement, and implementing regular evaluations of tools and methods. Feasibility assessments using SWOT and cost-benefit analyses prioritize immediate standardization and phased implementation of more complex strategies. Validation through stakeholder feedback and triangulated data analysis supports the practicality and potential impact of the recommendations.

This study contributes actionable recommendations for streamlining the order-to-delivery process. These include establishing a clear process blueprint with defined roles and responsibilities, leveraging data-driven decision-making, enhancing process standardization, cultivating a customer-centric mindset, and proactively monitoring tools and processes for continuous improvement. The findings provide a robust framework for addressing lead time challenges and driving sustainable operational improvements.

Public projects play a crucial role in societal development yet managing them effectively requires a nuanced understanding of the expectations and concerns of different stakeholders. This paper explores the complex landscape of public projects, with a particular focus on understanding the diverse perspectives of various stakeholder groups and their perceptions of the tangible and intangible impacts of these initiatives. The existing literature has provided valuable insights into specific stakeholder perspectives and regional nuances, but it remains fragmented, leading to a piecemeal understanding of the broader landscape. Addressing this gap, the research introduces a structured model that combines the RACI model for stakeholder identification and the Triple Bottom Line (TBL) approach for categorizing impact factors. This model aims to bring clarity and consistency to the assessment of stakeholder priorities in public projects. The research question guiding this study is: How do distinct stakeholder groups perceive the intangible and tangible impacts of public projects? To assess the validity of the proposed model, we explored the practical application within the context of smart street lighting projects. utilizing semi-structured interviews with 16 stakeholders across the four RACI categories. The findings reveal shared concerns across stakeholder groups, particularly regarding privacy and security issues associated with smart lighting. However, notable differences also emerged, such as manufacturers’ willingness to compromise social responsibility for economic gains and citizens’ feelings of exclusion from decision-making processes. Based on these findings, several suggestions were made: 1) Establish a regular dialogue mechanism with stakeholders, ensuring that each group, especially citizens, is included in the decision-making process; 2) Address privacy and security concerns by incorporating robust data protection and cybersecurity measures into the smart street lighting systems; 3) Encourage manufacturers and other profit-driven stakeholders to align more closely with social and environmental responsibilities; 4) Use the Triple Bottom Line (TBL) approach to regularly measure and (publicly) report the economic, social, and environmental impacts of the smart street lighting project to maintain transparency. This study contributes to the existing body of knowledge by providing a nuanced understanding of stakeholder perspectives in public projects, offering a structured model for future studies, and paving the way for more informed and inclusive decision-making processes. The limitations of the study, primarily related to its regional focus and potential biases in participant selection, are acknowledged, underscoring the need for further research to validate and refine the proposed model.

Freedom of thought and democracy are not straightforward, due to the destructive force of terrorism. Since the beginning of mankind, terrorism has been around in different forms and shapes and ever since, it has been a struggle to overcome terrorist actions. In the era where we currently live in, ‘counter-terrorism’ is a true verb beyond praise in the sense that it requires a lot of hard work, courage, and flexibility.