Identification and Valuation of Flexibility in Marine Systems Design

Marine systems, typically related to transport services and offshore petroleum projects, are often complex and involve a high degree of uncertainty related to their future operating context. Uncertain factors, such as oil prices and changing environmental regulations, are usually highly influential for the performance of these projects and introduce risks for investors in the capital-intensive maritime industry. This thesis investigates how flexibility can be considered at the design stage for handling uncertainty for marine systems, in contrast to traditional post-design operational methods. Flexibility opens up for both reducing the downside risk and taking advantage of upside possibilities, hence increasing the expected value of a design. Even though real options analysis represents an established approach for analysing flexibility, it may be inappropriate for more complex systems. To better structure options for marine systems design, a differentiation is made between more traditional, operational "on" options, and more complex, technical "in" options. Choosing the right method for analysis is ambiguous, therefore multiple approaches for identifying and valuing relevant flexibilities are discussed in this thesis. Identification methods include interviews and different systems engineering platforms for exploring how designs respond to changing contextual parameters. Valuation approaches include traditional analytical, lattice and Monte Carlo simulation methods for pricing real options, and more novel tradespace evaluation techniques. A generic framework for flexibility analysis is presented, serving as a stepwise approach to quantifying flexibility and as a means of communication between analysts and decision makers, both technical and non-technical. The flexibility analysis framework is illustrated through a case study of a large container ship design. By using screening methods to identify candidate flexibilities such as capacity expansion and fuel-switching, and Monte Carlo simulations for valuation, it was found that flexibility increases the profitability index by 27%, on a 200 million dollar investment. Furthermore, it was demonstrated that screening and simulation methods are appropriate for the use in design of large commercial deep-sea marine transportation systems. From an established real options valuation side, it is obvious that strategic flexibility has value, however, for non-standard applications typically involving complex "in" options, it is more ambiguous how to proceed. Even though system analysts recognise the value of flexibility, there is still a need for further research since flexibility rarely is seen in the maritime industry

Wharekauri, Rēkohu, Chatham Islands health and social needs

This report is an independent review of the health and social needs of Chatham Islanders. Executive summary Background: Whānau Ora is about the transformation of whānau/family – with whānau/family setting their direction. Whānau Ora is driven by a focus on outcomes: that whānau/family will be self-managing; living healthy lifestyles; participating fully in society; confidently participating in te ao Māori (the Māori world); economically secure and successfully involved in wealth creation; and cohesive, resilient and nurturing. Ha O Te Ora O Wharekauri Trust – Māori Community Services (‘Māori Community Services’) is one of 34 Whānau Ora provider collectives across New Zealand. Within these Whānau Ora provider collectives, there are approximately 180 service providers. The number of providers within each provider collective varies from 1 to 20. Ha O Te Ora O Wharekauri Trust is one of the few Whānau Ora provider collectives with only one provider: their service arm Māori Community Services. Te Whānau Whāriki: Whānau Ora Business Plan was developed by Māori Community Services (2011) to ensure business continuity, enhance management and governance, and put in place adequate infrastructure and appropriately trained staff to support Whānau Ora-based delivery programmes. The business plan seeks innovative opportunities to do things differently to support whānau/families to realise their aspirations. The Ministry of Health commissioned a report on the health and social needs of Chatham Islands. Māori Community Services intends to use the report to guide their work based on the aspirations and realities of whānau/families living on Chatham Islands. Māori Community Services were also keen to explore the feasibility of holding a Health and Wellbeing Day on Chatham Island, potentially using a model similar to PHARMAC’s One Heart Many Lives Program. It is intended that this report will inform other health and social organisations based on Chatham Islands and on the ‘mainland’, so they can work together to support whānau/families on Chatham Islands to realise their aspirations in both the short and long term

A Systematic Literature Review of the Use of Computational Text Analysis Methods in Intimate Partner Violence Research

Purpose: Computational text mining methods are proposed as a useful methodological innovation in Intimate Partner Violence (IPV) research. Text mining can offer researchers access to existing or new datasets, sourced from social media or from IPV-related organisations, that would be too large to analyse manually. This article aims to give an overview of current work applying text mining methodologies in the study of IPV, as a starting point for researchers wanting to use such methods in their own work. Methods This article reports the results of a systematic review of academic research using computational text mining to research IPV. A review protocol was developed according to PRISMA guidelines, and a literature search of 8 databases was conducted, identifying 22 unique studies that were included in the review. Results: The included studies cover a wide range of methodologies and outcomes. Supervised and unsupervised approaches are represented, including rule-based classification (n = 3), traditional Machine Learning (n = 8), Deep Learning (n = 6) and topic modelling (n = 4) methods. Datasets are mostly sourced from social media (n = 15), with other data being sourced from police forces (n = 3), health or social care providers (n = 3), or litigation texts (n = 1). Evaluation methods mostly used a held-out, labelled test set, or k-fold Cross Validation, with Accuracy and F1 metrics reported. Only a few studies commented on the ethics of computational IPV research. Conclusions: Text mining methodologies offer promising data collection and analysis techniques for IPV research. Future work in this space must consider ethical implications of computational approaches

Coastal management and adaptation: an integrated data-driven approach

Coastal regions are some of the most exposed to environmental hazards, yet the coast is the preferred settlement site for a high percentage of the global population, and most major global cities are located on or near the coast. This research adopts a predominantly anthropocentric approach to the analysis of coastal risk and resilience. This centres on the pervasive hazards of coastal flooding and erosion. Coastal management decision-making practices are shown to be reliant on access to current and accurate information. However, constraints have been imposed on information flows between scientists, policy makers and practitioners, due to a lack of awareness and utilisation of available data sources. This research seeks to tackle this issue in evaluating how innovations in the use of data and analytics can be applied to further the application of science within decision-making processes related to coastal risk adaptation. In achieving this aim a range of research methodologies have been employed and the progression of topics covered mark a shift from themes of risk to resilience. The work focuses on a case study region of East Anglia, UK, benefiting from the input of a partner organisation, responsible for the region’s coasts: Coastal Partnership East. An initial review revealed how data can be utilised effectively within coastal decision-making practices, highlighting scope for application of advanced Big Data techniques to the analysis of coastal datasets. The process of risk evaluation has been examined in detail, and the range of possibilities afforded by open source coastal datasets were revealed. Subsequently, open source coastal terrain and bathymetric, point cloud datasets were identified for 14 sites within the case study area. These were then utilised within a practical application of a geomorphological change detection (GCD) method. This revealed how analysis of high spatial and temporal resolution point cloud data can accurately reveal and quantify physical coastal impacts. Additionally, the research reveals how data innovations can facilitate adaptation through insurance; more specifically how the use of empirical evidence in pricing of coastal flood insurance can result in both communication and distribution of risk. The various strands of knowledge generated throughout this study reveal how an extensive range of data types, sources, and advanced forms of analysis, can together allow coastal resilience assessments to be founded on empirical evidence. This research serves to demonstrate how the application of advanced data-driven analytical processes can reduce levels of uncertainty and subjectivity inherent within current coastal environmental management practices. Adoption of methods presented within this research could further the possibilities for sustainable and resilient management of the incredibly valuable environmental resource which is the coast

Supply Chain Disruption Costs Study in International Containerised Maritime Transportation

The global economy relies highly on international trade, and the international maritime transport system acts as the lifeblood carrying and transporting materials and goods globally, realizing the economy globalization in an effective and efficient way. However, globalization increases the interdependence and complexity of global supply chains and drives it to be more vulnerable to disruptions. Meanwhile, the international marine transport system is a complex and intertwined system exposed to high risks and decreased safety due to its very accessibility and operational flexibility. Thereby, global supply chains integrated with international maritime transportation systems are inherently vulnerable to various disruptions. Studies of supply chain disruptions particularly quantifying transport related disruption costs are becoming increasingly important. However, research on maritime transport related supply chain disruptions, in particular, quantifying its disruption costs is under-represented in the transport literature, due largely to the features of supply chain disruptions, but also because of the complexity of maritime related supply chains. Current research in transportation has tended to concentrate on shippers’ transport mode choice and port selection. In the context of a global market, however, the behaviour of maritime containerised shippers has to be viewed as a complex decision and an integral element of the supply chain management strategy. Those shippers’ transportation choice decisions should be emphasized and studied to reveal their behaviour changes between normal operations and disruption circumstance. This research adds to the paucity work on investigating the maritime transport related supply chain disruptions and quantifying its disruption costs based on shippers’ maritime transportation choice behaviour. It presents the results of a microanalysis of freight transport choice decisions in an international containerised maritime transport chain context. The Latent Class Model (LCM) is applied to identify the key service attributes and its preference heterogeneity in maritime transportation and to estimate the marginal values for the quality of maritime transport service with and without a disruption, simultaneously, quantifying the disruption costs through comparing each attribute’s marginal value difference between normal and disruption operations. The Seemingly Unrelated Regression model (SURE) is utilized to explore the sources influencing shippers’ preference heterogeneities. In doing so, we are able to gain an understanding as to where and how much should be invested in order to facilitate recovery in the case of a disruption based on the view of the maritime participants’ perspectives. The research results confirm freight rate, transit time, reliability, damage rate, and frequency as the key service attributes influencing shippers’ transport choice. They also reveal shippers’ VOT increase by more than four-times, VOR nearly double, and VOD increase about twenty percent if a disruption takes place, and identify shippers’ transport decisions vary with its product, shipment, company and supply chain characteristics no matter with or without a disruption. This research quantifies the costs of supply chain disruption in containerised maritime transport context for the first time, and its results provide useful industrial implications for maritime transport chain related parties

Supply Chain Disruption Costs Study in International Containerised Maritime Transportation

The global economy relies highly on international trade, and the international maritime transport system acts as the lifeblood carrying and transporting materials and goods globally, realizing the economy globalization in an effective and efficient way. However, globalization increases the interdependence and complexity of global supply chains and drives it to be more vulnerable to disruptions. Meanwhile, the international marine transport system is a complex and intertwined system exposed to high risks and decreased safety due to its very accessibility and operational flexibility. Thereby, global supply chains integrated with international maritime transportation systems are inherently vulnerable to various disruptions. Studies of supply chain disruptions particularly quantifying transport related disruption costs are becoming increasingly important. However, research on maritime transport related supply chain disruptions, in particular, quantifying its disruption costs is under-represented in the transport literature, due largely to the features of supply chain disruptions, but also because of the complexity of maritime related supply chains. Current research in transportation has tended to concentrate on shippers’ transport mode choice and port selection. In the context of a global market, however, the behaviour of maritime containerised shippers has to be viewed as a complex decision and an integral element of the supply chain management strategy. Those shippers’ transportation choice decisions should be emphasized and studied to reveal their behaviour changes between normal operations and disruption circumstance. This research adds to the paucity work on investigating the maritime transport related supply chain disruptions and quantifying its disruption costs based on shippers’ maritime transportation choice behaviour. It presents the results of a microanalysis of freight transport choice decisions in an international containerised maritime transport chain context. The Latent Class Model (LCM) is applied to identify the key service attributes and its preference heterogeneity in maritime transportation and to estimate the marginal values for the quality of maritime transport service with and without a disruption, simultaneously, quantifying the disruption costs through comparing each attribute’s marginal value difference between normal and disruption operations. The Seemingly Unrelated Regression model (SURE) is utilized to explore the sources influencing shippers’ preference heterogeneities. In doing so, we are able to gain an understanding as to where and how much should be invested in order to facilitate recovery in the case of a disruption based on the view of the maritime participants’ perspectives. The research results confirm freight rate, transit time, reliability, damage rate, and frequency as the key service attributes influencing shippers’ transport choice. They also reveal shippers’ VOT increase by more than four-times, VOR nearly double, and VOD increase about twenty percent if a disruption takes place, and identify shippers’ transport decisions vary with its product, shipment, company and supply chain characteristics no matter with or without a disruption. This research quantifies the costs of supply chain disruption in containerised maritime transport context for the first time, and its results provide useful industrial implications for maritime transport chain related parties

Improving the analysis and use of patient complaints in the English National Health Service

The English National Health Service (NHS) receives over 200,000 patient complaints annually. Complaints provide rich narratives of poor and unsafe care, and are often submitted with the aim of preventing harm from occurring to others. Inquiries into safety failures have demonstrated that complaints signal problems where internal systems fail. Yet, their insights remain underutilised due to their complex unstructured nature, a disregard for their informational value, and a complaints process designed for case-by-case redress. This work develops evidence-based and theory-informed approaches towards improving the analysis and use of complaints in the English NHS. Using process modelling and realist review methods, this thesis generates theory on how and under what conditions healthcare settings can achieve both case-by-case redress and system-wide analysis of complaints. Findings identify the need for a robust coding taxonomy to detect systemic problems with healthcare delivery, and support the prioritisation of deeper qualitative analysis and investigation. The inter-rater reliability of the existing NHS complaints reporting scheme ‘KO41a’ is tested across four NHS Trusts, and compared to the psychometrically robust and theory-informed Healthcare Complaints Analysis Tool (HCAT). Results highlight the limited discriminative value of KO41a, and indicate HCAT as a reliable alternative in most investigated settings. Drawing from social science approaches to safety, the final study conducts data linkage and narrative analysis of complaints and staff incident reports, and demonstrates the contributions of using complainants’ interpretation and sense-making of adverse events to test, challenge, and complement staff representations of the causes and severity of harm. Collectively, the work in this thesis demonstrates why patient and staff perspectives need to be combined for a more holistic understanding of patient safety, and provides a pragmatic, evidence-based pathway towards integrating complaints into the historically staff-driven quality monitoring and improvement systems.Open Acces

Digital transformation in food supply chains: an implementation framework

Purpose Digital transformation using Industry 4.0 technologies can address various challenges in food supply chains (FSCs). However, the integration of emerging technologies to achieve digital transformation in FSCs is unclear. This study aims to establish how the digital transformation of FSCs can be achieved by adopting key technologies such as the Internet of Things (IoTs), cloud computing (CC) and big data analytics (BDA). Design/methodology/approach A systematic literature review (SLR) resulted in 57 articles from 2008 to 2022. Following descriptive and thematic analysis, a conceptual framework based on the diffusion of innovation (DOI) theory and the context-intervention-mechanism-outcome (CIMO) logic is established, along with avenues for future research. Findings The combination of DOI theory and CIMO logic provides the theoretical foundation for linking the general innovation process to the digital transformation process. A novel conceptual framework for achieving digital transformation in FSCs is developed from the initiation to implementation phases. Objectives and principles for digitally transforming FSCs are identified for the initiation phase. A four-layer technology implementation architecture is developed for the implementation phase, facilitating multiple applications for FSC digital transformation. Originality/value The study contributes to the development of theory on digital transformation in FSCs and offers managerial guidelines for accelerating the growth of the food industry using key Industry 4.0 emerging technologies. The proposed framework brings clarity into the “neglected” intermediate stage of data management between data collection and analysis. The study highlights the need for a balanced integration of IoT, CC and BDA as key Industry 4.0 technologies to achieve digital transformation successfully