The moderating impact of supply network topology on the effectiveness of risk management

While supply chain risk management offers a rich toolset for dealing with risk at the dyadic level, less attention has been given to the effectiveness of risk management in complex supply networks. We bridge this gap by building an agent based model to explore the relationship between topological characteristics of complex supply networks and their ability to recover through inventory mitigation and contingent rerouting. We simulate upstream supply networks, where each agent represents a supplier. Suppliers’ connectivity patterns are generated through random and preferential attachment models. Each supplier manages its inventory using an anchor-and-adjust ordering policy. We then randomly disrupt suppliers and observe how different topologies recover when risk management strategies are applied. Our results show that topology has a moderating effect on the effectiveness of risk management strategies. Scale-free supply networks generate lower costs, have higher fill-rates, and need less inventory to recover when exposed to random disruptions than random networks. Random networks need significantly more inventory distributed across the network to achieve the same fill rates as scale-free networks. Inventory mitigation improves fill-rate more than contingent rerouting regardless of network topology. Contingent rerouting is not effective for scale-free networks due to the low number of alternative suppliers, particularly for short-lasting disruptions. We also find that applying inventory mitigation to the most disrupted suppliers is only effective when the network is exposed to frequent disruptions; and not cost effective otherwise. Our work contributes to the emerging field of research on the relationship between complex supply network topology and resilience

Travel choices, internet accessibility, and extreme weather: translating trends in space-time flexibility in the digital age

Extreme weather affects not only transport infrastructure, but also travel behaviour. Climate change is causing more frequent and intense severe weather events, and thus is increasing the risks to transport infrastructure, services, and travellers. Travel behaviour trends are also in flux due to shifting working and activity patterns, as space-time flexibility and accessibility choice increases, and standard commuting journeys decline. Information and communication technologies (ICT) are one reason for these changing trends in travel behaviour, and, like climate change, create uncertainty in predicting transport operations and travel choices. However, ICT also has the potential to make mobility and accessibility more sustainable and more responsive to climate change impacts. This thesis sets out to identify the opportunities that improving ICT and increasing space-time flexibility create for commuters and other travellers to maintain accessibility, particularly to work activities, that they may better respond to severe weather, risk, and transport disruption, thereby boosting resilience. The research also concludes that through the integration of travel choices and Internet accessibility and by taking action to address spatial and temporal barriers, policy might better support both resilience and sustainability

Infraestructure readiness for autonomous vehicles

This study is aimed at identifying the major challenges in the infraestructure design, operation and maintenance to allow the implementation of Autonomous Vehicles in interurban and urban road network

Resilence of complex supply networks

During recent decades supply chains have grown, and became increasingly interconnected due to globalisation and outsourcing. Empirical and theoretical studies now characterise supply chains as complex networks rather than the hierarchical, linear chain structures often theorised in classical literature. Increased topological complexity resulted in an increased exposure to risk, however existing supply chain risk management methodologies are designed based on the linear structure assumption rather than interdependent network structures. There is a growing need to better understand the complexities of supply networks, and how to identify, measure and mitigate risks more efficiently. The aim of this thesis is to identify how supply network topology influences resilience. More specifically, how applying well-established supply chain risk management strategies can decrease disruption impact in different supply network topologies. The influence of supply network topology on resilience is captured using a dynamic agent-based model based on empirical and theoretical supply network structures, without a single entity controlling the whole system where each supplier is an independent decision-maker. These suppliers are then disrupted using various disruption scenarios. Suppliers in the network then apply inventory mitigation and contingent rerouting to decrease impact of disruptions on the rest of the network. To the best of author’s knowledge, this is the first time the impact of random disruptions and its reduction through risk management strategies in different supply network topologies have been assessed in a fully dynamic, interconnected environment. The main lessons from this work are as follows: It has been observed that the supply network topology plays a crucial role in reducing impact of disruptions. Some supply network topologies are more resilient to random disruptions as they better fulfil customer demand under perturbations. Under random disruptions, inventory mitigation is a well-performing shock absorption mechanism. Contingent rerouting, on the other hand, is a strategy that needs specific conditions to work well. Firstly, the strategy must be applied by companies in supply topologies where the majority of supply chain members have alternative suppliers. Secondly, contingent rerouting is only efficient in cases when the reaction time to supplier’s disruption is shorter than the duration of the disruption. It has also been observed that the topological position of the individual company who applies specific risk management strategy heavily impacts costs and fill-rates of the overall system. This property is moderated by other variables such as disruption duration, disruption frequency and the chosen risk management strategy. An additional, important lesson here is that, choosing the supplier that suffered the most from disruptions or have specific topological position in a network to apply a risk management strategy might not always decrease the costs incurred by the whole system. In contrast, it might increase it if not applied appropriately. This thesis underpins the significance of topology in supply network resilience. The results from this work are foundational to the claim that it is possible to design an extended supply network that will be able reduce the impact of certain disruption types. However, the design must consider topological properties as well as moderating variables.PhD in Manufacturin

An Agent-based Approach for Improving the Performance of Distributed Business Processes in Maritime Port Community

In the recent years, the concept of “port community” has been adopted by the maritime transport industry in order to achieve a higher degree of coordination and cooperation amongst organizations involved in the transfer of goods through the port area. The business processes of the port community supply chain form a complicated process which involves several process steps, multiple actors, and numerous information exchanges. One of the widely used applications of ICT in ports is the Port Community System (PCS) which is implemented in ports in order to reduce paperwork and to facilitate the information flow related to port operations and cargo clearance. However, existing PCSs are limited in functionalities that facilitate the management and coordination of material, financial, and information flows within the port community supply chain. This research programme addresses the use of agent technology to introduce business process management functionalities, which are vital for port communities, aiming to the enhancement of the performance of the port community supply chain. The investigation begins with an examination of the current state in view of the business perspective and the technical perspective. The business perspective focuses on understanding the nature of the port community, its main characteristics, and its problems. Accordingly, a number of requirements are identified as essential amendments to information systems in seaports. On the other hand, the technical perspective focuses on technologies that are convenient for solving problems in business process management within port communities. The research focuses on three technologies; the workflow technology, agent technology, and service orientation. An analysis of information systems across port communities enables an examination of the current PCSs with regard to their coordination and workflow management capabilities. The most important finding of this analysis is that the performance of the business processes, and in particular the performance of the port community supply chain, is not in the scope of the examined PCSs. Accordingly, the Agent-Based Middleware for Port Community Management (ABMPCM) is proposed as an approach for providing essential functionalities that would facilitate collaborative planning and business process management. As a core component of the ABMPCM, the Collaborative Planning Facility (CPF) is described in further details. A CPF prototype has been developed as an agent-based system for the domain of inland transport of containers to demonstrate its practical effectiveness. To evaluate the practical application of the CPF, a simulation environment is introduced in order to facilitate the evaluation process. The research started with the definition of a multi-agent simulation framework for port community supply chain. Then, a prototype has been implemented and employed for the evaluation of the CPF. The results of the simulation experiments demonstrate that our agent-based approach effectively enhances the performance of business process in the port community

Attitudes and Attitude Change in Personal Travel

High levels of personal car use have negative effects on the environment and on human health. This thesis presents four empirical studies that aimed to develop our knowledge of personal travel choices, focussing on the malleability of attitudes and their sensitivity in relation to specific contexts and goals. The first study (Chapter 2) presents a systematic review and meta-analysis of mechanisms of travel mode choice. The study provides a comprehensive overview of antecedents of car use and non-car use, including sub-group analyses of different contextual factors. Results also highlight the need for standardised measures and consideration of implicit thought processes. The second study (Chapter 3) employs a repertory grid technique to elicit perceptions of seven different transport modes from high mileage car users and non-car users. Comparisons between car users and non-car users highlight potentially effective and ineffective intervention targets. Findings show how sustainable transport might be promoted amongst a portfolio of travel choices. The third study (Chapter 4) utilises qualitative methods to explore the extent to which individuals’ attitude expressions are changeable. The study demonstrates that all participants hold ambivalent and conflicting attitudes, highlighting specific situations in which those attitudes are more likely to be unstable. Two related priming experiments are presented in the final empirical chapter (Chapter 5). Both use survey methodology to investigate whether manipulating the salience of car-use-incongruent goals can lead to more positive attitudes towards and increased willingness to use non-car travel modes. The study confirms that people who are motivated to make changes are a potentially optimal target group for interventions based on subliminal messages. Overall, the research presented in this thesis introduces context sensitivity into the transport literature and offers novel insights into perceptions of a range of travel modes. Recommendations include relevant avenues for future research, findings are discussed in light of implications for transport policy and practice.Shell Global Solutions (UK

Powerless In Movement: How Social Movements Influence, And Fail To Influence, American Politics And Policy

Much of the literature on social movements centers on cyclical theories of political opportunity. While such work lays an important foundation for understanding contentious politics, it fails to fully integrate movements as actors in the American political system and public policy process. As such, the ways movements exercise power in the American political system, and the ways that power is constrained, are often not clearly conceptualized. This dissertation argues that movements exercise political power in the US in three distinct but overlapping ways; pluralist interest group power, plebiscitary opinion power, and disruptive contentious power. Through public law and empirical analyses, it shows that opportunities to exercise these types of power are limited by three patterns of American Political Development; insiders building structural constraints such as tax and campaign finance laws, political inflation caused by the expansion of political resources such as campaign spending, and institutional thickening that commits government resources to existing issues and limits slack resources for new issues. Case law analysis shows that the Supreme Court’s First Amendment doctrines on tax law, campaign finance law, and time, place and manner restrictions disadvantage movements. Empirical analysis of nonprofit tax filings shows that movements have increasingly relied on apolitical organizational forms such as charities. Analysis of protest news reports shows that policing policies have reduced confrontations between police and protesters in ways that lower this visibility of movements. Analysis of congressional hearings and public laws shows that an increasing share of government activity is devoted to administering existing policy commitments. The dissertation concludes that emerging constraints increasingly limit movement power in the future of American politics. As such, this project suggests that declines in social movement influence since the 1960s may not be a cyclical phenomenon, and that political outsiders must learn to adapt to a closed political system. Movement cases considered include LGBTQ Rights, Animal Rights, Disability Rights, and Antiabortion

Modelling individual accessibility using Bayesian networks: A capabilities approach

The ability of an individual to reach and engage with basic services such as healthcare, education and activities such as employment is a fundamental aspect of their wellbeing. Within transport studies, accessibility is considered to be a valuable concept that can be used to generate insights on issues related to social exclusion due to limited access to transport options. Recently, researchers have attempted to link accessibility with popular theories of social justice such as Amartya Sen's Capabilities Approach (CA). Such studies have set the theoretical foundations on the way accessibility can be expressed through the CA, however, attempts to operationalise this approach remain fragmented and predominantly qualitative in nature. The data landscape however, has changed over the last decade providing an unprecedented quantity of transport related data at an individual level. Mobility data from dfferent sources have the potential to contribute to the understanding of individual accessibility and its relation to phenomena such as social exclusion. At the same time, the unlabelled nature of such data present a considerable challenge, as a non-trivial step of inference is required if one is to deduce the transportation modes used and activities reached. This thesis develops a novel framework for accessibility modelling using the CA as theoretical foundation. Within the scope of this thesis, this is used to assess the levels of equality experienced by individuals belonging to different population groups and its link to transport related social exclusion. In the proposed approach, activities reached and transportation modes used are considered manifestations of individual hidden capabilities. A modelling framework using dynamic Bayesian networks is developed to quantify and assess the relationships and dynamics of the different components in fluencing the capabilities sets. The developed approach can also provide inferential capabilities for activity type and transportation mode detection, making it suitable for use with unlabelled mobility data such as Automatic Fare Collection Systems (AFC), mobile phone and social media. The usefulness of the proposed framework is demonstrated through three case studies. In the first case study, mobile phone data were used to explore the interaction of individuals with different public transportation modes. It was found that assumptions about individual mobility preferences derived from travel surveys may not always hold, providing evidence for the significance of personal characteristics to the choices of transportation modes. In the second case, the proposed framework is used for activity type inference, testing the limits of accuracy that can be achieved from unlabelled social media data. A combination of the previous case studies, the third case further defines a generative model which is used to develop the proposed capabilities approach to accessibility model. Using data from London's Automatic Fare Collection Systems (AFC) system, the elements of the capabilities set are explicitly de ned and linked with an individual's personal characteristics, external variables and functionings. The results are used to explore the link between social exclusion and transport disadvantage, revealing distinct patterns that can be attributed to different accessibility levels